Finding pathways central to the pathogenesis of T2D through the integration of genetic and genomic data.

Background:

Novel therapeutic strategies need to be informed by a more complete understanding of the molecular and physiological basis of type 2 diabetes, designed to deliver validated interventional targets and biomarkers that can be used to define disease risk, progression, and subtype. We are using human genetics to deliver this understanding, and, working as part of large global consortia have interrogated several large genetic resources (~1,200,000 samples with GWAS and exome array data; ~55,000 with exome sequence data; several thousand whole genome sequences with tens of thousands more arriving via TOPMED and other project), and have contributed to identification of >100 T2D-associated regions. We are currently leading efforts to perform a massive transethnic analysis of T2D association, involving GWAS data from >1M individuals, which will define additional regions associated with T2D and further refine the location of the variants driving disease risk. Most of these will map to regulatory sequence, and most seem to act through perturbation of pancreatic islet function.

To define the molecular and cellular processes through which these risk variants act, we have been establishing a detailed genomic map of islet regulatory features incorporating RNA-Seq, ChiP-Seq, ATAC-Seq, Methylation-Seq and Capture-C conformational capture. By intersecting these data with the genetic maps, we are now in a position to highlight the processes which underlying T2D predisposition. The acquisition of richer genetic and genomic information continues, and this DPhil project will involve analysis of these growing genetic and genomic data sets and the systematic identification of key processes involved in the development of T2D. This work is funded by the Wellcome Trust and the US National Institutes of Health.

Description of the work:

The DPhil project will involve several components
•Analysis of the transethnic GWAS data sets described above, to identify new signals, and to fine-map others;
•Analysis and interpretation of additional islet genomic data (e.g. from conformational capture studies) and integration with the genetic data
•The identification of regulatory elements that are globally enriched for T2D association signals, as well as those that are likely to be perturbed at individual loci
•Design and implementation of follow-up studies.