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Bui H, Keshawarz A, Wang M, Lee M, Ratliff SM, Lin L, Birditt KS, Faul JD, Peters A, Gieger C, Delerue T, Kardia SLR, Zhao W, Guo X, Yao J, Rotter JI, Li Y, Liu X, Liu D, Tavares JF, Pehlivan G, Breteler MMB, Karabegovic I, Ochoa-Rosales C, Voortman T, Ghanbari M, van Meurs JBJ, Nasr MK, Dörr M, Grabe HJ, London SJ, Teumer A, Waldenberger M, Weir DR, Smith JA, Levy D, Ma J, Liu C. Association analysis between an epigenetic risk score and blood pressure. RESEARCH SQUARE 2024:rs.3.rs-4243866. [PMID: 38699335 PMCID: PMC11065078 DOI: 10.21203/rs.3.rs-4243866/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Background Epigenome-wide association studies have revealed multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases. Results We generated an alcohol consumption epigenetic risk score (ERS) based on previously reported 144 alcohol-associated CpGs and examined the association of the ERS with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension (HTN) in 3,898 Framingham Heart Study (FHS) participants. We found an association of alcohol intake with the ERS in the meta-analysis with 0.09 units higher ERS per drink consumed per day (p < 0.0001). Cross-sectional analyses in FHS revealed that a one-unit increment of the ERS was associated with 1.93 mm Hg higher SBP (p = 4.64E-07), 0.68 mm Hg higher DBP (p = 0.006), and an odds ratio of 1.78 for HTN (p < 2E-16). Meta-analysis of the cross-sectional association of the ERS with BP traits in eight independent external cohorts (n = 11,544) showed similar relationships with blood pressure levels, i.e., a one-unit increase in ERS was associated with 0.74 (p = 0.002) and 0.50 (p = 0.0006) mm Hg higher SBP and DBP, but could not confirm the association with hypertension. Longitudinal analyses in FHS (n = 3,260) and five independent external cohorts (n = 4,021) showed that the baseline ERS was not associated with a change in blood pressure over time or with incident HTN. Conclusions Our findings provide proof-of-concept that utilizing an ERS is a useful approach to capture the recent health consequences of lifestyle behaviors such as alcohol consumption.
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Affiliation(s)
| | | | | | - Mikyeong Lee
- National Institute of Environmental Health Sciences
| | | | | | | | | | - Annette Peters
- Helmholtz Munich, German Research Center for Environmental Health
| | - Christian Gieger
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance
| | - Thomas Delerue
- Helmholtz Munich, German Research Center for Environmental Health
| | | | | | - Xiuqing Guo
- Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center
| | - Jie Yao
- Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center
| | - Jerome I Rotter
- Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center
| | - Yi Li
- Boston University School of Public Health
| | - Xue Liu
- Boston University School of Public Health
| | - Dan Liu
- German Center for Neurodegenerative Diseases
| | | | | | | | | | | | | | | | | | | | - Marcus Dörr
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald
| | | | | | | | - Melanie Waldenberger
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance
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Bui H, Keshawarz A, Wang M, Lee M, Ratliff SM, Lin L, Birditt KS, Faul JD, Peters A, Gieger C, Delerue T, Kardia SLR, Zhao W, Guo X, Yao J, Rotter JI, Li Y, Liu X, Liu D, Tavares JF, Pehlivan G, Breteler MM, Karabegovic I, Ochoa-Rosales C, Voortman T, Ghanbari M, van Meurs JB, Nasr MK, Dörr M, Grabe HJ, London SJ, Teumer A, Waldenberger M, Weir DR, Smith JA, Levy D, Ma J, Liu C. Association analysis between an epigenetic alcohol risk score and blood pressure. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.29.24303545. [PMID: 38464320 PMCID: PMC10925472 DOI: 10.1101/2024.02.29.24303545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Background Epigenome-wide association studies have revealed multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases. Results We generated an alcohol consumption epigenetic risk score (ERS) based on previously reported 144 alcohol-associated CpGs and examined the association of the ERS with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension (HTN) in 3,898 Framingham Heart Study (FHS) participants. We found an association of alcohol intake with the ERS in the meta-analysis with 0.09 units higher ERS per drink consumed per day (p < 0.0001). Cross-sectional analyses in FHS revealed that a one-unit increment of the ERS was associated with 1.93 mm Hg higher SBP (p = 4.64E-07), 0.68 mm Hg higher DBP (p = 0.006), and an odds ratio of 1.78 for HTN (p < 2E-16). Meta-analysis of the cross-sectional association of the ERS with BP traits in eight independent external cohorts (n = 11,544) showed similar relationships with blood pressure levels, i.e., a one-unit increase in ERS was associated with 0.74 (p = 0.002) and 0.50 (p = 0.0006) mm Hg higher SBP and DBP, but could not confirm the association with hypertension. Longitudinal analyses in FHS (n = 3,260) and five independent external cohorts (n = 4,021) showed that the baseline ERS was not associated with a change in blood pressure over time or with incident HTN. Conclusions Our findings provide proof-of-concept that utilizing an ERS is a useful approach to capture the recent health consequences of lifestyle behaviors such as alcohol consumption.
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Affiliation(s)
- Helena Bui
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Amena Keshawarz
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Mengyao Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Mikyeong Lee
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Scott M. Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Lisha Lin
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Kira S. Birditt
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI
| | - Jessica D. Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Munich, German Research Center for Environmental Health, German
- Institute for Medical Informatics, Biometrics and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Christian Gieger
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Munich, German Research Center for Environmental Health, Bavaria, Germany
| | - Thomas Delerue
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Munich, German Research Center for Environmental Health, Bavaria, Germany
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Xiuqing Guo
- The Institute for Translational Genomics and Populations, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Jie Yao
- The Institute for Translational Genomics and Populations, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Populations, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Yi Li
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Xue Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Dan Liu
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Juliana F. Tavares
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Gökhan Pehlivan
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Monique M.B. Breteler
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Irma Karabegovic
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Carolina Ochoa-Rosales
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Centro de Vida Saludable de la Universidad de Concepción, Concepción, Chile
| | - Trudy Voortman
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Division of Human Nutrition and Health, Wageningen University and Research, Wageningen, The Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Joyce B.J. van Meurs
- Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Mohamed Kamal Nasr
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
| | - Marcus Dörr
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University Medicine, Greifswald, Germany
- German Center of Neurodegenerative Diseases (DZNE), Rostock/Greifswald, site Greifswald, Germany
| | - Stephanie J. London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland
| | - Melanie Waldenberger
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Munich, German Research Center for Environmental Health, Bavaria, Germany
| | - David R. Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI
| | - Daniel Levy
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Jiantao Ma
- Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Chunyu Liu
- Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
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Tio MC, Zhu X, Lirette S, Rule AD, Butler K, Hall ME, Dossabhoy NR, Mosley T, Shafi T. External Validation of a Novel Multimarker GFR Estimating Equation. KIDNEY360 2023; 4:1680-1689. [PMID: 37986202 PMCID: PMC10758515 DOI: 10.34067/kid.0000000000000304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 10/26/2023] [Indexed: 11/22/2023]
Abstract
Key Points Using multiple markers may improve GFR estimation especially in settings where creatinine and cystatin C are known to be limited. Panel eGFR is a novel multimarker eGFR equation consisting of age, sex, cystatin C, and nuclear magnetic resonance–measured creatinine, valine, and myo-inositol. eGFR-Cr and eGFR-Cr-CysC may underestimate measured GFR, while panel eGFR was unbiased among younger Black male individuals. Background Using multiple markers may improve accuracy in GFR estimation. We sought to externally validate and compare the performance of a novel multimarker eGFR (panel eGFR) equation among Black and White persons using the Genetic Epidemiology Network of Arteriopathy cohort. Methods We included 224 sex, race/ethnicity, and measured GFR (mGFR) category–matched persons, with GFR measured using urinary clearance of iothalamate. We calculated panel eGFR using serum creatinine, valine, myo-inositol, cystatin C, age, and sex. We compared its reliability with current eGFR equations (2021 CKD Epidemiology Collaboration creatinine [eGFR-Cr] and creatinine with cystatin C [eGFR-Cr-CysC]) using median bias, precision, and accuracy metrics. We evaluated each equation's performance in age, sex, and race subgroups. Results In the overall cohort, 49% were Black individuals, and mean mGFR was 79 ml/min per 1.73 m2. Panel eGFR overestimated mGFR (bias: −2.4 ml/min per 1.73 m2; 95% confidence interval [CI], −4.4 to −0.7), eGFR-Cr-CysC underestimated mGFR (bias: 4.8 ml/min per 1.73 m2; 95% CI, 2.1 to 6.7), while eGFR-Cr was unbiased (bias: 2.0 ml/min per 1.73 m2; 95% CI, −1.1 to 4.6). All equations had comparable accuracy. Among Black male individuals younger than 65 years, both eGFR-Cr (bias: 17.0 ml/min per 1.73 m2; 95% CI, 8.6 to 23.5) and eGFR-Cr-CysC (bias: 14.5 ml/min per 1.73 m2; 95% CI, 6.0 to 19.7) underestimated mGFR, whereas panel eGFR was unbiased (bias: 1.7 ml/min per 1.73 m2; 95% CI, −3.4 to 10.0). Metrics of accuracy for all eGFRs were acceptable in all subgroups except for panel eGFR in Black female individuals younger than 65 years (P30: 73.3%). Conclusions Panel eGFR can be used to estimate mGFR and may have utility among Black male individuals younger than 65 years where current CKD Epidemiology Collaboration equations are biased.
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Affiliation(s)
- Maria Clarissa Tio
- Division of Nephrology, Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi
| | - Xiaoqian Zhu
- Division of Nephrology, Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi
- Department of Data Science, Bower School of Population Health, University of Mississippi Medical Center, Jackson, Mississippi
| | - Seth Lirette
- Department of Data Science, Bower School of Population Health, University of Mississippi Medical Center, Jackson, Mississippi
| | - Andrew D. Rule
- Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota
| | - Kenneth Butler
- The Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, Mississippi
| | - Michael E. Hall
- Division of Cardiology, Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi
| | - Neville R. Dossabhoy
- Division of Nephrology, Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi
| | - Thomas Mosley
- The Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, Mississippi
| | - Tariq Shafi
- Division of Nephrology, Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi
- Division of Kidney Diseases, Hypertension & Transplantation, Department of Medicine, Houston Methodist Hospital, Houston, Texas
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4
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Abi Saleh R, Lirette ST, Benjamin EJ, Fornage M, Turner ST, Hammond PI, Mosley TH, Griswold ME, Windham BG. Mediation effects of diabetes and inflammation on the relationship of obesity to cognitive impairment in African Americans. J Am Geriatr Soc 2022; 70:3021-3029. [PMID: 35941823 PMCID: PMC9639783 DOI: 10.1111/jgs.17985] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 05/31/2022] [Accepted: 06/26/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND Whether diabetes and adipokine-driven inflammation explain the association of obesity to cognitive impairment is unknown. METHODS Structural equation models estimated the total effects of waist circumference on cognitive outcomes among African American participants cross-sectionally (index exam) and longitudinally. Total effects were deconstructed into direct pathways of waist circumference to cognitive impairment and indirect mediation pathways through leptin, soluble tumor necrosis factor receptor 2 (sTNFR2), and diabetes. Waist circumference, leptin, and sTNFR2 were standardized. Cognitive impairment was defined as MMSE <21 or a z-score < -1.5 standard deviation (SD). Incident cognitive impairment was defined among those without cognitive impairment at the index exam as follow-up MMSE<21, z- score < -1.5, MMSE decline >1 point/year, or z-score decline of >0.1 SD/year. RESULTS Among 1008 participants (70% women, mean age 62.9 years, 14.5% with obesity, 26% with diabetes), 132 (13%) had baseline cognitive impairment. Each SD higher waist circumference was associated with higher odds of cognitive impairment, odds ratio (OR) = 1.63; (95% confidence interval: 1.17, 2.24), with mediating pathways explaining 65% of the total effect (58% from diabetes; 7% from inflammation). At follow-up (mean 6.8 years), 106 of 535 (19.8%) had developed cognitive impairment. Each SD higher waist circumference was associated with higher odds of developing cognitive impairment (OR = 1.87; 95%CI: 1.18, 2.74); the direct effect of waist circumference explained 37% of the total effect and mediating pathways explained 63% (61% from diabetes; 2% from inflammation), although individual pathways were not statistically supported in the smaller sample. CONCLUSION Diabetes, and to a lesser degree, adiposity-driven inflammation, appear to explain a substantial proportion of abdominal adiposity relationships with cognitive impairment. The impact of preventing and treating obesity on cognitive outcomes merits study.
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Affiliation(s)
- Rola Abi Saleh
- Department of Medicine, Division of Geriatrics, University of Mississippi Medical Center, Jackson, Mississippi
| | - Seth T. Lirette
- Department of Data Science, University of Mississippi Medical Center, Jackson, Mississippi
| | - Emelia J. Benjamin
- Department of Medicine, Boston University School of Medicine and Boston Medical Center, and Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
| | - Myriam Fornage
- Institute of Molecular Medicine, Health Science Center at Houston, University of Texas
| | | | - Pamela I. Hammond
- Department of Endocrinology, Diabetes and Nutrition Research, Mayo Clinic, Rochester, Minnesota
| | - Thomas H. Mosley
- Department of Medicine, Division of Geriatrics, University of Mississippi Medical Center, Jackson, Mississippi
| | - Michael E. Griswold
- Department of Medicine, Division of Geriatrics, University of Mississippi Medical Center, Jackson, Mississippi
| | - B. Gwen Windham
- Department of Medicine, Division of Geriatrics, University of Mississippi Medical Center, Jackson, Mississippi
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5
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DiCorpo D, LeClair J, Cole JB, Sarnowski C, Ahmadizar F, Bielak LF, Blokstra A, Bottinger EP, Chaker L, Chen YDI, Chen Y, de Vries PS, Faquih T, Ghanbari M, Gudmundsdottir V, Guo X, Hasbani NR, Ibi D, Ikram MA, Kavousi M, Leonard HL, Leong A, Mercader JM, Morrison AC, Nadkarni GN, Nalls MA, Noordam R, Preuss M, Smith JA, Trompet S, Vissink P, Yao J, Zhao W, Boerwinkle E, Goodarzi MO, Gudnason V, Jukema JW, Kardia SL, Loos RJ, Liu CT, Manning AK, Mook-Kanamori D, Pankow JS, Picavet HSJ, Sattar N, Simonsick EM, Verschuren WM, Willems van Dijk K, Florez JC, Rotter JI, Meigs JB, Dupuis J, Udler MS. Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts. Diabetes Care 2022; 45:674-683. [PMID: 35085396 PMCID: PMC8918228 DOI: 10.2337/dc21-1395] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 12/15/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and outcomes. In previous work, we investigated the genetic basis of this heterogeneity by clustering 94 T2D genetic loci using their associations with 47 diabetes-related traits and identified five clusters, termed β-cell, proinsulin, obesity, lipodystrophy, and liver/lipid. The relationship between these clusters and individual-level metabolic disease outcomes has not been assessed. RESEARCH DESIGN AND METHODS Here we constructed individual-level partitioned polygenic scores (pPS) for these five clusters in 12 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (n = 454,193) and tested for cross-sectional association with T2D-related outcomes, including blood pressure, renal function, insulin use, age at T2D diagnosis, and coronary artery disease (CAD). RESULTS Despite all clusters containing T2D risk-increasing alleles, they had differential associations with metabolic outcomes. Increased obesity and lipodystrophy cluster pPS, which had opposite directions of association with measures of adiposity, were both significantly associated with increased blood pressure and hypertension. The lipodystrophy and liver/lipid cluster pPS were each associated with CAD, with increasing and decreasing effects, respectively. An increased liver/lipid cluster pPS was also significantly associated with reduced renal function. The liver/lipid cluster includes known loci linked to liver lipid metabolism (e.g., GCKR, PNPLA3, and TM6SF2), and these findings suggest that cardiovascular disease risk and renal function may be impacted by these loci through their shared disease pathway. CONCLUSIONS Our findings support that genetically driven pathways leading to T2D also predispose differentially to clinical outcomes.
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Affiliation(s)
- Daniel DiCorpo
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Jessica LeClair
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Joanne B. Cole
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Division of Endocrinology, Boston Children’s Hospital, Boston, MA
| | - Chloé Sarnowski
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Fariba Ahmadizar
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Julius Global Health, University Utrecht Medical Center, Utrecht, the Netherlands
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Anneke Blokstra
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Erwin P. Bottinger
- Hasso Plattner Institute Digital Health, Potsdam, Germany
- Mount Sinai Health System, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Layal Chaker
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Internal Medicine, Division of Endocrinology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Yii-Der I. Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Ye Chen
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA
| | - Paul S. de Vries
- 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
| | - Tariq Faquih
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Valborg Gudmundsdottir
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Natalie R. Hasbani
- 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
| | - Dorina Ibi
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Hampton L. Leonard
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD
- Data Tecnica International, Glen Echo, MD
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD
| | - Aaron Leong
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
| | - Josep M. Mercader
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Alanna C. Morrison
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA
| | - Girish N. Nadkarni
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Mike A. Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD
- Data Tecnica International, Glen Echo, MD
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD
| | - Raymond Noordam
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Michael Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
- Institute for Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI
| | - Stella Trompet
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Petra Vissink
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Eric Boerwinkle
- 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
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Mark O. Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - J. Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands
- Netherlands Heart Institute, Utrecht, the Netherlands
| | - Sharon L.R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI
| | - Ruth J.F. Loos
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Alisa K. Manning
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA
| | - Dennis Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - James S. Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN
| | - H. Susan J. Picavet
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Naveed Sattar
- British Heart Foundation Glasgow Cardiovascular Research Centre, Faculty of Medicine, Glasgow, U.K
| | - Eleanor M. Simonsick
- Translational Gerontology Branch, Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - W.M. Monique Verschuren
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Jose C. Florez
- Department of Medicine, Harvard Medical School, Boston, MA
- Endocrine Division, Massachusetts General Hospital, Boston, MA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - James B. Meigs
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Miriam S. Udler
- Programs in Metabolism and Medical & Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Endocrine Division, Massachusetts General Hospital, Boston, MA
- Harvard Medical School, Boston, MA
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6
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Oshunbade AA, Lirette ST, Windham BG, Shafi T, Hamid A, Gbadamosi SO, Tin A, Yimer WK, Tibuakuu M, Clark D, Kamimura D, Lutz EA, Mentz RJ, Fox ER, Butler J, Butler KR, Garovic VD, Turner ST, Mosley TH, Hall ME. Hypertensive Diseases in Pregnancy and Kidney Function Later in Life: The Genetic Epidemiology Network of Arteriopathy (GENOA) Study. Mayo Clin Proc 2022; 97:78-87. [PMID: 34565606 PMCID: PMC9031057 DOI: 10.1016/j.mayocp.2021.07.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 05/27/2021] [Accepted: 07/13/2021] [Indexed: 01/03/2023]
Abstract
OBJECTIVE To evaluate the relationship between hypertensive diseases in pregnancy and kidney function later in life. METHODS We evaluated measured glomerular filtration rate (mGFR) using iothalamate urinary clearance in 725 women of the Genetic Epidemiology Network of Arteriopathy (GENOA) study. Women were classified by self-report as nulliparous (n=62), a history of normotensive pregnancies (n=544), a history of hypertensive pregnancies (n=102), or a history of pre-eclampsia (n=17). We compared adjusted associations among these four groups with mGFR using generalized estimating equations to account for familial clustering. Chronic kidney disease (CKD) was defined as mGFR of less than 60 mL/min per 1.73 m2 or urinary albumin-creatinine ratio (UACR) greater than or equal to 30 mg/g. RESULTS Among women with kidney function measurements (mean age, 59±9 years, 52.9% African American), those with a history of hypertensive pregnancy had lower mGFR (-4.66 ml/min per 1.73 m2; 95% CI, -9.12 to -0.20) compared with women with a history of normotensive pregnancies. Compared with women with a history of normotensive pregnancies, women with a history of hypertensive pregnancy also had higher odds of mGFR less than 60 ml/min per 1.73 m2 (odds ratio, 2.09; 95% CI, 1.21 to 3.60). Additionally, women with a history of hypertensive pregnancy had greater odds for chronic kidney disease (odds ratio, 4.89; 95% CI, 1.55 to 15.44), after adjusting for age, race, education, smoking history, hypertension, body mass index, and diabetes. CONCLUSION A history of hypertension in pregnancy is an important prognostic risk factor for kidney disease. To our knowledge, this is the first and largest investigation showing the association between hypertensive diseases in pregnancy and subsequent kidney disease using mGFR in a large biracial cohort.
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Affiliation(s)
- Adebamike A Oshunbade
- University of Mississippi Medical Center, Department of Medicine, Division of Cardiology, Jackson, MS
| | | | - B Gwen Windham
- Division of Geriatrics, Jackson, MS; MIND Center, University of Mississippi Medical Center, Jackson, MS
| | - Tariq Shafi
- Division of Nephrology and Hypertension, Jackson, MS
| | - Arsalan Hamid
- University of Mississippi Medical Center, Department of Medicine, Division of Cardiology, Jackson, MS
| | - Semiu O Gbadamosi
- Florida International University, Department of Epidemiology, Miami, FL
| | - Adrienne Tin
- Division of Geriatrics, Jackson, MS; MIND Center, University of Mississippi Medical Center, Jackson, MS
| | | | - Martin Tibuakuu
- Johns Hopkins University School of Medicine, Department of Cardiology, Baltimore, MD
| | - Donald Clark
- University of Mississippi Medical Center, Department of Medicine, Division of Cardiology, Jackson, MS
| | - Daisuke Kamimura
- University of Mississippi Medical Center, Department of Medicine, Division of Cardiology, Jackson, MS; Yokohama City University Graduate School of Medicine, Department of Medical Science and Cardiorenal Medicine, Yokohama, Japan
| | | | - Robert J Mentz
- Duke University Medical Center, Duke Clinical Research Institute, Durham, NC
| | - Ervin R Fox
- University of Mississippi Medical Center, Department of Medicine, Division of Cardiology, Jackson, MS
| | - Javed Butler
- University of Mississippi Medical Center, Department of Medicine, Division of Cardiology, Jackson, MS
| | - Kenneth R Butler
- Division of Geriatrics, Jackson, MS; MIND Center, University of Mississippi Medical Center, Jackson, MS
| | - Vesna D Garovic
- Mayo Clinic, Division of Nephrology and Hypertension, Rochester, MN; Department of Obstetrics and Gynecology, Rochester, MN
| | - Stephen T Turner
- Mayo Clinic, Division of Nephrology and Hypertension, Rochester, MN
| | - Thomas H Mosley
- Division of Geriatrics, Jackson, MS; MIND Center, University of Mississippi Medical Center, Jackson, MS
| | - Michael E Hall
- University of Mississippi Medical Center, Department of Medicine, Division of Cardiology, Jackson, MS.
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7
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Lu Y, Dimitrov L, Chen SH, Bielak LF, Bis JC, Feitosa MF, Lu L, Kavousi M, Raffield LM, Smith AV, Wang L, Weiss S, Yao J, Zhu J, Gudmundsson EF, Gudmundsdottir V, Bos D, Ghanbari M, Ikram MA, Hwang SJ, Taylor KD, Budoff MJ, Gíslason GK, O’Donnell CJ, An P, Franceschini N, Freedman BI, Fu YP, Guo X, Heiss G, Kardia SL, Wilson JG, Langefeld CD, Schminke U, Uitterlinden AG, Lange LA, Peyser PA, Gudnason VG, Psaty BM, Rotter JI, Bowden DW, Ng MCY. Multiethnic Genome-Wide Association Study of Subclinical Atherosclerosis in Individuals With Type 2 Diabetes. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2021; 14:e003258. [PMID: 34241534 PMCID: PMC8435075 DOI: 10.1161/circgen.120.003258] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 06/20/2021] [Indexed: 11/16/2022]
Abstract
BACKGROUND Coronary artery calcification (CAC) and carotid artery intima-media thickness (cIMT) are measures of subclinical atherosclerosis in asymptomatic individuals and strong risk factors for cardiovascular disease. Type 2 diabetes (T2D) is an independent cardiovascular disease risk factor that accelerates atherosclerosis. METHODS We performed meta-analyses of genome-wide association studies in up to 2500 T2D individuals of European ancestry (EA) and 1590 T2D individuals of African ancestry with or without exclusion of prevalent cardiovascular disease, for CAC measured by cardiac computed tomography, and 3608 individuals of EA and 838 individuals of African ancestry with T2D for cIMT measured by ultrasonography within the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium. RESULTS We replicated 2 loci (rs9369640 and rs9349379 near PHACTR1 and rs10757278 near CDKN2B) for CAC and one locus for cIMT (rs7412 and rs445925 near APOE-APOC1) that were previously reported in the general EA populations. We identified one novel CAC locus (rs8000449 near CSNK1A1L/LINC00547/POSTN at 13q13.3) at P=2.0×10-8 in EA. No additional loci were identified with the meta-analyses of EA and African ancestry. The expression quantitative trait loci analysis with nearby expressed genes derived from arterial wall and metabolic tissues from the Genotype-Tissue Expression project pinpoints POSTN, encoding a matricellular protein involved in bone formation and bone matrix organization, as the potential candidate gene at this locus. In addition, we found significant associations (P<3.1×10-4) for 3 previously reported coronary artery disease loci for these subclinical atherosclerotic phenotypes (rs2891168 near CDKN2B-AS1 and rs11170820 near FLJ12825 for CAC, and rs7412 near APOE for cIMT). CONCLUSIONS Our results provide potential biological mechanisms that could link CAC and cIMT to increased cardiovascular disease risk in individuals with T2D.
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Affiliation(s)
- Yingchang Lu
- Vanderbilt Genetic Institute, Division of Genetic Medicine,
Vanderbilt University Medical Center, Nashville, TN
| | - Latchezar Dimitrov
- Center for Precision Medicine, Wake Forest School of
Medicine, Winston-Salem, NC
| | - Shyh-Huei Chen
- Department of Biostatistics & Data Science, Wake Forest
School of Medicine, Winston-Salem, NC
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health,
University of Michigan, Ann Arbor, MI
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Departments of
Medicine, Epidemiology & Health Services, University of Washington, Seattle,
WA
| | - Mary F. Feitosa
- Division of Statistical Genomics, Department of Genetics,
Washington University School of Medicine, Farrell Learning Center, St Louis,
MO
| | - Lingyi Lu
- Department of Biostatistics & Data Science, Wake Forest
School of Medicine, Winston-Salem, NC
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus Medical Centre,
Rotterdam, the Netherlands
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina,
Chapel Hill, NC
| | - Albert V. Smith
- Faculty of Medicine, University of Iceland, Reykjavik &
Icelandic Heart Association, Kopavogur, Iceland & Department of Biostatistics,
School of Public Health, University of Michigan, Ann Arbor, MI
| | - Lihua Wang
- Division of Statistical Genomics, Department of Genetics,
Washington University School of Medicine, Farrell Learning Center, St Louis,
MO
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional
Genomics, Department of Functional Genomics, University of Greifswald &
University Medicine Greifswald, Greifswald & DZHK (German Centre for
Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
| | - Jie Yao
- The Institute for Translational Genomics and Population
Sciences & Department of Pediatrics, The Lundquist Institute for Biomedical
Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Jiaxi Zhu
- Division of Statistical Genomics, Department of Genetics,
Washington University School of Medicine, Farrell Learning Center, St Louis,
MO
| | - Elias F. Gudmundsson
- Faculty of Medicine, University of Iceland, Reykjavik
& Icelandic Heart Association, Kopavogur, Iceland
| | - Valborg Gudmundsdottir
- Faculty of Medicine, University of Iceland, Reykjavik
& Icelandic Heart Association, Kopavogur, Iceland
| | - Daniel Bos
- Department of Epidemiology, Erasmus Medical Centre &
Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center
Rotterdam, Rotterdam, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus Medical Centre,
Rotterdam, the Netherlands
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus Medical Centre,
Rotterdam, the Netherlands
| | - Shih-Jen Hwang
- The Population Sciences Branch, Division of Intramural
Research, National Heart, Lung and Blood Institute, National Institutes of Health,
Bethesda, MD & The Framingham Heart Study, National Heart, Lung and Blood
Institute, National Institutes of Health, Framingham, MA
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population
Sciences & Department of Pediatrics, The Lundquist Institute for Biomedical
Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Matthew J. Budoff
- Division of Cardiology, Lundquist Institute at
Harbor-UCLA Medical Center, Torrance, CA
| | - Gauti K. Gíslason
- Faculty of Medicine, University of Iceland, Reykjavik
& Icelandic Heart Association, Kopavogur, Iceland
| | - Christopher J. O’Donnell
- VA Boston Healthcare System & Department of Medicine,
Brigham Women’s Hospital & Department of Medicine, Harvard Medical
School, Boston, MA
| | - Ping An
- Division of Statistical Genomics, Department of Genetics,
Washington University School of Medicine, Farrell Learning Center, St Louis,
MO
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina,
Chapel Hill, NC
| | - Barry I. Freedman
- Department of Internal Medicine, Wake Forest School of
Medicine, Winston-Salem, NC
| | - Yi-Ping Fu
- The Framingham Heart Study, National Heart, Lung and
Blood Institute, National Institutes of Health, Framingham, MA & Office of
Biostatistics Research, National Heart, Lung, and Blood Institute, National
Institutes of Health, Bethesda, MD
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population
Sciences & Department of Pediatrics, The Lundquist Institute for Biomedical
Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Gerardo Heiss
- Department of Epidemiology, University of North Carolina,
Chapel Hill, NC
| | - Sharon L.R. Kardia
- Department of Epidemiology, School of Public Health,
University of Michigan, Ann Arbor, MI
| | - James G. Wilson
- Department of Physiology and Biophysics, University of
Mississippi Medical Center, Jackson, MS & Department of Cardiology, Beth Israel
Deaconess Medical Center, Boston, MA
| | - Carl D. Langefeld
- Center for Precision Medicine & Department of
Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem,
NC
| | - Ulf Schminke
- Department of Neurology, University Medicine Greifswald,
Greifswald, Germany
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus Medical Centre &
Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam,
Rotterdam, the Netherlands
| | - Leslie A. Lange
- Division of Biomedical Informatics and Personalized
Medicine, School of Medicine, University of Colorado, Anschutz Medical Campus,
Aurora, CO
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public Health,
University of Michigan, Ann Arbor, MI
| | - Vilmundur G. Gudnason
- Faculty of Medicine, University of Iceland, Reykjavik
& Icelandic Heart Association, Kopavogur, Iceland
| | - Bruce M. Psaty
- Departments of Epidemiology & Health Services,
University of Washington, Seattle, WA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population
Sciences & Department of Pediatrics, The Lundquist Institute for Biomedical
Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Donald W. Bowden
- Center for Precision Medicine & Department of
Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC
| | - Maggie CY Ng
- Vanderbilt Genetic Institute, Division of Genetic
Medicine, Vanderbilt University Medical Center, Nashville, TN & Center for
Precision Medicine, Wake Forest School of Medicine, Winston-Salem, NC
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8
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Palmer ND, Kahali B, Kuppa A, Chen Y, Du X, Feitosa MF, Bielak LF, O’Connell JR, Musani SK, Guo X, Smith AV, Ryan KA, Eirksdottir G, Allison MA, Bowden DW, Budoff MJ, Carr JJ, Chen YDI, Taylor KD, Correa A, Crudup BF, Halligan B, Yang J, Kardia SLR, Launer LJ, Fu YP, Mosley TH, Norris JM, Terry JG, O’Donnell CJ, Rotter JI, Wagenknecht LE, Gudnason V, Province MA, Peyser PA, Speliotes EK. Allele-specific variation at APOE increases nonalcoholic fatty liver disease and obesity but decreases risk of Alzheimer's disease and myocardial infarction. Hum Mol Genet 2021; 30:1443-1456. [PMID: 33856023 PMCID: PMC8283205 DOI: 10.1093/hmg/ddab096] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 03/19/2021] [Accepted: 03/31/2021] [Indexed: 02/06/2023] Open
Abstract
Nonalcoholic fatty liver disease (NAFLD) is a leading cause of chronic liver disease and is highly correlated with metabolic disease. NAFLD results from environmental exposures acting on a susceptible polygenic background. This study performed the largest multiethnic investigation of exonic variation associated with NAFLD and correlated metabolic traits and diseases. An exome array meta-analysis was carried out among eight multiethnic population-based cohorts (n = 16 492) with computed tomography (CT) measured hepatic steatosis. A fixed effects meta-analysis identified five exome-wide significant loci (P < 5.30 × 10-7); including a novel signal near TOMM40/APOE. Joint analysis of TOMM40/APOE variants revealed the TOMM40 signal was attributed to APOE rs429358-T; APOE rs7412 was not associated with liver attenuation. Moreover, rs429358-T was associated with higher serum alanine aminotransferase, liver steatosis, cirrhosis, triglycerides and obesity; as well as, lower cholesterol and decreased risk of myocardial infarction and Alzheimer's disease (AD) in phenome-wide association analyses in the Michigan Genomics Initiative, United Kingdom Biobank and/or public datasets. These results implicate APOE in imaging-based identification of NAFLD. This association may or may not translate to nonalcoholic steatohepatitis; however, these results indicate a significant association with advanced liver disease and hepatic cirrhosis. These findings highlight allelic heterogeneity at the APOE locus and demonstrate an inverse link between NAFLD and AD at the exome level in the largest analysis to date.
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Affiliation(s)
- Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Bratati Kahali
- Centre for Brain Research, Indian Institute of Science, Bangalore, Karnataka, India
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Annapurna Kuppa
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Yanhua Chen
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Xiaomeng Du
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Lawrence F Bielak
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Jeffrey R O’Connell
- Department of Endocrinology, Diabetes, and Nutrition, University of Maryland-Baltimore, Baltimore, MD, USA
| | - Solomon K Musani
- Department of Medicine, University of Mississippi, Jackson, MS, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA USA
| | | | - Kathleen A Ryan
- Department of Endocrinology, Diabetes, and Nutrition, University of Maryland-Baltimore, Baltimore, MD, USA
| | | | - Matthew A Allison
- Department of Family Medicine and Public Health, University of California, San Diego, CA, USA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Matthew J Budoff
- Department of Internal Medicine, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - J Jeffrey Carr
- Department of Radiology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Yii-Der I Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA USA
| | - Adolfo Correa
- Department of Medicine, University of Mississippi, Jackson, MS, USA
| | - Breland F Crudup
- Department of Medicine, University of Mississippi, Jackson, MS, USA
| | - Brian Halligan
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Jian Yang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute of Aging, Bethesda, MD, USA
| | - Yi-Ping Fu
- Framingham Heart Study, NHLBI, NIH, Framingham, MA, USA
- Office of Biostatistics Research, NHLBI, NIH, Bethesda, MD, USA
| | - Thomas H Mosley
- Department of Medicine, University of Mississippi, Jackson, MS, USA
| | - Jill M Norris
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - James G Terry
- Department of Radiology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | | | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA USA
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Department of Medicine, University of Iceland, Reykjavik 101, Iceland
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Patricia A Peyser
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Elizabeth K Speliotes
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
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9
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Kahali B, Chen Y, Feitosa MF, Bielak LF, O’Connell JR, Musani SK, Hegde Y, Chen Y, Stetson LC, Guo X, Fu YP, Smith AV, Ryan KA, Eiriksdottir G, Cohain AT, Allison M, Bakshi A, Bowden DW, Budoff MJ, Carr JJ, Carskadon S, Chen YDI, Correa A, Crudup BF, Du X, Harris TB, Yang J, Kardia SLR, Launer LJ, Liu J, Mosley TH, Norris JM, Terry JG, Palanisamy N, Schadt EE, O’Donnell CJ, Yerges-Armstrong LM, Rotter JI, Wagenknecht LE, Handelman SK, Gudnason V, Province MA, Peyser PA, Halligan B, Palmer ND, Speliotes EK. A Noncoding Variant Near PPP1R3B Promotes Liver Glycogen Storage and MetS, but Protects Against Myocardial Infarction. J Clin Endocrinol Metab 2021; 106:372-387. [PMID: 33231259 PMCID: PMC7823249 DOI: 10.1210/clinem/dgaa855] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Indexed: 01/02/2023]
Abstract
CONTEXT Glycogen storage diseases are rare. Increased glycogen in the liver results in increased attenuation. OBJECTIVE Investigate the association and function of a noncoding region associated with liver attenuation but not histologic nonalcoholic fatty liver disease. DESIGN Genetics of Obesity-associated Liver Disease Consortium. SETTING Population-based. MAIN OUTCOME Computed tomography measured liver attenuation. RESULTS Carriers of rs4841132-A (frequency 2%-19%) do not show increased hepatic steatosis; they have increased liver attenuation indicative of increased glycogen deposition. rs4841132 falls in a noncoding RNA LOC157273 ~190 kb upstream of PPP1R3B. We demonstrate that rs4841132-A increases PPP1R3B through a cis genetic effect. Using CRISPR/Cas9 we engineered a 105-bp deletion including rs4841132-A in human hepatocarcinoma cells that increases PPP1R3B, decreases LOC157273, and increases glycogen perfectly mirroring the human disease. Overexpression of PPP1R3B or knockdown of LOC157273 increased glycogen but did not result in decreased LOC157273 or increased PPP1R3B, respectively, suggesting that the effects may not all occur via affecting RNA levels. Based on electronic health record (EHR) data, rs4841132-A associates with all components of the metabolic syndrome (MetS). However, rs4841132-A associated with decreased low-density lipoprotein (LDL) cholesterol and risk for myocardial infarction (MI). A metabolic signature for rs4841132-A includes increased glycine, lactate, triglycerides, and decreased acetoacetate and beta-hydroxybutyrate. CONCLUSIONS These results show that rs4841132-A promotes a hepatic glycogen storage disease by increasing PPP1R3B and decreasing LOC157273. rs4841132-A promotes glycogen accumulation and development of MetS but lowers LDL cholesterol and risk for MI. These results suggest that elevated hepatic glycogen is one cause of MetS that does not invariably promote MI.
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Affiliation(s)
- Bratati Kahali
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Centre for Brain Research, Indian Institute of Science, Bangalore, India
| | - Yue Chen
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Lawrence F Bielak
- School of Public Health, Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Jeffrey R O’Connell
- Department of Endocrinology, Diabetes, and Nutrition, University of Maryland-Baltimore, Baltimore, MD, USA
| | - Solomon K Musani
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Yash Hegde
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Yanhua Chen
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - L C Stetson
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, LABioMed and Department of Pediatrics at Harbor-UCLA, Torrance, CA, USA
| | - Yi-ping Fu
- Framingham Heart Study, NHLBI, NIH, Framingham, MA, USA
- Office of Biostatistics Research, Division of Cardiovascular Diseases, NHLBI, NIH, Bethesda, MD, USA
| | - Albert Vernon Smith
- School of Public Health, Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Kathleen A Ryan
- Department of Endocrinology, Diabetes, and Nutrition, University of Maryland-Baltimore, Baltimore, MD, USA
| | | | - Ariella T Cohain
- Department of Genetics and Genomics Sciences, Icahn School of Medicine, New York, NY, USA
| | - Matthew Allison
- Department of Family Medicine and Public Health, University of California, San Diego, CA, USA
| | - Andrew Bakshi
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Matthew J Budoff
- Department of Internal Medicine, LA Biomedical Research Institute at Harbor-UCLA, Torrance, CA, USA
| | - J Jeffrey Carr
- Department of Radiology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | | | - Yii-Der I Chen
- Institute for Translational Genomics and Population Sciences, LABioMed and Department of Pediatrics at Harbor-UCLA, Torrance, CA, USA
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Breland F Crudup
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Xiaomeng Du
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Tamara B Harris
- Laboratory of Epidemiology and Population Sciences, National Institute of Aging, Bethesda, MD, USA
| | - Jian Yang
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Sharon L R Kardia
- School of Public Health, Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute of Aging, Bethesda, MD, USA
| | - Jiankang Liu
- Brigham and Women’s Hospital, Havard University, Boston, MA, USA
| | - Thomas H Mosley
- Department of Medicine, Division of Geriatrics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Jill M Norris
- Department of Preventive Medicine and Biometrics, University of Colorado at Denver Health Sciences Center, Aurora, CO, USA
| | - James G Terry
- Department of Radiology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | | | - Eric E Schadt
- Department of Genetics and Genomics Sciences, Icahn School of Medicine, New York, NY, USA
| | - Christopher J O’Donnell
- Framingham Heart Study, NHLBI, NIH, Framingham, MA, USA
- Cardiology Section, Department of Medicine, Boston Veteran’s Administration Healthcare, Boston, MA, USA
| | - Laura M Yerges-Armstrong
- Department of Endocrinology, Diabetes, and Nutrition, University of Maryland-Baltimore, Baltimore, MD, USA
- Target Sciences, GlaxoSmithKline, Collegeville, PA, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, LABioMed and Department of Pediatrics at Harbor-UCLA, Torrance, CA, USA
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Samuel K Handelman
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Department of Medicine, University of Iceland, Reykjavik, Iceland
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Patricia A Peyser
- School of Public Health, Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Brian Halligan
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Elizabeth K Speliotes
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
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Kho M, Zhao W, Ratliff SM, Ammous F, Mosley TH, Shang L, Kardia SLR, Zhou X, Smith JA. Epigenetic loci for blood pressure are associated with hypertensive target organ damage in older African Americans from the genetic epidemiology network of Arteriopathy (GENOA) study. BMC Med Genomics 2020; 13:131. [PMID: 32917208 PMCID: PMC7488710 DOI: 10.1186/s12920-020-00791-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 09/03/2020] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Hypertension is a major modifiable risk factor for arteriosclerosis that can lead to target organ damage (TOD) of heart, kidneys, and peripheral arteries. A recent epigenome-wide association study for blood pressure (BP) identified 13 CpG sites, but it is not known whether DNA methylation at these sites is also associated with TOD. METHODS In 1218 African Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) study, a cohort of hypertensive sibships, we evaluated the associations between methylation at these 13 CpG sites measured in peripheral blood leukocytes and five TOD traits assessed approximately 5 years later. RESULTS Ten significant associations were found after adjustment for age, sex, blood cell counts, time difference between CpG and TOD measurement, and 10 genetic principal components (FDR q < 0.1): two with estimated glomerular filtration rate (eGFR, cg06690548, cg10601624), six with urinary albumin-to-creatinine ratio (UACR, cg16246545, cg14476101, cg19693031, cg06690548, cg00574958, cg22304262), and two with left ventricular mass indexed to height (LVMI, cg19693031, cg00574958). All associations with eGFR and four associations with UACR remained significant after further adjustment for body mass index (BMI), smoking status, and diabetes. We also found significant interactions between cg06690548 and BMI on UACR, and between 3 CpG sites (cg19693031, cg14476101, and cg06690548) and diabetes on UACR (FDR q < 0.1). Mediation analysis showed that 4.7% to 38.1% of the relationship between two CpG sites (cg19693031 and cg00574958) and two TOD measures (UACR and LVMI) was mediated by blood pressure (Bonferroni-corrected P < 0.05). Mendelian randomization analysis suggests that methylation at two sites (cg16246545 and cg14476101) in PHGDH may causally influence UACR. CONCLUSIONS In conclusion, we found compelling evidence for associations between arteriosclerotic traits of kidney and heart and previously identified blood pressure-associated DNA methylation sites. This study may lend insight into the role of DNA methylation in pathological mechanisms underlying target organ damage from hypertension.
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Affiliation(s)
- Minjung Kho
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109 USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109 USA
| | - Scott M. Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109 USA
| | - Farah Ammous
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109 USA
| | - Thomas H. Mosley
- Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS 39216 USA
| | - Lulu Shang
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI 48109 USA
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109 USA
| | - Xiang Zhou
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI 48109 USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109 USA
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11
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Kho M, Smith JA, Verweij N, Shang L, Ryan KA, Zhao W, Ware EB, Gansevoort RT, Irvin MR, Lee JE, Turner ST, Sung J, van der Harst P, Arnett DK, Baylin A, Park SK, Seo YA, Kelly KM, Chang YPC, Zhou X, Lieske JC, Kardia SLR. Genome-Wide Association Meta-Analysis of Individuals of European Ancestry Identifies Suggestive Loci for Sodium Intake, Potassium Intake, and Their Ratio Measured from 24-Hour or Half-Day Urine Samples. J Nutr 2020; 150:2635-2645. [PMID: 32840624 PMCID: PMC7549298 DOI: 10.1093/jn/nxaa241] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Revised: 05/19/2020] [Accepted: 07/17/2020] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Excess sodium intake and insufficient potassium intake are risk factors for hypertension, but there is limited knowledge regarding genetic factors that influence intake. Twenty-hour or half-day urine samples provide robust estimates of sodium and potassium intake, outperforming other measures such as spot urine samples and dietary self-reporting. OBJECTIVE The aim of this study was to investigate genomic regions associated with sodium intake, potassium intake, and sodium-to-potassium ratio measured from 24-h or half-day urine samples. METHODS Using samples of European ancestry (mean age: 54.2 y; 52.3% women), we conducted a meta-analysis of genome-wide association studies in 4 cohorts with 24-h or half-day urine samples (n = 6,519), followed by gene-based analysis. Suggestive loci (P < 10-6) were examined in additional European (n = 844), African (n = 1,246), and Asian (n = 2,475) ancestry samples. RESULTS We found suggestive loci (P < 10-6) for all 3 traits, including 7 for 24-h sodium excretion, 4 for 24-h potassium excretion, and 4 for sodium-to-potassium ratio. The most significant locus was rs77958157 near cocaine- and amphetamine-regulated transcript prepropeptide (CARTPT) , a gene involved in eating behavior and appetite regulation (P = 2.3 × 10-8 with sodium-to-potassium ratio). Two suggestive loci were replicated in additional samples: for sodium excretion, rs12094702 near zinc finger SWIM-type containing 5 (ZSWIM5) was replicated in the Asian ancestry sample reaching Bonferroni-corrected significance (P = 0.007), and for potassium excretion rs34473523 near sodium leak channel (NALCN) was associated at a nominal P value with potassium excretion both in European (P = 0.043) and African (P = 0.043) ancestry cohorts. Gene-based tests identified 1 significant gene for sodium excretion, CDC42 small effector 1 (CDC42SE1), which is associated with blood pressure regulation. CONCLUSIONS We identified multiple suggestive loci for sodium and potassium intake near genes associated with eating behavior, nervous system development and function, and blood pressure regulation in individuals of European ancestry. Further research is needed to replicate these findings and to provide insight into the underlying genetic mechanisms by which these genomic regions influence sodium and potassium intake.
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Affiliation(s)
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA,Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Niek Verweij
- Department of Cardiology, Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Lulu Shang
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Kathleen A Ryan
- Department of Medicine, School of Medicine, University of Maryland Baltimore, Baltimore, MD, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Erin B Ware
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Ron T Gansevoort
- Department of Nephrology, Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jung Eun Lee
- Department of Food and Nutrition, Seoul National University, Seoul, Republic of Korea
| | - Stephen T Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
| | - Joohon Sung
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Republic of Korea,Institute of Environment and Health, Seoul National University, Seoul, Republic of Korea
| | - Pim van der Harst
- Department of Cardiology, Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Ana Baylin
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA,Department of Nutritional Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Sung Kyun Park
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA,Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Young Ah Seo
- Department of Nutritional Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Kristen M Kelly
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Yen Pei C Chang
- Department of Medicine, School of Medicine, University of Maryland Baltimore, Baltimore, MD, USA
| | - Xiang Zhou
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - John C Lieske
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA,Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
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12
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Oshunbade AA, Hamid A, Lirette ST, Gbadamosi SO, Yimer WK, Orimoloye OA, Clark D, Kamimura D, Grado SD, Lutz EA, Mentz RJ, Fox ER, Butler J, Gwen Windham B, Butler KR, Mosley TH, Hall ME. Hypertensive diseases in pregnancy, cardiac structure and function later in life: Insights from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. Pregnancy Hypertens 2020; 21:184-190. [DOI: 10.1016/j.preghy.2020.05.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 05/08/2020] [Accepted: 05/25/2020] [Indexed: 01/14/2023]
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Hormone therapy and urine protein excretion: a multiracial cohort study, systematic review, and meta-analysis. Menopause 2019; 25:625-634. [PMID: 29381664 DOI: 10.1097/gme.0000000000001062] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
OBJECTIVE Experimental models suggest estrogen has a renoprotective effect, but human studies show variable results. Our objective was to study the association of hormone therapy (HT) and albuminuria in postmenopausal women and to synthesize the results with outcomes from prior studies. METHODS We analyzed data from postmenopausal women who participated in the second study visit (2000-2004) of the Genetic Epidemiology Network of Arteriopathy (GENOA) study. The exposure was self-reported HT use and the outcome was albuminuria (urine albumin-to-creatinine ratio >25 mg/g creatinine). We also conducted a systematic review and meta-analysis on the association of HT and urine protein in postmenopausal women. Continuous and dichotomous measures of protein excretion were converted to a standardized mean difference (SMD) for each study. RESULTS In the GENOA cohort (n = 2,217), there were fewer women with albuminuria among HT users than nonusers (9% vs 19%, P < 0.001). HT use was associated with decreased odds of albuminuria (odds ratio 0.65, 95% confidence interval (CI), 0.45-0.95), after adjusting for significant differences in age, race, education, comorbidities, and the age at and cause of menopause. The SMD of the effect of HT on urine proteinuria/albuminuria in the randomized control trials (n = 3) was 0.02 (95% CI, -0.29 to 0.33) and -0.13 (95% CI, -0.31 to 0.05) in the observational studies (n = 9). There was significantly less albuminuria among HT users (SMD -0.15, 95% CI, -0.27 to -0.04) in the 9 studies that only reported albuminuria as an outcome and in the 10 studies with a comparator arm (SMD -0.15, 95% CI, -0.26 to -0.04). CONCLUSIONS HT is associated with decreased odds of albuminuria, but some of the observed benefits may be related to reported outcomes, the presence of a comparator arm, and the type of study design.
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14
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Clemmer JS, Faulkner JL, Mullen AJ, Butler KR, Hester RL. Sex-specific responses to mineralocorticoid receptor antagonism in hypertensive African American males and females. Biol Sex Differ 2019; 10:24. [PMID: 31072402 PMCID: PMC6507140 DOI: 10.1186/s13293-019-0238-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Accepted: 04/16/2019] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND African Americans (AA) develop hypertension (HTN) at an earlier age, have a greater frequency and severity of HTN, and greater prevalence of uncontrolled HTN as compared to the white population. Mineralocorticoid antagonists have been shown to be very effective in treating uncontrolled HTN in both AA and white patients, but sex-specific responses are unclear. METHODS We evaluated the sex-specific impact of mineralocorticoid antagonism in an AA population. An AA cohort (n = 1483) from the Genetic Epidemiology Network of Arteriopathy study was stratified based on sex and whether they were taking spironolactone, a mineralocorticoid antagonist, in their antihypertensive regimen. RESULTS As compared to AA women not prescribed a mineralocorticoid antagonist, AA women taking spironolactone (n = 9) had lower systolic and diastolic blood pressure despite having a similar number of antihypertensive medications. The proportion of AA women with uncontrolled HTN was significantly less for patients taking spironolactone than for patients not prescribed spironolactone. Interestingly, none of these associations were found in the AA males or in white females. CONCLUSIONS Our data suggests that spironolactone is particularly effective in reducing blood pressure and controlling HTN in AA women. Further research into the impact of this therapy in this underserved and understudied minority is warranted.
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Affiliation(s)
- John S Clemmer
- Department of Physiology and Biophysics, Center for Computational Medicine, University of Mississippi Medical Center, 2500 North State Street, Jackson, MS, 39216-4505, USA.
| | - Jessica L Faulkner
- Vascular Biology Center, Medical College of Georgia, Augusta University, Augusta, GA, 30912-5563, USA
| | - Alex J Mullen
- Department of Physiology and Biophysics, Center for Computational Medicine, University of Mississippi Medical Center, 2500 North State Street, Jackson, MS, 39216-4505, USA
| | - Kenneth R Butler
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, 39216-4505, USA
| | - Robert L Hester
- Department of Physiology and Biophysics, Center for Computational Medicine, University of Mississippi Medical Center, 2500 North State Street, Jackson, MS, 39216-4505, USA.,Department of Data Sciences, John D. Bower School of Population Health, University of Mississippi Medical Center, Jackson, MS, 39216-4505, USA
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15
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Developing community-based health education strategies with family history: Assessing the association between community resident family history and interest in health education. Soc Sci Med 2019; 271:112160. [PMID: 30862375 DOI: 10.1016/j.socscimed.2019.02.011] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2018] [Revised: 02/01/2019] [Accepted: 02/07/2019] [Indexed: 02/07/2023]
Abstract
BACKGROUND Family history (FH) is an underutilized genetically informative tool that can influence disease prevention and treatment. It is unclear how FH fits into the development of community-based health education. This study examines the role that FH plays in perceived threat and health education related to mental and chronic physical conditions in the context of the health belief model. METHODS Data were collected from 1,048 adult participants aged 18-90 years. Approximately 76% of participants indicated African-American race/ethnicity and 35% had less than high school level education. Self-report data were collected on FH of four disorders: anxiety, depression, diabetes, and high blood pressure. Interest in receiving information regarding prevention as well as future testing efforts was assessed broadly. A series of logistic regressions examined the association between FH for each of the disorders and interest in receiving information on (1) prevention of diseases in general and (2) testing for diseases in general. These associations were also analyzed after accounting for the influence of perceived threat of conditions. RESULTS Interest in receiving general health education was significantly associated with FH of depression (OR = 2.72, 95% CI = 1.74-4.25), anxiety (OR = 2.26, 95% CI = 1.45-3.22), and high blood pressure (OR = 2.54, 95% CI = 1.05-6.12). After adjustment for perceived threat, the magnitude of these associations was reduced substantially. The associations between perceived threat and either interest in receiving information on disease testing or receiving general health education were strong and significant across all conditions (OR = 2.11-3.74). DISCUSSION These results provide evidence that perceived threat mediates the association between FH and engagement with health education. Currently available health education programs may benefit from considering the role of FH in an individual's motivation for participation in health education activities alongside other factors.
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Liu J, Zhao W, Ammous F, Turner ST, Mosley TH, Zhou X, Smith JA. Longitudinal analysis of epigenome-wide DNA methylation reveals novel smoking-related loci in African Americans. Epigenetics 2019; 14:171-184. [PMID: 30764717 PMCID: PMC6557606 DOI: 10.1080/15592294.2019.1581589] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2018] [Revised: 01/26/2019] [Accepted: 02/03/2019] [Indexed: 10/27/2022] Open
Abstract
Changes in DNA methylation may be a potential mechanism that mediates the effects of smoking on physiological function and subsequent disease risk. Given the dynamic nature of the epigenome, longitudinal studies are indispensable for investigating smoking-induced methylation changes over time. Using blood samples collected approximately five years apart in 380 African Americans (mean age 60.7 years) from the Genetic Epidemiology Network of Arteriopathy (GENOA) study, we measured DNA methylation levels using Illumina HumanMethylation BeadChips. We evaluated the association between Phase 1 smoking status and rate of methylation change, using generalized estimating equation models. Among the 6958 CpG sites examined, smoking status was associated with methylation change for 22 CpGs (false discovery rate q < 0.1), with the majority (91%) becoming less methylated over time. Methylation change was greater in ever smokers than never smokers, and the absolute differences in rates of change ranged from 0.18 to 0.77 per decade in M value, equivalent to a β value change of 0.013 to 0.047 per decade. Significant enrichment was observed for CpG islands, enhancers, and DNAse hypersensitivity sites (p < 0.05). Although biological pathway analyses were not significant, most of the 22 CpGs were within genes known to be associated with cardiovascular disease, cancers, and aging. In conclusion, we identified epigenetic signatures for cigarette smoking that may have been missed in cross-sectional analyses, providing insight into the epigenetic effect of smoking and highlighting the importance of longitudinal analysis in understanding the dynamic human epigenome.
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Affiliation(s)
- Jiaxuan Liu
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Farah Ammous
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Stephen T. Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA
| | - Thomas H. Mosley
- Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS, USA
| | - Xiang Zhou
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
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17
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Liu J, Zhao W, Ware EB, Turner ST, Mosley TH, Smith JA. DNA methylation in the APOE genomic region is associated with cognitive function in African Americans. BMC Med Genomics 2018; 11:43. [PMID: 29739406 PMCID: PMC5941603 DOI: 10.1186/s12920-018-0363-9] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2017] [Accepted: 04/26/2018] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Genetic variations in apolipoprotein E (APOE) and proximal genes (PVRL2, TOMM40, and APOC1) are associated with cognitive function and dementia, particularly Alzheimer's disease. Epigenetic mechanisms such as DNA methylation play a central role in the regulation of gene expression. Recent studies have found evidence that DNA methylation may contribute to the pathogenesis of dementia, but its association with cognitive function in populations without dementia remains unclear. METHODS We assessed DNA methylation levels of 48 CpG sites in the APOE genomic region in peripheral blood leukocytes collected from 289 African Americans (mean age = 67 years) from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. Using linear regression, we examined the relationship between methylation in the APOE genomic region and multiple cognitive measures including learning, memory, processing speed, concentration, language and global cognitive function. RESULTS We identified eight CpG sites in three genes (PVRL2, TOMM40, and APOE) that showed an inverse association between methylation level and delayed recall, a measure of memory, after adjusting for age and sex (False Discovery Rate q-value < 0.1). All eight CpGs are located in either CpG islands (CGIs) or CGI shelves, and six of them are in promoter regions. Education and APOE ε4 carrier status significantly modified the effect of methylation in cg08583001 (PVRL2) and cg22024783 (TOMM40), respectively. Together, methylation of the eight CpGs explained an additional 8.7% of the variance in delayed recall, after adjustment for age, sex, education, and APOE ε4 carrier status. Methylation was not significantly associated with any other cognitive measures. CONCLUSIONS Our results suggest that methylation levels at multiple CpGs in the APOE genomic region are inversely associated with delayed recall during normal cognitive aging, even after accounting for known genetic predictors for cognition. Our findings highlight the important role of epigenetic mechanisms in influencing cognitive performance, and suggest that changes in blood methylation may be an early indicator of individuals at risk for dementia as well as potential targets for intervention in asymptomatic populations.
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Affiliation(s)
- Jiaxuan Liu
- Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, 4602 SPH Tower, Ann Arbor, MI 48109-2029 USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, 4602 SPH Tower, Ann Arbor, MI 48109-2029 USA
| | - Erin B. Ware
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104 USA
| | - Stephen T. Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN 55905 USA
| | - Thomas H. Mosley
- Department of Neurology, University of Mississippi Medical Center, Jackson, MS 39126 USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, 4602 SPH Tower, Ann Arbor, MI 48109-2029 USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104 USA
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Jhun MA, Smith JA, Ware EB, Kardia SLR, Mosley TH, Turner ST, Peyser PA, Park SK. Modeling the Causal Role of DNA Methylation in the Association Between Cigarette Smoking and Inflammation in African Americans: A 2-Step Epigenetic Mendelian Randomization Study. Am J Epidemiol 2017; 186:1149-1158. [PMID: 29149250 DOI: 10.1093/aje/kwx181] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2016] [Accepted: 01/17/2017] [Indexed: 01/17/2023] Open
Abstract
The association between cigarette smoking and inflammation is well known. However, the biological mechanisms behind the association are not fully understood, particularly the role of DNA methylation, which is known to be affected by smoking. Using 2-step epigenetic Mendelian randomization, we investigated the role of DNA methylation in the association between cigarette smoking and inflammation. In 822 African Americans from the Genetic Epidemiology Network of Arteriopathy, phase 2 (Jackson, Mississippi; 2000-2005), study population, we examined the association of cigarette smoking with DNA methylation using single nucleotide polymorphisms identified in previous genome-wide association studies of cigarette smoking. We then investigated the association of DNA methylation with levels of inflammatory markers using cis-methylation quantitative trait loci single nucleotide polymorphisms. We found that current smoking status was associated with the DNA methylation levels (M values) of cg03636183 in the coagulation factor II (thrombin) receptor-like 3 gene (F2RL3) (M = -0.64, 95% confidence interval (CI): -0.84, -0.45) and of cg19859270 in the G protein-coupled receptor 15 gene (GPR15) (M = -0.21, 95% CI: -0.27, -0.15). The DNA methylation levels of cg03636183 in F2RL3 were associated with interleukin-18 concentration (-0.11 pg/mL, 95% CI: -0.19, -0.04). These combined negative effects suggest that cigarette smoking increases interleukin-18 levels through the decrease in DNA methylation levels of cg03636183 in F2RL3.
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Yano Y, Butler KR, Hall ME, Schwartz GL, Knopman DS, Lirette ST, Jones DW, Wilson JG, Hall JE, Correa A, Turner ST, Mosley TH. Associations of Nocturnal Blood Pressure With Cognition by Self-Identified Race in Middle-Aged and Older Adults: The GENOA (Genetic Epidemiology Network of Arteriopathy) Study. J Am Heart Assoc 2017; 6:e007022. [PMID: 29079569 PMCID: PMC5721781 DOI: 10.1161/jaha.117.007022] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2017] [Accepted: 08/29/2017] [Indexed: 12/21/2022]
Abstract
BACKGROUND Whether the association of blood pressure (BP) during sleep (nocturnal BP) with cognition differs by race is unknown. METHODS AND RESULTS Participants in the GENOA (Genetic Epidemiology Network of Arteriopathy) Study underwent ambulatory BP measurements, brain magnetic resonance imaging, and cognitive function testing (the Rey Auditory Verbal Learning Test, the Digit Symbol Substitution Task, and the Trail Making Test Part B) between 2000 and 2007. We examined multivariable linear regression models of the nocturnal BP-cognition association. Among 755 participants (mean age, 63 years; 64% women; 42% self-identified black race; 76% taking antihypertensive medication), mean nocturnal systolic BP (SBP)/diastolic BP was 126/69 mm Hg, daytime SBP/diastolic BP level was 139/82 mm Hg, and mean reduction in SBP from day to night (dipping) was 9%. Among the entire sample, a race interaction was observed in Digit Symbol Substitution Task and Trail Making Test Part B (both P<0.15). Race-stratified analyses showed that a 1-SD increase in nocturnal SBP levels was associated with poorer Digit Symbol Substitution Task and log-transformed Trail Making Test Part B scores (unstandardized regression coefficient [95% confidence interval]: -1.98 [-3.28 to -0.69] and 0.06 [0.004-0.12]; both P<0.05) in black but not white individuals. Additional adjustments for white matter hyperintensity volumes or brain atrophy, measured via brain magnetic resonance imaging, did not change the results. Results were similar when nocturnal SBP dipping was assessed as the exposure, yet daytime SBP levels yielded no association with cognition. CONCLUSIONS Nocturnal SBP measurements may be useful in assessing the potential risk for lower cognitive function in middle-aged and older adults, particularly in black individuals.
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Affiliation(s)
- Yuichiro Yano
- Department of Preventive Medicine, University of Mississippi Medical Center, Jackson, MS
| | - Kenneth R Butler
- Division of Geriatric Medicine, University of Mississippi Medical Center, Jackson, MS
| | - Michael E Hall
- Division of Cardiology, Department of Medicine, University of Mississippi Medical Center, Jackson, MS
- Division of Radiology and Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS
| | - Gary L Schwartz
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | - David S Knopman
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | - Seth T Lirette
- Department of Data Science, University of Mississippi Medical Center, Jackson, MS
| | - Daniel W Jones
- Mississippi Center for Obesity Research, University of Mississippi Medical Center, Jackson, MS
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS
| | - John E Hall
- Mississippi Center for Obesity Research, University of Mississippi Medical Center, Jackson, MS
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS
| | - Adolfo Correa
- Department of Pediatrics and Medicine, University of Mississippi Medical Center, Jackson, MS
| | - Stephen T Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | - Thomas H Mosley
- Division of Geriatric Medicine, University of Mississippi Medical Center, Jackson, MS
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20
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The association between cigarette smoking and inflammation: The Genetic Epidemiology Network of Arteriopathy (GENOA) study. PLoS One 2017; 12:e0184914. [PMID: 28922371 PMCID: PMC5602636 DOI: 10.1371/journal.pone.0184914] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2017] [Accepted: 09/01/2017] [Indexed: 01/30/2023] Open
Abstract
To inform the study and regulation of emerging tobacco products, we sought to identify sensitive biomarkers of tobacco-induced subclinical cardiovascular damage by testing the cross-sectional associations of smoking with 17 biomarkers of inflammation in 2,702 GENOA study participants belonging to sibships ascertained on the basis of hypertension. Cigarette smoking was assessed by status, intensity (number of cigarettes per day), burden (pack-years of smoking), and time since quitting. We modeled biomarkers as geometric mean (GM) ratios using generalized estimating equations (GEE). The mean age of participants was 61 ±10 years; 64.5% were women and 54.4% African American. The prevalence of smoking was 12.2%. After adjusting for potential confounders, 6 of 17 biomarkers were significantly higher among current smokers at a Bonferroni adjusted p-value threshold (p<0.003). High sensitivity C-reactive protein was the most elevated biomarker among current smokers when compared to never smokers [GM ratio = 1.39 (95% CI: 1.23, 1.57); p <0.001]. Among former smokers, each pack-year of cigarettes smoked was associated with a 0.4% higher serum level of hsCRP [GM ratio = 1.004 (95% CI: 1.001, 1.006); p = 0.002] and each 5-year lapsed since quitting was associated with a 4% lower serum level of hsCRP [GM ratio = 0.96 (95% CI: 0.93, 0.99); p = 0.006]. However, we found no significant association of smoking intensity or burden with biomarkers of inflammation among current smokers. HsCRP appears to be the most sensitive biomarker of inflammation associated with cigarette smoking of those investigated, and could be a useful biomarker of smoking-related injury for the study and regulation of emerging tobacco products.
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21
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Windham BG, Lirette ST, Fornage M, Benjamin EJ, Parker KG, Turner ST, Jack CR, Griswold ME, Mosley TH. Associations of Brain Structure With Adiposity and Changes in Adiposity in a Middle-Aged and Older Biracial Population. J Gerontol A Biol Sci Med Sci 2017; 72:825-831. [PMID: 27994005 DOI: 10.1093/gerona/glw239] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2016] [Accepted: 11/08/2016] [Indexed: 11/14/2022] Open
Abstract
Background Studies of adiposity and brain pathology in African Americans (AA) are sparse despite higher rates of obesity, dementia, and dementia-associated brain pathology in AA. This study examined relations of adiposity to white matter hyperintensities (WMH) and total brain volume (TBV) in AA and non-Hispanic whites (NHW). Methods Waist circumference (WC) and body mass index (BMI) were measured in the Genetic Epidemiology Network of Arteriopathy study at Visits 1 (mean age 57 [±11]) and 2 (mean age 61 [±10], mean 5.2 years later). Brain MRIs were obtained shortly after Visit 2 in 1,702 participants (64% women, 48% AA). Multilevel linear regression using generalized estimating equation estimated associations of adiposity (cross-sectional) or adiposity changes with WMH (accounting for intracranial size) or TBV adjusting for demographics, cardiovascular risk factors, and incorporating adiposity-by-race interactions. Adiposity-by-age interactions were examined. Results Concurrent TBV was inversely associated with BMI (β = -2.76 [95% confidence interval (CI): -4.99, -0.53]) and WC (β = -2.19 [CI: -4.04, -0.34]). Concurrent WMH were negatively associated with BMI (β = -0.04 [CI: -0.06, -0.01]) and, among NHW, with WC (β = -0.04 [CI: -0.06, -0.02]) but not with changes in BMI or WC. BMI increases were associated with lower TBV (β = -16.20, [CI: -30.34, -2.06]) in AA but not in NHW (β = -2.76 [CI: -14.02, 8.51]), although race-by-adiposity interactions were not supported. WC increases were not associated with MRI outcomes. Conclusion Greater measures of obesity and increases in measures of obesity, which are common in mid-life, could be detrimental to brain health, particularly in AA.
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Affiliation(s)
- B Gwen Windham
- Department of Medicine-Geriatrics, University of Mississippi Medical Center, Jackson
| | | | - Myriam Fornage
- Institute of Molecular Medicine, Health Science Center at Houston, University of Texas
| | | | - Kirby G Parker
- Department of Medicine-Geriatrics, University of Mississippi Medical Center, Jackson.,Center of Biostatistics, Jackson, Mississippi
| | | | | | | | - Thomas H Mosley
- Department of Medicine-Geriatrics, University of Mississippi Medical Center, Jackson
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22
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NANDAKUMAR P, LEE D, RICHARD MA, TEKOLA-AYELE F, TAYO BO, WARE E, SUNG YJ, SALAKO B, OGUNNIYI A, GU CC, GROVE ML, FORNAGE M, KARDIA S, ROTIMI C, COOPER RS, MORRISON AC, EHRET G, CHAKRAVARTI A. Rare coding variants associated with blood pressure variation in 15 914 individuals of African ancestry. J Hypertens 2017; 35:1381-1389. [PMID: 28234671 PMCID: PMC5451310 DOI: 10.1097/hjh.0000000000001319] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
OBJECTIVES Hypertension is a major risk factor for all cardiovascular diseases, especially among African Americans. This study focuses on identifying specific blood pressure (BP) genes using 15 914 individuals of African ancestry from eight cohorts (Africa America Diabetes Mellitus, Atherosclerosis Risk in Communities Study, Coronary Artery Risk Development in young Adults, Genetics Network, Genetic Epidemiology Network of Arteriopathy, Howard University Family Study, Hypertension Genetic Epidemiology Network, and Loyola University Chicago Cohort) to further genetic findings in this population which has generally been underrepresented in BP studies. METHODS We genotyped and performed various single variant and gene-based exome-wide analyses on 15 914 individuals on the Illumina HumanExome Beadchip v1.0 or v1.1 to test association with SBP and DBP long-term average residuals that were adjusted for age, age-squared, sex, and BMI. RESULTS We identified rare variants affecting SBP and DBP in 10 genes: AFF1, GAPDHS, SLC28A3, COL6A1, CRYBA2, KRBA1, SEL1L3, YOD1, CCDC13, and QSOX1. Prior experimental evidence for six of these 10 candidate genes supports their involvement in cardiovascular mechanisms, corroborating their potential roles in BP regulation. CONCLUSION Although our results require replication or validation due to their low numbers of carriers, and an ethnicity-specific genotyping array may be more informative, this study, which has identified several candidate genes in this population most susceptible to hypertension, presents one of the largest African-ancestry BP studies to date and the largest including analysis of rare variants.
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Affiliation(s)
- Priyanka NANDAKUMAR
- McKusick - Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD
| | - Dongwon LEE
- McKusick - Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD
| | - Melissa A. RICHARD
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX
| | - Fasil TEKOLA-AYELE
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD
| | - Bamidele O. TAYO
- Department of Public Health Sciences, Stritch School of Medicine, Loyola University Chicago, Maywood, IL
| | - Erin WARE
- Department of Epidemiology, University of Michigan, Ann Arbor, MI
- Institute for Social Research, University of Michigan, Ann Arbor, MI
| | - Yun Ju SUNG
- Division of Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, MO
| | | | | | - C. Charles GU
- Division of Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, MO
| | - Megan L. GROVE
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Myriam FORNAGE
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX
| | - Sharon KARDIA
- Department of Epidemiology, University of Michigan, Ann Arbor, MI
| | - Charles ROTIMI
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD
| | - Richard S. COOPER
- Department of Public Health Sciences, Stritch School of Medicine, Loyola University Chicago, Maywood, IL
| | - Alanna C. MORRISON
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, Houston TX
| | - Georg EHRET
- McKusick - Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD
- Department of Specialties of Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Aravinda CHAKRAVARTI
- McKusick - Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD
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23
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Wang H, Choi Y, Tayo B, Wang X, Morris N, Zhang X, Broeckel U, Hanis C, Kardia S, Redline S, Cooper RS, Tang H, Zhu X. Genome-wide survey in African Americans demonstrates potential epistasis of fitness in the human genome. Genet Epidemiol 2017; 41:122-135. [PMID: 27917522 PMCID: PMC5226866 DOI: 10.1002/gepi.22026] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2016] [Revised: 09/30/2016] [Accepted: 10/03/2016] [Indexed: 11/07/2022]
Abstract
The role played by epistasis between alleles at unlinked loci in shaping population fitness has been debated for many years and the existing evidence has been mainly accumulated from model organisms. In model organisms, fitness epistasis can be systematically inferred by detecting nonindependence of genotypic values between loci in a population and confirmed through examining the number of offspring produced in two-locus genotype groups. No systematic study has been conducted to detect epistasis of fitness in humans owing to experimental constraints. In this study, we developed a novel method to detect fitness epistasis by testing the correlation between local ancestries on different chromosomes in an admixed population. We inferred local ancestry across the genome in 16,252 unrelated African Americans and systematically examined the pairwise correlations between the genomic regions on different chromosomes. Our analysis revealed a pair of genomic regions on chromosomes 4 and 6 that show significant local ancestry correlation (P-value = 4.01 × 10-8 ) that can be potentially attributed to fitness epistasis. However, we also observed substantial local ancestry correlation that cannot be explained by systemic ancestry inference bias. To our knowledge, this study is the first to systematically examine evidence of fitness epistasis across the human genome.
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Affiliation(s)
- Heming Wang
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Yoonha Choi
- Department of Genetics, Stanford University, Stanford, California, United States of America
| | - Bamidele Tayo
- Department of Public Health Science, Loyola University Medical Center, Maywood, Illinois, United States of America
| | - Xuefeng Wang
- Departments of Preventive Medicine, Biomedical Informatics, and Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, United States of America
| | - Nathan Morris
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Xiang Zhang
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Uli Broeckel
- Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America
| | - Craig Hanis
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Sharon Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Susan Redline
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Richard S Cooper
- Department of Public Health Science, Loyola University Medical Center, Maywood, Illinois, United States of America
| | - Hua Tang
- Department of Genetics, Stanford University, Stanford, California, United States of America
| | - Xiaofeng Zhu
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, United States of America
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24
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Mielke MM, Milic NM, Weissgerber TL, White WM, Kantarci K, Mosley TH, Windham BG, Simpson BN, Turner ST, Garovic VD. Impaired Cognition and Brain Atrophy Decades After Hypertensive Pregnancy Disorders. CIRCULATION-CARDIOVASCULAR QUALITY AND OUTCOMES 2016; 9:S70-6. [PMID: 26908863 DOI: 10.1161/circoutcomes.115.002461] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Hypertensive pregnancy disorders have been associated with subjective cognitive complaints or brain white-matter lesions 5 to 10 years after the hypertensive pregnancy. The long-term effects of hypertensive pregnancies on brain structure and cognitive function remain unknown. METHODS AND RESULTS This study included 1279 women who participated in the Family Blood Pressure Project Genetic Epidemiology Network of Arteriopathy (GENOA) study. As part of the ancillary Genetics of Microangiopathic Brain Injury (GMBI) study, a neurocognitive battery was administered; 1075 also had a brain magnetic resonance imaging. A history of a hypertensive pregnancy disorder was obtained by a self-report using a validated questionnaire. Linear models fit with generalized estimating equations were used to assess the association between hypertensive pregnancy disorders and cognition, adjusting for age, race, education, body mass index, smoking, current hypertension, hypertension duration, and family history of hypertension. Regression models for the brain magnetic resonance imaging outcomes also were adjusted for total intracranial volume. Women with histories of hypertensive pregnancy disorders performed worse on all measures of processing speed (Digital Symbol Substitution Test [mean score, 41.2 versus 43.4; P=0.005], Trail Making Test Part A [mean seconds, 45.1 versus 42.2; P=0.035], and Stroop [mean score, 173.9 versus 181.0; P=0.002]) and had smaller brain volumes compared with women with histories of normotensive pregnancies (286 versus 297; P=0.023). CONCLUSIONS Hypertensive pregnancy disorders are associated with worse performance on tests of processing speed and smaller brain volumes decades later. Population-based studies are needed to provide critical insight as to the contribution of hypertensive pregnancies to risk of cognitive decline and dementia.
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Affiliation(s)
- Michelle M Mielke
- From the Departments of Health Sciences Research and Neurology (M.M.M.), Division of Nephrology and Hypertension (N.M.M., T.L.W., S.T.T., V.D.G.), Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology (W.M.W.), and Department of Radiology (K.K.), Mayo Clinic, Rochester, MN; Department of Biostatistics, Medical Faculty, University of Belgrade, Belgrade, Serbia (N.M.M.); and Department of Medicine, University of Mississippi Medical Center, Jackson (T.H.M., B.G.W., B.N.S.)
| | - Natasa M Milic
- From the Departments of Health Sciences Research and Neurology (M.M.M.), Division of Nephrology and Hypertension (N.M.M., T.L.W., S.T.T., V.D.G.), Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology (W.M.W.), and Department of Radiology (K.K.), Mayo Clinic, Rochester, MN; Department of Biostatistics, Medical Faculty, University of Belgrade, Belgrade, Serbia (N.M.M.); and Department of Medicine, University of Mississippi Medical Center, Jackson (T.H.M., B.G.W., B.N.S.)
| | - Tracey L Weissgerber
- From the Departments of Health Sciences Research and Neurology (M.M.M.), Division of Nephrology and Hypertension (N.M.M., T.L.W., S.T.T., V.D.G.), Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology (W.M.W.), and Department of Radiology (K.K.), Mayo Clinic, Rochester, MN; Department of Biostatistics, Medical Faculty, University of Belgrade, Belgrade, Serbia (N.M.M.); and Department of Medicine, University of Mississippi Medical Center, Jackson (T.H.M., B.G.W., B.N.S.)
| | - Wendy M White
- From the Departments of Health Sciences Research and Neurology (M.M.M.), Division of Nephrology and Hypertension (N.M.M., T.L.W., S.T.T., V.D.G.), Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology (W.M.W.), and Department of Radiology (K.K.), Mayo Clinic, Rochester, MN; Department of Biostatistics, Medical Faculty, University of Belgrade, Belgrade, Serbia (N.M.M.); and Department of Medicine, University of Mississippi Medical Center, Jackson (T.H.M., B.G.W., B.N.S.)
| | - Kejal Kantarci
- From the Departments of Health Sciences Research and Neurology (M.M.M.), Division of Nephrology and Hypertension (N.M.M., T.L.W., S.T.T., V.D.G.), Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology (W.M.W.), and Department of Radiology (K.K.), Mayo Clinic, Rochester, MN; Department of Biostatistics, Medical Faculty, University of Belgrade, Belgrade, Serbia (N.M.M.); and Department of Medicine, University of Mississippi Medical Center, Jackson (T.H.M., B.G.W., B.N.S.)
| | - Thomas H Mosley
- From the Departments of Health Sciences Research and Neurology (M.M.M.), Division of Nephrology and Hypertension (N.M.M., T.L.W., S.T.T., V.D.G.), Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology (W.M.W.), and Department of Radiology (K.K.), Mayo Clinic, Rochester, MN; Department of Biostatistics, Medical Faculty, University of Belgrade, Belgrade, Serbia (N.M.M.); and Department of Medicine, University of Mississippi Medical Center, Jackson (T.H.M., B.G.W., B.N.S.)
| | - B Gwen Windham
- From the Departments of Health Sciences Research and Neurology (M.M.M.), Division of Nephrology and Hypertension (N.M.M., T.L.W., S.T.T., V.D.G.), Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology (W.M.W.), and Department of Radiology (K.K.), Mayo Clinic, Rochester, MN; Department of Biostatistics, Medical Faculty, University of Belgrade, Belgrade, Serbia (N.M.M.); and Department of Medicine, University of Mississippi Medical Center, Jackson (T.H.M., B.G.W., B.N.S.)
| | - Brittany N Simpson
- From the Departments of Health Sciences Research and Neurology (M.M.M.), Division of Nephrology and Hypertension (N.M.M., T.L.W., S.T.T., V.D.G.), Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology (W.M.W.), and Department of Radiology (K.K.), Mayo Clinic, Rochester, MN; Department of Biostatistics, Medical Faculty, University of Belgrade, Belgrade, Serbia (N.M.M.); and Department of Medicine, University of Mississippi Medical Center, Jackson (T.H.M., B.G.W., B.N.S.)
| | - Stephen T Turner
- From the Departments of Health Sciences Research and Neurology (M.M.M.), Division of Nephrology and Hypertension (N.M.M., T.L.W., S.T.T., V.D.G.), Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology (W.M.W.), and Department of Radiology (K.K.), Mayo Clinic, Rochester, MN; Department of Biostatistics, Medical Faculty, University of Belgrade, Belgrade, Serbia (N.M.M.); and Department of Medicine, University of Mississippi Medical Center, Jackson (T.H.M., B.G.W., B.N.S.)
| | - Vesna D Garovic
- From the Departments of Health Sciences Research and Neurology (M.M.M.), Division of Nephrology and Hypertension (N.M.M., T.L.W., S.T.T., V.D.G.), Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology (W.M.W.), and Department of Radiology (K.K.), Mayo Clinic, Rochester, MN; Department of Biostatistics, Medical Faculty, University of Belgrade, Belgrade, Serbia (N.M.M.); and Department of Medicine, University of Mississippi Medical Center, Jackson (T.H.M., B.G.W., B.N.S.).
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25
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Morris BJ, Chen R, Donlon TA, Evans DS, Tranah GJ, Parimi N, Ehret GB, Newton-Cheh C, Seto T, Willcox DC, Masaki KH, Kamide K, Ryuno H, Oguro R, Nakama C, Kabayama M, Yamamoto K, Sugimoto K, Ikebe K, Masui Y, Arai Y, Ishizaki T, Gondo Y, Rakugi H, Willcox BJ. Association Analysis of FOXO3 Longevity Variants With Blood Pressure and Essential Hypertension. Am J Hypertens 2016; 29:1292-1300. [PMID: 26476085 PMCID: PMC5055732 DOI: 10.1093/ajh/hpv171] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2015] [Revised: 08/14/2015] [Accepted: 09/29/2015] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND The minor alleles of 3 FOXO3 single nucleotide polymorphisms (SNPs)- rs2802292 , rs2253310 , and rs2802288 -are associated with human longevity. The aim of the present study was to test these SNPs for association with blood pressure (BP) and essential hypertension (EHT). METHODS In a primary study involving Americans of Japanese ancestry drawn from the Family Blood Pressure Program II we genotyped 411 female and 432 male subjects aged 40-79 years and tested for statistical association by contingency table analysis and generalized linear models that included logistic regression adjusting for sibling correlation in the data set. Replication of rs2802292 with EHT was attempted in Japanese SONIC study subjects and of each SNP in a meta-analysis of genome-wide association studies of BP in individuals of European ancestry. RESULTS In Americans of Japanese ancestry, women homozygous for the longevity-associated (minor) allele of each FOXO3 SNP had 6mm Hg lower systolic BP and 3mm Hg lower diastolic BP compared with major allele homozygotes (Bonferroni corrected P < 0.05 and >0.05, respectively). Frequencies of minor allele homozygotes were 3.3-3.9% in women with EHT compared with 9.5-9.6% in normotensive women ( P = 0.03-0.04; haplotype analysis P = 0.0002). No association with BP or EHT was evident in males. An association with EHT was seen for the minor allele of rs2802292 in the Japanese SONIC cohort ( P = 0.03), while in European subjects the minor allele of each SNP was associated with higher systolic and diastolic BP. CONCLUSION Longevity-associated FOXO3 variants may be associated with lower BP and EHT in Japanese women.
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Affiliation(s)
| | - Randi Chen
- Honolulu Heart Program (HHP)/Honolulu-Asia Aging Study (HAAS), Department of Research, Kuakini Medical Center, Honolulu, Hawaii
| | - Timothy A. Donlon
- Honolulu Heart Program (HHP)/Honolulu-Asia Aging Study (HAAS), Department of Research, Kuakini Medical Center, Honolulu, Hawaii
| | - Daniel S. Evans
- California Pacific Medical Center Research Institute, San Francisco, California
| | - Gregory J. Tranah
- California Pacific Medical Center Research Institute, San Francisco, California
| | - Neeta Parimi
- California Pacific Medical Center Research Institute, San Francisco, California
| | - Georg B. Ehret
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Christopher Newton-Cheh
- Massachusetts General Hospital, Harvard Medical School, Broad Institute of Harvard and MIT, Boston, Massachusetts
| | - Todd Seto
- Department of Cardiology, The Queen’s Medical Center, Honolulu, Hawaii
| | - D. Craig Willcox
- Honolulu Heart Program (HHP)/Honolulu-Asia Aging Study (HAAS), Department of Research, Kuakini Medical Center, Honolulu, Hawaii
- Department of Geriatric Medicine, John A. Burns School of Medicine, University of Hawaii, Honolulu, Hawaii
- Department of Human Welfare, Okinawa International University, Okinawa, Japan
| | - Kamal H. Masaki
- Honolulu Heart Program (HHP)/Honolulu-Asia Aging Study (HAAS), Department of Research, Kuakini Medical Center, Honolulu, Hawaii
- Department of Geriatric Medicine, John A. Burns School of Medicine, University of Hawaii, Honolulu, Hawaii
| | - Kei Kamide
- Department of Health Science and
- Department of Geriatric Medicine and Nephrology, Osaka University, Graduate School of Medicine, Suita, Japan
| | | | - Ryosuke Oguro
- Department of Geriatric Medicine and Nephrology, Osaka University, Graduate School of Medicine, Suita, Japan
| | - Chikako Nakama
- Department of Geriatric Medicine and Nephrology, Osaka University, Graduate School of Medicine, Suita, Japan
| | | | - Koichi Yamamoto
- Department of Geriatric Medicine and Nephrology, Osaka University, Graduate School of Medicine, Suita, Japan
| | - Ken Sugimoto
- Department of Geriatric Medicine and Nephrology, Osaka University, Graduate School of Medicine, Suita, Japan
| | - Kazunori Ikebe
- Department of Prosthodontics, Gerodontology and Oral Rehabilitation, Osaka University Graduate School of Dentistry, Suita, Japan
| | - Yukie Masui
- Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, Tokyo, Japan
| | | | - Tatsuro Ishizaki
- Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology, Tokyo, Japan
| | - Yasuyuki Gondo
- Department of Clinical Thanatology and Geriatric Behavioral Science, Osaka University Graduate School of Human Sciences, Suita, Japan
| | - Hiromi Rakugi
- Department of Geriatric Medicine and Nephrology, Osaka University, Graduate School of Medicine, Suita, Japan
| | - Bradley J. Willcox
- Honolulu Heart Program (HHP)/Honolulu-Asia Aging Study (HAAS), Department of Research, Kuakini Medical Center, Honolulu, Hawaii
- Department of Geriatric Medicine, John A. Burns School of Medicine, University of Hawaii, Honolulu, Hawaii
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Franceschini N, Carty CL, Lu Y, Tao R, Sung YJ, Manichaikul A, Haessler J, Fornage M, Schwander K, Zubair N, Bien S, Hindorff LA, Guo X, Bielinski SJ, Ehret G, Kaufman JD, Rich SS, Carlson CS, Bottinger EP, North KE, Rao DC, Chakravarti A, Barrett PQ, Loos RJF, Buyske S, Kooperberg C. Variant Discovery and Fine Mapping of Genetic Loci Associated with Blood Pressure Traits in Hispanics and African Americans. PLoS One 2016; 11:e0164132. [PMID: 27736895 PMCID: PMC5063457 DOI: 10.1371/journal.pone.0164132] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2016] [Accepted: 09/12/2016] [Indexed: 01/11/2023] Open
Abstract
Despite the substantial burden of hypertension in US minority populations, few genetic studies of blood pressure have been conducted in Hispanics and African Americans, and it is unclear whether many of the established loci identified in European-descent populations contribute to blood pressure variation in non-European descent populations. Using the Metabochip array, we sought to characterize the genetic architecture of previously identified blood pressure loci, and identify novel cardiometabolic variants related to systolic and diastolic blood pressure in a multi-ethnic US population including Hispanics (n = 19,706) and African Americans (n = 18,744). Several known blood pressure loci replicated in African Americans and Hispanics. Fourteen variants in three loci (KCNK3, FGF5, ATXN2-SH2B3) were significantly associated with blood pressure in Hispanics. The most significant diastolic blood pressure variant identified in our analysis, rs2586886/KCNK3 (P = 5.2 x 10−9), also replicated in independent Hispanic and European-descent samples. African American and trans-ethnic meta-analysis data identified novel variants in the FGF5, ULK4 and HOXA-EVX1 loci, which have not been previously associated with blood pressure traits. Our identification and independent replication of variants in KCNK3, a gene implicated in primary hyperaldosteronism, as well as a variant in HOTTIP (HOXA-EVX1) suggest that further work to clarify the roles of these genes may be warranted. Overall, our findings suggest that loci identified in European descent populations also contribute to blood pressure variation in diverse populations including Hispanics and African Americans—populations that are understudied for hypertension genetic risk factors.
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Affiliation(s)
- Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America
- * E-mail:
| | - Cara L. Carty
- Center for Translational Science, George Washington University and Children’s National Medical Center, Washington, District of Columbia, United States of America
| | - Yingchang Lu
- Genetics of Obesity and Related Metabolic Traits Program, The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Ran Tao
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Yun Ju Sung
- Division of Biostatistics, Washington University, St. Louis, Missouri, United States of America
| | - Ani Manichaikul
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, 22908, United States of America
| | - Jeff Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine & Human Genetics Center, University of Texas Health Science Center, Houston, Texas, United States of America
| | - Karen Schwander
- Division of Biostatistics, Washington University, St. Louis, Missouri, United States of America
| | - Niha Zubair
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Stephanie Bien
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Lucia A. Hindorff
- Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, LABiomed at Harbor-University of California at Los Angeles Medical Center, Torrance, California, United States of America
| | - Suzette J. Bielinski
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Georg Ehret
- Center for Complex Disease Genomics, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Department of Specialties of Internal Medicine, Geneva University Hospital, Geneva, Switzerland
| | - Joel D. Kaufman
- Department of Environmental and Occupational Health Sciences, Epidemiology, and Medicine, University of Washington, Seattle, Washington, United States of America
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, 22908, United States of America
| | - Christopher S. Carlson
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Erwin P. Bottinger
- Genetics of Obesity and Related Metabolic Traits Program, The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Kari E. North
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - D. C. Rao
- Division of Biostatistics, Washington University, St. Louis, Missouri, United States of America
| | - Aravinda Chakravarti
- Center for Complex Disease Genomics, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Paula Q. Barrett
- Department of Pharmacology, University of Virginia, Charlottesville, Virginia, United States of America
| | - Ruth J. F. Loos
- Genetics of Obesity and Related Metabolic Traits Program, The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Steven Buyske
- Department of Statistics and Biostatistics, Rutgers University, Piscataway, New Jersey, United States of America
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
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Schmidt MF, Freeman KB, Windham BG, Griswold ME, Kullo IJ, Turner ST, Mosley TH. Associations Between Serum Inflammatory Markers and Hippocampal Volume in a Community Sample. J Am Geriatr Soc 2016; 64:1823-9. [PMID: 27549073 DOI: 10.1111/jgs.14283] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
OBJECTIVES To quantify associations between inflammatory biomarkers and hippocampal volume (HV) and to examine effect modification according to sex, race, and age. DESIGN Cross-sectional analyses using generalized estimating equations to account for familial clustering; standardized β-coefficients adjusted for age, sex, race, and education. SETTING Community cohorts in Jackson, Mississippi and Rochester, Minnesota. PARTICIPANTS The Genetic Epidemiology Network of Arteriopathy study. MEASUREMENTS C-reactive protein (CRP), interleukin-6 (IL-6), and soluble tumor necrosis factor receptors 1 (sTNFR-1) and 2 (sTNFR-2) from peripheral blood were measured in a sample of 773 non-Hispanic whites (61% women, aged 60.2 ± 9.8) and 514 African Americans (70% women, aged 63.9 ± 8.1) who also underwent brain magnetic resonance imaging. Biomarkers were standardized and compared according to sex, race and age with HV. RESULTS In the full sample, higher sTNFR-1 and sTNFR-2 were associated with smaller HV. Each standard deviation (SD) increase in sTNFR-1 was associated with 59.1 mm(3) (95% confidence interval (CI) = -101.4 to -16.7 mm(3) ) smaller HV and each SD increase in sTNFR-2 associated with 48.8 mm(3) (95% CI = -92.2 to -5.3 mm(3) ) smaller HV. Relationships were stronger for sTNFR-2 in men (HV = -116.6 mm(3) for each SD increase, 95% CI = -201.0 to -32.1) than women (HV = -26.0 per SD increase, 95% CI = -72.4-20.5) and sTNFR-1 in non-Hispanic whites (HV = -84.7 mm(3) per SD increase, 95% CI = -142.2 to -27.1) than African Americans (HV = -14.1 mm(3) per SD increase, 95% CI = -78.3-50.1). Associations between IL-6 or CRP and HV were not supported. CONCLUSION Higher levels of sTNFRs were associated cross-sectionally with smaller hippocampi. Longitudinal data are needed to determine whether these biomarkers may help to identify risk of late-life cognitive impairment.
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Affiliation(s)
- Mike F Schmidt
- Program in Neuroscience, University of Mississippi Medical Center, Jackson, Mississippi.,Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi
| | - Kevin B Freeman
- Department of Psychiatry and Human Behavior, University of Mississippi Medical Center, Jackson, Mississippi
| | - Beverly G Windham
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi
| | - Michael E Griswold
- Center of Biostatistics and Bioinformatics, University of Mississippi Medical Center, Jackson, Mississippi
| | - Iftikhar J Kullo
- Division of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota
| | - Stephen T Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Thomas H Mosley
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi.
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Taylor JY, Schwander K, Kardia SLR, Arnett D, Liang J, Hunt SC, Rao DC, Sun YV. A Genome-wide study of blood pressure in African Americans accounting for gene-smoking interaction. Sci Rep 2016; 6:18812. [PMID: 26752167 PMCID: PMC4707536 DOI: 10.1038/srep18812] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2015] [Accepted: 11/09/2015] [Indexed: 12/28/2022] Open
Abstract
Cigarette smoking has been shown to be a health hazard. In addition to being considered a negative lifestyle behavior, studies have shown that cigarette smoking has been linked to genetic underpinnings of hypertension. Because African Americans have the highest incidence and prevalence of hypertension, we examined the joint effect of genetics and cigarette smoking on health among this understudied population. The sample included African Americans from the genome wide association studies of HyperGEN (N = 1083, discovery sample) and GENOA (N = 1427, replication sample), both part of the FBPP. Results suggested that 2 SNPs located on chromosomes 14 (NEDD8; rs11158609; raw p = 9.80 × 10−9, genomic control-adjusted p = 2.09 × 10−7) and 17 (TTYH2; rs8078051; raw p = 6.28 × 10−8, genomic control-adjusted p = 9.65 × 10−7) were associated with SBP including the genetic interaction with cigarette smoking. These two SNPs were not associated with SBP in a main genetic effect only model. This study advances knowledge in the area of main and joint effects of genetics and cigarette smoking on hypertension among African Americans and offers a model to the reader for assessing these risks. More research is required to determine how these genes play a role in expression of hypertension.
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Affiliation(s)
| | - Karen Schwander
- Division of Biostatistics, School of Medicine, Washington University in St. Louis, St. Louis
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor
| | - Donna Arnett
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham
| | - Jingjing Liang
- Department of Epidemiology and Biostatistics, School of Medicine, Case Western Reserve University, Cleveland
| | - Steven C Hunt
- Cardiovascular Genetics Division, School of Medicine, University of Utah, Salt Lake City
| | - D C Rao
- Division of Biostatistics, School of Medicine, Washington University in St. Louis, St. Louis
| | - Yan V Sun
- Department of Epidemiology, Rollins School of Public Health, Emory University.,Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta
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Li W, Turner A, Aggarwal P, Matter A, Storvick E, Arnett DK, Broeckel U. Comprehensive evaluation of AmpliSeq transcriptome, a novel targeted whole transcriptome RNA sequencing methodology for global gene expression analysis. BMC Genomics 2015; 16:1069. [PMID: 26673413 PMCID: PMC4681149 DOI: 10.1186/s12864-015-2270-1] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2015] [Accepted: 12/03/2015] [Indexed: 12/29/2022] Open
Abstract
Background Whole transcriptome sequencing (RNA-seq) represents a powerful approach for whole transcriptome gene expression analysis. However, RNA-seq carries a few limitations, e.g., the requirement of a significant amount of input RNA and complications led by non-specific mapping of short reads. The Ion AmpliSeq™ Transcriptome Human Gene Expression Kit (AmpliSeq) was recently introduced by Life Technologies as a whole-transcriptome, targeted gene quantification kit to overcome these limitations of RNA-seq. To assess the performance of this new methodology, we performed a comprehensive comparison of AmpliSeq with RNA-seq using two well-established next-generation sequencing platforms (Illumina HiSeq and Ion Torrent Proton). We analyzed standard reference RNA samples and RNA samples obtained from human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs). Results Using published data from two standard RNA reference samples, we observed a strong concordance of log2 fold change for all genes when comparing AmpliSeq to Illumina HiSeq (Pearson’s r = 0.92) and Ion Torrent Proton (Pearson’s r = 0.92). We used ROC, Matthew’s correlation coefficient and RMSD to determine the overall performance characteristics. All three statistical methods demonstrate AmpliSeq as a highly accurate method for differential gene expression analysis. Additionally, for genes with high abundance, AmpliSeq outperforms the two RNA-seq methods. When analyzing four closely related hiPSC-CM lines, we show that both AmpliSeq and RNA-seq capture similar global gene expression patterns consistent with known sources of variations. Conclusions Our study indicates that AmpliSeq excels in the limiting areas of RNA-seq for gene expression quantification analysis. Thus, AmpliSeq stands as a very sensitive and cost-effective approach for very large scale gene expression analysis and mRNA marker screening with high accuracy. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-2270-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Wenli Li
- Department of Pediatrics, Section of Genomic Pediatrics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.
| | - Amy Turner
- Department of Pediatrics, Section of Genomic Pediatrics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.
| | - Praful Aggarwal
- Department of Pediatrics, Section of Genomic Pediatrics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.
| | - Andrea Matter
- Department of Pediatrics, Section of Genomic Pediatrics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.
| | - Erin Storvick
- Department of Pediatrics, Section of Genomic Pediatrics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.
| | - Donna K Arnett
- Department of Epidemiology, University of Alabama at Birmingham, 1530 3rd Avenue South, Birmingham, AL, 35294, USA.
| | - Ulrich Broeckel
- Department of Pediatrics, Section of Genomic Pediatrics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.
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30
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Hypertension in pregnancy is associated with elevated C-reactive protein levels later in life. J Hypertens 2015; 31:2213-9; discussion 2219. [PMID: 24029867 DOI: 10.1097/hjh.0b013e3283642f6c] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
OBJECTIVES We assessed whether hypertension in pregnancy is associated with elevated C-reactive protein (CRP) levels in later life, possibly reflecting an increased risk of cardiovascular disease (CVD). BACKGROUND Elevated CRP levels have been associated with hypertension in pregnancy and with CVD. METHODS We studied 2463 women from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. Participants were categorized as nulliparous women (n = 219), women with a history of normotensive pregnancies (n = 1839), or women with a history of a hypertensive pregnancy (n = 405). Using multiple linear regression models, we compared mean CRP levels among the groups after adjusting for age, race, education, smoking, hypertension, personal history of coronary heart disease (CHD) or stroke, diabetes, dyslipidemia, statins, hormone replacement therapy, and family history of CHD or stroke. As CRP levels may be influenced by BMI, the model was fit both with and without adjusting for BMI. RESULTS There was no significant difference in CRP levels between nulliparous women and those with a history of normotensive pregnancies, either with (P = 0.82) or without (P = 0.46) adjusting for BMI. In contrast, women with hypertensive pregnancies, compared with those with normotensive pregnancies, had higher CRP levels, both with (P = 0.009) and without (P < 0.001) adjusting for BMI. CONCLUSION A history of hypertension in pregnancy is associated with elevated CRP levels later in life, independent of traditional CVD risk factors and BMI. An elevated CRP may reflect an inflammatory state in women with a history of hypertensive pregnancy disorders who are at increased risk for CVD.
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31
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Hickson LJ, Rule AD, Butler KR, Schwartz GL, Jaffe AS, Bartley AC, Mosley TH, Turner ST. Troponin T as a Predictor of End-Stage Renal Disease and All-Cause Death in African Americans and Whites From Hypertensive Families. Mayo Clin Proc 2015; 90:1482-91. [PMID: 26494378 PMCID: PMC4636977 DOI: 10.1016/j.mayocp.2015.08.016] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2015] [Revised: 08/10/2015] [Accepted: 08/12/2015] [Indexed: 01/13/2023]
Abstract
OBJECTIVE To evaluate cardiac troponin T (cTnT) as a predictor of end-stage renal disease (ESRD) and death in a cohort of African American and white community-dwelling adults with hypertensive families. PATIENTS AND METHODS A total of 3050 participants (whites from Rochester, Minnesota; African Americans from Jackson, Mississippi) of the Genetic Epidemiology Network of Arteriopathy study were followed from baseline examination (June 1, 1996, through August 31, 2000) through January 22, 2010. Cox proportional hazards regression models were used to examine the association of cTnT with ESRD and death after adjusting for traditional risk factors. RESULTS Cohort demographic characteristics and measurements included 1395 whites (45.7%), 2174 hypertensive (71.3%), 992 estimated glomerular filtration rate of less than 60 mL/min per 1.73 m(2) (32.5%), 1574 high-sensitivity C-reactive protein level of greater than 3 mg/L (51.6%), and 66 abnormal cTnT level of 0.01 ng/mL or higher (2.2%). The estimated cumulative incidence of ESRD at 10 years was 27.4% among those with abnormal cTnT levels compared with 1.3% for those with normal levels. Similarly, the estimated cumulative incidence of death at 10 years was 47% among those with abnormal cTnT compared with 7.3% among those with normal cTnT. Abnormal cTnT levels were strongly associated with ESRD and death. This effect was attenuated but was still highly significant after adjustment for demographic characteristics, estimated glomerular filtration rate, and traditional risk factors for ESRD (unadjusted hazard ratio [HR], 23.91; 95% CI, 12.9-44.2; adjusted HR, 2.81; 95% CI, 1.3-5.9) and death (unadjusted HR, 8.43; 95% CI, 6.0-11.9; adjusted HR, 3.46; 95% CI, 2.3-5.1). CONCLUSION Cardiac troponin T makes an independent contribution to the prediction of ESRD and all-cause death in community-dwelling individuals beyond traditional risk markers. Further studies may be needed to determine whether cTnT screening in individuals with hypertension or in a subset of hypertensive individuals would help identify those at risk of ESRD and all-cause death.
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Affiliation(s)
- LaTonya J Hickson
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN; Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN.
| | - Andrew D Rule
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | - Kenneth R Butler
- Division of Geriatric Medicine, University of Mississippi Medical Center, Jackson, MS
| | - Gary L Schwartz
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | - Allan S Jaffe
- Division of Cardiovascular Diseases, Department of Medicine, Mayo Clinic, Rochester, MN; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Adam C Bartley
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Thomas H Mosley
- Division of Geriatric Medicine, University of Mississippi Medical Center, Jackson, MS
| | - Stephen T Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
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Wang W, Griswold ME. Natural interpretations in Tobit regression models using marginal estimation methods. Stat Methods Med Res 2015; 26:2622-2632. [PMID: 26329751 DOI: 10.1177/0962280215602716] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The Tobit model, also known as a censored regression model to account for left- and/or right-censoring in the dependent variable, has been used in many areas of applications, including dental health, medical research and economics. The reported Tobit model coefficient allows estimation and inference of an exposure effect on the latent dependent variable. However, this model does not directly provide overall exposure effects estimation on the original outcome scale. We propose a direct-marginalization approach using a reparameterized link function to model exposure and covariate effects directly on the truncated dependent variable mean. We also discuss an alternative average-predicted-value, post-estimation approach which uses model-predicted values for each person in a designated reference group under different exposure statuses to estimate covariate-adjusted overall exposure effects. Simulation studies were conducted to show the unbiasedness and robustness properties for both approaches under various scenarios. Robustness appears to diminish when covariates with substantial effects are imbalanced between exposure groups; we outline an approach for model choice based on information criterion fit statistics. The methods are applied to the Genetic Epidemiology Network of Arteriopathy (GENOA) cohort study to assess associations between obesity and cognitive function in the non-Hispanic white participants.
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Affiliation(s)
- Wei Wang
- Center of Biostatistics and Bioinformatics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Michael E Griswold
- Center of Biostatistics and Bioinformatics, University of Mississippi Medical Center, Jackson, MS, USA
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33
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Weissgerber TL, Milic NM, Turner ST, Asad RA, Mosley TH, Kardia SLR, Hanis CL, Garovic VD. Uric Acid: A Missing Link Between Hypertensive Pregnancy Disorders and Future Cardiovascular Disease? Mayo Clin Proc 2015; 90:1207-16. [PMID: 26260220 PMCID: PMC4567408 DOI: 10.1016/j.mayocp.2015.05.020] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2015] [Revised: 05/07/2015] [Accepted: 05/22/2015] [Indexed: 10/23/2022]
Abstract
OBJECTIVE To determine whether women who had a hypertensive pregnancy disorder (HPD) have elevated uric acid concentrations decades after pregnancy as compared with women who had normotensive pregnancies. PATIENTS AND METHODS The Genetic Epidemiology Network of Arteriopathy study measured uric acid concentrations in Hispanic (30%), non-Hispanic white (28%), and non-Hispanic black (42%) women (mean age, 60 ± 10 years). This cross-sectional study was conducted between July 1, 2000, and December 31, 2004. Hispanic participants were recruited from families with high rates of diabetes, whereas non-Hispanic participants were recruited from families with high rates of hypertension. This analysis compared uric acid concentrations in women with a history of normotensive (n = 1846) or hypertensive (n = 408) pregnancies by logistic regression. RESULTS Women who had an HPD had higher uric acid concentrations (median, 5.7 mg/dL vs 5.3 mg/dL; P < .001) and were more likely to have uric acid concentrations above 5.5 mg/dL (54.4% vs 42.4%; P = .001) than were women who had normotensive pregnancies. These differences persisted after adjusting for traditional cardiovascular risk factors, comorbidities, and other factors that affect uric acid concentrations. A family-based subgroup analysis comparing uric acid concentrations in women who had an HPD (n = 308) and their parous sisters who had normotensive pregnancies (n = 250) gave similar results (median uric acid concentrations, 5.7 mg/dL vs 5.2 mg/dL, P = 0.02; proportion of women with uric acid concentrations > 5.5 mg/dL, 54.0% vs 40.3%, P < .001). CONCLUSION Decades after pregnancy, women who had an HPD have higher uric acid concentrations. This effect does not appear to be explained by a familial predisposition to elevated uric acid concentrations.
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Affiliation(s)
| | - Natasa M Milic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN; Medical Faculty, Department of Biostatistics, University of Belgrade, Belgrade, Serbia
| | - Stephen T Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
| | - Reem A Asad
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN; Al Adan Hospital, Ministry of Health, Kuwait
| | | | | | - Craig L Hanis
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston
| | - Vesna D Garovic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN
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Weissgerber TL, Turner ST, Mosley TH, Kardia SLR, Hanis CL, Milic NM, Garovic VD. Hypertension in Pregnancy and Future Cardiovascular Event Risk in Siblings. J Am Soc Nephrol 2015; 27:894-902. [PMID: 26315531 DOI: 10.1681/asn.2015010086] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2015] [Accepted: 06/03/2015] [Indexed: 01/23/2023] Open
Abstract
Hypertension in pregnancy is a risk factor for future hypertension and cardiovascular disease. This may reflect an underlying familial predisposition or persistent damage caused by the hypertensive pregnancy. We sought to isolate the effect of hypertension in pregnancy by comparing the risk of hypertension and cardiovascular disease in women who had hypertension in pregnancy and their sisters who did not using the dataset from the Genetic Epidemiology Network of Arteriopathy study, which examined the genetics of hypertension in white, black, and Hispanic siblings. This analysis included all sibships with at least one parous woman and at least one other sibling. After gathering demographic and pregnancy data, BP and serum analytes were measured. Disease-free survival was examined using Kaplan-Meier curves and Cox proportional hazards regression. Compared with their sisters who did not have hypertension in pregnancy, women who had hypertension in pregnancy were more likely to develop new onset hypertension later in life, after adjusting for body mass index and diabetes (hazard ratio 1.75, 95% confidence interval 1.27-2.42). A sibling history of hypertension in pregnancy was also associated with an increased risk of hypertension in brothers and unaffected sisters, whereas an increased risk of cardiovascular events was observed in brothers only. These results suggest familial factors contribute to the increased risk of future hypertension in women who had hypertension in pregnancy. Further studies are needed to clarify the potential role of nonfamilial factors. Furthermore, a sibling history of hypertension in pregnancy may be a novel familial risk factor for future hypertension.
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Affiliation(s)
| | - Stephen T Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
| | - Thomas H Mosley
- University of Mississippi Medical Center, Jackson, Mississippi
| | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan
| | - Craig L Hanis
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas; and
| | - Natasa M Milic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota; Department of Biostatistics, Medical Faculty, University of Belgrade, Belgrade, Serbia
| | - Vesna D Garovic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota
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35
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Scantlebury DC, Kane GC, Wiste HJ, Bailey KR, Turner ST, Arnett DK, Devereux RB, Mosley TH, Hunt SC, Weder AB, Rodriguez B, Boerwinkle E, Weissgerber TL, Garovic VD. Left ventricular hypertrophy after hypertensive pregnancy disorders. Heart 2015; 101:1584-90. [PMID: 26243788 DOI: 10.1136/heartjnl-2015-308098] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2015] [Accepted: 07/09/2015] [Indexed: 12/21/2022] Open
Abstract
OBJECTIVE Cardiac changes of hypertensive pregnancy include left ventricular hypertrophy (LVH) and diastolic dysfunction. These are thought to regress postpartum. We hypothesised that women with a history of hypertensive pregnancy would have altered LV geometry and function when compared with women with only normotensive pregnancies. METHODS In this cohort study, we analysed echocardiograms of 2637 women who participated in the Family Blood Pressure Program. We compared LV mass and function in women with hypertensive pregnancies with those with normotensive pregnancies. RESULTS Women were evaluated at a mean age of 56 years: 427 (16%) had at least one hypertensive pregnancy; 2210 (84%) had normotensive pregnancies. Compared with women with normotensive pregnancies, women with hypertensive pregnancy had a greater risk of LVH (OR: 1.42; 95% CI 1.01 to 1.99, p=0.05), after adjusting for age, race, research network of the Family Blood Pressure Program, education, parity, BMI, hypertension and diabetes. When duration of hypertension was taken into account, this relationship was no longer significant (OR: 1.19; CI 0.08 to 1.78, p=0.38). Women with hypertensive pregnancies also had greater left atrial size and lower mitral E/A ratio after adjusting for demographic variables. The prevalence of systolic dysfunction was similar between the groups. CONCLUSIONS A history of hypertensive pregnancy is associated with LVH after adjusting for risk factors; this might be explained by longer duration of hypertension. This finding supports current guidelines recommending surveillance of women following a hypertensive pregnancy, and sets the stage for longitudinal echocardiographic studies to further elucidate progression of LV geometry and function after pregnancy. CLINICAL TRIAL REGISTRATIONS GENOA- NCT00005269; HyperGEN- NCT00005267; Sapphire- NCT00005270; GenNet- NCT00005268.
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Affiliation(s)
- Dawn C Scantlebury
- Division of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota, USA
| | - Garvan C Kane
- Division of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota, USA
| | - Heather J Wiste
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA
| | - Kent R Bailey
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA
| | - Stephen T Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA
| | - Donna K Arnett
- University of Alabama at Birmingham, Birmingham, Alabama, USA
| | | | - Thomas H Mosley
- University of Mississippi Medical Center, Jackson, Mississippi, USA
| | | | - Alan B Weder
- University of Michigan, Ann Arbor, Michigan, USA
| | | | | | | | - Vesna D Garovic
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA
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de Andrade M, Ray D, Pereira AC, Soler JP. Global Individual Ancestry Using Principal Components for Family Data. Hum Hered 2015; 80:1-11. [PMID: 26159893 DOI: 10.1159/000381908] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
Studies of complex human diseases and traits associated with candidate genes are potentially vulnerable to bias (confounding) due to population stratification and inbreeding, especially in admixed population. In GWAS, the principal components (PCs) method provides a global ancestry value per subject, allowing corrections for population stratification. However, these coefficients are typically estimated assuming unrelated individuals, and if family structure is present and ignored, such substructures may induce artifactual PCs. Extensions of the PCs method have been proposed by Konishi and Rao [Biometrika 1992;79:631-641], taking into account only siblings' relatedness, and by Oualkacha et al. [Stat Appl Genet Mol Biol 2012, DOI: 10.2202/1544-6115.1711], taking into account large pedigrees and high-dimensional phenotype data. In this work, we extend these methods to estimate the global individual ancestry coefficients from PCs derived from different variance component matrix estimators using SNPs from two simulated data sets and two real data sets: the GENOA sibship data consisting of European and African-American subjects and the Baependi Heart Study consisting of 80 extended Brazilian families, both with genotyping data from the Affymetrix 6.0 chip. Our results show that the family structure plays an important role in the estimation of the global individual ancestry value for extended pedigrees but not for sibships.
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Affiliation(s)
- Mariza de Andrade
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minn., USA
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Dauriz M, Porneala BC, Guo X, Bielak LF, Peyser PA, Durant NH, Carnethon MR, Bonadonna RC, Bonora E, Bowden DW, Florez JC, Fornage M, Hivert MF, Jacobs DR, Kabagambe EK, Lewis CE, Murabito JM, Rasmussen-Torvik LJ, Rich SS, Vassy JL, Yao J, Carr JJ, Kardia SL, Siscovick D, O'Donnell CJ, Rotter JI, Dupuis J, Meigs JB. Association of a 62 Variants Type 2 Diabetes Genetic Risk Score With Markers of Subclinical Atherosclerosis: A Transethnic, Multicenter Study. CIRCULATION. CARDIOVASCULAR GENETICS 2015; 8:507-15. [PMID: 25805414 PMCID: PMC4472563 DOI: 10.1161/circgenetics.114.000740] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2014] [Accepted: 03/09/2015] [Indexed: 12/19/2022]
Abstract
BACKGROUND Type 2 diabetes mellitus (T2D) and cardiovascular disease share risk factors and subclinical atherosclerosis (SCA) predicts events in those with and without diabetes mellitus. T2D genetic risk may predict both T2D and SCA. We hypothesized that greater T2D genetic risk is associated with higher extent of SCA. METHODS AND RESULTS In a cross-sectional analysis, including ≤9210 European Americans, 3773 African Americans, 1446 Hispanic Americans, and 773 Chinese Americans without known cardiovascular disease and enrolled in the Framingham Heart Study, Coronary Artery Risk Development in Young Adults, Multi-Ethnic Study of Atherosclerosis, and Genetic Epidemiology Network of Arteriopathy studies, we tested a 62 T2D-loci genetic risk score for association with measures of SCA, including coronary artery or abdominal aortic calcium score, common and internal carotid artery intima-media thickness, and ankle-brachial index. We used ancestry-stratified linear regression models, with random effects accounting for family relatedness when appropriate, applying a genetic-only (adjusted for sex) and a full SCA risk factors-adjusted model (significance, P<0.01=0.05/5, number of traits analyzed). An inverse association with coronary artery calcium score in Multi-Ethnic Study of Atherosclerosis Europeans (fully-adjusted P=0.004) and with common carotid artery intima-media thickness in the Framingham Heart Study (P=0.009) was not confirmed in other study cohorts, either separately or in meta-analysis. Secondary analyses showed no consistent associations with β-cell and insulin resistance genetic risk sub-scores in the Framingham Heart Study and in the Coronary Artery Risk Development in Young Adults. CONCLUSIONS SCA does not have a major genetic component linked to a burden of 62 T2D loci identified by large genome-wide association studies. A shared T2D-SCA genetic basis, if any, might become apparent from better functional information about both T2D and cardiovascular disease risk loci.
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Affiliation(s)
- Marco Dauriz
- General Medicine Division, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, University of Verona Medical School & Hospital Trust of Verona, Verona, Italy
| | - Bianca C. Porneala
- General Medicine Division, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Xiuqing Guo
- Institute for Translational Genomics & Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA
| | - Lawrence F. Bielak
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI
| | - Patricia A. Peyser
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI
| | - Nefertiti H. Durant
- Division of Pediatrics & Adolescent Medicine, Department of Pediatrics, University of Alabama Birmingham School of Medicine, Birmingham, AL
| | - Mercedes R. Carnethon
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Riccardo C. Bonadonna
- Division of Endocrinology, Department of Clinical & Experimental Medicine, University of Parma School of Medicine & AOI of Parma, Parma, Italy
| | - Enzo Bonora
- Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, University of Verona Medical School & Hospital Trust of Verona, Verona, Italy
| | - Donald W. Bowden
- Centers for Diabetes Research & Human Genomics, Wake Forest School of Medicine, Winston-Salem, NC
- Department of Biochemistry & Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC
| | - Jose C. Florez
- Department of Medicine, Harvard Medical School, Boston, MA
- Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA
- Program in Medical & Population Genetics, Broad Institute, Cambridge, MA
| | - Myriam Fornage
- Institute of Molecular Medicine & Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX
| | - Marie-France Hivert
- Harvard Pilgrim Health Care Institute, Department of Population Medicine, Harvard Medical School, Boston, MA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA
- Division of Endocrinology & Metabolism, Department of Medicine, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - David R. Jacobs
- Division of Epidemiology & Community Health, School of Public Health, University of Minnesota, Minneapolis, MN
| | - Edmond K. Kabagambe
- Division of Epidemiology, Department of Medicine, Vanderbilt University, Nashville, TN
| | - Cora E. Lewis
- Department of Epidemiology, University of Alabama Birmingham School of Public Health, Birmingham, AL
| | - Joanne M. Murabito
- Department of Medicine, Section of General Internal Medicine, Boston University School of Medicine, Boston
- National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA
| | | | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA
| | - Jason L. Vassy
- Department of Medicine, Harvard Medical School, Boston, MA
- Section of General Internal Medicine, VA Boston Healthcare System, Boston, MA
- Division of General Internal Medicine & Primary Care, Brigham and Women's Hospital, Boston, MA
| | - Jie Yao
- Institute for Translational Genomics & Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA
| | | | - Sharon L.R. Kardia
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI
| | | | - Christopher J. O'Donnell
- Department of Medicine, Harvard Medical School, Boston, MA
- National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA
- Cardiology Division, Department of Medicine, Massachusetts General Hospital & Harvard Medical School, Boston, MA
| | - Jerome I. Rotter
- Institute for Translational Genomics & Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA
| | - Josée Dupuis
- National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - James B. Meigs
- General Medicine Division, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
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A statistical approach for rare-variant association testing in affected sibships. Am J Hum Genet 2015; 96:543-54. [PMID: 25799106 DOI: 10.1016/j.ajhg.2015.01.020] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2014] [Accepted: 01/30/2015] [Indexed: 11/21/2022] Open
Abstract
Sequencing and exome-chip technologies have motivated development of novel statistical tests to identify rare genetic variation that influences complex diseases. Although many rare-variant association tests exist for case-control or cross-sectional studies, far fewer methods exist for testing association in families. This is unfortunate, because cosegregation of rare variation and disease status in families can amplify association signals for rare variants. Many researchers have begun sequencing (or genotyping via exome chips) familial samples that were either recently collected or previously collected for linkage studies. Because many linkage studies of complex diseases sampled affected sibships, we propose a strategy for association testing of rare variants for use in this study design. The logic behind our approach is that rare susceptibility variants should be found more often on regions shared identical by descent by affected sibling pairs than on regions not shared identical by descent. We propose both burden and variance-component tests of rare variation that are applicable to affected sibships of arbitrary size and that do not require genotype information from unaffected siblings or independent controls. Our approaches are robust to population stratification and produce analytic p values, thereby enabling our approach to scale easily to genome-wide studies of rare variation. We illustrate our methods by using simulated data and exome chip data from sibships ascertained for hypertension collected as part of the Genetic Epidemiology Network of Arteriopathy (GENOA) study.
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Shetty PB, Tang H, Feng T, Tayo B, Morrison AC, Kardia SLR, Hanis CL, Arnett DK, Hunt SC, Boerwinkle E, Rao DC, Cooper RS, Risch N, Zhu X. Variants for HDL-C, LDL-C, and triglycerides identified from admixture mapping and fine-mapping analysis in African American families. CIRCULATION. CARDIOVASCULAR GENETICS 2015; 8:106-13. [PMID: 25552592 PMCID: PMC4378661 DOI: 10.1161/circgenetics.114.000481] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
BACKGROUND Admixture mapping of lipids was followed-up by family-based association analysis to identify variants for cardiovascular disease in African Americans. METHODS AND RESULTS The present study conducted admixture mapping analysis for total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. The analysis was performed in 1905 unrelated African American subjects from the National Heart, Lung and Blood Institute's Family Blood Pressure Program (FBPP). Regions showing admixture evidence were followed-up with family-based association analysis in 3556 African American subjects from the FBPP. The admixture mapping and family-based association analyses were adjusted for age, age(2), sex, body mass index, and genome-wide mean ancestry to minimize the confounding caused by population stratification. Regions that were suggestive of local ancestry association evidence were found on chromosomes 7 (low-density lipoprotein cholesterol), 8 (high-density lipoprotein cholesterol), 14 (triglycerides), and 19 (total cholesterol and triglycerides). In the fine-mapping analysis, 52 939 single-nucleotide polymorphisms (SNPs) were tested and 11 SNPs (8 independent SNPs) showed nominal significant association with high-density lipoprotein cholesterol (2 SNPs), low-density lipoprotein cholesterol (4 SNPs), and triglycerides (5 SNPs). The family data were used in the fine-mapping to identify SNPs that showed novel associations with lipids and regions, including genes with known associations for cardiovascular disease. CONCLUSIONS This study identified regions on chromosomes 7, 8, 14, and 19 and 11 SNPs from the fine-mapping analysis that were associated with high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides for further studies of cardiovascular disease in African Americans.
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Affiliation(s)
- Priya B Shetty
- From the Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH (P.B.S., T.F., X.Z.); Department of Genetics, Stanford University School of Medicine, Stanford, CA (H.T.); Department of Public Health Sciences, Loyola University of Chicago Stritch School of Medicine, Maywood, IL (B.T., R.S.C.); Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health (A.C.M., C.L.H., E.B.); Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (S.L.R.K.); Department of Epidemiology, University of Alabama at Birmingham School of Public Health (D.K.A.); Cardiovascular Genetics Division, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City (S.C.H.); Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO (D.C. Rao); and Department of Epidemiology and Biostatistics, University of California, San Francisco (N.R.)
| | - Hua Tang
- From the Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH (P.B.S., T.F., X.Z.); Department of Genetics, Stanford University School of Medicine, Stanford, CA (H.T.); Department of Public Health Sciences, Loyola University of Chicago Stritch School of Medicine, Maywood, IL (B.T., R.S.C.); Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health (A.C.M., C.L.H., E.B.); Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (S.L.R.K.); Department of Epidemiology, University of Alabama at Birmingham School of Public Health (D.K.A.); Cardiovascular Genetics Division, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City (S.C.H.); Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO (D.C. Rao); and Department of Epidemiology and Biostatistics, University of California, San Francisco (N.R.)
| | - Tao Feng
- From the Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH (P.B.S., T.F., X.Z.); Department of Genetics, Stanford University School of Medicine, Stanford, CA (H.T.); Department of Public Health Sciences, Loyola University of Chicago Stritch School of Medicine, Maywood, IL (B.T., R.S.C.); Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health (A.C.M., C.L.H., E.B.); Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (S.L.R.K.); Department of Epidemiology, University of Alabama at Birmingham School of Public Health (D.K.A.); Cardiovascular Genetics Division, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City (S.C.H.); Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO (D.C. Rao); and Department of Epidemiology and Biostatistics, University of California, San Francisco (N.R.)
| | - Bamidele Tayo
- From the Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH (P.B.S., T.F., X.Z.); Department of Genetics, Stanford University School of Medicine, Stanford, CA (H.T.); Department of Public Health Sciences, Loyola University of Chicago Stritch School of Medicine, Maywood, IL (B.T., R.S.C.); Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health (A.C.M., C.L.H., E.B.); Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (S.L.R.K.); Department of Epidemiology, University of Alabama at Birmingham School of Public Health (D.K.A.); Cardiovascular Genetics Division, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City (S.C.H.); Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO (D.C. Rao); and Department of Epidemiology and Biostatistics, University of California, San Francisco (N.R.)
| | - Alanna C Morrison
- From the Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH (P.B.S., T.F., X.Z.); Department of Genetics, Stanford University School of Medicine, Stanford, CA (H.T.); Department of Public Health Sciences, Loyola University of Chicago Stritch School of Medicine, Maywood, IL (B.T., R.S.C.); Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health (A.C.M., C.L.H., E.B.); Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (S.L.R.K.); Department of Epidemiology, University of Alabama at Birmingham School of Public Health (D.K.A.); Cardiovascular Genetics Division, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City (S.C.H.); Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO (D.C. Rao); and Department of Epidemiology and Biostatistics, University of California, San Francisco (N.R.)
| | - Sharon L R Kardia
- From the Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH (P.B.S., T.F., X.Z.); Department of Genetics, Stanford University School of Medicine, Stanford, CA (H.T.); Department of Public Health Sciences, Loyola University of Chicago Stritch School of Medicine, Maywood, IL (B.T., R.S.C.); Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health (A.C.M., C.L.H., E.B.); Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (S.L.R.K.); Department of Epidemiology, University of Alabama at Birmingham School of Public Health (D.K.A.); Cardiovascular Genetics Division, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City (S.C.H.); Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO (D.C. Rao); and Department of Epidemiology and Biostatistics, University of California, San Francisco (N.R.)
| | - Craig L Hanis
- From the Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH (P.B.S., T.F., X.Z.); Department of Genetics, Stanford University School of Medicine, Stanford, CA (H.T.); Department of Public Health Sciences, Loyola University of Chicago Stritch School of Medicine, Maywood, IL (B.T., R.S.C.); Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health (A.C.M., C.L.H., E.B.); Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (S.L.R.K.); Department of Epidemiology, University of Alabama at Birmingham School of Public Health (D.K.A.); Cardiovascular Genetics Division, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City (S.C.H.); Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO (D.C. Rao); and Department of Epidemiology and Biostatistics, University of California, San Francisco (N.R.)
| | - Donna K Arnett
- From the Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH (P.B.S., T.F., X.Z.); Department of Genetics, Stanford University School of Medicine, Stanford, CA (H.T.); Department of Public Health Sciences, Loyola University of Chicago Stritch School of Medicine, Maywood, IL (B.T., R.S.C.); Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health (A.C.M., C.L.H., E.B.); Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (S.L.R.K.); Department of Epidemiology, University of Alabama at Birmingham School of Public Health (D.K.A.); Cardiovascular Genetics Division, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City (S.C.H.); Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO (D.C. Rao); and Department of Epidemiology and Biostatistics, University of California, San Francisco (N.R.)
| | - Steven C Hunt
- From the Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH (P.B.S., T.F., X.Z.); Department of Genetics, Stanford University School of Medicine, Stanford, CA (H.T.); Department of Public Health Sciences, Loyola University of Chicago Stritch School of Medicine, Maywood, IL (B.T., R.S.C.); Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health (A.C.M., C.L.H., E.B.); Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (S.L.R.K.); Department of Epidemiology, University of Alabama at Birmingham School of Public Health (D.K.A.); Cardiovascular Genetics Division, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City (S.C.H.); Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO (D.C. Rao); and Department of Epidemiology and Biostatistics, University of California, San Francisco (N.R.)
| | - Eric Boerwinkle
- From the Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH (P.B.S., T.F., X.Z.); Department of Genetics, Stanford University School of Medicine, Stanford, CA (H.T.); Department of Public Health Sciences, Loyola University of Chicago Stritch School of Medicine, Maywood, IL (B.T., R.S.C.); Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health (A.C.M., C.L.H., E.B.); Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (S.L.R.K.); Department of Epidemiology, University of Alabama at Birmingham School of Public Health (D.K.A.); Cardiovascular Genetics Division, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City (S.C.H.); Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO (D.C. Rao); and Department of Epidemiology and Biostatistics, University of California, San Francisco (N.R.)
| | - Dabeeru C Rao
- From the Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH (P.B.S., T.F., X.Z.); Department of Genetics, Stanford University School of Medicine, Stanford, CA (H.T.); Department of Public Health Sciences, Loyola University of Chicago Stritch School of Medicine, Maywood, IL (B.T., R.S.C.); Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health (A.C.M., C.L.H., E.B.); Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (S.L.R.K.); Department of Epidemiology, University of Alabama at Birmingham School of Public Health (D.K.A.); Cardiovascular Genetics Division, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City (S.C.H.); Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO (D.C. Rao); and Department of Epidemiology and Biostatistics, University of California, San Francisco (N.R.)
| | - Richard S Cooper
- From the Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH (P.B.S., T.F., X.Z.); Department of Genetics, Stanford University School of Medicine, Stanford, CA (H.T.); Department of Public Health Sciences, Loyola University of Chicago Stritch School of Medicine, Maywood, IL (B.T., R.S.C.); Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health (A.C.M., C.L.H., E.B.); Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (S.L.R.K.); Department of Epidemiology, University of Alabama at Birmingham School of Public Health (D.K.A.); Cardiovascular Genetics Division, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City (S.C.H.); Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO (D.C. Rao); and Department of Epidemiology and Biostatistics, University of California, San Francisco (N.R.)
| | - Neil Risch
- From the Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH (P.B.S., T.F., X.Z.); Department of Genetics, Stanford University School of Medicine, Stanford, CA (H.T.); Department of Public Health Sciences, Loyola University of Chicago Stritch School of Medicine, Maywood, IL (B.T., R.S.C.); Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health (A.C.M., C.L.H., E.B.); Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (S.L.R.K.); Department of Epidemiology, University of Alabama at Birmingham School of Public Health (D.K.A.); Cardiovascular Genetics Division, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City (S.C.H.); Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO (D.C. Rao); and Department of Epidemiology and Biostatistics, University of California, San Francisco (N.R.)
| | - Xiaofeng Zhu
- From the Department of Epidemiology and Biostatistics, Case Western Reserve University School of Medicine, Cleveland, OH (P.B.S., T.F., X.Z.); Department of Genetics, Stanford University School of Medicine, Stanford, CA (H.T.); Department of Public Health Sciences, Loyola University of Chicago Stritch School of Medicine, Maywood, IL (B.T., R.S.C.); Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health (A.C.M., C.L.H., E.B.); Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor (S.L.R.K.); Department of Epidemiology, University of Alabama at Birmingham School of Public Health (D.K.A.); Cardiovascular Genetics Division, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City (S.C.H.); Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO (D.C. Rao); and Department of Epidemiology and Biostatistics, University of California, San Francisco (N.R.).
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Kim DS, Smith JA, Bielak LF, Wu CY, Sun YV, Sheedy PF, Turner ST, Peyser PA, Kardia SLR. The relationship between diastolic blood pressure and coronary artery calcification is dependent on single nucleotide polymorphisms on chromosome 9p21.3. BMC MEDICAL GENETICS 2014; 15:89. [PMID: 25185447 PMCID: PMC4168694 DOI: 10.1186/s12881-014-0089-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2014] [Accepted: 07/18/2014] [Indexed: 12/20/2022]
Abstract
Background Single nucleotide polymorphisms (SNPs) within the 9p21.3 genomic region have been consistently associated with coronary heart disease (CHD), myocardial infarction, and quantity of coronary artery calcification (CAC), a marker of subclinical atherosclerosis. Prior studies have established an association between blood pressure measures and CAC. To examine mechanisms by which the 9p21.3 genomic region may influence CHD risk, we investigated whether SNPs in 9p21.3 modified associations between blood pressure and CAC quantity. Methods As part of the Genetic Epidemiology Network of Arteriopathy (GENOA) Study, 974 participants underwent non-invasive computed tomography (CT) to measure CAC quantity. Linear mixed effects models were used to investigate whether seven SNPs in the 9p21.3 region modified the association between blood pressure levels and CAC quantity. Four SNPs of at least marginal significance in GENOA for a SNP-by-diastolic blood pressure (DBP) interaction were then tested for replication in the Framingham Heart Study’s Offspring Cohort (N = 1,140). Results We found replicated evidence that one SNP, rs2069416, in CDKN2B-AS1, significantly modified the association between DBP and CAC quantity (combined P = 0.0065; Bonferroni-corrected combined P = 0.0455). Conclusions Our results represent a novel finding that the relationship between DBP and CAC is dependent on genetic variation in the 9p21.3 region. Thus, variation in 9p21.3 may not only be an independent genetic risk factor for CHD, but also may modify the association between DBP levels and the extent of subclinical coronary atherosclerosis.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor 48109, MI, USA.
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Simino J, Kume R, Kraja AT, Turner ST, Hanis CL, Sheu W, Chen I, Jaquish C, Cooper RS, Chakravarti A, Quertermous T, Boerwinkle E, Hunt SC, Rao DC. Linkage analysis incorporating gene-age interactions identifies seven novel lipid loci: the Family Blood Pressure Program. Atherosclerosis 2014; 235:84-93. [PMID: 24819747 PMCID: PMC4322916 DOI: 10.1016/j.atherosclerosis.2014.04.008] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2014] [Revised: 04/07/2014] [Accepted: 04/09/2014] [Indexed: 01/16/2023]
Abstract
OBJECTIVE To detect novel loci with age-dependent effects on fasting (≥ 8 h) levels of total cholesterol, high-density lipoprotein, low-density lipoprotein, and triglycerides using 3600 African Americans, 1283 Asians, 3218 European Americans, and 2026 Mexican Americans from the Family Blood Pressure Program (FBPP). METHODS Within each subgroup (defined by network, race, and sex), we employed stepwise linear regression (retention p ≤ 0.05) to adjust lipid levels for age, age-squared, age-cubed, body-mass-index, current smoking status, current drinking status, field center, estrogen therapy (females only), as well as antidiabetic, antihypertensive, and antilipidemic medication use. For each trait, we pooled the standardized male and female residuals within each network and race and fit a generalized variance components model that incorporated gene-age interactions. We conducted FBPP-wide and race-specific meta-analyses by combining the p-values of each linkage marker across subgroups using a modified Fisher's method. RESULTS We identified seven novel loci with age-dependent effects; four total cholesterol loci from the meta-analysis of Mexican Americans (on chromosomes 2q24.1, 4q21.21, 8q22.2, and 12p11.23) and three high-density lipoprotein loci from the meta-analysis of all FBPP subgroups (on chromosomes 1p12, 14q11.2, and 21q21.1). These loci lacked significant genome-wide linkage or association evidence in the literature and had logarithm of odds (LOD) score ≥ 3 in the meta-analysis with LOD ≥ 1 in at least two network and race subgroups (exclusively of non-European descent). CONCLUSION Incorporating gene-age interactions into the analysis of lipids using multi-ethnic cohorts can enhance gene discovery. These interaction loci can guide the selection of families for sequencing studies of lipid-associated variants.
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Affiliation(s)
- Jeannette Simino
- Division of Biostatistics, Washington University in St. Louis, School of Medicine, Saint Louis, Missouri, USA
| | - Rezart Kume
- Division of Biostatistics, Washington University in St. Louis, School of Medicine, Saint Louis, Missouri, USA
| | - Aldi T. Kraja
- Division of Statistical Genomics Washington University in St. Louis, School of Medicine, Saint Louis, Missouri, USA
| | - Stephen T. Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA
| | - Craig L. Hanis
- Human Genetics Center, University of Texas Health Science Center, Houston, Texas, USA
| | - Wayne Sheu
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Ida Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA 90502
| | - Cashell Jaquish
- Division of Cardiovascular Sciences, National Heart, Lung, Blood Institute, Bethesda, Maryland, USA
| | - Richard S. Cooper
- Department of Preventive Medicine and Epidemiology, Stritch School of Medicine, Loyola University Chicago, Maywood, Illinois, USA
| | - Aravinda Chakravarti
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Thomas Quertermous
- Department of Geriatric Medicine, John A. Burns School of Medicine, University of Hawaii, Honolulu, USA
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas Health Science Center, Houston, Texas, USA
| | - Steven C. Hunt
- Department of Internal Medicine, University of Utah, Salt Lake City, Utah, USA
| | - DC Rao
- Division of Biostatistics, Washington University in St. Louis, School of Medicine, Saint Louis, Missouri, USA
- Also Departments of Genetics, Psychiatry, and Mathematics, Washington University in St. Louis, School of Medicine, Missouri, USA
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Chen CTL, Liu CT, Chen GK, Andrews JS, Arnold AM, Dreyfus J, Franceschini N, Garcia ME, Kerr KF, Li G, Lohman KK, Musani SK, Nalls MA, Raffel LJ, Smith J, Ambrosone CB, Bandera EV, Bernstein L, Britton A, Brzyski RG, Cappola A, Carlson CS, Couper D, Deming SL, Goodarzi MO, Heiss G, John EM, Lu X, Le Marchand L, Marciante K, Mcknight B, Millikan R, Nock NL, Olshan AF, Press MF, Vaiyda D, Woods NF, Taylor HA, Zhao W, Zheng W, Evans MK, Harris TB, Henderson BE, Kardia SLR, Kooperberg C, Liu Y, Mosley TH, Psaty B, Wellons M, Windham BG, Zonderman AB, Cupples LA, Demerath EW, Haiman C, Murabito JM, Rajkovic A. Meta-analysis of loci associated with age at natural menopause in African-American women. Hum Mol Genet 2014; 23:3327-42. [PMID: 24493794 PMCID: PMC4030781 DOI: 10.1093/hmg/ddu041] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2014] [Revised: 01/11/2014] [Accepted: 01/27/2014] [Indexed: 12/23/2022] Open
Abstract
Age at menopause marks the end of a woman's reproductive life and its timing associates with risks for cancer, cardiovascular and bone disorders. GWAS and candidate gene studies conducted in women of European ancestry have identified 27 loci associated with age at menopause. The relevance of these loci to women of African ancestry has not been previously studied. We therefore sought to uncover additional menopause loci and investigate the relevance of European menopause loci by performing a GWAS meta-analysis in 6510 women with African ancestry derived from 11 studies across the USA. We did not identify any additional loci significantly associated with age at menopause in African Americans. We replicated the associations between six loci and age at menopause (P-value < 0.05): AMHR2, RHBLD2, PRIM1, HK3/UMC1, BRSK1/TMEM150B and MCM8. In addition, associations of 14 loci are directionally consistent with previous reports. We provide evidence that genetic variants influencing reproductive traits identified in European populations are also important in women of African ancestry residing in USA.
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Affiliation(s)
- Christina T L Chen
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Ching-Ti Liu
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA National Heart, Lung and Blood Institute's Framingham Heart Study, Framingham, MA 01702, USA
| | | | - Jeanette S Andrews
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | | | - Jill Dreyfus
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA
| | | | - Melissa E Garcia
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD 20814, USA
| | | | - Guo Li
- Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Kurt K Lohman
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Solomon K Musani
- University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Michael A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
| | | | - Jennifer Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Christine B Ambrosone
- Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, NY 14263, USA
| | - Elisa V Bandera
- The Cancer Institute of New Jersey, New Brunswick, NJ 08903, USA
| | - Leslie Bernstein
- Division of Cancer Etiology, Department of Population Science, Beckman Research Institute, City of Hope, Duarte, CA 91010, USA
| | - Angela Britton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
| | - Robert G Brzyski
- Department of Obstetrics and Gynecology, University of Texas Health Science Center, San Antonio, TX 78229, USA
| | - Anne Cappola
- Division of Endocrinology, Diabetes, and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Christopher S Carlson
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - David Couper
- Department of Biostatistics, Gillings School of Global Public Health
| | - Sandra L Deming
- Division of Epidemiology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Gerardo Heiss
- Department of Epidemiology, Gillings School of Global Public Health
| | - Esther M John
- Division of Epidemiology, Department of Health Research & Policy, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Xiaoning Lu
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA Division of Clinical Informatics, Beth Israel Deaconess Medical Center, Boston, MA 02118, USA
| | - Loic Le Marchand
- Epidemiology Program, Cancer Research Center, University of Hawaii, Honolulu, HI 96813, USA
| | - Kristin Marciante
- Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | | | - Robert Millikan
- Department of Epidemiology, Gillings School of Global Public Health Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Nora L Nock
- Department of Epidemiology and Biostatistics, Case Western University, Cleveland, OH 44106, USA
| | - Andrew F Olshan
- Department of Epidemiology, Gillings School of Global Public Health Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Michael F Press
- Department of Pathology, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90089, USA
| | - Dhananjay Vaiyda
- Department of Medicine, Johns Hopkins University, Baltimore, MD 21287, USA
| | - Nancy F Woods
- Biobehavioral Nursing and Health Systems, University of Washington, Seattle, WA 98109, USA
| | - Herman A Taylor
- University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Wei Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Michele K Evans
- Health Disparities Research Section, Clinical Research Branch
| | - Tamara B Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD 20814, USA
| | | | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA
| | - Thomas H Mosley
- Division of Geriatric Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Bruce Psaty
- Departments of Medicine, Epidemiology and Health Services, University of Washington and Group Health Research Institute, Seattle, WA, USA
| | - Melissa Wellons
- School of Medicine, Vanderbilt University, Nashville, TN 37240, USA
| | - Beverly G Windham
- Division of Geriatric Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Alan B Zonderman
- Laboratory of Personality and Cognition, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - L Adrienne Cupples
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA National Heart, Lung and Blood Institute's Framingham Heart Study, Framingham, MA 01702, USA
| | - Ellen W Demerath
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA
| | | | - Joanne M Murabito
- National Heart, Lung and Blood Institute's Framingham Heart Study, Framingham, MA 01702, USA Department of Medicine, Section of General Internal Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Aleksandar Rajkovic
- Department of Obstetrics, Gynecology and Reproductive Science, University of Pittsburgh, Pittsburgh, PA 15213, USA
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Yoon S, Assimes TL, Quertermous T, Hsiao CF, Chuang LM, Hwu CM, Rajaratnam B, Olshen RA. Insulin resistance: regression and clustering. PLoS One 2014; 9:e94129. [PMID: 24887437 PMCID: PMC4041565 DOI: 10.1371/journal.pone.0094129] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2012] [Accepted: 03/13/2014] [Indexed: 11/18/2022] Open
Abstract
In this paper we try to define insulin resistance (IR) precisely for a group of Chinese women. Our definition deliberately does not depend upon body mass index (BMI) or age, although in other studies, with particular random effects models quite different from models used here, BMI accounts for a large part of the variability in IR. We accomplish our goal through application of Gauss mixture vector quantization (GMVQ), a technique for clustering that was developed for application to lossy data compression. Defining data come from measurements that play major roles in medical practice. A precise statement of what the data are is in Section 1. Their family structures are described in detail. They concern levels of lipids and the results of an oral glucose tolerance test (OGTT). We apply GMVQ to residuals obtained from regressions of outcomes of an OGTT and lipids on functions of age and BMI that are inferred from the data. A bootstrap procedure developed for our family data supplemented by insights from other approaches leads us to believe that two clusters are appropriate for defining IR precisely. One cluster consists of women who are IR, and the other of women who seem not to be. Genes and other features are used to predict cluster membership. We argue that prediction with "main effects" is not satisfactory, but prediction that includes interactions may be.
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Affiliation(s)
- Sangho Yoon
- Google Inc., Mountain View, California, United States of America
- Department of Health Research and Policy, Stanford, California, United States of America
| | - Themistocles L. Assimes
- Division of Cardiovascular Medicine, Department of Medicine, Falk Cardiovascular Research Center, Stanford, California, United States of America
| | - Thomas Quertermous
- Division of Cardiovascular Medicine, Department of Medicine, Falk Cardiovascular Research Center, Stanford, California, United States of America
| | - Chin-Fu Hsiao
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Insititues, Miaoli County, Taiwan
| | - Lee-Ming Chuang
- Graduate Institute of Clinical Medicine, National Taiwan University, Taipei, Taiwan
| | - Chii-Min Hwu
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Bala Rajaratnam
- Department of Statistics, Stanford, California, United States of America
- Department of Environmental Earth System Sciences, Stanford, California, United States of America
| | - Richard A. Olshen
- Department of Health Research and Policy, Stanford, California, United States of America
- Department of Electrical Engineering, Stanford, California, United States of America
- Department of Statistics, Stanford, California, United States of America
- * E-mail:
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Simino J, Shi G, Weder A, Boerwinkle E, Hunt SC, Rao DC. Body mass index modulates blood pressure heritability: the Family Blood Pressure Program. Am J Hypertens 2014; 27:610-9. [PMID: 24029162 PMCID: PMC3958601 DOI: 10.1093/ajh/hpt144] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2012] [Accepted: 07/22/2013] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Candidate gene and twin studies suggest that interactions between body mass index (BMI) and genes contribute to the variability of blood pressure (BP). To determine whether there is evidence for gene-BMI interactions, we investigated the modulation of BP heritability by BMI using 4,153 blacks, 1,538 Asians, 4,013 whites, and 2,199 Hispanic Americans from the Family Blood Pressure Program. METHODS To capture the BP heritability dependence on BMI, we employed a generalized variance components model incorporating linear and Gaussian interactions between BMI and the genetic component. Within each race and network subgroup, we used the Akaike information criterion and likelihood ratio test to select the appropriate interaction function for each BP trait (systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP)) and determine interaction significance, respectively. RESULTS BP heritabilities were significantly modified by BMI in the GenNet and SAPPHIRe Networks, which contained the youngest and least-obese participants, respectively. GenNet Whites had unimodal SBP, MAP, and PP heritabilities that peaked between BMI values of 33 and 37kg/m(2). The SBP and MAP heritabilities in GenNet Hispanic Americans, as well as the PP heritability in GenNet blacks, were increasing functions of BMI. The DBP and SBP heritabilities in the SAPPHIRe Chinese and Japanese, respectively, were decreasing functions of BMI. CONCLUSIONS BP heritability differed by BMI in the youngest and least-obese networks, although the shape of this dependence differed by race. Use of nonlinear gene-BMI interactions may enhance BP gene discovery efforts in individuals of European ancestry.
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Affiliation(s)
- Jeannette Simino
- Division of Biostatistics, Washington University in St. Louis, School of Medicine, St. Louis, Missouri
| | - Gang Shi
- Division of Biostatistics, Washington University in St. Louis, School of Medicine, St. Louis, Missouri
| | - Alan Weder
- Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas Health Sciences Center, Houston, Texas
| | - Steven C. Hunt
- Cardiovascular Genetics Division, Department of Internal Medicine, University of Utah, Salt Lake City, Utah
| | - Dabeeru C. Rao
- Division of Biostatistics, Washington University in St. Louis, School of Medicine, St. Louis, Missouri
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Glasser SP, Lynch AI, Devereux RB, Hopkins P, Arnett DK. Hemodynamic and echocardiographic profiles in African American compared with White offspring of hypertensive parents: the HyperGEN study. Am J Hypertens 2014; 27:21-6. [PMID: 24242823 DOI: 10.1093/ajh/hpt178] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND Alterations in cardiovascular structure and function have been shown to precede the finding of elevated blood pressure. METHODS This study is part of the Hypertension Genetic Epidemiologic Network (HyperGEN) in which genetic and environmental determinants of hypertension were investigated in 5 geographical field centers. All nonhypertensive offspring (n = 1,035) were included from the entire HyperGEN study population that consists of 2,225 hypertensive patients and 1,380 nonhypertensive patients who had adequate echocardiographic left ventricular (LV) mass measurements. Participants were compared by self-declared race (African American and white). RESULTS Nonhypertensive African American offspring were younger (aged 31 years vs. 38 years), more likely to be female, and had a higher body mass index (BMI) and higher systolic blood pressure (SBP) than their white counterparts. After adjusting for age, sex, SBP, pulse pressure (PP), BMI, diabetes status, and family effects, we observed statistically significant and potentially pathophysiological differences (all with P ≤ 0.001) with greater LV mass/height, relative wall thickness, and posterior wall thickness and with lesser midwall shortening, PP/stroke volume, and (PP/stroke volume)/fat-free body mass. CONCLUSION This study shows that ethnic differences in hemodynamic and echocardiographic profiles exist in a large, population-based cohort of nonhypertensive offspring of hypertensive parents.
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Affiliation(s)
- Stephen P Glasser
- Department of Medicine and Epidemiology, University of Alabama at Birmingham, Birmingham, AL
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White WM, Turner ST, Bailey KR, Mosley TH, Kardia SL, Wiste HJ, Kullo IJ, Garovic VD. Hypertension in pregnancy is associated with elevated homocysteine levels later in life. Am J Obstet Gynecol 2013; 209:454.e1-7. [PMID: 23791689 DOI: 10.1016/j.ajog.2013.06.030] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2013] [Revised: 05/22/2013] [Accepted: 06/17/2013] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Hyperhomocysteinemia is associated with an elevated cardiovascular disease risk. We examined whether women with a history of hypertension in pregnancy are more likely to have a high level of serum homocysteine decades after pregnancy. STUDY DESIGN Serum homocysteine was measured at a mean age of 60 years in nulliparous women (n = 216), and women with a history of normotensive (n = 1825) or hypertensive (n = 401) pregnancies who participated in the Genetic Epidemiology Network of Arteriopathy (GENOA) study. Relationships between homocysteine and pregnancy history were examined by linear and logistic regression, controlling for multiple covariates including personal and family history of hypertension, diabetes, obesity, tobacco use, and demographics. RESULTS A history of hypertension in pregnancy, when compared with normotensive pregnancy, was associated with a 4.5% higher serum homocysteine level (P = .015) and 1.60-fold increased odds of having an elevated homocysteine (95% confidence interval, 1.15-2.21; P = .005) after adjusting for potentially confounding covariates. In contrast, a history of normotensive pregnancy, as compared with nulliparity, was associated with a 6.1% lower serum homocysteine level (P = .005) and a 0.49-fold reduced odds of elevated homocysteine levels (95% confidence interval, 0.32-0.74; P < .001). CONCLUSION Homocysteine levels decades after pregnancy are higher in women with a history of pregnancy hypertension, even after controlling for potential confounders. Thus, pregnancy history may prompt homocysteine assessment and risk modification in an attempt at primary prevention of cardiovascular disease.
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Palmer ND, Musani SK, Yerges-Armstrong LM, Feitosa MF, Bielak LF, Hernaez R, Kahali B, Carr JJ, Harris TB, Jhun MA, Kardia SLR, Langefeld CD, Mosley TH, Norris JM, Smith AV, Taylor HA, Wagenknecht LE, Liu J, Borecki IB, Peyser PA, Speliotes EK. Characterization of European ancestry nonalcoholic fatty liver disease-associated variants in individuals of African and Hispanic descent. Hepatology 2013; 58:966-75. [PMID: 23564467 PMCID: PMC3782998 DOI: 10.1002/hep.26440] [Citation(s) in RCA: 109] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2012] [Accepted: 04/03/2013] [Indexed: 12/15/2022]
Abstract
UNLABELLED Nonalcoholic fatty liver disease (NAFLD) is an obesity-related condition affecting over 50% of individuals in some populations and is expected to become the number one cause of liver disease worldwide by 2020. Common, robustly associated genetic variants in/near five genes were identified for hepatic steatosis, a quantifiable component of NAFLD, in European ancestry individuals. Here we tested whether these variants were associated with hepatic steatosis in African- and/or Hispanic-Americans and fine-mapped the observed association signals. We measured hepatic steatosis using computed tomography in five African American (n = 3,124) and one Hispanic American (n = 849) cohorts. All analyses controlled for variation in age, age(2) , gender, alcoholic drinks, and population substructure. Heritability of hepatic steatosis was estimated in three cohorts. Variants in/near PNPLA3, NCAN, LYPLAL1, GCKR, and PPP1R3B were tested for association with hepatic steatosis using a regression framework in each cohort and meta-analyzed. Fine-mapping across African American cohorts was conducted using meta-analysis. African- and Hispanic-American cohorts were 33.9/37.5% male, with average age of 58.6/42.6 years and body mass index of 31.8/28.9 kg/m(2) , respectively. Hepatic steatosis was 0.20-0.34 heritable in African- and Hispanic-American families (P < 0.02 in each cohort). Variants in or near PNPLA3, NCAN, GCKR, PPP1R3B in African Americans and PNPLA3 and PPP1R3B in Hispanic Americans were significantly associated with hepatic steatosis; however, allele frequency and effect size varied across ancestries. Fine-mapping in African Americans highlighted missense variants at PNPLA3 and GCKR and redefined the association region at LYPLAL1. CONCLUSION Multiple genetic variants are associated with hepatic steatosis across ancestries. This explains a substantial proportion of the genetic predisposition in African- and Hispanic-Americans. Missense variants in PNPLA3 and GCKR are likely functional across multiple ancestries.
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Affiliation(s)
- Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC
| | | | | | - Mary F Feitosa
- Department of Genetics, Washington University, St. Louis, MO
| | | | - Ruben Hernaez
- Department of Medicine, The Johns Hopkins School of Medicine, Baltimore, MD
| | - Bratati Kahali
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI
| | - J Jeffrey Carr
- Department of Radiologic Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Tamara B Harris
- National Institute on Aging, National Institutes of Health, Bethesda, MD
| | - Min A Jhun
- Department of Epidemiology, University of Michigan, Ann Arbor, MI
| | - Sharon LR Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI
| | - Carl D Langefeld
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Thomas H Mosley
- Department of Medicine, University of Mississippi, Jackson, MS
| | - Jill M Norris
- Department of Epidemiology, Colorado School of Public Health, Denver, CO
| | | | - Herman A Taylor
- Department of Medicine, University of Mississippi, Jackson, MS
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Jiankang Liu
- Jackson Heart Study, University of Mississippi, Jackson, MS
| | | | | | - Elizabeth K Speliotes
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI
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Kattah AG, Asad R, Scantlebury DC, Bailey KR, Wiste HJ, Hunt SC, Mosley TH, Kardia SLR, Turner ST, Garovic VD. Hypertension in pregnancy is a risk factor for microalbuminuria later in life. J Clin Hypertens (Greenwich) 2013; 15:617-23. [PMID: 24034653 PMCID: PMC3775278 DOI: 10.1111/jch.12116] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2013] [Revised: 03/20/2013] [Accepted: 03/20/2013] [Indexed: 01/14/2023]
Abstract
The authors aimed to compare renal function by estimated glomerular filtration rate and albuminuria in 3 groups of women: nulliparous women, women with a history of normotensive pregnancies, and women with a history of at least one hypertensive pregnancy. Women who participated in the second Family Blood Pressure Program Study visit (2000-2004) and had serum creatinine and urine albumin measurements (n=3015) were categorized as having had no pregnancy lasting >6 months (n=341), having had only normotensive pregnancies (n=2199), or having had at least 1 pregnancy with hypertension (n=475) based on a standardized questionnaire. Women who reported having had at least one pregnancy with hypertension were significantly more likely to be hypertensive (75.6% vs 59.4%, P<.001), diabetic (34.2% vs 27.3%, P≤.001), and have higher body mass index (32.8 vs 30.5, P<.001) than those who reported normotensive pregnancies. There was a significantly greater risk of microalbuminuria (urine albumin-creatinine ratio >25 mg/g) in those who reported at least one pregnancy with hypertension (odds ratio, 1.37; confidence interval, 1.02-1.85; P=.04) than in those with normotensive pregnancies, after adjusting for risk factors for chronic kidney and cardiovascular disease. Hypertension in pregnancy is associated with an increased risk of future microalbuminuria.
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Affiliation(s)
| | - Reem Asad
- Division of Nephrology and HypertensionMayo ClinicRochesterMN
| | | | - Kent R. Bailey
- Division of Biomedical Statistics and InformaticsMayo ClinicRochesterMN
| | - Heather J. Wiste
- Division of Biomedical Statistics and InformaticsMayo ClinicRochesterMN
| | - Steven C. Hunt
- Department of Internal MedicineUniversity of UtahSalt Lake CityUT
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Sun YV, Lazarus A, Smith JA, Chuang YH, Zhao W, Turner ST, Kardia SLR. Gene-specific DNA methylation association with serum levels of C-reactive protein in African Americans. PLoS One 2013; 8:e73480. [PMID: 23977389 PMCID: PMC3747126 DOI: 10.1371/journal.pone.0073480] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2013] [Accepted: 07/22/2013] [Indexed: 01/10/2023] Open
Abstract
A more thorough understanding of the differences in DNA methylation (DNAm) profiles in populations may hold promise for identifying molecular mechanisms through which genetic and environmental factors jointly contribute to human diseases. Inflammation is a key molecular mechanism underlying several chronic diseases including cardiovascular disease, and it affects DNAm profile on both global and locus-specific levels. To understand the impact of inflammation on the DNAm of the human genome, we investigated DNAm profiles of peripheral blood leukocytes from 966 African American participants in the Genetic Epidemiology Network of Arteriopathy (GENOA) study. By testing the association of DNAm sites on CpG islands of over 14,000 genes with C-reactive protein (CRP), an inflammatory biomarker of cardiovascular disease, we identified 257 DNAm sites in 240 genes significantly associated with serum levels of CRP adjusted for age, sex, body mass index and smoking status, and corrected for multiple testing. Of the significantly associated DNAm sites, 80.5% were hypomethylated with higher CRP levels. The most significant Gene Ontology terms enriched in the genes associated with the CRP levels were immune system process, immune response, defense response, response to stimulus, and response to stress, which are all linked to the functions of leukocytes. While the CRP-associated DNAm may be cell-type specific, understanding the DNAm association with CRP in peripheral blood leukocytes of multi-ethnic populations can assist in unveiling the molecular mechanism of how the process of inflammation affects the risks of developing common disease through epigenetic modifications.
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Affiliation(s)
- Yan V Sun
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.
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Abstract
The elucidation of genes implicated in Mendelian forms of hypertension demonstrates rare variants with substantial effects are responsible, and often these genes lie within pathways managing sodium homeostasis. More recently with advances in affordable high-throughput genotyping strategies, multiple common genetic variants with modest effects on blood pressure (<1 mmHg systolic) have been discovered in the population. In aggregate, these common variants explain <3% of the variance of blood pressure. Although these findings may offer new mechanistic insights into the biology of blood pressure, a key question is can these findings translate into patient benefit? It is timely to reflect on recent advances in genomics, and the use of new resources, such as the 1000 Genomes Project and the Encyclopedia of DNA Elements, to annotate likely causal variants, and their relevance to cardiovascular disease. In this review, we discuss the advances in relation to our knowledge of the genetic architecture of blood pressure, and whether gene discoveries might influence cardiovascular risk assessment, help to stratify patient response to medicine, or identify new biological pathways for novel therapeutic targets.
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Affiliation(s)
- Patricia B Munroe
- William Harvey Research Institute and Barts National Institute for Health Research Cardiovascular Biomedical Research Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ United Kingdom
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