Computational analyses of type 2 diabetes-associated loci identified by genome-wide association studies.

BACKGROUND

Genome-wide association studies (GWAS) of type 2 diabetes (T2D) have discovered a number of loci that contribute to susceptibility to the disease. Future challenges include elucidation of functional mechanisms through which these GWAS-identified loci modulate T2D disease risk. The aim of the present study was to comprehensively characterize T2D associated single nucleotide polymorphisms (SNPs) and genes through computational approaches.

METHODS

Computational biology approaches used in the present study included comparative genomic analyses and functional annotation using GWAS3D and RegulomeDB, investigation of the effects of T2D-associated SNPs on miRNA binding and protein phosphorylation, and gene ontology, pathway enrichment, protein-protein interaction (PPI) networks and functional module analysis of T2D-associated genes from previously published GWAS.

RESULTS

Computational analysis identified a number of T2D GWAS-associated SNPs that were located at protein binding sites, including CCCTC-binding factor (CTCF), E1A binding protein p300 (EP300), hepatocyte nuclear factor 4alpha (HNF4A), transcription factor 7 like 2 (TCF7L2), forkhead box A1 (FOXA1) and A2 (FOXA2), and potentially affected the binding of miRNAs and protein phosphorylation. Pathway enrichment analysis confirmed two well-known maturity onset diabetes of the young and T2D pathways, whereas PPI network analysis identified highly interconnected "hub" genes, such as TCF7L2, melatonin receptor 1B (MTNR1B), and solute carrier family 30 (zinc transporter), member 8 (SLC30A8), that created two tight subnetworks.

CONCLUSIONS

The results provide objectives and clues for future experimental studies and further insights into the molecular pathogenesis of T2D.

© 2016 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and John Wiley & Sons Australia, Ltd.