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Chen Z, Liu XA, Kenny PJ. Central and peripheral actions of nicotine that influence blood glucose homeostasis and the development of diabetes. Pharmacol Res 2023; 194:106860. [PMID: 37482325 DOI: 10.1016/j.phrs.2023.106860] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 07/06/2023] [Accepted: 07/18/2023] [Indexed: 07/25/2023]
Abstract
Cigarette smoking has long been recognized as a risk factor for type 2 diabetes (T2D), although the precise causal mechanisms underlying this relationship remain poorly understood. Recent evidence suggests that nicotine, the primary reinforcing component in tobacco, may play a pivotal role in connecting cigarette smoking and T2D. Extensive research conducted in both humans and animals has demonstrated that nicotine can elevate blood glucose levels, disrupt glucose homeostasis, and induce insulin resistance. The review aims to elucidate the genetic variants of nicotinic acetylcholine receptors associated with diabetes risk and provide a comprehensive overview of the available data on the mechanisms through which nicotine influences blood glucose homeostasis and the development of diabetes. Here we emphasize the central and peripheral actions of nicotine on the release of glucoregulatory hormones, as well as its effects on glucose tolerance and insulin sensitivity. Notably, the central actions of nicotine within the brain, which encompass both insulin-dependent and independent mechanisms, are highlighted as potential targets for intervention strategies in diabetes management.
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Affiliation(s)
- Zuxin Chen
- Shenzhen Key Laboratory of Drug Addiction, Shenzhen Neher Neural Plasticity Laboratory, The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China; University of Chinese Academy of Sciences, Beijing, China; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China
| | - Xin-An Liu
- Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Key Laboratory of Brain Connectome and Manipulation, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China; University of Chinese Academy of Sciences, Beijing, China; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China.
| | - Paul J Kenny
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, USA.
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Jha MK, Kim JW, Kenny PJ, Chin Fatt C, Minhajuddin A, Salas R, Ely BA, Klein M, Abdallah CG, Xu J, Trivedi MH. Smoking status links habenular volume to glycated hemoglobin: Findings from the Human Connectome Project-Young Adult. Psychoneuroendocrinology 2021; 131:105321. [PMID: 34157587 DOI: 10.1016/j.psyneuen.2021.105321] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 06/07/2021] [Accepted: 06/08/2021] [Indexed: 11/24/2022]
Abstract
BACKGROUND The habenula-pancreas axis regulates the stimulatory effects of nicotine on blood glucose levels and may participate in the emergence of type 2 diabetes in human tobacco smokers. This secondary analysis of young adults from the Human Connectome Project (HCP-YA) evaluated whether smoking status links the relationship between habenular volume and glycated hemoglobin (HbA1c), a marker of long-term glycemic control. METHODS Habenula segmentation was performed using a fully-automated myelin content-based approach in HCP-YA participants and the results were inspected visually (n = 693; aged 22-37 years). A linear regression analysis was used with habenular volume as the dependent variable, the smoking-by-HbA1c interaction as the independent variable of interest, and age, gender, race, ethnicity, education, income, employment status, body mass index, and total gray matter volume as covariates. RESULTS Habenula volume and HbA1c were similar in smokers and nonsmokers. There was a significant interaction effect (F(1, 673)= 5.03, p = 0.025) indicating that habenular volume was related to HbA1c in a manner that depended on smoking status. Among participants who were smokers (n = 120), higher HbA1c was associated with apparently larger habenular volume (β = 6.74, standard error=2.36, p = 0.005). No such association between habenular volume and HbA1c was noted among participants who were nonsmokers (n = 573). DISCUSSION Blood glucose levels over an extended time period, reflected by HbA1c, were correlated with habenular volume in smokers, consistent with a relationship between the habenula and blood glucose homeostasis in smokers. Future studies are needed to evaluate how habenular function relates to glycemic control in smokers and nonsmokers.
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Affiliation(s)
- Manish K Jha
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States
| | - Joo-Won Kim
- Department of Radiology, Baylor College of Medicine, Houston, TX, United States; Department of Psychiatry, Baylor College of Medicine, Houston, TX, United States
| | - Paul J Kenny
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Cherise Chin Fatt
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States
| | - Abu Minhajuddin
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States
| | - Ramiro Salas
- Department of Psychiatry, Baylor College of Medicine, Houston, TX, United States; Michael E DeBakey VA Medical Center, Houston, TX, United States; The Menninger Clinic, Houston, TX, United States
| | - Benjamin A Ely
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, The Bronx, NY, United States
| | - Matthew Klein
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Chadi G Abdallah
- Department of Psychiatry, Baylor College of Medicine, Houston, TX, United States; Michael E DeBakey VA Medical Center, Houston, TX, United States
| | - Junqian Xu
- Department of Radiology, Baylor College of Medicine, Houston, TX, United States; Department of Psychiatry, Baylor College of Medicine, Houston, TX, United States
| | - Madhukar H Trivedi
- Center for Depression Research and Clinical Care, UT Southwestern Medical Center, Dallas, TX, United States.
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3
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Henderson JA, Buchwald DS, Howard BV, Henderson PN, Li Y, Tyndale RF, Amos CI, Gorlova OY. Genetics of Smoking Behaviors in American Indians. Cancer Epidemiol Biomarkers Prev 2020; 29:2180-2186. [PMID: 32855268 DOI: 10.1158/1055-9965.epi-20-0026] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 04/15/2020] [Accepted: 08/18/2020] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND The smoking behavior of American Indians (AI) differs from that of non-Hispanic whites (NHW). Typically light smokers, cessation interventions in AIs are generally less effective. To develop more effective cessation programs for AIs, clinicians, researchers, and public health workers need a better understanding of the genetic factors involved in their smoking behavior. Our aim was to assess whether SNPs associated with smoking behavior in NHWs are also associated with smoking in AIs. METHODS We collected questionnaire data on smoking behaviors and analyzed blood and saliva samples from two Tribal populations with dramatically different cultures and smoking prevalence, one in the Northern Plains (n = 323) and the other in the Southwest (n = 176). A total of 384 SNPs were genotyped using an Illumina custom GoldenGate platform. Samples were also assessed for cotinine and 3-hydroxycotinine as markers of nicotine intake and nicotine metabolite ratio. RESULTS Among 499 participants, we identified, in the Northern Plains sample only, a variant of the gamma-aminobutyric acid receptor subunit alpha-2 (GABRA2) (rs2119767) on chromosome 4p that was associated with many of the intake biomarkers of smoking we examined, suggesting a role for this gene in modifying smoking behavior in this population. We also identified three SNPs, in the Southwest sample only, as significant correlates of only cigarettes per day: rs4274224, rs4245147 (both dopamine receptor D2 gene), and rs1386493 (tryptophan hydroxylase 2 gene). CONCLUSIONS The contribution of many genes known to underlie smoking behaviors in NHWs may differ in AIs. IMPACT Once validated, these variants could be useful in developing more effective cessation strategies.
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Affiliation(s)
| | - Dedra S Buchwald
- Elson S. Floyd College of Medicine, Washington State University, Seattle, Washington
| | - Barbara V Howard
- MedStar Health Research Institute, Hyattsville, Maryland
- The Georgetown-Howard Universities Center for Clinical and Translational Sciences, Washington, District of Columbia
| | | | - Yafang Li
- Baylor College of Medicine, Institute for Clinical and Translational Research, Houston, Texas
| | - Rachel F Tyndale
- Department of Psychiatry, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, Ontario, Canada
| | - Christopher I Amos
- Baylor College of Medicine, Institute for Clinical and Translational Research, Houston, Texas
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4
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Wu P, Rybin D, Bielak LF, Feitosa MF, Franceschini N, Li Y, Lu Y, Marten J, Musani SK, Noordam R, Raghavan S, Rose LM, Schwander K, Smith AV, Tajuddin SM, Vojinovic D, Amin N, Arnett DK, Bottinger EP, Demirkan A, Florez JC, Ghanbari M, Harris TB, Launer LJ, Liu J, Liu J, Mook-Kanamori DO, Murray AD, Nalls MA, Peyser PA, Uitterlinden AG, Voortman T, Bouchard C, Chasman D, Correa A, de Mutsert R, Evans MK, Gudnason V, Hayward C, Kao L, Kardia SLR, Kooperberg C, Loos RJF, Province MM, Rankinen T, Redline S, Ridker PM, Rotter JI, Siscovick D, Smith BH, van Duijn C, Zonderman AB, Rao DC, Wilson JG, Dupuis J, Meigs JB, Liu CT, Vassy JL. Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose. PLoS One 2020; 15:e0230815. [PMID: 32379818 PMCID: PMC7205201 DOI: 10.1371/journal.pone.0230815] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Accepted: 03/09/2020] [Indexed: 02/07/2023] Open
Abstract
Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p<1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D.
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Affiliation(s)
- Peitao Wu
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, MA, United States of America
| | - Denis Rybin
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, MA, United States of America
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States of America
| | - Mary F. Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Nora Franceschini
- University of North Carolina, Chapel Hill, NC, United States of America
| | - Yize Li
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Yingchang Lu
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Jonathan Marten
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Solomon K. Musani
- Jackson Heart Study, University of Mississippi Medical Center, MS, United States of America
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Sridharan Raghavan
- Section of Hospital Medicine, Veterans Affairs Eastern Colorado Healthcare System, Denver, CO, United States of America
- Division of General Internal Medicine, University of Colorado School of Medicine, Aurora, CO, United States of America
- Colorado Cardiovascular Outcomes Research Consortium, Aurora, CO, United States of America
| | - Lynda M. Rose
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, United States of America
| | - Karen Schwander
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Albert V. Smith
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Salman M. Tajuddin
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Dina Vojinovic
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Najaf Amin
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Donna K. Arnett
- Dean's Office, University of Kentucky College of Public Health, Lexington, Kentucky, United States of America
| | - Erwin P. Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Ayse Demirkan
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Jose C. Florez
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Massachusetts General Hospital, Boston, MA, United States of America
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Department of Medicine, Harvard Medical School, Boston, MA, United States of America
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Genetics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Tamara B. Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, MD, United States of America
| | - Lenore J. Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program, National Institutes of Health, Bethesda, MD, United States of America
| | - Jingmin Liu
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
| | - Jun Liu
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Dennis O. Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
| | - Alison D. Murray
- The Institute of Medical Sciences, Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, United Kingdom
| | - Mike A. Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, United States of America
- Data Tecnica International LLC, Glen Echo, MD, United States of America
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States of America
| | - André G. Uitterlinden
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Trudy Voortman
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, United States of America
| | - Daniel Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, United States of America
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Michele K. Evans
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - Caroline Hayward
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Linda Kao
- Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, United States of America
- Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, MD, United States of America
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States of America
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States of America
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
| | - Ruth J. F. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- The Mindich Child Health and Development Institute, Ichan School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Michael M. Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Tuomo Rankinen
- Human Genomics Laboratory, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, United States of America
| | - Susan Redline
- Harvard Medical School, Boston, MA, United States of America
- Departments of Medicine, Brigham and Women's Hospital, Boston, MA, United States of America
- Beth Israel Deaconess Medical Center, Boston, MA, United States of America
| | - Paul M. Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
| | - 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, United States of America
| | - David Siscovick
- The New York Academy of Medicine, New York, NY, United States of America
| | - Blair H. Smith
- Division of Population Health and Genomics, University of Dundee, Dundee, United Kingdom
| | - Cornelia van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Alan B. Zonderman
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - D. C. Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States of America
| | - James G. Wilson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, United States of America
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, MA, United States of America
- The National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, United States of America
| | - James B. Meigs
- Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Division of General Internal Medicine Division, Massachusetts General Hospital, Boston, MA, United States of America
- Department of Medicine, Harvard Medical School, Boston, MA, United States of America
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, MA, United States of America
| | - Jason L. Vassy
- Department of Medicine, Harvard Medical School, Boston, MA, United States of America
- VA Boston Healthcare System, Boston, MA, United States of America
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Peng H, Zhu Y, Goldberg J, Vaccarino V, Zhao J. DNA Methylation of Five Core Circadian Genes Jointly Contributes to Glucose Metabolism: A Gene-Set Analysis in Monozygotic Twins. Front Genet 2019; 10:329. [PMID: 31031806 PMCID: PMC6473046 DOI: 10.3389/fgene.2019.00329] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Accepted: 03/28/2019] [Indexed: 02/06/2023] Open
Abstract
The timing of daily fluctuations in blood glucose is tightly controlled by the circadian rhythm. DNA methylation accompanies the circadian clock, and aberrant DNA methylation has been associated with circadian disruption and hyperglycemia. However, the precise role of circadian genes methylation in glucose metabolism is unknown. Using a gene-set approach in monozygotic (MZ) twin pairs, we examined the joint effect of 77 CpGs in five core circadian genes (CLOCK, BMAL1, PER1, PER2, PER3) on glucose-related traits in 138 middle-aged, male-male MZ twins (69 pairs). DNA methylation was quantified by bisulfite pyrosequencing. We first conducted matched twin pair analysis to examine the association of single CpG methylation with glucose metabolism. We then performed gene-based and gene-set analyses by the truncated product method to examine the combined effect of DNA methylation at multiple CpGs in a gene or all five circadian genes as a pathway on glucose metabolism. Of the 77 assayed CpGs, only one site was individually associated with insulin resistance at FDR < 0.05. However, the joint effect of DNA methylation in all five circadian genes together showed a significant association with glucose metabolism. Our results may unravel a biological mechanism through which circadian rhythm regulates blood glucose, and highlight the importance of testing the joint effect of multiple CpGs in epigenetic analysis.
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Affiliation(s)
- Hao Peng
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States
| | - Yun Zhu
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States
| | - Jack Goldberg
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, United States
| | - Viola Vaccarino
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Jinying Zhao
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States
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6
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Balakrishnan P, Vaidya D, Voruganti VS, Haack K, Kent JW, North KE, Laston S, Howard BV, Umans JG, Lee ET, Best LG, MacCluer JW, Cole SA, Navas-Acien A, Franceschini N. Genetic Variants Related to Cardiometabolic Traits Are Associated to B Cell Function, Insulin Resistance, and Diabetes Among AmeriCan Indians: The Strong Heart Family Study. Front Genet 2018; 9:466. [PMID: 30369944 PMCID: PMC6194194 DOI: 10.3389/fgene.2018.00466] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2018] [Accepted: 09/24/2018] [Indexed: 01/03/2023] Open
Abstract
Background: Genetic research may inform underlying mechanisms for disparities in the burden of type 2 diabetes mellitus among American Indians. Our objective was to assess the association of genetic variants in cardiometabolic candidate genes with B cell dysfunction via HOMA-B, insulin resistance via HOMA-IR, and type 2 diabetes mellitus in the Strong Heart Family Study (SHFS). Methods and Results: We examined the association of variants, previously associated with cardiometabolic traits (∼200,000 from Illumina Cardio MetaboChip), using mixed models of HOMA-B residuals corrected for HOMA-IR (cHOMA-B), log transformed HOMA-IR, and incident diabetes, adjusted for age, sex, population stratification, and familial relatedness. Center-specific estimates were combined using fixed effect meta-analyses. We used Bonferroni correction to account for multiple testing (P < 4.13 × 10−7). We also assessed the association between variants in candidate diabetes genes with these metabolic traits. We explored the top SNPs in an independent, replication sample from Southwestern Arizona. We identified significant associations with cHOMA-B for common variants at 26 loci of which 8 were novel (PRSS7, FCRL5, PEL1, LRP12, IGLL1, ARHGEF10, PARVA, FLJ16686). The most significant variant association with cHOMA-B was observed on chromosome 5 for an intergenic variant near PARP8 (rs2961831, P = 6.39 × 10−9). In the replication study, we found a signal at rs4607517 near GCK/YKT6 (P = 0.01). Variants near candidate diabetes genes (especially GCK and KCNQ1) were also nominally associated with HOMA-IR and cHOMA-B. Conclusion: We identified variants at novel loci and confirmed those at known candidate diabetes loci associations for cHOMA-B. This study also provided evidence for association of variants at KCNQ2, CTNAA2, and KCNQ1with cHOMA-B among American Indians. Further studies are needed to account for the high heritability of diabetes among the American Indian participants of the SHFS cohort.
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Affiliation(s)
- Poojitha Balakrishnan
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, United States
| | - Dhananjay Vaidya
- Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, United States.,Clinical and Translational Research, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - V Saroja Voruganti
- Department of Nutrition, UNC Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, United States
| | - Karin Haack
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, United States
| | - Jack W Kent
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, United States
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Sandra Laston
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, United States
| | - Barbara V Howard
- MedStar Health Research Institute, Hyattsville, MD, United States
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD, United States.,Georgetown and Howard Universities Center for Clinical and Translational Science, Washington, DC, United States
| | - Elisa T Lee
- Center for American Indian Health Research, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Lyle G Best
- Missouri Breaks Industries Research, Inc., Eagle Butte, SD, United States
| | - Jean W MacCluer
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, United States
| | - Shelley A Cole
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, United States
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, United States
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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Childhood Trauma, DNA Methylation of Stress-Related Genes, and Depression: Findings From Two Monozygotic Twin Studies. Psychosom Med 2018; 80:599-608. [PMID: 29781947 PMCID: PMC6113110 DOI: 10.1097/psy.0000000000000604] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
OBJECTIVE DNA methylation has been associated with both early life stress and depression. This study examined the combined association of DNA methylation at multiple CpG probes in five stress-related genes with depressive symptoms and tested whether these genes methylation mediated the association between childhood trauma and depression in two monozygotic (MZ) twin studies. METHODS The current analysis comprised 119 MZ twin pairs (84 male pairs [mean = 55 years] and 35 female pairs [mean = 36 years]). Peripheral blood DNA methylation of five stress-related genes (BDNF, NR3C1, SLC6A4, MAOA, and MAOB) was quantified by bisulfite pyrosequencing or 450K BeadChip. We applied generalized Poisson linear-mixed models to examine the association between each single CpG methylation and depressive symptoms. The joint associations of multiple CpGs in a single gene or all five stress-related genes as a pathway were tested by weighted truncated product method. Mediation analysis was conducted to test the potential mediating effect of stress gene methylation on the relationship between childhood trauma and depressive symptoms. RESULTS Multiple CpG probes showed nominal individual associations, but very few survived multiple testing. Gene-based or gene-set approach, however, revealed significant joint associations of DNA methylation in all five stress-related genes with depressive symptoms in both studies. Moreover, two CpG probes in the BDNF and NR3C1 mediated approximately 20% of the association between childhood trauma and depressive symptoms. CONCLUSIONS DNA methylation at multiple CpG sites are jointly associated with depressive symptoms and partly mediates the association between childhood trauma and depression. Our results highlight the importance of testing the combined effects of multiple CpG loci on complex traits and may unravel a molecular mechanism through which adverse early life experiences are biologically embedded.
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Coverstone ED, Bach RG, Chen L, Bierut LJ, Li AY, Lenzini PA, O'Neill HC, Spertus JA, Sucharov CC, Stitzel JA, Schilling JD, Cresci S. A novel genetic marker of decreased inflammation and improved survival after acute myocardial infarction. Basic Res Cardiol 2018; 113:38. [PMID: 30097758 PMCID: PMC6292447 DOI: 10.1007/s00395-018-0697-7] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2017] [Accepted: 08/06/2018] [Indexed: 10/28/2022]
Abstract
The CHRNA5 gene encodes a neurotransmitter receptor subunit involved in multiple processes, including cholinergic autonomic nerve activity and inflammation. Common variants in CHRNA5 have been linked with atherosclerotic cardiovascular disease. Association of variation in CHRNA5 and specific haplotypes with cardiovascular outcomes has not been described. The aim of this study was to examine the association of CHRNA5 haplotypes with gene expression and mortality among patients with acute myocardial infarction (AMI) and explore potential mechanisms of this association. Patients (N = 2054) hospitalized with AMI were genotyped for two common variants in CHRNA5. Proportional hazard models were used to estimate independent association of CHRNA5 haplotype with 1-year mortality. Both individual variants were associated with mortality (p = 0.0096 and 0.0004, respectively) and were in tight LD (D' = 0.99). One haplotype, HAP3, was associated with decreased mortality one year after AMI (adjusted HR = 0.42, 95% CI 0.26, 0.68; p = 0.0004). This association was validated in an independent cohort (N = 637) of post-MI patients (adjusted HR = 0.23, 95% CI 0.07, 0.79; p = 0.019). Differences in CHRNA5 expression by haplotype were investigated in human heart samples (n = 28). Compared with non-carriers, HAP3 carriers had threefold lower cardiac CHRNA5 mRNA expression (p = 0.023). Circulating levels of the inflammatory marker hsCRP were significantly lower in HAP3 carriers versus non-carriers (3.43 ± 4.2 versus 3.91 ± 5.1; p = 0.0379). Activation of the inflammasome, an important inflammatory complex involved in cardiovascular disease that is necessary for release of the pro-inflammatory cytokine IL-1 β, was assessed in bone marrow-derived macrophages (BMDM) from CHRNA5 knockout mice and wild-type controls. In BMDM from CHRNA5 knockout mice, IL-1β secretion was reduced by 50% compared to wild-type controls (p = 0.004). Therefore, a common haplotype of CHRNA5 that results in reduced cardiac expression of CHRNA5 and attenuated macrophage inflammasome activation is associated with lower mortality after AMI. These results implicate CHRNA5 and the cholinergic anti-inflammatory pathway in survival following AMI.
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Affiliation(s)
- Edward D Coverstone
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, 660 S. Euclid Ave., Campus, Box 8086, Saint Louis, MO, 63110, USA
| | - Richard G Bach
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, 660 S. Euclid Ave., Campus, Box 8086, Saint Louis, MO, 63110, USA
| | - LiShiun Chen
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Laura J Bierut
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Allie Y Li
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, 660 S. Euclid Ave., Campus, Box 8086, Saint Louis, MO, 63110, USA
| | - Petra A Lenzini
- Statistical Genomics Division, Department of Genetics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Heidi C O'Neill
- Institute for Behavioral Genetics, University of Colorado, Boulder, USA
| | - John A Spertus
- Saint Luke's Mid America Heart Institute and the University of Missouri-Kansas City, Kansas City, MO, USA
| | - Carmen C Sucharov
- Cardiology Division, Department of Medicine, University of Colorado Denver, Aurora, USA
| | - Jerry A Stitzel
- Institute for Behavioral Genetics, University of Colorado, Boulder, USA
| | - Joel D Schilling
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, 660 S. Euclid Ave., Campus, Box 8086, Saint Louis, MO, 63110, USA
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Sharon Cresci
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine, 660 S. Euclid Ave., Campus, Box 8086, Saint Louis, MO, 63110, USA.
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO, USA.
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White WB, Cain LR, Benjamin EJ, DeFilippis AP, Blaha MJ, Wang W, Okhomina V, Keith RJ, Al Rifai M, Kianoush S, Winniford MD, Robertson RM, Bhatnagar A, Correa A, Hall ME. High-Intensity Cigarette Smoking Is Associated With Incident Diabetes Mellitus In Black Adults: The Jackson Heart Study. J Am Heart Assoc 2018; 7:JAHA.117.007413. [PMID: 29330255 PMCID: PMC5850161 DOI: 10.1161/jaha.117.007413] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Background Previous reports on whether smoking is associated with insulin resistance and diabetes mellitus have yielded inconsistent findings. We aimed to evaluate the relationship between cigarette smoking and incident diabetes mellitus in the Jackson Heart Study. Methods and Results Jackson Heart Study participants enrolled at baseline without prevalent diabetes mellitus (n=2991) were classified by self‐report as current smokers, past smokers (smoked ≥400 cigarettes/life and no longer smoking), or never smokers. We quantified smoking intensity by number of cigarettes smoked daily; we considered ≥20 cigarettes per day (1 pack) “high‐intensity.” We defined diabetes mellitus as fasting glucose ≥126 mg/dL, hemoglobin A1c ≥6.5% or International Federation of Clinical Chemistry units HbA1c 48 mmol/mol, or use of diabetes mellitus medication. We estimated the adjusted associations of smoking status, intensity, and dose (pack‐years) with incident diabetes mellitus using Poisson regression models. At baseline there were 361 baseline current (1–10 cigarettes per day [n=242]; ≥20 [n=119]), 502 past, and 2128 never smokers. From Visit 1 to Visit 3 (mean 8.0±0.9 years), 479 participants developed incident diabetes mellitus. After adjustment for covariates, baseline current smokers who smoked less than a pack/d and past smokers had similar rates of incident diabetes mellitus compared with never smokers (incidence rate ratios 1.04, 95% confidence interval, 0.69–1.58 and 1.08, 95% confidence interval, 0.82–1.42, respectively). Baseline current high‐intensity smokers had a 79% (95% confidence interval, 1.14–2.81) higher incidence of diabetes mellitus compared with never smokers. Smoking dose (per 10 pack‐years) was also associated with a higher incidence of diabetes mellitus (incidence rate ratios 1.10, 95% confidence interval, 1.03–1.19) in adjusted models. Conclusions High‐intensity cigarette smoking and smoking pack‐years are associated with an increased risk of developing diabetes mellitus in blacks.
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Affiliation(s)
| | - Loretta R Cain
- Department of Data Sciences, University of Mississippi Medical Center, Jackson, MS
| | - Emelia J Benjamin
- Department of Medicine, Boston University School of Medicine, Boston, MA
| | | | - Michael J Blaha
- Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins School of Medicine, Baltimore, MD
| | - Wei Wang
- Department of Data Sciences, University of Mississippi Medical Center, Jackson, MS
| | - Victoria Okhomina
- Department of Data Sciences, University of Mississippi Medical Center, Jackson, MS
| | - Rachel J Keith
- Diabetes and Obesity Center, University of Louisville, Louisville, KY
| | - Mahmoud Al Rifai
- Department of Medicine, University of Kansas School of Medicine, Wichita, KS
| | - Sina Kianoush
- Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins School of Medicine, Baltimore, MD
| | - Michael D Winniford
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS
| | - Rose M Robertson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Aruni Bhatnagar
- Diabetes and Obesity Center, University of Louisville, Louisville, KY
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS
| | - Michael E Hall
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS
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Nicotine-Induced Apoptosis in Human Renal Proximal Tubular Epithelial Cells. PLoS One 2016; 11:e0152591. [PMID: 27028622 PMCID: PMC4814027 DOI: 10.1371/journal.pone.0152591] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2015] [Accepted: 03/16/2016] [Indexed: 01/26/2023] Open
Abstract
Background Nicotine is, to a large extent, responsible for smoking-mediated renal dysfunction. This study investigated nicotine’s effects on renal tubular epithelial cell apoptosis in vitro and it explored the mechanisms underlying its effects. Methods Human proximal tubular epithelial (HK-2) cells were treated with nicotine. Cell viability was examined by using the WST-1 assay. Intracellular levels of reactive oxygen species (ROS) and the expression of mitogen-activated protein kinase (MAPK) and nuclear factor-κB (NF-κB) proteins were determined. The messenger ribonucleic acid and the protein expression associated with the nicotine acetylcholine receptors (nAChRs) in HK-2 cells was examined, and apoptosis was detected using flow cytometry, cell cycle analysis, and immunoblot analysis. Results The HK-2 cells were endowed with nAChRs. Nicotine treatment reduced cell viability dose dependently, increased ROS levels, and increased extracellular signal-regulated kinase (ERK), c-Jun N-terminal kinase (JNK), and p38 MAPK expression. Nicotine increased NF-κB activation, which was attenuated by N-acetyl-L-cysteine, and ERK and JNK inhibitors, but was not affected by a p38 MAPK inhibitor. Nicotine increased the Bax/Bcl-2 ratio, which was attenuated by N-acetyl-L-cysteine, the NF-κB inhibitor, Bay 11–7082, and hexamethonium, a non-specific nAChR blocker. Flow cytometry revealed nicotine-induced G2/M phase arrest. While nicotine treatment increased the expression of phosphorylated cdc2 and histone H3, a marker of G2/M phase arrest, hexamethonium and Bay 11–7082 pretreatment reduced their expression. Conclusions Nicotine caused apoptosis in HK-2 cells by inducing ROS generation that activated the NF-κB signaling pathway via the MAPK pathway and it arrested the cell cycle at the G2/M phase. Nicotine-induced apoptosis in HK-2 cells involves the nAChRs.
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Kelly TN, Raj D, Rahman M, Kretzler M, Kallem RR, Ricardo AC, Rosas SE, Tao K, Xie D, Hamm LL, He J. The role of renin-angiotensin-aldosterone system genes in the progression of chronic kidney disease: findings from the Chronic Renal Insufficiency Cohort (CRIC) study. Nephrol Dial Transplant 2015; 30:1711-8. [PMID: 25906781 DOI: 10.1093/ndt/gfv125] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2015] [Accepted: 03/31/2015] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND We conducted single-marker, gene- and pathway-based analyses to examine the association between renin-angiotensin-aldosterone system (RAAS) variants and chronic kidney disease (CKD) progression among Chronic Renal Insufficiency Cohort study participants. METHODS A total of 1523 white and 1490 black subjects were genotyped for 490 single nucleotide polymorphisms (SNPs) in 12 RAAS genes as part of the ITMAT-Broad-CARe array. CKD progression phenotypes included decline in estimated glomerular filtration rate (eGFR) over time and the occurrence of a renal disease event, defined as incident end-stage renal disease or halving of eGFR from baseline. Mixed-effects models were used to examine SNP associations with eGFR decline, while Cox proportional hazards models tested SNP associations with renal events. Gene- and pathway-based analyses were conducted using the truncated product method. All analyses were stratified by race, and a Bonferroni correction was applied to adjust for multiple testing. RESULTS Among white and black participants, eGFR declined an average of 1.2 and 2.3 mL/min/1.73 m(2)/year, respectively, while renal events occurred in a respective 11.5 and 24.9% of participants. We identified strong gene- and pathway-based associations with CKD progression. The AGT and RENBP genes were consistently associated with risk of renal events in separate analyses of white and black participants (both P < 1.00 × 10(-6)). Driven by the significant gene-based findings, the entire RAAS pathway was also associated with renal events in both groups (both P < 1.00 × 10(-6)). No single-marker associations with CKD progression were observed. CONCLUSIONS The current study provides strong evidence for a role of the RAAS in CKD progression.
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Affiliation(s)
- Tanika N Kelly
- School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Dominic Raj
- Medical Faculty Associates, George Washington University, Washington, DC 20037, USA
| | - Mahboob Rahman
- University Hospitals Case Medical Center, Case Western Reserve University, Louis Stokes Cleveland VA Medical Center, Cleveland, OH 44106, USA
| | | | - Radhakrishna R Kallem
- University of Pennsylvania, Translational Research Center, Philadelphia, PA 19104, USA
| | - Ana C Ricardo
- University of Illinois at Chicago, Chicago, IL 60612, USA
| | - Sylvia E Rosas
- Joslin Diabetes Center, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA
| | - Kaixiang Tao
- The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Dawei Xie
- The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Lotuce Lee Hamm
- Tulane University School of Medicine, New Orleans, LA 70112, USA
| | - Jiang He
- School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA Tulane University School of Medicine, New Orleans, LA 70112, USA
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Li C, Bazzano LAL, Rao DC, Hixson JE, He J, Gu D, Gu CC, Shimmin LC, Jaquish CE, Schwander K, Liu DP, Huang J, Lu F, Cao J, Chong S, Lu X, Kelly TN. Genome-wide linkage and positional association analyses identify associations of novel AFF3 and NTM genes with triglycerides: the GenSalt study. J Genet Genomics 2015; 42:107-17. [PMID: 25819087 PMCID: PMC4761343 DOI: 10.1016/j.jgg.2015.02.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2014] [Revised: 02/06/2015] [Accepted: 02/10/2015] [Indexed: 01/17/2023]
Abstract
We conducted a genome-wide linkage scan and positional association study to identify genes and variants influencing blood lipid levels among participants of the Genetic Epidemiology Network of Salt-Sensitivity (GenSalt) study. The GenSalt study was conducted among 1906 participants from 633 Han Chinese families. Lipids were measured from overnight fasting blood samples using standard methods. Multipoint quantitative trait genome-wide linkage scans were performed on the high-density lipoprotein, low-density lipoprotein, and log-transformed triglyceride phenotypes. Using dense panels of single nucleotide polymorphisms (SNPs), single-marker and gene-based association analyses were conducted to follow-up on promising linkage signals. Additive associations between each SNP and lipid phenotypes were tested using mixed linear regression models. Gene-based analyses were performed by combining P-values from single-marker analyses within each gene using the truncated product method (TPM). Significant associations were assessed for replication among 777 Asian participants of the Multi-ethnic Study of Atherosclerosis (MESA). Bonferroni correction was used to adjust for multiple testing. In the GenSalt study, suggestive linkage signals were identified at 2p11.2‒2q12.1 [maximum multipoint LOD score (MML) = 2.18 at 2q11.2] and 11q24.3‒11q25 (MML = 2.29 at 11q25) for the log-transformed triglyceride phenotype. Follow-up analyses of these two regions revealed gene-based associations of charged multivesicular body protein 3 (CHMP3), ring finger protein 103 (RNF103), AF4/FMR2 family, member 3 (AFF3), and neurotrimin (NTM) with triglycerides (P = 4 × 10(-4), 1.00 × 10(-5), 2.00 × 10(-5), and 1.00 × 10(-7), respectively). Both the AFF3 and NTM triglyceride associations were replicated among MESA study participants (P = 1.00 × 10(-7) and 8.00 × 10(-5), respectively). Furthermore, NTM explained the linkage signal on chromosome 11. In conclusion, we identified novel genes associated with lipid phenotypes in linkage regions on chromosomes 2 and 11.
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Affiliation(s)
- Changwei Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA
| | - Lydia A L Bazzano
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA; Department of Medicine, Tulane University School of Medicine, New Orleans, LA 70112, USA
| | - Dabeeru C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - James E Hixson
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas School of Public Health, Houston, TX 77030, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA; Department of Medicine, Tulane University School of Medicine, New Orleans, LA 70112, USA
| | - Dongfeng Gu
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Charles C Gu
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - Lawrence C Shimmin
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas School of Public Health, Houston, TX 77030, USA
| | - Cashell E Jaquish
- Division of Prevention and Population Sciences, National Heart, Lung, Blood Institute, Bethesda, MD 20892-7936, USA
| | - Karen Schwander
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110-1093, USA
| | - De-Pei Liu
- National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Jianfeng Huang
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Fanghong Lu
- Institute of Basic Medicine, Shandong Academy of Medical Sciences, Ji'nan 250062, China
| | - Jie Cao
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Shen Chong
- Department of Epidemiology and Biostatistics, Nanjing Medical University School of Public Health, Nanjing 210029, China
| | - Xiangfeng Lu
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Tanika N Kelly
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA.
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Li C, Chen W, Jiang F, Simino J, Srinivasan SR, Berenson GS, Mei H. Genetic association and gene-smoking interaction study of carotid intima-media thickness at five GWAS-indicated genes: the Bogalusa Heart Study. Gene 2015; 562:226-31. [PMID: 25746325 DOI: 10.1016/j.gene.2015.02.078] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2014] [Revised: 02/23/2015] [Accepted: 02/27/2015] [Indexed: 11/25/2022]
Abstract
OBJECTIVES To examine the associations of five GWAS-identified genes with carotid intima-media thickness (IMT) in a biracial sample from the Bogalusa Heart Study, and evaluate their participation in gene-smoking interactions. METHODS Far wall IMTs of common carotid arteries were measured using high-resolution B-mode ultrasound. Both the gene-smoking interactions and single-marker associations were evaluated by linear models of carotid IMT levels, while the gene-based analyses were assessed through the truncated product method. A Bonferroni multiple testing correction was applied. RESULTS Marker rs7840785 (PINX1) was significantly associated with right carotid IMT (p=0.0003) using all participants; mean levels for the CC, TC, and TT genotypes were 0.74 (0.73 to 0.75), 0.76 (0.75 to 0.78), and 0.78 (0.75, 0.81), respectively. Similar trends were observed in blacks (p=0.0031) and whites (p=0.0118). Marker rs7844465 (ZHX2) was significantly associated with left carotid IMT in whites (p=0.0005); mean IMT levels for the GG, TG, and TT genotypes were 0.73 (0.71 to 0.74), 0.75 (0.74 to 0.77) and 0.78 (0.75 to 0.81), respectively. Marker rs6841473 (EDNRA) modified the association between smoking and left carotid IMT in blacks (p=2.79×10(-5)). In addition, gene-based analysis demonstrated that EDNRA and ZHX2 were associated with left carotid IMT in the white and overall participants, respectively, while PINX1 was associated with right carotid IMT in both blacks and whites. CONCLUSION We identified two novel markers that were associated with IMT in both blacks and whites. One gene-smoking interaction was identified in blacks only. Three genes showed gene-based associations with IMT levels. However, genetic markers with small effects may have been missed due to the limited number of black participants.
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Affiliation(s)
- Changwei Li
- Department of Epidemiology, Tulane University, New Orleans, LA, USA.
| | - Wei Chen
- Tulane Center for Cardiovascular Health, Tulane University, New Orleans, LA, USA.
| | - Fan Jiang
- Shanghai Children's Medical Center, Shanghai Jiaotong University, Shanghai, China.
| | - Jeannette Simino
- Center of Biostatistics and Bioinformatics, University of Mississippi Medical Center, Jackson, MS 39216-4505, USA.
| | | | - Gerald S Berenson
- Center for Cardiovascular Health, 1440 Canal St, Suite 1829, New Orleans, LA 70112, USA.
| | - Hao Mei
- Shanghai Children's Medical Center, Shanghai Jiaotong University, Shanghai, China; Center of Biostatistics and Bioinformatics, University of Mississippi Medical Center, Jackson, MS 39216-4505, USA.
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Genetic variants in nicotinic acetylcholine receptor genes jointly contribute to kidney function in American Indians: the Strong Heart Family Study. J Hypertens 2014; 32:1042-8; discussion 1049. [PMID: 24569419 DOI: 10.1097/hjh.0000000000000151] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
BACKGROUND Cigarette smoking negatively affects kidney function. Genetic variants in the nicotinic acetylcholine receptor (nAChR) genes have been associated with nicotine dependence, and are likely to influence renal function and related traits. Whereas each single variant may only exert a small effect, the joint contribution of multiple variants to the risk of disease could be substantial. METHODS Using a gene-family approach, we investigated the joint association of 61 tagging SNPs in seven genes encoding the nAChRs with kidney function in 3620 American Indians participating in the Strong Heart Family Study, independent of known risk factors. Kidney function was evaluated by estimated glomerular filtration rate, urinary albumin/creatinine ratio, albuminuria and chronic kidney disease. The joint impact of smoking-related variants was assessed using the weighted truncated product method. RESULTS Multiple SNPs showed marginal individual effect on renal function variability, and only a few survive multiple comparison correction. In contrast, a gene-family analysis considering the joint impact of all 61 SNPs reveals significant associations of the nAChR gene family with kidney function variables including estimated glomerular filtration rate, urinary albumin/creatinine ratio, and albuminuria (all Ps ≤ 0.0001) after adjusting for established risk factors including cigarette smoking. CONCLUSION Genetic variants in nAChR genes jointly contribute to renal function or kidney damage in American Indians. The effects of these genetic variants on kidney function or damage are independent of traditional risk factors including cigarette smoking per se.
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Joint association of nicotinic acetylcholine receptor variants with abdominal obesity in American Indians: the Strong Heart Family Study. PLoS One 2014; 9:e102220. [PMID: 25036316 PMCID: PMC4103845 DOI: 10.1371/journal.pone.0102220] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2014] [Accepted: 06/16/2014] [Indexed: 11/19/2022] Open
Abstract
Cigarette smoke is a strong risk factor for obesity and cardiovascular disease. The effect of genetic variants involved in nicotine metabolism on obesity or body composition has not been well studied. Though many genetic variants have previously been associated with adiposity or body fat distribution, a single variant usually confers a minimal individual risk. The goal of this study is to evaluate the joint association of multiple variants involved in cigarette smoke or nicotine dependence with obesity-related phenotypes in American Indians. To achieve this goal, we genotyped 61 tagSNPs in seven genes encoding nicotine acetylcholine receptors (nAChRs) in 3,665 American Indians participating in the Strong Heart Family Study. Single SNP association with obesity-related traits was tested using family-based association, adjusting for traditional risk factors including smoking. Joint association of all SNPs in the seven nAChRs genes were examined by gene-family analysis based on weighted truncated product method (TPM). Multiple testing was controlled by false discovery rate (FDR). Results demonstrate that multiple SNPs showed weak individual association with one or more measures of obesity, but none survived correction for multiple testing. However, gene-family analysis revealed significant associations with waist circumference (p = 0.0001) and waist-to-hip ratio (p = 0.0001), but not body mass index (p = 0.20) and percent body fat (p = 0.29), indicating that genetic variants are jointly associated with abdominal, but not general, obesity among American Indians. The observed combined genetic effect is independent of cigarette smoking per se. In conclusion, multiple variants in the nAChR gene family are jointly associated with abdominal obesity in American Indians, independent of general obesity and cigarette smoking per se.
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Yang X, Gu D, He J, Hixson JE, Rao DC, Lu F, Mu J, Jaquish CE, Chen J, Huang J, Shimmin LC, Rice TK, Chen J, Wu X, Liu D, Kelly TN. Genome-wide linkage and regional association study of blood pressure response to the cold pressor test in Han Chinese: the genetic epidemiology network of salt sensitivity study. ACTA ACUST UNITED AC 2014; 7:521-8. [PMID: 25028485 DOI: 10.1161/circgenetics.113.000332] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
BACKGROUND Blood pressure (BP) response to cold pressor test (CPT) is associated with increased risk of cardiovascular disease. We performed a genome-wide linkage scan and regional association analysis to identify genetic determinants of BP response to CPT. METHODS AND RESULTS A total of 1961 Chinese participants completed the CPT. Multipoint quantitative trait linkage analysis was performed, followed by single-marker and gene-based analyses of variants in promising linkage regions (logarithm of odds ≥2). A suggestive linkage signal was identified for systolic BP response to CPT at 20p13 to 20p12.3, with a maximum multipoint logarithm of odds score of 2.37. On the basis of regional association analysis with 1351 single nucleotide polymorphisms in the linkage region, we found that marker rs2326373 at 20p13 was significantly associated with mean arterial pressure responses to CPT (P=8.8×10(-6)) after false discovery rate adjustment for multiple comparisons. A similar trend was also observed for systolic BP response (P=0.03) and diastolic BP response (P=4.6×10(-5)). Results of gene-based analyses showed that variants in genes MCM8 and SLC23A2 were associated with systolic BP response to CPT (P=4.0×10(-5) and 2.7×10(-4), respectively), and variants in genes MCM8 and STK35 were associated with mean arterial pressure response to CPT (P=1.5×10(-5) and 5.0×10(-5), respectively). CONCLUSIONS Within a suggestive linkage region on chromosome 20, we identified a novel variant associated with BP responses to CPT. We also found gene-based associations of MCM8, SLC23A2, and STK35 in this region. Additional work is warranted to confirm these findings. CLINICAL TRIAL REGISTRATION URL http://www.clinicaltrials.gov; Unique identifier: NCT00721721.
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Affiliation(s)
- Xueli Yang
- From the Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (X.Y., J.H., J.C., T.N.K.); State Key Laboratory of Cardiovascular Disease, Department of Epidemiology and Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases (X.Y., D.G., J.H., J.C., X.W.) and National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences (D.L.), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.H., J.C.); Department of Epidemiology, University of Texas School of Public Health, Houston (J.E.H., L.C.S.); Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R., T.K.R.); Institute of Basic Medicine, Shandong Academy of Medical Sciences, Shandong, China (F.L.); Department of Cardiology, First Affiliated Hospital of Medical College of Xi'an Jiaotong University, Shaanxi, China (J.M.); and Division of Prevention and Population Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (C.E.J.)
| | - Dongfeng Gu
- From the Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (X.Y., J.H., J.C., T.N.K.); State Key Laboratory of Cardiovascular Disease, Department of Epidemiology and Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases (X.Y., D.G., J.H., J.C., X.W.) and National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences (D.L.), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.H., J.C.); Department of Epidemiology, University of Texas School of Public Health, Houston (J.E.H., L.C.S.); Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R., T.K.R.); Institute of Basic Medicine, Shandong Academy of Medical Sciences, Shandong, China (F.L.); Department of Cardiology, First Affiliated Hospital of Medical College of Xi'an Jiaotong University, Shaanxi, China (J.M.); and Division of Prevention and Population Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (C.E.J.).
| | - Jiang He
- From the Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (X.Y., J.H., J.C., T.N.K.); State Key Laboratory of Cardiovascular Disease, Department of Epidemiology and Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases (X.Y., D.G., J.H., J.C., X.W.) and National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences (D.L.), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.H., J.C.); Department of Epidemiology, University of Texas School of Public Health, Houston (J.E.H., L.C.S.); Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R., T.K.R.); Institute of Basic Medicine, Shandong Academy of Medical Sciences, Shandong, China (F.L.); Department of Cardiology, First Affiliated Hospital of Medical College of Xi'an Jiaotong University, Shaanxi, China (J.M.); and Division of Prevention and Population Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (C.E.J.)
| | - James E Hixson
- From the Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (X.Y., J.H., J.C., T.N.K.); State Key Laboratory of Cardiovascular Disease, Department of Epidemiology and Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases (X.Y., D.G., J.H., J.C., X.W.) and National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences (D.L.), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.H., J.C.); Department of Epidemiology, University of Texas School of Public Health, Houston (J.E.H., L.C.S.); Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R., T.K.R.); Institute of Basic Medicine, Shandong Academy of Medical Sciences, Shandong, China (F.L.); Department of Cardiology, First Affiliated Hospital of Medical College of Xi'an Jiaotong University, Shaanxi, China (J.M.); and Division of Prevention and Population Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (C.E.J.)
| | - Dabeeru C Rao
- From the Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (X.Y., J.H., J.C., T.N.K.); State Key Laboratory of Cardiovascular Disease, Department of Epidemiology and Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases (X.Y., D.G., J.H., J.C., X.W.) and National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences (D.L.), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.H., J.C.); Department of Epidemiology, University of Texas School of Public Health, Houston (J.E.H., L.C.S.); Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R., T.K.R.); Institute of Basic Medicine, Shandong Academy of Medical Sciences, Shandong, China (F.L.); Department of Cardiology, First Affiliated Hospital of Medical College of Xi'an Jiaotong University, Shaanxi, China (J.M.); and Division of Prevention and Population Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (C.E.J.)
| | - Fanghong Lu
- From the Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (X.Y., J.H., J.C., T.N.K.); State Key Laboratory of Cardiovascular Disease, Department of Epidemiology and Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases (X.Y., D.G., J.H., J.C., X.W.) and National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences (D.L.), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.H., J.C.); Department of Epidemiology, University of Texas School of Public Health, Houston (J.E.H., L.C.S.); Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R., T.K.R.); Institute of Basic Medicine, Shandong Academy of Medical Sciences, Shandong, China (F.L.); Department of Cardiology, First Affiliated Hospital of Medical College of Xi'an Jiaotong University, Shaanxi, China (J.M.); and Division of Prevention and Population Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (C.E.J.)
| | - Jianjun Mu
- From the Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (X.Y., J.H., J.C., T.N.K.); State Key Laboratory of Cardiovascular Disease, Department of Epidemiology and Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases (X.Y., D.G., J.H., J.C., X.W.) and National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences (D.L.), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.H., J.C.); Department of Epidemiology, University of Texas School of Public Health, Houston (J.E.H., L.C.S.); Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R., T.K.R.); Institute of Basic Medicine, Shandong Academy of Medical Sciences, Shandong, China (F.L.); Department of Cardiology, First Affiliated Hospital of Medical College of Xi'an Jiaotong University, Shaanxi, China (J.M.); and Division of Prevention and Population Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (C.E.J.)
| | - Cashell E Jaquish
- From the Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (X.Y., J.H., J.C., T.N.K.); State Key Laboratory of Cardiovascular Disease, Department of Epidemiology and Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases (X.Y., D.G., J.H., J.C., X.W.) and National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences (D.L.), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.H., J.C.); Department of Epidemiology, University of Texas School of Public Health, Houston (J.E.H., L.C.S.); Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R., T.K.R.); Institute of Basic Medicine, Shandong Academy of Medical Sciences, Shandong, China (F.L.); Department of Cardiology, First Affiliated Hospital of Medical College of Xi'an Jiaotong University, Shaanxi, China (J.M.); and Division of Prevention and Population Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (C.E.J.)
| | - Jing Chen
- From the Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (X.Y., J.H., J.C., T.N.K.); State Key Laboratory of Cardiovascular Disease, Department of Epidemiology and Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases (X.Y., D.G., J.H., J.C., X.W.) and National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences (D.L.), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.H., J.C.); Department of Epidemiology, University of Texas School of Public Health, Houston (J.E.H., L.C.S.); Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R., T.K.R.); Institute of Basic Medicine, Shandong Academy of Medical Sciences, Shandong, China (F.L.); Department of Cardiology, First Affiliated Hospital of Medical College of Xi'an Jiaotong University, Shaanxi, China (J.M.); and Division of Prevention and Population Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (C.E.J.)
| | - Jianfeng Huang
- From the Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (X.Y., J.H., J.C., T.N.K.); State Key Laboratory of Cardiovascular Disease, Department of Epidemiology and Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases (X.Y., D.G., J.H., J.C., X.W.) and National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences (D.L.), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.H., J.C.); Department of Epidemiology, University of Texas School of Public Health, Houston (J.E.H., L.C.S.); Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R., T.K.R.); Institute of Basic Medicine, Shandong Academy of Medical Sciences, Shandong, China (F.L.); Department of Cardiology, First Affiliated Hospital of Medical College of Xi'an Jiaotong University, Shaanxi, China (J.M.); and Division of Prevention and Population Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (C.E.J.)
| | - Lawrence C Shimmin
- From the Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (X.Y., J.H., J.C., T.N.K.); State Key Laboratory of Cardiovascular Disease, Department of Epidemiology and Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases (X.Y., D.G., J.H., J.C., X.W.) and National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences (D.L.), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.H., J.C.); Department of Epidemiology, University of Texas School of Public Health, Houston (J.E.H., L.C.S.); Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R., T.K.R.); Institute of Basic Medicine, Shandong Academy of Medical Sciences, Shandong, China (F.L.); Department of Cardiology, First Affiliated Hospital of Medical College of Xi'an Jiaotong University, Shaanxi, China (J.M.); and Division of Prevention and Population Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (C.E.J.)
| | - Treva K Rice
- From the Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (X.Y., J.H., J.C., T.N.K.); State Key Laboratory of Cardiovascular Disease, Department of Epidemiology and Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases (X.Y., D.G., J.H., J.C., X.W.) and National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences (D.L.), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.H., J.C.); Department of Epidemiology, University of Texas School of Public Health, Houston (J.E.H., L.C.S.); Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R., T.K.R.); Institute of Basic Medicine, Shandong Academy of Medical Sciences, Shandong, China (F.L.); Department of Cardiology, First Affiliated Hospital of Medical College of Xi'an Jiaotong University, Shaanxi, China (J.M.); and Division of Prevention and Population Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (C.E.J.)
| | - Jichun Chen
- From the Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (X.Y., J.H., J.C., T.N.K.); State Key Laboratory of Cardiovascular Disease, Department of Epidemiology and Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases (X.Y., D.G., J.H., J.C., X.W.) and National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences (D.L.), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.H., J.C.); Department of Epidemiology, University of Texas School of Public Health, Houston (J.E.H., L.C.S.); Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R., T.K.R.); Institute of Basic Medicine, Shandong Academy of Medical Sciences, Shandong, China (F.L.); Department of Cardiology, First Affiliated Hospital of Medical College of Xi'an Jiaotong University, Shaanxi, China (J.M.); and Division of Prevention and Population Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (C.E.J.)
| | - Xigui Wu
- From the Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (X.Y., J.H., J.C., T.N.K.); State Key Laboratory of Cardiovascular Disease, Department of Epidemiology and Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases (X.Y., D.G., J.H., J.C., X.W.) and National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences (D.L.), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.H., J.C.); Department of Epidemiology, University of Texas School of Public Health, Houston (J.E.H., L.C.S.); Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R., T.K.R.); Institute of Basic Medicine, Shandong Academy of Medical Sciences, Shandong, China (F.L.); Department of Cardiology, First Affiliated Hospital of Medical College of Xi'an Jiaotong University, Shaanxi, China (J.M.); and Division of Prevention and Population Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (C.E.J.)
| | - Depei Liu
- From the Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (X.Y., J.H., J.C., T.N.K.); State Key Laboratory of Cardiovascular Disease, Department of Epidemiology and Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases (X.Y., D.G., J.H., J.C., X.W.) and National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences (D.L.), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.H., J.C.); Department of Epidemiology, University of Texas School of Public Health, Houston (J.E.H., L.C.S.); Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R., T.K.R.); Institute of Basic Medicine, Shandong Academy of Medical Sciences, Shandong, China (F.L.); Department of Cardiology, First Affiliated Hospital of Medical College of Xi'an Jiaotong University, Shaanxi, China (J.M.); and Division of Prevention and Population Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (C.E.J.)
| | - Tanika N Kelly
- From the Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (X.Y., J.H., J.C., T.N.K.); State Key Laboratory of Cardiovascular Disease, Department of Epidemiology and Population Genetics, Fuwai Hospital, National Center of Cardiovascular Diseases (X.Y., D.G., J.H., J.C., X.W.) and National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences (D.L.), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Medicine, Tulane University School of Medicine, New Orleans, LA (J.H., J.C.); Department of Epidemiology, University of Texas School of Public Health, Houston (J.E.H., L.C.S.); Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R., T.K.R.); Institute of Basic Medicine, Shandong Academy of Medical Sciences, Shandong, China (F.L.); Department of Cardiology, First Affiliated Hospital of Medical College of Xi'an Jiaotong University, Shaanxi, China (J.M.); and Division of Prevention and Population Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD (C.E.J.).
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Li C, Yang X, He J, Hixson JE, Gu D, Rao DC, Shimmin LC, Huang J, Gu CC, Chen J, Li J, Kelly TN. A gene-based analysis of variants in the serum/glucocorticoid regulated kinase (SGK) genes with blood pressure responses to sodium intake: the GenSalt Study. PLoS One 2014; 9:e98432. [PMID: 24878720 PMCID: PMC4039502 DOI: 10.1371/journal.pone.0098432] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2014] [Accepted: 04/22/2014] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Serum and glucocorticoid regulated kinase (SGK) plays a critical role in the regulation of renal sodium transport. We examined the association between SGK genes and salt sensitivity of blood pressure (BP) using single-marker and gene-based association analysis. METHODS A 7-day low-sodium (51.3 mmol sodium/day) followed by a 7-day high-sodium intervention (307.8 mmol sodium/day) was conducted among 1,906 Chinese participants. BP measurements were obtained at baseline and each intervention using a random-zero sphygmomanometer. Additive associations between each SNP and salt-sensitivity phenotypes were assessed using a mixed linear regression model to account for family dependencies. Gene-based analyses were conducted using the truncated p-value method. The Bonferroni-method was used to adjust for multiple testing in all analyses. RESULTS In single-marker association analyses, SGK1 marker rs2758151 was significantly associated with diastolic BP (DBP) response to high-sodium intervention (P = 0.0010). DBP responses (95% confidence interval) to high-sodium intervention for genotypes C/C, C/T, and T/T were 2.04 (1.57 to 2.52), 1.79 (1.42 to 2.16), and 0.85 (0.30 to 1.41) mmHg, respectively. Similar trends were observed for SBP and MAP responses although not significant (P = 0.15 and 0.0026, respectively). In addition, gene-based analyses demonstrated significant associations between SGK1 and SBP, DBP and MAP responses to high sodium intervention (P = 0.0002, 0.0076, and 0.00001, respectively). Neither SGK2 nor SGK3 were associated with the salt-sensitivity phenotypes in single-maker or gene-based analyses. CONCLUSIONS The current study identified association of the SGK1 gene and BP salt-sensitivity in the Han Chinese population. Further studies are warranted to identify causal SGK1 gene variants.
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Affiliation(s)
- Changwei Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, United States of America
| | - Xueli Yang
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, United States of America
- Department of Medicine, Tulane University School of Medicine, New Orleans, Louisiana, United States of America
| | - James E. Hixson
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas School of Public Health, Houston, Texas, United States of America
| | - Dongfeng Gu
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Dabeeru C. Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Lawrence C. Shimmin
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas School of Public Health, Houston, Texas, United States of America
| | - Jianfeng Huang
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Charles C. Gu
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Jichun Chen
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianxin Li
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Tanika N. Kelly
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, United States of America
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Otake T, Fukumoto J, Abe M, Takemura S, Mihn PN, Mizoue T, Kiyohara C. Linking lifestyle factors and insulin resistance, based on fasting plasma insulin and HOMA-IR in middle-aged Japanese men: a cross-sectional study. Scandinavian Journal of Clinical and Laboratory Investigation 2014; 74:536-45. [PMID: 24830843 DOI: 10.3109/00365513.2014.913304] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
OBJECTIVE Insulin resistance (IR) is regarded as one of the earliest features of many metabolic diseases, and major efforts are aimed at improving insulin function to confront this issue. The aim of this study was to investigate the relationship of body mass index (BMI), cigarette smoking, alcohol intake, physical activity, green tea and coffee consumption to IR. METHODS We performed a cross-sectional study of 1542 male self defense officials. IR was defined as the highest quartile of the fasting plasma insulin (≥ 50 pmol/L) or the homeostasis model assessment-estimated IR (HOMA-IR ≥ 1.81). An unconditional logistic model was used to estimate the odds ratio (OR) and 95% confidence interval (CI) for the association between IR and influential factors. Stratified analysis by obesity status (BMI < 25 kg/m(2), non-obese; ≥ 25 kg/m(2), obese) was performed. RESULTS IR was significantly positively related to BMI and glucose tolerance, negatively related to alcohol use. Independent of obesity status, significant trends were observed between IR and alcohol use. Drinking 30 mL or more of ethanol per day reduced IR by less than 40%. Strong physical activity was associated with decreased risk of IR based on fasting plasma insulin only in the obese. Coffee consumption was inversely associated with the risk of IR based on HOMA-IR in the non-obese group. CONCLUSION Higher coffee consumption may be protective against IR among only the non-obese. Further studies are warranted to examine the effect modification of the obesity status on the coffee-IR association.
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Affiliation(s)
- Toshie Otake
- Self Defense Forces Fukuoka Hospital , Kasuga, Fukuoka , Japan
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Somm E, Guérardel A, Maouche K, Toulotte A, Veyrat-Durebex C, Rohner-Jeanrenaud F, Maskos U, Hüppi PS, Schwitzgebel VM. Concomitant alpha7 and beta2 nicotinic AChR subunit deficiency leads to impaired energy homeostasis and increased physical activity in mice. Mol Genet Metab 2014; 112:64-72. [PMID: 24685552 DOI: 10.1016/j.ymgme.2014.03.003] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2013] [Revised: 03/12/2014] [Accepted: 03/12/2014] [Indexed: 12/18/2022]
Abstract
Nicotinic acetylcholine receptors (nAChRs) are pentameric ligand-gated cation channels well characterized in neuronal signal transmission. Moreover, recent studies have revealed nAChR expression in nonneuronal cell types throughout the body, including tissues involved in metabolism. In the present study, we screen gene expression of nAChR subunits in pancreatic islets and adipose tissues. Mice pancreatic islets present predominant expression of α7 and β2 nAChR subunits but at a lower level than in central structures. Characterization of glucose and energy homeostasis in α7β2nAChR(-/-) mice revealed no major defect in insulin secretion and sensitivity but decreased glycemia apparently unrelated to gluconeogenesis or glycogenolysis. α7β2nAChR(-/-) mice presented an increase in lean and bone body mass and a decrease in fat storage with normal body weight. These observations were associated with elevated spontaneous physical activity in α7β2nAChR(-/-) mice, mainly due to elevation in fine vertical (rearing) activity while their horizontal (ambulatory) activity remained unchanged. In contrast to α7nAChR(-/-) mice presenting glucose intolerance and insulin resistance associated to excessive inflammation of adipose tissue, the present metabolic phenotyping of α7β2nAChR(-/-) mice revealed a metabolic improvement possibly linked to the increase in spontaneous physical activity related to central β2nAChR deficiency.
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Affiliation(s)
- Emmanuel Somm
- Division of Development and Growth, Department of Paediatrics, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
| | - Audrey Guérardel
- Division of Development and Growth, Department of Paediatrics, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Kamel Maouche
- Université Paris-Diderot, Sorbonne-Paris-Cité, Laboratoire B2PE (Biologie et Pathologie du Pancréas Endocrine), Unité BFA (Biologie Fonctionnelle et Adaptative), CNRS UMR 8251, Paris, France
| | - Audrey Toulotte
- Division of Development and Growth, Department of Paediatrics, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Christelle Veyrat-Durebex
- Laboratory of Metabolism, Department of Internal Medicine Specialties, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Françoise Rohner-Jeanrenaud
- Laboratory of Metabolism, Department of Internal Medicine Specialties, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Uwe Maskos
- Département de Neuroscience, Institut Pasteur, Unité Neurobiologie intégrative des systèmes cholinergiques, Paris, France
| | - Petra S Hüppi
- Division of Development and Growth, Department of Paediatrics, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Valérie M Schwitzgebel
- Division of Development and Growth, Department of Paediatrics, Faculty of Medicine, University of Geneva, Geneva, Switzerland
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Nicotinic Cholinergic Signaling in Adipose Tissue and Pancreatic Islets Biology: Revisited Function and Therapeutic Perspectives. Arch Immunol Ther Exp (Warsz) 2013; 62:87-101. [DOI: 10.1007/s00005-013-0266-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2013] [Accepted: 11/14/2013] [Indexed: 12/14/2022]
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ALI R, LEE ET, KNEHANS AW, ZHANG Y, YEH J, RHOADES ER, JOBE JB, ALI T, JOHNSON MR. Dietary Intake among American Indians with Metabolic Syndrome - Comparison to Dietary Recommendations: the Balance Study. INTERNATIONAL JOURNAL OF HEALTH AND NUTRITION 2013; 4:33-45. [PMID: 26594109 PMCID: PMC4651460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
BACKGROUND American Indians have a very high prevalence of metabolic syndrome that increases their risk of developing cardiovascular disease and type 2 diabetes. Dietary habits are of central importance in the prevention and treatment of metabolic syndrome. OBJECTIVE The main objective of this article was to describe dietary intake among American Indians with metabolic syndrome and compare it to several dietary recommendations. A secondary objective was to identify certain barriers to dietary adherence experienced by this population. METHODS A total of 213 participants with metabolic syndrome were enrolled in the Balance Study, a randomized controlled trial with two intervention groups: Guided Group and Self-Managed Group. Dietary intake was assessed using the Block Food Frequency questionnaire. Dietary intakes were evaluated against the Dietary Guidelines for Americans. RESULTS Intakes of saturated fats, cholesterol, and sodium were higher and intakes of dietary fiber, calcium, magnesium, potassium, vitamin A, vitamin D, and vitamin E were lower than recommended. Additionally, intake of many food groups was noticeably low. Economic factors seem to be related to low adherence to dietary recommendations. CONCLUSION Results showed low adherence by the participants to dietary recommendations for key nutrients and food groups related to risk factors for metabolic syndrome, type 2 diabetes, and cardiovascular disease. Economic factors are related to this low adherence. These findings illustrate a need to develop innovative, focused, and perhaps individualized health promotion strategies that can improve dietary habits of American Indians with metabolic syndrome.
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Affiliation(s)
- Rohaid ALI
- Center for American Indian Health Research, University of Oklahoma Health Sciences Center, United States
| | - Elisa T. LEE
- Center for American Indian Health Research, University of Oklahoma Health Sciences Center, United States
| | - Allen W. KNEHANS
- Department of Nutritional Sciences, University of Oklahoma Health Sciences Center, United States
| | - Ying ZHANG
- Center for American Indian Health Research, University of Oklahoma Health Sciences Center, United States
| | - Jeunliang YEH
- Center for American Indian Health Research, University of Oklahoma Health Sciences Center, United States
| | - Everett R. RHOADES
- Center for American Indian Health Research, University of Oklahoma Health Sciences Center, United States
| | - Jared B. JOBE
- Division of Cancer Control and Population Sciences, National Cancer Institute, United States
| | - Tauqeer ALI
- Center for American Indian Health Research, University of Oklahoma Health Sciences Center, United States
| | - Melanie R. JOHNSON
- Center for American Indian Health Research, University of Oklahoma Health Sciences Center, United States
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Yang J, Zhu Y, Lee ET, Zhang Y, Cole SA, Haack K, Best LG, Devereux RB, Roman MJ, Howard BV, Zhao J. Joint associations of 61 genetic variants in the nicotinic acetylcholine receptor genes with subclinical atherosclerosis in American Indians: a gene-family analysis. ACTA ACUST UNITED AC 2012; 6:89-96. [PMID: 23264444 DOI: 10.1161/circgenetics.112.963967] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
BACKGROUND Atherosclerosis is the underlying cause of cardiovascular disease, the leading cause of morbidity and mortality in all American populations, including American Indians. Genetic factors play an important role in the pathogenesis of atherosclerosis. Although a single-nucleotide polymorphism (SNP) may explain only a small portion of variability in disease, the joint effect of multiple variants in a pathway on disease susceptibility could be large. METHODS AND RESULTS Using a gene-family analysis, we investigated the joint associations of 61 tag SNPs in 7 nicotinic acetylcholine receptor genes with subclinical atherosclerosis, as measured by carotid intima-media thickness and plaque score, in 3665 American Indians from 94 families recruited by the Strong Heart Family Study (SHFS). Although multiple SNPs showed marginal association with intima-media thickness and plaque score individually, only a few survived adjustments for multiple testing. However, simultaneously modeling of the joint effect of all 61 SNPs in 7 nicotinic acetylcholine receptor genes revealed significant association of the nicotinic acetylcholine receptor gene family with both intima-media thickness and plaque score independent of known coronary risk factors. CONCLUSIONS Genetic variants in the nicotinic acetylcholine receptor gene family jointly contribute to subclinical atherosclerosis in American Indians who participated in the SHFS. These variants may influence the susceptibility of atherosclerosis through pathways other than cigarette smoking per se.
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Affiliation(s)
- Jingyun Yang
- Tulane University School of Public Health and Tropical Medicine, New Orleans, LA
| | - Yun Zhu
- Tulane University School of Public Health and Tropical Medicine, New Orleans, LA
| | - Elisa T Lee
- Center for American Indian Health Research, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Ying Zhang
- Center for American Indian Health Research, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | | | - Karin Haack
- Texas Biomedical Research Institute, San Antonio, TX
| | - Lyle G Best
- Missouri Breaks Industries Research Inc., Timber Lake, SD
| | | | - Mary J Roman
- The New York Hospital-Cornell Medical Center, New York, NY
| | - Barbara V Howard
- MedStar Health Research Institute Hyattsville, MD & Georgetown and Howard Universities Centers for Translational Sciences, Washington DC
| | - Jinying Zhao
- Tulane University School of Public Health and Tropical Medicine, New Orleans, LA
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