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Amiri Khosroshahi R, Mirzababaei A, Setayesh L, Bagheri R, Heidari Seyedmahalleh M, Wong A, Suzuki K, Mirzaei K. Dietary Insulin Index (DII) and Dietary Insulin load (DIL) and Caveolin gene variant interaction on cardiometabolic risk factors among overweight and obese women: a cross-sectional study. Eur J Med Res 2024; 29:74. [PMID: 38268038 PMCID: PMC10807169 DOI: 10.1186/s40001-024-01638-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Accepted: 01/03/2024] [Indexed: 01/26/2024] Open
Abstract
BACKGROUND AND OBJECTIVE Studies have shown that Caveolin gene polymorphisms (CAV-1) are involved in chronic diseases, such as metabolic syndrome. Moreover, the dietary insulin index (DII) and dietary insulin load (DIL) have been shown to potentially elicit favorable effects on cardiovascular disease (CVD) risk. Therefore, this study sought to investigate the effect of DII DIL and CAV-1 interaction on CVD risk factors. METHODS This cross-sectional study consisted of 333 overweight and obese women aged 18-48 years. Dietary intakes, DII, and DIL were evaluated using the 147-item food frequency questionnaire (FFQ). Serum profiles were measured by standard protocols. The CAV-1 rs 3,807,992 and anthropometric data were measured by the PCR-RFLP method and bioelectrical impedance analysis (BIA), respectively. Participants were also divided into three groups based on DII, DIL score, and rs3807992 genotype. RESULTS This comparative cross-sectional study was conducted on 333 women classified as overweight or obese. Participants with A allele for the caveolin genotype and higher DII score showed significant interactions with high-density lipoprotein (HDL) (P for AA = 0.006 and P for AG = 0.019) and CRI-I (P for AA < 0.001 and P for AG = 0.024). In participants with AA genotype and greater DII score, interactions were observed in weight, systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol, CRI-II, fat-free mass (FFM), and skeletal muscle mass (SMM) (P < 0.079). Those with higher DIL scores and AA genotype had higher weight (P = 0.033), FFM (P = 0.022), and SMM (P = 0.024). In addition, DIL interactions for waist/hip ratio (WHR), waist circumference (WC), triglyceride (TG), CRI-I, and body fat mass (BFM) among individuals with AA genotype, while an HDL interaction was observed in individuals with AG and AA (P < 0.066). CONCLUSION The findings of the present study indicate that people who carry the caveolin rs3807992 (A) allele and have greater DII and DIL scores are at higher risk for several cardiovascular disease and metabolic syndrome biomarkers. These results highlight that diet, gene variants, and their interaction, should be considered in the risk evaluation of developing CVD.
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Affiliation(s)
- Reza Amiri Khosroshahi
- Department of Clinical Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Atieh Mirzababaei
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Leila Setayesh
- Department of Clinical Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran
| | - Reza Bagheri
- Department of Exercise Physiology, University of Isfahan, Isfahan, Iran
| | - Mohammad Heidari Seyedmahalleh
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Alexei Wong
- Department of Health and Human Performance, Marymount University, Arlington, USA
| | - Katsuhiko Suzuki
- Faculty of Sport Sciences, Waseda University, 2-579-15 Mikajima, Tokorozawa, 359-1192, Japan.
| | - Khadijeh Mirzaei
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, Iran.
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Suzuki K, Hatzikotoulas K, Southam L, Taylor HJ, Yin X, Lorenz KM, Mandla R, Huerta-Chagoya A, Rayner NW, Bocher O, Arruda ALDSV, Sonehara K, Namba S, Lee SSK, Preuss MH, Petty LE, Schroeder P, Vanderwerff B, Kals M, Bragg F, Lin K, Guo X, Zhang W, Yao J, Kim YJ, Graff M, Takeuchi F, Nano J, Lamri A, Nakatochi M, Moon S, Scott RA, Cook JP, Lee JJ, Pan I, Taliun D, Parra EJ, Chai JF, Bielak LF, Tabara Y, Hai Y, Thorleifsson G, Grarup N, Sofer T, Wuttke M, Sarnowski C, Gieger C, Nousome D, Trompet S, Kwak SH, Long J, Sun M, Tong L, Chen WM, Nongmaithem SS, Noordam R, Lim VJY, Tam CHT, Joo YY, Chen CH, Raffield LM, Prins BP, Nicolas A, Yanek LR, Chen G, Brody JA, Kabagambe E, An P, Xiang AH, Choi HS, Cade BE, Tan J, Broadaway KA, Williamson A, Kamali Z, Cui J, Adair LS, Adeyemo A, Aguilar-Salinas CA, Ahluwalia TS, Anand SS, Bertoni A, Bork-Jensen J, Brandslund I, Buchanan TA, Burant CF, Butterworth AS, Canouil M, Chan JCN, Chang LC, Chee ML, Chen J, Chen SH, Chen YT, Chen Z, Chuang LM, Cushman M, Danesh J, Das SK, de Silva HJ, Dedoussis G, Dimitrov L, Doumatey AP, Du S, Duan Q, Eckardt KU, Emery LS, Evans DS, Evans MK, Fischer K, Floyd JS, Ford I, Franco OH, Frayling TM, Freedman BI, Genter P, Gerstein HC, Giedraitis V, González-Villalpando C, González-Villalpando ME, Gordon-Larsen P, Gross M, Guare LA, Hackinger S, Han S, Hattersley AT, Herder C, Horikoshi M, Howard AG, Hsueh W, Huang M, Huang W, Hung YJ, Hwang MY, Hwu CM, Ichihara S, Ikram MA, Ingelsson M, Islam MT, Isono M, Jang HM, Jasmine F, Jiang G, Jonas JB, Jørgensen T, Kandeel FR, Kasturiratne A, Katsuya T, Kaur V, Kawaguchi T, Keaton JM, Kho AN, Khor CC, Kibriya MG, Kim DH, Kronenberg F, Kuusisto J, Läll K, Lange LA, Lee KM, Lee MS, Lee NR, Leong A, Li L, Li Y, Li-Gao R, Lithgart S, Lindgren CM, Linneberg A, Liu CT, Liu J, Locke AE, Louie T, Luan J, Luk AO, Luo X, Lv J, Lynch JA, Lyssenko V, Maeda S, Mamakou V, Mansuri SR, Matsuda K, Meitinger T, Metspalu A, Mo H, Morris AD, Nadler JL, Nalls MA, Nayak U, Ntalla I, Okada Y, Orozco L, Patel SR, Patil S, Pei P, Pereira MA, Peters A, Pirie FJ, Polikowsky HG, Porneala B, Prasad G, Rasmussen-Torvik LJ, Reiner AP, Roden M, Rohde R, Roll K, Sabanayagam C, Sandow K, Sankareswaran A, Sattar N, Schönherr S, Shahriar M, Shen B, Shi J, Shin DM, Shojima N, Smith JA, So WY, Stančáková A, Steinthorsdottir V, Stilp AM, Strauch K, Taylor KD, Thorand B, Thorsteinsdottir U, Tomlinson B, Tran TC, Tsai FJ, Tuomilehto J, Tusie-Luna T, Udler MS, Valladares-Salgado A, van Dam RM, van Klinken JB, Varma R, Wacher-Rodarte N, Wheeler E, Wickremasinghe AR, van Dijk KW, Witte DR, Yajnik CS, Yamamoto K, Yamamoto K, Yoon K, Yu C, Yuan JM, Yusuf S, Zawistowski M, Zhang L, Zheng W, Raffel LJ, Igase M, Ipp E, Redline S, Cho YS, Lind L, Province MA, Fornage M, Hanis CL, Ingelsson E, Zonderman AB, Psaty BM, Wang YX, Rotimi CN, Becker DM, Matsuda F, Liu Y, Yokota M, Kardia SLR, Peyser PA, Pankow JS, Engert JC, Bonnefond A, Froguel P, Wilson JG, Sheu WHH, Wu JY, Hayes MG, Ma RCW, Wong TY, Mook-Kanamori DO, Tuomi T, Chandak GR, Collins FS, Bharadwaj D, Paré G, Sale MM, Ahsan H, Motala AA, Shu XO, Park KS, Jukema JW, Cruz M, Chen YDI, Rich SS, McKean-Cowdin R, Grallert H, Cheng CY, Ghanbari M, Tai ES, Dupuis J, Kato N, Laakso M, Köttgen A, Koh WP, Bowden DW, Palmer CNA, Kooner JS, Kooperberg C, Liu S, North KE, Saleheen D, Hansen T, Pedersen O, Wareham NJ, Lee J, Kim BJ, Millwood IY, Walters RG, Stefansson K, Goodarzi MO, Mohlke KL, Langenberg C, Haiman CA, Loos RJF, Florez JC, Rader DJ, Ritchie MD, Zöllner S, Mägi R, Denny JC, Yamauchi T, Kadowaki T, Chambers JC, Ng MCY, Sim X, Below JE, Tsao PS, Chang KM, McCarthy MI, Meigs JB, Mahajan A, Spracklen CN, Mercader JM, Boehnke M, Rotter JI, Vujkovic M, Voight BF, Morris AP, Zeggini E. Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.31.23287839. [PMID: 37034649 PMCID: PMC10081410 DOI: 10.1101/2023.03.31.23287839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/30/2023]
Abstract
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P<5×10-8) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care.
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Affiliation(s)
- Ken Suzuki
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Konstantinos Hatzikotoulas
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Lorraine Southam
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Henry J. Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Xianyong Yin
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing City, China
| | - Kim M. Lorenz
- Corporal Michael J Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ravi Mandla
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Alicia Huerta-Chagoya
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Consejo Nacional de Ciencia y Tecnología (CONACYT), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Nigel W. Rayner
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Ozvan Bocher
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Ana Luiza de S. V. Arruda
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Kyuto Sonehara
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Shinichi Namba
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Simon S. K. Lee
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael H. Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lauren E. Petty
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Philip Schroeder
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Brett Vanderwerff
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Mart Kals
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Fiona Bragg
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hosptial, London NorthWest Healthcare NHS Trust, Middlesex, UK
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Young Jin Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, South Korea
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Jana Nano
- Institute of Epidemiology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Germany
| | - Amel Lamri
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
| | - Masahiro Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Sanghoon Moon
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, South Korea
| | - Robert A. Scott
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - James P. Cook
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Jung-Jin Lee
- Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Ian Pan
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
| | - Daniel Taliun
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Esteban J. Parra
- Department of Anthropology, University of Toronto at Mississsauga, Mississauga, ON, Canada
| | - Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yang Hai
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | | | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tamar Sofer
- Department of Biostatistics, Harvard University, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medicine, Harvard University, Boston, MA, USA
| | - Matthias Wuttke
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Chloé Sarnowski
- Department of Epidemiology, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Darryl Nousome
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Soo-Heon Kwak
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Meng Sun
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Lin Tong
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Wei-Min Chen
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Suraj S. Nongmaithem
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Raymond Noordam
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Victor J. Y. Lim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Claudia H. T. Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Yoonjung Yoonie Joo
- Institute of Data Science, Korea University, Seoul, South Korea
- Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Health and Biomedical Informatics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Chien-Hsiun Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Bram Peter Prins
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Aude Nicolas
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Lisa R. Yanek
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jennifer A. Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Edmond Kabagambe
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Division of Academics, Ochsner Health, New Orleans, LA, USA
| | - Ping An
- Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA
| | - Anny H. Xiang
- Department of Research and Evaluation, Division of Biostatistics Research, Kaiser Permanente of Southern California, Pasadena, CA, USA
| | - Hyeok Sun Choi
- Department of Biomedical Science, Hallym University, Chuncheon, South Korea
| | - Brian E. Cade
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Jingyi Tan
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - K. Alaine Broadaway
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Alice Williamson
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Metabolic Research Laboratories, Wellcome Trust-Medical Research Council Institute of Metabolic Science, Department of Clinical Biochemistry, University of Cambridge, Cambridge, UK
| | - Zoha Kamali
- Department of Epidemiology, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Jinrui Cui
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Linda S. Adair
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Carlos A. Aguilar-Salinas
- Unidad de Investigación en Enfermedades Metabólicas and Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Tarunveer S. Ahluwalia
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- The Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Sonia S. Anand
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Alain Bertoni
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jette Bork-Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ivan Brandslund
- Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
- Department of Clinical Biochemistry, Vejle Hospital, Vejle, Denmark
| | - Thomas A. Buchanan
- Department of Medicine, Division of Endocrinology and Diabetes, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Charles F. Burant
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Adam S. Butterworth
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, Addenbrooke’s Hospital, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Hinxton, UK
- National Institute for Health and Care Research (NIHR) Blood and Transplant Unit (BTRU) in Donor Health and Behaviour, Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Mickaël Canouil
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, Lille University Hospital, Lille, France
- University of Lille, Lille, France
| | - Juliana C. N. Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Li-Ching Chang
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Miao-Li Chee
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Ji Chen
- Exeter Centre of Excellence in Diabetes (ExCEeD), Exeter Medical School, University of Exeter, Exeter, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Shyh-Huei Chen
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Yuan-Tsong Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Lee-Ming Chuang
- Division of Endocrinology and Metabolism, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
- Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
| | - Mary Cushman
- Department of Medicine, University of Vermont, Colchester, VT, USA
| | - John Danesh
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
- British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, Addenbrooke’s Hospital, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Hinxton, UK
- National Institute for Health and Care Research (NIHR) Blood and Transplant Unit (BTRU) in Donor Health and Behaviour, Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Swapan K. Das
- Section on Endocrinology and Metabolism, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - H. Janaka de Silva
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
| | - George Dedoussis
- Department of Nutrition and Dietetics, Harokopio University of Athens, Athens, Greece
| | - Latchezar Dimitrov
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Ayo P. Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Shufa Du
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Qing Duan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kai-Uwe Eckardt
- Department of Nephrology and Medical Intensive Care Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany
- Department of Nephrology and Hypertension, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Leslie S. Emery
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Daniel S. Evans
- California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - Michele K. Evans
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Krista Fischer
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
| | - James S. Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Ian Ford
- Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK
| | - Oscar H. Franco
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Timothy M. Frayling
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Barry I. Freedman
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Pauline Genter
- Department of Medicine, Division of Endocrinology and Metabolism, Lundquist Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Hertzel C. Gerstein
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Vilmantas Giedraitis
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Clicerio González-Villalpando
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Publica, Mexico City, Mexico
| | - Maria Elena González-Villalpando
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Publica, Mexico City, Mexico
| | - Penny Gordon-Larsen
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Myron Gross
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Lindsay A. Guare
- Genomics and Computational Biology Graduate Group, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sophie Hackinger
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Sohee Han
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, South Korea
| | | | - Christian Herder
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Dusseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Annie-Green Howard
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Willa Hsueh
- Department of Internal Medicine, Diabetes and Metabolism Research Center, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Mengna Huang
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
- Center for Global Cardiometabolic Health, Brown University, Providence, RI, USA
| | - Wei Huang
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai (CHGC) and Shanghai Institute for Biomedical and Pharmaceutical Technologies (SIBPT), Shanghai, China
| | - Yi-Jen Hung
- Division of Endocrine and Metabolism, Tri-Service General Hospital Songshan Branch, Taipei, Taiwan
- School of Medicine, National Defense Medical Center, Taipei, Taiwan
| | - Mi Yeong Hwang
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Chii-Min Hwu
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Sahoko Ichihara
- Department of Environmental and Preventive Medicine, Jichi Medical University School of Medicine, Shimotsuke, Japan
| | - Mohammad Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Martin Ingelsson
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | | | - Masato Isono
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Hye-Mi Jang
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Farzana Jasmine
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Guozhi Jiang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Jost B. Jonas
- Institute of Molecular and Clinical Ophthalmology Basel, Basel, Switzerland
| | - Torben Jørgensen
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Faculty of Medicine, Aalborg University, Aalborg, Denmark
| | - Fouad R. Kandeel
- Department of Clinical Diabetes, Endocrinology and Metabolism, Department of Translational Research and Cellular Therapeutics, City of Hope, Duarte, CA, USA
| | | | - Tomohiro Katsuya
- Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Osaka, Japan
- Department of Geriatric and General Medicine, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Varinderpal Kaur
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Takahisa Kawaguchi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Jacob M. Keaton
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Abel N. Kho
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Health Information Partnerships, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Chiea-Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Muhammad G. Kibriya
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Duk-Hwan Kim
- Department of Molecular Cell Biology, Sungkyunkwan University School of Medicine, Suwon, South Korea
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Kristi Läll
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Leslie A. Lange
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - Kyung Min Lee
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Myung-Shik Lee
- Severance Biomedical Science Institute and Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea
- Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Nanette R. Lee
- USC-Office of Population Studies Foundation Inc., University of San Carlos, Cebu City, Philippines
| | - Aaron Leong
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Yun Li
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Symen Lithgart
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Cecilia M. Lindgren
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Big Data Institute, Li Ka Shing Centre For Health Information and Discovery, University of Oxford, Oxford, UK
| | - Allan Linneberg
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Adam E. Locke
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
- Department of Medicine, Division of Genomics and Bioinformatics, Washington University School of Medicine, St Louis, MO, USA
- Present address: Regeneron Genetics Center, Tarrytown, NY, USA
| | - Tin Louie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Jian’an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Andrea O. Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Xi Luo
- Department of Biostatistics and Data Science, The University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Julie A. Lynch
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Valeriya Lyssenko
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Malmö, Sweden
- Department of Clinical Science, Center for Diabetes Research, University of Bergen, Bergen, Norway
| | - Shiro Maeda
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Okinawa, Japan
| | - Vasiliki Mamakou
- Dromokaiteio Psychiatric Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Sohail Rafik Mansuri
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Koichi Matsuda
- Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technical University Munich, Munich, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Andres Metspalu
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Huan Mo
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Andrew D. Morris
- The Usher Institute to the Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Jerry L. Nadler
- Department of Medicine and Pharmacology, New York Medical College, Valhalla, NY, USA
| | - Michael A. Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Data Tecnica International LLC, Glen Echo, MD, USA
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD, USA
| | - Uma Nayak
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Ioanna Ntalla
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
| | - Lorena Orozco
- Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Sanjay R. Patel
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Snehal Patil
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Mark A Pereira
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig Maximilians Universität München, Munich, Germany
| | - Fraser J. Pirie
- Department of Diabetes and Endocrinology, Nelson R Mandela School of Medicine, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Hannah G. Polikowsky
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bianca Porneala
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Gauri Prasad
- Academy of Scientific and Innovative Research, CSIR-Human Resource Development Campus, Ghaziabad, India
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India
| | - Laura J. Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | - Michael Roden
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Dusseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Rebecca Rohde
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Katheryn Roll
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Kevin Sandow
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Alagu Sankareswaran
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Sebastian Schönherr
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Mohammad Shahriar
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Botong Shen
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Jinxiu Shi
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai (CHGC) and Shanghai Institute for Biomedical and Pharmaceutical Technologies (SIBPT), Shanghai, China
| | - Dong Mun Shin
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Nobuhiro Shojima
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Wing Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Alena Stančáková
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | | | - Adrienne M. Stilp
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
- Chair of Genetic Epidemiology, Institute of Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, Ludwig Maximilians Universität München, Munich, Germany
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Unnur Thorsteinsdottir
- deCODE Genetics, Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Brian Tomlinson
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Faculty of Medicine, Macau University of Science and Technology, Macau, China
| | - Tam C. Tran
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Fuu-Jen Tsai
- Department of Medical Genetics and Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Jaakko Tuomilehto
- Population Health Unit, Finnish Institute for Health and Welfare, Helsinki, Finland, Finnish Institute for Health and Welfare, Helsinki, Finland
- National School of Public Health, Madrid, Spain
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Teresa Tusie-Luna
- Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
- Departamento de Medicina Genómica y Toxiología Ambiental, Instituto de Investigaciones Biomédicas, UNAM, Mexico City, Mexico
| | - Miriam S. Udler
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Adan Valladares-Salgado
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Rob M. van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Jan B. van Klinken
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, The Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Clinical Chemistry, Laboratory of Genetic Metabolic Disease, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Rohit Varma
- Southern California Eye Institute, CHA Hollywood Presbyterian Hospital, Los Angeles, CA, USA
| | - Niels Wacher-Rodarte
- Unidad de Investigación Médica en Epidemiologia Clinica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Eleanor Wheeler
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | | | - Ko Willems van Dijk
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, The Netherlands
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, The Netherlands
| | - Daniel R. Witte
- Department of Public Health, Aarhus University, Aarhus, Denmark
- Danish Diabetes Academy, Odense, Denmark
| | - Chittaranjan S. Yajnik
- Diabetology Research Centre, King Edward Memorial Hospital and Research Centre, Pune, India
| | - Ken Yamamoto
- Department of Medical Biochemistry, Kurume University School of Medicine, Kurume, Japan
| | - Kenichi Yamamoto
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Department of Pediatrics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Kyungheon Yoon
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Salim Yusuf
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Matthew Zawistowski
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Liang Zhang
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | | | | | | | | | | | | | | | - Leslie J Raffel
- Department of Pediatrics, Division of Genetic and Genomic Medicine, UCI Irvine School of Medicine, Irvine, CA, USA
| | - Michiya Igase
- Department of Anti-Aging Medicine, Ehime University Graduate School of Medicine, Ehime, Japan
| | - Eli Ipp
- Department of Medicine, Division of Endocrinology and Metabolism, Lundquist Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Yoon Shin Cho
- Department of Biomedical Science, Hallym University, Chuncheon, South Korea
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Michael A. Province
- Division of Statistical Genomics, Washington University School of Medicine, St. Louis, MO, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, The University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Craig L. Hanis
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, US
| | - Erik Ingelsson
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Alan B. Zonderman
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Ya-Xing Wang
- Beijing Institute of Ophthalmology, Ophthalmology and Visual Sciences Key Laboratory, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Charles N. Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Diane M. Becker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Medicine, Division of Cardiology, Duke University School of Medicine, Durham, NC, USA
| | | | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Patricia A. Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - James S. Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - James C. Engert
- Department of Medicine, McGill University, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Amélie Bonnefond
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, Lille University Hospital, Lille, France
- University of Lille, Lille, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Philippe Froguel
- Inserm U1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, Lille University Hospital, Lille, France
- University of Lille, Lille, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - James G. Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Wayne H. H. Sheu
- School of Medicine, National Defense Medical Center, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Division of Endocrinology and Metabolism, Department of Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Jer-Yuarn Wu
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - M. Geoffrey Hayes
- Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Anthropology, Northwestern University, Evanston, IL, USA
| | - Ronald C. W. Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Chinese University of Hong Kong-Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Dennis O. Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Tiinamaija Tuomi
- Department of Endocrinology, Helsinki University Hospital, Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
- Lund University Diabetes Centre, Malmö, Sweden
| | - Giriraj R. Chandak
- Genomic Research on Complex Diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Francis S. Collins
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Dwaipayan Bharadwaj
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, India
| | - Guillaume Paré
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
| | - Michèle M. Sale
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
- Deceased
| | - Habibul Ahsan
- Institute for Population and Precision Health (IPPH), Biological Sciences Division, The University of Chicago, Chicago, IL, USA
| | - Ayesha A. Motala
- Department of Diabetes and Endocrinology, Nelson R Mandela School of Medicine, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Institute for Medicine and Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kyong-Soo Park
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, South Korea
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
- Netherlands Heart Institute, Utrecht, The Netherlands
| | - Miguel Cruz
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Roberta McKean-Cowdin
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Harald Grallert
- Institute of Epidemiology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - E-Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Josee Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Department of Data Driven Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Woon-Puay Koh
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore, Singapore
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Donald W. Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Colin N. A. Palmer
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, University of Dundee, Dundee, UK
| | - Jaspal S. Kooner
- Department of Cardiology, Ealing Hosptial, London NorthWest Healthcare NHS Trust, Middlesex, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | | | - Simin Liu
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
- Center for Global Cardiometabolic Health, Brown University, Providence, RI, USA
- Department of Medicine, Brown University Alpert School of Medicine, Providence, RI, USA
| | - Kari E. North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Danish Saleheen
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
- Department of Cardiology, Columbia University Irving Medical Center, New York, NY, USA
- Center for Non-Communicable Diseases, Karachi, Pakistan
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nicholas J. Wareham
- The Usher Institute to the Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Juyoung Lee
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Bong-Jo Kim
- Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea
| | - Iona Y. Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Robin G. Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Kari Stefansson
- deCODE Genetics, Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Mark O. Goodarzi
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Karen L. Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Computational Medicine, Berlin Institute of Health at Charité Universitätsmedizin, Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Christopher A. Haiman
- Department of Preventive Medicine, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Ruth J. F. Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Mindich Child Health and Development Institute, Ichan School of Medicine at Mount Sinai, New York, NY, USA
| | - Jose C. Florez
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Daniel J. Rader
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Translational Medicine and Therapeutics, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Marylyn D. Ritchie
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Center for Precision Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sebastian Zöllner
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Joshua C. Denny
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- All of Us Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Toshimasa Yamauchi
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Takashi Kadowaki
- Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Toranomon Hospital, Tokyo, Japan
| | - John C. Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hosptial, London NorthWest Healthcare NHS Trust, Middlesex, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Maggie C. Y. Ng
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Jennifer E. Below
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Philip S. Tsao
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Kyong-Mi Chang
- Corporal Michael J Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Mark I. McCarthy
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hosptial, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Present address: Genentech, South San Francisco, CA, USA
| | - James B. Meigs
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Present address: Genentech, South San Francisco, CA, USA
| | - Cassandra N. Spracklen
- Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA, USA
| | - Josep M. Mercader
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Marijana Vujkovic
- Corporal Michael J Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Division of Epidemiology, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Benjamin F. Voight
- Corporal Michael J Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Andrew P. Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- TUM School of Medicine, Technical University of Munich and Klinikum Rechts der Isar, Munich, Germany
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3
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Liang J, Wang H, Cade BE, Kurniansyah N, He KY, Lee J, Sands SA, A. Brody J, Chen H, Gottlieb DJ, Evans DS, Guo X, Gharib SA, Hale L, Hillman DR, Lutsey PL, Mukherjee S, Ochs-Balcom HM, Palmer LJ, Purcell S, Saxena R, Patel SR, Stone KL, Tranah GJ, Boerwinkle E, Lin X, Liu Y, Psaty BM, Vasan RS, Manichaikul A, Rich SS, Rotter JI, Sofer T, Redline S, Zhu X. Targeted Genome Sequencing Identifies Multiple Rare Variants in Caveolin-1 Associated with Obstructive Sleep Apnea. Am J Respir Crit Care Med 2022; 206:1271-1280. [PMID: 35822943 PMCID: PMC9746833 DOI: 10.1164/rccm.202203-0618oc] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 07/06/2022] [Indexed: 01/04/2023] Open
Abstract
Rationale: Obstructive sleep apnea (OSA) is a common disorder associated with increased risk for cardiovascular disease, diabetes, and premature mortality. There is strong clinical and epidemiologic evidence supporting the importance of genetic factors influencing OSA but limited data implicating specific genes. Objectives: To search for rare variants contributing to OSA severity. Methods: Leveraging high-depth genomic sequencing data from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and imputed genotype data from multiple population-based studies, we performed linkage analysis in the CFS (Cleveland Family Study), followed by multistage gene-based association analyses in independent cohorts for apnea-hypopnea index (AHI) in a total of 7,708 individuals of European ancestry. Measurements and Main Results: Linkage analysis in the CFS identified a suggestive linkage peak on chromosome 7q31 (LOD = 2.31). Gene-based analysis identified 21 noncoding rare variants in CAV1 (Caveolin-1) associated with lower AHI after accounting for multiple comparisons (P = 7.4 × 10-8). These noncoding variants together significantly contributed to the linkage evidence (P < 10-3). Follow-up analysis revealed significant associations between these variants and increased CAV1 expression, and increased CAV1 expression in peripheral monocytes was associated with lower AHI (P = 0.024) and higher minimum overnight oxygen saturation (P = 0.007). Conclusions: Rare variants in CAV1, a membrane-scaffolding protein essential in multiple cellular and metabolic functions, are associated with higher CAV1 gene expression and lower OSA severity, suggesting a novel target for modulating OSA severity.
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Affiliation(s)
- Jingjing Liang
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, Ohio
| | - Heming Wang
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, and
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
| | - Brian E. Cade
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, and
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
| | - Nuzulul Kurniansyah
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Karen Y. He
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, Ohio
| | - Jiwon Lee
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Scott A. Sands
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, and
| | | | - Han Chen
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, and
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas
| | - Daniel J. Gottlieb
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, and
- VA Boston Healthcare System, Boston, Massachusetts
| | - Daniel S. Evans
- California Pacific Medical Center Research Institute, San Francisco, California
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences and
- Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California
| | - Sina A. Gharib
- Computational Medicine Core, Center for Lung Biology, University of Washington Medicine Sleep Center, Department of Medicine
| | - Lauren Hale
- Family, Population, and Preventive Medicine, Program in Public Health, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York
| | - David R. Hillman
- Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia
| | - Pamela L. Lutsey
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | - Sutapa Mukherjee
- Sleep Health Service, Respiratory and Sleep Service, Southern Adelaide Local Health Network, Adelaide, South Australia, Australia
- Adelaide Institute for Sleep Health, Flinders Health and Medical Research Institute, College Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - Heather M. Ochs-Balcom
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York
| | - Lyle J. Palmer
- School of Public Health, University of Adelaide, Adelaide, South Australia, Australia
| | - Shaun Purcell
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, and
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
| | - Richa Saxena
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, and
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Center for Genomic Medicine and
- Department of Anesthesia, Pain and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Sanjay R. Patel
- Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Katie L. Stone
- California Pacific Medical Center Research Institute, San Francisco, California
| | - Gregory J. Tranah
- California Pacific Medical Center Research Institute, San Francisco, California
| | - Eric Boerwinkle
- Cardiovascular Health Research Unit, Department of Medicine
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas
| | - Xihong Lin
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts
| | - Yongmei Liu
- Department of Medicine, Division of Cardiology, Duke Molecular Physiology Institute, Duke University Medical Center, Durham, North Carolina
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine
- Department of Epidemiology, and
- Department of Health Services and Population Health, University of Washington, Seattle, Washington
| | - Ramachandran S. Vasan
- Framingham Heart Study, Framingham, Massachusetts
- Section of Preventive Medicine and Epidemiology and
- Section of Cardiology, Department of Medicine, School of Medicine, and
- Department of Epidemiology, School of Public Health, Boston University, Boston, Massachusetts; and
| | - Ani Manichaikul
- Center for Public Health Genomics and
- Biostatistics Section, Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia
| | | | - Jerome I. Rotter
- California Pacific Medical Center Research Institute, San Francisco, California
- Institute for Translational Genomics and Population Sciences and
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, and
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, and
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, Ohio
| | - TOPMed Sleep Working Group
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, Ohio
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Sleep Medicine, Harvard Medical School, and
- Department of Biostatistics, T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Cardiovascular Health Research Unit, Department of Medicine
- Computational Medicine Core, Center for Lung Biology, University of Washington Medicine Sleep Center, Department of Medicine
- Department of Epidemiology, and
- Department of Health Services and Population Health, University of Washington, Seattle, Washington
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, and
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas
- VA Boston Healthcare System, Boston, Massachusetts
- California Pacific Medical Center Research Institute, San Francisco, California
- Institute for Translational Genomics and Population Sciences and
- Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California
- Family, Population, and Preventive Medicine, Program in Public Health, Renaissance School of Medicine, Stony Brook University, Stony Brook, New York
- Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota
- Sleep Health Service, Respiratory and Sleep Service, Southern Adelaide Local Health Network, Adelaide, South Australia, Australia
- Adelaide Institute for Sleep Health, Flinders Health and Medical Research Institute, College Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, New York
- School of Public Health, University of Adelaide, Adelaide, South Australia, Australia
- Center for Genomic Medicine and
- Department of Anesthesia, Pain and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas
- Department of Medicine, Division of Cardiology, Duke Molecular Physiology Institute, Duke University Medical Center, Durham, North Carolina
- Framingham Heart Study, Framingham, Massachusetts
- Section of Preventive Medicine and Epidemiology and
- Section of Cardiology, Department of Medicine, School of Medicine, and
- Department of Epidemiology, School of Public Health, Boston University, Boston, Massachusetts; and
- Center for Public Health Genomics and
- Biostatistics Section, Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia
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4
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Loh M, Zhang W, Ng HK, Schmid K, Lamri A, Tong L, Ahmad M, Lee JJ, Ng MCY, Petty LE, Spracklen CN, Takeuchi F, Islam MT, Jasmine F, Kasturiratne A, Kibriya M, Mohlke KL, Paré G, Prasad G, Shahriar M, Chee ML, de Silva HJ, Engert JC, Gerstein HC, Mani KR, Sabanayagam C, Vujkovic M, Wickremasinghe AR, Wong TY, Yajnik CS, Yusuf S, Ahsan H, Bharadwaj D, Anand SS, Below JE, Boehnke M, Bowden DW, Chandak GR, Cheng CY, Kato N, Mahajan A, Sim X, McCarthy MI, Morris AP, Kooner JS, Saleheen D, Chambers JC. Identification of genetic effects underlying type 2 diabetes in South Asian and European populations. Commun Biol 2022; 5:329. [PMID: 35393509 PMCID: PMC8991226 DOI: 10.1038/s42003-022-03248-5] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Accepted: 03/08/2022] [Indexed: 02/08/2023] Open
Abstract
South Asians are at high risk of developing type 2 diabetes (T2D). We carried out a genome-wide association meta-analysis with South Asian T2D cases (n = 16,677) and controls (n = 33,856), followed by combined analyses with Europeans (neff = 231,420). We identify 21 novel genetic loci for significant association with T2D (P = 4.7 × 10-8 to 5.2 × 10-12), to the best of our knowledge at the point of analysis. The loci are enriched for regulatory features, including DNA methylation and gene expression in relevant tissues, and highlight CHMP4B, PDHB, LRIG1 and other genes linked to adiposity and glucose metabolism. A polygenic risk score based on South Asian-derived summary statistics shows ~4-fold higher risk for T2D between the top and bottom quartile. Our results provide further insights into the genetic mechanisms underlying T2D, and highlight the opportunities for discovery from joint analysis of data from across ancestral populations.
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Affiliation(s)
- Marie Loh
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Middlesex, UB1 3HW, UK
| | - Hong Kiat Ng
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
| | - Katharina Schmid
- Institute of Computational Biology, Deutsches Forschungszentrum für Gesundheit und Umwelt, Helmholtz Zentrum München, 85764, Neuherberg, Germany
- Department of Informatics, Technical University of Munich, 85748, Garching bei München, Neuherberg, Germany
| | - Amel Lamri
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
| | - Lin Tong
- The University of Chicago, Biological Sciences Division, Public Health Sciences, 5841 South Maryland Avenue, MC2000, Chicago, IL, 60637, USA
| | - Meraj Ahmad
- Genomic Research on Complex diseases, CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Jung-Jin Lee
- Translational Medicine and Human Genetics, Department of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Medicine, Mayo Hospital, Lahore, Pakistan
| | - Maggie C Y Ng
- Center for Genomics and Personalized Medicine Research, Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, 37215, USA
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Lauren E Petty
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Cassandra N Spracklen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst, MA, 01003, USA
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Md Tariqul Islam
- U Chicago Research Bangladesh, House#4, Road#2b, Sector#4, Uttara, Dhaka, 1230, Bangladesh
| | - Farzana Jasmine
- The University of Chicago, Biological Sciences Division, Public Health Sciences, 5841 South Maryland Avenue, MC2000, Chicago, IL, 60637, USA
| | - Anuradhani Kasturiratne
- Department of Public Health, Faculty of Medicine, University of Kelaniya, Kelaniya, Sri Lanka
| | - Muhammad Kibriya
- The University of Chicago, Biological Sciences Division, Public Health Sciences, 5841 South Maryland Avenue, MC2000, Chicago, IL, 60637, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Guillaume Paré
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
| | - Gauri Prasad
- Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, 110020, India
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, 110067, India
| | - Mohammad Shahriar
- The University of Chicago, Biological Sciences Division, Public Health Sciences, 5841 South Maryland Avenue, MC2000, Chicago, IL, 60637, USA
| | - Miao Ling Chee
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - H Janaka de Silva
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Kelaniya, Sri Lanka
| | - James C Engert
- Department of Medicine, McGill University, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Hertzel C Gerstein
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - K Radha Mani
- Genomic Research on Complex diseases, CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
| | - Marijana Vujkovic
- Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
| | - Ananda R Wickremasinghe
- Department of Public Health, Faculty of Medicine, University of Kelaniya, Kelaniya, Sri Lanka
| | - Tien Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | | | - Salim Yusuf
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Habibul Ahsan
- The University of Chicago, Biological Sciences Division, Public Health Sciences, 5841 South Maryland Avenue, MC2000, Chicago, IL, 60637, USA
| | - Dwaipayan Bharadwaj
- Academy of Scientific and Innovative Research, CSIR-Institute of Genomics and Integrative Biology Campus, New Delhi, 110020, India
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi, 110067, India
| | - Sonia S Anand
- Department of Medicine, McMaster University, Hamilton, ON, Canada
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, 48109, USA
| | - Donald W Bowden
- Department of Medicine, Mayo Hospital, Lahore, Pakistan
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, 37215, USA
| | - Giriraj R Chandak
- Genomic Research on Complex diseases, CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India
- JSS Academy of Health Education of Research, Mysuru, India
- Science and Engineering Research Board, Department of Science and Technology, Ministry of Science and technology, Government of India, New Delhi, India
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Anubha Mahajan
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Mark I McCarthy
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hosptial, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, UK
| | - Andrew P Morris
- Department of Biostatistics, University of Liverpool, Liverpool, L69 3GL, UK
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Middlesex, UB1 3HW, UK.
- Imperial College Healthcare NHS Trust, Imperial College London, London, W12 0HS, UK.
- MRC-PHE Centre for Enviroment and Health, Imperial College London, London, W2 1PG, UK.
- National Heart and Lung Institute, Imperial College London, London, W12 0NN, UK.
| | - Danish Saleheen
- Center for Non-Communicable Diseases, Karachi, Pakistan.
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA.
- Department of Cardiology, Columbia University Irving Medical Center, New York, NY, 10032, USA.
| | - John C Chambers
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore.
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK.
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Middlesex, UB1 3HW, UK.
- Imperial College Healthcare NHS Trust, Imperial College London, London, W12 0HS, UK.
- MRC-PHE Centre for Enviroment and Health, Imperial College London, London, W2 1PG, UK.
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5
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Abstract
Diabetes mellitus is a major risk factor for coronary heart disease (CHD). The major form of diabetes mellitus is type 2 diabetes mellitus (T2D), which is thus largely responsible for the CHD association in the general population. Recent years have seen major advances in the genetics of T2D, principally through ever-increasing large-scale genome-wide association studies. This article addresses the question of whether this expanding knowledge of the genomics of T2D provides insight into the etiologic relationship between T2D and CHD. We will investigate this relationship by reviewing the evidence for shared genetic loci between T2D and CHD; by examining the formal testing of this interaction (Mendelian randomization studies assessing whether T2D is causal for CHD); and then turn to the implications of this genetic relationship for therapies for CHD, for therapies for T2D, and for therapies that affect both. In conclusion, the growing knowledge of the genetic relationship between T2D and CHD is beginning to provide the promise for improved prevention and treatment of both disorders.
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Affiliation(s)
- Mark O. Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
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6
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Goodarzi MO, Palmer ND, Cui J, Guo X, Chen YDI, Taylor KD, Raffel LJ, Wagenknecht LE, Buchanan TA, Hsueh WA, Rotter JI. Classification of Type 2 Diabetes Genetic Variants and a Novel Genetic Risk Score Association With Insulin Clearance. J Clin Endocrinol Metab 2020; 105:dgz198. [PMID: 31714576 PMCID: PMC7059988 DOI: 10.1210/clinem/dgz198] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 11/11/2019] [Indexed: 12/16/2022]
Abstract
CONTEXT Genome-wide association studies have identified more than 450 single nucleotide polymorphisms (SNPs) for type 2 diabetes (T2D). OBJECTIVE To facilitate use of these SNPs in future genetic risk score (GRS)-based analyses, we aimed to classify the SNPs based on physiology. We also sought to validate GRS associations with insulin-related traits in deeply phenotyped Mexican Americans. DESIGN, SETTING, AND PARTICIPANTS A total of 457 T2D SNPs from the literature were assigned physiologic function based on association studies and cluster analyses. All SNPs (All-GRS), beta-cell (BC-GRS), insulin resistance (IR-GRS), lipodystrophy (Lipo-GRS), and body mass index plus lipids (B + L-GRS) were evaluated for association with diabetes and indices of insulin secretion (from oral glucose tolerance test), insulin sensitivity and insulin clearance (from euglycemic clamp), and adiposity and lipid markers in 1587 Mexican Americans. RESULTS Of the 457 SNPs, 52 were classified as BC, 30 as IR, 12 as Lipo, 12 as B + L, whereas physiologic function of 351 was undefined. All-GRS was strongly associated with T2D. Among nondiabetic Mexican Americans, BC-GRS was associated with reduced insulinogenic index, IR-GRS was associated with reduced insulin sensitivity, and Lipo-GRS was associated with reduced adiposity. B + L-GRS was associated with increased insulin clearance. The latter did not replicate in an independent cohort wherein insulin clearance was assessed by a different method. CONCLUSIONS Supporting their utility, BC-GRS, IR-GRS, and Lipo-GRS, based on SNPs discovered largely in Europeans, exhibited expected associations in Mexican Americans. The novel association of B + L-GRS with insulin clearance suggests that impaired ability to reduce insulin clearance in compensation for IR may play a role in the pathogenesis of T2D. Whether this applies to other ethnic groups remains to be determined.
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Affiliation(s)
- Mark O Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, US
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, US
| | - Jinrui Cui
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, US
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California, US
| | - Yii-Der I Chen
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California, US
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California, US
| | - Leslie J Raffel
- Division of Genetic and Genomic Medicine, Department of Pediatrics, University of California, Irvine, US
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, US
| | - Thomas A Buchanan
- Department of Physiology and Biophysics and Department of Medicine, Keck School of Medicine of USC, Los Angeles, California, US
| | - Willa A Hsueh
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Wexner Medical Center, The Ohio State University, Columbus, US
| | - Jerome I Rotter
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, US
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7
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Treesaranuwattana T, Wong KYH, Brooks DL, Tay CS, Williams GH, Williams JS, Pojoga LH. Lysine-Specific Demethylase-1 Deficiency Increases Agonist Signaling Via the Mineralocorticoid Receptor. Hypertension 2020; 75:1045-1053. [PMID: 32160100 DOI: 10.1161/hypertensionaha.119.13821] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
LSD1 (lysine-specific demethylase-1) is an epigenetic regulator of gene transcription. LSD1 risk allele in humans and LSD1 deficiency (LSD1+/-) in mice confer increasing salt-sensitivity of blood pressure with age, which evolves into salt-sensitive hypertension in older individuals. However, the mechanism underlying the relationship between LSD1 and salt-sensitivity of blood pressure remains elusive. Here, we show that LSD1 genotype (in humans) and LSD1 deficiency (in mice) lead to similar associations with increased blood pressure and urine potassium levels but with decreased aldosterone levels during a liberal salt diet. Thus, we hypothesized that LSD1 deficiency leads to an MR (mineralocorticoid receptor)-dependent hypertensive state. Yet, further studies in LSD1+/- mice treated with the MR antagonist eplerenone demonstrate that hypertension, kaliuria, and albuminuria are substantially improved, suggesting that the ligand-independent activation of the MR is the underlying cause of this LSD1 deficiency-mediated phenotype. Indeed, while MR and epithelial sodium channel expression levels were increased in LSD1+/- mouse kidney tissues, aldosterone secretion from LSD1+/- glomerulosa cells was significantly lower. Collectively, these data establish that LSD1 deficiency leads to an inappropriate activation and increased levels of the MR during a liberal salt regimen and suggest that inhibiting the MR pathway is a useful strategy for treatment of hypertension in human LSD1 risk allele carriers.
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Affiliation(s)
- Thitinan Treesaranuwattana
- From the Division of Endocrinology, Diabetes and Hypertension, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (T.T., K.Y.H.W., D.L.B., C.S.T., G.H.W., J.S.W., L.H.P.).,Division of Endocrinology and Metabolism, Rajavithi Hospital, Rangsit University, Bangkok, Thailand (T.T.)
| | - Kelly Yin Han Wong
- From the Division of Endocrinology, Diabetes and Hypertension, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (T.T., K.Y.H.W., D.L.B., C.S.T., G.H.W., J.S.W., L.H.P.).,Faculty of Medicine and Health Sciences, UCSI University, Kuala Lumpur, Malaysia (K.Y.H.W., C.S.T.)
| | - Danielle L Brooks
- From the Division of Endocrinology, Diabetes and Hypertension, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (T.T., K.Y.H.W., D.L.B., C.S.T., G.H.W., J.S.W., L.H.P.)
| | - Chee Sin Tay
- From the Division of Endocrinology, Diabetes and Hypertension, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (T.T., K.Y.H.W., D.L.B., C.S.T., G.H.W., J.S.W., L.H.P.).,Faculty of Medicine and Health Sciences, UCSI University, Kuala Lumpur, Malaysia (K.Y.H.W., C.S.T.)
| | - Gordon H Williams
- From the Division of Endocrinology, Diabetes and Hypertension, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (T.T., K.Y.H.W., D.L.B., C.S.T., G.H.W., J.S.W., L.H.P.)
| | - Jonathan S Williams
- From the Division of Endocrinology, Diabetes and Hypertension, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (T.T., K.Y.H.W., D.L.B., C.S.T., G.H.W., J.S.W., L.H.P.)
| | - Luminita H Pojoga
- From the Division of Endocrinology, Diabetes and Hypertension, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (T.T., K.Y.H.W., D.L.B., C.S.T., G.H.W., J.S.W., L.H.P.)
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8
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Young KA, Palmer ND, Fingerlin TE, Langefeld CD, Norris JM, Wang N, Xiang AH, Guo X, Williams AH, Chen YDI, Taylor KD, Rotter JI, Raffel LJ, Goodarzi MO, Watanabe RM, Wagenknecht LE. Genome-Wide Association Study Identifies Loci for Liver Enzyme Concentrations in Mexican Americans: The GUARDIAN Consortium. Obesity (Silver Spring) 2019; 27:1331-1337. [PMID: 31219225 PMCID: PMC6656610 DOI: 10.1002/oby.22527] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Accepted: 04/18/2019] [Indexed: 12/18/2022]
Abstract
OBJECTIVE Populations of Mexican American ancestry are at an increased risk for nonalcoholic fatty liver disease. The objective of this study was to determine whether loci in known and novel genes were associated with variation in aspartate aminotransferase (AST) (n = 3,644), alanine aminotransferase (ALT) (n = 3,595), and gamma-glutamyl transferase (GGT) (n = 1,577) levels by conducting the first genome-wide association study (GWAS) of liver enzymes, which commonly measure liver function, in individuals of Mexican American ancestry. METHODS Levels of AST, ALT, and GGT were determined by enzymatic colorimetric assays. A multi-cohort GWAS of individuals of Mexican American ancestry was performed. Single-nucleotide polymorphisms (SNP) were tested for association with liver outcomes by multivariable linear regression using an additive genetic model. Association analyses were conducted separately in each cohort, followed by a nonparametric meta-analysis. RESULTS In the PNPLA3 gene, rs4823173 (P = 3.44 × 10-10 ), rs2896019 (P = 7.29 × 10-9 ), and rs2281135 (P = 8.73 × 10-9 ) were significantly associated with AST levels. Although not genome-wide significant, these same SNPs were the top hits for ALT (P = 7.12 × 10-8 , P = 1.98 × 10-7 , and P = 1.81 × 10-7 , respectively). The strong correlation (r2 = 1.0) for these SNPs indicated a single hit in the PNPLA3 gene. No genome-wide significant associations were found for GGT. CONCLUSIONS PNPLA3, a locus previously identified with ALT, AST, and nonalcoholic fatty liver disease in European and Japanese GWAS, is also associated with liver enzymes in populations of Mexican American ancestry.
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Affiliation(s)
- Kendra A Young
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado, USA
| | - Nicholette D Palmer
- Department of Biochemistry, School of Medicine, Wake Forest University, Winston-Salem, North Carolina, USA
| | - Tasha E Fingerlin
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado, USA
- Center for Genes, Environment, and Health, National Jewish Health, Denver, Colorado, USA
| | - Carl D Langefeld
- Department of Biostatistical Sciences, School of Medicine, Wake Forest University, Winston-Salem, North Carolina, USA
| | - Jill M Norris
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado, USA
| | - Nan Wang
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Anny H Xiang
- Research and Evaluation Branch, Kaiser Permanente of Southern California, Pasadena, California, USA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, California, USA
| | - Adrienne H Williams
- Department of Biostatistical Sciences, School of Medicine, Wake Forest University, Winston-Salem, North Carolina, USA
| | - Yii-Der I Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, California, USA
- Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, California, USA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, California, USA
- Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, California, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, California, USA
- Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, California, USA
| | - Leslie J Raffel
- Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Mark O Goodarzi
- Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Richard M Watanabe
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Lynne E Wagenknecht
- Division of Public Health Sciences, School of Medicine, Wake Forest University, Winston-Salem, North Carolina, USA
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9
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Ehrhardt N, Cui J, Dagdeviren S, Saengnipanthkul S, Goodridge HS, Kim JK, Lantier L, Guo X, Chen YDI, Raffel LJ, Buchanan TA, Hsueh WA, Rotter JI, Goodarzi MO, Péterfy M. Adiposity-Independent Effects of Aging on Insulin Sensitivity and Clearance in Mice and Humans. Obesity (Silver Spring) 2019; 27:434-443. [PMID: 30801985 PMCID: PMC6474357 DOI: 10.1002/oby.22418] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Accepted: 11/21/2018] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Aging is associated with impaired insulin sensitivity and increased prevalence of type 2 diabetes. However, it remains unclear whether aging-associated insulin resistance is due to increased adiposity or other age-related factors. To address this question, the impact of aging on insulin sensitivity was investigated independently of changes in body composition. METHODS Cohorts of mice aged 4 to 8 months ("young") and 18 to 27 months ("aged") exhibiting similar body composition were characterized for glucose metabolism on chow and high-fat diets. Insulin sensitivity was assessed by hyperinsulinemic-euglycemic clamp analyses. The relationship between aging and insulin resistance in humans was investigated in 1,250 nondiabetic Mexican Americans who underwent hyperinsulinemic-euglycemic clamps. RESULTS In mice with similar body composition, age had no detrimental effect on plasma glucose and insulin levels. While aging did not diminish glucose tolerance, hyperinsulinemic-euglycemic clamps demonstrated impaired insulin sensitivity and reduced insulin clearance in aged mice on chow and high-fat diets. Consistent with results in the mouse, age remained an independent determinant of insulin resistance after adjustment for body composition in Mexican American males. CONCLUSIONS This study demonstrates that in addition to altered body composition, adiposity-independent mechanisms also contribute to aging-associated insulin resistance in mice and humans.
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Affiliation(s)
- Nicole Ehrhardt
- Department of Basic Medical Sciences, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Jinrui Cui
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Sezin Dagdeviren
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Suchaorn Saengnipanthkul
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Helen S. Goodridge
- Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Jason K. Kim
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA
- Division of Endocrinology, Metabolism, and Diabetes, Department of Medicine, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Louise Lantier
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37235, USA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Yii-Der I. Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Leslie J. Raffel
- Department of Pediatrics, Division of Genetic and Genomic Medicine, University of California, Irvine, CA 92697, USA
| | - Thomas A. Buchanan
- Department of Physiology and Biophysics and Department of Medicine, Keck School of Medicine of USC, Los Angeles, CA 90033, USA
| | - Willa A. Hsueh
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Wexner Medical Center, The Ohio State University, Columbus, OH 43210, USA
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Mark O. Goodarzi
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
- Corresponding authors: Mark O. Goodarzi () and Miklós Péterfy () Tel: +1 909 706 3949
| | - Miklós Péterfy
- Department of Basic Medical Sciences, Western University of Health Sciences, Pomona, CA 91766, USA
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
- Corresponding authors: Mark O. Goodarzi () and Miklós Péterfy () Tel: +1 909 706 3949
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10
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Gao C, Tabb KL, Dimitrov LM, Taylor KD, Wang N, Guo X, Long J, Rotter JI, Watanabe RM, Curran JE, Blangero J, Langefeld CD, Bowden DW, Palmer ND. Exome Sequencing Identifies Genetic Variants Associated with Circulating Lipid Levels in Mexican Americans: The Insulin Resistance Atherosclerosis Family Study (IRASFS). Sci Rep 2018; 8:5603. [PMID: 29618726 PMCID: PMC5884862 DOI: 10.1038/s41598-018-23727-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2017] [Accepted: 03/12/2018] [Indexed: 02/02/2023] Open
Abstract
Genome-wide association studies have identified numerous variants associated with lipid levels; yet, the majority are located in non-coding regions with unclear mechanisms. In the Insulin Resistance Atherosclerosis Family Study (IRASFS), heritability estimates suggest a strong genetic basis: low-density lipoprotein (LDL, h2 = 0.50), high-density lipoprotein (HDL, h2 = 0.57), total cholesterol (TC, h2 = 0.53), and triglyceride (TG, h2 = 0.42) levels. Exome sequencing of 1,205 Mexican Americans (90 pedigrees) from the IRASFS identified 548,889 variants and association and linkage analyses with lipid levels were performed. One genome-wide significant signal was detected in APOA5 with TG (rs651821, PTG = 3.67 × 10-10, LODTG = 2.36, MAF = 14.2%). In addition, two correlated SNPs (r2 = 1.0) rs189547099 (PTG = 6.31 × 10-08, LODTG = 3.13, MAF = 0.50%) and chr4:157997598 (PTG = 6.31 × 10-08, LODTG = 3.13, MAF = 0.50%) reached exome-wide significance (P < 9.11 × 10-08). rs189547099 is an intronic SNP in FNIP2 and SNP chr4:157997598 is intronic in GLRB. Linkage analysis revealed 46 SNPs with a LOD > 3 with the strongest signal at rs1141070 (LODLDL = 4.30, PLDL = 0.33, MAF = 21.6%) in DFFB. A total of 53 nominally associated variants (P < 5.00 × 10-05, MAF ≥ 1.0%) were selected for replication in six Mexican-American cohorts (N = 3,280). The strongest signal observed was a synonymous variant (rs1160983, PLDL = 4.44 × 10-17, MAF = 2.7%) in TOMM40. Beyond primary findings, previously reported lipid loci were fine-mapped using exome sequencing in IRASFS. These results support that exome sequencing complements and extends insights into the genetics of lipid levels.
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Affiliation(s)
- Chuan Gao
- Molecular Genetics and Genomics Program, Winston-Salem, NC, USA.,Center for Genomics and Personalized Medicine Research, Winston-Salem, NC, USA
| | - Keri L Tabb
- Center for Genomics and Personalized Medicine Research, Winston-Salem, NC, USA.,Department of Biochemistry, Winston-Salem, NC, USA
| | | | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Nan Wang
- Department of Preventive Medicine and Physiology and Biophysics, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jirong Long
- Department of Medicine and Vanderbilt Epidemiology Center Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Richard M Watanabe
- Department of Preventive Medicine and Physiology and Biophysics, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
| | - Joanne E Curran
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - John Blangero
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Carl D Langefeld
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Donald W Bowden
- Center for Genomics and Personalized Medicine Research, Winston-Salem, NC, USA.,Department of Biochemistry, Winston-Salem, NC, USA
| | - Nicholette D Palmer
- Center for Genomics and Personalized Medicine Research, Winston-Salem, NC, USA. .,Department of Biochemistry, Winston-Salem, NC, USA.
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11
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Manosroi W, Tan JW, Rariy CM, Sun B, Goodarzi MO, Saxena AR, Williams JS, Pojoga LH, Lasky-Su J, Cui J, Guo X, Taylor KD, Chen YDI, Xiang AH, Hsueh WA, Raffel LJ, Buchanan TA, Rotter JI, Williams GH, Seely EW. The Association of Estrogen Receptor-β Gene Variation With Salt-Sensitive Blood Pressure. J Clin Endocrinol Metab 2017; 102:4124-4135. [PMID: 28938457 PMCID: PMC5673274 DOI: 10.1210/jc.2017-00957] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2017] [Accepted: 08/29/2017] [Indexed: 11/19/2022]
Abstract
CONTEXT Hypertension in young women is uncommon compared with young men and older women. Estrogen appears to protect most women against hypertension, with incidence increasing after menopause. Because some premenopausal women develop hypertension, estrogen may play a different role in these women. Genetic variations in the estrogen receptor (ER) are associated with cardiovascular disease. ER-β, encoded by ESR2, is the ER predominantly expressed in vascular smooth muscle. OBJECTIVE To determine an association of single nucleotide polymorphisms in ESR2 with salt sensitivity of blood pressure (SSBP) and estrogen status in women. METHODS Candidate gene association study with ESR2 and SSBP conducted in normotensive and hypertensive women and men in two cohorts: International Hypertensive Pathotype (HyperPATH) (n = 584) (discovery) and Mexican American Hypertension-Insulin Resistance Study (n = 662) (validation). Single nucleotide polymorphisms in ESR1 (ER-α) were also analyzed. Analysis conducted in younger (<51 years, premenopausal, "estrogen-replete") and older women (≥51 years, postmenopausal, "estrogen-deplete"). Men were analyzed to control for aging. RESULTS Multivariate analyses of HyperPATH data between variants of ESR2 and SSBP documented that ESR2 rs10144225 minor (risk) allele carriers had a significantly positive association with SSBP driven by estrogen-replete women (β = +4.4 mm Hg per risk allele, P = 0.004). Findings were confirmed in Hypertension Insulin-Resistance Study premenopausal women. HyperPATH cohort analyses revealed risk allele carriers vs noncarriers had increased aldosterone/renin ratios. No associations were detected with ESR1. CONCLUSIONS The variation at rs10144225 in ESR2 was associated with SSBP in premenopausal women (estrogen-replete) and not in men or postmenopausal women (estrogen-deplete). Inappropriate aldosterone levels on a liberal salt diet may mediate the SSBP.
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Affiliation(s)
- Worapaka Manosroi
- Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115
- Division of Endocrinology and Metabolism, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
| | - Jia Wei Tan
- Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115
- Cell and Molecular Biology Laboratory, Department of Cellular Biology and Pharmacology, Faculty of Medicine and Health Sciences, UCSI University, Cheras 56000, Kuala Lumpur, Malaysia
| | - Chevon M. Rariy
- Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115
| | - Bei Sun
- Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115
| | - Mark O. Goodarzi
- Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, California 90048
| | - Aditi R. Saxena
- Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115
| | - Jonathan S. Williams
- Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115
| | - Luminita H. Pojoga
- Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115
| | - Jessica Lasky-Su
- Channing Laboratory, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts 02115
| | - Jinrui Cui
- Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, California 90048
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, California 90502
- Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, California 90502
| | - Kent D. Taylor
- Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, California 90502
- Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, California 90502
| | - Yii-Der I. Chen
- Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, California 90502
- Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, California 90502
| | - Anny H. Xiang
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California 91101
| | - Willa A. Hsueh
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California 91101
- Division of Endocrinology, Diabetes and Metabolism and Diabetes and Metabolism Research Center, The Ohio State University, Columbus, Ohio 43210
| | - Leslie J. Raffel
- Division of Genetic and Genomic Medicine, Department of Pediatrics, University of California, Irvine, California 92868
| | - Thomas A. Buchanan
- Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, Los Angeles, California 90089
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, California 90502
- Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, California 90502
| | - Gordon H. Williams
- Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115
| | - Ellen W. Seely
- Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115
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12
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Graff M, Emery LS, Justice AE, Parra E, Below JE, Palmer ND, Gao C, Duan Q, Valladares-Salgado A, Cruz M, Morrison AC, Boerwinkle E, Whitsel EA, Kooperberg C, Reiner A, Li Y, Rodriguez CJ, Talavera GA, Langefeld CD, Wagenknecht LE, Norris JM, Taylor KD, Papanicolaou G, Kenny E, Loos RJF, Chen YDI, Laurie C, Sofer T, North KE. Genetic architecture of lipid traits in the Hispanic community health study/study of Latinos. Lipids Health Dis 2017; 16:200. [PMID: 29025430 PMCID: PMC5639746 DOI: 10.1186/s12944-017-0591-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Accepted: 10/04/2017] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Despite ethnic disparities in lipid profiles, there are few genome-wide association studies investigating genetic variation of lipids in non-European ancestry populations. In this study, we present findings from genetic association analyses for total cholesterol, low density lipoprotein cholesterol (LDL), high density lipoprotein cholesterol (HDL), and triglycerides in a large Hispanic/Latino cohort in the U.S., the Hispanic Community Health Study / Study of Latinos (HCHS/SOL). METHODS We estimated a heritability of approximately 20% for each lipid trait, similar to previous estimates in Europeans. To search for novel lipid loci, we performed conditional association analysis in which the statistical model was adjusted for previously reported SNPs associated with any of the four lipid traits. SNPs that remained genome-wide significant (P < 5 × 10-8) after conditioning on known loci were evaluated for replication. RESULTS We identified eight potentially novel lipid signals with minor allele frequencies <1%, none of which replicated. We tested previously reported SNP-trait associations for generalization to Hispanics/Latinos via a statistical framework. The generalization analysis revealed that approximately 50% of previously established lipid variants generalize to HCHS/SOL based on directional FDR r-value < 0.05. Some failures to generalize were due to lack of power. CONCLUSIONS These results demonstrate that many loci associated with lipid levels are shared across populations.
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Affiliation(s)
- Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
| | - Leslie S Emery
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Anne E Justice
- Biomedical and Translational Informatics, Geisinger Health, Danville, PA, USA
| | - Esteban Parra
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON, Canada
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Vanderbuilt University, Nashville, TN, USA
| | - Nicholette D Palmer
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Chuan Gao
- Molecular Genetics and Genomics Program, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Qing Duan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Adan Valladares-Salgado
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, CMNSXX1-IMSS, Mexico City, Mexico
| | - Miguel Cruz
- Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, CMNSXX1-IMSS, Mexico City, Mexico
| | - Alanna C Morrison
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Eric Boerwinkle
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Charles Kooperberg
- Fred Hutchinson Cancer Research Center, Public Health Sciences, Seattle, WA, USA
| | - Alex Reiner
- Fred Hutchinson Cancer Research Center, Public Health Sciences, Seattle, WA, USA
| | - Yun Li
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Carlos Jose Rodriguez
- Department of Medicine and Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Gregory A Talavera
- Graduate School of Public Health, San Diego State University, San Diego, CA, USA
| | - Carl D Langefeld
- Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Lynne E Wagenknecht
- Department of Medicine and Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Jill M Norris
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, CO, USA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | | | - Eimear Kenny
- Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Cathy Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
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13
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Gao C, Wang N, Guo X, Ziegler JT, Taylor KD, Xiang AH, Hai Y, Kridel SJ, Nadler JL, Kandeel F, Raffel LJ, Chen YDI, Norris JM, Rotter JI, Watanabe RM, Wagenknecht LE, Bowden DW, Speliotes EK, Goodarzi MO, Langefeld CD, Palmer ND. A Comprehensive Analysis of Common and Rare Variants to Identify Adiposity Loci in Hispanic Americans: The IRAS Family Study (IRASFS). PLoS One 2015; 10:e0134649. [PMID: 26599207 PMCID: PMC4658008 DOI: 10.1371/journal.pone.0134649] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2015] [Accepted: 07/10/2015] [Indexed: 11/18/2022] Open
Abstract
Obesity is growing epidemic affecting 35% of adults in the United States. Previous genome-wide association studies (GWAS) have identified numerous loci associated with obesity. However, the majority of studies have been completed in Caucasians focusing on total body measures of adiposity. Here we report the results from genome-wide and exome chip association studies focusing on total body measures of adiposity including body mass index (BMI), percent body fat (PBF) and measures of fat deposition including waist circumference (WAIST), waist-hip ratio (WHR), subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT) in Hispanic Americans (nmax = 1263) from the Insulin Resistance Atherosclerosis Family Study (IRASFS). Five SNPs from two novel loci attained genome-wide significance (P<5.00x10-8) in IRASFS. A missense SNP in the isocitrate dehydrogenase 1 gene (IDH1) was associated with WAIST (rs34218846, MAF = 6.8%, PDOM = 1.62x10-8). This protein is postulated to play an important role in fat and cholesterol biosynthesis as demonstrated in cell and knock-out animal models. Four correlated intronic SNPs in the Zinc finger, GRF-type containing 1 gene (ZGRF1; SNP rs1471880, MAF = 48.1%, PDOM = 1.00x10-8) were strongly associated with WHR. The exact biological function of ZGRF1 and the connection with adiposity remains unclear. SNPs with p-values less than 5.00x10-6 from IRASFS were selected for replication. Meta-analysis was computed across seven independent Hispanic-American cohorts (nmax = 4156) and the strongest signal was rs1471880 (PDOM = 8.38x10-6) in ZGRF1 with WAIST. In conclusion, a genome-wide and exome chip association study was conducted that identified two novel loci (IDH1 and ZGRF1) associated with adiposity. While replication efforts were inconclusive, when taken together with the known biology, IDH1 and ZGRF1 warrant further evaluation.
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Affiliation(s)
- Chuan Gao
- Molecular Genetics and Genomics Program, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Nan Wang
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Physiology and Biophysics, University of Southern California Keck School of Medicine, Los Angeles, California, United States of America
- Department of Preventive Medicine, University of Southern California Keck School of Medicine, Los Angeles, California, United States of America
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Julie T. Ziegler
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Kent D. Taylor
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Anny H. Xiang
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, United States of America
| | - Yang Hai
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Steven J. Kridel
- Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Jerry L. Nadler
- Department of Internal Medicine, Strelitz Diabetes Center, Eastern Virginia Medical School, Norfolk, Virginia, United States of America
| | - Fouad Kandeel
- Department of Diabetes and Metabolic Diseases Research, Beckman Research Institute of City of Hope, Duarte, California, United States of America
| | - Leslie J. Raffel
- Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Yii-Der I. Chen
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Jill M. Norris
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado, United States of America
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Richard M. Watanabe
- Physiology and Biophysics, University of Southern California Keck School of Medicine, Los Angeles, California, United States of America
- Department of Preventive Medicine, University of Southern California Keck School of Medicine, Los Angeles, California, United States of America
| | - Lynne E. Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Donald W. Bowden
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Elizabeth K. Speliotes
- Department of Internal Medicine, Division of Gastroenterology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Mark O. Goodarzi
- Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
- Division of Endocrinology, Diabetes, and Metabolism, Cedars-Sinai Medical Center, Los Angeles, California, United States of America
| | - Carl D. Langefeld
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Nicholette D. Palmer
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
- * E-mail:
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14
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Palmer ND, Goodarzi MO, Langefeld CD, Wang N, Guo X, Taylor KD, Fingerlin TE, Norris JM, Buchanan TA, Xiang AH, Haritunians T, Ziegler JT, Williams AH, Stefanovski D, Cui J, Mackay AW, Henkin LF, Bergman RN, Gao X, Gauderman J, Varma R, Hanis CL, Cox NJ, Highland HM, Below JE, Williams AL, Burtt NP, Aguilar-Salinas CA, Huerta-Chagoya A, Gonzalez-Villalpando C, Orozco L, Haiman CA, Tsai MY, Johnson WC, Yao J, Rasmussen-Torvik L, Pankow J, Snively B, Jackson RD, Liu S, Nadler JL, Kandeel F, Chen YDI, Bowden DW, Rich SS, Raffel LJ, Rotter JI, Watanabe RM, Wagenknecht LE. Genetic Variants Associated With Quantitative Glucose Homeostasis Traits Translate to Type 2 Diabetes in Mexican Americans: The GUARDIAN (Genetics Underlying Diabetes in Hispanics) Consortium. Diabetes 2015; 64:1853-66. [PMID: 25524916 PMCID: PMC4407862 DOI: 10.2337/db14-0732] [Citation(s) in RCA: 68] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2014] [Accepted: 12/06/2014] [Indexed: 12/31/2022]
Abstract
Insulin sensitivity, insulin secretion, insulin clearance, and glucose effectiveness exhibit strong genetic components, although few studies have examined their genetic architecture or influence on type 2 diabetes (T2D) risk. We hypothesized that loci affecting variation in these quantitative traits influence T2D. We completed a multicohort genome-wide association study to search for loci influencing T2D-related quantitative traits in 4,176 Mexican Americans. Quantitative traits were measured by the frequently sampled intravenous glucose tolerance test (four cohorts) or euglycemic clamp (three cohorts), and random-effects models were used to test the association between loci and quantitative traits, adjusting for age, sex, and admixture proportions (Discovery). Analysis revealed a significant (P < 5.00 × 10(-8)) association at 11q14.3 (MTNR1B) with acute insulin response. Loci with P < 0.0001 among the quantitative traits were examined for translation to T2D risk in 6,463 T2D case and 9,232 control subjects of Mexican ancestry (Translation). Nonparametric meta-analysis of the Discovery and Translation cohorts identified significant associations at 6p24 (SLC35B3/TFAP2A) with glucose effectiveness/T2D, 11p15 (KCNQ1) with disposition index/T2D, and 6p22 (CDKAL1) and 11q14 (MTNR1B) with acute insulin response/T2D. These results suggest that T2D and insulin secretion and sensitivity have both shared and distinct genetic factors, potentially delineating genomic components of these quantitative traits that drive the risk for T2D.
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Affiliation(s)
- Nicholette D Palmer
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Carl D Langefeld
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Nan Wang
- Department of Preventive Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA Diabetes & Obesity Research Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA
| | - Tasha E Fingerlin
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, CO Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver, Aurora, CO
| | - Jill M Norris
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, CO
| | - Thomas A Buchanan
- Diabetes & Obesity Research Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA Department of Physiology and Biophysics, Keck School of Medicine of University of Southern California, Los Angeles, CA Department of Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA
| | - Anny H Xiang
- Research and Evaluation Branch, Kaiser Permanente of Southern California, Pasadena, CA
| | - Talin Haritunians
- Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Julie T Ziegler
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Adrienne H Williams
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | - Darko Stefanovski
- Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Jinrui Cui
- Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Adrienne W Mackay
- Department of Preventive Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA
| | - Leora F Henkin
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | | | - Xiaoyi Gao
- Department of Preventive Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA Department of Ophthalmology and Visual Science, University of Illinois at Chicago, Chicago, IL
| | - James Gauderman
- Department of Preventive Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA Department of Ophthalmology and Visual Science, University of Illinois at Chicago, Chicago, IL
| | - Rohit Varma
- Department of Ophthalmology and Visual Science, University of Illinois at Chicago, Chicago, IL
| | - Craig L Hanis
- Human Genetics Center, School of Public Health, University of Texas Health Science Center, Houston, TX
| | - Nancy J Cox
- Department of Human Genetics, University of Chicago, Chicago, IL
| | - Heather M Highland
- Human Genetics Center, School of Public Health, University of Texas Health Science Center, Houston, TX
| | - Jennifer E Below
- Human Genetics Center, School of Public Health, University of Texas Health Science Center, Houston, TX
| | - Amy L Williams
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA Howard Hughes Medical Institute, Chicago, IL Biological Sciences Department, Columbia University, New York, NY
| | - Noel P Burtt
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
| | - Carlos A Aguilar-Salinas
- Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Alicia Huerta-Chagoya
- Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico Universidad Nacional Autónoma de México, Mexico City, Mexico
| | | | - Lorena Orozco
- Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN
| | - W Craig Johnson
- Collaborative Health Studies Coordinating Center, Department of Biostatistics, University of Washington, Seattle, WA
| | - Jie Yao
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA
| | - Laura Rasmussen-Torvik
- Division of Epidemiology, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Evanston, IL
| | - James Pankow
- Division of Epidemiology & Community Health, University of Minnesota, Minneapolis, MN
| | - Beverly Snively
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC
| | | | - Simin Liu
- Department of Epidemiology, Brown University, Providence, RI
| | - Jerry L Nadler
- Department of Medicine, Eastern Virginia Medical School, Norfolk, VA
| | - Fouad Kandeel
- Department of Diabetes, Endocrinology & Metabolism, City of Hope, Duarte, CA
| | - Yii-Der I Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA
| | - Donald W Bowden
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC Section on Endocrinology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA
| | - Leslie J Raffel
- Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-University of California, Los Angeles Medical Center, Torrance, CA
| | - Richard M Watanabe
- Department of Preventive Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA Diabetes & Obesity Research Institute, Keck School of Medicine of University of Southern California, Los Angeles, CA Department of Physiology and Biophysics, Keck School of Medicine of University of Southern California, Los Angeles, CA
| | - Lynne E Wagenknecht
- Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC
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Huang JC, Chen SC, Lin MY, Chang JM, Hwang SJ, Tsai JC, Chen HC. Association of relatives of hemodialysis patients with metabolic syndrome, albuminuria and Framingham Risk Score. PLoS One 2014; 9:e96362. [PMID: 24804770 PMCID: PMC4012957 DOI: 10.1371/journal.pone.0096362] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2013] [Accepted: 04/05/2014] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND AND AIM Metabolic syndrome (MetS), albuminuria, and the Framingham Risk Score (FRS) are significant predictors for cardiovascular disease (CVD). However, the relationship and clinical significance of these CVD predictors in individuals with a family history of end-stage renal disease (ESRD) are unclear. We investigated the association of relatives of hemodialysis (HD) patients with MetS, albuminuria, and the FRS. METHODS One hundred and sixty-six relatives of HD patients and 374 age- and sex- matched community controls were enrolled. MetS was defined using the Adult Treatment Panel III for Asians. Albuminuria was defined as urine albumin-to-creatinine ratio ≥ 30 mg/g. CVD risk was evaluated by the FRS. RESULTS A significantly higher prevalence of MetS (19.9% vs. 12.5%, P = 0.026), albuminuria (12.7% vs. 5.1%, P = 0.002) and high FRS risk ≥ 10% of 10-year risk (15.7% vs. 8.5%, P = 0.013) was found in relatives of HD patients compared to their counterpart controls. In multivariate analysis, being relatives of HD patients (vs. controls) was an independent determinant for MetS (odds ratio [OR], 1.785; 95% confidence interval [CI], 1.045 to 3.050), albuminuria (OR, 2.891; 95% CI, 1.431 to 5.841), and high FRS risk (OR, 1.863; 95% CI, 1.015 to 3.418). Higher low-density lipoprotein cholesterol (OR, 1.034; 95% CI, 1.017 to 1.052) and betel nut chewing (OR, 13.994; 95% CI, 3.384 to 57.871) were independent determinants for having a high FRS risk in relatives of HD patients. CONCLUSIONS Being relatives of HD patients was independently associated with MetS, albuminuria and high FRS risk, suggesting family members of ESRD patients may have higher CVD risks through the interactions of renal risk factors. Proactive surveillance of these CVD predictors and preventive strategies should be targeted to this high-risk population.
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Affiliation(s)
- Jiun-Chi Huang
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
- Department of Internal Medicine, Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Szu-Chia Chen
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
- Department of Internal Medicine, Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
- Faculty of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Ming-Yen Lin
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Jer-Ming Chang
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
- Department of Internal Medicine, Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
- Faculty of Renal Care, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Shang-Jyh Hwang
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
- Faculty of Renal Care, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Jer-Chia Tsai
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
- Faculty of Renal Care, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
- * E-mail:
| | - Hung-Chun Chen
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
- Faculty of Renal Care, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
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16
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Goodarzi MO, Langefeld CD, Xiang AH, Chen YDI, Guo X, Hanley AJG, Raffel LJ, Kandeel F, Buchanan TA, Norris JM, Fingerlin TE, Lorenzo C, Rewers MJ, Haffner SM, Bowden DW, Rich SS, Bergman RN, Rotter JI, Watanabe RM, Wagenknecht LE. Insulin sensitivity and insulin clearance are heritable and have strong genetic correlation in Mexican Americans. Obesity (Silver Spring) 2014; 22:1157-64. [PMID: 24124113 PMCID: PMC3968231 DOI: 10.1002/oby.20639] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2013] [Revised: 08/29/2013] [Accepted: 10/02/2013] [Indexed: 11/08/2022]
Abstract
OBJECTIVE The GUARDIAN (Genetics UndeRlying DIAbetes in HispaNics) consortium is described, along with heritability estimates and genetic and environmental correlations of insulin sensitivity and metabolic clearance rate of insulin (MCRI). METHODS GUARDIAN is comprised of seven cohorts, consisting of 4,336 Mexican-American individuals in 1,346 pedigrees. Insulin sensitivity (SI ), MCRI, and acute insulin response (AIRg) were measured by frequently sampled intravenous glucose tolerance test in four cohorts. Insulin sensitivity (M, M/I) and MCRI were measured by hyperinsulinemic-euglycemic clamp in three cohorts. Heritability and genetic and environmental correlations were estimated within the family cohorts (totaling 3,925 individuals) using variance components. RESULTS Across studies, age, and gender-adjusted heritability of insulin sensitivity (SI , M, M/I) ranged from 0.23 to 0.48 and of MCRI from 0.35 to 0.73. The ranges for the genetic correlations were 0.91 to 0.93 between SI and MCRI; and -0.57 to -0.59 for AIRg and MCRI (all P < 0.0001). The ranges for the environmental correlations were 0.54 to 0.74 for SI and MCRI (all P < 0.0001); and -0.16 to -0.36 for AIRg and MCRI (P < 0.0001-0.06). CONCLUSIONS These data support a strong familial basis for insulin sensitivity and MCRI in Mexican Americans. The strong genetic correlations between MCRI and SI suggest common genetic determinants.
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Affiliation(s)
- Mark O. Goodarzi
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California
- the Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Carl D. Langefeld
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Anny H. Xiang
- Department of Research and Evaluation, Kaiser Permanente Southern California Medical Group, Pasadena, California
| | - Yii-Der I. Chen
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California
| | - Anthony J. G. Hanley
- Departments of Nutritional Sciences and Medicine and Dalla Lana School of Public Health, University of Toronto, Ontario, Canada
| | - Leslie J. Raffel
- the Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Fouad Kandeel
- Department of Diabetes, Endocrinology and Metabolism, City of Hope, Duarte, California
| | - Thomas A. Buchanan
- Department of Medicine, University of Southern California Keck School of Medicine, Los Angeles, California
- Department of Physiology and Biophysics, University of Southern California Keck School of Medicine, Los Angeles, California
| | - Jill M. Norris
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado
| | - Tasha E. Fingerlin
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado
| | - Carlos Lorenzo
- Division of Clinical Epidemiology, University of Texas Health Sciences Center, San Antonio, Texas
| | - Marian J. Rewers
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, Colorado
| | | | - Donald W. Bowden
- Department of Biochemistry, Centers for Diabetes Research and Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia
| | - Richard N. Bergman
- Diabetes and Obesity Research Institute, Burns and Allen Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California
| | - Richard M. Watanabe
- Department of Physiology and Biophysics, University of Southern California Keck School of Medicine, Los Angeles, California
- Department of Preventive Medicine, University of Southern California Keck School of Medicine, Los Angeles, California
| | - Lynne E. Wagenknecht
- Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
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Goodarzi MO, Guo X, Cui J, Jones MR, Haritunians T, Xiang AH, Chen YDI, Taylor KD, Buchanan TA, Hsueh WA, Raffel LJ, Rotter JI. Systematic evaluation of validated type 2 diabetes and glycaemic trait loci for association with insulin clearance. Diabetologia 2013; 56:1282-90. [PMID: 23494448 PMCID: PMC3651757 DOI: 10.1007/s00125-013-2880-6] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2012] [Accepted: 02/12/2013] [Indexed: 12/25/2022]
Abstract
AIMS/HYPOTHESIS Insulin clearance is a highly heritable trait, for which few quantitative trait loci have been discovered. We sought to determine whether validated type 2 diabetes and/or glycaemic trait loci are associated with insulin clearance. METHODS Hyperinsulinaemic-euglycaemic clamps were performed in two Hispanic-American family cohorts totalling 1329 participants in 329 families. The Metabochip was used to fine-map about 50 previously identified loci for type 2 diabetes, fasting glucose, fasting insulin, 2 h glucose or HbA1c. This resulted in 17,930 variants, which were tested for association with clamp-derived insulin clearance via meta-analysis of the two cohorts. RESULTS In the meta-analysis, 38 variants located within seven loci demonstrated association with insulin clearance (p < 0.001). The top signals for each locus were rs10241087 (DGKB/TMEM195 [TMEM195 also known as AGMO]) (p = 4.4 × 10(-5)); chr1:217605433 (LYPLAL1) (p = 3.25 × 10(-4)); rs2380949 (GLIS3) (p = 3.4 × 10(-4)); rs55903902 (FADS1) (p = 5.6 × 10(-4)); rs849334 (JAZF1) (p = 6.4 × 10(-4)); rs35749 (IGF1) (p = 6.7 × 10(-4)); and rs9460557 (CDKAL1) (p = 6.8 × 10(-4)). CONCLUSIONS/INTERPRETATION While the majority of validated loci for type 2 diabetes and related traits do not appear to influence insulin clearance in Hispanics, several of these loci do show evidence of association with this trait. It is therefore possible that these loci could have pleiotropic effects on insulin secretion, insulin sensitivity and insulin clearance.
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Affiliation(s)
- M O Goodarzi
- Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Room B-131, Los Angeles, CA 90048, USA.
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Ho LT, Hsu YP, Hsiao CF, Ting CT, Shih KC, Chuang LM, Masaki K, Grove J, Quertermous T, Juan CC, Lin MW, Chiang SC, Chen YDI. Endothelin Type A Receptor Genotype is a Determinant of Quantitative Traits of Metabolic Syndrome in Asian Hypertensive Families: A SAPPHIRe Study. Front Endocrinol (Lausanne) 2013; 4:172. [PMID: 24348460 PMCID: PMC3842518 DOI: 10.3389/fendo.2013.00172] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2013] [Accepted: 10/25/2013] [Indexed: 02/01/2023] Open
Abstract
Co-heritability of hypertension and insulin resistance (IR) within families not only implies genetic susceptibility may be responsible for these complex traits but also suggests a rational that biological candidate genes for hypertension may serve as markers for features of the metabolic syndrome (MetS). Thus we determined whether the T323C polymorphism (rs5333) of endothelin type A (ETA) receptor, a predominant receptor evoking potent vasoconstrictive action of endothelin-1, contributes to susceptibility to IR-associated hypertension in 1694 subjects of Chinese and Japanese origins. Blood pressures (BPs) and biochemistries were measured. Fasting insulin level, insulin-resistance homeostasis model assessment (HOMAIR) score, and area under curve of insulin concentration (AUCINS) were selected for assessing insulin sensitivity. Genotypes were obtained by methods of polymerase chain reaction-restriction fragment length polymorphism. Foremost findings were that minor allele frequency of the T323C polymorphism was noticeable lower in our overall Asian subjects compared to multi-national population reported in gene database; moreover both the genotypic and allelic frequencies of the polymorphism were significantly different between the two ethnic groups we studied. The genotype distributions at TT/TC/CC were 65, 31, 4% in Chinese and 51, 41, 8% in Japanese, respectively (p < 0.0001). Additionally, carriers of the C homozygote revealed characteristics of IR, namely significantly higher levels of fasting insulin, HOMAIR score, and AUCINS at 29.3, 35.3, and 39.3%, respectively, when compared to their counterparts with TT/TC genotypes in Chinese. Meanwhile, the CC genotype was associated with a higher level of high density lipoprotein cholesterol in Japanese. No association of the polymorphism with BP was observed. This study demonstrated for the first time that T323C polymorphism of ETA receptor gene was associated with an adverse insulin response in Chinese and a favorite atherogenic index in Japanese.
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Affiliation(s)
- Low-Tone Ho
- Department of Medical Research and Education, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang-Ming University, Taipei, Taiwan
- Faculty of Medicine, National Yang-Ming University, Taipei, Taiwan
- Institute of Physiology, National Yang-Ming University, Taipei, Taiwan
- Institute of Clinical Medicine, National Yang-Ming University, Taipei, Taiwan
- *Correspondence: Low-Tone Ho, Department of Medical Research and Education, Taipei Veterans General Hospital, No. 201 Shih-Pai Road Section 2, Taipei 11217, Taiwan e-mail:
| | - Yung-Pei Hsu
- Department of Medical Research and Education, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Chin-Fu Hsiao
- Division of Biostatistics and Bioinformatics, National Health Research Institutes, Taipei, Taiwan
| | - Chih-Tai Ting
- Cardiovascular Center, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Kuang-Chung Shih
- Division of Endocrinology and Metabolism, Tri-Service General Hospital, Taipei, Taiwan
| | - Lee-Ming Chuang
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
- Graduate Institute of Clinical Medicine, National Taiwan University, Taipei, Taiwan
| | | | - John Grove
- Department of Public Health Sciences and Epidemiology, John A. Burns School of Medicine, University of Hawaii and Pacific Health Research Institute, Honolulu, Hawaii
| | - Thomas Quertermous
- Division of Cardiovascular Medicine, Falk Cardiovascular Research Center, Stanford University, Stanford, CA, USA
| | - Chi-Chung Juan
- Department of Medical Research and Education, Taipei Veterans General Hospital, Taipei, Taiwan
- Institute of Physiology, National Yang-Ming University, Taipei, Taiwan
- Institute of Clinical Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Ming-Wei Lin
- Department of Medical Research and Education, Taipei Veterans General Hospital, Taipei, Taiwan
- Faculty of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Shu-Chiung Chiang
- Information Service Center, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yii-Der I. Chen
- Medical Genetics Institute, Cedars-Sinai Medical Center, University of California at Los Angeles, Los Angeles, CA, USA
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Guo X, Cui J, Jones MR, Haritunians T, Xiang AH, Chen YDI, Taylor KD, Buchanan TA, Davis RC, Hsueh WA, Raffel LJ, Rotter JI, Goodarzi MO. Insulin clearance: confirmation as a highly heritable trait, and genome-wide linkage analysis. Diabetologia 2012; 55:2183-92. [PMID: 22584727 PMCID: PMC3391346 DOI: 10.1007/s00125-012-2577-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2012] [Accepted: 04/09/2012] [Indexed: 01/11/2023]
Abstract
AIMS/HYPOTHESIS We have previously documented a high heritability of insulin clearance in a Hispanic cohort. Here, our goal was to confirm the high heritability in a second cohort and search for genetic loci contributing to insulin clearance. METHODS Hyperinsulinaemic-euglycaemic clamps were performed in 513 participants from 140 Hispanic families. Heritability was estimated for clamp-derived insulin clearance and a two-phase genome-wide linkage scan was conducted using a variance components approach. Linkage peaks were further investigated by candidate gene association analysis in two cohorts. RESULTS The covariate-adjusted heritability of insulin clearance was 73%, indicating that the majority of the phenotypic variance is due to genetic factors. In the Phase 1 linkage scan, no signals with a logarithm of odds (LOD) score >2 were detected. In the Phase 2 scan, two linkage peaks with an LOD >2 for insulin clearance were identified on chromosomes 15 (LOD 3.62) and 20 (LOD 2.43). These loci harbour several promising candidate genes for insulin clearance, with 12 single nucleotide polymorphisms (SNPs) on chromosome 15 and six SNPs on chromosome 20 being associated with insulin clearance in both Hispanic cohorts. CONCLUSIONS/INTERPRETATION In a second Hispanic cohort, we confirmed that insulin clearance is a highly heritable trait and identified chromosomal loci that harbour genes regulating insulin clearance. The identification of such genes may improve our understanding of how the body clears insulin, thus leading to improved risk assessment, diagnosis, prevention and therapy of diabetes, as well as of other hyperinsulinaemic disorders, such as the metabolic syndrome and polycystic ovary syndrome.
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Affiliation(s)
- X. Guo
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - J. Cui
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - M. R. Jones
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, 8700 Beverly Blvd., Room B-131, Los Angeles, CA 90048, USA
| | - T. Haritunians
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - A. H. Xiang
- Department of Research and Evaluation, Kaiser Permanente Southern California Medical Group, Pasadena, CA, USA
| | - Y.-D. I. Chen
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - K. D. Taylor
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - T. A. Buchanan
- Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - R. C. Davis
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - W. A. Hsueh
- Diabetes Research Center, Division of Diabetes, Obesity and Lipids, Methodist Hospital Research Institute, Houston, TX, USA
| | - L. J. Raffel
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - J. I. Rotter
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - M. O. Goodarzi
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA. Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, 8700 Beverly Blvd., Room B-131, Los Angeles, CA 90048, USA
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20
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Williams JS, Chamarthi B, Goodarzi MO, Pojoga LH, Sun B, Garza AE, Raby BA, Adler GK, Hopkins PN, Brown NJ, Jeunemaitre X, Ferri C, Fang R, Leonor T, Cui J, Guo X, Taylor KD, Chen YDI, Xiang A, Raffel LJ, Buchanan TA, Rotter JI, Williams GH, Shi Y. Lysine-specific demethylase 1: an epigenetic regulator of salt-sensitive hypertension. Am J Hypertens 2012; 25:812-7. [PMID: 22534796 DOI: 10.1038/ajh.2012.43] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
BACKGROUND Hypertension (HTN) represents a complex heritable disease in which environmental factors may directly affect gene function via epigenetic mechanisms. The aim of this study was to test the hypothesis that dietary salt influences the activity of a histone-modifying enzyme, lysine-specific demethylase 1 (LSD-1), which in turn is associated with salt-sensitivity of blood pressure (BP). METHODS Animal and human studies were performed. Salt-sensitivity of LSD-1 expression was assessed in wild-type (WT) and LSD-1 heterozygote knockout (LSD-1(+/-)) mice. Clinical relevance was tested by multivariate associations between single-nuclear polymorphisms (SNPs) in the LSD-1 gene and salt-sensitivity of BP, with control of dietary sodium, in a primary African-American hypertensive cohort and two replication hypertensive cohorts (Caucasian and Mexican-American). RESULTS LSD-1 expression was modified by dietary salt in WT mice with lower levels associated with liberal salt intake. LSD-1(+/-) mice expressed lower LSD-1 protein levels than WT mice in kidney tissue. Similar to LSD-1(+/-) mice, African-American minor allele carriers of two LSD-1 SNPs displayed greater change in systolic BP (SBP) in response to change from low to liberal salt diet (rs671357, P = 0.01; rs587168, P = 0.005). This association was replicated in the Hispanic (rs587168, P = 0.04) but not the Caucasian cohort. Exploratory analyses demonstrated decreased serum aldosterone concentrations in African-American minor allele carriers similar to findings in the LSD-1(+/-) mice, decreased α-EnaC expression in LSD-1(+/-) mice, and impaired renovascular responsiveness to salt loading in minor allele carriers. CONCLUSION The results of this translational research study support a role for LSD-1 in the pathogenesis of salt-sensitive HTN.
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Lee MH, Kim HC, Thomas GN, Ahn SV, Hur NW, Choi DP, Suh I. Familial concordance of metabolic syndrome in Korean population--Korean National Health and Nutrition Examination Survey 2005. Diabetes Res Clin Pract 2011; 93:430-6. [PMID: 21733593 DOI: 10.1016/j.diabres.2011.06.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2010] [Accepted: 06/02/2011] [Indexed: 11/28/2022]
Abstract
AIMS To investigate the familial concordance of metabolic syndrome and its components in a nationally representative survey in Korean. METHODS We used data from the Korean National Health and Nutrition Examination Survey (KNHANES), a nationwide survey examining the general health and nutritional status of the Korean people. We enrolled 1641 married couples and 1527 parents-1342 offspring. RESULTS Prevalence of the metabolic syndrome was 17.1% for husbands, 11.7% for wives, 14.3% for parents, and 7.2% for offspring. After adjustment for age, there were strong positive correlations between family members for the metabolic variables. Compared with husbands whose wives did not have metabolic syndrome, adjusted odds ratio in husbands whose wives had metabolic syndrome was 1.43 (95% CI: 1.10-1.87) for the risk of having metabolic syndrome. Similarly, wives whose husbands had metabolic syndrome had 1.41 (95% CI: 1.08-1.84) times higher risk of having metabolic syndrome. Compared with children whose parents did not have metabolic syndrome, adjusted odds ratio in children with at least one parent with the metabolic syndrome was 2.56 (95% CI: 1.09-5.98) for the metabolic syndrome. CONCLUSIONS Our study revealed that there is significant familial concordance for metabolic syndrome and its components in Korean families.
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Affiliation(s)
- Myung Ha Lee
- Department of Preventive Medicine, Yonsei University College of Medicine, 250 Seongsanno, Seodaemun-Gu, Seoul 120-752, South Korea
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22
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Pojoga LH, Underwood PC, Goodarzi MO, Williams JS, Adler GK, Jeunemaitre X, Hopkins PN, Raby BA, Lasky-Su J, Sun B, Cui J, Guo X, Taylor KD, Chen YDI, Xiang A, Raffel LJ, Buchanan TA, Rotter JI, Williams GH. Variants of the caveolin-1 gene: a translational investigation linking insulin resistance and hypertension. J Clin Endocrinol Metab 2011; 96:E1288-92. [PMID: 21613355 PMCID: PMC3146791 DOI: 10.1210/jc.2010-2738] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
CONTEXT The co-occurrence of insulin resistance (IR) and hypertension is a heritable condition leading to cardiovascular complications. Caveolin-1 (CAV1), a gene previously associated with metabolic dysfunction in animal and cellular models, may be a marker for these conditions in humans. OBJECTIVE The objective of the study was to examine the relationship between CAV1 variants and IR in two hypertensive cohorts and to corroborate the findings in a CAV1 knockout mouse. DESIGN, SETTING, AND PARTICIPANTS A candidate gene association study was conducted in two hypertensive cohorts: 1) Caucasian and 2) Hispanic. Multivariate associations between individual variants and insulin-resistant phenotypes were analyzed, accounting for age, gender, body mass index, and sibling relatedness. Intraperitoneal glucose tolerance tests were conducted in wild-type and CAV1 knockout mice. RESULTS In the Caucasian hypertensive cohort, minor allele carriers of two CAV1 single-nucleotide polymorphisms (rs926198, rs3807989) had significantly higher fasting insulin levels (P = 0.005, P = 0.007), increased homeostatic assessment model for insulin resistance (HOMA-IR) (P =0.005, P = 0.008), and decreased M value during hyperinsulinemic, euglycemic clamp procedure (P = 0.004, P = 0.05) than major allele homozygotes. Findings were replicated in the Hispanic hypertensive cohort cohort for fasting insulin levels (P = 0.005, P = 0.02) and HOMA-IR (P = 0.008 and P = 0.02). Meta-analysis demonstrated significant associations of both single-nucleotide polymorphisms with fasting insulin levels (P = 0.00008, P = 0.0004) and HOMA-IR (P = 0.0001, P = 0.0004). As compared with wild type, CAV1 knockout mice displayed higher blood pressure levels and higher fasting glucose, insulin, and HOMA-IR levels and an exaggerated glycemic response to a glucose challenge. CONCLUSION Variations in the CAV1 gene are associated with IR and hypertension. CAV1 gene polymorphisms may be a biomarker for IR and hypertension, enabling earlier detection and improved treatment strategies.
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Levin G, Kestenbaum B, Ida Chen YD, Jacobs DR, Psaty BM, Rotter JI, Siscovick DS, de Boer IH. Glucose, insulin, and incident hypertension in the multi-ethnic study of atherosclerosis. Am J Epidemiol 2010; 172:1144-54. [PMID: 20961972 DOI: 10.1093/aje/kwq266] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Diabetes mellitus and hypertension commonly coexist, but the nature of this link is not well understood. The authors tested whether diabetes and higher concentrations of fasting serum glucose and insulin are associated with increased risk of developing incident hypertension in the community-based Multi-Ethnic Study of Atherosclerosis. At baseline, 3,513 participants were free of hypertension, defined as systolic blood pressure ≥140 mm Hg, diastolic blood pressure ≥90 mm Hg, or use of antihypertensive medications to treat high blood pressure. Of these, 965 participants (27%) developed incident hypertension over 4.7 years' median follow-up between 2002 and 2007. Compared with participants with normal baseline fasting glucose, those with impaired fasting glucose and diabetes had adjusted relative risks of hypertension of 1.16 (95% confidence interval (CI): 0.96, 1.40) and 1.41 (95% CI: 1.17, 1.71), respectively (P = 0.0015). The adjusted relative risk of incident hypertension was 1.08 (95% CI: 1.04, 1.13) for each mmol/L higher glucose (P < 0.0001) and 1.15 (95% CI: 1.05, 1.25) for each doubling of insulin (P = 0.0016). Further adjustment for serum cystatin C, urinary albumin/creatinine ratio, and arterial elasticity measured by tonometry substantially reduced the magnitudes of these associations. In conclusion, diabetes and higher concentrations of glucose and insulin may contribute to the development of hypertension, in part through kidney disease and arterial stiffness.
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Affiliation(s)
- Gregory Levin
- Cedars-Sinai Medical Center, Los Angeles, California, USA
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A statistical investigation into the sharing of common genetic factors between blood pressure and obesity phenotypes in nuclear families from the Greater Bilbao (Spain). J Hypertens 2010; 28:723-31. [DOI: 10.1097/hjh.0b013e328336ecf3] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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25
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Kopf D, Cheng LSC, Blandau P, Hsueh W, Raffel LJ, Buchanan TA, Xiang AH, Davis RC, Rotter JI, Lehnert H. Association of insulin sensitivity and glucose tolerance with the c.825C>T variant of the G protein beta-3 subunit gene. J Diabetes Complications 2008; 22:205-9. [PMID: 18413224 PMCID: PMC2695761 DOI: 10.1016/j.jdiacomp.2006.12.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2006] [Revised: 11/17/2006] [Accepted: 12/19/2006] [Indexed: 10/22/2022]
Abstract
UNLABELLED The risk of macrovascular complications of diabetes mellitus is greatly enhanced by the presence of high blood pressure. In addition, hypertension and diabetes share insulin resistance as a common pathophysiological mechanism. Despite evidence for a common molecular genetic background of insulin resistance, glucose intolerance, and hypertension, few candidate genes have been shown to influence all of these features simultaneously. We examined the association of insulin sensitivity with the c.825C>T variant of the g-protein beta-3 subunit (GNB3), a candidate gene of hypertension, in families of Mexican-American hypertensive patients. METHODS One hundred eighty subjects enrolled in a family study of Mexican-American hypertensive patients were recruited from hypertension clinics in Los Angeles. Subjects underwent pretreatment blood pressure recording, an oral glucose tolerance test, euglycemic hyperinsulinemic clamp, and anthropometric measurements. DNA from peripheral blood leukocytes was genotyped by polymerase chain reaction and restriction enzyme digest with BseD1 (GNB). Statistical analysis was performed by transmission disequilibrium testing. RESULTS In carriers of the T-allele, blood glucose was significantly lower [(mean+S.D.) fasting: 96.7+22.9 vs. 106.7+51.7mg/dl, P=.009; oral glucose tolerance test (oGTT) 120 min: 131.7+48.7 vs. 137.8+64.9 mg/dl, P=.036], and insulin sensitivity was significantly higher (229.0+108.7 vs. 188.5+94.2 mg/kg per minute, P=.037) than in homozygous carriers of the C-allele. Blood pressure did not differ significantly between the phenotypes. CONCLUSION In a Mexican-American hypertensive population, we found evidence for higher insulin sensitivity in carriers of the T allele of the c.825C>T variant of GNB3.
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Affiliation(s)
- Daniel Kopf
- Department of Endocrinology and Metabolism, University of Magdeburg, Magdeburg, Germany.
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26
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Tang W, Hong Y, Province MA, Rich SS, Hopkins PN, Arnett DK, Pankow JS, Miller MB, Eckfeldt JH. Familial clustering for features of the metabolic syndrome: the National Heart, Lung, and Blood Institute (NHLBI) Family Heart Study. Diabetes Care 2006; 29:631-6. [PMID: 16505518 DOI: 10.2337/diacare.29.03.06.dc05-0679] [Citation(s) in RCA: 52] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Metabolic syndrome-related traits (obesity, glucose intolerance/insulin resistance, dyslipidemia, and hypertension) have been shown to be genetically correlated. It is less clear, however, if the genetic correlation extends to novel risk factors associated with inflammation, impaired fibrinolytic activity, and hyperuricemia. We present a bivariate genetic analysis of MetS-related traits including both traditional and novel risk factors. RESEARCH DESIGN AND METHODS Genetic correlations were estimated using a variance components procedure in 1,940 nondiabetic white individuals from 445 families in the National Heart, Lung, and Blood Institute (NHLBI) Family Heart Study. Twelve MetS-related traits, including BMI, waist circumference, blood pressure, white blood cell count, fasting serum triglycerides, HDL cholesterol, insulin, glucose, plasminogen activator inhibitor-1 antigen, uric acid, and C-reactive protein, were measured and adjusted for covariates, including lifestyle variables. RESULTS Significant genetic correlations were detected among BMI, waist circumference, HDL cholesterol, triglycerides, insulin, and plasminogen activator inhibitor-1 antigen and between uric acid and all of the above variables except insulin. C-reactive protein and white blood cell count were genetically correlated with each other, and both showed significant genetic correlations with waist circumference and insulin. Fasting glucose was not significantly genetically correlated with any of the other traits. CONCLUSIONS These results suggest that pleiotropic effects of genes or shared family environment contribute to the familial clustering of MetS-related traits.
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Affiliation(s)
- Weihong Tang
- Division of Epidemiology and Community Health, University of Minnesota, 1300 South Second St., Suite 300, Minneapolis, MN 55454, USA.
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Rich SS, Bowden DW, Haffner SM, Norris JM, Saad MF, Mitchell BD, Rotter JI, Langefeld CD, Wagenknecht LE, Bergman RN. Identification of quantitative trait loci for glucose homeostasis: the Insulin Resistance Atherosclerosis Study (IRAS) Family Study. Diabetes 2004; 53:1866-75. [PMID: 15220212 DOI: 10.2337/diabetes.53.7.1866] [Citation(s) in RCA: 48] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Genetic and environmental determinants play critical roles in insulin resistance and beta-cell function. A model of the complex feedback system for maintenance of glucose tolerance has been developed that reflects the constraint of glycemia within narrow physiologic limits. The "glucose homeostasis" model is described by insulin sensitivity (S(I)), glucose disposition (S(G)), acute insulin response to glucose (AIR(G)), and disposition index (DI). Relatively little is known about the genetic basis of glucose homeostasis phenotypes or their relationship to risk of diabetes and atherosclerotic cardiovascular disease. A genome scan for glucose homeostasis phenotypes in nondiabetic subjects has been carried out in African-American (n = 21) and Hispanic (n = 45) extended families as part of the IRAS Family Study. In African-American families, there was significant evidence for linkage of DI between D11S2371 and D11S2002 (logarithm of odds [LOD] = 3.21) at 81 cM, and in the combined sample of African-American and Hispanic families, there was evidence at GATA117D01 (140 cM) on chromosome 11 (LOD = 2.21). Evidence of linkage was also observed for S(I) in Hispanic (LOD = 2.28, between D15S822 and GTTTT001) and AIR(G) in African-American families (LOD = 2.73, between D4S1625 and D4S1629; and LOD = 2.56 at PAH (phenylalanine hydroxylase) on chromosome 12). These results provide impetus for future positional cloning of quantitative trait loci (QTLs). Identifying genes in these regions should provide insight into the nature of the metabolic syndrome and diabetes, and facilitate the development of more effective therapies for prevention and treatment of diabetes and other diseases associated with disordered glucose metabolism.
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Affiliation(s)
- Stephen S Rich
- Department of Public Health Sciences, Wake Forest University School of Medicine, 3rd Floor, MRI Center, Winston-Salem, NC 27157, USA.
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Chen H, Sullivan G, Yue LQ, Katz A, Quon MJ. QUICKI is a useful index of insulin sensitivity in subjects with hypertension. Am J Physiol Endocrinol Metab 2003; 284:E804-12. [PMID: 12678026 DOI: 10.1152/ajpendo.00330.2002] [Citation(s) in RCA: 97] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Insulin resistance may link disorders of metabolic homeostasis such as diabetes and obesity with disorders of hemodynamic homeostasis such as hypertension. Thus it is of interest to validate simple methods for quantifying insulin sensitivity in hypertensive patients. The quantitative insulin-sensitivity check index (QUICKI) is a novel mathematical transformation of fasting blood glucose and insulin levels. In obese and diabetic subjects, QUICKI has a significantly better linear correlation with glucose clamp determinations of insulin sensitivity than minimal-model estimates. To determine whether QUICKI is also useful in hypertensive subjects, we performed glucose clamps and frequently sampled intravenous glucose tolerance tests (FSIVGTT) on 27 hypertensive subjects taken off antihypertensive medication. Indexes of insulin sensitivity derived from glucose clamp studies (SIClamp) were compared with QUICKI, minimal-model analysis of FSIVGTTs (SIMM), and homeostasis model assessment (HOMA). The correlation between QUICKI and SIClamp ( r = 0.84) was significantly better than that between SIMM and SIClamp( r = 0.65; P < 0.028). The correlation between QUICKI and SIClamp was comparable to that between 1/HOMA and SIClamp ( r = 0.82). When studies were repeated in 14 subjects who had resumed antihypertensive medications, the percent changes in SIClamp for each of these patients were significantly correlated with percent changes in QUICKI ( r = 0.61) and HOMA ( r = −0.54) but not SIMM ( r = −0.18). We conclude that QUICKI is a simple, robust index of insulin sensitivity that is useful for evaluating and following the insulin resistance of hypertensive subjects in both research studies and clinical practice.
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Affiliation(s)
- Hui Chen
- National Center for Complementary and Alternative Medicine, National Institutes of Health, Bethesda, 20892.
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29
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Hwu CM, Hsiao CF, Sheu WHH, Pei D, Tai TY, Quertermous T, Rodriguez B, Pratt R, Chen YDI, Ho LT. Sagittal abdominal diameter is associated with insulin sensitivity in Chinese hypertensive patients and their siblings. J Hum Hypertens 2003; 17:193-8. [PMID: 12624610 DOI: 10.1038/sj.jhh.1001532] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
The purpose of the study is to observe the relation between anthropometric measurements, focusing on sagittal abdominal diameter (SAD), and insulin sensitivity indices in Chinese hypertensive patients and their siblings. In total, 907 participants, 537 hypertensive and 370 nonhypertensive, from 311 Taiwanese families were drawn from the Stanford Asia and Pacific Program for Hypertension and Insulin Resistance for the study. The participants received anthropometric measurements and 75-g oral glucose tolerance tests after an overnight fast. Fasting insulin, homeostasis model assessment for insulin resistance (HOMA-IR), and the insulin sensitivity index ISI(0,120) were chosen as surrogate measures of insulin sensitivity. In addition to Pearson and partial correlations, we used generalized estimating equations (GEEs) to examine the association between anthropometric measurements and insulin sensitivity indices. A small deviance in the GEEs indicates the goodness of model fit, irrespective of the independence among variables. The hypertensive patients were older in age, wider in waist circumference (WC), larger in body mass index (BMI) and SAD, and more insulin resistant than the nonhypertensive counterparts. The logarithmic transformation of fasting insulin, HOMA-IR, and ISI(0,120) significantly correlated with SAD, WC, and BMI before and after adjustments for age and sex. The deviances of SAD in the GEEs were similar to those of WC in all subjects, while BMI had smaller deviances than SAD and WC in the hypertensive patients. Our results suggest that the performance of SAD in predicting insulin sensitivity is comparable with WC in Chinese hypertensive patients and their siblings. BMI, however, seems to have better association with insulin sensitivity than SAD and WC in the patients with hypertension.
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Affiliation(s)
- C-M Hwu
- Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.
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30
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An P, Hong Y, Weisnagel SJ, Rice T, Rankinen T, Leon AS, Skinner JS, Wilmore JH, Chagnon YC, Bergman RN, Bouchard C, Rao DC. Genomic scan of glucose and insulin metabolism phenotypes: the HERITAGE Family Study. Metabolism 2003; 52:246-53. [PMID: 12601641 DOI: 10.1053/meta.2003.50030] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Genetic factors play a role in the regulation of glucose metabolism-related traits such as insulin sensitivity (S(I)), insulin secretion, and glucose effectiveness (S(G)). Several genomic scans have been performed to localize genes involved in glucose metabolism-related traits. However, few of these studies have been performed with phenotypes derived from the frequently sampled intravenous glucose tolerance test (IVGTT) using the minimal modeling (MINMOD) approach. Here, we report on such a scan for glucose metabolism-related traits derived from MINMOD analysis of IVGTT data in 322 sibling pairs from 95 sedentary white families and 75 sibling pairs from 49 sedentary black families from the HERITAGE Family Study. In addition to S(I) and S(G), we also considered acute insulin response to a glucose challenge (AIR(Glucose)), which is an index for insulin secretion, and disposition index (DI, product of S(I) and AIR(Glucose)), which is a measure of the activity of pancreatic beta cells corrected for insulin resistance. These traits were adjusted for age, sex, and body mass index (BMI) in each of 8 sex-by-generation-by-race groups, and then standardized residuals were used as the phenotypes in the linkage analyses. Analyses were with the multipoint variance components linkage method, as implemented in the computer program SEGPATH, using 509 markers. Several regions with promising linkages (LOD score >/= 1.75, P </=.0023) were detected. They include five regions (1q41 and 8p23.2 for S(I), 4q32.1 and 10p15.3 for AIR(Glucose), and 13q32.1 for DI) in whites and 2 regions (9p11.2 for S(G) and 10q26.11 for S(I)) in blacks. Three of these regions (4q32.1, 9p11.2, 10p15.3) are likely to harbor genes that influence interindividual variation in glucose metabolism-related traits as they replicate findings from other studies. Fine mapping and association studies of candidate genes within these genomic regions are warranted.
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Affiliation(s)
- Ping An
- Division of Biostatistics, and the Department of Genetics, Washington University School of Medicine, St Louis, MO 63110, USA
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Kwiterovich PO. Clinical relevance of the biochemical, metabolic, and genetic factors that influence low-density lipoprotein heterogeneity. Am J Cardiol 2002; 90:30i-47i. [PMID: 12419479 DOI: 10.1016/s0002-9149(02)02749-2] [Citation(s) in RCA: 128] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Traditional risk factors for coronary artery disease (CAD) predict about 50% of the risk of developing CAD. The Adult Treatment Panel (ATP) III has defined emerging risk factors for CAD, including small, dense low-density lipoprotein (LDL). Small, dense LDL is often accompanied by increased triglycerides (TGs) and low high-density lipoprotein (HDL). An increased number of small, dense LDL particles is often missed when the LDL cholesterol level is normal or borderline elevated. Small, dense LDL particles are present in families with premature CAD and hyperapobetalipoproteinemia, familial combined hyperlipidemia, LDL subclass pattern B, familial dyslipidemic hypertension, and syndrome X. The metabolic syndrome, as defined by ATP III, incorporates a number of the components of these syndromes, including insulin resistance and intra-abdominal fat. Subclinical inflammation and elevated procoagulants also appear to be part of this atherogenic syndrome. Overproduction of very low-density lipoproteins (VLDLs) by the liver and increased secretion of large, apolipoprotein (apo) B-100-containing VLDL is the primary metabolic characteristic of most of these patients. The TG in VLDL is hydrolyzed by lipoprotein lipase (LPL) which produces intermediate-density lipoprotein. The TG in intermediate-density lipoprotein is hydrolyzed further, resulting in the generation of LDL. The cholesterol esters in LDL are exchanged for TG in VLDL by the cholesterol ester tranfer proteins, followed by hydrolysis of TG in LDL by hepatic lipase which produces small, dense LDL. Cholesterol ester transfer protein mediates a similar lipid exchange between VLDL and HDL, producing a cholesterol ester-poor HDL. In adipocytes, reduced fatty acid trapping and retention by adipose tissue may result from a primary defect in the incorporation of free fatty acids into TGs. Alternatively, insulin resistance may promote reduced retention of free fatty acids by adipocytes. Both these abnormalities lead to increased levels of free fatty acids in plasma, increased flux of free fatty acids back to the liver, enhanced production of TGs, decreased proteolysis of apo B-100, and increased VLDL production. Decreased removal of postprandial TGs often accompanies these metabolic abnormalities. Genes regulating the expression of the major players in this metabolic cascade, such as LPL, cholesterol ester transfer protein, and hepatic lipase, can modulate the expression of small, dense LDL but these are not the major defects. New candidates for major gene effects have been identified on chromosome 1. Regardless of their fundamental causes, small, dense LDL (compared with normal LDL) particles have a prolonged residence time in plasma, are more susceptible to oxidation because of decreased interaction with the LDL receptor, and enter the arterial wall more easily, where they are retained more readily. Small, dense LDL promotes endothelial dysfunction and enhanced production of procoagulants by endothelial cells. Both in animal models of atherosclerosis and in most human epidemiologic studies and clinical trials, small, dense LDL (particularly when present in increased numbers) appears more atherogenic than normal LDL. Treatment of patients with small, dense LDL particles (particularly when accompanied by low HDL and hypertriglyceridemia) often requires the use of combined lipid-altering drugs to decrease the number of particles and to convert them to larger, more buoyant LDL. The next critical step in further reduction of CAD will be the correct diagnosis and treatment of patients with small, dense LDL and the dyslipidemia that accompanies it.
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Affiliation(s)
- Peter O Kwiterovich
- Lipid Research Atherosclerosis Division, Departments of Pediatrics and Medicine, the Johns Hopkins University School of Medicine, University Lipid Clinic, Baltimore, Maryland 21205, USA.
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Rubiés-Prat J, Pedro-Botet J. [Arterial hypertension and atherosclerosis: beyond hemodynamic stress]. Med Clin (Barc) 2001; 117:497-9. [PMID: 11707206 DOI: 10.1016/s0025-7753(01)72156-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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