An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans

Robert A Scott, Laura J Scott, Reedik Mägi, Letizia Marullo, Kyle J Gaulton, Marika Kaakinen, Natalia Pervjakova, Tune H Pers, Andrew D Johnson, John D Eicher, Anne U Jackson, Teresa Ferreira, Yeji Lee, Clement Ma, Valgerdur Steinthorsdottir, Gudmar Thorleifsson, Lu Qi, Natalie R Van Zuydam, Anubha Mahajan, Han Chen, Peter Almgren, Ben F Voight, Harald Grallert, Martina Müller-Nurasyid, Janina S Ried, Nigel W Rayner, Neil Robertson, Lennart C Karssen, Elisabeth M van Leeuwen, Sara M Willems, Christian Fuchsberger, Phoenix Kwan, Tanya M Teslovich, Pritam Chanda, Man Li, Yingchang Lu, Christian Dina, Dorothee Thuillier, Loic Yengo, Longda Jiang, Thomas Sparso, Hans A Kestler, Himanshu Chheda, Lewin Eisele, Stefan Gustafsson, Mattias Frånberg, Rona J Strawbridge, Rafn Benediktsson, Astradur B Hreidarsson, Augustine Kong, Gunnar Sigurðsson, Nicola D Kerrison, Jian'an Luan, Liming Liang, Thomas Meitinger, Michael Roden, Barbara Thorand, Tõnu Esko, Evelin Mihailov, Caroline Fox, Ching-Ti Liu, Denis Rybin, Bo Isomaa, Valeriya Lyssenko, Tiinamaija Tuomi, David J Couper, James S Pankow, Niels Grarup, Christian T Have, Marit E Jørgensen, Torben Jørgensen, Allan Linneberg, Marilyn C Cornelis, Rob M van Dam, David J Hunter, Peter Kraft, Qi Sun, Sarah Edkins, Katharine R Owen, John R B Perry, Andrew R Wood, Eleftheria Zeggini, Juan Tajes-Fernandes, Goncalo R Abecasis, Lori L Bonnycastle, Peter S Chines, Heather M Stringham, Heikki A Koistinen, Leena Kinnunen, Bengt Sennblad, Thomas W Mühleisen, Markus M Nöthen, Sonali Pechlivanis, Damiano Baldassarre, Karl Gertow, Steve E Humphries, Elena Tremoli, Norman Klopp, Julia Meyer, Gerald Steinbach, Roman Wennauer, Johan G Eriksson, Satu Mӓnnistö, Leena Peltonen, Emmi Tikkanen, Guillaume Charpentier, Elodie Eury, Stéphane Lobbens, Bruna Gigante, Karin Leander, Olga McLeod, Erwin P Bottinger, Omri Gottesman, Douglas Ruderfer, Matthias Blüher, Peter Kovacs, Anke Tonjes, Nisa M Maruthur, Chiara Scapoli, Raimund Erbel, Karl-Heinz Jöckel, Susanne Moebus, Ulf de Faire, Anders Hamsten, Michael Stumvoll, Panagiotis Deloukas, Peter J Donnelly, Timothy M Frayling, Andrew T Hattersley, Samuli Ripatti, Veikko Salomaa, Nancy L Pedersen, Bernhard O Boehm, Richard N Bergman, Francis S Collins, Karen L Mohlke, Jaakko Tuomilehto, Torben Hansen, Oluf Pedersen, Inês Barroso, Lars Lannfelt, Erik Ingelsson, Lars Lind, Cecilia M Lindgren, Stephane Cauchi, Philippe Froguel, Ruth J F Loos, Beverley Balkau, Heiner Boeing, Paul W Franks, Aurelio Barricarte Gurrea, Domenico Palli, Yvonne T van der Schouw, David Altshuler, Leif C Groop, Claudia Langenberg, Nicholas J Wareham, Eric Sijbrands, Cornelia M van Duijn, Jose C Florez, James B Meigs, Eric Boerwinkle, Christian Gieger, Konstantin Strauch, Andres Metspalu, Andrew D Morris, Colin N A Palmer, Frank B Hu, Unnur Thorsteinsdottir, Kari Stefansson, Josée Dupuis, Andrew P Morris, Michael Boehnke, Mark I McCarthy, Inga Prokopenko, DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Robert A Scott, Laura J Scott, Reedik Mägi, Letizia Marullo, Kyle J Gaulton, Marika Kaakinen, Natalia Pervjakova, Tune H Pers, Andrew D Johnson, John D Eicher, Anne U Jackson, Teresa Ferreira, Yeji Lee, Clement Ma, Valgerdur Steinthorsdottir, Gudmar Thorleifsson, Lu Qi, Natalie R Van Zuydam, Anubha Mahajan, Han Chen, Peter Almgren, Ben F Voight, Harald Grallert, Martina Müller-Nurasyid, Janina S Ried, Nigel W Rayner, Neil Robertson, Lennart C Karssen, Elisabeth M van Leeuwen, Sara M Willems, Christian Fuchsberger, Phoenix Kwan, Tanya M Teslovich, Pritam Chanda, Man Li, Yingchang Lu, Christian Dina, Dorothee Thuillier, Loic Yengo, Longda Jiang, Thomas Sparso, Hans A Kestler, Himanshu Chheda, Lewin Eisele, Stefan Gustafsson, Mattias Frånberg, Rona J Strawbridge, Rafn Benediktsson, Astradur B Hreidarsson, Augustine Kong, Gunnar Sigurðsson, Nicola D Kerrison, Jian'an Luan, Liming Liang, Thomas Meitinger, Michael Roden, Barbara Thorand, Tõnu Esko, Evelin Mihailov, Caroline Fox, Ching-Ti Liu, Denis Rybin, Bo Isomaa, Valeriya Lyssenko, Tiinamaija Tuomi, David J Couper, James S Pankow, Niels Grarup, Christian T Have, Marit E Jørgensen, Torben Jørgensen, Allan Linneberg, Marilyn C Cornelis, Rob M van Dam, David J Hunter, Peter Kraft, Qi Sun, Sarah Edkins, Katharine R Owen, John R B Perry, Andrew R Wood, Eleftheria Zeggini, Juan Tajes-Fernandes, Goncalo R Abecasis, Lori L Bonnycastle, Peter S Chines, Heather M Stringham, Heikki A Koistinen, Leena Kinnunen, Bengt Sennblad, Thomas W Mühleisen, Markus M Nöthen, Sonali Pechlivanis, Damiano Baldassarre, Karl Gertow, Steve E Humphries, Elena Tremoli, Norman Klopp, Julia Meyer, Gerald Steinbach, Roman Wennauer, Johan G Eriksson, Satu Mӓnnistö, Leena Peltonen, Emmi Tikkanen, Guillaume Charpentier, Elodie Eury, Stéphane Lobbens, Bruna Gigante, Karin Leander, Olga McLeod, Erwin P Bottinger, Omri Gottesman, Douglas Ruderfer, Matthias Blüher, Peter Kovacs, Anke Tonjes, Nisa M Maruthur, Chiara Scapoli, Raimund Erbel, Karl-Heinz Jöckel, Susanne Moebus, Ulf de Faire, Anders Hamsten, Michael Stumvoll, Panagiotis Deloukas, Peter J Donnelly, Timothy M Frayling, Andrew T Hattersley, Samuli Ripatti, Veikko Salomaa, Nancy L Pedersen, Bernhard O Boehm, Richard N Bergman, Francis S Collins, Karen L Mohlke, Jaakko Tuomilehto, Torben Hansen, Oluf Pedersen, Inês Barroso, Lars Lannfelt, Erik Ingelsson, Lars Lind, Cecilia M Lindgren, Stephane Cauchi, Philippe Froguel, Ruth J F Loos, Beverley Balkau, Heiner Boeing, Paul W Franks, Aurelio Barricarte Gurrea, Domenico Palli, Yvonne T van der Schouw, David Altshuler, Leif C Groop, Claudia Langenberg, Nicholas J Wareham, Eric Sijbrands, Cornelia M van Duijn, Jose C Florez, James B Meigs, Eric Boerwinkle, Christian Gieger, Konstantin Strauch, Andres Metspalu, Andrew D Morris, Colin N A Palmer, Frank B Hu, Unnur Thorsteinsdottir, Kari Stefansson, Josée Dupuis, Andrew P Morris, Michael Boehnke, Mark I McCarthy, Inga Prokopenko, DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium

Abstract

To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.

© 2017 by the American Diabetes Association.

Figures

Figure 1
Figure 1
The effect sizes of the established (blue diamonds, N = 69, P < 5 × 10−4) (Supplementary Material), novel (red diamonds, N = 13), and additional distinct (sky blue diamonds, N = 13) (Supplementary Table 7) signals according to their risk allele frequency (Supplementary Table 3). The additional distinct signals are based on approximate conditional analyses. The distinct signal at TP53INP1 led by rs11786613 (Supplementary Table 7) is plotted (sky blue diamond). This signal did not reach locus-wide significance but was selected for follow-up because of its low frequency and absence of LD with previously reported signal at this locus. The power curve shows the estimated effect size for which we had 80% power to detect associations. Established common variants with OR >1.12 are annotated.
Figure 2
Figure 2
A: The number (N) of SNVs included in 99% credible sets when performed on all SNVs compared with when analyses were restricted to those SNVs present in HapMap. B: The cumulative πc of the top three SNVs among all 1000G SNVs and after restriction to HapMap SNVs is shown. While the low-frequency SNV at TP53INP1 (rs11786613) did not reach the threshold for a distinct signal in approximate conditional analyses, we fine-mapped both this variant and the previous common signal separately after reciprocal conditioning, which suggested they were independent. C: The MAF of the lead SNV identified in current analyses compared with that identified among SNVs present in HapMap. D: The association of the low-frequency variant rs11786613 (blue) and that of the previous lead variant at this locus, rs7845219 (purple). The low-frequency variant overlaps regulatory annotations active in pancreatic islets, among other tissues, and the sequence surrounding the A allele of this variant has an in silico recognition motif for a FOXA1:AR (androgen receptor) protein complex.
Figure 3
Figure 3
T2D loci stratified by patterns of quantitative trait (e.g., glycemic, insulin, lipid, and anthropometric) effects show distinct cell-type annotation patterns. We hierarchically clustered loci based on endophenotype data and identified groups of T2D loci associated with measures of insulin secretion (A), insulin resistance (B), and BMI/lipids (C). We then tested the effect of variants in cell-type enhancer and promoter chromatin states on the posterior probabilities of credible sets for each group. We identified most significant effects among pancreatic (Panc.) islet chromatin for insulin secretion loci, CD14+ monocyte and adipose chromatin for insulin resistance loci, and liver chromatin for BMI/lipid loci.

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Source: PubMed

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