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Hajek C, Guo X, Yao J, Hai Y, Johnson WC, Frazier-Wood AC, Post WS, Psaty BM, Taylor KD, Rotter JI. Coronary Heart Disease Genetic Risk Score Predicts Cardiovascular Disease Risk in Men, Not Women. Circ Genom Precis Med 2019; 11:e002324. [PMID: 30354305 DOI: 10.1161/circgen.118.002324] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Catherine Hajek
- Los Angeles Biomedical Research Institute (LA BioMed), CA (C.H., X.G., J.Y., Y.H., K.D.T., J.I.R.).,Department of Internal Medicine, Sanford School of Medicine, University of South Dakota, Vermillion (C.H.)
| | - Xiuqing Guo
- Los Angeles Biomedical Research Institute (LA BioMed), CA (C.H., X.G., J.Y., Y.H., K.D.T., J.I.R.)
| | - Jie Yao
- Los Angeles Biomedical Research Institute (LA BioMed), CA (C.H., X.G., J.Y., Y.H., K.D.T., J.I.R.)
| | - Yang Hai
- Los Angeles Biomedical Research Institute (LA BioMed), CA (C.H., X.G., J.Y., Y.H., K.D.T., J.I.R.)
| | - W Craig Johnson
- Department of Biostatistics, Collaborative Health Studies Coordinating Center, University of Washington, Seattle (W.C.J.)
| | - Alexis C Frazier-Wood
- Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX (A.C.F.-W.)
| | - Wendy S Post
- Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD (W.S.P.)
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology and Health Services, University of Washington, Seattle, WA (B.M.P.).,Kaiser Permanente Washington Health Research Institute, Seattle, WA (B.M.P.). Group Health Research Institute, Group Health Cooperative, Seattle, WA
| | - Kent D Taylor
- Los Angeles Biomedical Research Institute (LA BioMed), CA (C.H., X.G., J.Y., Y.H., K.D.T., J.I.R.)
| | - Jerome I Rotter
- Los Angeles Biomedical Research Institute (LA BioMed), CA (C.H., X.G., J.Y., Y.H., K.D.T., J.I.R.)
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Merino J, Guasch-Ferré M, Ellervik C, Dashti HS, Sharp SJ, Wu P, Overvad K, Sarnowski C, Kuokkanen M, Lemaitre RN, Justice AE, Ericson U, Braun KVE, Mahendran Y, Frazier-Wood AC, Sun D, Chu AY, Tanaka T, Luan J, Hong J, Tjønneland A, Ding M, Lundqvist A, Mukamal K, Rohde R, Schulz CA, Franco OH, Grarup N, Chen YDI, Bazzano L, Franks PW, Buring JE, Langenberg C, Liu CT, Hansen T, Jensen MK, Sääksjärvi K, Psaty BM, Young KL, Hindy G, Sandholt CH, Ridker PM, Ordovas JM, Meigs JB, Pedersen O, Kraft P, Perola M, North KE, Orho-Melander M, Voortman T, Toft U, Rotter JI, Qi L, Forouhi NG, Mozaffarian D, Sørensen TIA, Stampfer MJ, Männistö S, Selvin E, Imamura F, Salomaa V, Hu FB, Wareham NJ, Dupuis J, Smith CE, Kilpeläinen TO, Chasman DI, Florez JC. Quality of dietary fat and genetic risk of type 2 diabetes: individual participant data meta-analysis. BMJ 2019; 366:l4292. [PMID: 31345923 PMCID: PMC6652797 DOI: 10.1136/bmj.l4292] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
OBJECTIVE To investigate whether the genetic burden of type 2 diabetes modifies the association between the quality of dietary fat and the incidence of type 2 diabetes. DESIGN Individual participant data meta-analysis. DATA SOURCES Eligible prospective cohort studies were systematically sourced from studies published between January 1970 and February 2017 through electronic searches in major medical databases (Medline, Embase, and Scopus) and discussion with investigators. REVIEW METHODS Data from cohort studies or multicohort consortia with available genome-wide genetic data and information about the quality of dietary fat and the incidence of type 2 diabetes in participants of European descent was sought. Prospective cohorts that had accrued five or more years of follow-up were included. The type 2 diabetes genetic risk profile was characterized by a 68-variant polygenic risk score weighted by published effect sizes. Diet was recorded by using validated cohort-specific dietary assessment tools. Outcome measures were summary adjusted hazard ratios of incident type 2 diabetes for polygenic risk score, isocaloric replacement of carbohydrate (refined starch and sugars) with types of fat, and the interaction of types of fat with polygenic risk score. RESULTS Of 102 305 participants from 15 prospective cohort studies, 20 015 type 2 diabetes cases were documented after a median follow-up of 12 years (interquartile range 9.4-14.2). The hazard ratio of type 2 diabetes per increment of 10 risk alleles in the polygenic risk score was 1.64 (95% confidence interval 1.54 to 1.75, I2=7.1%, τ2=0.003). The increase of polyunsaturated fat and total omega 6 polyunsaturated fat intake in place of carbohydrate was associated with a lower risk of type 2 diabetes, with hazard ratios of 0.90 (0.82 to 0.98, I2=18.0%, τ2=0.006; per 5% of energy) and 0.99 (0.97 to 1.00, I2=58.8%, τ2=0.001; per increment of 1 g/d), respectively. Increasing monounsaturated fat in place of carbohydrate was associated with a higher risk of type 2 diabetes (hazard ratio 1.10, 95% confidence interval 1.01 to 1.19, I2=25.9%, τ2=0.006; per 5% of energy). Evidence of small study effects was detected for the overall association of polyunsaturated fat with the risk of type 2 diabetes, but not for the omega 6 polyunsaturated fat and monounsaturated fat associations. Significant interactions between dietary fat and polygenic risk score on the risk of type 2 diabetes (P>0.05 for interaction) were not observed. CONCLUSIONS These data indicate that genetic burden and the quality of dietary fat are each associated with the incidence of type 2 diabetes. The findings do not support tailoring recommendations on the quality of dietary fat to individual type 2 diabetes genetic risk profiles for the primary prevention of type 2 diabetes, and suggest that dietary fat is associated with the risk of type 2 diabetes across the spectrum of type 2 diabetes genetic risk.
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Cade BE, Chen H, Stilp AM, Louie T, Ancoli-Israel S, Arens R, Barfield R, Below JE, Cai J, Conomos MP, Evans DS, Frazier-Wood AC, Gharib SA, Gleason KJ, Gottlieb DJ, Hillman DR, Johnson WC, Lederer DJ, Lee J, Loredo JS, Mei H, Mukherjee S, Patel SR, Post WS, Purcell SM, Ramos AR, Reid KJ, Rice K, Shah NA, Sofer T, Taylor KD, Thornton TA, Wang H, Yaffe K, Zee PC, Hanis CL, Palmer LJ, Rotter JI, Stone KL, Tranah GJ, Wilson JG, Sunyaev SR, Laurie CC, Zhu X, Saxena R, Lin X, Redline S. Associations of variants In the hexokinase 1 and interleukin 18 receptor regions with oxyhemoglobin saturation during sleep. PLoS Genet 2019; 15:e1007739. [PMID: 30990817 PMCID: PMC6467367 DOI: 10.1371/journal.pgen.1007739] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Accepted: 10/03/2018] [Indexed: 12/12/2022] Open
Abstract
Sleep disordered breathing (SDB)-related overnight hypoxemia is associated with cardiometabolic disease and other comorbidities. Understanding the genetic bases for variations in nocturnal hypoxemia may help understand mechanisms influencing oxygenation and SDB-related mortality. We conducted genome-wide association tests across 10 cohorts and 4 populations to identify genetic variants associated with three correlated measures of overnight oxyhemoglobin saturation: average and minimum oxyhemoglobin saturation during sleep and the percent of sleep with oxyhemoglobin saturation under 90%. The discovery sample consisted of 8,326 individuals. Variants with p < 1 × 10(-6) were analyzed in a replication group of 14,410 individuals. We identified 3 significantly associated regions, including 2 regions in multi-ethnic analyses (2q12, 10q22). SNPs in the 2q12 region associated with minimum SpO2 (rs78136548 p = 2.70 × 10(-10)). SNPs at 10q22 were associated with all three traits including average SpO2 (rs72805692 p = 4.58 × 10(-8)). SNPs in both regions were associated in over 20,000 individuals and are supported by prior associations or functional evidence. Four additional significant regions were detected in secondary sex-stratified and combined discovery and replication analyses, including a region overlapping Reelin, a known marker of respiratory complex neurons.These are the first genome-wide significant findings reported for oxyhemoglobin saturation during sleep, a phenotype of high clinical interest. Our replicated associations with HK1 and IL18R1 suggest that variants in inflammatory pathways, such as the biologically-plausible NLRP3 inflammasome, may contribute to nocturnal hypoxemia.
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Affiliation(s)
- Brian E. Cade
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, United States of America
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, United States of America
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
| | - Han Chen
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX United States of America
- Center for Precision Health, School of Public Health and School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX United States of America
| | - Adrienne M. Stilp
- Department of Biostatistics, University of Washington, Seattle, WA United States of America
| | - Tin Louie
- Department of Biostatistics, University of Washington, Seattle, WA United States of America
| | - Sonia Ancoli-Israel
- Department of Psychiatry, University of California, San Diego, CA, United States of America
| | - Raanan Arens
- The Children’s Hospital at Montefiore, Division of Respiratory and Sleep Medicine, Albert Einstein College of Medicine, Bronx, NY, United States of America
| | - Richard Barfield
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America
| | - Jennifer E. Below
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States of America
| | - Jianwen Cai
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, United States of America
| | - Matthew P. Conomos
- Department of Biostatistics, University of Washington, Seattle, WA United States of America
| | - Daniel S. Evans
- California Pacific Medical Center Research Institute, San Francisco, CA, United States of America
| | - Alexis C. Frazier-Wood
- USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, United States of America
| | - Sina A. Gharib
- Computational Medicine Core, Center for Lung Biology, UW Medicine Sleep Center, Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington, Seattle WA, United States of America
| | - Kevin J. Gleason
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, United States of America
- Department of Public Health Sciences, University of Chicago, Chicago, IL, United States of America
| | - Daniel J. Gottlieb
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, United States of America
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, United States of America
- VA Boston Healthcare System, Boston, MA, United States of America
| | - David R. Hillman
- Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia
| | - W. Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA United States of America
| | - David J. Lederer
- Departments of Medicine and Epidemiology, Columbia University, New York, NY, United States of America
| | - Jiwon Lee
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, United States of America
| | - Jose S. Loredo
- Division of Pulmonary Critical Care and Sleep Medicine, Department of Medicine, UC San Diego School of Medicine, La Jolla, CA, United States of America
| | - Hao Mei
- Department of Data Science, University of Mississippi Medical Center, Jackson, MS, United States of America
| | - Sutapa Mukherjee
- Sleep Health Service, Respiratory and Sleep Services, Southern Adelaide Local Health Network, Adelaide, South Australia
- Adelaide Institute for Sleep Health, Flinders University, Adelaide, South Australia
| | - Sanjay R. Patel
- Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Wendy S. Post
- Division of Cardiology, Johns Hopkins University, Baltimore, MD, United States of America
| | - Shaun M. Purcell
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, United States of America
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, United States of America
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
| | - Alberto R. Ramos
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, United States of America
| | - Kathryn J. Reid
- Department of Neurology, Center for Circadian and Sleep Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States of America
| | - Ken Rice
- Department of Biostatistics, University of Washington, Seattle, WA United States of America
| | - Neomi A. Shah
- Division of Pulmonary, Critical Care and Sleep Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, United States of America
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, United States of America
- Department of Biostatistics, University of Washington, Seattle, WA United States of America
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - Timothy A. Thornton
- Department of Biostatistics, University of Washington, Seattle, WA United States of America
| | - Heming Wang
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, United States of America
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, United States of America
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
| | - Kristine Yaffe
- Department of Psychiatry, Neurology, and Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, CA, United States of America
- San Francisco VA Medical Center, San Francisco, CA, United States of America
| | - Phyllis C. Zee
- Department of Neurology, Center for Circadian and Sleep Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States of America
| | - Craig L. Hanis
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX United States of America
| | - Lyle J. Palmer
- School of Public Health, University of Adelaide, South Australia, Australia
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, LABioMed at Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - Katie L. Stone
- California Pacific Medical Center Research Institute, San Francisco, CA, United States of America
| | - Gregory J. Tranah
- California Pacific Medical Center Research Institute, San Francisco, CA, United States of America
| | - James G. Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson MS, United States of America
| | - Shamil R. Sunyaev
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Division of Genetics, Brigham and Women's Hospital, Boston, MA, United States of America
- Division of Medical Sciences, Harvard Medical School, Boston, MA, United States of America
| | - Cathy C. Laurie
- Department of Biostatistics, University of Washington, Seattle, WA United States of America
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, United States of America
| | - Richa Saxena
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, United States of America
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, United States of America
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Center for Genomic Medicine and Department of Anesthesia, Pain, and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, United States of America
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, United States of America
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, United States of America
- Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States of America
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Geng X, Irvin MR, Hidalgo B, Aslibekyan S, Srinivasasainagendra V, An P, Frazier-Wood AC, Tiwari HK, Dave T, Ryan K, Ordovas JM, Straka RJ, Feitosa MF, Hopkins PN, Borecki I, Province MA, Mitchell BD, Arnett DK, Zhi D. An Exome-Wide Sequencing Study of the GOLDN Cohort Reveals Novel Associations of Coding Variants and Fasting Plasma Lipids. Front Genet 2019; 10:158. [PMID: 30863429 PMCID: PMC6399202 DOI: 10.3389/fgene.2019.00158] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2018] [Accepted: 02/13/2019] [Indexed: 11/13/2022] Open
Abstract
Background: Associations of both common and rare genetic variants with fasting blood lipids have been extensively studied. However, most of the rare coding variants associated with lipids are population-specific, and exploration of genetic data from diverse population samples may enhance the identification of novel associations with rare variants. Results: We searched for novel coding genetic variants associated with fasting lipid levels in 894 samples from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) with exome-wide sequencing-based genotype data. In single variant tests, one variant (rs11171663 in ITGA7) was associated with fasting triglyceride levels (P = 7.66E-08), explaining approximately 3.2% of the total trait variance. In gene-based tests, we found statistically significant associations between ITGA7 (P = 1.77E-07) and SLCO2A1 (P = 7.18E-07) and triglycerides, as well as between POT1 (P = 3.00E-07) and low-density lipoprotein cholesterol. In another independent replication cohort consisting of 3,183 African American samples from Hypertension Genetic Epidemiology Network (HyperGEN) and the Genetic Epidemiology Network of Arteriopathy (GENOA), the top genes achieved P-values of 0.04 (ITGA7), 0.08 (SLCO2A1), and 0.02 (POT1). In GOLDN, gene transcript levels of ITGA7 and SLCO2A1 were associated with fasting triglycerides (P = 0.07 and P = 0.02), highlighting functional relevance of our findings. Conclusion: In this study, we present preliminary evidence of novel rare variant determinants of fasting lipids, and reveal potential underlying molecular mechanisms. Moreover, these results were replicated in an independent cohort. Our findings may inform novel biomarkers of disease risk and treatment targets.
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Affiliation(s)
- Xin Geng
- School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States.,BGI-Shenzhen, Shenzhen, China
| | - Marguerite R Irvin
- Department of Epidemiology, The University of Alabama at Birmingham, Birmingham, AL, United States
| | - Bertha Hidalgo
- Department of Epidemiology, The University of Alabama at Birmingham, Birmingham, AL, United States
| | - Stella Aslibekyan
- Department of Epidemiology, The University of Alabama at Birmingham, Birmingham, AL, United States
| | | | - Ping An
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Alexis C Frazier-Wood
- USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, United States
| | - Hemant K Tiwari
- Department of Biostatistics, The University of Alabama at Birmingham, Birmingham, AL, United States
| | - Tushar Dave
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Kathleen Ryan
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Jose M Ordovas
- Nutrition and Genomics Laboratory, Jean Mayer United States Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, United States.,IMDEA Alimentación, Madrid, Spain.,Centro Nacional de Investigaciones Cardiovasculares, Madrid, Spain
| | - Robert J Straka
- Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN, United States
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Paul N Hopkins
- Division of Cardiovascular Medicine, University of Utah, Salt Lake City, UT, United States
| | - Ingrid Borecki
- Genetic Analysis Center, Department of Biostatistics, University of Washington, Seattle, WA, United States
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
| | - Braxton D Mitchell
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY, United States
| | - Degui Zhi
- School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States.,School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States
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5
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Xu J, Bartz TM, Chittoor G, Eiriksdottir G, Manichaikul AW, Sun F, Terzikhan N, Zhou X, Booth SL, Brusselle GG, de Boer IH, Fornage M, Frazier-Wood AC, Graff M, Gudnason V, Harris TB, Hofman A, Hou R, Houston DK, Jacobs Jr DR, Kritchevsky SB, Latourelle J, Lemaitre RN, Lutsey PL, Connor GO, Oelsner EC, Pankow JS, Psaty BM, Rohde RR, Rich SS, Rotter JI, Smith LJ, Stricker BH, Voruganti VS, Wang TJ, Zillikens MC, Barr RG, Dupuis J, Gharib SA, Lahousse L, London SJ, North KE, Smith AV, Steffen LM, Hancock DB, Cassano PA. Meta-analysis across Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium provides evidence for an association of serum vitamin D with pulmonary function. Br J Nutr 2018; 120:1159-1170. [PMID: 30205856 PMCID: PMC6263170 DOI: 10.1017/s0007114518002180] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
The role that vitamin D plays in pulmonary function remains uncertain. Epidemiological studies reported mixed findings for serum 25-hydroxyvitamin D (25(OH)D)-pulmonary function association. We conducted the largest cross-sectional meta-analysis of the 25(OH)D-pulmonary function association to date, based on nine European ancestry (EA) cohorts (n 22 838) and five African ancestry (AA) cohorts (n 4290) in the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium. Data were analysed using linear models by cohort and ancestry. Effect modification by smoking status (current/former/never) was tested. Results were combined using fixed-effects meta-analysis. Mean serum 25(OH)D was 68 (sd 29) nmol/l for EA and 49 (sd 21) nmol/l for AA. For each 1 nmol/l higher 25(OH)D, forced expiratory volume in the 1st second (FEV1) was higher by 1·1 ml in EA (95 % CI 0·9, 1·3; P<0·0001) and 1·8 ml (95 % CI 1·1, 2·5; P<0·0001) in AA (P race difference=0·06), and forced vital capacity (FVC) was higher by 1·3 ml in EA (95 % CI 1·0, 1·6; P<0·0001) and 1·5 ml (95 % CI 0·8, 2·3; P=0·0001) in AA (P race difference=0·56). Among EA, the 25(OH)D-FVC association was stronger in smokers: per 1 nmol/l higher 25(OH)D, FVC was higher by 1·7 ml (95 % CI 1·1, 2·3) for current smokers and 1·7 ml (95 % CI 1·2, 2·1) for former smokers, compared with 0·8 ml (95 % CI 0·4, 1·2) for never smokers. In summary, the 25(OH)D associations with FEV1 and FVC were positive in both ancestries. In EA, a stronger association was observed for smokers compared with never smokers, which supports the importance of vitamin D in vulnerable populations.
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Affiliation(s)
- Jiayi Xu
- Division of Nutritional Sciences, Cornell University, Ithaca, New York, United States
| | - Traci M. Bartz
- Department of Biostatistics, University of Washington, Seattle, Washington, United States
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States
| | - Geetha Chittoor
- Department of Biomedical and Translational Informatics, Geisinger, Danville, Pennsylvania, United States
- Gillings School of Global Public Health, Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
| | | | - Ani W. Manichaikul
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, Virginia, United States
| | - Fangui Sun
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States
| | - Natalie Terzikhan
- Department of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Xia Zhou
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, United States
| | - Sarah L. Booth
- Jean Mayer-U.S. Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, Massachusetts, United States
| | - Guy G. Brusselle
- Department of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Respiratory Medicine, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Ian H. de Boer
- Department of Medicine, University of Washington, Seattle, Washington, United States
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas, United States
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, United States
| | - Alexis C. Frazier-Wood
- Children’s Nutrition Research Center, Baylor College of Medicine, Houston, Texas, United States
| | - Mariaelisa Graff
- Gillings School of Global Public Health, Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - Tamara B. Harris
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, United States
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging, Leiden, the Netherlands
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States
| | - Ruixue Hou
- Department of Nutrition and Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, North Carolina, United States
| | - Denise K. Houston
- Sticht Center on Aging, Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United State
| | - David R. Jacobs Jr
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, United States
| | - Stephen B. Kritchevsky
- Sticht Center on Aging, Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United State
| | - Jeanne Latourelle
- The Pulmonary Center, Department of Medicine, Boston University, Boston, Massachusetts, United State
- Department of Neurology, Boston University, Boston, Massachusetts, United States
| | - Rozenn N. Lemaitre
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States
- Department of Medicine, University of Washington, Seattle, Washington, United States
| | - Pamela L. Lutsey
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, United States
| | - George O. Connor
- The Pulmonary Center, Department of Medicine, Boston University, Boston, Massachusetts, United State
| | | | - James S. Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, United States
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, United States
- Department of Medicine, University of Washington, Seattle, Washington, United States
- Department of Epidemiology, University of Washington, Seattle, Washington, United States
- Department of Health Services, University of Washington, Seattle, Washington, United States
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, United States
| | - Rebecca R. Rohde
- Gillings School of Global Public Health, Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, Virginia, United States
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics at Harbor-UCLA Medical Center, Torrance, California, United States
| | - Lewis J. Smith
- Division of Pulmonary and Critical Care, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States
| | - Bruno H. Stricker
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging, Leiden, the Netherlands
| | - V. Saroja Voruganti
- Department of Nutrition and Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, North Carolina, United States
| | - Thomas J. Wang
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University, Nashville, Tennessee, United States
| | - M. Carola Zillikens
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging, Leiden, the Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, the Netherlands
| | - R. Graham Barr
- Department of Medicine, Columbia University, New York, New York, United States
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States
| | - Sina A. Gharib
- Department of Medicine, University of Washington, Seattle, Washington, United States
- Center for Lung Biology, University of Washington, Seattle, Washington, United States
| | - Lies Lahousse
- Department of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Bioanalysis, Ghent University, Ghent, Belgium
| | - Stephanie J. London
- Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, United States
| | - Kari E. North
- Gillings School of Global Public Health, Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
| | - Albert V. Smith
- Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - Lyn M. Steffen
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, United States
| | - Dana B. Hancock
- Behavioral and Urban Health Program, Behavioral Health and Criminal Justice Division, RTI International, Research Triangle Park, North Carolina, United States
| | - Patricia A. Cassano
- Division of Nutritional Sciences, Cornell University, Ithaca, New York, United States
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6
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Imamura F, Fretts A, Marklund M, Ardisson Korat AV, Yang WS, Lankinen M, Qureshi W, Helmer C, Chen TA, Wong K, Bassett JK, Murphy R, Tintle N, Yu CI, Brouwer IA, Chien KL, Frazier-Wood AC, del Gobbo LC, Djoussé L, Geleijnse JM, Giles GG, de Goede J, Gudnason V, Harris WS, Hodge A, Hu F, Koulman A, Laakso M, Lind L, Lin HJ, McKnight B, Rajaobelina K, Risérus U, Robinson JG, Samieri C, Siscovick DS, Soedamah-Muthu SS, Sotoodehnia N, Sun Q, Tsai MY, Uusitupa M, Wagenknecht LE, Wareham NJ, Wu JHY, Micha R, Forouhi NG, Lemaitre RN, Mozaffarian D. Fatty acid biomarkers of dairy fat consumption and incidence of type 2 diabetes: A pooled analysis of prospective cohort studies. PLoS Med 2018; 15:e1002670. [PMID: 30303968 PMCID: PMC6179183 DOI: 10.1371/journal.pmed.1002670] [Citation(s) in RCA: 129] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Accepted: 09/07/2018] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND We aimed to investigate prospective associations of circulating or adipose tissue odd-chain fatty acids 15:0 and 17:0 and trans-palmitoleic acid, t16:1n-7, as potential biomarkers of dairy fat intake, with incident type 2 diabetes (T2D). METHODS AND FINDINGS Sixteen prospective cohorts from 12 countries (7 from the United States, 7 from Europe, 1 from Australia, 1 from Taiwan) performed new harmonised individual-level analysis for the prospective associations according to a standardised plan. In total, 63,682 participants with a broad range of baseline ages and BMIs and 15,180 incident cases of T2D over the average of 9 years of follow-up were evaluated. Study-specific results were pooled using inverse-variance-weighted meta-analysis. Prespecified interactions by age, sex, BMI, and race/ethnicity were explored in each cohort and were meta-analysed. Potential heterogeneity by cohort-specific characteristics (regions, lipid compartments used for fatty acid assays) was assessed with metaregression. After adjustment for potential confounders, including measures of adiposity (BMI, waist circumference) and lipogenesis (levels of palmitate, triglycerides), higher levels of 15:0, 17:0, and t16:1n-7 were associated with lower incidence of T2D. In the most adjusted model, the hazard ratio (95% CI) for incident T2D per cohort-specific 10th to 90th percentile range of 15:0 was 0.80 (0.73-0.87); of 17:0, 0.65 (0.59-0.72); of t16:1n7, 0.82 (0.70-0.96); and of their sum, 0.71 (0.63-0.79). In exploratory analyses, similar associations for 15:0, 17:0, and the sum of all three fatty acids were present in both genders but stronger in women than in men (pinteraction < 0.001). Whereas studying associations with biomarkers has several advantages, as limitations, the biomarkers do not distinguish between different food sources of dairy fat (e.g., cheese, yogurt, milk), and residual confounding by unmeasured or imprecisely measured confounders may exist. CONCLUSIONS In a large meta-analysis that pooled the findings from 16 prospective cohort studies, higher levels of 15:0, 17:0, and t16:1n-7 were associated with a lower risk of T2D.
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Affiliation(s)
- Fumiaki Imamura
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Amanda Fretts
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, United States of America
| | - Matti Marklund
- Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Sweden
| | - Andres V. Ardisson Korat
- Department of Nutrition and Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Wei-Sin Yang
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei City, Taiwan
| | - Maria Lankinen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Waqas Qureshi
- Section of Cardiovascular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Bowman Gray Center, Winston-Salem, North Carolina, United States of America
| | - Catherine Helmer
- INSERM, UMR 1219, Bordeaux Population Health Research Center, University of Bordeaux, Bordeaux, France
| | - Tzu-An Chen
- USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, United States of America
| | - Kerry Wong
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Australia
| | - Julie K. Bassett
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Australia
| | - Rachel Murphy
- Centre of Excellence in Cancer Prevention, School of Population & Public Health, Faculty of Medicine, The University of British Columbia, Vancouver, Canada
| | - Nathan Tintle
- Department of Mathematics and Statistics, Dordt College, Sioux Center, Iowa, United States of America
| | - Chaoyu Ian Yu
- Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington, United States of America
| | - Ingeborg A. Brouwer
- Department of Health Sciences, Faculty of Earth & Life Sciences, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Kuo-Liong Chien
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei City, Taiwan
| | - Alexis C. Frazier-Wood
- USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, United States of America
| | - Liana C. del Gobbo
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America
| | - Luc Djoussé
- Divisions of Aging, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | | | - Graham G. Giles
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, Australia
| | - Janette de Goede
- Division of Human Nutrition, Wageningen University, Wageningen, the Netherlands
| | - Vilmundur Gudnason
- Icelandic Heart Association Research Institute, Holtasmári 1, Kópavogur, Iceland, Iceland
| | - William S. Harris
- Department of Internal Medicine, Sanford School of Medicine, University of South Dakota, Sioux Falls, South Dakota, United States of America
- OmegaQuant Analytics LLC, Sioux Falls, South Dakota, United States of America
| | - Allison Hodge
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, Australia
| | - Frank Hu
- Department of Nutrition and Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - InterAct Consortium
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Albert Koulman
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
- National Institute for Health Research Biomedical Research Centres Core Nutritional Biomarker Laboratory, University of Cambridge, Addenbrooke’s Hospital, Cambridge, United Kingdom
- National Institute for Health Research Biomedical Research Centres Core Metabolomics and Lipidomics Laboratory, University of Cambridge, Addenbrooke’s Hospital, Cambridge, United Kingdom
- Medical Research Council Elsie Widdowson Laboratory, Cambridge, United Kingdom
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Markku Laakso
- Department of Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Hung-Ju Lin
- Department of Internal Medicine, National Taiwan University Hospital, Zhongzheng District, Taipei City, Taiwan
| | - Barbara McKnight
- Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington, United States of America
| | - Kalina Rajaobelina
- INSERM, UMR 1219, Bordeaux Population Health Research Center, University of Bordeaux, Bordeaux, France
| | - Ulf Risérus
- Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Sweden
| | - Jennifer G. Robinson
- Departments of Epidemiology and Medicine at the University of Iowa College of Public Health, Iowa City, Iowa, United States of America
| | - Cécilia Samieri
- INSERM, UMR 1219, Bordeaux Population Health Research Center, University of Bordeaux, Bordeaux, France
| | - David S. Siscovick
- The New York Academy of Medicine, New York, New York, United States of America
| | - Sabita S. Soedamah-Muthu
- Division of Human Nutrition, Wageningen University, Wageningen, the Netherlands
- Center of Research on Psychology in Somatic Diseases, Department of Medical and Clinical Psychology, Tilburg University, Tilburg, the Netherlands
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, United States of America
| | - Qi Sun
- Department of Nutrition and Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Michael Y. Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Matti Uusitupa
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Lynne E. Wagenknecht
- Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Nick J. Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Jason HY Wu
- The George Institute for Global Health and the Faculty of Medicine, University of New South Wales, Sydney, Australia
| | - Renata Micha
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, Massachusetts, United States of America
| | - Nita G. Forouhi
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Rozenn N. Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, United States of America
| | - Dariush Mozaffarian
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, Massachusetts, United States of America
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7
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Al Rifai M, Greenland P, Blaha MJ, Michos ED, Nasir K, Miedema MD, Yeboah J, Sandfort V, Frazier-Wood AC, Shea S, Lima JA, Szklo M, Post WS, Blumenthal RS, McEvoy JW. Factors of health in the protection against death and cardiovascular disease among adults with subclinical atherosclerosis. Am Heart J 2018; 198:180-188. [PMID: 29653643 DOI: 10.1016/j.ahj.2017.10.026] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2017] [Accepted: 10/03/2017] [Indexed: 11/29/2022]
Abstract
BACKGROUND Although cardiovascular disease (CVD) prevention traditionally emphasizes risk factor control, recent evidence also supports the promotion of "health factors" associated with cardiovascular wellness. However, whether such health factors exist among adults with advanced subclinical atherosclerosis is unknown. We aimed to study the association between health factors and events among persons with elevated coronary artery calcium (CAC). METHODS Self-reported health-factors studied included nonsmoking, physical activity, Mediterranean-style diet, sleep quality, emotional support, low stress burden, and absence of depression. Measured health-factors included optimal weight, blood pressure, lipids, and glucose. Multivariable-adjusted Cox models examined the association between health factors and incident CVD or mortality, independent of risk factor treatment. Accelerated failure time models assessed whether health factors were associated with relative time delays in disease onset. RESULTS Among 1,601 Multi-Ethnic Study of Atherosclerosis participants with CAC >100 without baseline clinical atherosclerotic CVD, mean age was 69 (±9) years, 64% were male, and median CAC score was 332 Agatston units. Over 12 years of follow-up, nonsmoking, high-density lipoprotein cholesterol levels >40 mg/dL for men and >50 mg/dL for women, and low stress burden were inversely associated with ASCVD (hazard ratios ranging from 0.58 to 0.71, all P<.05). Nonsmoking, glucose levels <100 mg/dL, regular physical activity, and low stress burden were inversely associated with mortality (hazard ratios ranging from 0.40 to 0.77, all P<.05). Each of these factors was also associated with delays in onset of clinical disease, as was absence of depression. CONCLUSIONS Adults with elevated CAC appear to have healthy lifestyle options to lower risk and delay onset of CVD, over and above standard preventive therapies.
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Affiliation(s)
- Mahmoud Al Rifai
- Department of Medicine, University of Kansas School of Medicine, Wichita, KS; Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Philip Greenland
- Departments of Preventive Medicine and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Michael J Blaha
- Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Erin D Michos
- Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Khurram Nasir
- Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, MD; Center for Prevention and Wellness, Baptist Health South Florida, Miami, FL
| | - Michael D Miedema
- Minneapolis Heart Institute and Minneapolis Heart Institute Foundation, Minneapolis, MN
| | - Joseph Yeboah
- Department of Cardiology, Wake Forest Baptist Health, Winston-Salem, NC
| | | | - Alexis C Frazier-Wood
- ARS/USDA Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX
| | - Steven Shea
- Departments of Medicine and Epidemiology, Columbia University, New York, NY
| | - Joao Ac Lima
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Moyses Szklo
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Wendy S Post
- Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Roger S Blumenthal
- Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, MD
| | - John W McEvoy
- Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, MD.
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8
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Geng X, Irvin MR, Hidalgo B, Aslibekyan S, Srinivasasainagendra V, An P, Frazier-Wood AC, Tiwari HK, Dave T, Ryan K, Ordovas JM, Straka RJ, Feitosa MF, Hopkins PN, Borecki I, Province MA, Mitchell BD, Arnett DK, Zhi D. An exome-wide sequencing study of lipid response to high-fat meal and fenofibrate in Caucasians from the GOLDN cohort. J Lipid Res 2018; 59:722-729. [PMID: 29463568 PMCID: PMC5880495 DOI: 10.1194/jlr.p080333] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Revised: 02/04/2018] [Indexed: 12/30/2022] Open
Abstract
Our understanding of genetic influences on the response of lipids to specific interventions is limited. In this study, we sought to elucidate effects of rare genetic variants on lipid response to a high-fat meal challenge and fenofibrate (FFB) therapy in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) cohort using an exome-wide sequencing-based association study. Our results showed that the rare coding variants in ITGA7, SIPA1L2, and CEP72 are significantly associated with fasting LDL cholesterol response to FFB (P = 1.24E-07), triglyceride postprandial area under the increase (AUI) (P = 2.31E-06), and triglyceride postprandial AUI response to FFB (P = 1.88E-06), respectively. We sought to replicate the association for SIPA1L2 in the Heredity and Phenotype Intervention (HAPI) Heart Study, which included a high-fat meal challenge but not FFB treatment. The associated rare variants in GOLDN were not observed in the HAPI Heart study, and thus the gene-based result was not replicated. For functional validation, we found that gene transcript level of SIPA1L2 is associated with triglyceride postprandial AUI (P < 0.05) in GOLDN. Our study suggests unique genetic mechanisms contributing to the lipid response to the high-fat meal challenge and FFB therapy.
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Affiliation(s)
- Xin Geng
- School of Biomedical Informatics The University of Texas Health Science Center at Houston, Houston, TX 77030
| | - Marguerite R Irvin
- Departments of Epidemiology University of Alabama at Birmingham, Birmingham, AL 35233
| | - Bertha Hidalgo
- Departments of Epidemiology University of Alabama at Birmingham, Birmingham, AL 35233
| | - Stella Aslibekyan
- Departments of Epidemiology University of Alabama at Birmingham, Birmingham, AL 35233
| | | | - Ping An
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110
| | - Alexis C Frazier-Wood
- US Department of Agriculture/Agricultural Research Service Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX 77030
| | - Hemant K Tiwari
- Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35233
| | - Tushar Dave
- Department of Medicine, Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201
| | - Kathleen Ryan
- Department of Medicine, Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201
| | - Jose M Ordovas
- Nutrition and Genomics Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA 02111; Instituto Madrileño de Estudios Avanzados en Alimentación, Madrid 28049, Spain; Centro Nacional Investigaciones Cardiovasculares, Madrid 28029, Spain
| | - Robert J Straka
- Department of Experimental and Clinical Pharmacology Minneapolis, University of Minnesota, MN 55455
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110
| | - Paul N Hopkins
- Division of Cardiovascular Medicine, University of Utah, Salt Lake City, UT 84112
| | - Ingrid Borecki
- Genetic Analysis Center, Department of Biostatistics, University of Washington, Seattle, WA 98105
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110
| | - Braxton D Mitchell
- Department of Medicine, Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY 40506.
| | - Degui Zhi
- School of Biomedical Informatics The University of Texas Health Science Center at Houston, Houston, TX 77030; School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030.
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9
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Chen H, Cade BE, Gleason KJ, Bjonnes AC, Stilp AM, Sofer T, Conomos MP, Ancoli-Israel S, Arens R, Azarbarzin A, Bell GI, Below JE, Chun S, Evans DS, Ewert R, Frazier-Wood AC, Gharib SA, Haba-Rubio J, Hagen EW, Heinzer R, Hillman DR, Johnson WC, Kutalik Z, Lane JM, Larkin EK, Lee SK, Liang J, Loredo JS, Mukherjee S, Palmer LJ, Papanicolaou GJ, Penzel T, Peppard PE, Post WS, Ramos AR, Rice K, Rotter JI, Sands SA, Shah NA, Shin C, Stone KL, Stubbe B, Sul JH, Tafti M, Taylor KD, Teumer A, Thornton TA, Tranah GJ, Wang C, Wang H, Warby SC, Wellman DA, Zee PC, Hanis CL, Laurie CC, Gottlieb DJ, Patel SR, Zhu X, Sunyaev SR, Saxena R, Lin X, Redline S. Multiethnic Meta-Analysis Identifies RAI1 as a Possible Obstructive Sleep Apnea-related Quantitative Trait Locus in Men. Am J Respir Cell Mol Biol 2018; 58:391-401. [PMID: 29077507 PMCID: PMC5854957 DOI: 10.1165/rcmb.2017-0237oc] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2017] [Accepted: 10/24/2017] [Indexed: 12/19/2022] Open
Abstract
Obstructive sleep apnea (OSA) is a common heritable disorder displaying marked sexual dimorphism in disease prevalence and progression. Previous genetic association studies have identified a few genetic loci associated with OSA and related quantitative traits, but they have only focused on single ethnic groups, and a large proportion of the heritability remains unexplained. The apnea-hypopnea index (AHI) is a commonly used quantitative measure characterizing OSA severity. Because OSA differs by sex, and the pathophysiology of obstructive events differ in rapid eye movement (REM) and non-REM (NREM) sleep, we hypothesized that additional genetic association signals would be identified by analyzing the NREM/REM-specific AHI and by conducting sex-specific analyses in multiethnic samples. We performed genome-wide association tests for up to 19,733 participants of African, Asian, European, and Hispanic/Latino American ancestry in 7 studies. We identified rs12936587 on chromosome 17 as a possible quantitative trait locus for NREM AHI in men (N = 6,737; P = 1.7 × 10-8) but not in women (P = 0.77). The association with NREM AHI was replicated in a physiological research study (N = 67; P = 0.047). This locus overlapping the RAI1 gene and encompassing genes PEMT1, SREBF1, and RASD1 was previously reported to be associated with coronary artery disease, lipid metabolism, and implicated in Potocki-Lupski syndrome and Smith-Magenis syndrome, which are characterized by abnormal sleep phenotypes. We also identified gene-by-sex interactions in suggestive association regions, suggesting that genetic variants for AHI appear to vary by sex, consistent with the clinical observations of strong sexual dimorphism.
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Affiliation(s)
- Han Chen
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health and
- Center for Precision Health, School of Public Health & School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas
| | - Brian E. Cade
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts
| | - Kevin J. Gleason
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Department of Public Health Sciences, University of Chicago, Chicago, Illinois
| | - Andrew C. Bjonnes
- Division of Genetics, Brigham and Women’s Hospital, Boston, Massachusetts
- Center for Genomic Medicine and Department of Anesthesia, Pain, and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Adrienne M. Stilp
- Department of Biostatistics, University of Washington, Seattle, Washington
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Biostatistics, University of Washington, Seattle, Washington
| | - Matthew P. Conomos
- Department of Biostatistics, University of Washington, Seattle, Washington
| | - Sonia Ancoli-Israel
- Departments of Medicine and Psychiatry, University of California, San Diego, California
| | - Raanan Arens
- the Children’s Hospital at Montefiore, Division of Respiratory and Sleep Medicine, Albert Einstein College of Medicine, Bronx, New York
| | - Ali Azarbarzin
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts
| | - Graeme I. Bell
- Section of Adult and Pediatric Endocrinology, Diabetes, and Metabolism, the University of Chicago, Chicago, Illinois
| | - Jennifer E. Below
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health and
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Sung Chun
- Division of Genetics, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Medical Sciences, Harvard Medical School, Boston, Massachusetts
| | - Daniel S. Evans
- California Pacific Medical Center Research Institute, San Francisco, California
| | - Ralf Ewert
- Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | | | - Sina A. Gharib
- Computational Medicine Core, Center for Lung Biology, University of Washington Medicine Sleep Center, Division of Pulmonary, Critical Care, and Sleep Medicine, University of Washington, Seattle, Washington
| | - José Haba-Rubio
- Center of Investigation and Research on Sleep, Lausanne University Hospital, Lausanne, Switzerland
| | - Erika W. Hagen
- Department of Population Health Sciences, University of Wisconsin, Madison, Wisconsin
| | - Raphael Heinzer
- Center of Investigation and Research on Sleep, Lausanne University Hospital, Lausanne, Switzerland
| | - David R. Hillman
- Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia
| | - W. Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, Washington
| | - Zoltan Kutalik
- Institute of Social and Preventive Medicine, University Hospital of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Jacqueline M. Lane
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts
- Center for Genomic Medicine and Department of Anesthesia, Pain, and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
| | - Emma K. Larkin
- Department of Medicine, Division of Allergy, Pulmonary, and Critical Care, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Seung Ku Lee
- Institute of Human Genomic Study, College of Medicine, Korea University Ansan Hospital, Jeokgum-ro, Danwon-gu, Ansan-si, Gyeonggi-Do, Republic of Korea
| | - Jingjing Liang
- Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Cleveland, Ohio
| | - Jose S. Loredo
- Division of Pulmonary Critical Care and Sleep Medicine, Department of Medicine, University of California San Diego School of Medicine, La Jolla, California
| | - Sutapa Mukherjee
- Adelaide Institute for Sleep Health, Flinders Centre of Research Excellence, Flinders University, Adelaide, South Australia, Australia
| | - Lyle J. Palmer
- School of Public Health, University of Adelaide, Adelaide, South Australia, Australia
| | - George J. Papanicolaou
- Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, Maryland
| | - Thomas Penzel
- University Hospital Charité Berlin, Sleep Center, Berlin, Germany
| | - Paul E. Peppard
- Department of Population Health Sciences, University of Wisconsin, Madison, Wisconsin
| | - Wendy S. Post
- Division of Cardiology, Johns Hopkins University, Baltimore, Maryland
| | - Alberto R. Ramos
- Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida
| | - Ken Rice
- Department of Biostatistics, University of Washington, Seattle, Washington
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute and Department of Pediatrics at Harbor–University of California Los Angeles Medical Center, Torrance, California
| | - Scott A. Sands
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts
| | - Neomi A. Shah
- Division of Pulmonary, Critical Care, and Sleep, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Chol Shin
- Department of Pulmonary, Sleep, and Critical Care Medicine, College of Medicine, Korea University Ansan Hospital, Jeokgum-ro, Danwon-gu, Ansan-si, Gyeonggi-do, Republic of Korea
| | - Katie L. Stone
- California Pacific Medical Center Research Institute, San Francisco, California
| | - Beate Stubbe
- Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Jae Hoon Sul
- Division of Genetics, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Medical Sciences, Harvard Medical School, Boston, Massachusetts
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, California
| | - Mehdi Tafti
- Center of Investigation and Research on Sleep, Lausanne University Hospital, Lausanne, Switzerland
- Department of Physiology, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Kent D. Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute and Department of Pediatrics at Harbor–University of California Los Angeles Medical Center, Torrance, California
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | | | - Gregory J. Tranah
- California Pacific Medical Center Research Institute, San Francisco, California
| | - Chaolong Wang
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
- Computational and Systems Biology, Genome Institute of Singapore, Singapore
| | - Heming Wang
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Cleveland, Ohio
| | - Simon C. Warby
- Department of Psychiatry, University of Montreal, Montreal, Quebec, Canada
| | - D. Andrew Wellman
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts
| | - Phyllis C. Zee
- Department of Neurology and Sleep Medicine Center, Northwestern University, Chicago, Illinois
| | - Craig L. Hanis
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health and
| | - Cathy C. Laurie
- Department of Biostatistics, University of Washington, Seattle, Washington
| | - Daniel J. Gottlieb
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts
- Veterans Affairs Boston Healthcare System, Boston, Massachusetts
| | - Sanjay R. Patel
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Xiaofeng Zhu
- Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Cleveland, Ohio
| | - Shamil R. Sunyaev
- Division of Genetics, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Medical Sciences, Harvard Medical School, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts; and
| | - Richa Saxena
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts
- Center for Genomic Medicine and Department of Anesthesia, Pain, and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
| | - Xihong Lin
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts
- Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
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10
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Smith CE, Follis JL, Dashti HS, Tanaka T, Graff M, Fretts AM, Kilpeläinen TO, Wojczynski MK, Richardson K, Nalls MA, Schulz CA, Liu Y, Frazier-Wood AC, van Eekelen E, Wang C, de Vries PS, Mikkilä V, Rohde R, Psaty BM, Hansen T, Feitosa MF, Lai CQ, Houston DK, Ferruci L, Ericson U, Wang Z, de Mutsert R, Oddy WH, de Jonge EAL, Seppälä I, Justice AE, Lemaitre RN, Sørensen TIA, Province MA, Parnell LD, Garcia ME, Bandinelli S, Orho-Melander M, Rich SS, Rosendaal FR, Pennell CE, Kiefte-de Jong JC, Kähönen M, Young KL, Pedersen O, Aslibekyan S, Rotter JI, Mook-Kanamori DO, Zillikens MC, Raitakari OT, North KE, Overvad K, Arnett DK, Hofman A, Lehtimäki T, Tjønneland A, Uitterlinden AG, Rivadeneira F, Franco OH, German JB, Siscovick DS, Cupples LA, Ordovás JM. Genome-Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent. Mol Nutr Food Res 2018; 62:10.1002/mnfr.201700347. [PMID: 28941034 PMCID: PMC5803424 DOI: 10.1002/mnfr.201700347] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2017] [Revised: 07/28/2017] [Indexed: 11/10/2022]
Abstract
SCOPE Body weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter-individual variability in associations between body weight and dairy consumption. METHODS AND RESULTS A genome-wide interaction study to discover genetic variants that account for variation in BMI in the context of low-fat, high-fat and total dairy intake in cross-sectional analysis was conducted. Data from nine discovery studies (up to 25 513 European descent individuals) were meta-analyzed. Twenty-six genetic variants reached the selected significance threshold (p-interaction <10-7) , and six independent variants (LINC01512-rs7751666, PALM2/AKAP2-rs914359, ACTA2-rs1388, PPP1R12A-rs7961195, LINC00333-rs9635058, AC098847.1-rs1791355) were evaluated meta-analytically for replication of interaction in up to 17 675 individuals. Variant rs9635058 (128 kb 3' of LINC00333) was replicated (p-interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p-interaction = 7.36 × 10-8) such that each serving of low-fat dairy was associated with 0.225 kg m-2 lower BMI per each additional copy of the effect allele (A). A second genetic variant (ACTA2-rs1388) approached interaction replication significance for low-fat dairy exposure. CONCLUSION Body weight responses to dairy intake may be modified by genotype, in that greater dairy intake may protect a genetic subgroup from higher body weight.
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Affiliation(s)
- Caren E Smith
- Nutrition and Genomics Laboratory, Jean Mayer-US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA
| | | | - Hassan S Dashti
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Amanda M Fretts
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Tuomas O Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, 2100, Denmark
| | - Mary K Wojczynski
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Kris Richardson
- Nutrition and Genomics Laboratory, Jean Mayer-USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
- Contractor/consultant with Kelly Services, Rockville, MD, USA
| | | | - Yongmei Liu
- Department of Epidemiology & Prevention, Wake Forest School of Medicine, Wake Forest University, Winston-Salem, NC, USA
| | - Alexis C Frazier-Wood
- USDA / ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA
| | - Esther van Eekelen
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Carol Wang
- School of Women's and Infants' Health, University of Western Australia, Perth, Australia
| | - Paul S de Vries
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - Vera Mikkilä
- Division of Nutrition, Department of Food and Environmental Sciences, University of Helsinki, Helsinki
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Rebecca Rohde
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Bruce M Psaty
- Departments of Medicine, Epidemiology and Health Services, University of Washington, Seattle, WA, USA
- Group Health Research Institute, Group Health Cooperative, Seattle, WA, USA
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, 2100, Denmark
| | - Mary F Feitosa
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Chao-Qiang Lai
- USDA ARS, Nutrition and Genomics Laboratory, Jean Mayer-USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
| | - Denise K Houston
- Department of Internal Medicine, Wake Forest School of Medicine, Wake Forest University, Winston-Salem, NC, USA
| | - Luigi Ferruci
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Ulrika Ericson
- LUDC, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Zhe Wang
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Wendy H Oddy
- Menzies Institute for Medical Research, University of Tasmania, Australia
| | - Ester A L de Jonge
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere University School of Medicine, Tampere, Finland
| | - Anne E Justice
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA
| | | | - Thorkild I A Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, 2100, Denmark
- Department of Clinical Epidemiology (formerly Institute of Preventive Medicine), Bispebjerg and Frederiksberg Hospitals, The Capital Region, Copenhagen, 2000, Denmark
- MRC Integrative Epidemiology Unit & School of Social and community Medicine, University of Bristol, Bristol, BS82BN, UK
| | - Michael A Province
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Laurence D Parnell
- USDA ARS, Nutrition and Genomics Laboratory, Jean Mayer-USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
| | | | | | | | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Craig E Pennell
- School of Women's and Infants' Health, University of Western Australia, Perth, Australia
| | | | - Mika Kähönen
- Department of Clinical Physiology, University of Tampere and Tampere University Hospital, Tampere, Finland
| | - Kristin L Young
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, 2100, Denmark
| | - Stella Aslibekyan
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
| | - M Carola Zillikens
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, University of Turku, Turku, Finland
| | - Kari E North
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA
- Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, 27514, USA
| | - Kim Overvad
- Department of Public Health, Section for Epidemiology, Aarhus University, DK-8000, Aarhus C, Denmark
- Aalborg University Hospital, DK-9000, Aalborg, Denmark
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
- Department of Nutrition, Harvard School of Public Health, Boston, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere University School of Medicine, Tampere, Finland
| | - Anne Tjønneland
- Danish Cancer Society Research Center, Copenhagen, 2100, Denmark
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, the Netherlands
| | - Oscar H Franco
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - J Bruce German
- Department of Food Science and Technology, University of California, Davis, CA, USA
| | | | - L Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, USA
| | - José M Ordovás
- Nutrition and Genomics Laboratory, Jean Mayer-US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA
- The Department of Epidemiology and Population Genetics, Centro Nacional Investigación Cardiovasculares (CNIC) Madrid, Spain
- IMDEA Food, Madrid, Spain
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11
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McKeown NM, Dashti HS, Ma J, Haslam DE, Kiefte-de Jong JC, Smith CE, Tanaka T, Graff M, Lemaitre RN, Rybin D, Sonestedt E, Frazier-Wood AC, Mook-Kanamori DO, Li Y, Wang CA, Leermakers ETM, Mikkilä V, Young KL, Mukamal KJ, Cupples LA, Schulz CA, Chen TA, Li-Gao R, Huang T, Oddy WH, Raitakari O, Rice K, Meigs JB, Ericson U, Steffen LM, Rosendaal FR, Hofman A, Kähönen M, Psaty BM, Brunkwall L, Uitterlinden AG, Viikari J, Siscovick DS, Seppälä I, North KE, Mozaffarian D, Dupuis J, Orho-Melander M, Rich SS, de Mutsert R, Qi L, Pennell CE, Franco OH, Lehtimäki T, Herman MA. Sugar-sweetened beverage intake associations with fasting glucose and insulin concentrations are not modified by selected genetic variants in a ChREBP-FGF21 pathway: a meta-analysis. Diabetologia 2018; 61:317-330. [PMID: 29098321 PMCID: PMC5826559 DOI: 10.1007/s00125-017-4475-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2016] [Accepted: 08/29/2017] [Indexed: 12/13/2022]
Abstract
AIMS/HYPOTHESIS Sugar-sweetened beverages (SSBs) are a major dietary contributor to fructose intake. A molecular pathway involving the carbohydrate responsive element-binding protein (ChREBP) and the metabolic hormone fibroblast growth factor 21 (FGF21) may influence sugar metabolism and, thereby, contribute to fructose-induced metabolic disease. We hypothesise that common variants in 11 genes involved in fructose metabolism and the ChREBP-FGF21 pathway may interact with SSB intake to exacerbate positive associations between higher SSB intake and glycaemic traits. METHODS Data from 11 cohorts (six discovery and five replication) in the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided association and interaction results from 34,748 adults of European descent. SSB intake (soft drinks, fruit punches, lemonades or other fruit drinks) was derived from food-frequency questionnaires and food diaries. In fixed-effects meta-analyses, we quantified: (1) the associations between SSBs and glycaemic traits (fasting glucose and fasting insulin); and (2) the interactions between SSBs and 18 independent SNPs related to the ChREBP-FGF21 pathway. RESULTS In our combined meta-analyses of discovery and replication cohorts, after adjustment for age, sex, energy intake, BMI and other dietary covariates, each additional serving of SSB intake was associated with higher fasting glucose (β ± SE 0.014 ± 0.004 [mmol/l], p = 1.5 × 10-3) and higher fasting insulin (0.030 ± 0.005 [log e pmol/l], p = 2.0 × 10-10). No significant interactions on glycaemic traits were observed between SSB intake and selected SNPs. While a suggestive interaction was observed in the discovery cohorts with a SNP (rs1542423) in the β-Klotho (KLB) locus on fasting insulin (0.030 ± 0.011 log e pmol/l, uncorrected p = 0.006), results in the replication cohorts and combined meta-analyses were non-significant. CONCLUSIONS/INTERPRETATION In this large meta-analysis, we observed that SSB intake was associated with higher fasting glucose and insulin. Although a suggestive interaction with a genetic variant in the ChREBP-FGF21 pathway was observed in the discovery cohorts, this observation was not confirmed in the replication analysis. TRIAL REGISTRATION Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005121 (Framingham Offspring Study), NCT00005487 (Multi-Ethnic Study of Atherosclerosis) and NCT00005152 (Nurses' Health Study).
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Affiliation(s)
- Nicola M McKeown
- Nutritional Epidemiology Program, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, 711 Washington Street, Boston, MA, 02111, USA.
| | - Hassan S Dashti
- Nutrition & Genomics Laboratory, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA.
- Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge Street, Boston, MA, 02114, USA.
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.
| | - Jiantao Ma
- National Heart, Lung, and Blood Institute's Framingham Heart Study and Population Sciences Branch, Framingham, MA, USA
| | - Danielle E Haslam
- Nutritional Epidemiology Program, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, 711 Washington Street, Boston, MA, 02111, USA
| | - Jessica C Kiefte-de Jong
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
- Global Public Health, Leiden University College, The Hague, the Netherlands
| | - Caren E Smith
- Nutrition & Genomics Laboratory, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | | | - Denis Rybin
- Boston University Data Coordinating Center, Boston University, Boston, MA, USA
| | - Emily Sonestedt
- Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Alexis C Frazier-Wood
- USDA/ARS Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Yanping Li
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Carol A Wang
- School of Women's and Infants' Health, The University of Western Australia, Crawley, WA, Australia
| | | | - Vera Mikkilä
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Food and Environmental Sciences, University of Helsinki, Helsinki, Finland
| | - Kristin L Young
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Kenneth J Mukamal
- Division of General Medicine and Primary Care, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - L Adrienne Cupples
- National Heart, Lung, and Blood Institute's Framingham Heart Study and Population Sciences Branch, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | | | - Tzu-An Chen
- USDA/ARS Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Tao Huang
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Wendy H Oddy
- Telethon Kids Institute, Subiaco, WA, Australia
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Kenneth Rice
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - James B Meigs
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Ulrika Ericson
- Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Lyn M Steffen
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Bruce M Psaty
- Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Services, University of Washington, Seattle, WA, USA
- Group Health Research Institute, Group Health Cooperative, Seattle, WA, USA
| | - Louise Brunkwall
- Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Andre G Uitterlinden
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Jorma Viikari
- Department of Medicine, University of Turku, Turku, Finland
- Division of Medicine, Turku University Hospital, Turku, Finland
| | | | - Ilkka Seppälä
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Kari E North
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Dariush Mozaffarian
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Josée Dupuis
- National Heart, Lung, and Blood Institute's Framingham Heart Study and Population Sciences Branch, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | | | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Lu Qi
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Craig E Pennell
- School of Women's and Infants' Health, The University of Western Australia, Crawley, WA, Australia
| | - Oscar H Franco
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Terho Lehtimäki
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Mark A Herman
- Division Of Endocrinology, Metabolism, and Nutrition, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
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12
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McComb B, Frazier-Wood AC, Dawson J, Allison DB. Drawing conclusions from within-group comparisons and selected subsets of data leads to unsubstantiated conclusions: Letter regarding Malakellis et al. Aust N Z J Public Health 2017; 42:214. [PMID: 29281164 DOI: 10.1111/1753-6405.12755] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Affiliation(s)
- Bryan McComb
- Division of Biostatistics and Department of Population Health, New York University School of Medicine, US
| | | | - John Dawson
- Department of Nutritional Sciences, Texas Tech University, US
| | - David B Allison
- Department of Epidemiology and Biostatistics, School of Public Health, Indiana University - Bloomington, US
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Wu JHY, Marklund M, Imamura F, Tintle N, Ardisson Korat AV, de Goede J, Zhou X, Yang WS, de Oliveira Otto MC, Kröger J, Qureshi W, Virtanen JK, Bassett JK, Frazier-Wood AC, Lankinen M, Murphy RA, Rajaobelina K, Del Gobbo LC, Forouhi NG, Luben R, Khaw KT, Wareham N, Kalsbeek A, Veenstra J, Luo J, Hu FB, Lin HJ, Siscovick DS, Boeing H, Chen TA, Steffen B, Steffen LM, Hodge A, Eriksdottir G, Smith AV, Gudnason V, Harris TB, Brouwer IA, Berr C, Helmer C, Samieri C, Laakso M, Tsai MY, Giles GG, Nurmi T, Wagenknecht L, Schulze MB, Lemaitre RN, Chien KL, Soedamah-Muthu SS, Geleijnse JM, Sun Q, Harris WS, Lind L, Ärnlöv J, Riserus U, Micha R, Mozaffarian D. Omega-6 fatty acid biomarkers and incident type 2 diabetes: pooled analysis of individual-level data for 39 740 adults from 20 prospective cohort studies. Lancet Diabetes Endocrinol 2017; 5:965-974. [PMID: 29032079 PMCID: PMC6029721 DOI: 10.1016/s2213-8587(17)30307-8] [Citation(s) in RCA: 196] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2017] [Revised: 08/01/2017] [Accepted: 08/04/2017] [Indexed: 12/23/2022]
Abstract
BACKGROUND The metabolic effects of omega-6 polyunsaturated fatty acids (PUFAs) remain contentious, and little evidence is available regarding their potential role in primary prevention of type 2 diabetes. We aimed to assess the associations of linoleic acid and arachidonic acid biomarkers with incident type 2 diabetes. METHODS We did a pooled analysis of new, harmonised, individual-level analyses for the biomarkers linoleic acid and its metabolite arachidonic acid and incident type 2 diabetes. We analysed data from 20 prospective cohort studies from ten countries (Iceland, the Netherlands, the USA, Taiwan, the UK, Germany, Finland, Australia, Sweden, and France), with biomarkers sampled between 1970 and 2010. Participants included in the analyses were aged 18 years or older and had data available for linoleic acid and arachidonic acid biomarkers at baseline. We excluded participants with type 2 diabetes at baseline. The main outcome was the association between omega-6 PUFA biomarkers and incident type 2 diabetes. We assessed the relative risk of type 2 diabetes prospectively for each cohort and lipid compartment separately using a prespecified analytic plan for exposures, covariates, effect modifiers, and analysis, and the findings were then pooled using inverse-variance weighted meta-analysis. FINDINGS Participants were 39 740 adults, aged (range of cohort means) 49-76 years with a BMI (range of cohort means) of 23·3-28·4 kg/m2, who did not have type 2 diabetes at baseline. During a follow-up of 366 073 person-years, we identified 4347 cases of incident type 2 diabetes. In multivariable-adjusted pooled analyses, higher proportions of linoleic acid biomarkers as percentages of total fatty acid were associated with a lower risk of type 2 diabetes overall (risk ratio [RR] per interquintile range 0·65, 95% CI 0·60-0·72, p<0·0001; I2=53·9%, pheterogeneity=0·002). The associations between linoleic acid biomarkers and type 2 diabetes were generally similar in different lipid compartments, including phospholipids, plasma, cholesterol esters, and adipose tissue. Levels of arachidonic acid biomarker were not significantly associated with type 2 diabetes risk overall (RR per interquintile range 0·96, 95% CI 0·88-1·05; p=0·38; I2=63·0%, pheterogeneity<0·0001). The associations between linoleic acid and arachidonic acid biomarkers and the risk of type 2 diabetes were not significantly modified by any prespecified potential sources of heterogeneity (ie, age, BMI, sex, race, aspirin use, omega-3 PUFA levels, or variants of the FADS gene; all pheterogeneity≥0·13). INTERPRETATION Findings suggest that linoleic acid has long-term benefits for the prevention of type 2 diabetes and that arachidonic acid is not harmful. FUNDING Funders are shown in the appendix.
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Affiliation(s)
- Jason H Y Wu
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
| | - Matti Marklund
- Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Uppsala, Sweden
| | - Fumiaki Imamura
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Nathan Tintle
- Department of Mathematics and Statistics, Dordt College, Sioux Center, IA, USA
| | - Andres V Ardisson Korat
- Department of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Janette de Goede
- Division of Human Nutrition, Wageningen University, Wageningen, Netherlands
| | - Xia Zhou
- School of Public Health, Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - Wei-Sin Yang
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Marcia C de Oliveira Otto
- Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center, School of Public Health, Houston, TX, USA
| | - Janine Kröger
- German Institute of Human Nutrition, Potsdam, Germany
| | | | - Jyrki K Virtanen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | | | - Alexis C Frazier-Wood
- US Department of Agriculture/Agricultural Research Service, Children's Nutrition Research Center, Houston, TX, USA
| | - Maria Lankinen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | | | - Kalina Rajaobelina
- University of Bordeaux, INSERM, Bordeaux Population Health Research Centre, UMR 1219, Bordeaux, France
| | - Liana C Del Gobbo
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Nita G Forouhi
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Robert Luben
- Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Kay-Tee Khaw
- Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, UK; Department of Mathematics and Statistics, Dordt College, Sioux Center, IA, USA
| | - Nick Wareham
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Anya Kalsbeek
- Department of Mathematics and Statistics, Dordt College, Sioux Center, IA, USA; Department of Biology, Dordt College, Sioux Center, IA, USA
| | - Jenna Veenstra
- Department of Mathematics and Statistics, Dordt College, Sioux Center, IA, USA; Department of Biology, Dordt College, Sioux Center, IA, USA
| | - Juhua Luo
- Department of Epidemiology and Biostatistics, Indiana University, Bloomington, IN, USA
| | - Frank B Hu
- Department of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Hung-Ju Lin
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | | | - Heiner Boeing
- German Institute of Human Nutrition, Potsdam, Germany
| | - Tzu-An Chen
- US Department of Agriculture/Agricultural Research Service, Children's Nutrition Research Center, Houston, TX, USA
| | - Brian Steffen
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Lyn M Steffen
- School of Public Health, Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | | | | | | | | | | | | | - Claudine Berr
- INSERM U1061, Neuropsychiatry: Epidemiological and Clinical Research, and Montpellier University Hospital, Montpellier University, Montpellier, France
| | - Catherine Helmer
- University of Bordeaux, INSERM, Bordeaux Population Health Research Centre, UMR 1219, Bordeaux, France
| | - Cecilia Samieri
- University of Bordeaux, INSERM, Bordeaux Population Health Research Centre, UMR 1219, Bordeaux, France
| | - Markku Laakso
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | | | - Tarja Nurmi
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | | | | | - Rozenn N Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Kuo-Liong Chien
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan; Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | | | | | - Qi Sun
- Department of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - William S Harris
- Department of Internal Medicine, Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, USA; OmegaQuant Analytics, Sioux Falls, SD, USA
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Johan Ärnlöv
- Department of Neurobiology, Care Sciences and Society, Division of Family Medicine, Karolinska Institute, Stockholm, Sweden; School of Health and Social Studies, Dalarna University, Falun, Sweden
| | - Ulf Riserus
- Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Uppsala, Sweden
| | - Renata Micha
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Dariush Mozaffarian
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
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14
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Simon TG, Trejo MEP, Zeb I, Frazier-Wood AC, McClelland RL, Chung RT, Budoff MJ. Coffee consumption is not associated with prevalent subclinical cardiovascular disease (CVD) or the risk of CVD events, in nonalcoholic fatty liver disease: results from the multi-ethnic study of atherosclerosis. Metabolism 2017; 75:1-5. [PMID: 28964324 PMCID: PMC5657519 DOI: 10.1016/j.metabol.2017.06.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2017] [Revised: 05/27/2017] [Accepted: 06/17/2017] [Indexed: 01/19/2023]
Abstract
BACKGROUND Atherosclerosis and its clinical sequelae represent the leading cause of mortality among patients with nonalcoholic fatty liver disease (NAFLD). While epidemiologic data support the hepatoprotective benefits of coffee in NAFLD, whether coffee improves NAFLD-associated CVD risk is unknown. METHODS We examined 3710 ethnically-diverse participants from the Multi-Ethnic Study of Atherosclerosis (MESA) cohort, without history of known liver disease, and with available coffee data from a validated 120-item food frequency questionnaire. All participants underwent baseline non-contrast cardiac CT from which NAFLD was defined by liver:spleen ratio (L:S<1.0), and subclinical CVD was defined by coronary artery calcium (CAC)>0. Major CVD events were defined by the first occurrence of myocardial infarction, cardiac arrest, angina, stroke, or CVD death. We used log-binomial regression to calculate the adjusted prevalence ratio (PR) for CAC>0 by coffee intake and NAFLD status, and events were compared between groups using frequency of events within adjusted Cox proportional hazard regression models. RESULTS Seventeen percent (N=637) of participants met criteria for NAFLD. NAFLD participants were more likely to have elevated BMI (mean 31.1±5.5kg/m2 vs. 28.0±5.2kg/m2, p<0.0001), and diabetes (22% vs. 11%, p<0.0001), but did not differ in daily coffee consumption (p=0.97). Among NAFLD participants, coffee consumption was not associated with prevalent, baseline CAC>0 (PR=1.02 [0.98-1.07]). Over 12.8years of follow-up, 93 NAFLD and 415 non-NAFLD participants experienced a CV event. However, coffee intake was not associated with incident CVD events, in either NAFLD (HR=1.05 [0.91-1.21]) or non-NAFLD participants (HR=1.03 [0.97-1.11]). CONCLUSION In a large, population-based cohort, coffee consumption was not associated with the prevalence of subclinical CVD, nor did coffee impact the future risk of major CVD events, regardless of underlying NAFLD status.
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Affiliation(s)
- Tracey G Simon
- Liver Center, Gastrointestinal Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | | | - Irfan Zeb
- Department of Cardiology, Mount Sinai St. Luke's Roosevelt Hospital (Bronx-Lebanon Hospital Center), United States
| | - Alexis C Frazier-Wood
- Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, United States
| | - Robyn L McClelland
- Department of Biostatistics, University of Washington, Seattle, WA, United States
| | - Raymond T Chung
- Liver Center, Gastrointestinal Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Matthew J Budoff
- Los Angeles Biomedical Research Institute, Division of Cardiology, Harbor-UCLA Medical Center, Los Angeles, CA, United States.
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15
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Dashti HS, Follis JL, Smith CE, Tanaka T, Garaulet M, Gottlieb DJ, Hruby A, Jacques PF, Kiefte-de Jong JC, Lamon-Fava S, Scheer FAJL, Bartz TM, Kovanen L, Wojczynski MK, Frazier-Wood AC, Ahluwalia TS, Perälä MM, Jonsson A, Muka T, Kalafati IP, Mikkilä V, Ordovás JM. Erratum. Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits. Diabetes Care 2015;38:1456-1466. Diabetes Care 2017; 40:1420. [PMID: 28842526 PMCID: PMC5606312 DOI: 10.2337/dc17-er10a] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
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16
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Wang H, Cade BE, Chen H, Gleason KJ, Saxena R, Feng T, Larkin EK, Vasan RS, Lin H, Patel SR, Tracy RP, Liu Y, Gottlieb DJ, Below JE, Hanis CL, Petty LE, Sunyaev SR, Frazier-Wood AC, Rotter JI, Post W, Lin X, Redline S, Zhu X. Variants in angiopoietin-2 (ANGPT2) contribute to variation in nocturnal oxyhaemoglobin saturation level. Hum Mol Genet 2017; 25:5244-5253. [PMID: 27798093 DOI: 10.1093/hmg/ddw324] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2016] [Accepted: 09/19/2016] [Indexed: 12/30/2022] Open
Abstract
Genetic determinants of sleep-disordered breathing (SDB), a common set of disorders that contribute to significant cardiovascular and neuropsychiatric morbidity, are not clear. Overnight nocturnal oxygen saturation (SaO2) is a clinically relevant and easily measured indicator of SDB severity but its genetic contribution has never been studied. Our recent study suggests nocturnal SaO2 is heritable. We performed linkage analysis, association analysis and haplotype analysis of average nocturnal oxyhaemoglobin saturation in participants in the Cleveland Family Study (CFS), followed by gene-based association and additional tests in four independent samples. Linkage analysis identified a peak (LOD = 4.29) on chromosome 8p23. Follow-up association analysis identified two haplotypes in angiopoietin-2 (ANGPT2) that significantly contributed to the variation of SaO2 (P = 8 × 10-5) and accounted for a portion of the linkage evidence. Gene-based association analysis replicated the association of ANGPT2 and nocturnal SaO2. A rare missense SNP rs200291021 in ANGPT2 was associated with serum angiopoietin-2 level (P = 1.29 × 10-4), which was associated with SaO2 (P = 0.002). Our study provides the first evidence for the association of ANGPT2, a gene previously implicated in acute lung injury syndromes, with nocturnal SaO2, suggesting that this gene has a broad range of effects on gas exchange, including influencing oxygenation during sleep.
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Affiliation(s)
- Heming Wang
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA
| | - Brian E Cade
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Han Chen
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Kevin J Gleason
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.,Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Richa Saxena
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.,Center for Human Genetic Research and Department of Anesthesia, Pain, and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Tao Feng
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA
| | - Emma K Larkin
- Department of Medicine, Division of Allergy, Pulmonary and Critical Care, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ramachandran S Vasan
- Preventive Medicine & Epidemiology, Boston University School of Medicine, Boston, MA, USA.,Framingham Heart Study, Framingham, MA
| | - Honghuang Lin
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Sanjay R Patel
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.,Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Russell P Tracy
- Department of Pathology & Laboratory Medicine, University of Vermont, Burlington, VT, USA
| | - Yongmei Liu
- Epidemiology and Prevention Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Daniel J Gottlieb
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.,Sleep Disorders Center, VA Boston Healthcare System, Boston, MA, USA
| | - Jennifer E Below
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Craig L Hanis
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Lauren E Petty
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Shamil R Sunyaev
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.,Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Wendy Post
- Division of Cardiology, Johns Hopkins University, Baltimore, MD, USA
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.,Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Xiaofeng Zhu
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA
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17
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Abstract
The observation that children's activity level (AL) differs between novel and familiar situations is well established. What influences individual differences in how AL is different across these situations is less well understood. Drawing on animal literature, which links rats' AL when 1st placed in a novel setting with novelty seeking phenotypes, and child temperament literature, which links AL, novelty response, and shyness, we hypothesized that shyness would be an important component of children's AL in a novel situation. We examined this using mechanically assessed AL from 2 situations (the home and the lab) and 2 measures of shyness (1 parent-rated and 1 observer-rated) on up to 313 twin pairs (145 monozygotic and 168 dizygotic), at 2 and 3 years of age. Biometric genetic models removed from lab AL the variance shared with home AL, representing what was different in AL when the child entered the lab compared to the home. We report that almost half (43%) of the genetic component of AL in the lab was independent of AL in the home, and this unique genetic component shared genetic covariance with shyness. Shyness influences AL in a novel situation such as the lab, indicating that mechanically assessed AL represents more than global motoric activity and provides information on a child's temperamental response to novelty. (PsycINFO Database Record
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18
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Hu Y, Tanaka T, Zhu J, Guan W, Wu JHY, Psaty BM, McKnight B, King IB, Sun Q, Richard M, Manichaikul A, Frazier-Wood AC, Kabagambe EK, Hopkins PN, Ordovas JM, Ferrucci L, Bandinelli S, Arnett DK, Chen YDI, Liang S, Siscovick DS, Tsai MY, Rich SS, Fornage M, Hu FB, Rimm EB, Jensen MK, Lemaitre RN, Mozaffarian D, Steffen LM, Morris AP, Li H, Lin X. Discovery and fine-mapping of loci associated with MUFAs through trans-ethnic meta-analysis in Chinese and European populations. J Lipid Res 2017; 58:974-981. [PMID: 28298293 PMCID: PMC5408616 DOI: 10.1194/jlr.p071860] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2016] [Revised: 02/17/2017] [Indexed: 11/20/2022] Open
Abstract
MUFAs are unsaturated FAs with one double bond and are derived from endogenous synthesis and dietary intake. Accumulating evidence has suggested that plasma and erythrocyte MUFA levels are associated with cardiometabolic disorders, including CVD, T2D, and metabolic syndrome (MS). Previous genome-wide association studies (GWASs) have identified seven loci for plasma and erythrocyte palmitoleic and oleic acid levels in populations of European origin. To identify additional MUFA-associated loci and the potential functional variant at each locus, we performed ethnic-specific GWAS meta-analyses and trans-ethnic meta-analyses in more than 15,000 participants of Chinese and European ancestry. We identified novel genome-wide significant associations for vaccenic acid at FADS1/2 and PKD2L1 [log10(Bayes factor) ≥ 8.07] and for gondoic acid at FADS1/2 and GCKR [log10(Bayes factor) ≥ 6.22], and also observed improved fine-mapping resolutions at FADS1/2 and GCKR loci. The greatest improvement was observed at GCKR, where the number of variants in the 99% credible set was reduced from 16 (covering 94.8 kb) to 5 (covering 19.6 kb, including a missense variant rs1260326) after trans-ethnic meta-analysis. We also confirmed the previously reported associations of PKD2L1, FADS1/2, GCKR, and HIF1AN with palmitoleic acid and of FADS1/2 and LPCAT3 with oleic acid in the Chinese-specific GWAS and the trans-ethnic meta-analyses. Pathway-based analyses suggested that the identified loci were in unsaturated FA metabolism and signaling pathways. Our findings provide novel insight into the genetic basis relevant to MUFA metabolism and biology.
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Affiliation(s)
- Yao Hu
- The Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of the Chinese Academy of Sciences, Shanghai, People's Republic of China
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD
| | - Jingwen Zhu
- The Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of the Chinese Academy of Sciences, Shanghai, People's Republic of China
| | - Weihua Guan
- Division of Biostatistics University of Minnesota, Minneapolis, MN
| | - Jason H Y Wu
- George Institute for Global Health, Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
- Group Health Research Institute, Group Health Cooperative, Seattle, WA
| | - Barbara McKnight
- Department of Biostatistics, University of Washington, Seattle, WA
| | - Irena B King
- Department of Internal Medicine, University of New Mexico, Albuquerque, NM
| | - Qi Sun
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Harvard University, Cambridge, MA
| | - Melissa Richard
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA
- Biostatistics Section, Department of Public Health Sciences, University of Virginia, Charlottesville, VA
| | - Alexis C Frazier-Wood
- USDA Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX
| | - Edmond K Kabagambe
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Paul N Hopkins
- Department of Internal Medicine, University of Utah, Salt Lake City, UT
| | - Jose M Ordovas
- Nutrition and Genomics Laboratory, Jean Mayer-USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA
- Department of Epidemiology and Population Genetics, National Center for Cardiovascular Investigation, Madrid, Spain
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD
| | | | - Donna K Arnett
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL
| | - Yii-Der I Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA
| | - Shuang Liang
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN
| | - David S Siscovick
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA
- New York Academy of Medicine, New York, NY
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX
| | - Frank B Hu
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Harvard University, Cambridge, MA
| | - Eric B Rimm
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Harvard University, Cambridge, MA
| | - Majken K Jensen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Harvard University, Cambridge, MA
| | - Rozenn N Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
| | - Dariush Mozaffarian
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA
| | - Lyn M Steffen
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN
| | - Andrew P Morris
- Genetic and Genomic Epidemiology Unit, Wellcome Trust Centre for Human Genetics, Oxford, United Kingdom
| | - Huaixing Li
- The Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of the Chinese Academy of Sciences, Shanghai, People's Republic of China
| | - Xu Lin
- The Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of the Chinese Academy of Sciences, Shanghai, People's Republic of China
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19
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Davis JS, Lee HY, Kim J, Advani SM, Peng HL, Banfield E, Hawk ET, Chang S, Frazier-Wood AC. Use of non-steroidal anti-inflammatory drugs in US adults: changes over time and by demographic. Open Heart 2017; 4:e000550. [PMID: 28674622 PMCID: PMC5471872 DOI: 10.1136/openhrt-2016-000550] [Citation(s) in RCA: 70] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2016] [Revised: 02/13/2017] [Accepted: 02/21/2017] [Indexed: 12/21/2022] Open
Abstract
OBJECTIVE Aspirin and non-aspirin non-steroidal anti-inflammatory drugs (NSAIDs) are preventive against cardiovascular disease (CVD) and several cancer types, but long-term use has been associated with significant health risks, resulting in conflicting recommendations on NSAID use for prevention of CVD and cancer. Previous research indicates that aspirin use increases with age and CVD risk factors and that a large percentage of the US population regularly use analgesics, including NSAIDs, but there has not been a recent, in-depth assessment of NSAID use prevalence, changes in use over time or predictors of NSAID use in the USA. METHODS We used the cross-sectional, National Health And Nutrition Examination Survey (NHANES) from 1988 to 1994 and three continuous cycles (1999-2004) to assess regular NSAID use prevalence, changes over time and predictors of regular NSAID use. RESULTS Overall, regular NSAID use increased over time and varied by demographic features. Participants over 60 years of age, women, participants with high body mass index, increased waist circumference or heart disease were significantly more likely to be regular NSAID users. By contrast, non-Hispanic African American and Mexican American participants were significantly less likely to regularly use NSAIDs. CONCLUSIONS This study uses a nationally representative data set (NHANES) to provide an exploration of regular NSAID use patterns over time, highlighting several demographic, lifestyle and clinical conditions associated with regular NSAID use. Understanding who is likely to regularly use NSAIDs enables more targeted messaging both for increasing the preventive benefits and for limiting the toxicities associated with regular use of NSAIDs.
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Affiliation(s)
- Jennifer S Davis
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Hwa Young Lee
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jihye Kim
- Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas School of Public Health, Houston, Texas, USA
| | - Shailesh M Advani
- Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas School of Public Health, Houston, Texas, USA.,Department of Pediatrics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Ho-Lan Peng
- Department of Biostatistics, The University of Texas School of Public Health, Houston, Texas, USA
| | - Emilyn Banfield
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.,Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas School of Public Health, Houston, Texas, USA
| | - Ernest T Hawk
- Division of Cancer Prevention and Population Sciences, UT MD Anderson Cancer Center, Houston, Texas, USA
| | - Shine Chang
- Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Alexis C Frazier-Wood
- Baylor College of Medicine, USDA/ARS Children's Nutrition Research Center, Houston, Texas, USA
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20
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Wang Z, Manichukal A, Goff DC, Mora S, Ordovas JM, Pajewski NM, Post WS, Rotter JI, Sale MM, Santorico SA, Siscovick D, Tsai MY, Arnett DK, Rich S, Frazier-Wood AC. Genetic associations with lipoprotein subfraction measures differ by ethnicity in the multi-ethnic study of atherosclerosis (MESA). Hum Genet 2017; 136:715-726. [PMID: 28352986 PMCID: PMC5429342 DOI: 10.1007/s00439-017-1782-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2016] [Accepted: 03/16/2017] [Indexed: 12/25/2022]
Abstract
A recent genome-wide association study associated 62 single nucleotide polymorphisms (SNPs) from 43 genomic loci, with fasting lipoprotein subfractions in European–Americans (EAs) at genome-wide levels of significance across three independent samples. Whether these associations are consistent across ethnicities with a non-European ancestry is unknown. We analyzed 15 lipoprotein subfraction measures, on 1677 African–Americans (AAs), 1450 Hispanic–Americans (HAs), and 775 Chinese–Americans (CHN) participating in the multi-ethnic study of atherosclerosis (MESA). Genome-wide data were obtained using the Affymetrix 6.0 and Illumina HumanOmni chips. Linear regression models between genetic variables and lipoprotein subfractions were adjusted for age, gender, body mass index, smoking, study center, and genetic ancestry (based on principal components), and additionally adjusted for Mexican/Non-Mexican status in HAs. A false discovery rate correction was applied separately within the results for each ethnicity to correct for multiple testing. Power calculations revealed that we did not have the power for SNP-based measures of association, so we analyzed phenotype-specific genetic risk scores (GRSs), constructed as in the original genome-wide analysis. We successfully replicated all 15 GRS–lipoprotein associations in 2527 EAs. Among the 15 significant GRS–lipoprotein associations in EAs, 11 were significant in AAs, 13 in HAs, and 1 in CHNs. Further analyses revealed that ethnicity differences could not be explained by differences in linkage disequilibrium, lipid lowering drugs, diabetes, or gender. Our study emphasizes the importance of ethnicity (here indexing genetic ancestry) in genetic risk for CVD and highlights the need to identify ethnicity-specific genetic variants associated with CVD risk.
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Affiliation(s)
- Zhe Wang
- Department of Epidemiology, Human Genetics and Environmental Health, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Ani Manichukal
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA.,Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA
| | - David C Goff
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, 80045, USA
| | - Samia Mora
- Divisions of Preventive Medicine and Cardiovascular Medicine Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Jose M Ordovas
- Nutrition and Genomics Laboratory, Jean Mayer-US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, 02111, USA.,The Department of Epidemiology and Population Genetics, Centro Nacional Investigación Cardiovasculares (CNIC), 28029, Madrid, Spain.,IMDEA Food, 28049, Madrid, Spain
| | - Nicholas M Pajewski
- Division of Public Health Sciences, Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
| | - Wendy S Post
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.,Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA
| | - Jerome I Rotter
- Los Angeles Biomedical Research Institute and Department of Pediatrics, Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Michele M Sale
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA.,Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA
| | - Stephanie A Santorico
- Department of Mathematical and Statistical Sciences, Human Medical Genetics and Genomics Program, Department of Biostatistics & Informatics, University of Colorado Denver, Denver, CO, 80204, USA
| | - David Siscovick
- Cardiovascular Health Research Unit, Department of Medicine and Epidemiology, University of Washington, Seattle, WA, 98195, USA.,The New York Academy of Medicine, New York, NY, 10029, USA
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY, 40508, USA
| | - Stephen Rich
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, 22908, USA.,Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA
| | - Alexis C Frazier-Wood
- Department of Pediatrics, USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, 77030, USA.
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21
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Miller PE, Zhao D, Frazier-Wood AC, Michos ED, Averill M, Sandfort V, Burke GL, Polak JF, Lima JAC, Post WS, Blumenthal RS, Guallar E, Martin SS. Associations of Coffee, Tea, and Caffeine Intake with Coronary Artery Calcification and Cardiovascular Events. Am J Med 2017; 130:188-197.e5. [PMID: 27640739 PMCID: PMC5263166 DOI: 10.1016/j.amjmed.2016.08.038] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2016] [Revised: 08/17/2016] [Accepted: 08/18/2016] [Indexed: 11/15/2022]
Abstract
BACKGROUND Coffee and tea are 2 of the most commonly consumed beverages in the world. The association of coffee and tea intake with coronary artery calcium and major adverse cardiovascular events remains uncertain. METHODS We examined 6508 ethnically diverse participants with available coffee and tea data from the Multi-Ethnic Study of Atherosclerosis. Intake for each was classified as never, occasional (<1 cup per day), and regular (≥1 cup per day). A coronary artery calcium progression ratio was derived from mixed effect regression models using loge(calcium score+1) as the outcome, with coefficients exponentiated to reflect coronary artery calcium progression ratio versus the reference. Cox proportional hazards analyses were used to evaluate the association between beverage intake and incident cardiovascular events. RESULTS Over a median follow-up of 5.3 years for coronary artery calcium and 11.1 years for cardiovascular events, participants who regularly drank tea (≥1 cup per day) had a slower progression of coronary artery calcium compared with never drinkers after multivariable adjustment. This correlated with a statistically significant lower incidence of cardiovascular events for ≥1 cup per day tea drinkers (adjusted hazard ratio 0.71; 95% confidence interval 0.53-0.95). Compared with never coffee drinkers, regular coffee intake (≥1 cup per day) was not statistically associated with coronary artery calcium progression or cardiovascular events (adjusted hazard ratio 0.97; 95% confidence interval 0.78-1.20). Caffeine intake was marginally inversely associated with coronary artery calcium progression. CONCLUSIONS Moderate tea drinkers had slower progression of coronary artery calcium and reduced risk for cardiovascular events. Future research is needed to understand the potentially protective nature of moderate tea intake.
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Affiliation(s)
- P Elliott Miller
- Department of Critical Care Medicine, National Institutes of Health, Bethesda, Md; Division of Cardiology, Department of Medicine, Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, Md.
| | - Di Zhao
- Department of Epidemiology, Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | | | - Erin D Michos
- Division of Cardiology, Department of Medicine, Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, Md
| | - Michelle Averill
- Department of Environmental and Occupational Health, University of Washington, Seattle
| | - Veit Sandfort
- Department of Radiology and Imaging Sciences, National Institutes of Health, Bethesda, Md
| | - Gregory L Burke
- Division of Public Health Sciences, Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC
| | - Joseph F Polak
- Department of Radiology, Tufts Medical Center, Tufts University School of Medicine, Boston, Mass
| | - Joao A C Lima
- Division of Cardiology, Department of Medicine, Johns Hopkins Hospital, Baltimore, Md
| | - Wendy S Post
- Division of Cardiology, Department of Medicine, Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, Md; Department of Epidemiology, Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Roger S Blumenthal
- Division of Cardiology, Department of Medicine, Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, Md
| | - Eliseo Guallar
- Division of Cardiology, Department of Medicine, Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, Md; Department of Epidemiology, Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Seth S Martin
- Division of Cardiology, Department of Medicine, Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins University School of Medicine, Baltimore, Md
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22
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Cade BE, Chen H, Stilp AM, Gleason KJ, Sofer T, Ancoli-Israel S, Arens R, Bell GI, Below JE, Bjonnes AC, Chun S, Conomos MP, Evans DS, Johnson WC, Frazier-Wood AC, Lane JM, Larkin EK, Loredo JS, Post WS, Ramos AR, Rice K, Rotter JI, Shah NA, Stone KL, Taylor KD, Thornton TA, Tranah GJ, Wang C, Zee PC, Hanis CL, Sunyaev SR, Patel SR, Laurie CC, Zhu X, Saxena R, Lin X, Redline S. Genetic Associations with Obstructive Sleep Apnea Traits in Hispanic/Latino Americans. Am J Respir Crit Care Med 2016; 194:886-897. [PMID: 26977737 PMCID: PMC5074655 DOI: 10.1164/rccm.201512-2431oc] [Citation(s) in RCA: 85] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2015] [Accepted: 03/14/2016] [Indexed: 11/16/2022] Open
Abstract
RATIONALE Obstructive sleep apnea is a common disorder associated with increased risk for cardiovascular disease, diabetes, and premature mortality. Although there is strong clinical and epidemiologic evidence supporting the importance of genetic factors in influencing obstructive sleep apnea, its genetic basis is still largely unknown. Prior genetic studies focused on traits defined using the apnea-hypopnea index, which contains limited information on potentially important genetically determined physiologic factors, such as propensity for hypoxemia and respiratory arousability. OBJECTIVES To define novel obstructive sleep apnea genetic risk loci for obstructive sleep apnea, we conducted genome-wide association studies of quantitative traits in Hispanic/Latino Americans from three cohorts. METHODS Genome-wide data from as many as 12,558 participants in the Hispanic Community Health Study/Study of Latinos, Multi-Ethnic Study of Atherosclerosis, and Starr County Health Studies population-based cohorts were metaanalyzed for association with the apnea-hypopnea index, average oxygen saturation during sleep, and average respiratory event duration. MEASUREMENTS AND MAIN RESULTS Two novel loci were identified at genome-level significance (rs11691765, GPR83, P = 1.90 × 10-8 for the apnea-hypopnea index, and rs35424364; C6ORF183/CCDC162P, P = 4.88 × 10-8 for respiratory event duration) and seven additional loci were identified with suggestive significance (P < 5 × 10-7). Secondary sex-stratified analyses also identified one significant and several suggestive associations. Multiple loci overlapped genes with biologic plausibility. CONCLUSIONS These are the first genome-level significant findings reported for obstructive sleep apnea-related physiologic traits in any population. These findings identify novel associations in inflammatory, hypoxia signaling, and sleep pathways.
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Affiliation(s)
- Brian E. Cade
- Division of Sleep and Circadian Disorders and
- Division of Sleep Medicine and
| | - Han Chen
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Adrienne M. Stilp
- Department of Biostatistics, University of Washington, Seattle, Washington
| | | | - Tamar Sofer
- Department of Biostatistics, University of Washington, Seattle, Washington
| | - Sonia Ancoli-Israel
- Department of Medicine and
- Department of Psychiatry, University of California, San Diego, California
- Department of Veterans Affairs San Diego Center of Excellence for Stress and Mental Health, San Diego, California
| | - Raanan Arens
- The Children’s Hospital at Montefiore, Division of Respiratory and Sleep Medicine, Albert Einstein College of Medicine, Bronx, New York
| | - Graeme I. Bell
- Section of Adult and Pediatric Endocrinology, Diabetes, and Metabolism, The University of Chicago, Chicago, Illinois
| | - Jennifer E. Below
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas
| | - Andrew C. Bjonnes
- Division of Genetics, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Sung Chun
- Division of Genetics, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Medical Sciences, Harvard Medical School, Boston, Massachusetts
| | - Matthew P. Conomos
- Department of Biostatistics, University of Washington, Seattle, Washington
| | - Daniel S. Evans
- California Pacific Medical Center Research Institute, San Francisco, California
| | - W. Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, Washington
| | | | - Jacqueline M. Lane
- Division of Sleep and Circadian Disorders and
- Division of Sleep Medicine and
- Center for Human Genetic Research and Department of Anesthesia, Pain, and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
| | - Emma K. Larkin
- Department of Medicine, Division of Allergy, Pulmonary and Critical Care, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Jose S. Loredo
- Division of Pulmonary Critical Care and Sleep Medicine, Department of Medicine, UC San Diego School of Medicine, La Jolla, California
| | - Wendy S. Post
- Division of Cardiology, Johns Hopkins University, Baltimore, Maryland
| | - Alberto R. Ramos
- Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida
| | - Ken Rice
- Department of Biostatistics, University of Washington, Seattle, Washington
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, California
| | - Neomi A. Shah
- Department of Medicine, Montefiore Medical Center, Bronx, New York
| | - Katie L. Stone
- California Pacific Medical Center Research Institute, San Francisco, California
| | - Kent D. Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, California
| | | | - Gregory J. Tranah
- California Pacific Medical Center Research Institute, San Francisco, California
| | - Chaolong Wang
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
- Genome Institute of Singapore, Singapore
| | - Phyllis C. Zee
- Department of Neurology and Sleep Medicine Center, Northwestern University, Chicago, Illinois
| | - Craig L. Hanis
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas
| | - Shamil R. Sunyaev
- Division of Genetics, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Medical Sciences, Harvard Medical School, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
| | - Sanjay R. Patel
- Division of Sleep and Circadian Disorders and
- Division of Sleep Medicine and
- Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts; and
| | - Cathy C. Laurie
- Department of Biostatistics, University of Washington, Seattle, Washington
| | - Xiaofeng Zhu
- Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Cleveland, Ohio
| | - Richa Saxena
- Division of Sleep and Circadian Disorders and
- Center for Human Genetic Research and Department of Anesthesia, Pain, and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
| | - Xihong Lin
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Susan Redline
- Division of Sleep and Circadian Disorders and
- Division of Sleep Medicine and
- Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts; and
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23
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Del Gobbo LC, Imamura F, Aslibekyan S, Marklund M, Virtanen JK, Wennberg M, Yakoob MY, Chiuve SE, Dela Cruz L, Frazier-Wood AC, Fretts AM, Guallar E, Matsumoto C, Prem K, Tanaka T, Wu JHY, Zhou X, Helmer C, Ingelsson E, Yuan JM, Barberger-Gateau P, Campos H, Chaves PHM, Djoussé L, Giles GG, Gómez-Aracena J, Hodge AM, Hu FB, Jansson JH, Johansson I, Khaw KT, Koh WP, Lemaitre RN, Lind L, Luben RN, Rimm EB, Risérus U, Samieri C, Franks PW, Siscovick DS, Stampfer M, Steffen LM, Steffen BT, Tsai MY, van Dam RM, Voutilainen S, Willett WC, Woodward M, Mozaffarian D. ω-3 Polyunsaturated Fatty Acid Biomarkers and Coronary Heart Disease: Pooling Project of 19 Cohort Studies. JAMA Intern Med 2016; 176:1155-66. [PMID: 27357102 PMCID: PMC5183535 DOI: 10.1001/jamainternmed.2016.2925] [Citation(s) in RCA: 269] [Impact Index Per Article: 33.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
IMPORTANCE The role of ω-3 polyunsaturated fatty acids for primary prevention of coronary heart disease (CHD) remains controversial. Most prior longitudinal studies evaluated self-reported consumption rather than biomarkers. OBJECTIVE To evaluate biomarkers of seafood-derived eicosapentaenoic acid (EPA; 20:5ω-3), docosapentaenoic acid (DPA; 22:5ω-3), and docosahexaenoic acid (DHA; 22:6ω-3) and plant-derived α-linolenic acid (ALA; 18:3ω-3) for incident CHD. DATA SOURCES A global consortium of 19 studies identified by November 2014. STUDY SELECTION Available prospective (cohort, nested case-control) or retrospective studies with circulating or tissue ω-3 biomarkers and ascertained CHD. DATA EXTRACTION AND SYNTHESIS Each study conducted standardized, individual-level analysis using harmonized models, exposures, outcomes, and covariates. Findings were centrally pooled using random-effects meta-analysis. Heterogeneity was examined by age, sex, race, diabetes, statins, aspirin, ω-6 levels, and FADS desaturase genes. MAIN OUTCOMES AND MEASURES Incident total CHD, fatal CHD, and nonfatal myocardial infarction (MI). RESULTS The 19 studies comprised 16 countries, 45 637 unique individuals, and 7973 total CHD, 2781 fatal CHD, and 7157 nonfatal MI events, with ω-3 measures in total plasma, phospholipids, cholesterol esters, and adipose tissue. Median age at baseline was 59 years (range, 18-97 years), and 28 660 (62.8%) were male. In continuous (per 1-SD increase) multivariable-adjusted analyses, the ω-3 biomarkers ALA, DPA, and DHA were associated with a lower risk of fatal CHD, with relative risks (RRs) of 0.91 (95% CI, 0.84-0.98) for ALA, 0.90 (95% CI, 0.85-0.96) for DPA, and 0.90 (95% CI, 0.84-0.96) for DHA. Although DPA was associated with a lower risk of total CHD (RR, 0.94; 95% CI, 0.90-0.99), ALA (RR, 1.00; 95% CI, 0.95-1.05), EPA (RR, 0.94; 95% CI, 0.87-1.02), and DHA (RR, 0.95; 95% CI, 0.91-1.00) were not. Significant associations with nonfatal MI were not evident. Associations appeared generally stronger in phospholipids and total plasma. Restricted cubic splines did not identify evidence of nonlinearity in dose responses. CONCLUSIONS AND RELEVANCE On the basis of available studies of free-living populations globally, biomarker concentrations of seafood and plant-derived ω-3 fatty acids are associated with a modestly lower incidence of fatal CHD.
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Affiliation(s)
- Liana C Del Gobbo
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California
| | - Fumiaki Imamura
- Medical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge University, Cambridge, United Kingdom
| | - Stella Aslibekyan
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham
| | - Matti Marklund
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Jyrki K Virtanen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Joensuu, Finland
| | - Maria Wennberg
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Mohammad Y Yakoob
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California
| | - Stephanie E Chiuve
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts8Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Luicito Dela Cruz
- Cancer Epidemiology Centre, Cancer Council Victoria, Victoria, Australia
| | - Alexis C Frazier-Wood
- USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas
| | - Amanda M Fretts
- Department of Epidemiology, University of Washington, Seattle
| | - Eliseo Guallar
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Chisa Matsumoto
- Division of Cardiology, Tokyo Medical University, Tokyo, Japan14Division of Aging, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Kiesha Prem
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Tosh Tanaka
- Translational Gerontology Branch, National Institute on Aging, Bethesda, Maryland
| | - Jason H Y Wu
- The George Institute for Global Health, Sydney Medical School, University of Sydney, Sydney, Australia
| | - Xia Zhou
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis
| | - Catherine Helmer
- Institut National de la Santé et de la Recherche Médicale, Institut de Santé Publique, d'Épidémiologie et de Développement, Centre IInstitut National de la Santé et de la Recherche Médicale U897-Epidemiologie-Biostatistique, Bordeaux, France20University B
| | - Erik Ingelsson
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California21Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania23Department of Epidemiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania
| | - Pascale Barberger-Gateau
- Institut National de la Santé et de la Recherche Médicale, Institut de Santé Publique, d'Épidémiologie et de Développement, Centre IInstitut National de la Santé et de la Recherche Médicale U897-Epidemiologie-Biostatistique, Bordeaux, France20University B
| | - Hannia Campos
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Paulo H M Chaves
- Benjamin Leon Center for Geriatric Research and Education, Florida International University, Miami
| | - Luc Djoussé
- Division of Aging, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Graham G Giles
- Cancer Epidemiology Centre, Cancer Council Victoria, Victoria, Australia
| | | | - Allison M Hodge
- Cancer Epidemiology Centre, Cancer Council Victoria, Victoria, Australia
| | - Frank B Hu
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts24Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts27Channing Division of Network Medicine, Department of Medicine, Brigh
| | - Jan-Håkan Jansson
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | | | - Kay-Tee Khaw
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Woon-Puay Koh
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore30Duke-NUS Graduate Medical School Singapore, Singapore
| | - Rozenn N Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Robert N Luben
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Eric B Rimm
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts24Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts27Channing Division of Network Medicine, Department of Medicine, Brigh
| | - Ulf Risérus
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Cecilia Samieri
- Institut National de la Santé et de la Recherche Médicale, Institut de Santé Publique, d'Épidémiologie et de Développement, Centre IInstitut National de la Santé et de la Recherche Médicale U897-Epidemiologie-Biostatistique, Bordeaux, France20University B
| | - Paul W Franks
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden24Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts32Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund Un
| | | | - Meir Stampfer
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts24Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts27Channing Division of Network Medicine, Department of Medicine, Brigh
| | - Lyn M Steffen
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis
| | - Brian T Steffen
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore24Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts35Department of Medicine, Yong Loo Lin School of Medicine, National University of
| | - Sari Voutilainen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Joensuu, Finland
| | - Walter C Willett
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts24Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts27Channing Division of Network Medicine, Department of Medicine, Brigh
| | - Mark Woodward
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland17The George Institute for Global Health, Sydney Medical School, University of Sydney, Sydney, Australia36The George Institute for Global Health, Nuffield Depa
| | - Dariush Mozaffarian
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, Massachusetts
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Okbay A, Baselmans BML, Neve JED, Turley P, Nivard MG, Fontana MA, Meddens SFW, Linnér RK, Rietveld CA, Derringer J, Gratten J, Lee JJ, Liu JZ, de Vlaming R, Ahluwalia TS, Buchwald J, Cavadino A, Frazier-Wood AC, Furlotte NA, Garfield V, Geisel MH, Gonzalez JR, Haitjema S, Karlsson R, van der Laan SW, Ladwig KH, Lahti J, van der Lee SJ, Lind PA, Liu T, Matteson L, Mihailov E, Miller MB, Minica CC, Nolte IM, Mook-Kanamori D, van der Most PJ, Oldmeadow C, Qian Y, Raitakari O, Rawal R, Realo A, Rueedi R, Schmidt B, Smith AV, Stergiakouli E, Tanaka T, Taylor K, Thorleifsson G, Wedenoja J, Wellmann J, Westra HJ, Willems SM, Zhao W, Amin N, Bakshi A, Bergmann S, Bjornsdottir G, Boyle PA, Cherney S, Cox SR, Davies G, Davis OSP, Ding J, Direk N, Eibich P, Emeny RT, Fatemifar G, Faul JD, Ferrucci L, Forstner AJ, Gieger C, Gupta R, Harris TB, Harris JM, Holliday EG, Hottenga JJ, Jager PLD, Kaakinen MA, Kajantie E, Karhunen V, Kolcic I, Kumari M, Launer LJ, Franke L, Li-Gao R, Liewald DC, Koini M, Loukola A, Marques-Vidal P, Montgomery GW, Mosing MA, Paternoster L, Pattie A, Petrovic KE, Pulkki-Råback L, Quaye L, Räikkönen K, Rudan I, Scott RJ, Smith JA, Sutin AR, Trzaskowski M, Vinkhuyzen AE, Yu L, Zabaneh D, Attia JR, Bennett DA, Berger K, Bertram L, Boomsma DI, Snieder H, Chang SC, Cucca F, Deary IJ, van Duijn CM, Eriksson JG, Bültmann U, de Geus EJC, Groenen PJF, Gudnason V, Hansen T, Hartman CA, Haworth CMA, Hayward C, Heath AC, Hinds DA, Hyppönen E, Iacono WG, Järvelin MR, Jöckel KH, Kaprio J, Kardia SLR, Keltikangas-Järvinen L, Kraft P, Kubzansky LD, Lehtimäki T, Magnusson PKE, Martin NG, McGue M, Metspalu A, Mills M, de Mutsert R, Oldehinkel AJ, Pasterkamp G, Pedersen NL, Plomin R, Polasek O, Power C, Rich SS, Rosendaal FR, den Ruijter HM, Schlessinger D, Schmidt H, Svento R, Schmidt R, Alizadeh BZ, Sørensen TIA, Spector TD, Starr JM, Stefansson K, Steptoe A, Terracciano A, Thorsteinsdottir U, Thurik AR, Timpson NJ, Tiemeier H, Uitterlinden AG, Vollenweider P, Wagner GG, Weir DR, Yang J, Conley DC, Smith GD, Hofman A, Johannesson M, Laibson DI, Medland SE, Meyer MN, Pickrell JK, Esko T, Krueger RF, Beauchamp JP, Koellinger PD, Benjamin DJ, Bartels M, Cesarini D. Corrigendum: Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nat Genet 2016; 48:970. [PMID: 27463399 DOI: 10.1038/ng0816-970c] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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25
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Okbay A, Baselmans BML, De Neve JE, Turley P, Nivard MG, Fontana MA, Meddens SFW, Linnér RK, Rietveld CA, Derringer J, Gratten J, Lee JJ, Liu JZ, de Vlaming R, Ahluwalia TS, Buchwald J, Cavadino A, Frazier-Wood AC, Furlotte NA, Garfield V, Geisel MH, Gonzalez JR, Haitjema S, Karlsson R, van der Laan SW, Ladwig KH, Lahti J, van der Lee SJ, Lind PA, Liu T, Matteson L, Mihailov E, Miller MB, Minica CC, Nolte IM, Mook-Kanamori D, van der Most PJ, Oldmeadow C, Qian Y, Raitakari O, Rawal R, Realo A, Rueedi R, Schmidt B, Smith AV, Stergiakouli E, Tanaka T, Taylor K, Thorleifsson G, Wedenoja J, Wellmann J, Westra HJ, Willems SM, Zhao W, Amin N, Bakshi A, Bergmann S, Bjornsdottir G, Boyle PA, Cherney S, Cox SR, Davies G, Davis OSP, Ding J, Direk N, Eibich P, Emeny RT, Fatemifar G, Faul JD, Ferrucci L, Forstner AJ, Gieger C, Gupta R, Harris TB, Harris JM, Holliday EG, Hottenga JJ, De Jager PL, Kaakinen MA, Kajantie E, Karhunen V, Kolcic I, Kumari M, Launer LJ, Franke L, Li-Gao R, Liewald DC, Koini M, Loukola A, Marques-Vidal P, Montgomery GW, Mosing MA, Paternoster L, Pattie A, Petrovic KE, Pulkki-Råback L, Quaye L, Räikkönen K, Rudan I, Scott RJ, Smith JA, Sutin AR, Trzaskowski M, Vinkhuyzen AE, Yu L, Zabaneh D, Attia JR, Bennett DA, Berger K, Bertram L, Boomsma DI, Snieder H, Chang SC, Cucca F, Deary IJ, van Duijn CM, Eriksson JG, Bültmann U, de Geus EJC, Groenen PJF, Gudnason V, Hansen T, Hartman CA, Haworth CMA, Hayward C, Heath AC, Hinds DA, Hyppönen E, Iacono WG, Järvelin MR, Jöckel KH, Kaprio J, Kardia SLR, Keltikangas-Järvinen L, Kraft P, Kubzansky LD, Lehtimäki T, Magnusson PKE, Martin NG, McGue M, Metspalu A, Mills M, de Mutsert R, Oldehinkel AJ, Pasterkamp G, Pedersen NL, Plomin R, Polasek O, Power C, Rich SS, Rosendaal FR, den Ruijter HM, Schlessinger D, Schmidt H, Svento R, Schmidt R, Alizadeh BZ, Sørensen TIA, Spector TD, Starr JM, Stefansson K, Steptoe A, Terracciano A, Thorsteinsdottir U, Thurik AR, Timpson NJ, Tiemeier H, Uitterlinden AG, Vollenweider P, Wagner GG, Weir DR, Yang J, Conley DC, Smith GD, Hofman A, Johannesson M, Laibson DI, Medland SE, Meyer MN, Pickrell JK, Esko T, Krueger RF, Beauchamp JP, Koellinger PD, Benjamin DJ, Bartels M, Cesarini D. Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nat Genet 2016; 48:624-33. [PMID: 27089181 PMCID: PMC4884152 DOI: 10.1038/ng.3552] [Citation(s) in RCA: 561] [Impact Index Per Article: 70.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2015] [Accepted: 03/24/2016] [Indexed: 12/15/2022]
Abstract
Very few genetic variants have been associated with depression and neuroticism, likely because of limitations on sample size in previous studies. Subjective well-being, a phenotype that is genetically correlated with both of these traits, has not yet been studied with genome-wide data. We conducted genome-wide association studies of three phenotypes: subjective well-being (n = 298,420), depressive symptoms (n = 161,460), and neuroticism (n = 170,911). We identify 3 variants associated with subjective well-being, 2 variants associated with depressive symptoms, and 11 variants associated with neuroticism, including 2 inversion polymorphisms. The two loci associated with depressive symptoms replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ^| ≈ 0.8) strengthen the overall credibility of the findings and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal or pancreas tissues are strongly enriched for association.
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Affiliation(s)
- Aysu Okbay
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, the Netherlands
| | - Bart M L Baselmans
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- EMGO+ Institute for Health and Care Research, Amsterdam, the Netherlands
| | | | - Patrick Turley
- Department of Economics, Harvard University, Cambridge, Massachusetts, USA
| | - Michel G Nivard
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
| | - Mark Alan Fontana
- Center for Economic and Social Research, University of Southern California, Los Angeles, California, USA
| | - S Fleur W Meddens
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, the Netherlands
- Department of Complex Trait Genetics, Vrije Universiteit, Center for Neurogenomics and Cognitive Research, Amsterdam, the Netherlands
- Amsterdam Business School, University of Amsterdam, Amsterdam, the Netherlands
| | - Richard Karlsson Linnér
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, the Netherlands
- Department of Complex Trait Genetics, Vrije Universiteit, Center for Neurogenomics and Cognitive Research, Amsterdam, the Netherlands
- Amsterdam Business School, University of Amsterdam, Amsterdam, the Netherlands
| | - Cornelius A Rietveld
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, the Netherlands
| | - Jaime Derringer
- Department of Psychology, University of Illinois, Champaign, Illinois, USA
| | - Jacob Gratten
- Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia
| | - James J Lee
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA
| | - Jimmy Z Liu
- New York Genome Center, New York, New York, USA
| | - Ronald de Vlaming
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, the Netherlands
| | - Tarunveer S Ahluwalia
- COPSAC (Copenhagen Prospective Studies on Asthma in Childhood), Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, Faculty of Health and Medical Sciences, Copenhagen, Denmark
- Steno Diabetes Center, Gentofte, Denmark
| | - Jadwiga Buchwald
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Alana Cavadino
- Centre for Environmental and Preventive Medicine, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - Alexis C Frazier-Wood
- USDA-ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA
| | | | - Victoria Garfield
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Marie Henrike Geisel
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, Essen, Germany
| | - Juan R Gonzalez
- Centre for Research in Environmental Epidemiology, Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Barcelona, Spain
| | - Saskia Haitjema
- Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sander W van der Laan
- Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Karl-Heinz Ladwig
- Department of Psychosomatic Medicine and Psychotherapy, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany
| | - Jari Lahti
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
- Folkhälsan Research Centre, Helsingfors, Finland
- Helsinki Collegium for Advanced Studies, University of Helsinki, Helsinki, Finland
| | - Sven J van der Lee
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Penelope A Lind
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Tian Liu
- Max Planck Institute for Human Development, Berlin, Germany
- Max Planck Institute for Molecular Genetics, Department of Vertebrate Genomics, Berlin, Germany
| | - Lindsay Matteson
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA
| | | | - Michael B Miller
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA
| | - Camelia C Minica
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Dennis Mook-Kanamori
- Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
- Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
- BESC, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Christopher Oldmeadow
- Public Health Stream, Hunter Medical Research Institute, New Lambton, New South Wales, Australia
- Faculty of Health and Medicine, University of Newcastle, Newcastle, New South Wales, Australia
| | - Yong Qian
- Laboratory of Genetics, National Institute on Aging, Baltimore, Maryland, USA
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology, Turku University Hospital, Turku, Finland
| | - Rajesh Rawal
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Anu Realo
- Department of Psychology, University of Tartu, Tartu, Estonia
- Department of Psychology, University of Warwick, Coventry, UK
| | - Rico Rueedi
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, Essen, Germany
| | - Albert V Smith
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Evie Stergiakouli
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Toshiko Tanaka
- National Institute on Aging, US National Institutes of Health, Baltimore, Maryland, USA
| | - Kent Taylor
- Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA, Torrence, California, USA
| | | | - Juho Wedenoja
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Juergen Wellmann
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Harm-Jan Westra
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Division of Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Sara M Willems
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Najaf Amin
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Andrew Bakshi
- Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia
| | | | | | - Patricia A Boyle
- Department of Behavioral Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | | | - Simon R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Gail Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Oliver S P Davis
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Jun Ding
- Laboratory of Genetics, National Institute on Aging, Baltimore, Maryland, USA
| | - Nese Direk
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Peter Eibich
- German Socio-Economic Panel Study, DIW Berlin, Berlin, Germany
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Rebecca T Emeny
- Institute of Epidemiology II, Mental Health Research Unit, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire, USA
| | - Ghazaleh Fatemifar
- Farr Institute of Health Informatics, University College London, London, UK
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, USA
| | - Luigi Ferrucci
- National Institute on Aging, US National Institutes of Health, Baltimore, Maryland, USA
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Richa Gupta
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Tamara B Harris
- Laboratory of Epidemiology, Demography, National Institute on Aging, US National Institutes of Health, Bethesda, Maryland, USA
| | - Juliette M Harris
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Elizabeth G Holliday
- Public Health Stream, Hunter Medical Research Institute, New Lambton, New South Wales, Australia
- Faculty of Health and Medicine, University of Newcastle, Newcastle, New South Wales, Australia
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- EMGO+ Institute for Health and Care Research, Amsterdam, the Netherlands
| | - Philip L De Jager
- Program in Translational NeuroPsychiatric Genomics, Departments of Neurology and Psychiatry, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Marika A Kaakinen
- Department of Genomics of Common Disease, Imperial College London, London, UK
- Center for Life Course Health Research, University of Oulu and Oulu University Hospital, Oulu, Finland
| | - Eero Kajantie
- Department of Pediatrics, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
| | - Ville Karhunen
- Center for Life Course Health Research, University of Oulu and Oulu University Hospital, Oulu, Finland
| | - Ivana Kolcic
- Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia
| | - Meena Kumari
- Institute for Social and Economic Research, University of Essex, Wivenhoe Park, UK
| | - Lenore J Launer
- Neuroepidemiology Section, National Institute on Aging, US National Institutes of Health, Bethesda, Maryland, USA
| | - Lude Franke
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Ruifang Li-Gao
- Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | | | - Marisa Koini
- Department of Neurology, General Hospital and Medical University Graz, Graz, Austria
| | - Anu Loukola
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Pedro Marques-Vidal
- Department of Internal Medicine, Internal Medicine, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Grant W Montgomery
- Molecular Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Miriam A Mosing
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | | | - Alison Pattie
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Katja E Petrovic
- Department of Neurology, General Hospital and Medical University Graz, Graz, Austria
| | - Laura Pulkki-Råback
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
- Helsinki Collegium for Advanced Studies, University of Helsinki, Helsinki, Finland
| | - Lydia Quaye
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Katri Räikkönen
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Rodney J Scott
- Faculty of Health and Medicine, University of Newcastle, Newcastle, New South Wales, Australia
- Information-Based Medicine Stream, Hunter Medical Research Institute, New Lambton, New South Wales, Australia
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Angelina R Sutin
- National Institute on Aging, US National Institutes of Health, Baltimore, Maryland, USA
- Department of Behavioral Sciences and Social Medicine, Florida State University College of Medicine, Tallahassee, Florida, USA
| | - Maciej Trzaskowski
- Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia
- Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia
| | - Anna E Vinkhuyzen
- Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Lei Yu
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Delilah Zabaneh
- Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia
| | - John R Attia
- Public Health Stream, Hunter Medical Research Institute, New Lambton, New South Wales, Australia
- Faculty of Health and Medicine, University of Newcastle, Newcastle, New South Wales, Australia
| | - David A Bennett
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institute of Neurogenetics and Institute of Integrative and Experimental Genomics, University of Lübeck, Lübeck, Germany
- Neuroepidemiology and Ageing Research Unit, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- EMGO+ Institute for Health and Care Research, Amsterdam, the Netherlands
- Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Shun-Chiao Chang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche, Cittadella Universitarià di Monserrato, Monserrato, Italy
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | | | - Johan G Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
- Unit of General Practice, University Central Hospital, Helsinki, Finland
| | - Ute Bültmann
- Department of Health Sciences, Community and Occupational Medicine, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- EMGO+ Institute for Health and Care Research, Amsterdam, the Netherlands
- Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Patrick J F Groenen
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, the Netherlands
- Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, Faculty of Health and Medical Sciences, Copenhagen, Denmark
| | - Catharine A Hartman
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | | | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Andrew C Heath
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
| | | | - Elina Hyppönen
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
- Centre for Population Health Research, School of Health Sciences and Sansom Institute, University of South Australia, Adelaide, South Australia, Australia
- Population, Policy and Practice, UCL Institute of Child Health, London, UK
| | - William G Iacono
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA
| | - Marjo-Riitta Järvelin
- Department of Genomics of Common Disease, Imperial College London, London, UK
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - Karl-Heinz Jöckel
- Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, Essen, Germany
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department for Health, THL (National Institute for Health and Welfare), Helsinki, Finland
| | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA
| | | | - Peter Kraft
- Department of Epidemiology and Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Laura D Kubzansky
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Terho Lehtimäki
- Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, University of Tampere, School of Medicine, Tampere, Finland
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nicholas G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Matt McGue
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Melinda Mills
- Department of Sociology, University of Oxford, Oxford, UK
| | - Renée de Mutsert
- Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Albertine J Oldehinkel
- Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
| | - Gerard Pasterkamp
- Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht, the Netherlands
- Laboratory of Clinical Chemistry and Hematology, Division of Laboratories and Pharmacy, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Robert Plomin
- Social, Genetic and Developmental Psychiatry Centre, King's College London, De Crespigny Park, UK
| | - Ozren Polasek
- Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia
| | - Christine Power
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
- Population, Policy and Practice, UCL Institute of Child Health, London, UK
| | - Stephen S Rich
- Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, USA
| | - Frits R Rosendaal
- Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Hester M den Ruijter
- Laboratory of Experimental Cardiology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - David Schlessinger
- Laboratory of Genetics, National Institute on Aging, Baltimore, Maryland, USA
| | - Helena Schmidt
- Department of Neurology, General Hospital and Medical University Graz, Graz, Austria
- Research Unit for Genetic Epidemiology, Institute of Molecular Biology and Biochemistry, Center of Molecular Medicine, General Hospital and Medical University Graz, Graz, Austria
| | - Rauli Svento
- Department of Economics, Oulu Business School, Oulu, Finland
| | - Reinhold Schmidt
- Department of Neurology, General Hospital and Medical University Graz, Graz, Austria
| | - Behrooz Z Alizadeh
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Gastroenterology and Hepatology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, Faculty of Health and Medical Sciences, Copenhagen, Denmark
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Institute of Preventive Medicine, Bispebjerg and Frederiksberg Hospitals, Capital Region, Frederiksberg, Denmark
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | | | | | - Andrew Steptoe
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Antonio Terracciano
- National Institute on Aging, US National Institutes of Health, Baltimore, Maryland, USA
- Department of Behavioral Sciences and Social Medicine, Florida State University College of Medicine, Tallahassee, Florida, USA
| | | | - A Roy Thurik
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, the Netherlands
- Montpellier Business School, Montpellier, France
- Panteia, Zoetermeer, the Netherlands
| | | | - Henning Tiemeier
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Psychiatry, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Child and Adolescent Psychiatry, Erasmus Medical Center, Rotterdam, the Netherlands
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Peter Vollenweider
- Department of Internal Medicine, Internal Medicine, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Gert G Wagner
- Max Planck Institute for Human Development, Berlin, Germany
- German Socio-Economic Panel Study, DIW Berlin, Berlin, Germany
- School of Economics and Management, Berlin University of Technology, Berlin, Germany
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, USA
| | - Jian Yang
- Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia
- University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia
| | - Dalton C Conley
- Department of Sociology, Princeton University, Princeton, New Jersey, USA
| | | | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Magnus Johannesson
- Department of Economics, Stockholm School of Economics, Stockholm, Sweden
| | - David I Laibson
- Department of Economics, Harvard University, Cambridge, Massachusetts, USA
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Michelle N Meyer
- Department of Bioethics, Clarkson University, Schenectady, New York, USA
- Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Joseph K Pickrell
- New York Genome Center, New York, New York, USA
- Department of Biological Sciences, Columbia University, New York, New York, USA
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Robert F Krueger
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, Minnesota, USA
| | | | - Philipp D Koellinger
- Erasmus University Rotterdam Institute for Behavior and Biology, Rotterdam, the Netherlands
- Department of Complex Trait Genetics, Vrije Universiteit, Center for Neurogenomics and Cognitive Research, Amsterdam, the Netherlands
- Amsterdam Business School, University of Amsterdam, Amsterdam, the Netherlands
| | - Daniel J Benjamin
- Center for Economic and Social Research, University of Southern California, Los Angeles, California, USA
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- EMGO+ Institute for Health and Care Research, Amsterdam, the Netherlands
- Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - David Cesarini
- Department of Economics, New York University, New York, New York, USA
- Research Institute for Industrial Economics, Stockholm, Sweden
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Shah RV, Murthy VL, Allison MA, Ding J, Budoff M, Frazier-Wood AC, Lima JAC, Steffen L, Siscovick D, Tucker KL, Ouyang P, Abbasi SA, Danielson K, Jerosch-Herold M, Mozaffarian D. Diet and adipose tissue distributions: The Multi-Ethnic Study of Atherosclerosis. Nutr Metab Cardiovasc Dis 2016; 26:185-193. [PMID: 26899879 PMCID: PMC4788543 DOI: 10.1016/j.numecd.2015.12.012] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Revised: 12/12/2015] [Accepted: 12/21/2015] [Indexed: 02/03/2023]
Abstract
BACKGROUND AND AIMS Dietary quality affects cardiometabolic risk, yet its pathways of influence on regional adipose tissue depots involved in metabolic and diabetes risk are not well established. We aimed to investigate the relationship between dietary quality and regional adiposity. METHODS AND RESULTS We investigated 5079 individuals in the Multi-Ethnic Study of Atherosclerosis (MESA) who had food-frequency questionnaires and measurement of pericardial fat and hepatic attenuation at the baseline study visit in MESA, as well as a subgroup with imaging for visceral and subcutaneous fat (N = 1390). A dietary quality score (DietQuality) was constructed to include established food group constituents of a Mediterranean-type diet. Linear models estimated associations of dietary score as well as its constituents with regional adiposity. Baseline mean age was 61 (± 10) years, and approximately half of the participants (47%) were male. Those with a higher DietQuality score were generally older, female, with a lower body mass index, C-reactive protein, and markers of insulin resistance. After adjustment, a higher DietQuality score was associated with lower visceral fat (lowest vs. highest dietary score quartile: 523.6 vs. 460.5 cm(2)/m; P < 0.01 for trend), pericardial fat (47.5 vs. 41.3 cm(3)/m; P < 0.01 for trend), lesser hepatic steatosis (by hepatic attenuation; 58.6 vs. 60.7 Hounsfield units; P < 0.01 for trend), but not subcutaneous fat (P = 0.39). Greater fruits, vegetables, whole grains, seeds/nuts and yogurt intake were associated with decreased adiposity, while red/processed meats were associated with greater regional adiposity. CONCLUSION A higher quality diet pattern is associated with less regional adiposity, suggesting a potential mechanism of beneficial dietary effects on diabetes, metabolic, and cardiovascular risk.
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Affiliation(s)
- R V Shah
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, 330 Brookline Ave., Boston, MA 02215, USA.
| | - V L Murthy
- Department of Medicine (Cardiovascular Medicine Division), University of Michigan, Ann Arbor, MI, USA; Department of Radiology (Nuclear Medicine Division), University of Michigan, Ann Arbor, MI, USA.
| | - M A Allison
- Department of Family and Preventive Medicine, University of California, San Diego, La Jolla, CA, USA
| | - J Ding
- Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - M Budoff
- Department of Cardiology and Medicine, University of California - Los Angeles, Los Angeles, CA, USA
| | - A C Frazier-Wood
- USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA
| | - J A C Lima
- Department of Medicine, Division of Cardiology, Johns Hopkins University, Baltimore, MD, USA
| | - L Steffen
- University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - D Siscovick
- University of Washington School of Public Health, Seattle, WA, USA
| | - K L Tucker
- University of Massachusetts at Lowell School of Public Health, Lowell, MA, USA
| | - P Ouyang
- Department of Medicine, Division of Cardiology, Johns Hopkins University, Baltimore, MD, USA
| | - S A Abbasi
- Department of Cardiology, Brown University, Providence, RI, USA
| | - K Danielson
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center, 330 Brookline Ave., Boston, MA 02215, USA
| | - M Jerosch-Herold
- Noninvasive Cardiovascular Imaging Section, Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA
| | - D Mozaffarian
- Tufts University School of Public Health, Boston, MA, USA.
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27
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Abstract
Child eating self-regulation refers to behaviors that enable children to start and stop eating in a manner consistent with maintaining energy balance. Perturbations in these behaviors, manifesting as poorer child eating self-regulation, are associated with higher child weight status. Initial research into child eating self-regulation focused on the role of parent feeding styles and behaviors. However, we argue that child eating self-regulation is better understood as arising from a complex interplay between the child and their feeding environment, and highlight newer research into the heritable child characteristics, such as cognitive ability, that play an important role in this dynamic. Therefore, child eating self-regulation arises from gene-environment interactions. Identifying the genes and environmental influences contributing to these will help us tailor our parental feeding advice to the unique nature of the child. In this way, we will devise more effective advice for preventing childhood obesity.
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Affiliation(s)
- Sheryl O Hughes
- USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, 1100 Bates Street, Houston, TX, 77030, USA
| | - Alexis C Frazier-Wood
- USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, 1100 Bates Street, Houston, TX, 77030, USA.
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28
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Fretts AM, Follis JL, Nettleton JA, Lemaitre RN, Ngwa JS, Wojczynski MK, Kalafati IP, Varga TV, Frazier-Wood AC, Houston DK, Lahti J, Ericson U, van den Hooven EH, Mikkilä V, Kiefte-de Jong JC, Mozaffarian D, Rice K, Renström F, North KE, McKeown NM, Feitosa MF, Kanoni S, Smith CE, Garcia ME, Tiainen AM, Sonestedt E, Manichaikul A, van Rooij FJA, Dimitriou M, Raitakari O, Pankow JS, Djoussé L, Province MA, Hu FB, Lai CQ, Keller MF, Perälä MM, Rotter JI, Hofman A, Graff M, Kähönen M, Mukamal K, Johansson I, Ordovas JM, Liu Y, Männistö S, Uitterlinden AG, Deloukas P, Seppälä I, Psaty BM, Cupples LA, Borecki IB, Franks PW, Arnett DK, Nalls MA, Eriksson JG, Orho-Melander M, Franco OH, Lehtimäki T, Dedoussis GV, Meigs JB, Siscovick DS. Consumption of meat is associated with higher fasting glucose and insulin concentrations regardless of glucose and insulin genetic risk scores: a meta-analysis of 50,345 Caucasians. Am J Clin Nutr 2015; 102:1266-78. [PMID: 26354543 PMCID: PMC4625584 DOI: 10.3945/ajcn.114.101238] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2014] [Accepted: 08/05/2015] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND Recent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown. OBJECTIVE We investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus. DESIGN Fourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations. RESULTS Processed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance. CONCLUSION The association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).
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Affiliation(s)
- Amanda M Fretts
- Departments of Epidemiology, Cardiovascular Health Research Unit, University of Washington, Seattle, WA;
| | - Jack L Follis
- Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX
| | - Jennifer A Nettleton
- Division of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Sciences Center, Houston, TX
| | - Rozenn N Lemaitre
- Medicine, Cardiovascular Health Research Unit, University of Washington, Seattle, WA
| | - Julius S Ngwa
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Mary K Wojczynski
- Department of Genetics, Division of Statistical Genomics, School of Medicine, Washington University, St. Louis, MO
| | | | - Tibor V Varga
- Department of Clinical Sciences Genetic and Molecular Epidemiology Unit and
| | - Alexis C Frazier-Wood
- USDA/Agricultural Research Service Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX
| | | | | | - Ulrika Ericson
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | | | - Vera Mikkilä
- Department of Food and Environmental Sciences, and Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | | | | | - Kenneth Rice
- Biostatistics, and Cardiovascular Health Research Unit, University of Washington, Seattle, WA
| | - Frida Renström
- Department of Clinical Sciences Genetic and Molecular Epidemiology Unit and Department of Biobank Research
| | - Kari E North
- Department of Epidemiology, Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC
| | - Nicola M McKeown
- Nutritional Epidemiology Program, Jean Mayer-USDA Human Nutrition Research Center on Aging, and
| | - Mary F Feitosa
- Department of Genetics, Division of Statistical Genomics, School of Medicine, Washington University, St. Louis, MO
| | - Stavroula Kanoni
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Caren E Smith
- Nutrition and Genomics Laboratory, Tufts University, Boston, MA
| | | | - Anna-Maija Tiainen
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Emily Sonestedt
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Ani Manichaikul
- Center for Public Health Genomics, Department of Public Health Sciences, Division of Biostatistics and Epidemiology, University of Virginia, Charlottesville, VA
| | - Frank J A van Rooij
- Department of Epidemiology and Netherlands Genomics Initiative, Leiden, Netherlands
| | - Maria Dimitriou
- Department of Nutrition and Dietetics, Harokopio University of Athens, Athens, Greece
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland; Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - James S Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN
| | - Luc Djoussé
- Department of Medicine Brigham and Women's Hospital, Harvard Medical School, Boston MA and
| | - Michael A Province
- Department of Genetics, Division of Statistical Genomics, School of Medicine, Washington University, St. Louis, MO
| | - Frank B Hu
- Department of Epidemiology and Department of Nutrition, Harvard School of Public Health, Boston, MA
| | - Chao-Qiang Lai
- Jean Mayer-USDA Human Nutrition Research Center on Aging, and Nutrition and Genomics Laboratory, Tufts University, Boston, MA
| | - Margaux F Keller
- Laboratory of Neurogenetics, National Institute of Aging, Bethesda, MD; Department of Clinical Physiology
| | - Mia-Maria Perälä
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA
| | | | | | - Mika Kähönen
- School of Medicine, and Tampere University Hospital, University of Tampere, Tampere, Finland
| | - Kenneth Mukamal
- Division of General Medicine and Primary Care, Beth Israel Deaconess Medical Center, Boston, MA
| | | | - Jose M Ordovas
- Jean Mayer-USDA Human Nutrition Research Center on Aging, and Nutrition and Genomics Laboratory, Tufts University, Boston, MA; Department of Epidemiology and Population Genetics, Cardiovascular Research Center, Madrid, Spain; IMDEA Food Institute, Madrid, Spain
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Satu Männistö
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - André G Uitterlinden
- Department of Epidemiology and Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Panos Deloukas
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom; Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Fimlab Laboratories, School of Medicine, and
| | - Bruce M Psaty
- Departments of Epidemiology, Medicine, Health Services and Cardiovascular Health Research Unit, University of Washington, Seattle, WA; Group Health Research Institute, Group Health Cooperative, Seattle, WA
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA; Framingham Heart Study, Framingham, MA
| | - Ingrid B Borecki
- Department of Genetics, Division of Statistical Genomics, School of Medicine, Washington University, St. Louis, MO
| | - Paul W Franks
- Department of Clinical Sciences Genetic and Molecular Epidemiology Unit and Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden; Department of Nutrition, Harvard School of Public Health, Boston, MA
| | - Donna K Arnett
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute of Aging, Bethesda, MD
| | - Johan G Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland; Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland; General Practice Unit, Helsinki University Central Hospital, Helsinki, Finland; Folkhälsan Research Center, Helsinki, Finland
| | | | | | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, School of Medicine, and
| | - George V Dedoussis
- Department of Nutrition and Dietetics, Harokopio University of Athens, Athens, Greece
| | - James B Meigs
- Clinical Epidemiology Unit and Diabetes Research Unit, General Medicine Division, Massachusetts General Hospital, Boston, MA; and
| | - David S Siscovick
- Departments of Epidemiology, Medicine, Cardiovascular Health Research Unit, University of Washington, Seattle, WA; New York Academy of Medicine, New York, NY
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29
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Wojczynski MK, Parnell LD, Pollin TI, Lai CQ, Feitosa MF, O'Connell JR, Frazier-Wood AC, Gibson Q, Aslibekyan S, Ryan KA, Province MA, Tiwari HK, Ordovas JM, Shuldiner AR, Arnett DK, Borecki IB. Genome-wide association study of triglyceride response to a high-fat meal among participants of the NHLBI Genetics of Lipid Lowering Drugs and Diet Network (GOLDN). Metabolism 2015; 64:1359-71. [PMID: 26256467 PMCID: PMC4573277 DOI: 10.1016/j.metabol.2015.07.001] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2014] [Revised: 05/19/2015] [Accepted: 07/01/2015] [Indexed: 12/21/2022]
Abstract
OBJECTIVE The triglyceride (TG) response to a high-fat meal (postprandial lipemia, PPL) affects cardiovascular disease risk and is influenced by genes and environment. Genes involved in lipid metabolism have dominated genetic studies of PPL TG response. We sought to elucidate common genetic variants through a genome-wide association (GWA) study in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN). METHODS The GOLDN GWAS discovery sample consisted of 872 participants within families of European ancestry. Genotypes for 2,543,887 variants were measured or imputed from HapMap. Replication of our top results was performed in the Heredity and Phenotype Intervention (HAPI) Heart Study (n = 843). PPL TG response phenotypes were constructed from plasma TG measured at baseline (fasting, 0 hour), 3.5 and 6 hours after a high-fat meal, using a random coefficient regression model. Association analyses were adjusted for covariates and principal components, as necessary, in a linear mixed model using the kinship matrix; additional models further adjusted for fasting TG were also performed. Meta-analysis of the discovery and replication studies (n = 1715) was performed on the top SNPs from GOLDN. RESULTS GOLDN revealed 111 suggestive (p < 1E-05) associations, with two SNPs meeting GWA significance level (p < 5E-08). Of the two significant SNPs, rs964184 demonstrated evidence of replication (p = 1.20E-03) in the HAPI Heart Study and in a joint analysis, was GWA significant (p = 1.26E-09). Rs964184 has been associated with fasting lipids (TG and HDL) and is near ZPR1 (formerly ZNF259), close to the APOA1/C3/A4/A5 cluster. This association was attenuated upon additional adjustment for fasting TG. CONCLUSION This is the first report of a genome-wide significant association with replication for a novel phenotype, namely PPL TG response. Future investigation into response phenotypes is warranted using pathway analyses, or newer genetic technologies such as metabolomics.
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Affiliation(s)
- Mary K Wojczynski
- Department of Genetics, Washington University School of Medicine, St. Louis, MO.
| | - Laurence D Parnell
- Nutrition and Genomics Laboratory, Jean Mayer-US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA
| | - Toni I Pollin
- Program in Personalized and Genomic Medicine, and Departments of Medicine and Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD
| | - Chao Q Lai
- Nutrition and Genomics Laboratory, Jean Mayer-US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA
| | - Mary F Feitosa
- Department of Genetics, Washington University School of Medicine, St. Louis, MO
| | - Jeff R O'Connell
- Program in Personalized and Genomic Medicine, and Departments of Medicine and Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD
| | | | - Quince Gibson
- Program in Personalized and Genomic Medicine, and Departments of Medicine and Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD
| | - Stella Aslibekyan
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - Kathy A Ryan
- Program in Personalized and Genomic Medicine, and Departments of Medicine and Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD
| | - Michael A Province
- Department of Genetics, Washington University School of Medicine, St. Louis, MO
| | - Hemant K Tiwari
- Section on Statistical Genetics, Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - Jose M Ordovas
- Nutrition and Genomics Laboratory, Jean Mayer-US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA
| | - Alan R Shuldiner
- Program in Personalized and Genomic Medicine, and Departments of Medicine and Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD; Geriatric Research and Education Clinical Center, Veterans Administration Medical Center, Baltimore, MD
| | - Donna K Arnett
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL
| | - Ingrid B Borecki
- Department of Genetics, Washington University School of Medicine, St. Louis, MO
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30
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Banfield EC, Liu Y, Davis JS, Chang S, Frazier-Wood AC. Poor Adherence to US Dietary Guidelines for Children and Adolescents in the National Health and Nutrition Examination Survey Population. J Acad Nutr Diet 2015; 116:21-27. [PMID: 26391469 DOI: 10.1016/j.jand.2015.08.010] [Citation(s) in RCA: 207] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2014] [Accepted: 08/04/2015] [Indexed: 11/18/2022]
Abstract
BACKGROUND Poor diet quality in childhood and adolescence is associated with adverse health outcomes throughout life, yet the dietary habits of American children and how they change across childhood and adolescence are unknown. OBJECTIVES This study sought to describe diet quality among children and adolescents by assessing adherence to the 2010 Dietary Guidelines for Americans (DGA) and to determine whether any differences in adherence occurred across childhood. DESIGN, SETTING, AND PARTICIPANTS We employed a cross-sectional design using data from the National Health and Nutrition Examination Survey (NHANES). Of 9,280 children aged 4 to 18 years who participated in NHANES from 2005 to 2010, those with insufficient data on dietary recall (n=852) or who were pregnant or lactating during the time of interview (n=38) were excluded from the final study sample (n=8,390). MAIN OUTCOME MEASURES We measured adherence to the DGA using the Healthy Eating Index 2010 (HEI-2010) and stratified participants into three age groups (4 to 8, 9 to 13, and 14 to 18 years of age). We analyzed each of 12 HEI-2010 components and total HEI-2010 score. RESULTS The youngest children had the highest overall diet quality due to significantly greater scores for total fruit, whole fruit, dairy, and whole grains. These children also had the highest scores for sodium, refined grains, and empty calories. Total HEI-2010 scores ranged from 43.59 to 52.11 out of 100, much lower than the minimum score of 80 that is thought to indicate a diet associated with good health. CONCLUSIONS Overall, children and adolescents are failing to meet the DGA and may be at an increased risk of chronic diseases throughout life. By analyzing which food groups show differences between age groups, we provide data that can inform the development of dietary interventions to promote specific food groups targeting specific ages and improve diet quality among children and adolescents.
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Dashti HS, Follis JL, Smith CE, Tanaka T, Garaulet M, Gottlieb DJ, Hruby A, Jacques PF, Kiefte-de Jong JC, Lamon-Fava S, Scheer FAJL, Bartz TM, Kovanen L, Wojczynski MK, Frazier-Wood AC, Ahluwalia TS, Perälä MM, Jonsson A, Muka T, Kalafati IP, Mikkilä V, Ordovás JM, Partonen T, Ebeling T, Hopkins PN, Paternoster L, Lahti J, Hernandez DG, Toft U, Saxena R, Vitezova A, Kanoni S, Raitakari OT, Psaty BM, Perola M, Männistö S, Straka RJ, Hansen T, Räikkönen K, Ferrucci L, Grarup N, Johnson WC, Rallidis L, Kähönen M, Siscovick DS, Havulinna AS, Astrup A, Jørgensen T, Chen TA, Hofman A, Deloukas P, Viikari JS, Mozaffarian D, Pedersen O, Rotter JI, Uitterlinden AG, Seppälä I, Tiemeier H, Salomaa V, Gharib SA, Borecki IB, Arnett DK, Sørensen TI, Eriksson JG, Bandinelli S, Linneberg A, Rich SS, Franco OH, Dedoussis G, Lehtimäki T. Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits. Diabetes Care 2015; 38:1456-66. [PMID: 26084345 PMCID: PMC4512139 DOI: 10.2337/dc14-2709] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2014] [Accepted: 04/11/2015] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153, MTNR1B-rs10830963, NR1D1-rs2314339) and cardiometabolic traits (fasting glucose [FG], HOMA-insulin resistance, BMI, waist circumference, and HDL-cholesterol) to facilitate personalized recommendations. RESEARCH DESIGN AND METHODS We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations and interactions between dietary intake/sleep duration and selected variants on cardiometabolic traits from 15 cohort studies including up to 28,190 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. RESULTS We observed significant associations between relative macronutrient intakes and glycemic traits and short sleep duration (<7 h) and higher FG and replicated known MTNR1B associations with glycemic traits. No interactions were evident after accounting for multiple comparisons. However, we observed nominally significant interactions (all P < 0.01) between carbohydrate intake and MTNR1B-rs1387153 for FG with a 0.003 mmol/L higher FG with each additional 1% carbohydrate intake in the presence of the T allele, between sleep duration and CRY2-rs11605924 for HDL-cholesterol with a 0.010 mmol/L higher HDL-cholesterol with each additional hour of sleep in the presence of the A allele, and between long sleep duration (≥9 h) and MTNR1B-rs1387153 for BMI with a 0.60 kg/m(2) higher BMI with long sleep duration in the presence of the T allele relative to normal sleep duration (≥7 to <9 h). CONCLUSIONS Our results suggest that lower carbohydrate intake and normal sleep duration may ameliorate cardiometabolic abnormalities conferred by common circadian-related genetic variants. Until further mechanistic examination of the nominally significant interactions is conducted, recommendations applicable to the general population regarding diet—specifically higher carbohydrate and lower fat composition—and normal sleep duration should continue to be emphasized among individuals with the investigated circadian-related gene variants.
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Affiliation(s)
- Hassan S Dashti
- Nutrition and Genomics Laboratory, Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA
| | - Jack L Follis
- Department of Mathematics, Computer Science and Cooperative Engineering, University of St. Thomas, Houston, TX
| | - Caren E Smith
- Nutrition and Genomics Laboratory, Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD
| | - Marta Garaulet
- Department of Physiology, University of Murcia, Murcia, Spain
| | - Daniel J Gottlieb
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA Division of Sleep Medicine, Harvard Medical School, Boston, MA Sleep Disorders Center, VA Boston Healthcare System, Boston, MA
| | - Adela Hruby
- Department of Nutrition, Harvard School of Public Health, Boston, MA
| | - Paul F Jacques
- Nutritional Epidemiology Laboratory, Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA
| | - Jessica C Kiefte-de Jong
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands Global Public Health, Leiden University College, The Hague, the Netherlands
| | - Stefania Lamon-Fava
- Cardiovascular Nutrition Laboratory, Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA
| | - Frank A J L Scheer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA Division of Sleep Medicine, Harvard Medical School, Boston, MA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA Department of Biostatistics, University of Washington, Seattle, WA
| | - Leena Kovanen
- Department of Mental Health and Substance Abuse Services, National Institute for Health and Welfare (THL), Helsinki, Finland
| | - Mary K Wojczynski
- Department of Genetics, Washington University School of Medicine, St. Louis, MO
| | - Alexis C Frazier-Wood
- U.S. Department of Agriculture/Agricultural Research Service Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX
| | - Tarunveer S Ahluwalia
- The Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark Danish Pediatric Asthma Centre, Gentofte Hospital, The Capital Region, Copenhagen, Denmark
| | - Mia-Maria Perälä
- Department of Chronic Disease Prevention, National Institute for Health and Welfare (THL), Helsinki, Finland
| | - Anna Jonsson
- The Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Taulant Muka
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Ioanna P Kalafati
- Department of Nutrition and Dietetics, Harokopio University, Athens, Greece
| | - Vera Mikkilä
- Department of Food and Environmental Sciences, Division of Nutrition, University of Helsinki, Helsinki, Finland Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - José M Ordovás
- Nutrition and Genomics Laboratory, Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA Department of Epidemiology, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain Instituto Madrileño de Estudios Avanzados en Alimentación (IMDEA-FOOD), Madrid, Spain
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Jung SY, Vitolins MZ, Fenton J, Frazier-Wood AC, Hursting SD, Chang S. Risk profiles for weight gain among postmenopausal women: a classification and regression tree analysis approach. PLoS One 2015; 10:e0121430. [PMID: 25822239 PMCID: PMC4378852 DOI: 10.1371/journal.pone.0121430] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2014] [Accepted: 02/16/2015] [Indexed: 01/11/2023] Open
Abstract
Purpose Risk factors for obesity and weight gain are typically evaluated individually while “adjusting for” the influence of other confounding factors, and few studies, if any, have created risk profiles by clustering risk factors. We identified subgroups of postmenopausal women homogeneous in their clustered modifiable and non-modifiable risk factors for gaining ≥ 3% weight. Methods This study included 612 postmenopausal women 50–79 years old, enrolled in an ancillary study of the Women's Health Initiative Observational Study between February 1995 and July 1998. Classification and regression tree and stepwise regression models were built and compared. Results Of 27 selected variables, the factors significantly related to ≥ 3% weight gain were weight change in the past 2 years, age at menopause, dietary fiber, fat, alcohol intake, and smoking. In women younger than 65 years, less than 4 kg weight change in the past 2 years sufficiently reduced risk of ≥ 3% weight gain. Different combinations of risk factors related to weight gain were reported for subgroups of women: women 65 years or older (essential factor: < 9.8 g/day dietary factor), African Americans (essential factor: currently smoking), and white women (essential factor: ≥ 5 kg weight change for the past 2 years). Conclusions Our findings suggest specific characteristics for particular subgroups of postmenopausal women that may be useful for identifying those at risk for weight gain. The study results may be useful for targeting efforts to promote strategies to reduce the risk of obesity and weight gain in subgroups of postmenopausal women and maximize the effect of weight control by decreasing obesity-relevant adverse health outcomes.
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Affiliation(s)
- Su Yon Jung
- Translational Sciences Section, Jonsson Comprehensive Cancer Center, School of Nursing, University of California Los Angeles, Los Angeles, CA, United States of America
- * E-mail:
| | - Mara Z. Vitolins
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Jenifer Fenton
- Department of Food Science and Human Nutrition, Michigan State University, East Lansing, Michigan, United States of America
| | - Alexis C. Frazier-Wood
- USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, United States of America
| | - Stephen D. Hursting
- Department of Nutritional Sciences, The University of Texas at Austin, Austin, Texas, United States of America
| | - Shine Chang
- Translational Sciences Section, Jonsson Comprehensive Cancer Center, School of Nursing, University of California Los Angeles, Los Angeles, CA, United States of America
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Abstract
Several dietary approaches have been proposed to prevent the onset of chronic diseases. As yet, no single approach has emerged as having the most consistent health benefits. This arises, in part, due to the fact that diet influences health in the context of individual factors with genetic components. Therefore, the effects of diet on health may be dependent on an individual's genetic background. At this time we lack robust evidence for the effects of interactions between genes and dietary patterns on health. To understand why, I will briefly review the most methodologically strong attempts to identify gene-diet interactions, which will illuminate how the challenges facing all of genetic research apply to the search for gene-diet interactions. Then I will discuss some ways in which these challenges are being addressed that offer hope for the future in which the best diet for an individual is identified based on their genetic variation.
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Affiliation(s)
- Alexis C. Frazier-Wood
- USDA/ARS Children’s Nutrition Research Center, Baylor College of Medicine, 1100 Bates Street, Houston, TX 77030 USA
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Dashti HS, Follis JL, Smith CE, Tanaka T, Cade BE, Gottlieb DJ, Hruby A, Jacques PF, Lamon-Fava S, Richardson K, Saxena R, Scheer FAJL, Kovanen L, Bartz TM, Perälä MM, Jonsson A, Frazier-Wood AC, Kalafati IP, Mikkilä V, Partonen T, Lemaitre RN, Lahti J, Hernandez DG, Toft U, Johnson WC, Kanoni S, Raitakari OT, Perola M, Psaty BM, Ferrucci L, Grarup N, Highland HM, Rallidis L, Kähönen M, Havulinna AS, Siscovick DS, Räikkönen K, Jørgensen T, Rotter JI, Deloukas P, Viikari JSA, Mozaffarian D, Linneberg A, Seppälä I, Hansen T, Salomaa V, Gharib SA, Eriksson JG, Bandinelli S, Pedersen O, Rich SS, Dedoussis G, Lehtimäki T, Ordovás JM. Habitual sleep duration is associated with BMI and macronutrient intake and may be modified by CLOCK genetic variants. Am J Clin Nutr 2015; 101:135-43. [PMID: 25527757 PMCID: PMC4266883 DOI: 10.3945/ajcn.114.095026] [Citation(s) in RCA: 83] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Short sleep duration has been associated with greater risks of obesity, hypertension, diabetes, and cardiovascular disease. Also, common genetic variants in the human Circadian Locomotor Output Cycles Kaput (CLOCK) show associations with ghrelin and total energy intake. OBJECTIVES We examined associations between habitual sleep duration, body mass index (BMI), and macronutrient intake and assessed whether CLOCK variants modify these associations. DESIGN We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations of sleep duration and BMI and macronutrient intake as percentages of total energy as well as interactions with CLOCK variants from 9 cohort studies including up to 14,906 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium. RESULTS We observed a significant association between sleep duration and lower BMI (β ± SE = 0.16 ± 0.04, P < 0.0001) in the overall sample; however, associations between sleep duration and relative macronutrient intake were evident in age- and sex-stratified analyses only. We observed a significant association between sleep duration and lower saturated fatty acid intake in younger (aged 20-64 y) adults (men: 0.11 ± 0.06%, P = 0.03; women: 0.10 ± 0.05%, P = 0.04) and with lower carbohydrate (-0.31 ± 0.12%, P < 0.01), higher total fat (0.18 ± 0.09%, P = 0.05), and higher PUFA (0.05 ± 0.02%, P = 0.02) intakes in older (aged 65-80 y) women. In addition, the following 2 nominally significant interactions were observed: between sleep duration and rs12649507 on PUFA intake and between sleep duration and rs6858749 on protein intake. CONCLUSIONS Our results indicate that longer habitual sleep duration is associated with lower BMI and age- and sex-specific favorable dietary behaviors. Differences in the relative intake of specific macronutrients associated with short sleep duration could, at least in part, explain previously reported associations between short sleep duration and chronic metabolic abnormalities. In addition, the influence of obesity-associated CLOCK variants on the association between sleep duration and macronutrient intake suggests that longer habitual sleep duration could ameliorate the genetic predisposition to obesity via a favorable dietary profile.
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Affiliation(s)
- Hassan S Dashti
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Jack L Follis
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Caren E Smith
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Toshiko Tanaka
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Brian E Cade
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Daniel J Gottlieb
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Adela Hruby
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Paul F Jacques
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Stefania Lamon-Fava
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Kris Richardson
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Richa Saxena
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Frank A J L Scheer
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Leena Kovanen
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Traci M Bartz
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Mia-Maria Perälä
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Anna Jonsson
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Alexis C Frazier-Wood
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Ioanna-Panagiota Kalafati
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Vera Mikkilä
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Timo Partonen
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Rozenn N Lemaitre
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Jari Lahti
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Dena G Hernandez
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Ulla Toft
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - W Craig Johnson
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Stavroula Kanoni
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Olli T Raitakari
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Markus Perola
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Bruce M Psaty
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Luigi Ferrucci
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Niels Grarup
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Heather M Highland
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Loukianos Rallidis
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Mika Kähönen
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Aki S Havulinna
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - David S Siscovick
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Katri Räikkönen
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Torben Jørgensen
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Jerome I Rotter
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Panos Deloukas
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Jorma S A Viikari
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Dariush Mozaffarian
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Allan Linneberg
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Ilkka Seppälä
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Torben Hansen
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Veikko Salomaa
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Sina A Gharib
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Johan G Eriksson
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Stefania Bandinelli
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Oluf Pedersen
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Stephen S Rich
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - George Dedoussis
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - Terho Lehtimäki
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
| | - José M Ordovás
- From the Nutrition and Genomics Laboratory (HSD, CES, KR, and JMO), Nutritional Epidemiology Laboratory (PFJ), and Cardiovascular Nutrition Laboratory (SL-F), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, MA; the Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX (JLF); the Translational Gerontology Branch (TT and LF) and Laboratory of Neurogenetics (DGH), National Institute on Aging, Baltimore, MD; the Divisions of Sleep and Circadian Disorders (BEC, DJG, RS, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Brigham and Women's Hospital, Boston, MA; the Divisions of Sleep Medicine (BEC, DJG, and FAJLS) and Cardiovascular Medicine and Channing Division of Network Medicine (DM), Harvard Medical School, Boston, MA; the Sleep Disorders Center, VA Boston Healthcare System, Boston, MA (DJG); the Department of Nutrition, Harvard School of Public Health, Boston, MA (AH and DM); the Center for Human Genetic Research and Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (RS); the Departments of Mental Health and Substance Abuse Services (LK and TP) and Chronic Disease Prevention (M-MP, MP, ASH, VS, and JGE) and National Institute for Health and Welfare (THL), Helsinki, Finland; the Cardiovascular Health Research Unit (TMB, RNL, and BMP), Departments of Medicine (TMB, RNL, BMP, and SAG), Biostatistics (TMB and WCJ), and Epidemiology and Health Services (BMP), Computational Medicine Core (SAG), Center for Lung Biology (SAG), and University of Washington Medicine Sleep Center (SAG), University of Washington, Seattle, WA; The Novo Nordisk Foundation Center for Basic Metabolic Research (AJ, NG, TH, and OP) and Department of Clinical Medicine (AL), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; the USDA
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Frazier-Wood AC, Carnell S, Pena O, Hughes SO, O’Connor TM, Asherson P, Kuntsi J. Cognitive performance and BMI in childhood: Shared genetic influences between reaction time but not response inhibition. Obesity (Silver Spring) 2014; 22:2312-8. [PMID: 25376398 PMCID: PMC4313367 DOI: 10.1002/oby.20862] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2014] [Accepted: 07/23/2014] [Indexed: 11/10/2022]
Abstract
OBJECTIVE The aim of this work is to understand whether shared genetic influences can explain the association between obesity and cognitive performance, including slower and more variable reaction times (RTs) and worse response inhibition. METHODS RT on a four-choice RT task and the go/no-go task, and commission errors on the go/no-go task for 1,312 twins ages 7-10 years were measured. BMI was measured at 9-12 years. Biometric twin models were run to give an estimate of the genetic correlation (rG ) between body mass index (BMI) and three cognitive measures: mean RT (MRT), RT variability (RTV; the standard deviation of RTs), and commission errors (a measure of response inhibition). RESULTS Genetic correlations indicated that 20%-30% of the genes underlying BMI were shared with both RT measures. However, only small phenotypic correlations between MRT and RTV with later BMI (rPh = ∼0.1) were observed. Commission errors were unassociated with later BMI (rPh = -0.03, ns). CONCLUSIONS Our results are the first to demonstrate significant shared genetic effects between RT performance and BMI. Our findings add biological support to the notion that obesity is associated with slower and more variable RTs. However, our results also emphasize the small nature of the association, which may explain previous negative findings.
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Affiliation(s)
- Alexis C. Frazier-Wood
- USDA/ARS Children’s Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA
| | - Susan Carnell
- Division of Child and Adolescent Psychiatry, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, Maryland, USA
| | - Oscar Pena
- Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Sciences Center, Houston, Texas, USA
| | - Sheryl O. Hughes
- USDA/ARS Children’s Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA
| | - Teresia M. O’Connor
- USDA/ARS Children’s Nutrition Research Center, Baylor College of Medicine, Houston, Texas, USA
| | - Philip Asherson
- King’s College London, MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, De Crespigny Park, London, UK
| | - Jonna Kuntsi
- King’s College London, MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, De Crespigny Park, London, UK
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Frazier-Wood AC, Wojczynski MK, Borecki IB, Hopkins PN, Lai CQ, Ordovas JM, Straka RJ, Tsai MY, Tiwari HK, Arnett DK. Genetic risk scores associated with baseline lipoprotein subfraction concentrations do not associate with their responses to fenofibrate. Biology (Basel) 2014; 3:536-50. [PMID: 25157911 PMCID: PMC4192626 DOI: 10.3390/biology3030536] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/23/2014] [Revised: 07/29/2014] [Accepted: 08/05/2014] [Indexed: 12/11/2022]
Abstract
Lipoprotein subclass concentrations are modifiable markers of cardiovascular disease risk. Fenofibrate is known to show beneficial effects on lipoprotein subclasses, but little is known about the role of genetics in mediating the responses of lipoprotein subclasses to fenofibrate. A recent genomewide association study (GWAS) associated several single nucleotide polymorphisms (SNPs) with lipoprotein measures, and validated these associations in two independent populations. We used this information to construct genetic risk scores (GRSs) for fasting lipoprotein measures at baseline (pre-fenofibrate), and aimed to examine whether these GRSs also associated with the responses of lipoproteins to fenofibrate. Fourteen lipoprotein subclass measures were assayed in 817 men and women before and after a three week fenofibrate trial. We set significance at a Bonferroni corrected alpha <0.05 (p < 0.004). Twelve subclass measures changed with fenofibrate administration (each p = 0.003 to <0.0001). Mixed linear models which controlled for age, sex, body mass index (BMI), smoking status, pedigree and study-center, revealed that GRSs were associated with eight baseline lipoprotein measures (p < 0.004), however no GRS was associated with fenofibrate response. These results suggest that the mechanisms for changes in lipoprotein subclass concentrations with fenofibrate treatment are not mediated by the genetic risk for fasting levels.
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Affiliation(s)
- Alexis C Frazier-Wood
- USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX 77030, USA.
| | - Mary K Wojczynski
- Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA.
| | - Ingrid B Borecki
- Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA.
| | - Paul N Hopkins
- Department of Internal Medicine, University of Utah, Salt Lake City, UT 84132, USA.
| | - Chao-Qiang Lai
- Nutrition and Genomics Laboratory, Jean Mayer-US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA 02111, USA.
| | - Jose M Ordovas
- Nutrition and Genomics Laboratory, Jean Mayer-US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA 02111, USA.
| | - Robert J Straka
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN 55455, USA.
| | - Micheal Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, MN55455, USA.
| | - Hemant K Tiwari
- Section on Statistical Genetics, University of Alabama at Birmingham, School of Public Health, AL 35294, USA.
| | - Donna K Arnett
- USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX 77030, USA.
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Kuntsi J, Pinto R, Price TS, van der Meere JJ, Frazier-Wood AC, Asherson P. The separation of ADHD inattention and hyperactivity-impulsivity symptoms: pathways from genetic effects to cognitive impairments and symptoms. J Abnorm Child Psychol 2014; 42:127-36. [PMID: 23839718 DOI: 10.1007/s10802-013-9771-7] [Citation(s) in RCA: 65] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Both shared and unique genetic risk factors underlie the two symptom domains of attention deficit hyperactivity disorder (ADHD): inattention and hyperactivity-impulsivity. The developmental course and relationship to co-occurring disorders differs across the two symptom domains, highlighting the importance of their partially distinct etiologies. Familial cognitive impairment factors have been identified in ADHD, but whether they show specificity in relation to the two ADHD symptom domains remains poorly understood. We aimed to investigate whether different cognitive impairments are genetically linked to the ADHD symptom domains of inattention versus hyperactivity-impulsivity. We conducted multivariate genetic model fitting analyses on ADHD symptom scores and cognitive data, from go/no-go and fast tasks, collected on a population twin sample of 1,312 children aged 7-10. Reaction time variability (RTV) showed substantial genetic overlap with inattention, as observed in an additive genetic correlation of 0.64, compared to an additive genetic correlation of 0.31 with hyperactivity-impulsivity. Commission errors (CE) showed low additive genetic correlations with both hyperactivity-impulsivity and inattention (genetic correlations of 0.17 and 0.11, respectively). The additive genetic correlation between RTV and CE was also low and non-significant at -0.10, consistent with the etiological separation between the two indices of cognitive impairments. Overall, two key cognitive impairments phenotypically associated with ADHD symptoms, captured by RTV and CE, showed different genetic relationships to the two ADHD symptom domains. The findings extend a previous model of two familial cognitive impairment factors in combined subtype ADHD by separating pathways underlying inattention and hyperactivity-impulsivity symptoms.
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Affiliation(s)
- Jonna Kuntsi
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, De Crespigny Park, London, SE5 8AF, UK,
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Casas-Agustench P, Arnett DK, Smith CE, Lai CQ, Parnell LD, Borecki IB, Frazier-Wood AC, Allison M, Chen YDI, Taylor KD, Rich SS, Rotter JI, Lee YC, Ordovás JM. Saturated fat intake modulates the association between an obesity genetic risk score and body mass index in two US populations. J Acad Nutr Diet 2014; 114:1954-66. [PMID: 24794412 DOI: 10.1016/j.jand.2014.03.014] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2013] [Accepted: 03/17/2014] [Indexed: 11/26/2022]
Abstract
Combining multiple genetic variants related to obesity into a genetic risk score (GRS) might improve identification of individuals at risk of developing obesity. Moreover, characterizing gene-diet interactions is a research challenge to establish dietary recommendations to individuals with higher predisposition to obesity. Our objective was to analyze the association between an obesity GRS and body mass index (BMI) in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) population, focusing on gene-diet interactions with total fat and saturated fatty acid (SFA) intake, and to replicate findings in the Multi-Ethnic Study of Atherosclerosis (MESA) population. Cross-sectional analyses included 783 white US participants from GOLDN and 2,035 from MESA. Dietary intakes were estimated with validated food frequency questionnaires. Height and weight were measured. A weighted GRS was calculated on the basis of 63 obesity-associated variants. Multiple linear regression models adjusted by potential confounders were used to examine gene-diet interactions between dietary intake (total fat and SFA) and the obesity GRS in determining BMI. Significant interactions were found between total fat intake and the obesity GRS using these variables as continuous for BMI (P for interaction=0.010, 0.046, and 0.002 in GOLDN, MESA, and meta-analysis, respectively). These association terms were stronger when assessing interactions between SFA intake and GRS for BMI (P for interaction=0.005, 0.018, and <0.001 in GOLDN, MESA, and meta-analysis, respectively). SFA intake interacts with an obesity GRS in modulating BMI in two US populations. Although determining the causal direction requires further investigation, these findings suggest that potential dietary recommendations to reduce BMI effectively in populations with high obesity GRS would be to reduce total fat intake mainly by limiting SFAs.
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Frazier-Wood AC, Aslibekyan S, Absher DM, Hopkins PN, Sha J, Tsai MY, Tiwari HK, Waite LL, Zhi D, Arnett DK. Methylation at CPT1A locus is associated with lipoprotein subfraction profiles. J Lipid Res 2014; 55:1324-30. [PMID: 24711635 DOI: 10.1194/jlr.m048504] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2014] [Indexed: 12/18/2022] Open
Abstract
Lipoprotein subfractions help discriminate cardiometabolic disease risk. Genetic loci validated as associating with lipoprotein measures do not account for a large proportion of the individual variation in lipoprotein measures. We hypothesized that DNA methylation levels across the genome contribute to interindividual variation in lipoprotein measures. Using data from participants of the Genetics of Lipid Lowering Drugs and Diet Network (n = 663 for discovery and n = 331 for replication stages, respectively), we conducted the first systematic screen of the genome to determine associations between methylation status at ∼470,000 cytosine-guanine dinucleotide (CpG) sites in CD4(+) T cells and 14 lipoprotein subfraction measures. We modeled associations between methylation at each CpG site and each lipoprotein measure separately using linear mixed models, adjusted for age, sex, study site, cell purity, and family structure. We identified two CpGs, both in the carnitine palmitoyltransferase-1A (CPT1A) gene, which reached significant levels of association with VLDL and LDL subfraction parameters in both discovery and replication phases (P < 1.1 × 10(-7) in the discovery phase, P < .004 in the replication phase, and P < 1.1 × 10(-12) in the full sample). CPT1A is regulated by PPARα, a ligand for drugs used to reduce CVD. Our associations between methylation in CPT1A and lipoprotein measures highlight the epigenetic role of this gene in metabolic dysfunction.
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Affiliation(s)
- Alexis C Frazier-Wood
- USDA/Agricultural Research Service Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX
| | - Stella Aslibekyan
- Department of Epidemiology, University of Alabama at Birmingham, School of Public Health, Birmingham, AL
| | - Devin M Absher
- Department of Epidemiology, University of Alabama at Birmingham, School of Public Health, Birmingham, AL HudsonAlpha Institute for Biotechnology, Huntsville, AL
| | - Paul N Hopkins
- Department of Internal Medicine, University of Utah, Salt Lake City, UT
| | - Jin Sha
- Department of Epidemiology, University of Alabama at Birmingham, School of Public Health, Birmingham, AL
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, MN
| | - Hemant K Tiwari
- Section on Statistical Genetics, University of Alabama at Birmingham, School of Public Health, Birmingham, AL
| | - Lindsay L Waite
- HudsonAlpha Institute for Biotechnology, Huntsville, AL Section on Statistical Genetics, University of Alabama at Birmingham, School of Public Health, Birmingham, AL
| | - Degui Zhi
- Section on Statistical Genetics, University of Alabama at Birmingham, School of Public Health, Birmingham, AL
| | - Donna K Arnett
- Department of Epidemiology, University of Alabama at Birmingham, School of Public Health, Birmingham, AL
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Frazier-Wood AC, Kabagambe EK, Wojczynski MK, Borecki IB, Tiwari HK, Smith CE, Ordovas JM, Arnett DK. The association between LRP-1 variants and chylomicron uptake after a high fat meal. Nutr Metab Cardiovasc Dis 2013; 23:1154-1158. [PMID: 23484911 PMCID: PMC3686991 DOI: 10.1016/j.numecd.2012.12.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2012] [Revised: 12/19/2012] [Accepted: 12/27/2012] [Indexed: 11/22/2022]
Abstract
BACKGROUND AND AIMS In vitro studies suggest that low density lipoprotein receptor-related protein 1 (LRP1) plays a role in the secondary uptake of chylomicrons. In addition, in vivo studies using LRP-1 knockout mice show these animals exhibit delayed chylomicron clearance. Whether this is true in humans is unknown. We aimed to determine whether genetic variants in LRP-1 are associated with postprandial chylomicron uptake in humans given an oral fat challenge. METHODS AND RESULTS As many as 817 men and women (mean age +/- standard deviation = 48.4 +/- 16.4 years) forming the study population for the Genetics of Lipid Lowering Drugs Network (GOLDN) study ingested an oral fat load of 700 kilocalories per m² of body surface area at 83% fat, after an 8-h fast. Chylomicrons were measured by nuclear resonance spectroscopy (NMR) at fasting, and 3.5 and 6 h after the meal. 26 Single nucleotide polymorphisms (SNPs) in the LRP-1 gene were genotyped on the Affymetrix 6.0 array. Chylomicrons were, as expected, zero at fasting. Mixed linear models adjusted for age, sex, study site and pedigree tested for associations between LRP-1 SNPs and changes in chylomicron concentrations 3.5-6 h. A gene-based test across all 26 SNPs was conducted which corrected for the linkage disequilibrium (LD) between SNPs. 11 LRP-1 SNPs were significantly associated with the change in chylomicron concentration correction for multiple testing (Q < 0.05). The subsequent gene-based test, was also significant (P = 0.01). CONCLUSION These results require replication but strongly indicate the role of LRP1 in postprandial lipoprotein uptake and/or clearance.
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Affiliation(s)
- A C Frazier-Wood
- Department of Epidemiology, University of Alabama at Birmingham, School of Public Health, Birmingham, AL 35294, United States; Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas School of Public Health, Houston, TX 77030, United States.
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Aslibekyan S, An P, Frazier-Wood AC, Kabagambe EK, Irvin MR, Straka RJ, Tiwari HK, Tsai MY, Hopkins PN, Borecki IB, Ordovas JM, Arnett DK. Preliminary evidence of genetic determinants of adiponectin response to fenofibrate in the Genetics of Lipid Lowering Drugs and Diet Network. Nutr Metab Cardiovasc Dis 2013; 23:987-994. [PMID: 23149075 PMCID: PMC3578131 DOI: 10.1016/j.numecd.2012.07.010] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2012] [Revised: 07/27/2012] [Accepted: 07/27/2012] [Indexed: 01/13/2023]
Abstract
BACKGROUND AND AIMS Adiponectin is an adipose-secreted protein that has been linked to changes in insulin sensitivity, high-density lipoprotein cholesterol levels, and inflammatory patterns. Although fenofibrate therapy can raise adiponectin levels, treatment response is heterogeneous and heritable, suggesting a role for genetic mediators. This is the first genome-wide association study of fenofibrate effects on circulating adiponectin. METHODS AND RESULTS Plasma adiponectin was measured in participants of the Genetics of Lipid Lowering Drugs and Diet Network (n = 793) before and after a 3-week daily treatment with 160 mg of fenofibrate. Associations between variants on the Affymetrix Genome-Wide Human SNP Array 6.0 and adiponectin were assessed using mixed linear models, adjusted for age, sex, site, and family. We observed a statistically significant (P = 5 × 10⁻⁸) association between rs2384207 in 12q24, a region previously linked to several metabolic traits, and the fenofibrate-induced change in circulating adiponectin. Additionally, our genome-wide analysis of baseline adiponectin levels replicated the previously reported association with CDH13 and suggested novel associations with markers near the PCK1, ZBP1, TMEM18, and SCUBE1 genes. The findings from the single marker tests were corroborated in gene-based analyses. Biological pathway analyses suggested a borderline significant association between the EGF receptor signaling pathway and baseline adiponectin levels. CONCLUSIONS We present preliminary evidence linking several biologically relevant genetic variants to adiponectin levels at baseline and in response to fenofibrate therapy. Our findings provide support for fine-mapping of the 12q24 region to investigate the shared biological mechanisms underlying levels of circulating adiponectin and susceptibility to metabolic disease.
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Affiliation(s)
- S Aslibekyan
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, RPHB 217G, Birmingham, AL 35294, USA.
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Abstract
Obesity can have multifactorial causes that may change with development and are not simply attributable to one's genetic constitution. To date, expensive and laborious genome-wide association studies have only ascribed a small contribution of genetic variants to obesity. The emergence of the field of epigenetics now offers a new paradigm with which to study excess fat mass. Currently, however, there are no compelling epigenetic studies to explain the role of epigenetics in obesity, especially from a developmental perspective. It is clear that until there are advances in the understanding of the main mechanisms by which different fat types, i.e. brown, beige, and white, are established and how these differ between depots and species, population-based studies designed to determine specific aspects of epigenetics will be potentially limited. Obesity is a slowly evolving condition that is not simply explained by changes in the intake of one macronutrient. The latest advances in epigenetics, coupled with the establishment of relevant longitudinal models of obesity, which incorporate functionally relevant end points, may now permit the precise contribution of epigenetic modifications to excess fat mass to be effectively studied.
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Affiliation(s)
- Michael E Symonds
- Early Life Nutrition Research Unit, Academic Division of Child Health, School of Medicine, University Hospital, The University of Nottingham, Nottingham, UK
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Tanaka T, Ngwa JS, van Rooij FJA, Zillikens MC, Wojczynski MK, Frazier-Wood AC, Houston DK, Kanoni S, Lemaitre RN, Luan J, Mikkilä V, Renstrom F, Sonestedt E, Zhao JH, Chu AY, Qi L, Chasman DI, de Oliveira Otto MC, Dhurandhar EJ, Feitosa MF, Johansson I, Khaw KT, Lohman KK, Manichaikul A, McKeown NM, Mozaffarian D, Singleton A, Stirrups K, Viikari J, Ye Z, Bandinelli S, Barroso I, Deloukas P, Forouhi NG, Hofman A, Liu Y, Lyytikäinen LP, North KE, Dimitriou M, Hallmans G, Kähönen M, Langenberg C, Ordovas JM, Uitterlinden AG, Hu FB, Kalafati IP, Raitakari O, Franco OH, Johnson A, Emilsson V, Schrack JA, Semba RD, Siscovick DS, Arnett DK, Borecki IB, Franks PW, Kritchevsky SB, Lehtimäki T, Loos RJF, Orho-Melander M, Rotter JI, Wareham NJ, Witteman JCM, Ferrucci L, Dedoussis G, Cupples LA, Nettleton JA. Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake. Am J Clin Nutr 2013; 97:1395-402. [PMID: 23636237 PMCID: PMC3652928 DOI: 10.3945/ajcn.112.052183] [Citation(s) in RCA: 167] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Macronutrient intake varies substantially between individuals, and there is evidence that this variation is partly accounted for by genetic variants. OBJECTIVE The objective of the study was to identify common genetic variants that are associated with macronutrient intake. DESIGN We performed 2-stage genome-wide association (GWA) meta-analysis of macronutrient intake in populations of European descent. Macronutrients were assessed by using food-frequency questionnaires and analyzed as percentages of total energy consumption from total fat, protein, and carbohydrate. From the discovery GWA (n = 38,360), 35 independent loci associated with macronutrient intake at P < 5 × 10(-6) were identified and taken forward to replication in 3 additional cohorts (n = 33,533) from the DietGen Consortium. For one locus, fat mass obesity-associated protein (FTO), cohorts with Illumina MetaboChip genotype data (n = 7724) provided additional replication data. RESULTS A variant in the chromosome 19 locus (rs838145) was associated with higher carbohydrate (β ± SE: 0.25 ± 0.04%; P = 1.68 × 10(-8)) and lower fat (β ± SE: -0.21 ± 0.04%; P = 1.57 × 10(-9)) consumption. A candidate gene in this region, fibroblast growth factor 21 (FGF21), encodes a fibroblast growth factor involved in glucose and lipid metabolism. The variants in this locus were associated with circulating FGF21 protein concentrations (P < 0.05) but not mRNA concentrations in blood or brain. The body mass index (BMI)-increasing allele of the FTO variant (rs1421085) was associated with higher protein intake (β ± SE: 0.10 ± 0.02%; P = 9.96 × 10(-10)), independent of BMI (after adjustment for BMI, β ± SE: 0.08 ± 0.02%; P = 3.15 × 10(-7)). CONCLUSION Our results indicate that variants in genes involved in nutrient metabolism and obesity are associated with macronutrient consumption in humans. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetic and Environmental Determinants of Triglycerides), NCT01331512 (InCHIANTI Study), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).
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Affiliation(s)
- Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD 21225, USA.
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Kuntsi J, Frazier-Wood AC, Banaschewski T, Gill M, Miranda A, Oades RD, Roeyers H, Rothenberger A, Steinhausen HC, van der Meere JJ, Faraone SV, Asherson P, Rijsdijk F. Genetic analysis of reaction time variability: room for improvement? Psychol Med 2013; 43:1323-1333. [PMID: 22975296 PMCID: PMC3801159 DOI: 10.1017/s0033291712002061] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2012] [Revised: 07/26/2012] [Accepted: 07/27/2012] [Indexed: 11/18/2022]
Abstract
BACKGROUND Increased reaction time variability (RTV) on cognitive tasks requiring a speeded response is characteristic of several psychiatric disorders. In attention deficit hyperactivity disorder (ADHD), the association with RTV is strong phenotypically and genetically, yet high RTV is not a stable impairment but shows ADHD-sensitive improvement under certain conditions, such as those with rewards. The state regulation theory proposed that the RTV difference score, which captures change from baseline to a rewarded or fast condition, specifically measures 'state regulation'. By contrast, the interpretation of RTV baseline (slow, unrewarded) scores is debated. We aimed to investigate directly the degree of phenotypic and etiological overlap between RTV baseline and RTV difference scores. Method We conducted genetic model fitting analyses on go/no-go and fast task RTV data, across task conditions manipulating rewards and event rate, from a population-based twin sample (n=1314) and an ADHD and control sibling-pair sample (n=1265). RESULTS Phenotypic and genetic/familial correlations were consistently high (0.72-0.98) between RTV baseline and difference scores, across tasks, manipulations and samples. By contrast, correlations were low between RTV in the manipulated condition and difference scores. A comparison across two different go/no-go task RTV difference scores (slow-fast/slow-incentive) showed high phenotypic and genetic/familial overlap (r = 0.75-0.83). CONCLUSIONS Our finding that RTV difference scores measure largely the same etiological process as RTV under baseline condition supports theories emphasizing the malleability of the observed high RTV. Given the statistical shortcomings of difference scores, we recommend the use of RTV baseline scores for most analyses, including genetic analyses.
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Affiliation(s)
- J Kuntsi
- King's College London, MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, UK.
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Kraja AT, Borecki IB, Tsai MY, Ordovas JM, Hopkins PN, Lai CQ, Frazier-Wood AC, Straka RJ, Hixson JE, Province MA, Arnett DK. Genetic analysis of 16 NMR-lipoprotein fractions in humans, the GOLDN study. Lipids 2012. [PMID: 23192668 DOI: 10.1007/s11745-012-3740-8] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Sixteen nuclear magnetic resonance (NMR) spectroscopy lipoprotein measurements of more than 1,000 subjects of GOLDN study, at fasting and at 3.5 and 6 h after a postprandial fat (PPL) challenge at visits 2 and 4, before and after a 3 weeks Fenofibrate (FF) treatment, were included in 6 time-independent multivariate factor analyses. Their top 1,541 unique SNPs were assessed for association with GOLDN NMR-particles and classical lipids. Several SNPs with -log₁₀ p > 7.3 and MAF ≥ 0.10, mostly intergenic associated with NMR-single traits near genes FAM84B (8q24.21), CRIPT (2p21), ACOXL (2q13), BCL2L11 (2q13), PCDH10 (4q28.3), NXPH1 (7p22), and SLC24A4 (14q32.12) in association with NMR-LDLs; HOMER1 (5q14.2), KIT (4q11-q12), VSNL1 (2p24.3), QPRT (16p11.2), SYNPR (3p14.2), NXPH1 (7p22), NELL1 (11p15.1), and RUNX3 (1p36) with NMR-HDLs; and DOK5-CBLN4-MC3R (20q13), NELL1 (11p15.1), STXBP6 (14q12), APOB (2p24-p23), GPR133 (12q24.33), FAM84B (8q24.21) and NR5A2 (1q32.1) in association with NMR-VLDLs particles. NMR single traits associations produced 75 % of 114 significant candidates, 7 % belonged to classical lipids and 18 % overlapped, and 16 % matched for time of discovery between NMR- and classical traits. Five proxy genes, (ACOXL, FAM84B, NXPH1, STK40 and VAPA) showed pleiotropic effects. While tagged for significant associations in our study and with some extra evidence from the literature, candidates as CBNL4, FAM84B, NXPH1, SLC24A4 remain unclear for their functional relation to lipid metabolism. Although GOLDN study is one of the largest in studying PPL and FF treatment effects, the relatively small samples (over 700-1,000 subjects) in association tests appeals for a replication of such a study. Thus, further investigation is needed.
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Affiliation(s)
- Aldi T Kraja
- Division of Statistical Genomics, Washington University School of Medicine, 4444 Forest Park Ave, Campus Box 8506, St. Louis, MO 63108, USA.
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Banaschewski T, Jennen-Steinmetz C, Brandeis D, Buitelaar JK, Kuntsi J, Poustka L, Sergeant JA, Sonuga-Barke EJ, Frazier-Wood AC, Albrecht B, Chen W, Uebel H, Schlotz W, van der Meere JJ, Gill M, Manor I, Miranda A, Mulas F, Oades RD, Roeyers H, Rothenberger A, Steinhausen HC, Faraone SV, Asherson P. Neuropsychological correlates of emotional lability in children with ADHD. J Child Psychol Psychiatry 2012; 53:1139-48. [PMID: 22882111 PMCID: PMC3472099 DOI: 10.1111/j.1469-7610.2012.02596.x] [Citation(s) in RCA: 77] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
BACKGROUND Emotional lability (EL) is commonly seen in patients with attention-deficit/hyperactivity disorder (ADHD). The reasons for this association remain currently unknown. To address this question, we examined the relationship between ADHD and EL symptoms, and performance on a range of neuropsychological tasks to clarify whether EL symptoms are predicted by particular cognitive and/or motivational dysfunctions and whether these associations are mediated by the presence of ADHD symptoms. METHODS A large multi-site sample of 424 carefully diagnosed ADHD cases and 564 unaffected siblings and controls aged 6-18 years performed a broad neuropsychological test battery, including a Go/No-Go Task, a warned four-choice Reaction Time task, the Maudsley Index of Childhood Delay Aversion and Digit span backwards. Neuropsychological variables were aggregated as indices of processing speed, response variability, executive functions, choice impulsivity and the influence of energetic and/or motivational factors. EL and ADHD symptoms were regressed on each neuropsychological variable in separate analyses controlling for age, gender and IQ, and, in subsequent regression analyses, for ADHD and EL symptoms respectively. RESULTS Neuropsychological variables significantly predicted ADHD and EL symptoms with moderate-to-low regression coefficients. However, the association between neuropsychological parameters on EL disappeared entirely when the effect of ADHD symptoms was taken into account, revealing that the association between the neuropsychological performance measures and EL is completely mediated statistically by variations in ADHD symptoms. Conversely, neuropsychological effects on ADHD symptoms remained after EL symptom severity was taken into account. CONCLUSIONS The neuropsychological parameters examined, herein, predict ADHD more strongly than EL. They cannot explain EL symptoms beyond what is already accounted for by ADHD symptom severity. The association between EL and ADHD cannot be explained by these cognitive or motivational deficits. Alternative mechanisms, including overlapping genetic influences (pleiotropic effects) and/or alternative neuropsychological processes need to be considered.
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Affiliation(s)
- Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany.
| | - Christine Jennen-Steinmetz
- Department of Biostatistics, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Germany
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Germany,Department of Child and Adolescent Psychiatry, University of Zürich, Switzerland
| | - Jan K. Buitelaar
- Department of Cognitive Neuroscience, Radboud University Nijmegen Medical Center, Karakter Child and Adolescent Psychiatry University Center, Nijmegen, Netherlands
| | - Jonna Kuntsi
- King’s College London, MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, London, UK
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Germany
| | - Joseph A. Sergeant
- Department of Clinical Neuropsychology, Free University Amsterdam, Netherlands
| | - Edmund J. Sonuga-Barke
- Developmental Brain Behaviour Laboratory, School of Psychology, University of Southampton, Southampton, UK,Department of Clinical & Experimental Psychology, Ghent University, Belgium
| | | | - Björn Albrecht
- Child and Adolescent Psychiatry, University of Göttingen, Germany
| | - Wai Chen
- Division of Clinical Neuroscience, School of Medicine, University of Southampton, Southampton, UK
| | - Henrik Uebel
- Child and Adolescent Psychiatry, University of Göttingen, Germany
| | - Wolff Schlotz
- Developmental Brain Behaviour Laboratory, School of Psychology, University of Southampton, Southampton, UK
| | | | - Michael Gill
- Department of Psychiatry, Trinity Centre for Health Sciences, St. James’s Hospital, Dublin, Ireland
| | - Iris Manor
- ADHD Unit, Geha Mental Health Centre, Petach-Tiqva, Israel
| | - Ana Miranda
- Department of Developmental and Educational Psychology, University of Valencia, Spain
| | - Fernando Mulas
- Neuropediatrics Unit, La Fé University Hospital, Valencia, Spain
| | - Robert D. Oades
- Clinic for Child and Adolescent Psychiatry, University of Duisburg-Essen, Germany
| | - Herbert Roeyers
- Department of Clinical & Experimental Psychology, Ghent University, Belgium
| | | | - Hans-Christoph Steinhausen
- Department of Child and Adolescent Psychiatry, University of Zürich, Switzerland,Clinical Psychology and Epidemiology, Institute of Psychology, University of Basel, Switzerland,Aalborg Psychiatric Hospital, Aarhus University Hospital, Aalborg, Denmark
| | - Stephen V. Faraone
- Departments of Psychiatry and of Neuroscience and Physiology. SUNY Upstate Medical University, USA
| | - Philip Asherson
- King’s College London, MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, London, UK
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Aslibekyan S, Goodarzi MO, Frazier-Wood AC, Yan X, Irvin MR, Kim E, Tiwari HK, Guo X, Straka RJ, Taylor KD, Tsai MY, Hopkins PN, Korenman SG, Borecki IB, Chen YDI, Ordovas JM, Rotter JI, Arnett DK. Variants identified in a GWAS meta-analysis for blood lipids are associated with the lipid response to fenofibrate. PLoS One 2012; 7:e48663. [PMID: 23119086 PMCID: PMC3485381 DOI: 10.1371/journal.pone.0048663] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2012] [Accepted: 09/28/2012] [Indexed: 12/23/2022] Open
Abstract
A recent large-scale meta-analysis of genome-wide studies has identified 95 loci, 59 of them novel, as statistically significant predictors of blood lipid traits; we tested whether the same loci explain the observed heterogeneity in response to lipid-lowering therapy with fenofibrate. Using data from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, n = 861) we fit linear mixed models with the genetic markers as predictors and high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, total cholesterol, and triglyceride concentrations as outcomes. For all four traits, we analyzed both baseline levels and changes in response to treatment with fenofibrate. For the markers that were significantly associated with fenofibrate response, we fit additional models evaluating potential epistatic interactions. All models were adjusted for age, sex, and study center as fixed effects, and pedigree as a random effect. Statistically significant associations were observed between the rs964184 polymorphism near APOA1 (P-value≤0.0001) and fenofibrate response for HDL and triglycerides. The association was replicated in the Pharmacogenetics of Hypertriglyceridemia in Hispanics study (HyperTG, n = 267). Suggestive associations with fenofibrate response were observed for markers in or near PDE3A, MOSC1, FLJ36070, CETP, the APOE-APOC1-APOC4-APOC2, and CILP2. Finally, we present strong evidence for epistasis (P-value for interaction = 0.0006 in GOLDN, 0.05 in HyperTG) between rs10401969 near CILP2 and rs4420638 in the APOE-APOC1-APOC4-APOC2 cluster with total cholesterol response to fenofibrate. In conclusion, we present evidence linking several novel and biologically relevant genetic polymorphisms to lipid lowering drug response, as well as suggesting novel gene-gene interactions in fenofibrate pharmacogenetics.
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Affiliation(s)
- Stella Aslibekyan
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
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48
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Pinto R, Rijsdijk F, Frazier-Wood AC, Asherson P, Kuntsi J. Bigger families fare better: a novel method to estimate rater contrast effects in parental ratings on ADHD symptoms. Behav Genet 2012; 42:875-85. [PMID: 23053732 DOI: 10.1007/s10519-012-9561-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2011] [Accepted: 08/22/2012] [Indexed: 10/27/2022]
Abstract
Many twin studies on parental ratings of attention deficit hyperactivity disorder (ADHD) symptoms report low or negative DZ correlations. The observed differences in MZ and DZ variances indicate sibling contrast effects, which appear to reflect a bias in parent ratings. Knowledge of the factors that contribute to this rater contrast effect is, however, limited. Using parent-rated ADHD symptoms from the Twins' Early Development Study and a novel application of a twin model, we explored a range of socio-demographic variables (ethnicity, socio-economic status, and family size), as potential contributors to contrast effects and their interactive effect with gender composition of twin pairs. Gender did moderate contrast effects but only in DZ opposite-sex twin pairs. Family size also showed a moderating effect on rater contrast effects, which was further modified by gender. We further observed an effect of rating scale, with the DSM-IV ADHD subscale of the Revised Conners' Parent Rating Scale more resistant to contrast effects than shorter scales of ADHD symptoms. The improved identification of situations where the accuracy of the most common informant of childhood ADHD symptoms-parents-is compromised as a result of rater bias, might have implications for future research on ADHD.
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Affiliation(s)
- R Pinto
- King's College London, MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, London, UK.
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Loop MS, Frazier-Wood AC, Thomas AS, Dhurandhar EJ, Shikany JM, Gadbury GL, Allison DB. Submitted for your consideration: potential advantages of a novel clinical trial design and initial patient reaction. Front Genet 2012; 3:145. [PMID: 22891075 PMCID: PMC3413942 DOI: 10.3389/fgene.2012.00145] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2012] [Accepted: 07/17/2012] [Indexed: 01/29/2023] Open
Abstract
In many circumstances, individuals do not respond identically to the same treatment. This phenomenon, which is called treatment response heterogeneity (TRH), appears to be present in treatments for many conditions, including obesity. Estimating the total amount of TRH, predicting an individual's response, and identifying the mediators of TRH are of interest to biomedical researchers. Clinical investigators and physicians commonly postulate that some of these mediators could be genetic. Current designs can estimate TRH as a function of specific, measurable observed factors; however, they cannot estimate the total amount of TRH, nor provide reliable estimates of individual persons' responses. We propose a new repeated randomizations design (RRD), which can be conceived as a generalization of the Balaam design, that would allow estimates of that variability and facilitate estimation of the total amount of TRH, prediction of an individual's response, and identification of the mediators of TRH. In a pilot study, we asked 118 subjects entering a weight loss trial for their opinion of the RRD, and they stated a preference for the RRD over the conventional two-arm parallel groups design. Research is needed as to how the RRD will work in practice and its relative statistical properties, and we invite dialog about it.
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Affiliation(s)
- Matthew Shane Loop
- Section on Statistical Genetics, Department of Biostatistics, Ryals School of Public Health, University of Alabama at Birmingham Birmingham, AL, USA
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Aslibekyan S, Irvin MM, Frazier-Wood AC, Straka RJ, Borecki IB, Tiwari HK, Tsai MY, Hopkins PN, Ordovas JM, Mayer USDA HNRCA J, Arnett DK. Abstract 141: APOA1, CETP, and CILP2 Variants Modify the Lipid Response to Fenofibrate: Genetics of Lipid Lowering and Diet Network. Arterioscler Thromb Vasc Biol 2012. [DOI: 10.1161/atvb.32.suppl_1.a141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Introduction:
Despite the widespread use of fibrates in treatment of dyslipidemia, the observed response is highly heterogeneous, suggesting a role for genetic determinants. Whether replicated variants associated with blood lipids identified by genome wide association studies (GWAS) are also associated with lipid response to fenofibrate is unknown.
Objectives:
To test if 95 genome-wide significant loci identified in a recent meta-analysis of blood lipids are associated with changes in high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), non-HDL-C, and triglycerides (TG) following 3 weeks of therapy with 160 mg of micronized fenofibrate.
Methods:
Using data from 861 European American Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) participants, we fit mixed linear models with baseline blood lipids and the post-to-pre fenofibrate treatment ratio of blood lipid levels as outcomes, the corresponding genetic markers from the published meta-analysis as predictors, and age, sex, pedigree, and ancestry as assessed by principal components as covariates. A Bonferroni correction was applied to adjust for multiple comparisons. Least square means were used to report the direction of fenofibrate-induced changes by genotype.
Results:
We observed statistically significant associations between
rs964184
, a variant near the APOA1 gene, and baseline HDL-C (P<0.0001) and baseline TG (P<0.0001), as well as with diminished response to fenofibrate as evidenced by a smaller increase in HDL-C (P<0.0001) and a smaller decrease in TG (P=0.0001) per each copy of the variant allele. Additionally, we report suggestive associations of rs3764261 locus in the CETP gene and the rs10401969 locus in the CILP2 gene with decreased fenofibrate response as measured by changes in LDL-C (P=0.0003 and 0.02, respectively) and non-HDL-C (P=0.004 and 0.005, respectively).
Conclusions:
We have identified several novel biologically relevant loci associated with baseline blood lipids and fenofibrate-induced changes in blood lipids.
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