Common variants at 10 genomic loci influence hemoglobin A1C levels via glycemic and nonglycemic pathways

Nicole Soranzo, Serena Sanna, Eleanor Wheeler, Christian Gieger, Dörte Radke, Josée Dupuis, Nabila Bouatia-Naji, Claudia Langenberg, Inga Prokopenko, Elliot Stolerman, Manjinder S. Sandhu, Matthew M. Heeney, Joseph M. Devaney, Muredach P. Reilly, Sally L. Ricketts, Alexandre F.R. Stewart, Benjamin F. Voight, Christina Willenborg, Benjamin Wright, David AltshulerDan Arking, Beverley Balkau, Daniel Barnes, Eric Boerwinkle, Bernhard Böhm, Amélie Bonnefond, Lori L. Bonnycastle, Dorret I. Boomsma, Stefan R. Bornstein, Yvonne Böttcher, Suzannah Bumpstead, Mary Susan Burnett-Miller, Harry Campbell, Antonio Cao, John Chambers, Robert Clark, Francis S. Collins, Josef Coresh, Eco J.C. De Geus, Mariano Dei, Panos Deloukas, Angela Döring, Josephine M. Egan, Roberto Elosua, Luigi Ferrucci, Nita Forouhi, Caroline S. Fox, Christopher Franklin, Maria Grazia Franzosi, Sophie Gallina, Anuj Goel, Jürgen Graessler, Harald Grallert, Andreas Greinacher, David Hadley, Alistair Hall, Anders Hamsten, Caroline Hayward, Simon Heath, Christian Herder, Georg Homuth, Jouke Jan Hottenga, Rachel Hunter-Merrill, Thomas Illig, Anne U. Jackson, Antti Jula, Marcus Kleber, Christopher W. Knouff, Augustine Kong, Jaspal Kooner, Anna Köttgen, Peter Kovacs, Knut Krohn, Brigitte Kühnel, Johanna Kuusisto, Markku Laakso, Mark Lathrop, Cécile Lecoeur, Man Li, Mingyao Li, Ruth J.F. Loos, Jian'an Luan, Valeriya Lyssenko, Reedik Mägi, Patrik K.E. Magnusson, Anders Mälarstig, Massimo Mangino, María Teresa Martínez-Larrad, Winfried März, Wendy L. McArdle, Ruth McPherson, Christa Meisinger, Thomas Meitinger, Olle Melander, Karen L. Mohlke, Vincent E. Mooser, Mario A. Morken, Narisu Narisu, David M. Nathan, Matthias Nauck, Chris O'Donnell, Konrad Oexle, Nazario Olla, James S. Pankow, Felicity Payne, John F. Peden, Nancy L. Pedersen, Leena Peltonen, Markus Perola, Ozren Polasek, Eleonora Porcu, Daniel J. Rader, Wolfgang Rathmann, Samuli Ripatti, Ghislain Rocheleau, Michael Roden, Igor Rudan, Veikko Salomaa, Richa Saxena, David Schlessinger, Heribert Schunkert, Peter Schwarz, Udo Seedorf, Elizabeth Selvin, Manuel Serrano-Ríos, Peter Shrader, Angela Silveira, David Siscovick, Kjioung Song, Timothy D. Spector, Kari Stefansson, Valgerdur Steinthorsdottir, David P. Strachan, Rona Strawbridge, Michael Stumvoll, Ida Surakka, Amy J. Swift, Toshiko Tanaka, Alexander Teumer, Gudmar Thorleifsson, Unnur Thorsteinsdottir, Anke Tönjes, Gianluca Usala, Veronique Vitart, Henry Völzke, Henri Wallaschofski, Dawn M. Waterworth, Hugh Watkins, H. Erich Wichmann, Sarah H. Wild, Gonneke Willemsen, Gordon H. Williams, James F. Wilson, Juliane Winkelmann, Alan F. Wright, Carina Zabena, Jing Hua Zhao, Stephen E. Epstein, Jeanette Erdmann, Hakon H. Hakonarson, Sekar Kathiresan, Kay Tee Khaw, Robert Roberts, Nilesh J. Samani, Mark D. Fleming, Robert Sladek, Gonçalo Abecasis, Michael Boehnke, Philippe Froguel, Leif Groop, Mark I. McCarthy, Wen-Hong Linda Kao, Jose C. Florez, Manuela Uda, Nicholas J. Wareham, Inês Barroso, James B. Meigs

Research output: Contribution to journalArticlepeer-review

275 Scopus citations

Abstract

OBJECTIVE - Glycated hemoglobin (HbA1c), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA 1c. We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA1c levels. RESEARCH DESIGN AND METHODS - We studied associations with HbA 1c in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA1c loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening. RESULTS - Ten loci reached genome-wide significant association with HbA1c, including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10-26), HFE (rs1800562/P = 2.6 × 10-20), TMPRSS6 (rs855791/P = 2.7 x 10-14), ANK1 (rs4737009/P = 6.1 × 10-12), SPTA1 (rs2779116/P = 2.8 × 10-9) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10 -9), and four known HbA1c loci: HK1 (rs16926246/P = 3.1 × 10-54), MTNR1B (rs1387153/P = 4.0 × 10-11), GCK (rs1799884/P = 1.5 × 10-20) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10-18). We show that associations with HbA1c are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA 1c) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA1c. CONCLUSIONS - GWAS identified 10 genetic loci reproducibly associated with HbA1c. Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA1c levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA1c.

Original languageEnglish (US)
Pages (from-to)3229-3239
Number of pages11
JournalDiabetes
Volume59
Issue number12
DOIs
StatePublished - Dec 2010

ASJC Scopus subject areas

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism

Fingerprint

Dive into the research topics of 'Common variants at 10 genomic loci influence hemoglobin A1C levels via glycemic and nonglycemic pathways'. Together they form a unique fingerprint.

Cite this