Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes

Eleftheria Zeggini, Michael N Weedon, Cecilia M Lindgren, Timothy M Frayling, Katherine S Elliott, Hana Lango, Nicholas J Timpson, John R B Perry, Nigel W Rayner, Rachel M Freathy, Jeffrey C Barrett, Beverley Shields, Andrew P Morris, Sian Ellard, Christopher J Groves, Lorna W Harries, Jonathan L Marchini, Katharine R Owen, Beatrice Knight, Lon R CardonMark Walker, Graham A Hitman, Andrew D Morris, Alex S F Doney, Mark I McCarthy, Andrew T Hattersley, Wellcome Trust Case Control Consortium, Alastair Forbes

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1815 Citations (Scopus)

Abstract

The molecular mechanisms involved in the development of type 2 diabetes are poorly understood. Starting from genome-wide genotype data for 1924 diabetic cases and 2938 population controls generated by the Wellcome Trust Case Control Consortium, we set out to detect replicated diabetes association signals through analysis of 3757 additional cases and 5346 controls and by integration of our findings with equivalent data from other international consortia. We detected diabetes susceptibility loci in and around the genes CDKAL1, CDKN2A/CDKN2B, and IGF2BP2 and confirmed the recently described associations at HHEX/IDE and SLC30A8. Our findings provide insight into the genetic architecture of type 2 diabetes, emphasizing the contribution of multiple variants of modest effect. The regions identified underscore the importance of pathways influencing pancreatic beta cell development and function in the etiology of type 2 diabetes.
Original languageEnglish
Pages (from-to)1336-41
Number of pages6
JournalScience
Volume316
Issue number5829
DOIs
Publication statusPublished - 1 Jun 2007

Keywords

  • Adult
  • Aged
  • Case-Control Studies
  • Chromosome Mapping
  • Diabetes Mellitus, Type 2
  • Female
  • Genes, p16
  • Genetic Predisposition to Disease
  • Genome, Human
  • Great Britain
  • Homeodomain Proteins
  • Humans
  • Insulin-Like Growth Factor Binding Proteins
  • Introns
  • Male
  • Meta-Analysis as Topic
  • Middle Aged
  • Oligonucleotide Array Sequence Analysis
  • Polymorphism, Single Nucleotide
  • Transcription Factors

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