Identification of genetic loci simultaneously associated with multiple cardiometabolic traits |
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| Affiliation: | 1. USDA/ARS Children''s Nutrition Research Center, 1100 Bates Avenue, Houston, TX, USA;2. Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA;3. Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, UK;4. Nutrition and Genomics Laboratory, Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA;5. IMDEA-Food, Madrid, Spain;6. BIO5 Institute, University of Arizona, Tucson, AZ, USA;7. Division of Geriatric Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA;8. Department of Biostatistics, University of California, Los Angeles, CA, USA;1. Department of Non-communicable Disease Prevention, Nanjing Municipal Center for Disease Control and Prevention, Nanjing, 210003, China;2. Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China;3. Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, 211166, China;4. Department of Chronic Disease Prevention and Control, Huai''an City Center for Disease Control and Prevention, Huai''an, 223001, China;5. Department of Chronic Disease Prevention and Control, Suzhou City Center for Disease Control and Prevention, Suzhou, 215003, China;6. Changshu County Center for Disease Control and Prevention, Suzhou, 215500, China;7. Department of Epidemiology and Biostatistics, School of Public Health, Southeast University, Nanjing, 210009, China;1. Division of Cardiology, Ospedale degli Infermi, ASL Biella, Biella, Italy;2. Department of Translational Medicine, Università del Piemonte Orientale, Novara, Italy;3. Clinical Chemistry Ospedale degli Infermi, ASL Biella, Biella, Italy;4. Dipartimento di Scienze della Sanità Pubblica e Pediatriche, Università degli Studi di Torino, Italy;5. Clinical Chemistry, Azienda Ospedaliera-Universitaria “Maggiore della Carità”, Università del Piemonte Orientale, Novara, Italy;6. Radiology, Azienda Ospedaliera-Universitaria “Maggiore della Carità”, Università del Piemonte Orientale, Novara, Italy;7. Division of Cardiology, Azienda Ospedaliera-Universitaria “Maggiore della Carità”, Università del Piemonte Orientale, Novara, Italy;1. Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing 100069, China;2. Physical Examination Center, Xuanwu Hospital, Capital Medical University, Beijing 100053, China;3. Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China;1. Department of Dermatology, West Virginia University, Morgantown, West Virginia;2. West Virginia Clinical and Translational Science Institute, Morgantown, West Virginia |
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| Abstract: | Background and aimsCardiometabolic disorders (CMD) arise from a constellation of features such as increased adiposity, hyperlipidemia, hypertension and compromised glucose control. Many genetic loci have shown associations with individual CMD-related traits, but no investigations have focused on simultaneously identifying loci showing associations across all domains. We therefore sought to identify loci associated with risk across seven continuous CMD-related traits.Methods and resultsWe conducted separate genome-wide association studies (GWAS) for systolic and diastolic blood pressure (SBP/DBP), hemoglobin A1c (HbA1c), low- and high- density lipoprotein cholesterol (LDL-C/HDL-C), waist-to-hip-ratio (WHR), and triglycerides (TGs) in the UK Biobank (N = 356,574–456,823). Multiple loci reached genome-wide levels of significance (N = 145–333) for each trait, but only four loci (in/near VEGFA, GRB14-COBLL1, KLF14, and RGS19-OPRL1) were associated with risk across all seven traits (P < 5 × 10?8). We sought replication of these four loci in an independent set of seven trait-specific GWAS meta-analyses. GRB14-COBLL1 showed the most consistent replication, revealing nominally significant associations (P < 0.05) with all traits except DBP.ConclusionsOur analyses suggest that very few loci are associated in the same direction of risk with traits representing the full spectrum of CMD features. We identified four such loci, and an understanding of the pathways between these loci and CMD risk may eventually identify factors that can be used to identify pathologic disturbances that represent broadly beneficial therapeutic targets. |
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| Keywords: | Cardiometabolic disease Epidemiology Fat distribution GWAS Pleiotropy Risk alleles Risk factors ALT" },{" #name" :" keyword" ," $" :{" id" :" kwrd0050" }," $$" :[{" #name" :" text" ," _" :" alanine aminotransferase BMI" },{" #name" :" keyword" ," $" :{" id" :" kwrd0060" }," $$" :[{" #name" :" text" ," _" :" body mass index CARDIOGRAM" },{" #name" :" keyword" ," $" :{" id" :" kwrd0070" }," $$" :[{" #name" :" text" ," _" :" Coronary Artery Disease Genome-wide Replication And Meta-analysis CAD" },{" #name" :" keyword" ," $" :{" id" :" kwrd0080" }," $$" :[{" #name" :" text" ," _" :" coronary artery disease CMD" },{" #name" :" keyword" ," $" :{" id" :" kwrd0090" }," $$" :[{" #name" :" text" ," _" :" cardiometabolic disorders CVD" },{" #name" :" keyword" ," $" :{" id" :" kwrd0100" }," $$" :[{" #name" :" text" ," _" :" cardiovascular disease DIAGRAM" },{" #name" :" keyword" ," $" :{" id" :" kwrd0110" }," $$" :[{" #name" :" text" ," _" :" Diabetes Genetics Replication And Meta-analysis DBP" },{" #name" :" keyword" ," $" :{" id" :" kwrd0120" }," $$" :[{" #name" :" text" ," _" :" diastolic blood pressure GERA" },{" #name" :" keyword" ," $" :{" id" :" kwrd0130" }," $$" :[{" #name" :" text" ," _" :" Genetic Epidemiology Research on Adult Health and Aging cohort GIANT" },{" #name" :" keyword" ," $" :{" id" :" kwrd0140" }," $$" :[{" #name" :" text" ," _" :" Genetic Investigation of Anthropometric Traits consortium GLGC" },{" #name" :" keyword" ," $" :{" id" :" kwrd0150" }," $$" :[{" #name" :" text" ," _" :" Global Lipids Genetics Consortium GWAS" },{" #name" :" keyword" ," $" :{" id" :" kwrd0160" }," $$" :[{" #name" :" text" ," _" :" genome-wide association studies HbA1c" },{" #name" :" keyword" ," $" :{" id" :" kwrd0170" }," $$" :[{" #name" :" text" ," _" :" hemoglobin A1c HDL-C" },{" #name" :" keyword" ," $" :{" id" :" kwrd0180" }," $$" :[{" #name" :" text" ," _" :" high-density lipoprotein cholesterol LDL-C" },{" #name" :" keyword" ," $" :{" id" :" kwrd0190" }," $$" :[{" #name" :" text" ," _" :" low-density lipoprotein cholesterol NHANES" },{" #name" :" keyword" ," $" :{" id" :" kwrd0200" }," $$" :[{" #name" :" text" ," _" :" National Health and Nutrition Examination Survey PPFC" },{" #name" :" keyword" ," $" :{" id" :" kwrd0210" }," $$" :[{" #name" :" text" ," _" :" posterior probability of full colocalization SBP" },{" #name" :" keyword" ," $" :{" id" :" kwrd0220" }," $$" :[{" #name" :" text" ," _" :" systolic blood pressure T2D" },{" #name" :" keyword" ," $" :{" id" :" kwrd0230" }," $$" :[{" #name" :" text" ," _" :" type 2 diabetes TGs" },{" #name" :" keyword" ," $" :{" id" :" kwrd0240" }," $$" :[{" #name" :" text" ," _" :" triglycerides UK" },{" #name" :" keyword" ," $" :{" id" :" kwrd0250" }," $$" :[{" #name" :" text" ," _" :" United Kingdom WHR" },{" #name" :" keyword" ," $" :{" id" :" kwrd0260" }," $$" :[{" #name" :" text" ," _" :" waist-to-hip-ratio WHRadjBMI" },{" #name" :" keyword" ," $" :{" id" :" kwrd0270" }," $$" :[{" #name" :" text" ," _" :" waist-to-hip ratio adjusted for BMI |
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