Susceptibility gene identification in type 2 diabetes and related conditions

The group has access, through national and international collaborations, to extensive family collections, case-control samples and population cohorts necessary for susceptibility gene identification. In the past we have pursued large-scale linkage analysis (followed by positional cloning within regions of interest) and candidate gene association analyses as our main tools. For example, we are leading an international group of researchers within the NIH-funded "international 1q consortium" to map the gene(s) underlying the type 2 diabetes linkage signal on chromosome 1q, now seen in 10 different studies employing an indirect linkage disequilibrium mapping strategy using high-throughput genotyping platforms. Our recent candidate gene studies have included large scale (6000-10000 subjects) analyses of genome sequence variation within a number of interesting genes, these studies either extending (e.g PPARG, KCNJ11, TCF7L2) or refuting (e.g. INS, USF1, IDE) associations previously-reported.

Our main focus over the coming year will be the analysis of the data arising from the diabetes component of the Wellcome Trust Case Control Consortium (www.wtccc.org.uk). The Oxford group (in partnership with the group of Andrew Hattersley in Exeter) has primary responsibility for the analysis of the T2D component of this study (which is typing 2000 T2D cases and 3000 controls on the 500k Affymetrix chip). Genotype collection is almost complete, and analysis will proceed over the autumn. We have strong collaborative links to other groups undertaking type 2 diabetes genome wide scans worldwide, and have formed an alliance (the IGWANA consortium) which is committed to early data-sharing and rapid execution of meta-analyses across the 8000 or so T2D subjects (and equivalent numbers of controls) that are currently being scanned by various groups worldwide. For this and our other work we maintain very close and productive ties to the Statistical Genetics and Bioinformatics groups at the Wellcome Trust centre for Human Genetics (led by Lon Cardon and Richard Mott respectively, and including Andrew Morris, Steven Wiltshire, and through joint sponsorship of her fellowship, Ele Zeggini) and to the Dept of Statistics (Peter Donnelly, Gil McVean, Jonathan Marchini).

We also have a research program in the genetics of polycystic ovarian syndrome (collaboration with Steve Franks, Imperial) and in the genetic basis of variation in early growth phenotypes (collaborations with Prof MarjoRiitta Jarvelin, Imperial; Prof Chris Power, ICH and others). Anna Gloyn (University Research Lecturer) and Katharine Owen (Clinical Lecturer) are continuing their work to identify and characterize genes implicated in less common forms of diabetes (and related conditions) including lipodystrophy, maturity onset diabetes of the young, neonatal diabetes, severe forms of insulin resistance and hyperinsulinaemia of infancy.