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Genetic Variants Associated with Quantitative Glucose Homeostasis

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Genetic Variants Associated with Quantitative Glucose Homeostasis Page 3 of 127 Diabetes Genetic Variants Associated with Quantitative Glucose Homeostasis Traits Translate to Type 2 Diabetes in Mexican Americans: The GUARDIAN (Genetics Underlying Diabetes in Hispanics) Consortium Running Title: Glucose Homeostasis in the GUARDIAN Consortium Nicholette D. Palmer1,2,3,4*, Mark O. Goodarzi5,6*, Carl D. Langefeld4,7*, Nan Wang9,41*, Xiuqing Guo15,16, Kent D. Taylor15,16, Tasha E. Fingerlin11,12, Jill M. Norris11, Thomas A. Buchanan8,13,41, Anny H. Xiang14, Talin Haritunians6, Julie T. Ziegler4,7, Adrienne H. Williams4,7, Darko Stefansovski6, Jinrui Cui6, Adrienne W. Mackay9, Leora F. Henkin4,17, Richard N. Bergman10, Xiaoyi Gao9,28, James Gauderman9,28, Rohit Varma28, Craig L. Hanis21, Nancy J. Cox29, Heather M. Highland21, Jennifer E. Below21, Amy L. Williams19,30,31, Noel P. Burtt19, Carlos A. Aguilar- Salinas32, Alicia Huerta-Chagoya32,33, Clicerio Gonzalez-Villalpando34, Lorena Orozco35, Christopher A. Haiman9, Michael Y. Tsai18, W. Craig Johnson36, Jie Yao15, Laura Rasmussen- Torvik37, James Pankow38, Beverly Snively7, Rebecca D. Jackson39, Simin Liu40, Jerry L. Nadler24, Fouad Kandeel25, Yii-Der I. Chen15,16, Donald W. Bowden1,2,3,26 Stephen S. Rich27, Leslie J. Raffel6, Jerome I. Rotter15,16†, Richard M. Watanabe8,9,41†, Lynne E. Wagenknecht4,17† *These authors contributed equally to this work †These authors jointly directed this work and are co-corresponding authors 1Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA 2Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA 3Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA 4Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA 5Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 6Medical Genetics Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 7Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC 8Department of Physiology and Biophysics, Keck School of Medicine of USC, Los Angeles, CA 9Department of Preventive Medicine, Keck School of Medicine of USC, Los Angeles, CA 10Cedars-Sinai Diabetes and Obesity Research Institute, Los Angeles, CA 11Departments of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, CO 12Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver, Aurora, CO 13Department of Medicine, Keck School of Medicine of USC, Los Angeles, CA 14Research and Evaluation Branch, Kaiser Permanente of Southern California, Pasadena, CA 15Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA 16Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA 17Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC 18Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN 19Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 20Department of Genetics, Harvard Medical School, Boston, MA 21Human Genetics Center, School of Public Health, University of Texas Health Science Center, Houston, TX 22Department of Ophthalmology, Keck School of Medicine, University of Southern California, Los Angeles, CA 23Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 24Department of Medicine, Eastern Virginia Medical School, Norfolk, VA 25Department of Diabetes, Endocrinology and Metabolism, City of Hope, Duarte, California 26Section on Endocrinology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA 28UIC Department of Ophthalmology and Visual Sciences, Illinois Eye and Ear Infirmary, Chicago, IL 29Department of Human Genetics, University of Chicago, Chicago, IL 30Howard Hughes Medical Institute, Chicago, IL 31Biological Sciences Department, Columbia University, New York, NY 32Endocrinologia y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico 33Universidad Nacional Autónoma de México, Mexico City, Mexico 34Centro de Estudios en Diabetes Instituto Nacional de Salud Publica, Mexico 35Instituto Nacional de Medicina Genómica 36Collaborative Health Studies Coodinating Center, Department of Biostatistics, University of Washington, Seattle, WA 37Preventive Medicine-Epidemiology, Northwestern University Feinberg School of Medicine, Evanston, IL 38Division of Epidemiology & Community Health, University of Minnesota, Minneapolis, MN 39Ohio State University Medical Center, Columbus, OH 1 Diabetes Publish Ahead of Print, published online December 18, 2014 Diabetes Page 4 of 127 40Department of Epidemiology, Brown University, Providence, RI 41USC Diabetes and Obesity Research Institute, Keck School of Medicine of USC, Los Angeles, CA Corresponding Authors: Jerome I. Rotter Harbor-UCLA Medical Center 1124 W. Carson Street, Bldg., E-5 Torrance, CA 90502 Phone: 310-974-9501 E-mail: [email protected] Richard M. Watanabe Keck School of Medicine of USC 2250 Alcazar Street, Suite 200 Los Angeles, CA 90033 Phone: 323-442-2053 Fax: 323-442-2349 E-Mail: [email protected] Lynne E. Wagenknecht Wake Forest School of Medicine 1 Medical Center Blvd. Winston-Salem, NC 27157, USA Phone: 336-716-7652 Fax: 336-716-6427 E-mail: [email protected] Journal: Diabetes Word Count (max. 4000): 200 (abstract), 4000 (body) References (max 50): 50 Number of Tables and Figures (max. 8): 6 2 Page 5 of 127 Diabetes ABSTRACT Insulin sensitivity, insulin secretion, insulin clearance, and glucose effectiveness exhibit strong genetic components although few studies have examined their genetic architecture or their influence on type 2 diabetes (T2D) risk. We hypothesized that loci affecting variation in these quantitative traits influence T2D. We completed a multi-cohort 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 (4 cohorts) or euglycemic clamp (3 cohorts) and random effects models were used to test association between loci and quantitative traits, adjusting for age, gender, and admixture proportions (Discovery). Analysis revealed significant (P<5.00x10-8) 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 cases and 9,232 controls of Mexican ancestry (Translation). Non-parametric 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 risk for T2D. 3 Diabetes Page 6 of 127 INTRODUCTION The pathophysiologic basis of type 2 diabetes (T2D) reflects derangements in both insulin sensitivity and beta-cell function(1). Alterations in insulin clearance and glucose effectiveness may also contribute to the development of T2D(2). Genome-wide association studies (GWAS) of T2D have focused almost entirely on clinical presentation of disease and not on these underlying pathophysiologic traits. Expanding the focus to include the genetic basis of insulin sensitivity and beta-cell function has the potential to expand our knowledge of the pathophysiologic pathways underlying T2D. To date, GWAS of T2D and related traits have been conducted primarily in European origin populations(3). However, the prevalence of T2D and related traits vary by ethnicity, suggesting differential genetic architecture will provide important insight into T2D diathesis. GWAS in case/control samples of T2D have had a substantial impact on the current understanding of genetic susceptibility to disease, implicating variants in at least 70 genes/regions that each have relatively small individual effects but are common in the general population(4). Most identified T2D genes appear to mediate their influence through the beta-cell and not through insulin resistance. These data contrast with other evidence and the widely accepted belief that insulin resistance is a major(5; 6) heritable(7-10) component of T2D susceptibility. This suggests that insulin resistance is a part of the necessary milieu, but is insufficient to cause frank T2D in isolation. GWAS of the underlying pathophysiologic traits of insulin sensitivity and beta-cell function have relied almost entirely on surrogate measures such as homeostasis model assessment (HOMA) parameters(11). While these fasting measures do not reflect the dynamic processes of glucose homeostasis, new T2D loci have been identified through GWAS of basic T2D-related traits such as fasting glucose(11; 12). We have recently documented substantial heritability of direct measures of insulin resistance and insulin clearance in Mexican Americans(13), suggesting that genetic
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