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McAteer JB, Danda S, Nhende T, Manamike P, Parayiwa T, Tarupihwa A, Tapfumanei O, Manangazira P, Mhlanga G, Garone DB, Martinsen A, Aubert RD, Davis W, Narra R, Balachandra S, Tippett Barr BA, Mintz E. Notes from the Field: Outbreak of Vibrio cholerae Associated with Attending a Funeral - Chegutu District, Zimbabwe, 2018. MMWR Morb Mortal Wkly Rep 2018; 67:560-561. [PMID: 29771875 PMCID: PMC6048946 DOI: 10.15585/mmwr.mm6719a6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Billings LK, Jablonski KA, Warner AS, Cheng YC, McAteer JB, Tipton L, Shuldiner AR, Ehrmann DA, Manning AK, Dabelea D, Franks PW, Kahn SE, Pollin TI, Knowler WC, Altshuler D, Florez JC. Variation in Maturity-Onset Diabetes of the Young Genes Influence Response to Interventions for Diabetes Prevention. J Clin Endocrinol Metab 2017; 102:2678-2689. [PMID: 28453780 PMCID: PMC5546852 DOI: 10.1210/jc.2016-3429] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2016] [Accepted: 04/21/2017] [Indexed: 11/19/2022]
Abstract
Context Variation in genes that cause maturity-onset diabetes of the young (MODY) has been associated with diabetes incidence and glycemic traits. Objectives This study aimed to determine whether genetic variation in MODY genes leads to differential responses to insulin-sensitizing interventions. Design and Setting This was a secondary analysis of a multicenter, randomized clinical trial, the Diabetes Prevention Program (DPP), involving 27 US academic institutions. We genotyped 22 missense and 221 common variants in the MODY-causing genes in the participants in the DPP. Participants and Interventions The study included 2806 genotyped DPP participants randomized to receive intensive lifestyle intervention (n = 935), metformin (n = 927), or placebo (n = 944). Main Outcome Measures Association of MODY genetic variants with diabetes incidence at a median of 3 years and measures of 1-year β-cell function, insulinogenic index, and oral disposition index. Analyses were stratified by treatment group for significant single-nucleotide polymorphism × treatment interaction (Pint < 0.05). Sequence kernel association tests examined the association between an aggregate of rare missense variants and insulinogenic traits. Results After 1 year, the minor allele of rs3212185 (HNF4A) was associated with improved β-cell function in the metformin and lifestyle groups but not the placebo group; the minor allele of rs6719578 (NEUROD1) was associated with an increase in insulin secretion in the metformin group but not in the placebo and lifestyle groups. Conclusions These results provide evidence that genetic variation among MODY genes may influence response to insulin-sensitizing interventions.
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Affiliation(s)
- Liana K. Billings
- Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02114
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114
- Department of Medicine, NorthShore University HealthSystem, Evanston, Illinois 60201
- Department of Medicine, Pritzker School of Medicine, University of Chicago, Chicago, Illinois 60637
| | | | - A. Sofia Warner
- Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114
| | - Yu-Chien Cheng
- Department of Medicine, NorthShore University HealthSystem, Evanston, Illinois 60201
- Department of Medicine, Pritzker School of Medicine, University of Chicago, Chicago, Illinois 60637
| | - Jarred B. McAteer
- Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114
| | - Laura Tipton
- Biostatistics Center, George Washington University, Rockville, Maryland 20852
| | - Alan R. Shuldiner
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland 21201
| | - David A. Ehrmann
- Department of Medicine, Pritzker School of Medicine, University of Chicago, Chicago, Illinois 60637
| | - Alisa K. Manning
- Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02114
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142
| | - Dana Dabelea
- Department of Epidemiology, Colorado School of Public Health, University of Colorado, Denver, Colorado 80045
| | - Paul W. Franks
- Department of Clinical Sciences, Genetic, and Molecular Epidemiology Unit, Lund University Diabetes Center, Skåne University Hospital Malmö, SE-205 02 Malmö, Sweden
| | - Steven E. Kahn
- Division of Metabolism, Endocrinology, and Nutrition, VA Puget Sound Health Care System and University of Washington, Seattle, Washington 98195
| | - Toni I. Pollin
- Departments of Medicine (Division of Endocrinology, Diabetes, and Nutrition) and Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland 21201
| | - William C. Knowler
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona 85014
| | - David Altshuler
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02114
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142
- Vertex Pharmaceuticals, Boston, Massachusetts 02210
| | - Jose C. Florez
- Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02114
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142
| | - for the Diabetes Prevention Program Research Group
- Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02114
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114
- Department of Medicine, NorthShore University HealthSystem, Evanston, Illinois 60201
- Department of Medicine, Pritzker School of Medicine, University of Chicago, Chicago, Illinois 60637
- Biostatistics Center, George Washington University, Rockville, Maryland 20852
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland 21201
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142
- Department of Epidemiology, Colorado School of Public Health, University of Colorado, Denver, Colorado 80045
- Department of Clinical Sciences, Genetic, and Molecular Epidemiology Unit, Lund University Diabetes Center, Skåne University Hospital Malmö, SE-205 02 Malmö, Sweden
- Division of Metabolism, Endocrinology, and Nutrition, VA Puget Sound Health Care System and University of Washington, Seattle, Washington 98195
- Departments of Medicine (Division of Endocrinology, Diabetes, and Nutrition) and Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland 21201
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona 85014
- Vertex Pharmaceuticals, Boston, Massachusetts 02210
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Billings LK, Jablonski KA, Ackerman RJ, Taylor A, Fanelli RR, McAteer JB, Guiducci C, Delahanty LM, Dabelea D, Kahn SE, Franks PW, Hanson RL, Maruthur NM, Shuldiner AR, Mayer-Davis EJ, Knowler WC, Florez JC. The influence of rare genetic variation in SLC30A8 on diabetes incidence and β-cell function. J Clin Endocrinol Metab 2014; 99:E926-30. [PMID: 24471563 PMCID: PMC4010688 DOI: 10.1210/jc.2013-2378] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
CONTEXT/OBJECTIVE The variant rs13266634 in SLC30A8, encoding a β-cell-specific zinc transporter, is associated with type 2 diabetes. We aimed to identify other variants in SLC30A8 that increase diabetes risk and impair β-cell function, and test whether zinc intake modifies this risk. DESIGN/OUTCOME: We sequenced exons in SLC30A8 in 380 Diabetes Prevention Program (DPP) participants and identified 44 novel variants, which were genotyped in 3445 DPP participants and tested for association with diabetes incidence and measures of insulin secretion and processing. We examined individual common variants and used gene burden tests to test 39 rare variants in aggregate. RESULTS We detected a near-nominal association between a rare-variant genotype risk score and diabetes risk. Five common variants were associated with the oral disposition index. Various methods aggregating rare variants demonstrated associations with changes in oral disposition index and insulinogenic index during year 1 of follow-up. We did not find a clear interaction of zinc intake with genotype on diabetes incidence. CONCLUSIONS Individual common and an aggregate of rare genetic variation in SLC30A8 are associated with measures of β-cell function in the DPP. Exploring rare variation may complement ongoing efforts to uncover the genetic influences that underlie complex diseases.
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Affiliation(s)
- Liana K Billings
- Center for Human Genetic Research (L.K.B., R.J.A., A.T., R.R.F., J.B.M., J.C.F.) and Diabetes Research Center (Diabetes Unit) (L.K.B., L.M.D., J.C.F.), Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114; Department of Medicine (L.K.B., L.M.D., J.C.F.), Harvard Medical School, and Department of Nutrition (P.W.F.), Harvard School of Public Health, Boston, Massachusetts 02115; Department of Medicine (L.K.B.), NorthShore University HealthSystem, Evanston, Illinois 60201; University of Chicago (L.K.B.), Pritzker School of Medicine, Chicago, Illinois 60637; The Biostatistics Center (K.A.J.), George Washington University, Rockville, Maryland 20852; Program in Medical and Population Genetics (A.T., J.B.M., C.G., J.C.F.), Broad Institute, Cambridge, Massachusetts 02142; Department of Epidemiology (D.D.), Colorado School of Public Health, University of Colorado, Denver, Colorado 80045; Division of Metabolism, Endocrinology, and Nutrition (S.E.K.), VA Puget Sound Health Care System and University of Washington, Seattle, Washington 98108; Department of Clinical Sciences (P.W.F.), Genetic and Molecular Epidemiology Unit, Lund University, SE-200 41 Malmö, Sweden; Diabetes Epidemiology and Clinical Research Section (R.L.H., W.C.K.), National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, Arizona 85014; Department of Medicine (N.M.M.), Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205; Department of Medicine (A.R.S.), Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland 21201; and Department of Nutrition (E.J.M.-D.), University of North Carolina, Gillings School of Global Public Health, Chapel Hill, North Carolina 27599
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Florez JC, Jablonski KA, McAteer JB, Franks PW, Mason CC, Mather K, Horton E, Goldberg R, Dabelea D, Kahn SE, Arakaki RF, Shuldiner AR, Knowler WC. Effects of genetic variants previously associated with fasting glucose and insulin in the Diabetes Prevention Program. PLoS One 2012; 7:e44424. [PMID: 22984506 PMCID: PMC3439414 DOI: 10.1371/journal.pone.0044424] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2012] [Accepted: 08/03/2012] [Indexed: 11/19/2022] Open
Abstract
Common genetic variants have been recently associated with fasting glucose and insulin levels in white populations. Whether these associations replicate in pre-diabetes is not known. We extended these findings to the Diabetes Prevention Program, a clinical trial in which participants at high risk for diabetes were randomized to placebo, lifestyle modification or metformin for diabetes prevention. We genotyped previously reported polymorphisms (or their proxies) in/near G6PC2, MTNR1B, GCK, DGKB, GCKR, ADCY5, MADD, CRY2, ADRA2A, FADS1, PROX1, SLC2A2, GLIS3, C2CD4B, IGF1, and IRS1 in 3,548 Diabetes Prevention Program participants. We analyzed variants for association with baseline glycemic traits, incident diabetes and their interaction with response to metformin or lifestyle intervention. We replicated associations with fasting glucose at MTNR1B (P<0.001), G6PC2 (P = 0.002) and GCKR (P = 0.001). We noted impaired β-cell function in carriers of glucose-raising alleles at MTNR1B (P<0.001), and an increase in the insulinogenic index for the glucose-raising allele at G6PC2 (P<0.001). The association of MTNR1B with fasting glucose and impaired β-cell function persisted at 1 year despite adjustment for the baseline trait, indicating a sustained deleterious effect at this locus. We also replicated the association of MADD with fasting proinsulin levels (P<0.001). We detected no significant impact of these variants on diabetes incidence or interaction with preventive interventions. The association of several polymorphisms with quantitative glycemic traits is replicated in a cohort of high-risk persons. These variants do not have a detectable impact on diabetes incidence or response to metformin or lifestyle modification in the Diabetes Prevention Program.
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Affiliation(s)
- Jose C. Florez
- Center for Human Genetic Research and Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- * E-mail: (DPPRG); (JCF)
| | - Kathleen A. Jablonski
- The Biostatistics Center, George Washington University, Rockville, Maryland, United States of America
| | - Jarred B. McAteer
- Center for Human Genetic Research and Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
| | - Paul W. Franks
- Lund University Diabetes Center, Department of Clinical Sciences, Lund University, Malmö, Sweden
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Clinton C. Mason
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona, United States of America
| | - Kieren Mather
- Division of Endocrinology, Indiana University School of Medicine, Indianapolis, Indiana, United States of America
| | - Edward Horton
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Joslin Diabetes Center, Boston, Massachusetts, United States of America
| | - Ronald Goldberg
- Lipid Disorders Clinic, Division of Endocrinology, Diabetes, and Metabolism, and the Diabetes Research Institute, Leonard M. Miller School of Medicine, University of Miami, Miami, Florida, United States of America
| | - Dana Dabelea
- Department of Preventive Medicine and Biometrics, University of Colorado at Denver and Health Sciences Center, Denver, Colorado, United States of America
| | - Steven E. Kahn
- Division of Metabolism, Endocrinology and Nutrition, Department of Medicine, VA Puget Sound Health Care System and University of Washington, Seattle, Washington, United States of America
| | - Richard F. Arakaki
- Department of Medicine Clinical Research, University of Hawaii, Honolulu, Hawaii, United States of America
| | - Alan R. Shuldiner
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - William C. Knowler
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona, United States of America
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Williams WW, Salem RM, McKnight AJ, Sandholm N, Forsblom C, Taylor A, Guiducci C, McAteer JB, McKay GJ, Isakova T, Brennan EP, Sadlier DM, Palmer C, Söderlund J, Fagerholm E, Harjutsalo V, Lithovius R, Gordin D, Hietala K, Kytö J, Parkkonen M, Rosengård-Bärlund M, Thorn L, Syreeni A, Tolonen N, Saraheimo M, Wadén J, Pitkäniemi J, Sarti C, Tuomilehto J, Tryggvason K, Österholm AM, He B, Bain S, Martin F, Godson C, Hirschhorn JN, Maxwell AP, Groop PH, Florez JC. Association testing of previously reported variants in a large case-control meta-analysis of diabetic nephropathy. Diabetes 2012; 61:2187-94. [PMID: 22721967 PMCID: PMC3402313 DOI: 10.2337/db11-0751] [Citation(s) in RCA: 69] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
We formed the GEnetics of Nephropathy-an International Effort (GENIE) consortium to examine previously reported genetic associations with diabetic nephropathy (DN) in type 1 diabetes. GENIE consists of 6,366 similarly ascertained participants of European ancestry with type 1 diabetes, with and without DN, from the All Ireland-Warren 3-Genetics of Kidneys in Diabetes U.K. and Republic of Ireland (U.K.-R.O.I.) collection and the Finnish Diabetic Nephropathy Study (FinnDiane), combined with reanalyzed data from the Genetics of Kidneys in Diabetes U.S. Study (U.S. GoKinD). We found little evidence for the association of the EPO promoter polymorphism, rs161740, with the combined phenotype of proliferative retinopathy and end-stage renal disease in U.K.-R.O.I. (odds ratio [OR] 1.14, P = 0.19) or FinnDiane (OR 1.06, P = 0.60). However, a fixed-effects meta-analysis that included the previously reported cohorts retained a genome-wide significant association with that phenotype (OR 1.31, P = 2 × 10(-9)). An expanded investigation of the ELMO1 locus and genetic regions reported to be associated with DN in the U.S. GoKinD yielded only nominal statistical significance for these loci. Finally, top candidates identified in a recent meta-analysis failed to reach genome-wide significance. In conclusion, we were unable to replicate most of the previously reported genetic associations for DN, and significance for the EPO promoter association was attenuated.
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Affiliation(s)
- Winfred W. Williams
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Division of Nephrology, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Rany M. Salem
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Endocrine Research Unit, Department of Endocrinology, Children’s Hospital, Boston, Massachusetts
| | - Amy Jayne McKnight
- Nephrology Research, Centre for Public Health, Queen’s University of Belfast, Belfast, U.K
| | - Niina Sandholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
- Department of Biomedical Engineering and Computational Science, Aalto University, Helsinki, Finland
| | - Carol Forsblom
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Andrew Taylor
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Diabetes Research Center (Diabetes Unit), Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Candace Guiducci
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
| | - Jarred B. McAteer
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Diabetes Research Center (Diabetes Unit), Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Gareth J. McKay
- Nephrology Research, Centre for Public Health, Queen’s University of Belfast, Belfast, U.K
| | - Tamara Isakova
- Division of Nephrology, University of Miami, Miller School of Medicine, Miami, Florida
| | - Eoin P. Brennan
- UCD Diabetes Research Centre, Conway Institute, University College Dublin, Belfield, Dublin, Ireland
- School of Medicine, University College Dublin, Belfield, Dublin, Ireland
| | - Denise M. Sadlier
- UCD Diabetes Research Centre, Conway Institute, University College Dublin, Belfield, Dublin, Ireland
- School of Medicine, University College Dublin, Belfield, Dublin, Ireland
- Mater University Hospital, Dublin, Ireland
| | - Cameron Palmer
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Endocrine Research Unit, Department of Endocrinology, Children’s Hospital, Boston, Massachusetts
| | - Jenny Söderlund
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Emma Fagerholm
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Valma Harjutsalo
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
- Department of Chronic Disease Prevention, Welfare and Health Promotion Division, National Institute for Health and Welfare, Helsinki, Finland
| | - Raija Lithovius
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Daniel Gordin
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Kustaa Hietala
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Department of Ophthalmology, Helsinki University Central Hospital, Helsinki, Finland
| | - Janne Kytö
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Department of Ophthalmology, Helsinki University Central Hospital, Helsinki, Finland
| | - Maija Parkkonen
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Milla Rosengård-Bärlund
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Lena Thorn
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Anna Syreeni
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Nina Tolonen
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Markku Saraheimo
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Johan Wadén
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Janne Pitkäniemi
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Cinzia Sarti
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Jaakko Tuomilehto
- Department of Chronic Disease Prevention, Welfare and Health Promotion Division, National Institute for Health and Welfare, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- South Ostrobothnia Central Hospital, Seinäjoki, Finland
| | - Karl Tryggvason
- Division of Matrix Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Anne-May Österholm
- Division of Matrix Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Bing He
- Division of Matrix Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Steve Bain
- Institute of Life Sciences, Swansea University, Swansea, U.K
| | - Finian Martin
- UCD Diabetes Research Centre, Conway Institute, University College Dublin, Belfield, Dublin, Ireland
- School of Biomolecular and Biomedical Sciences, University College Dublin, Belfield, Dublin, Ireland
| | - Catherine Godson
- UCD Diabetes Research Centre, Conway Institute, University College Dublin, Belfield, Dublin, Ireland
- School of Medicine, University College Dublin, Belfield, Dublin, Ireland
| | - Joel N. Hirschhorn
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Endocrine Research Unit, Department of Endocrinology, Children’s Hospital, Boston, Massachusetts
| | - Alexander P. Maxwell
- Nephrology Research, Centre for Public Health, Queen’s University of Belfast, Belfast, U.K
| | - Per-Henrik Groop
- Folkhälsan Institute of Genetics, Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
- Division of Nephrology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
| | - Jose C. Florez
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Diabetes Research Center (Diabetes Unit), Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Corresponding author: Jose C. Florez,
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Palmer ND, McDonough CW, Hicks PJ, Roh BH, Wing MR, An SS, Hester JM, Cooke JN, Bostrom MA, Rudock ME, Talbert ME, Lewis JP, Ferrara A, Lu L, Ziegler JT, Sale MM, Divers J, Shriner D, Adeyemo A, Rotimi CN, Ng MCY, Langefeld CD, Freedman BI, Bowden DW, Voight BF, Scott LJ, Steinthorsdottir V, Morris AP, Dina C, Welch RP, Zeggini E, Huth C, Aulchenko YS, Thorleifsson G, McCulloch LJ, Ferreira T, Grallert H, Amin N, Wu G, Willer CJ, Raychaudhuri S, McCarroll SA, Langenberg C, Hofmann OM, Dupuis J, Qi L, Segrè AV, van Hoek M, Navarro P, Ardlie K, Balkau B, Benediktsson R, Bennett AJ, Blagieva R, Boerwinkle E, Bonnycastle LL, Boström KB, Bravenboer B, Bumpstead S, Burtt NP, Charpentier G, Chines PS, Cornelis M, Couper DJ, Crawford G, Doney ASF, Elliott KS, Elliott AL, Erdos MR, Fox CS, Franklin CS, Ganser M, Gieger C, Grarup N, Green T, Griffin S, Groves CJ, Guiducci C, Hadjadj S, Hassanali N, Herder C, Isomaa B, Jackson AU, Johnson PRV, Jørgensen T, Kao WHL, Klopp N, Kong A, Kraft P, Kuusisto J, Lauritzen T, Li M, Lieverse A, Lindgren CM, Lyssenko V, Marre M, Meitinger T, Midthjell K, Morken MA, Narisu N, Nilsson P, Owen KR, Payne F, Perry JRB, Petersen AK, Platou C, Proença C, Prokopenko I, Rathmann W, Rayner NW, Robertson NR, Rocheleau G, Roden M, Sampson MJ, Saxena R, Shields BM, Shrader P, Sigurdsson G, Sparsø T, Strassburger K, Stringham HM, Sun Q, Swift AJ, Thorand B, Tichet J, Tuomi T, van Dam RM, van Haeften TW, van Herpt T, van Vliet-Ostaptchouk JV, Walters GB, Weedon MN, Wijmenga C, Witteman J, Bergman RN, Cauchi S, Collins FS, Gloyn AL, Gyllensten U, Hansen T, Hide WA, Hitman GA, Hofman A, Hunter DJ, Hveem K, Laakso M, Mohlke KL, Morris AD, Palmer CNA, Pramstaller PP, Rudan I, Sijbrands E, Stein LD, Tuomilehto J, Uitterlinden A, Walker M, Wareham NJ, Watanabe RM, Abecasis GR, Boehm BO, Campbell H, Daly MJ, Hattersley AT, Hu FB, Meigs JB, Pankow JS, Pedersen O, Wichmann HE, Barroso I, Florez JC, Frayling TM, Groop L, Sladek R, Thorsteinsdottir U, Wilson JF, Illig T, Froguel P, van Duijn CM, Stefansson K, Altshuler D, Boehnke M, McCarthy MI, Soranzo N, Wheeler E, Glazer NL, Bouatia-Naji N, Mägi R, Randall J, Johnson T, Elliott P, Rybin D, Henneman P, Dehghan A, Hottenga JJ, Song K, Goel A, Egan JM, Lajunen T, Doney A, Kanoni S, Cavalcanti-Proença C, Kumari M, Timpson NJ, Zabena C, Ingelsson E, An P, O'Connell J, Luan J, Elliott A, McCarroll SA, Roccasecca RM, Pattou F, Sethupathy P, Ariyurek Y, Barter P, Beilby JP, Ben-Shlomo Y, Bergmann S, Bochud M, Bonnefond A, Borch-Johnsen K, Böttcher Y, Brunner E, Bumpstead SJ, Chen YDI, Chines P, Clarke R, Coin LJM, Cooper MN, Crisponi L, Day INM, de Geus EJC, Delplanque J, Fedson AC, Fischer-Rosinsky A, Forouhi NG, Frants R, Franzosi MG, Galan P, Goodarzi MO, Graessler J, Grundy S, Gwilliam R, Hallmans G, Hammond N, Han X, Hartikainen AL, Hayward C, Heath SC, Hercberg S, Hicks AA, Hillman DR, Hingorani AD, Hui J, Hung J, Jula A, Kaakinen M, Kaprio J, Kesaniemi YA, Kivimaki M, Knight B, Koskinen S, Kovacs P, Kyvik KO, Lathrop GM, Lawlor DA, Le Bacquer O, Lecoeur C, Li Y, Mahley R, Mangino M, Manning AK, Martínez-Larrad MT, McAteer JB, McPherson R, Meisinger C, Melzer D, Meyre D, Mitchell BD, Mukherjee S, Naitza S, Neville MJ, Oostra BA, Orrù M, Pakyz R, Paolisso G, Pattaro C, Pearson D, Peden JF, Pedersen NL, Perola M, Pfeiffer AFH, Pichler I, Polasek O, Posthuma D, Potter SC, Pouta A, Province MA, Psaty BM, Rayner NW, Rice K, Ripatti S, Rivadeneira F, Rolandsson O, Sandbaek A, Sandhu M, Sanna S, Sayer AA, Scheet P, Seedorf U, Sharp SJ, Shields B, Sijbrands EJG, Silveira A, Simpson L, Singleton A, Smith NL, Sovio U, Swift A, Syddall H, Syvänen AC, Tanaka T, Tönjes A, Uitterlinden AG, van Dijk KW, Varma D, Visvikis-Siest S, Vitart V, Vogelzangs N, Waeber G, Wagner PJ, Walley A, Ward KL, Watkins H, Wild SH, Willemsen G, Witteman JCM, Yarnell JWG, Zelenika D, Zethelius B, Zhai G, Zhao JH, Zillikens MC, Borecki IB, Loos RJF, Meneton P, Magnusson PKE, Nathan DM, Williams GH, Silander K, Salomaa V, Smith GD, Bornstein SR, Schwarz P, Spranger J, Karpe F, Shuldiner AR, Cooper C, Dedoussis GV, Serrano-Ríos M, Lind L, Palmer LJ, Franks PW, Ebrahim S, Marmot M, Kao WHL, Pramstaller PP, Wright AF, Stumvoll M, Hamsten A, Buchanan TA, Valle TT, Rotter JI, Siscovick DS, Penninx BWJH, Boomsma DI, Deloukas P, Spector TD, Ferrucci L, Cao A, Scuteri A, Schlessinger D, Uda M, Ruokonen A, Jarvelin MR, Waterworth DM, Vollenweider P, Peltonen L, Mooser V, Sladek R. A genome-wide association search for type 2 diabetes genes in African Americans. PLoS One 2012; 7:e29202. [PMID: 22238593 PMCID: PMC3251563 DOI: 10.1371/journal.pone.0029202] [Citation(s) in RCA: 137] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2011] [Accepted: 11/22/2011] [Indexed: 12/16/2022] Open
Abstract
African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P<0.0071), were directionally consistent in the Replication cohort and were associated with T2DM in subjects without nephropathy (P<0.05). Meta-analysis in all cases and controls revealed a single SNP reaching genome-wide significance (P<2.5×10(-8)). SNP rs7560163 (P = 7.0×10(-9), OR (95% CI) = 0.75 (0.67-0.84)) is located intergenically between RND3 and RBM43. Four additional loci (rs7542900, rs4659485, rs2722769 and rs7107217) were associated with T2DM (P<0.05) and reached more nominal levels of significance (P<2.5×10(-5)) in the overall analysis and may represent novel loci that contribute to T2DM. We have identified novel T2DM-susceptibility variants in the African-American population. Notably, T2DM risk was associated with the major allele and implies an interesting genetic architecture in this population. These results suggest that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations.
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Affiliation(s)
- Nicholette D Palmer
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America.
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de Miguel-Yanes JM, Manning AK, Shrader P, McAteer JB, Goel A, Hamsten A, Fox CS, Florez JC, Dupuis J, Meigs JB. Variants at the endocannabinoid receptor CB1 gene (CNR1) and insulin sensitivity, type 2 diabetes, and coronary heart disease. Obesity (Silver Spring) 2011; 19:2031-7. [PMID: 21633404 PMCID: PMC3686489 DOI: 10.1038/oby.2011.135] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Inhibition of the endocannabinoid receptor CB1 improves insulin sensitivity, lowers glycemia, and slows atherosclerosis. We analyzed whether common variants in the gene encoding CB1, CNR1, are associated with insulin resistance, risk of type 2 diabetes (T2D) or coronary heart disease (CHD). We studied 2,411 participants of the Framingham Offspring Study (mean age 60 years, 52% women) for quantitative traits and CHD, and the Framingham SHARe database for T2D risk. We genotyped 19 single-nucleotide polymorphisms (SNPs) that tagged 85% (at r(2) = 0.8) of common (>5%) CNR1 SNPs. Fasting blood glucose and insulin at the 7th (1999-2001) exam were collected. We used age-, sex-, BMI-adjusted models to test additive associations of genotype with homeostasis model assessment of insulin resistance (HOMA(IR)) (linear mixed-effect models), T2D, or CHD. To account for multiple tests of SNPs, we generated empirical P values. The C allele at SNP rs806365 (frequency, 57.4%), ~4.1 kb 3' from CNR1, was associated with increased HOMA(IR) (n = 2,261, β = 0.05 per C, empirical P = 0.01), risk of T2D (674 cases, odds ratio = 1.19 per C, nominal P = 0.01) and CHD (237 cases, hazard ratio = 1.23 per C, nominal P = 0.04). The association of rs806365 with HOMA(IR) was replicated in a meta-analysis of two independent cohorts (National Health and Nutrition Examination Survey III genetic cohort (NHANES-III) plus Partners Case-Control Diabetes Study; 2,540 white individuals, β = 0.037, nominal P = 0.007), but not in the large Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) Consortium (n = 29,248, nominal P = 0.74). The association of rs806365 was not replicated either with T2D in Diabetes Genetics Replication and Meta-analysis (DIAGRAM) (n = 10,128, nominal P = 0.31), or with CHD in PROCARDIS (n = 13,614, nominal P = 0.37). Although supported by initial results, we found no reproducible statistical association of common variation at CNR1 with insulin resistance, T2D, or CHD.
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Majithia AR, Jablonski KA, McAteer JB, Mather KJ, Goldberg RB, Kahn SE, Florez JC. Association of the SLC30A8 missense polymorphism R325W with proinsulin levels at baseline and after lifestyle, metformin or troglitazone intervention in the Diabetes Prevention Program. Diabetologia 2011; 54:2570-4. [PMID: 21779873 PMCID: PMC3444290 DOI: 10.1007/s00125-011-2234-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2011] [Accepted: 06/08/2011] [Indexed: 10/18/2022]
Abstract
AIMS/HYPOTHESIS Individuals with impaired glucose tolerance have increased proinsulin levels, despite normal glucose or C-peptide levels. In the Diabetes Prevention Program (DPP), increased proinsulin levels predicted type 2 diabetes and proinsulin levels were significantly reduced following treatment with metformin, lifestyle modification or troglitazone compared with placebo. Genetic and physiological studies suggest a role for the zinc transporter gene SLC30A8 in diabetes risk, possibly through effects on insulin-processing in beta cells. We hypothesised that the risk allele at the type 2 diabetes-associated missense polymorphism rs13266634 (R325W) in SLC30A8 would predict proinsulin levels in individuals at risk of type 2 diabetes and may modulate response to preventive interventions. METHODS We genotyped rs13266634 in 3,007 DPP participants and examined its association with fasting proinsulin and fasting insulin at baseline and at 1 year post-intervention. RESULTS We found that increasing dosage of the C risk allele at SLC30A8 rs13266634 was significantly associated with higher proinsulin levels at baseline (p = 0.002) after adjustment for baseline insulin. This supports the hypothesis that risk alleles at SLC30A8 mark individuals with insulin-processing defects. At the 1 year analysis, proinsulin levels decreased significantly in all groups receiving active intervention and were no longer associated with SLC30A8 genotype (p = 0.86) after adjustment for insulin at baseline and 1 year. We found no genotype × treatment interactions at 1 year. CONCLUSIONS/INTERPRETATION In prediabetic individuals, genotype at SLC30A8 predicts baseline proinsulin levels independently of insulin levels, but does not predict proinsulin levels after amelioration of insulin sensitivity at 1 year.
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Affiliation(s)
- A R Majithia
- Center for Human Genetic Research and Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, MA, USA
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Pollin TI, Jablonski KA, McAteer JB, Saxena R, Kathiresan S, Kahn SE, Goldberg RB, Altshuler D, Florez JC. Triglyceride response to an intensive lifestyle intervention is enhanced in carriers of the GCKR Pro446Leu polymorphism. J Clin Endocrinol Metab 2011; 96:E1142-7. [PMID: 21525158 PMCID: PMC3205512 DOI: 10.1210/jc.2010-2324] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
CONTEXT Glucokinase regulatory protein (GCKR) regulates the trafficking and enzymatic activity of hepatic glucokinase, the rate-limiting enzyme in glycogen synthesis and glycolysis. The intronic single-nucleotide polymorphism (SNP) rs780094 (intron 16) and the missense SNP rs1260326 (P446L) in the GCKR gene are strongly associated with increased circulating triglyceride and C-reactive protein levels and, paradoxically, reductions in diabetes incidence, fasting glucose levels, and insulin resistance. OBJECTIVE, SETTING, AND PATIENTS: We sought to replicate these associations and evaluate interactions with lifestyle and metformin interventions in the multiethnic Diabetes Prevention Program (DPP). INTERVENTIONS AND MAIN OUTCOME MEASURES We genotyped the two GCKR SNP in 3346 DPP participants and evaluated association with progression to diabetes and both baseline levels and changes in triglycerides, homeostasis model assessment of insulin resistance (HOMA-IR), oral disposition index, and inflammatory markers along with their interactions with DPP interventions. RESULTS GCKR variation did not predict development of type 2 diabetes. At baseline, the 446L allele was associated with higher triglyceride and C-reactive protein levels (both P < 0.0001) and lower fasting glucose (P = 0.001) and HOMA-IR (P = 0.06). The lifestyle intervention was associated with a decrease in magnitude of the effect of the 446L allele on triglyceride levels (interaction P = 0.04). Metformin was more effective in reducing HOMA-IR in carriers of the P446 allele (interaction P = 0.05). CONCLUSIONS Intensive lifestyle intervention appears to partially mitigate the effect of the 446L allele on higher triglycerides, whereas the P446 allele appears to enhance responsiveness to the HOMA-IR-lowering effect of metformin.
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Affiliation(s)
- Toni I Pollin
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland21201, USA.
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Hivert MF, Jablonski KA, Perreault L, Saxena R, McAteer JB, Franks PW, Hamman RF, Kahn SE, Haffner S, Meigs JB, Altshuler D, Knowler WC, Florez JC. Updated genetic score based on 34 confirmed type 2 diabetes Loci is associated with diabetes incidence and regression to normoglycemia in the diabetes prevention program. Diabetes 2011; 60:1340-8. [PMID: 21378175 PMCID: PMC3064108 DOI: 10.2337/db10-1119] [Citation(s) in RCA: 136] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
OBJECTIVE Over 30 loci have been associated with risk of type 2 diabetes at genome-wide statistical significance. Genetic risk scores (GRSs) developed from these loci predict diabetes in the general population. We tested if a GRS based on an updated list of 34 type 2 diabetes-associated loci predicted progression to diabetes or regression toward normal glucose regulation (NGR) in the Diabetes Prevention Program (DPP). RESEARCH DESIGN AND METHODS We genotyped 34 type 2 diabetes-associated variants in 2,843 DPP participants at high risk of type 2 diabetes from five ethnic groups representative of the U.S. population, who had been randomized to placebo, metformin, or lifestyle intervention. We built a GRS by weighting each risk allele by its reported effect size on type 2 diabetes risk and summing these values. We tested its ability to predict diabetes incidence or regression to NGR in models adjusted for age, sex, ethnicity, waist circumference, and treatment assignment. RESULTS In multivariate-adjusted models, the GRS was significantly associated with increased risk of progression to diabetes (hazard ratio [HR] = 1.02 per risk allele [95% CI 1.00-1.05]; P = 0.03) and a lower probability of regression to NGR (HR = 0.95 per risk allele [95% CI 0.93-0.98]; P < 0.0001). At baseline, a higher GRS was associated with a lower insulinogenic index (P < 0.001), confirming an impairment in β-cell function. We detected no significant interaction between GRS and treatment, but the lifestyle intervention was effective in the highest quartile of GRS (P < 0.0001). CONCLUSIONS A high GRS is associated with increased risk of developing diabetes and lower probability of returning to NGR in high-risk individuals, but a lifestyle intervention attenuates this risk.
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Affiliation(s)
- Marie-France Hivert
- Division of Endocrinology, Department of Medicine, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | | | - Leigh Perreault
- Department of Medicine, Division of Endocrinology, Metabolism and Diabetes, University of Colorado at Denver School of Medicine, Aurora, Colorado
| | - Richa Saxena
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
| | - Jarred B. McAteer
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
| | - Paul W. Franks
- Department of Public Health and Clinical Medicine, Division of Medicine, Genetic Epidemiology and Clinical Research Group, Umeå University Hospital, Umeå, Sweden
- Department of Clinical Sciences, Lund University Diabetes Center, Lund University, Malmö, Sweden
| | - Richard F. Hamman
- Department of Epidemiology, Colorado School of Public Health, University of Colorado at Denver, Aurora, Colorado
| | - Steven E. Kahn
- Division of Metabolism, Endocrinology and Nutrition, Veterans’ Affairs Puget Sound Health Care System and the University of Washington, Seattle, Washington
| | | | | | - James B. Meigs
- General Medicine Unit, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - David Altshuler
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Genetics, Harvard Medical School, Boston, Massachusetts
- Diabetes Research Center (Diabetes Unit), Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - William C. Knowler
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona
| | - Jose C. Florez
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Diabetes Research Center (Diabetes Unit), Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Corresponding author: Jose C. Florez, and
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Dabelea D, Dolan LM, D'Agostino R, Hernandez AM, McAteer JB, Hamman RF, Mayer-Davis EJ, Marcovina S, Lawrence JM, Pihoker C, Florez JC. Association testing of TCF7L2 polymorphisms with type 2 diabetes in multi-ethnic youth. Diabetologia 2011; 54:535-9. [PMID: 21109996 PMCID: PMC3766323 DOI: 10.1007/s00125-010-1982-7] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2010] [Accepted: 10/25/2010] [Indexed: 10/18/2022]
Abstract
AIM/HYPOTHESIS Common variants in the transcription factor 7-like 2 (TCF7L2) gene have been associated with type 2 diabetes in adults. However, it is not known whether TCF7L2 variation increases the risk of early onset type 2 diabetes. Using a case-control design, we examined whether the reported variants [rs12255372 (T/G) and rs7903146 (T/C)] are associated with type 2 diabetes in SEARCH for Diabetes in Youth study participants. METHODS Variants were genotyped in 694 non-Hispanic white (NHW) youth (86 cases, mean age 15.5 years, mean BMI 34.8; and 608 controls, mean age 14.4 years, mean BMI 22.3) and 545 African-American (AA) youth (154 cases, mean age 15.9, mean BMI 37; and 391 controls, mean age 14.8, mean BMI 23.8). Logistic regression adjusted for age, sex, BMI and West African ancestry. RESULTS The association of the risk T allele with case/control status was different in AA and NHW youth (p = 0.025). Among AA youth, each copy of the T allele (rs7903146) was associated with a 1.97-fold (1.37, 2.82) increased odds for type 2 diabetes (p < 0.0001), after adjustment for age, sex, BMI and African ancestry. No significant association was detected in NHW youth (adjusted OR, 1.14; 0.73, 1.79). CONCLUSION/INTERPRETATION TCF7L2 variation is associated with an increased risk of early-onset type 2 diabetes among AA youth, and the association appears to be stronger in AA than NHW youth. This suggests potential different contributions of genetic and environmental factors to early-onset type 2 diabetes by race.
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Affiliation(s)
- D Dabelea
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, 13001 17th Place, Aurora, CO 80045, USA.
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Jablonski KA, McAteer JB, de Bakker PIW, Franks PW, Pollin TI, Hanson RL, Saxena R, Fowler S, Shuldiner AR, Knowler WC, Altshuler D, Florez JC. Common variants in 40 genes assessed for diabetes incidence and response to metformin and lifestyle intervention in the diabetes prevention program. Diabetes 2010; 59:2672-81. [PMID: 20682687 PMCID: PMC3279522 DOI: 10.2337/db10-0543] [Citation(s) in RCA: 208] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
OBJECTIVE Genome-wide association studies have begun to elucidate the genetic architecture of type 2 diabetes. We examined whether single nucleotide polymorphisms (SNPs) identified through targeted complementary approaches affect diabetes incidence in the at-risk population of the Diabetes Prevention Program (DPP) and whether they influence a response to preventive interventions. RESEARCH DESIGN AND METHODS We selected SNPs identified by prior genome-wide association studies for type 2 diabetes and related traits, or capturing common variation in 40 candidate genes previously associated with type 2 diabetes, implicated in monogenic diabetes, encoding type 2 diabetes drug targets or drug-metabolizing/transporting enzymes, or involved in relevant physiological processes. We analyzed 1,590 SNPs for association with incident diabetes and their interaction with response to metformin or lifestyle interventions in 2,994 DPP participants. We controlled for multiple hypothesis testing by assessing false discovery rates. RESULTS We replicated the association of variants in the metformin transporter gene SLC47A1 with metformin response and detected nominal interactions in the AMP kinase (AMPK) gene STK11, the AMPK subunit genes PRKAA1 and PRKAA2, and a missense SNP in SLC22A1, which encodes another metformin transporter. The most significant association with diabetes incidence occurred in the AMPK subunit gene PRKAG2 (hazard ratio 1.24, 95% CI 1.09-1.40, P = 7 × 10(-4)). Overall, there were nominal associations with diabetes incidence at 85 SNPs and nominal interactions with the metformin and lifestyle interventions at 91 and 69 mostly nonoverlapping SNPs, respectively. The lowest P values were consistent with experiment-wide 33% false discovery rates. CONCLUSIONS We have identified potential genetic determinants of metformin response. These results merit confirmation in independent samples.
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Affiliation(s)
- Kathleen A Jablonski
- The Biostatistics Center, George Washington University, Rockville, Maryland, USA.
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Dupuis J, Langenberg C, Prokopenko I, Saxena R, Soranzo N, Jackson AU, Wheeler E, Glazer NL, Bouatia-Naji N, Gloyn AL, Lindgren CM, Mägi R, Morris AP, Randall J, Johnson T, Elliott P, Rybin D, Thorleifsson G, Steinthorsdottir V, Henneman P, Grallert H, Dehghan A, Hottenga JJ, Franklin CS, Navarro P, Song K, Goel A, Perry JRB, Egan JM, Lajunen T, Grarup N, Sparsø T, Doney A, Voight BF, Stringham HM, Li M, Kanoni S, Shrader P, Cavalcanti-Proença C, Kumari M, Qi L, Timpson NJ, Gieger C, Zabena C, Rocheleau G, Ingelsson E, An P, O'Connell J, Luan J, Elliott A, McCarroll SA, Payne F, Roccasecca RM, Pattou F, Sethupathy P, Ardlie K, Ariyurek Y, Balkau B, Barter P, Beilby JP, Ben-Shlomo Y, Benediktsson R, Bennett AJ, Bergmann S, Bochud M, Boerwinkle E, Bonnefond A, Bonnycastle LL, Borch-Johnsen K, Böttcher Y, Brunner E, Bumpstead SJ, Charpentier G, Chen YDI, Chines P, Clarke R, Coin LJM, Cooper MN, Cornelis M, Crawford G, Crisponi L, Day INM, de Geus EJC, Delplanque J, Dina C, Erdos MR, Fedson AC, Fischer-Rosinsky A, Forouhi NG, Fox CS, Frants R, Franzosi MG, Galan P, Goodarzi MO, Graessler J, Groves CJ, Grundy S, Gwilliam R, Gyllensten U, Hadjadj S, Hallmans G, Hammond N, Han X, Hartikainen AL, Hassanali N, Hayward C, Heath SC, Hercberg S, Herder C, Hicks AA, Hillman DR, Hingorani AD, Hofman A, Hui J, Hung J, Isomaa B, Johnson PRV, Jørgensen T, Jula A, Kaakinen M, Kaprio J, Kesaniemi YA, Kivimaki M, Knight B, Koskinen S, Kovacs P, Kyvik KO, Lathrop GM, Lawlor DA, Le Bacquer O, Lecoeur C, Li Y, Lyssenko V, Mahley R, Mangino M, Manning AK, Martínez-Larrad MT, McAteer JB, McCulloch LJ, McPherson R, Meisinger C, Melzer D, Meyre D, Mitchell BD, Morken MA, Mukherjee S, Naitza S, Narisu N, Neville MJ, Oostra BA, Orrù M, Pakyz R, Palmer CNA, Paolisso G, Pattaro C, Pearson D, Peden JF, Pedersen NL, Perola M, Pfeiffer AFH, Pichler I, Polasek O, Posthuma D, Potter SC, Pouta A, Province MA, Psaty BM, Rathmann W, Rayner NW, Rice K, Ripatti S, Rivadeneira F, Roden M, Rolandsson O, Sandbaek A, Sandhu M, Sanna S, Sayer AA, Scheet P, Scott LJ, Seedorf U, Sharp SJ, Shields B, SigurÐsson G, Sijbrands EJG, Silveira A, Simpson L, Singleton A, Smith NL, Sovio U, Swift A, Syddall H, Syvänen AC, Tanaka T, Thorand B, Tichet J, Tönjes A, Tuomi T, Uitterlinden AG, van Dijk KW, van Hoek M, Varma D, Visvikis-Siest S, Vitart V, Vogelzangs N, Waeber G, Wagner PJ, Walley A, Walters GB, Ward KL, Watkins H, Weedon MN, Wild SH, Willemsen G, Witteman JCM, Yarnell JWG, Zeggini E, Zelenika D, Zethelius B, Zhai G, Zhao JH, Zillikens MC, Consortium DIAGRAM, Consortium GIANT, Consortium GBP, Borecki IB, Loos RJF, Meneton P, Magnusson PKE, Nathan DM, Williams GH, Hattersley AT, Silander K, Salomaa V, Smith GD, Bornstein SR, Schwarz P, Spranger J, Karpe F, Shuldiner AR, Cooper C, Dedoussis GV, Serrano-Ríos M, Morris AD, Lind L, Palmer LJ, Hu FB, Franks PW, Ebrahim S, Marmot M, Kao WHL, Pankow JS, Sampson MJ, Kuusisto J, Laakso M, Hansen T, Pedersen O, Pramstaller PP, Wichmann HE, Illig T, Rudan I, Wright AF, Stumvoll M, Campbell H, Wilson JF, Hamsten A, Bergman RN, Buchanan TA, Collins FS, Mohlke KL, Tuomilehto J, Valle TT, Altshuler D, Rotter JI, Siscovick DS, Penninx BWJH, Boomsma DI, Deloukas P, Spector TD, Frayling TM, Ferrucci L, Kong A, Thorsteinsdottir U, Stefansson K, van Duijn CM, Aulchenko YS, Cao A, Scuteri A, Schlessinger D, Uda M, Ruokonen A, Jarvelin MR, Waterworth DM, Vollenweider P, Peltonen L, Mooser V, Abecasis GR, Wareham NJ, Sladek R, Froguel P, Watanabe RM, Meigs JB, Groop L, Boehnke M, McCarthy MI, Florez JC, Barroso I. Erratum: New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet 2010. [DOI: 10.1038/ng0510-464a] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Dupuis J, Langenberg C, Prokopenko I, Saxena R, Soranzo N, Jackson AU, Wheeler E, Glazer NL, Bouatia-Naji N, Gloyn AL, Lindgren CM, Mägi R, Morris AP, Randall J, Johnson T, Elliott P, Rybin D, Thorleifsson G, Steinthorsdottir V, Henneman P, Grallert H, Dehghan A, Hottenga JJ, Franklin CS, Navarro P, Song K, Goel A, Perry JRB, Egan JM, Lajunen T, Grarup N, Sparsø T, Doney A, Voight BF, Stringham HM, Li M, Kanoni S, Shrader P, Cavalcanti-Proença C, Kumari M, Qi L, Timpson NJ, Gieger C, Zabena C, Rocheleau G, Ingelsson E, An P, O’Connell J, Luan J, Elliott A, McCarroll SA, Payne F, Roccasecca RM, Pattou F, Sethupathy P, Ardlie K, Ariyurek Y, Balkau B, Barter P, Beilby JP, Ben-Shlomo Y, Benediktsson R, Bennett AJ, Bergmann S, Bochud M, Boerwinkle E, Bonnefond A, Bonnycastle LL, Borch-Johnsen K, Böttcher Y, Brunner E, Bumpstead SJ, Charpentier G, Chen YDI, Chines P, Clarke R, Coin LJM, Cooper MN, Cornelis M, Crawford G, Crisponi L, Day INM, de Geus E, Delplanque J, Dina C, Erdos MR, Fedson AC, Fischer-Rosinsky A, Forouhi NG, Fox CS, Frants R, Franzosi MG, Galan P, Goodarzi MO, Graessler J, Groves CJ, Grundy S, Gwilliam R, Gyllensten U, Hadjadj S, Hallmans G, Hammond N, Han X, Hartikainen AL, Hassanali N, Hayward C, Heath SC, Hercberg S, Herder C, Hicks AA, Hillman DR, Hingorani AD, Hofman A, Hui J, Hung J, Isomaa B, Johnson PRV, Jørgensen T, Jula A, Kaakinen M, Kaprio J, Kesaniemi YA, Kivimaki M, Knight B, Koskinen S, Kovacs P, Kyvik KO, Lathrop GM, Lawlor DA, Le Bacquer O, Lecoeur C, Li Y, Lyssenko V, Mahley R, Mangino M, Manning AK, Martínez-Larrad MT, McAteer JB, McCulloch LJ, McPherson R, Meisinger C, Melzer D, Meyre D, Mitchell BD, Morken MA, Mukherjee S, Naitza S, Narisu N, Neville MJ, Oostra BA, Orrù M, Pakyz R, Palmer CNA, Paolisso G, Pattaro C, Pearson D, Peden JF, Pedersen NL, Perola M, Pfeiffer AFH, Pichler I, Polasek O, Posthuma D, Potter SC, Pouta A, Province MA, Psaty BM, Rathmann W, Rayner NW, Rice K, Ripatti S, Rivadeneira F, Roden M, Rolandsson O, Sandbaek A, Sandhu M, Sanna S, Sayer AA, Scheet P, Scott LJ, Seedorf U, Sharp SJ, Shields B, Sigurðsson G, Sijbrands EJG, Silveira A, Simpson L, Singleton A, Smith NL, Sovio U, Swift A, Syddall H, Syvänen AC, Tanaka T, Thorand B, Tichet J, Tönjes A, Tuomi T, Uitterlinden AG, van Dijk KW, van Hoek M, Varma D, Visvikis-Siest S, Vitart V, Vogelzangs N, Waeber G, Wagner PJ, Walley A, Walters GB, Ward KL, Watkins H, Weedon MN, Wild SH, Willemsen G, Witteman JCM, Yarnell JWG, Zeggini E, Zelenika D, Zethelius B, Zhai G, Zhao JH, Zillikens MC, Borecki IB, Loos RJF, Meneton P, Magnusson PKE, Nathan DM, Williams GH, Hattersley AT, Silander K, Salomaa V, Smith GD, Bornstein SR, Schwarz P, Spranger J, Karpe F, Shuldiner AR, Cooper C, Dedoussis GV, Serrano-Ríos M, Morris AD, Lind L, Palmer LJ, Hu FB, Franks PW, Ebrahim S, Marmot M, Kao WHL, Pankow JS, Sampson MJ, Kuusisto J, Laakso M, Hansen T, Pedersen O, Pramstaller PP, Wichmann HE, Illig T, Rudan I, Wright AF, Stumvoll M, Campbell H, Wilson JF, Hamsten A, Bergman RN, Buchanan TA, Collins FS, Mohlke KL, Tuomilehto J, Valle TT, Altshuler D, Rotter JI, Siscovick DS, Penninx BWJH, Boomsma D, Deloukas P, Spector TD, Frayling TM, Ferrucci L, Kong A, Thorsteinsdottir U, Stefansson K, van Duijn CM, Aulchenko YS, Cao A, Scuteri A, Schlessinger D, Uda M, Ruokonen A, Jarvelin MR, Waterworth DM, Vollenweider P, Peltonen L, Mooser V, Abecasis GR, Wareham NJ, Sladek R, Froguel P, Watanabe RM, Meigs JB, Groop L, Boehnke M, McCarthy MI, Florez JC, Barroso I. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet 2010; 42:105-16. [PMID: 20081858 PMCID: PMC3018764 DOI: 10.1038/ng.520] [Citation(s) in RCA: 1655] [Impact Index Per Article: 118.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2009] [Accepted: 10/14/2009] [Indexed: 02/08/2023]
Abstract
Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes.
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Affiliation(s)
- Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts 02118, USA
- National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts 01702, USA
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Inga Prokopenko
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LJ, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Richa Saxena
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts 02142, USA
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Nicole Soranzo
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
- Twin Research & Genetic Epidemiology Department, King’s College London, St Thomas' Hospital Campus, Lambeth Palace Rd, London SE1 7EH, UK
| | - Anne U Jackson
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan 48109, USA
| | - Eleanor Wheeler
- Metabolic Disease Group, Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - Nicole L Glazer
- Cardiovascular Health Research Unit and Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Nabila Bouatia-Naji
- CNRS-UMR8090, Pasteur Institute, Lille 2-Droit et Santé University, F-59000 Lille, France
| | - Anna L Gloyn
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LJ, UK
| | - Cecilia M Lindgren
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LJ, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Reedik Mägi
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LJ, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Andrew P Morris
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Joshua Randall
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Toby Johnson
- Department of Medical Genetics, University of Lausanne, 1005 Lausanne, Switzerland
- University Institute of Social and Preventative Medicine, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne, 1005 Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Switzerland
| | - Paul Elliott
- Department of Epidemiology and Public Health, Imperial College of London, Faculty of Medicine, Norfolk Place, London W2 1PG, UK
| | - Denis Rybin
- Boston University Data Coordinating Center, Boston, Massachusetts 02118, USA
| | | | | | - Peter Henneman
- Department of Human Genetics, Leiden University Medical Centre, 2300 RC Leiden, The Netherlands
| | - Harald Grallert
- Institute of Epidemiology, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Abbas Dehghan
- Department of Epidemiology, Erasmus MC Rotterdam, 3000 CA, The Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, VU, Van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands
| | | | - Pau Navarro
- MRC Human Genetics Unit, IGMM, Edinburgh EH4 2XU, UK
| | - Kijoung Song
- Division of Genetics, R&D, Glaxo SmithKline, King of Prussia, Pennsylvania 19406, USA
| | - Anuj Goel
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- Department of Cardiovascular Medicine, University of Oxford, Oxford OX3 9DU, UK
| | - John R B Perry
- Genetics of Complex Traits, Institute of Biomedical and Clinical Sciences, Peninsula College of Medicine and Dentistry, University of Exeter EX1 2LU, UK
| | - Josephine M Egan
- Laboratory of Clinical Investigation, National Institute of Aging, Baltimore, Maryland 21250, USA
| | - Taina Lajunen
- Unit for Child and Adolescent Health and Welfare, National Institute for Health and Welfare, Biocenter Oulu, University of Oulu, 90014 Oulu, Finland
| | - Niels Grarup
- Hagedorn Research Institute, 2820 Gentofte, Denmark
| | | | - Alex Doney
- Department of Medicine & Therapeutics, Level 7, Ninewells Hospital & Medical School, Dundee DD1 9SY, UK
| | - Benjamin F Voight
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts 02142, USA
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Heather M Stringham
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan 48109, USA
| | - Man Li
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland 21287, USA
| | - Stavroula Kanoni
- Department of Nutrition - Dietetics, Harokopio University, 17671 Athens, Greece
| | - Peter Shrader
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts, USA
| | | | - Meena Kumari
- Department of Epidemiology and Public Health, University College London, UK
| | - Lu Qi
- Depts. of Nutrition and Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA
| | - Nicholas J Timpson
- MRC Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol BS8 2PR, UK
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Carina Zabena
- Fundación para la Investigación Biomédica del Hospital Clínico San Carlos, Madrid, Spain
| | - Ghislain Rocheleau
- Departments of Medicine and Human Genetics, McGill University, Montreal, Canada
- Genome Quebec Innovation Centre, Montreal H3A 1A4, Canada
| | - Erik Ingelsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Ping An
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Jeffrey O’Connell
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Amanda Elliott
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts 02142, USA
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Steven A McCarroll
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts 02142, USA
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Felicity Payne
- Metabolic Disease Group, Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - Rosa Maria Roccasecca
- Metabolic Disease Group, Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - François Pattou
- INSERM U859, Universite de Lille-Nord de France, F-59000 Lille, France
| | - Praveen Sethupathy
- Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland 20892, USA
| | - Kristin Ardlie
- The Broad Institute, Cambridge, Massachusetts 02141, USA
| | - Yavuz Ariyurek
- Leiden Genome Technology Center, Leiden University Medical Center, 2300 RC Leiden, The Netherlands
| | - Beverley Balkau
- INSERM U780-IFR69, Paris Sud University, F-94807 Villejuif, France
| | - Philip Barter
- The Heart Research Institute, Sydney, New South Wales, Australia
| | - John P Beilby
- PathWest Laboratory of Western Australia, Department of Molecular Genetics, J Block, QEII Medical Centre, NEDLANDS WA 6009, Australia
- School of Surgery and Pathology, University of Western Australia, Nedlands WA 6009, Australia
| | - Yoav Ben-Shlomo
- Department of Social Medicine, University of Bristol, Bristol BS8 2PR, UK
| | - Rafn Benediktsson
- Landspitali University Hospital, 101 Reykjavik, Iceland
- Icelandic Heart Association, 201 Kopavogur, Iceland
| | - Amanda J Bennett
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LJ, UK
| | - Sven Bergmann
- Department of Medical Genetics, University of Lausanne, 1005 Lausanne, Switzerland
- University Institute of Social and Preventative Medicine, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne, 1005 Lausanne, Switzerland
| | - Murielle Bochud
- University Institute of Social and Preventative Medicine, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne, 1005 Lausanne, Switzerland
| | - Eric Boerwinkle
- The Human Genetics Center and Institute of Molecular Medicine, University of Texas Health Science Center, Houston, Texas 77030, USA
| | - Amélie Bonnefond
- CNRS-UMR8090, Pasteur Institute, Lille 2-Droit et Santé University, F-59000 Lille, France
| | - Lori L Bonnycastle
- Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland 20892, USA
| | - Knut Borch-Johnsen
- Steno Diabetes Center, DK-2820 Gentofte, Copenhagen, Denmark
- Faculty of Health Science, University of Aarhus, Aarhus DK-8000, Denmark
| | - Yvonne Böttcher
- Department of Medicine, University of Leipzig, Liebigstr. 18, 04103 Leipzig, Germany
| | - Eric Brunner
- Department of Epidemiology and Public Health, University College London, UK
| | | | | | - Yii-Der Ida Chen
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Peter Chines
- Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland 20892, USA
| | - Robert Clarke
- Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Oxford OX3 7LF, UK
| | - Lachlan J M Coin
- Department of Epidemiology and Public Health, Imperial College of London, Faculty of Medicine, Norfolk Place, London W2 1PG, UK
| | - Matthew N Cooper
- Centre for Genetic Epidemiology and Biostatistics, University of Western Australia, Perth, Australia
| | - Marilyn Cornelis
- Depts. of Nutrition and Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA
| | - Gabe Crawford
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts 02142, USA
| | - Laura Crisponi
- Istituto di Neurogenetica e Neurofarmacologia (INN), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Monserrato, Cagliari 09042, Italy
| | - Ian N M Day
- MRC Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol BS8 2PR, UK
| | - Eco de Geus
- Department of Biological Psychology, VU, Van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands
| | - Jerome Delplanque
- CNRS-UMR8090, Pasteur Institute, Lille 2-Droit et Santé University, F-59000 Lille, France
| | - Christian Dina
- CNRS-UMR8090, Pasteur Institute, Lille 2-Droit et Santé University, F-59000 Lille, France
| | - Michael R Erdos
- Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland 20892, USA
| | - Annette C Fedson
- Centre for Genetic Epidemiology and Biostatistics, University of Western Australia, Perth, Australia
- Western Australian Sleep Disorders Research Institute, Queen Elizabeth Medical Centre II, Perth, Australia
| | - Antje Fischer-Rosinsky
- Department of Endocrinology, Diabetes and Nutrition, Charite-Universitaetsmedizin Berlin, Berlin, Germany
- Department of Clinical Nutrition, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Nita G Forouhi
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Caroline S Fox
- National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts 01702, USA
- Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Rune Frants
- Department of Human Genetics, Leiden University Medical Centre, 2300 RC Leiden, The Netherlands
| | - Maria Grazia Franzosi
- Department of Cardiovascular Research, Istituto di Ricerche Farmacologiche 'Mario Negri', Milan, Italy
| | - Pilar Galan
- U557 Institut National de la Santé et de la Recherche Médicale, U1125 Institut National de la Recherche Agronomique, Université Paris 13, 74 rue Marcel Cachin, 93017 Bobigny Cedex, France
| | - Mark O Goodarzi
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Jürgen Graessler
- Department of Medicine III, Division Prevention and Care of Diabetes, University of Dresden, 01307 Dresden
| | - Christopher J Groves
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LJ, UK
| | - Scott Grundy
- Center for Human Nutrition, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Rhian Gwilliam
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - Ulf Gyllensten
- Department of Genetics and Pathology, Rudbeck Laboratory, Uppsala University, S-751 85 Uppsala, Sweden
| | - Samy Hadjadj
- CHU de Poitiers, Endocrinologie Diabetologie, CIC INSERM 0802, INSERM U927, Université de Poitiers, UFR, Médecine Pharmacie, Poitiers, France
| | - Göran Hallmans
- Department of Public Health & Clinical Medicine, Section for Nutritional Research, Umeå University, Umeå, Sweden
| | - Naomi Hammond
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - Xijing Han
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan 48109, USA
| | - Anna-Liisa Hartikainen
- Department of Clinical Sciences, Obstetrics and Gynecology, University of Oulu, Box 5000, Fin-90014 University of Oulu, Finland
| | - Neelam Hassanali
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LJ, UK
| | | | - Simon C Heath
- Centre National de Génotypage/IG/CEA, 2 rue Gaston Crémieux CP 5721, 91057 Evry Cedex, France
| | - Serge Hercberg
- U872 Institut National de la Santé et de la Recherche Médicale, Faculté de Médecine Paris Descartes, 15 rue de l’Ecole de Médecine, 75270 Paris Cedex, France
| | - Christian Herder
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Andrew A Hicks
- Institute of Genetic Medicine, European Academy Bozen/Bolzano (EURAC), Viale Druso 1, 39100 Bolzano, Italy, Affiliated Institute of the University Lübeck, Germany
| | - David R Hillman
- Western Australian Sleep Disorders Research Institute, Queen Elizabeth Medical Centre II, Perth, Australia
- Department of Pulmonary Physiology, Sir Charles Gairdner Hospital, Perth, Australia
| | - Aroon D Hingorani
- Department of Epidemiology and Public Health, University College London, UK
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC Rotterdam, 3000 CA, The Netherlands
| | - Jennie Hui
- PathWest Laboratory of Western Australia, Department of Molecular Genetics, J Block, QEII Medical Centre, NEDLANDS WA 6009, Australia
- Busselton Population Medical Research Foundation, Sir Charles Gairdner Hospital, Perth, Australia
| | - Joe Hung
- Heart Institute of Western Australia, Sir Charles Gairdner Hospital, Nedlands WA 6009, Australia
- School of Medicine and Pharmacology, University of Western Australia, Nedlands, WA 6009, Australia
| | - Bo Isomaa
- Folkhalsan Research Centre, Helsinki, Finland
- Malmska Municipal Health Care Center and Hospital, Jakobstad, Finland
| | - Paul R V Johnson
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LJ, UK
- Nuffield Department of Surgery, University of Oxford, Oxford OX3 9DU, UK
| | - Torben Jørgensen
- Research Centre for Prevention and Health, Glostrup University Hospital, Glostrup, Denmark
- Faculty of Health Science, University of Copenhagen, Copenhagen, Denmark
| | - Antti Jula
- National Institute for Health and Welfare, Unit of Population Studies, Turku, Finland
| | - Marika Kaakinen
- Institute of Health Sciences and Biocenter Oulu, Box 5000, Fin-90014 University of Oulu, Finland
| | - Jaakko Kaprio
- Department of Public Health, Faculty of Medicine, P.O. Box 41 (Mannerheimintie 172), University of Helsinki, 00014 Helsinki, Finland
- National Institute for Health and Welfare, Unit for Child and Adolescent Mental Health, Helsinki, Finland
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | | | - Mika Kivimaki
- Department of Epidemiology and Public Health, University College London, UK
| | - Beatrice Knight
- Diabetes Genetics, Institute of Biomedical and Clinical Science, Peninsula College of Medicine and Dentistry, University of Exeter, Exeter EX2 5DW, UK
| | - Seppo Koskinen
- National Institute for Health and Welfare, Unit of Living Conditions, Health and Wellbeing, Helsinki, Finland
| | - Peter Kovacs
- Interdisciplinary Centre for Clinical Research, University of Leipzig, Inselstr. 22, 04103 Leipzig, Germany
| | - Kirsten Ohm Kyvik
- The Danish Twin Registry, Epidemiology, Institute of Public Health, University of Southern Denmark, J.B. Winsløws Vej 9B, 5000 Odense, Denmark
| | - G Mark Lathrop
- Centre National de Génotypage/IG/CEA, 2 rue Gaston Crémieux CP 5721, 91057 Evry Cedex, France
| | - Debbie A Lawlor
- MRC Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol BS8 2PR, UK
| | - Olivier Le Bacquer
- CNRS-UMR8090, Pasteur Institute, Lille 2-Droit et Santé University, F-59000 Lille, France
| | - Cécile Lecoeur
- CNRS-UMR8090, Pasteur Institute, Lille 2-Droit et Santé University, F-59000 Lille, France
| | - Yun Li
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan 48109, USA
| | - Valeriya Lyssenko
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, University Hospital Malmo, Malmo, Sweden
| | - Robert Mahley
- Gladstone Institute of Cardiovascular Disease, University of California, San Francisco, California, USA
| | - Massimo Mangino
- Twin Research & Genetic Epidemiology Department, King’s College London, St Thomas' Hospital Campus, Lambeth Palace Rd, London SE1 7EH, UK
| | - Alisa K Manning
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts 02118, USA
| | | | - Jarred B McAteer
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts 02142, USA
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Laura J McCulloch
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LJ, UK
| | - Ruth McPherson
- Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Ontario, Canada
| | - Christa Meisinger
- Institute of Epidemiology, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - David Melzer
- Genetics of Complex Traits, Institute of Biomedical and Clinical Sciences, Peninsula College of Medicine and Dentistry, University of Exeter EX1 2LU, UK
| | - David Meyre
- CNRS-UMR8090, Pasteur Institute, Lille 2-Droit et Santé University, F-59000 Lille, France
| | - Braxton D Mitchell
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA
| | - Mario A Morken
- Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland 20892, USA
| | - Sutapa Mukherjee
- Western Australian Sleep Disorders Research Institute, Queen Elizabeth Medical Centre II, Perth, Australia
- Department of Pulmonary Physiology, Sir Charles Gairdner Hospital, Perth, Australia
| | - Silvia Naitza
- Istituto di Neurogenetica e Neurofarmacologia (INN), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Monserrato, Cagliari 09042, Italy
| | - Narisu Narisu
- Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland 20892, USA
| | - Matthew J Neville
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LJ, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford OX3 7LJ, UK
| | - Ben A Oostra
- Department of Clinical Genetics, Erasmus MC Rotterdam, 3000 CA, The Netherlands
| | - Marco Orrù
- Istituto di Neurogenetica e Neurofarmacologia (INN), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Monserrato, Cagliari 09042, Italy
| | - Ruth Pakyz
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA
| | - Colin N A Palmer
- Biomedical Research Institute, University of Dundee, Ninewells Hospital & Medical School, Dundee DD1 9SY, UK
| | - Giuseppe Paolisso
- Department of Geriatric Medicine and Metabolic Disease, Second University of Naples, Naples, Italy
| | - Cristian Pattaro
- Institute of Genetic Medicine, European Academy Bozen/Bolzano (EURAC), Viale Druso 1, 39100 Bolzano, Italy, Affiliated Institute of the University Lübeck, Germany
| | - Daniel Pearson
- Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland 20892, USA
| | - John F Peden
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- Department of Cardiovascular Medicine, University of Oxford, Oxford OX3 9DU, UK
| | - Nancy L. Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Markus Perola
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Unit of Public Health Genomics, Helsinki, Finland
- Department of Medical Genetics, University of Helsinki, Helsinki, Finland
| | - Andreas F H Pfeiffer
- Department of Endocrinology, Diabetes and Nutrition, Charite-Universitaetsmedizin Berlin, Berlin, Germany
- Department of Clinical Nutrition, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Irene Pichler
- Institute of Genetic Medicine, European Academy Bozen/Bolzano (EURAC), Viale Druso 1, 39100 Bolzano, Italy, Affiliated Institute of the University Lübeck, Germany
| | - Ozren Polasek
- Department of Medical Statistics, Epidemiology and Medical Informatics, Andrija Stampar School of Public Health, Medical School, University of Zagreb, Rockefellerova 4, 10000 Zagreb, Croatia
| | - Danielle Posthuma
- Department of Biological Psychology, VU, Van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands
- Department of Clinical Genetics, VUMC, Van der Boechorststraat 7, 1081 BT Amsterdam, The Netherlands
| | - Simon C Potter
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - Anneli Pouta
- Department of Obstetrics and Gynaecology, Oulu University Hospital, Oulu, Finland
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Bruce M Psaty
- Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, Washington, USA
- Group Health Center for Health Studies, Seattle, Washington, USA
| | - Wolfgang Rathmann
- Institute of Biometrics and Epidemiology, German Diabetes Centre, Leibniz Centre at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Nigel W Rayner
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LJ, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Kenneth Rice
- Department of Biostatistics, University of Washington, Seattle, Washington 98195, USA
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Unit of Public Health Genomics, Helsinki, Finland
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus MC Rotterdam, 3000 CA, The Netherlands
- Department of Internal Medicine, Erasmus MC Rotterdam, 3000 CA, The Netherlands
| | - Michael Roden
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
- Department of Medicine/Metabolic Diseases, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Olov Rolandsson
- Department of Public Health & Clinical Medicine, Section for Family Medicine, Umeå University Hospital, Umeå, Sweden
| | - Annelli Sandbaek
- School of Public Health, Department of General Practice, University of Aarhus, Aarhus DK-8000, Denmark
| | - Manjinder Sandhu
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
- Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Cambridge, UK
| | - Serena Sanna
- Istituto di Neurogenetica e Neurofarmacologia (INN), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Monserrato, Cagliari 09042, Italy
| | - Avan Aihie Sayer
- MRC Epidemiology Resource Centre, University of Southampton, Southampton General Hospital, Southampton SO16 6YD, UK
| | - Paul Scheet
- Department of Epidemiology, University of Texas, M.D. Anderson Cancer Center, Houston, Texas, 77030, USA
| | - Laura J Scott
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan 48109, USA
| | - Udo Seedorf
- Leibniz-Institut für Arterioskleroseforschung an der Universität Münster,Münster, Germany
| | - Stephen J Sharp
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Beverley Shields
- Diabetes Genetics, Institute of Biomedical and Clinical Science, Peninsula College of Medicine and Dentistry, University of Exeter, Exeter EX2 5DW, UK
| | - Gunnar Sigurðsson
- Landspitali University Hospital, 101 Reykjavik, Iceland
- Icelandic Heart Association, 201 Kopavogur, Iceland
| | - Erik J G Sijbrands
- Department of Epidemiology, Erasmus MC Rotterdam, 3000 CA, The Netherlands
- Department of Internal Medicine, Erasmus MC Rotterdam, 3000 CA, The Netherlands
| | - Angela Silveira
- Atherosclerosis Research Unit, Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Laila Simpson
- Centre for Genetic Epidemiology and Biostatistics, University of Western Australia, Perth, Australia
- Western Australian Sleep Disorders Research Institute, Queen Elizabeth Medical Centre II, Perth, Australia
| | - Andrew Singleton
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, Maryland 20892, USA
| | - Nicholas L Smith
- Department of Epidemiology, University of Washington, Seattle, Washington 98195, USA
- Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, Washington, USA
| | - Ulla Sovio
- Department of Epidemiology and Public Health, Imperial College of London, Faculty of Medicine, Norfolk Place, London W2 1PG, UK
| | - Amy Swift
- Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland 20892, USA
| | - Holly Syddall
- MRC Epidemiology Resource Centre, University of Southampton, Southampton General Hospital, Southampton SO16 6YD, UK
| | | | - Toshiko Tanaka
- Medstar Research Institute, Baltimore, Maryland 21250, USA
- Clinical Research Branch, National Institute on Aging, Baltimore, Maryland 21250, USA
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Jean Tichet
- Institut interrégional pour la santé (IRSA), F-37521 La Riche, France
| | - Anke Tönjes
- Department of Medicine, University of Leipzig, Liebigstr. 18, 04103 Leipzig, Germany
- Coordination Centre for Clinical Trials, University of Leipzig, Härtelstr. 16-18, 04103 Leipzig, Germany
| | - Tiinamaija Tuomi
- Folkhalsan Research Centre, Helsinki, Finland
- Department of Medicine, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus MC Rotterdam, 3000 CA, The Netherlands
- Department of Internal Medicine, Erasmus MC Rotterdam, 3000 CA, The Netherlands
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Centre, 2300 RC Leiden, The Netherlands
- Department of Internal Medicine, Leiden University Medical Centre, 2300 RC Leiden, The Netherlands
| | - Mandy van Hoek
- Department of Internal Medicine, Erasmus MC Rotterdam, 3000 CA, The Netherlands
| | - Dhiraj Varma
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - Sophie Visvikis-Siest
- Research Unit, Cardiovascular Genetics, Nancy University Henri Poincaré, Nancy, France
| | | | - Nicole Vogelzangs
- EMGO Institute/Department of Psychiatry, VU University Medical Center, Amsterdam, The Netherlands
| | - Gérard Waeber
- Department of Internal Medicine, Centre Hospitalier Universitaire Vaudois, 1011 Lausanne, Switzerland
| | - Peter J Wagner
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Unit of Public Health Genomics, Helsinki, Finland
| | - Andrew Walley
- Genomic Medicine, Imperial College London, Hammersmith Hospital, W12 0NN, London, UK
| | | | - Kim L Ward
- Centre for Genetic Epidemiology and Biostatistics, University of Western Australia, Perth, Australia
- Western Australian Sleep Disorders Research Institute, Queen Elizabeth Medical Centre II, Perth, Australia
| | - Hugh Watkins
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- Department of Cardiovascular Medicine, University of Oxford, Oxford OX3 9DU, UK
| | - Michael N Weedon
- Genetics of Complex Traits, Institute of Biomedical and Clinical Sciences, Peninsula College of Medicine and Dentistry, University of Exeter EX1 2LU, UK
| | - Sarah H Wild
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Gonneke Willemsen
- Department of Biological Psychology, VU, Van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands
| | | | - John W G Yarnell
- Epidemiology & Public Health, Queen's University Belfast, Belfast BT12 6BJ, UK
| | - Eleftheria Zeggini
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - Diana Zelenika
- Centre National de Génotypage/IG/CEA, 2 rue Gaston Crémieux CP 5721, 91057 Evry Cedex, France
| | - Björn Zethelius
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
- Medical Products Agency, Uppsala, Sweden
| | - Guangju Zhai
- Twin Research & Genetic Epidemiology Department, King’s College London, St Thomas' Hospital Campus, Lambeth Palace Rd, London SE1 7EH, UK
| | - Jing Hua Zhao
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - M Carola Zillikens
- Department of Internal Medicine, Erasmus MC Rotterdam, 3000 CA, The Netherlands
| | | | | | | | - Ingrid B Borecki
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Ruth J F Loos
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Pierre Meneton
- U872 Institut National de la Santé et de la Recherche Médicale, Faculté de Médecine Paris Descartes, 15 rue de l’Ecole de Médecine, 75270 Paris Cedex, France
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - David M Nathan
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Gordon H Williams
- Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Andrew T Hattersley
- Diabetes Genetics, Institute of Biomedical and Clinical Science, Peninsula College of Medicine and Dentistry, University of Exeter, Exeter EX2 5DW, UK
| | - Kaisa Silander
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Unit of Public Health Genomics, Helsinki, Finland
| | - Veikko Salomaa
- National Institute for Health and Welfare, Unit of Chronic Disease Epidemiology and Prevention, Helsinki, Finland
| | - George Davey Smith
- MRC Centre for Causal Analyses in Translational Epidemiology, University of Bristol, Bristol BS8 2PR, UK
| | - Stefan R Bornstein
- Department of Medicine III, Division Prevention and Care of Diabetes, University of Dresden, 01307 Dresden
| | - Peter Schwarz
- Department of Medicine III, Division Prevention and Care of Diabetes, University of Dresden, 01307 Dresden
| | - Joachim Spranger
- Department of Endocrinology, Diabetes and Nutrition, Charite-Universitaetsmedizin Berlin, Berlin, Germany
- Department of Clinical Nutrition, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Fredrik Karpe
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LJ, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford OX3 7LJ, UK
| | - Alan R Shuldiner
- Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA
| | - Cyrus Cooper
- MRC Epidemiology Resource Centre, University of Southampton, Southampton General Hospital, Southampton SO16 6YD, UK
| | - George V Dedoussis
- Department of Nutrition - Dietetics, Harokopio University, 17671 Athens, Greece
| | - Manuel Serrano-Ríos
- Fundación para la Investigación Biomédica del Hospital Clínico San Carlos, Madrid, Spain
| | - Andrew D Morris
- Biomedical Research Institute, University of Dundee, Ninewells Hospital & Medical School, Dundee DD1 9SY, UK
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Lyle J Palmer
- Centre for Genetic Epidemiology and Biostatistics, University of Western Australia, Perth, Australia
- Western Australian Sleep Disorders Research Institute, Queen Elizabeth Medical Centre II, Perth, Australia
- Busselton Population Medical Research Foundation, Sir Charles Gairdner Hospital, Perth, Australia
| | - Frank B. Hu
- Departments of Nutrition and Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA
- Channing Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Paul W Franks
- Genetic Epidemiology & Clinical Research Group, Department of Public Health & Clinical Medicine, Section for Medicine, Umeå University Hospital, Umeå, Sweden
| | - Shah Ebrahim
- London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
| | - Michael Marmot
- Department of Epidemiology and Public Health, University College London, UK
| | - W H Linda Kao
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland 21287, USA
- Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21287, USA
- The Welch Center for Prevention, Epidemiology, and Clinical Research, School of Medicine and Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland 21287, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota 55454, USA
| | - Michael J Sampson
- Department of Endocrinology and Diabetes, Norfolk and Norwich University Hospital NHS Trust, Norwich, NR1 7UY, UK
| | - Johanna Kuusisto
- Department of Medicine, University of Kuopio and Kuopio University Hospital, Kuopio 70210, Finland
| | - Markku Laakso
- Department of Medicine, University of Kuopio and Kuopio University Hospital, Kuopio 70210, Finland
| | - Torben Hansen
- Hagedorn Research Institute, 2820 Gentofte, Denmark
- Faculty of Health Science, University of Southern Denmark, Odense, Denmark
| | - Oluf Pedersen
- Hagedorn Research Institute, 2820 Gentofte, Denmark
- Faculty of Health Science, University of Aarhus, Aarhus DK-8000, Denmark
- Institute of Biomedical Science, Faculty of Health Science, University of Copenhagen, Denmark
| | - Peter Paul Pramstaller
- Institute of Genetic Medicine, European Academy Bozen/Bolzano (EURAC), Viale Druso 1, 39100 Bolzano, Italy, Affiliated Institute of the University Lübeck, Germany
- Department of Neurology, General Central Hospital, 39100 Bolzano, Italy
- Department of Neurology, University of Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany
| | - H Erich Wichmann
- Institute of Epidemiology, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
- Klinikum Grosshadern, Munich, Germany
| | - Thomas Illig
- Institute of Epidemiology, Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Igor Rudan
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH8 9AG, UK
- School of Medicine, University of Split, Soltanska 2, 21000 Split, Croatia
- Gen-Info Ltd, Ruzmarinka 17, 10000 Zagreb, Croatia
| | - Alan F Wright
- MRC Human Genetics Unit, IGMM, Edinburgh EH4 2XU, UK
| | - Michael Stumvoll
- Department of Medicine, University of Leipzig, Liebigstr. 18, 04103 Leipzig, Germany
| | - Harry Campbell
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH8 9AG, UK
| | - James F Wilson
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Anders Hamsten
- Atherosclerosis Research Unit, Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Richard N Bergman
- Department of Physiology and Biophysics, Keck School of Medicine, University of Southern California, Los Angeles, California 90033, USA
| | - Thomas A Buchanan
- Department of Physiology and Biophysics, Keck School of Medicine, University of Southern California, Los Angeles, California 90033, USA
- Department of Medicine, Division of Endocrinology, Keck School of Medicine, University of Southern California, Los Angeles, California 90033, USA
| | - Francis S Collins
- Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland 20892, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599, USA
| | - Jaakko Tuomilehto
- Department of Public Health, Faculty of Medicine, P.O. Box 41 (Mannerheimintie 172), University of Helsinki, 00014 Helsinki, Finland
- National Institute for Health and Welfare, Unit of Diabetes Prevention, Helsinki, Finland
| | - Timo T Valle
- National Institute for Health and Welfare, Unit of Diabetes Prevention, Helsinki, Finland
| | - David Altshuler
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts 02142, USA
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Jerome I Rotter
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - David S Siscovick
- Departments of Medicine and Epidemiology, University of Washington, Seattle, Washington, USA
| | - Brenda W J H Penninx
- EMGO Institute/Department of Psychiatry, VU University Medical Center, Amsterdam, The Netherlands
| | - Dorret Boomsma
- Department of Biological Psychology, VU, Van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands
| | - Panos Deloukas
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - Timothy D Spector
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
- Twin Research & Genetic Epidemiology Department, King’s College London, St Thomas' Hospital Campus, Lambeth Palace Rd, London SE1 7EH, UK
| | - Timothy M Frayling
- Genetics of Complex Traits, Institute of Biomedical and Clinical Sciences, Peninsula College of Medicine and Dentistry, University of Exeter EX1 2LU, UK
| | - Luigi Ferrucci
- Longitudinal Studies Section, Clinical Research Branch, National Institute on Aging, NIH, Baltimore, Maryland, USA
| | | | - Unnur Thorsteinsdottir
- deCODE Genetics, 101 Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, 101 Reykjavík, Iceland
| | - Kari Stefansson
- deCODE Genetics, 101 Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, 101 Reykjavík, Iceland
| | | | - Yurii S Aulchenko
- Department of Epidemiology, Erasmus MC Rotterdam, 3000 CA, The Netherlands
| | - Antonio Cao
- Istituto di Neurogenetica e Neurofarmacologia (INN), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Monserrato, Cagliari 09042, Italy
| | - Angelo Scuteri
- Istituto di Neurogenetica e Neurofarmacologia (INN), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Monserrato, Cagliari 09042, Italy
- Lab of Cardiovascular Sciences, National Institute on Aging, NIH, Baltimore, Maryland, USA
| | - David Schlessinger
- Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland 20892, USA
| | - Manuela Uda
- Istituto di Neurogenetica e Neurofarmacologia (INN), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Monserrato, Cagliari 09042, Italy
| | - Aimo Ruokonen
- Department of Clinical Sciences/Clinical Chemistry, University of Oulu, Box 5000, Fin-90014 University of Oulu, Finland
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Public Health, Imperial College of London, Faculty of Medicine, Norfolk Place, London W2 1PG, UK
- Institute of Health Sciences and Biocenter Oulu, Box 5000, Fin-90014 University of Oulu, Finland
- National Institute of Health and Welfare, Aapistie 1, P.O. Box 310, Fin-90101 Oulu, Finland
| | - Dawn M Waterworth
- Division of Genetics, R&D, Glaxo SmithKline, King of Prussia, Pennsylvania 19406, USA
| | - Peter Vollenweider
- Department of Internal Medicine, Centre Hospitalier Universitaire Vaudois, 1011 Lausanne, Switzerland
| | - Leena Peltonen
- Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
- The Broad Institute, Cambridge, Massachusetts 02141, USA
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Unit of Public Health Genomics, Helsinki, Finland
- Department of Medical Genetics, University of Helsinki, Helsinki, Finland
| | - Vincent Mooser
- Division of Genetics, R&D, Glaxo SmithKline, King of Prussia, Pennsylvania 19406, USA
| | - Goncalo R Abecasis
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan 48109, USA
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Robert Sladek
- Departments of Medicine and Human Genetics, McGill University, Montreal, Canada
- Genome Quebec Innovation Centre, Montreal H3A 1A4, Canada
| | - Philippe Froguel
- CNRS-UMR8090, Pasteur Institute, Lille 2-Droit et Santé University, F-59000 Lille, France
- Genomic Medicine, Imperial College London, Hammersmith Hospital, W12 0NN, London, UK
| | - Richard M Watanabe
- Department of Physiology and Biophysics, Keck School of Medicine, University of Southern California, Los Angeles, California 90033, USA
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, 90033, USA
| | - James B Meigs
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Leif Groop
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, University Hospital Malmo, Malmo, Sweden
| | - Michael Boehnke
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan 48109, USA
| | - Mark I McCarthy
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LJ, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford OX3 7LJ, UK
| | - Jose C Florez
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts 02142, USA
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Inês Barroso
- Metabolic Disease Group, Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
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Saxena R, Hivert MF, Langenberg C, Tanaka T, Pankow JS, Vollenweider P, Lyssenko V, Bouatia-Naji N, Dupuis J, Jackson AU, Kao WHL, Li M, Glazer NL, Manning AK, Luan J, Stringham HM, Prokopenko I, Johnson T, Grarup N, Boesgaard TW, Lecoeur C, Shrader P, O'Connell J, Ingelsson E, Couper DJ, Rice K, Song K, Andreasen CH, Dina C, Köttgen A, Le Bacquer O, Pattou F, Taneera J, Steinthorsdottir V, Rybin D, Ardlie K, Sampson M, Qi L, van Hoek M, Weedon MN, Aulchenko YS, Voight BF, Grallert H, Balkau B, Bergman RN, Bielinski SJ, Bonnefond A, Bonnycastle LL, Borch-Johnsen K, Böttcher Y, Brunner E, Buchanan TA, Bumpstead SJ, Cavalcanti-Proença C, Charpentier G, Chen YDI, Chines PS, Collins FS, Cornelis M, J Crawford G, Delplanque J, Doney A, Egan JM, Erdos MR, Firmann M, Forouhi NG, Fox CS, Goodarzi MO, Graessler J, Hingorani A, Isomaa B, Jørgensen T, Kivimaki M, Kovacs P, Krohn K, Kumari M, Lauritzen T, Lévy-Marchal C, Mayor V, McAteer JB, Meyre D, Mitchell BD, Mohlke KL, Morken MA, Narisu N, Palmer CNA, Pakyz R, Pascoe L, Payne F, Pearson D, Rathmann W, Sandbaek A, Sayer AA, Scott LJ, Sharp SJ, Sijbrands E, Singleton A, Siscovick DS, Smith NL, Sparsø T, Swift AJ, Syddall H, Thorleifsson G, Tönjes A, Tuomi T, Tuomilehto J, Valle TT, Waeber G, Walley A, Waterworth DM, Zeggini E, Zhao JH, Illig T, Wichmann HE, Wilson JF, van Duijn C, Hu FB, Morris AD, Frayling TM, Hattersley AT, Thorsteinsdottir U, Stefansson K, Nilsson P, Syvänen AC, Shuldiner AR, Walker M, Bornstein SR, Schwarz P, Williams GH, Nathan DM, Kuusisto J, Laakso M, Cooper C, Marmot M, Ferrucci L, Mooser V, Stumvoll M, Loos RJF, Altshuler D, Psaty BM, Rotter JI, Boerwinkle E, Hansen T, Pedersen O, Florez JC, McCarthy MI, Boehnke M, Barroso I, Sladek R, Froguel P, Meigs JB, Groop L, Wareham NJ, Watanabe RM. Genetic variation in GIPR influences the glucose and insulin responses to an oral glucose challenge. Nat Genet 2010; 42:142-8. [PMID: 20081857 PMCID: PMC2922003 DOI: 10.1038/ng.521] [Citation(s) in RCA: 481] [Impact Index Per Article: 34.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2009] [Accepted: 12/10/2009] [Indexed: 12/18/2022]
Abstract
Glucose levels 2 h after an oral glucose challenge are a clinical measure of glucose tolerance used in the diagnosis of type 2 diabetes. We report a meta-analysis of nine genome-wide association studies (n = 15,234 nondiabetic individuals) and a follow-up of 29 independent loci (n = 6,958-30,620). We identify variants at the GIPR locus associated with 2-h glucose level (rs10423928, beta (s.e.m.) = 0.09 (0.01) mmol/l per A allele, P = 2.0 x 10(-15)). The GIPR A-allele carriers also showed decreased insulin secretion (n = 22,492; insulinogenic index, P = 1.0 x 10(-17); ratio of insulin to glucose area under the curve, P = 1.3 x 10(-16)) and diminished incretin effect (n = 804; P = 4.3 x 10(-4)). We also identified variants at ADCY5 (rs2877716, P = 4.2 x 10(-16)), VPS13C (rs17271305, P = 4.1 x 10(-8)), GCKR (rs1260326, P = 7.1 x 10(-11)) and TCF7L2 (rs7903146, P = 4.2 x 10(-10)) associated with 2-h glucose. Of the three newly implicated loci (GIPR, ADCY5 and VPS13C), only ADCY5 was found to be associated with type 2 diabetes in collaborating studies (n = 35,869 cases, 89,798 controls, OR = 1.12, 95% CI 1.09-1.15, P = 4.8 x 10(-18)).
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Affiliation(s)
- Richa Saxena
- Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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Stolerman ES, Manning AK, McAteer JB, Fox CS, Dupuis J, Meigs JB, Florez JC. TCF7L2 variants are associated with increased proinsulin/insulin ratios but not obesity traits in the Framingham Heart Study. Diabetologia 2009; 52:614-20. [PMID: 19183934 PMCID: PMC3430962 DOI: 10.1007/s00125-009-1266-2] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2008] [Accepted: 01/08/2009] [Indexed: 01/15/2023]
Abstract
AIMS/HYPOTHESIS Common variants in the TCF7L2 gene are associated with type 2 diabetes via impaired insulin secretion. One hypothesis is that variation in TCF7L2 impairs insulin processing in the beta cell. In contrast, the association of related TCF7L2 polymorphisms with obesity is controversial in that it has only been shown in cohorts susceptible to ascertainment bias. We reproduced the association of diabetes-associated variants with proinsulin/insulin ratios, and also examined the association of a TCF7L2 haplotype with obesity in the Framingham Heart Study (FHS). METHODS We genotyped the TCF7L2 single nucleotide polymorphisms rs7903146 and rs12255372 (previously associated with type 2 diabetes) and rs10885406 and rs7924080 (which tag haplotype A [HapA], a haplotype reported to be associated with obesity) in 2,512 FHS participants. We used age- and sex-adjusted linear mixed-effects models to test for association with glycaemic traits, proinsulin/insulin ratios and obesity measures. RESULTS As expected, the T risk allele of rs7903146 was associated with higher fasting plasma glucose (p = 0.01). T/T homozygotes had a 23.5% increase in the proinsulin/insulin ratio (p = 1 x 10(-7)) compared with C/C homozygotes. There was no association of HapA with BMI (p = 0.98), waist circumference (p = 0.89), subcutaneous adipose tissue (p = 0.32) or visceral adipose tissue (p = 0.92). CONCLUSIONS/INTERPRETATION We confirmed that the risk allele of rs7903146 is associated with hyperglycaemia and a higher proinsulin/insulin ratio. We did not detect any association of the TCF7L2 HapA with adiposity measures, suggesting that this may have been a spurious association from ascertainment bias, possibly induced by the evaluation of obesity in separate groups of glycaemic cases and controls.
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Affiliation(s)
- E S Stolerman
- Simches Research Building-CPZN 5.250, Diabetes Unit/Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, 02114, USA
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Lieb W, Manning AK, Florez JC, Dupuis J, Cupples LA, McAteer JB, Vasan RS, Hoffmann U, O'Donnell CJ, Meigs JB, Fox CS. Variants in the CNR1 and the FAAH genes and adiposity traits in the community. Obesity (Silver Spring) 2009; 17:755-60. [PMID: 19165169 PMCID: PMC3039277 DOI: 10.1038/oby.2008.608] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Pharmacologic blockade of the endocannabinoid receptor 1 leads to weight loss and an improved metabolic risk profile in overweight and obese individuals. We hypothesize that common genetic variants in the CNR1 (encoding endocannabinoid receptor 1) and FAAH genes (encoding fatty acid amide hydrolase, a key enzyme hydrolyzing endocannabinoids) are associated with adiposity traits. We genotyped 18 single-nucleotide polymorphisms (SNPs) in the CNR1 gene and 9 SNPs in the FAAH gene in 2,415 Framingham Offspring Study participants (mean age 61 +/- 10 years; 52.6% women; mean BMI 28.2 +/- 5.4 kg/m(2); 30.3% obese) and studied them for association with cross-sectional and longitudinal measures of adiposity (BMI, waist circumference, change over time in BMI and waist circumference, visceral and subcutaneous adipose tissue) using linear mixed-effect models. The selected SNPs captured 85% (r(2) = 0.8) of the common variation (minor allele frequency >5%) at the CNR1 locus and 96% (r(2) = 0.8) of the common variation at the FAAH locus (defined as the genomic segment containing the gene +20 kb upstream and +10 kb downstream). After correction for multiple testing, none of the SNPs in the CNR1 gene or in the FAAH gene displayed statistical evidence for association with BMI, waist circumference, and visceral adipose tissue or subcutaneous adipose tissue (all P > 0.18). Despite comprehensive SNP mapping across the genes and their regulatory regions in a large unselected sample, we failed to find evidence for an association of common variants in the CNR1 and FAAH genes with measures of adiposity in our community-based sample.
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Affiliation(s)
- Wolfgang Lieb
- National Heart, Lung and Blood Institute's Framingham Heart Study, Framingham, MA
| | - Alisa K. Manning
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Jose C. Florez
- Diabetes Unit (Department of Medicine) and Center for Human Genetic Research, Massachusetts General Hospital; Department of Medicine, Harvard Medical School, Boston, MA, and Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - L. Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Jarred B. McAteer
- Diabetes Unit (Department of Medicine) and Center for Human Genetic Research, Massachusetts General Hospital; Department of Medicine, Harvard Medical School, Boston, MA, and Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA
| | | | - Udo Hoffmann
- Department of Radiology, Massachusetts General Hospital, Boston, MA
| | | | - James B. Meigs
- General Medicine Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Caroline S. Fox
- National Heart, Lung and Blood Institute's Framingham Heart Study, Framingham, MA
- Endocrinology Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
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Hivert MF, Manning AK, McAteer JB, Dupuis J, Fox CS, Cupples LA, Meigs JB, Florez JC. Association of variants in RETN with plasma resistin levels and diabetes-related traits in the Framingham Offspring Study. Diabetes 2009; 58:750-6. [PMID: 19074981 PMCID: PMC2646076 DOI: 10.2337/db08-1339] [Citation(s) in RCA: 78] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
OBJECTIVE The RETN gene encodes the adipokine resistin. Associations of RETN with plasma resistin levels, type 2 diabetes, and related metabolic traits have been inconsistent. Using comprehensive linkage disequilibrium mapping, we genotyped tag single nucleotide polymorphisms (SNPs) in RETN and tested associations with plasma resistin levels, risk of diabetes, and glycemic traits. RESEARCH DESIGN AND METHODS We examined 2,531 Framingham Offspring Study participants for resistin levels, glycemic phenotypes, and incident diabetes over 28 years of follow-up. We genotyped 21 tag SNPs that capture common (minor allele frequency >0.05) or previously reported SNPs at r2 > 0.8 across RETN and its flanking regions. We used sex- and age-adjusted linear mixed-effects models (with/without BMI adjustment) to test additive associations of SNPs with traits, adjusted Cox proportional hazards models accounting for relatedness for incident diabetes, and generated empirical P values (Pe) to control for type 1 error. RESULTS Four tag SNPs (rs1477341, rs4804765, rs1423096, and rs10401670) on the 3' side of RETN were strongly associated with resistin levels (all minor alleles associated with higher levels, Pe<0.05 after multiple testing correction). rs10401670 was also associated with fasting plasma glucose (Pe = 0.02, BMI adjusted) and mean glucose over follow-up (Pe = 0.01; BMI adjusted). No significant association was observed for adiposity traits. On meta-analysis, the previously reported association of SNP -420C/G (rs1862513) with resistin levels remained significant (P = 0.0009) but with high heterogeneity across studies (P < 0.0001). CONCLUSIONS SNPs in the 3' region of RETN are associated with resistin levels, and one of them is also associated with glucose levels, although replication is needed.
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Affiliation(s)
- Marie-France Hivert
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts, USA
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Moore AF, Jablonski KA, Mason CC, McAteer JB, Arakaki RF, Goldstein BJ, Kahn SE, Kitabchi AE, Hanson RL, Knowler WC, Florez JC. The association of ENPP1 K121Q with diabetes incidence is abolished by lifestyle modification in the diabetes prevention program. J Clin Endocrinol Metab 2009; 94:449-55. [PMID: 19017751 PMCID: PMC2646511 DOI: 10.1210/jc.2008-1583] [Citation(s) in RCA: 42] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
CONTEXT Insulin resistance is an important feature of type 2 diabetes. Ectoenzyme nucleotide pyrophosphatase phosphodiesterase 1 (ENPP1) inhibits insulin signaling, and a recent meta-analysis reported a nominal association between the Q allele in the K121Q (rs1044498) single nucleotide polymorphism in its gene ENPP1 and type 2 diabetes. OBJECTIVE AND INTERVENTION: We examined the impact of this polymorphism on diabetes incidence as well as insulin secretion and sensitivity at baseline and after treatment with a lifestyle intervention or metformin vs. placebo in the Diabetes Prevention Program (DPP). DESIGN, SETTING, PARTICIPANTS, AND OUTCOME: We genotyped ENPP1 K121Q in 3548 DPP participants and performed Cox regression analyses using genotype, intervention, and interactions as predictors of diabetes incidence. RESULTS Fasting glucose and glycated hemoglobin were higher in QQ homozygotes at baseline (P < 0.001 for both). There was a significant interaction between genotype at rs1044498 and intervention under the dominant model (P = 0.03). In analyses stratified by treatment arm, a positive association with diabetes incidence was found in Q allele carriers compared to KK homozygotes [hazard ratio (HR), 1.38; 95% confidence interval (CI), 1.08-1.76; P = 0.009] in the placebo arm (n = 996). Lifestyle modification eliminated this increased risk. These findings persisted after adjustment for body mass index and race/ethnicity. Association of ENPP1 K121Q genotype with diabetes incidence under the additive and recessive genetic models showed consistent trends [HR, 1.10 (95% CI, 0.99-1.23), P = 0.08; and HR, 1.16 (95% CI, 0.92-1.45), P = 0.20, respectively] but did not reach statistical significance. CONCLUSIONS ENPP1 K121Q is associated with increased diabetes incidence; the DPP lifestyle intervention eliminates this increased risk.
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Affiliation(s)
- Allan F Moore
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts 02114-2622, USA
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Hivert MF, Manning AK, McAteer JB, Florez JC, Dupuis J, Fox CS, O'Donnell CJ, Cupples LA, Meigs JB. Common variants in the adiponectin gene (ADIPOQ) associated with plasma adiponectin levels, type 2 diabetes, and diabetes-related quantitative traits: the Framingham Offspring Study. Diabetes 2008; 57:3353-9. [PMID: 18776141 PMCID: PMC2584143 DOI: 10.2337/db08-0700] [Citation(s) in RCA: 133] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2008] [Accepted: 08/22/2008] [Indexed: 01/19/2023]
Abstract
OBJECTIVE Variants in ADIPOQ have been inconsistently associated with adiponectin levels or diabetes. Using comprehensive linkage disequilibrium mapping, we genotyped single nucleotide polymorphisms (SNPs) in ADIPOQ to evaluate the association of common variants with adiponectin levels and risk of diabetes. RESEARCH DESIGN AND METHODS Participants in the Framingham Offspring Study (n = 2,543, 53% women) were measured for glycemic phenotypes and incident diabetes over 28 years of follow-up; adiponectin levels were quantified at exam 7. We genotyped 22 tag SNPs that captured common (minor allele frequency >0.05) variation at r(2) > 0.8 across ADIPOQ plus 20 kb 5' and 10 kb 3' of the gene. We used linear mixed effects models to test additive associations of each SNP with adiponectin levels and glycemic phenotypes. Hazard ratios (HRs) for incident diabetes were estimated using an adjusted Cox proportional hazards model. RESULTS Two promoter SNPs in strong linkage disequilibrium with each other (r(2) = 0.80) were associated with adiponectin levels (rs17300539; P(nominal) [P(n)] = 2.6 x 10(-8); P(empiric) [P(e)] = 0.0005 and rs822387; P(n) = 3.8 x 10(-5); P(e) = 0.001). A 3'-untranslated region (3'UTR) SNP (rs6773957) was associated with adiponectin levels (P(n) = 4.4 x 10(-4); P(e) = 0.005). A nonsynonymous coding SNP (rs17366743, Y111H) was confirmed to be associated with diabetes incidence (HR 1.94 [95% CI 1.16-3.25] for the minor C allele; P(n) = 0.01) and with higher mean fasting glucose over 28 years of follow-up (P(n) = 0.0004; P(e) = 0.004). No other significant associations were found with other adiposity and metabolic phenotypes. CONCLUSIONS Adiponectin levels are associated with SNPs in two different regulatory regions (5' promoter and 3'UTR), whereas diabetes incidence and time-averaged fasting glucose are associated with a missense SNP of ADIPOQ.
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Affiliation(s)
- Marie-France Hivert
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Alisa K. Manning
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Jarred B. McAteer
- Center for Human Genetic Research and Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | - Jose C. Florez
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Center for Human Genetic Research and Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Caroline S. Fox
- Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
- Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, Massachusetts
| | - Christopher J. O'Donnell
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, Massachusetts
| | - L. Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - James B. Meigs
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
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Franks PW, Jablonski KA, Delahanty LM, McAteer JB, Kahn SE, Knowler WC, Florez JC. Assessing gene-treatment interactions at the FTO and INSIG2 loci on obesity-related traits in the Diabetes Prevention Program. Diabetologia 2008; 51:2214-23. [PMID: 18839134 PMCID: PMC2947367 DOI: 10.1007/s00125-008-1158-x] [Citation(s) in RCA: 62] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2008] [Accepted: 08/22/2008] [Indexed: 01/11/2023]
Abstract
AIMS/HYPOTHESIS The single nucleotide polymorphism (SNP) rs9939609 in the fat mass and obesity associated gene (FTO) and the rs7566605 SNP located 10 kb upstream of the insulin-induced gene 2 gene (INSIG2) have been proposed as risk factors for common obesity. METHODS We tested for genotype-treatment interactions on changes in obesity-related traits in the Diabetes Prevention Program (DPP). The DPP is a randomised controlled trial of 3,548 high-risk individuals from 27 participating centres throughout the USA who were originally randomised to receive metformin, troglitazone, intensive lifestyle modification or placebo to prevent the development of type 2 diabetes. Measures of adiposity from computed tomography were available in a subsample (n = 908). This report focuses on the baseline and 1 year results. RESULTS The minor A allele at FTO rs9939609 was positively associated with baseline BMI (p = 0.003), but not with baseline adiposity or the change at 1 year in any anthropometric trait. For the INSIG2 rs7566605 genotype, the minor C allele was associated with more subcutaneous adiposity (second and third lumbar vertebrae [L2/3]) at baseline (p = 0.04). During follow-up, CC homozygotes lost more weight than G allele carriers (p = 0.009). In an additive model, we observed nominally significant gene-lifestyle interactions on weight change (p = 0.02) and subcutaneous (L2/3 [p = 0.01] and L4/5 [p = 0.03]) and visceral (L2/3 [p = 0.02]) adipose areas. No statistical evidence of association with physical activity energy expenditure or energy intake was observed for either genotype. CONCLUSIONS/INTERPRETATION Within the DPP study population, common variants in FTO and INSIG2 are nominally associated with quantitative measures of obesity, directly and possibly by interacting with metformin or lifestyle intervention.
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Affiliation(s)
- P W Franks
- Genetic Epidemiology and Clinical Research Group, Department of Public Health and Clinical Medicine, Section for Medicine, Umeå University Hospital, Umeå, Sweden.
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Meigs JB, Shrader P, Sullivan LM, McAteer JB, Fox CS, Dupuis J, Manning AK, Florez JC, Wilson PWF, D'Agostino RB, Cupples LA. Genotype score in addition to common risk factors for prediction of type 2 diabetes. N Engl J Med 2008; 359:2208-19. [PMID: 19020323 PMCID: PMC2746946 DOI: 10.1056/nejmoa0804742] [Citation(s) in RCA: 547] [Impact Index Per Article: 34.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
BACKGROUND Multiple genetic loci have been convincingly associated with the risk of type 2 diabetes mellitus. We tested the hypothesis that knowledge of these loci allows better prediction of risk than knowledge of common phenotypic risk factors alone. METHODS We genotyped single-nucleotide polymorphisms (SNPs) at 18 loci associated with diabetes in 2377 participants of the Framingham Offspring Study. We created a genotype score from the number of risk alleles and used logistic regression to generate C statistics indicating the extent to which the genotype score can discriminate the risk of diabetes when used alone and in addition to clinical risk factors. RESULTS There were 255 new cases of diabetes during 28 years of follow-up. The mean (+/-SD) genotype score was 17.7+/-2.7 among subjects in whom diabetes developed and 17.1+/-2.6 among those in whom diabetes did not develop (P<0.001). The sex-adjusted odds ratio for diabetes was 1.12 per risk allele (95% confidence interval, 1.07 to 1.17). The C statistic was 0.534 without the genotype score and 0.581 with the score (P=0.01). In a model adjusted for sex and self-reported family history of diabetes, the C statistic was 0.595 without the genotype score and 0.615 with the score (P=0.11). In a model adjusted for age, sex, family history, body-mass index, fasting glucose level, systolic blood pressure, high-density lipoprotein cholesterol level, and triglyceride level, the C statistic was 0.900 without the genotype score and 0.901 with the score (P=0.49). The genotype score resulted in the appropriate risk reclassification of, at most, 4% of the subjects. CONCLUSIONS A genotype score based on 18 risk alleles predicted new cases of diabetes in the community but provided only a slightly better prediction of risk than knowledge of common risk factors alone.
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Affiliation(s)
- James B Meigs
- General Medicine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA.
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Moore AF, Jablonski KA, McAteer JB, Saxena R, Pollin TI, Franks PW, Hanson RL, Shuldiner AR, Knowler WC, Altshuler D, Florez JC. Extension of type 2 diabetes genome-wide association scan results in the diabetes prevention program. Diabetes 2008; 57:2503-10. [PMID: 18544707 PMCID: PMC2518503 DOI: 10.2337/db08-0284] [Citation(s) in RCA: 87] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2008] [Accepted: 06/01/2008] [Indexed: 11/25/2022]
Abstract
OBJECTIVE Genome-wide association scans (GWASs) have identified novel diabetes-associated genes. We evaluated how these variants impact diabetes incidence, quantitative glycemic traits, and response to preventive interventions in 3,548 subjects at high risk of type 2 diabetes enrolled in the Diabetes Prevention Program (DPP), which examined the effects of lifestyle intervention, metformin, and troglitazone versus placebo. RESEARCH DESIGN AND METHODS We genotyped selected single nucleotide polymorphisms (SNPs) in or near diabetes-associated loci, including EXT2, CDKAL1, CDKN2A/B, IGF2BP2, HHEX, LOC387761, and SLC30A8 in DPP participants and performed Cox regression analyses using genotype, intervention, and their interactions as predictors of diabetes incidence. We evaluated their effect on insulin resistance and secretion at 1 year. RESULTS None of the selected SNPs were associated with increased diabetes incidence in this population. After adjustments for ethnicity, baseline insulin secretion was lower in subjects with the risk genotype at HHEX rs1111875 (P = 0.01); there were no significant differences in baseline insulin sensitivity. Both at baseline and at 1 year, subjects with the risk genotype at LOC387761 had paradoxically increased insulin secretion; adjustment for self-reported ethnicity abolished these differences. In ethnicity-adjusted analyses, we noted a nominal differential improvement in beta-cell function for carriers of the protective genotype at CDKN2A/B after 1 year of troglitazone treatment (P = 0.01) and possibly lifestyle modification (P = 0.05). CONCLUSIONS We were unable to replicate the GWAS findings regarding diabetes risk in the DPP. We did observe genotype associations with differences in baseline insulin secretion at the HHEX locus and a possible pharmacogenetic interaction at CDKNA2/B.
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Affiliation(s)
- Allan F. Moore
- Center for Human Genetic Research, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Diabetes Center, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
| | | | - Jarred B. McAteer
- Center for Human Genetic Research, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Richa Saxena
- Center for Human Genetic Research, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Toni I. Pollin
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland
| | - Paul W. Franks
- Genetic Epidemiology and Clinical Research Group, Department of Public Health and Clinical Medicine, Division of Medicine, Umeå University Hospital, Umeå, Sweden
| | - Robert L. Hanson
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona
| | - Alan R. Shuldiner
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, Maryland
| | - William C. Knowler
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona
| | - David Altshuler
- Center for Human Genetic Research, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Diabetes Center, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
- Department of Genetics, Harvard Medical School, Boston, Massachusetts
| | - Jose C. Florez
- Center for Human Genetic Research, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Diabetes Center, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
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Stolerman ES, Manning AK, McAteer JB, Dupuis J, Fox CS, Cupples LA, Meigs JB, Florez JC. Haplotype structure of the ENPP1 Gene and Nominal Association of the K121Q missense single nucleotide polymorphism with glycemic traits in the Framingham Heart Study. Diabetes 2008; 57:1971-7. [PMID: 18426862 PMCID: PMC2453609 DOI: 10.2337/db08-0266] [Citation(s) in RCA: 41] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2008] [Accepted: 04/16/2008] [Indexed: 12/03/2022]
Abstract
OBJECTIVE A recent meta-analysis demonstrated a nominal association of the ectonucleotide pyrophosphatase phosphodiesterase 1 (ENPP1) K-->Q missense single nucleotide polymorphism (SNP) at position 121 with type 2 diabetes. We set out to confirm the association of ENPP1 K121Q with hyperglycemia, expand this association to insulin resistance traits, and determine whether the association stems from K121Q or another variant in linkage disequilibrium with it. RESEARCH DESIGN AND METHODS We characterized the haplotype structure of ENPP1 and selected 39 tag SNPs that captured 96% of common variation in the region (minor allele frequency > or =5%) with an r(2) value > or =0.80. We genotyped the SNPs in 2,511 Framingham Heart Study participants and used age- and sex-adjusted linear mixed effects (LME) models to test for association with quantitative metabolic traits. We also examined whether interaction between K121Q and BMI affected glycemic trait levels. RESULTS The Q allele of K121Q (rs1044498) was associated with increased fasting plasma glucose (FPG), A1C, fasting insulin, and insulin resistance by homeostasis model assessment (HOMA-IR; all P = 0.01-0.006). Two noncoding SNPs (rs7775386 and rs7773477) demonstrated similar associations, but LME models indicated that their effects were not independent from K121Q. We found no association of K121Q with obesity, but interaction models suggested that the effect of the Q allele on FPG and HOMA-IR was stronger in those with a higher BMI (P = 0.008 and 0.01 for interaction, respectively). CONCLUSIONS The Q allele of ENPP1 K121Q is associated with hyperglycemia and insulin resistance in whites. We found an adiposity-SNP interaction, with a stronger association of K121Q with diabetes-related quantitative traits in people with a higher BMI.
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Affiliation(s)
- Elliot S. Stolerman
- Center for Human Genetic Research and Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Alisa K. Manning
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Jarred B. McAteer
- Center for Human Genetic Research and Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Caroline S. Fox
- Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
- National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, Massachusetts
| | - L. Adrienne Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - James B. Meigs
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts
| | - Jose C. Florez
- Center for Human Genetic Research and Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
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25
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McAteer JB, Prudente S, Bacci S, Lyon HN, Hirschhorn JN, Trischitta V, Florez JC. The ENPP1 K121Q polymorphism is associated with type 2 diabetes in European populations: evidence from an updated meta-analysis in 42,042 subjects. Diabetes 2008; 57:1125-30. [PMID: 18071025 DOI: 10.2337/db07-1336] [Citation(s) in RCA: 77] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
OBJECTIVE Functional studies suggest that the nonsynonymous K121Q polymorphism in the ectoenzyme nucleotide pyrophosphate phosphodiesterase 1 (ENPP1) may confer susceptibility to insulin resistance; genetic evidence on its effect on type 2 diabetes, however, has been conflicting. We therefore conducted a new meta-analysis that includes novel unpublished data from the ENPP1 Consortium and recent negative findings from large association studies to address the contribution of K121Q to type 2 diabetes. RESEARCH DESIGN AND METHODS After a systematic review of the literature, we evaluated the effect of ENPP1 K121Q on diabetes risk under three genetic models using a random-effects approach. Our primary analysis consisted of 30 studies comprising 15,801 case and 26,241 control subjects. Due to considerable heterogeneity and large differences in allele frequencies across populations, we limited our meta-analysis to those of self-reported European descent and, when available, included BMI as a covariate. RESULTS We found a modest increase in risk of type 2 diabetes for QQ homozygotes in white populations (combined odds ratio [OR] 1.38 [95% CI 1.10-1.74], P = 0.005). There was no evidence of publication bias, but we noted significant residual heterogeneity among studies (P = 0.02). On meta-regression, 16% of the effect was accounted for by the mean BMI of control subjects. This association was stronger in studies in which control subjects were leaner but disappeared after adjustment for mean control BMI (combined OR 0.93 [95% CI 0.75-1.15], P = 0.50). CONCLUSIONS The ENPP1 Q121 variant increases risk of type 2 diabetes under a recessive model of inheritance in whites, an effect that appears to be modulated by BMI.
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Affiliation(s)
- Jarred B McAteer
- Diabetes Unit/Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA
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