The genetic architecture of type 2 diabetes

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.

Stephen C. J. Parker | Taylor J. Maxwell | Mauricio O. Carneiro | Tanya M. Teslovich | Kyle J. Gaulton | Nicholette D. Palmer | Davis J. McCarthy | Y. J. Kim | P. Donnelly | P. Elliott | J. Danesh | L. Liang | C. Gieger | W. Rathmann | T. Spector | A. Peters | R. Mägi | E. Mihailov | M. McCarthy | P. Deloukas | E. Zeggini | A. Morris | F. Hu | M. DePristo | E. Banks | R. Poplin | J. Maguire | C. Hartl | M. Rivas | T. Fennell | S. Gabriel | M. Daly | G. Abecasis | H. Kang | G. McVean | E. Lander | K. Stirrups | D. Altshuler | V. Salomaa | T. Hansen | O. Pedersen | N. Grarup | T. Jørgensen | I. Brandslund | C. Lindgren | L. Groop | A. Farmer | J. Levy | M. Laakso | F. Collins | K. Strauch | M. Boehnke | B. Neale | Joshua D. Smith | M. Mangino | T. Frayling | J. Perry | A. Hattersley | M. Walker | C. Groves | T. Ferreira | Y. Teo | R. Onofrio | R. Bergman | T. Wieland | S. Purcell | T. Green | George B. Grant | N. Cox | E. Gamazon | H. Im | R. Duggirala | J. Blangero | T. Wong | K. Jablonski | D. Prabhakaran | E. Tai | J. Justesen | J. Chan | W. So | R. Ma | K. Small | T. Meitinger | T. Strom | S. O’Rahilly | J. Flannick | A. Metspalu | T. Esko | M. Sandhu | L. Milani | E. Ingelsson | C. Meisinger | L. Scott | K. Mohlke | L. Bonnycastle | H. Stringham | P. Chines | A. Jackson | A. Swift | N. Narisu | R. Watanabe | L. Kinnunen | J. Tuomilehto | K. Owen | A. Morris | A. Doney | B. Voight | V. Lyssenko | N. Burtt | J. Florez | B. Isomaa | O. Melander | P. Nilsson | M. Orho-Melander | T. Tuomi | R. Sladek | B. Balkau | P. Froguel | T. Illig | L. Lind | N. Tandon | R. DeFronzo | G. Buck | R. Rauramaa | A. Syvänen | J. Meigs | N. Wareham | Jianjun Liu | Han Chen | J. Dupuis | M. Horikoshi | A. Mahajan | C. Ladenvall | J. Ried | H. Grallert | M. Müller-Nurasyid | I. Prokopenko | P. Franks | B. Glaser | Y. S. Cho | Jong-Young Lee | B. Han | D. Bharadwaj | S. Ebrahim | M. Roden | C. Herder | W. Lim | K. Shakir | D. Saleheen | James G. Wilson | A. Gloyn | P. Njølstad | T. Schwarzmayr | J. Kooner | G. Jun | O. Gottesman | E. Bottinger | R. Pearson | I. Barroso | J. Howson | N. Robertson | Wei Zhao | L. Lannfelt | Ching-Yu Cheng | X. Sim | S. Musani | A. Manning | R. Scott | A. Stančáková | T. V. Varga | Weihua Zhang | T. Aung | A. Correa | C. Khor | J. Kuusisto | C. Langenberg | B. Lehne | M. Loh | N. Palmer | W. Scott | D. Bowden | J. Chambers | B. Freedman | James G. Scott | K. Chia | M. Go | J. Bork-Jensen | R. Loos | Ashish Kumar | L. Yengo | D. Rybin | P. Fontanillas | A. Wood | Jason P. Carey | Jasmina Kravic | B. Thorand | J. Trakalo | C. Palmer | L. Qi | T. Lauritzen | D. Buck | J. Curran | L. Moutsianas | M. Griswold | A. Butterworth | C. Fuchsberger | H. Boeing | A. Linneberg | D. Palli | G. Surdulescu | M. Stitzel | R. Welch | C. Huth | U. Afzal | A. Locke | D. Pasko | V. Giedraitis | Yingchang Lu | H. Highland | M. Ng | C. Christensen | Mette Hollensted | M. Jørgensen | F. Karpe | J. Kriebel | M. Neville | O. Rolandsson | A. Gjesing | Sian-Tsung Tan | Jinyan Huang | J. Fadista | A. Käräjämäki | A. Rosengren | Y. Farjoun | T. Pollin | M. van de Bunt | Y. T. van der Schouw | Vineeta Agarwala | Pablo Cingolani | Clement Ma | T. Blackwell | N. Rayner | J. Fernandez Tajes | J. Huyghe | Jaehoon Lee | Yuhui Chen | J. Below | Peng Chen | N. Beer | A. Day-Williams | T. Fingerlin | Cheng Hu | Iksoo Huh | M. Ikram | Bong-Jo Kim | Yongkang Kim | Min-Seok Kwon | Juyoung Lee | Selyeong Lee | Keng-Han Lin | Yoshihiko Nagai | Xu Wang | Joon Yoon | N. Barzilai | C. Jenkinson | T. Kuulasmaa | H. Abboud | Phoenix Kwan | Heung Man Lee | S. Kwak | V. Lam | K. Park | C. Tam | D. Aguilar | R. Arya | E. Chan | C. Navarro | V. Farook | S. Fowler | D. Hale | P. Hicks | Satish Kumar | D. Thuillier | S. Puppala | H. Taylor | F. Thameem | G. Wilson | H. Koistinen | Liisa Hakaste | Dylan Hodgkiss | Q. Qi | C. Blancher | M. D. de Angelis | Jacquelyn Murphy | G. Chandak | D. Lehman | W. Jia | T. Park | G. Atzmon | G. Bell | C. Hanis | Mark Seielstad | Sharon P Fowler | N. Cox | T. Varga | K. Gaulton | D. Hodgkiss | Khalid Shakir | Y. Cho | S. Tan | A. Morris | Weihua Zhang | J. Scott | R. Watanabe | Wei Zhao | Narisu Narisu | Dorothée Thuillier | J. Kravic | T. Wong | J. Perry | R. Scott | A. Morris | João Fadista | R. Loos | Annemari Käräjämäki | R. Scott | M. McCarthy | T. Wong | P. Kwan | R. Scott | T. Wong | T. Hansen | Xu Wang | F. Hu | A. Peters | A. Jackson | Todd Green | M. McCarthy | T. Wong | Wei Zhao | A. Correa | C. H. Tam | C. Palmer | L. Moutsianas | Denis Rybin | W. Lim | A. Peters | T. Wong | P. Fontanillas | J. Chan | A. Morris

[1]  D. Falconer The inheritance of liability to certain diseases, estimated from the incidence among relatives , 1965 .

[2]  W. R. Rice A Consensus Combined P-Value Test and the Family-wide Significance of Component Tests , 1990 .

[3]  D. Firth Bias reduction of maximum likelihood estimates , 1993 .

[4]  S. Baylin,et al.  RREB1, a ras responsive element binding protein, maps to human chromosome 6p25. , 1997, Genomics.

[5]  K. Roeder,et al.  Genomic Control for Association Studies , 1999, Biometrics.

[6]  Ahmed Mansouri,et al.  Opposing actions of Arx and Pax4 in endocrine pancreas development. , 2003, Genes & development.

[7]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[8]  D. Reich,et al.  Principal components analysis corrects for stratification in genome-wide association studies , 2006, Nature Genetics.

[9]  P. Donnelly,et al.  A new multipoint method for genome-wide association studies by imputation of genotypes , 2007, Nature Genetics.

[10]  Jon Wakefield,et al.  A Bayesian measure of the probability of false discovery in genetic epidemiology studies. , 2007, American journal of human genetics.

[11]  Pall I. Olason,et al.  A human phenome-interactome network of protein complexes implicated in genetic disorders , 2007, Nature Biotechnology.

[12]  Simon C. Potter,et al.  Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls , 2007, Nature.

[13]  B. Browning,et al.  Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. , 2007, American journal of human genetics.

[14]  K. Shianna,et al.  Long-range LD can confound genome scans in admixed populations. , 2008, American journal of human genetics.

[15]  Joshua M. Korn,et al.  Integrated genotype calling and association analysis of SNPs, common copy number polymorphisms and rare CNVs , 2008, Nature Genetics.

[16]  Kenneth M. Weiss,et al.  ForSim: a tool for exploring the genetic architecture of complex traits with controlled truth , 2008, Bioinform..

[17]  A. Hattersley,et al.  Clinical implications of a molecular genetic classification of monogenic β-cell diabetes , 2008, Nature Clinical Practice Endocrinology &Metabolism.

[18]  Judy H. Cho,et al.  Finding the missing heritability of complex diseases , 2009, Nature.

[19]  K. Narayan,et al.  Clinical risk factors, DNA variants, and the development of type 2 diabetes. , 2009, The New England journal of medicine.

[20]  D. Reich,et al.  Sensitive Detection of Chromosomal Segments of Distinct Ancestry in Admixed Populations , 2009, PLoS genetics.

[21]  F. Collins,et al.  Potential etiologic and functional implications of genome-wide association loci for human diseases and traits , 2009, Proceedings of the National Academy of Sciences.

[22]  Richard Durbin,et al.  Sequence analysis Fast and accurate short read alignment with Burrows – Wheeler transform , 2009 .

[23]  Ayellet V. Segrè,et al.  Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis , 2010, Nature Genetics.

[24]  M. DePristo,et al.  The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. , 2010, Genome research.

[25]  M. King,et al.  Genetic Heterogeneity in Human Disease , 2010, Cell.

[26]  Manolis Kellis,et al.  Discovery and characterization of chromatin states for systematic annotation of the human genome , 2010, Nature Biotechnology.

[27]  H. Kang,et al.  Variance component model to account for sample structure in genome-wide association studies , 2010, Nature Genetics.

[28]  David B. Goldstein,et al.  Rare Variants Create Synthetic Genome-Wide Associations , 2010, PLoS biology.

[29]  Yun Li,et al.  METAL: fast and efficient meta-analysis of genomewide association scans , 2010, Bioinform..

[30]  Karen L. Mohlke,et al.  A map of open chromatin in human pancreatic islets , 2010, Nature Genetics.

[31]  P. Visscher,et al.  Common SNPs explain a large proportion of heritability for human height , 2011 .

[32]  Eric S. Lander,et al.  Comparative Epigenomic Analysis of Murine and Human Adipogenesis , 2010, Cell.

[33]  M. Boehnke,et al.  Transferability of Type 2 Diabetes Implicated Loci in Multi-Ethnic Cohorts from Southeast Asia , 2011, PLoS genetics.

[34]  M. DePristo,et al.  A framework for variation discovery and genotyping using next-generation DNA sequencing data , 2011, Nature Genetics.

[35]  Tien Yin Wong,et al.  Genome-wide association study in individuals of South Asian ancestry identifies six new type 2 diabetes susceptibility loci , 2011, Nature Genetics.

[36]  D. Altshuler,et al.  Power in the phenotypic extremes: a simulation study of power in discovery and replication of rare variants , 2011, Genetic epidemiology.

[37]  Naomi R. Wray,et al.  Synthetic Associations Created by Rare Variants Do Not Explain Most GWAS Results , 2011, PLoS biology.

[38]  David B. Goldstein,et al.  The Importance of Synthetic Associations Will Only Be Resolved Empirically , 2011, PLoS biology.

[39]  N Slimani,et al.  Design and cohort description of the InterAct Project: an examination of the interaction of genetic and lifestyle factors on the incidence of type 2 diabetes in the EPIC Study , 2011, Diabetologia.

[40]  Joshua M. Korn,et al.  Discovery and genotyping of genome structural polymorphism by sequencing on a population scale , 2011, Nature Genetics.

[41]  G. Abecasis,et al.  Low-coverage sequencing: implications for design of complex trait association studies. , 2011, Genome research.

[42]  P. Visscher,et al.  GCTA: a tool for genome-wide complex trait analysis. , 2011, American journal of human genetics.

[43]  E. Zeggini,et al.  Synthetic Associations Are Unlikely to Account for Many Common Disease Genome-Wide Association Signals , 2011, PLoS biology.

[44]  Wei Zheng,et al.  dmGWAS: dense module searching for genome-wide association studies in protein-protein interaction networks , 2011, Bioinform..

[45]  A. Price,et al.  New approaches to disease mapping in admixed populations , 2011, Nature Reviews Genetics.

[46]  A. Morris,et al.  Transethnic Meta-Analysis of Genomewide Association Studies , 2011, Genetic epidemiology.

[47]  P. Visscher,et al.  Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits , 2012, Nature Genetics.

[48]  Haiyuan Yu,et al.  Detecting overlapping protein complexes in protein-protein interaction networks , 2012, Nature Methods.

[49]  Bronwen L. Aken,et al.  GENCODE: The reference human genome annotation for The ENCODE Project , 2012, Genome research.

[50]  Wei Lu,et al.  Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians , 2011, Nature Genetics.

[51]  Jake K. Byrnes,et al.  Bayesian refinement of association signals for 14 loci in 3 common diseases , 2012, Nature Genetics.

[52]  Data production leads,et al.  An integrated encyclopedia of DNA elements in the human genome , 2012 .

[53]  Shane J. Neph,et al.  Systematic Localization of Common Disease-Associated Variation in Regulatory DNA , 2012, Science.

[54]  Kenny Q. Ye,et al.  An integrated map of genetic variation from 1,092 human genomes , 2012, Nature.

[55]  ENCODEConsortium,et al.  An Integrated Encyclopedia of DNA Elements in the Human Genome , 2012, Nature.

[56]  M. McCarthy,et al.  Exome sequencing-driven discovery of coding polymorphisms associated with common metabolic phenotypes , 2012, Diabetologia.

[57]  Inês Barroso,et al.  Rare MTNR1B variants impairing melatonin receptor 1B function contribute to type 2 diabetes , 2012, Nature Genetics.

[58]  Tanya M. Teslovich,et al.  Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes , 2012, Nature Genetics.

[59]  G. Abecasis,et al.  Detecting and estimating contamination of human DNA samples in sequencing and array-based genotype data. , 2012, American journal of human genetics.

[60]  Xihong Lin,et al.  Optimal tests for rare variant effects in sequencing association studies. , 2012, Biostatistics.

[61]  H. Furuta,et al.  Defective PAX4 R192H transcriptional repressor activities associated with maturity onset diabetes of the young and early onset-age of type 2 diabetes. , 2012, Journal of diabetes and its complications.

[62]  Michael Boehnke,et al.  Recommended Joint and Meta‐Analysis Strategies for Case‐Control Association Testing of Single Low‐Count Variants , 2013, Genetic epidemiology.

[63]  Christian Fuchsberger,et al.  Exome array analysis identifies new loci and low-frequency variants influencing insulin processing and secretion , 2012, Nature Genetics.

[64]  K. Liestøl,et al.  Production of phosphatidylinositol 5‐phosphate via PIKfyve and MTMR3 regulates cell migration , 2013, EMBO reports.

[65]  Stephen C. J. Parker,et al.  Chromatin stretch enhancer states drive cell-specific gene regulation and harbor human disease risk variants , 2013, Proceedings of the National Academy of Sciences.

[66]  Seunggeun Lee,et al.  General framework for meta-analysis of rare variants in sequencing association studies. , 2013, American journal of human genetics.

[67]  Y. J. Kim,et al.  Genome-wide association study in a Chinese population identifies a susceptibility locus for type 2 diabetes at 7q32 near PAX4 , 2013, Diabetologia.

[68]  Jason Flannick,et al.  Evaluating empirical bounds on complex disease genetic architecture , 2013, Nature Genetics.

[69]  Cedric Gondro,et al.  Quality control for genome-wide association studies. , 2013, Methods in molecular biology.

[70]  J. Marchini,et al.  Multiway Admixture Deconvolution Using Phased or Unphased Ancestral Panels , 2013, Genetic epidemiology.

[71]  Søren Brunak,et al.  Whole-exome sequencing of 2,000 Danish individuals and the role of rare coding variants in type 2 diabetes. , 2013, American journal of human genetics.

[72]  Amy L. Williams,et al.  Association of a low-frequency variant in HNF1A with type 2 diabetes in a Latino population. , 2014, JAMA.

[73]  Anne Tybjærg-Hansen,et al.  Exome-wide association study identifies a TM6SF2 variant that confers susceptibility to nonalcoholic fatty liver disease , 2014, Nature Genetics.

[74]  Kari Stefansson,et al.  Identification of low-frequency and rare sequence variants associated with elevated or reduced risk of type 2 diabetes , 2014, Nature Genetics.

[75]  Tanya M. Teslovich,et al.  Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility , 2014, Nature Genetics.

[76]  J. Al-Aama,et al.  A common Greenlandic TBC1D4 variant confers muscle insulin resistance and type 2 diabetes , 2014, Nature.

[77]  Mark I. McCarthy,et al.  Pancreatic islet enhancer clusters enriched in type 2 diabetes risk–associated variants , 2013, Nature Genetics.

[78]  E. Lander,et al.  Genetic Screens in Human Cells Using the CRISPR-Cas9 System , 2013, Science.

[79]  Bernhard Horsthemke,et al.  Leveraging Cross-Species Transcription Factor Binding Site Patterns: From Diabetes Risk Loci to Disease Mechanisms , 2014, Cell.

[80]  Joseph K. Pickrell Joint analysis of functional genomic data and genome-wide association studies of 18 human traits , 2013, bioRxiv.

[81]  Thomas Meitinger,et al.  Loss-of-function mutations in SLC30A8 protect against type 2 diabetes , 2014, Nature Genetics.

[82]  Eric S. Lander,et al.  A polygenic burden of rare disruptive mutations in schizophrenia , 2014, Nature.

[83]  Pierre Fontanillas,et al.  Rare variants in PPARG with decreased activity in adipocyte differentiation are associated with increased risk of type 2 diabetes , 2014, Proceedings of the National Academy of Sciences.

[84]  Tanya M. Teslovich,et al.  Sequence variants in SLC16A11 are a common risk factor for type 2 diabetes in Mexico , 2013, Nature.

[85]  A. Hamsten,et al.  TM6SF2 is a regulator of liver fat metabolism influencing triglyceride secretion and hepatic lipid droplet content , 2014, Proceedings of the National Academy of Sciences.

[86]  T. Spector,et al.  The Concordance and Heritability of Type 2 Diabetes in 34,166 Twin Pairs From International Twin Registers: The Discordant Twin (DISCOTWIN) Consortium , 2015, Twin Research and Human Genetics.

[87]  Christian Gieger,et al.  Genetic fine-mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci , 2016 .

[88]  Gonçalo R. Abecasis,et al.  Minimac2: Faster Genotype Imputation , 2015, Bioinform..