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, Ian N. Bruce, Hannah Donovan, Steve Eyre, Paul D. Gilbert, Samantha L. Hider, Anne M. Hinks, Sally L. John, Catherine Potter, Alan J. Silman, Deborah P M Symmons, Wendy Thomson, Jane Worthington

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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)1336-1341
Number of pages6
Issue number5829
Publication statusPublished - 1 Jun 2007


Dive into the research topics of 'Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes'. Together they form a unique fingerprint.

Cite this