Developing a network view of type 2 diabetes risk pathways through integration of genetic, genomic and functional data.

ABSTRACT:

Background

Genome-wide association studies (GWAS) have identified several hundred susceptibility loci for type 2 diabetes (T2D). One critical, but unresolved, issue concerns the extent to which the mechanisms through which these diverse signals influencing T2D predisposition converge on a limited set of biological processes. However, the causal variants identified by GWAS mostly fall into a non-coding sequence, complicating the task of defining the effector transcripts through which they operate.

Methods

Here, we describe implementation of an analytical pipeline to address this question. First, we integrate multiple sources of genetic, genomic and biological data to assign positional candidacy scores to the genes that map to T2D GWAS signals. Second, we introduce genes with

SUBMITTER: Fernandez-Tajes J 

PROVIDER: S-EPMC6436236 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature