In silico functional and pathway analysis of risk genes and SNPs for type 2 diabetes in Asian population

Abstract

Type 2 diabetes (T2D) has earned widespread recognition as a primary cause of death, disability, and increasing healthcare costs. There is compelling evidence that hereditary factors contribute to the development of T2D. Clinical trials in T2D have mostly focused on genes and single nucleotide polymorphisms (SNPs) in protein-coding areas. Recently, it was revealed that SNPs located in noncoding areas also play a significant impact on disease vulnerability. It is required for cell type-specific gene expression. However, the precise mechanism by which T2D risk genes and SNPs work remains unknown. We integrated risk genes and SNPs from genome-wide association studies (GWASs) and performed comprehensive bioinformatics analyses to further investigate the functional significance of these genes and SNPs. We identified four intriguing transcription factors (TFs) associated with T2D. The analysis revealed that the SNPs are engaged in chromatin interaction regulation and/or may have an effect on TF binding affinity. The Gene Ontology (GO) study revealed high enrichment in a number of well-characterized signaling pathways and regulatory processes, including the STAT3 and JAK signaling pathways, which are both involved in T2D metabolism. Additionally, a detailed KEGG pathway analysis identified two major T2D genes and their prospective therapeutic targets. Our findings underscored the potential functional significance of T2D risk genes and SNPs, which may provide unique insights into the disease’s pathophysiology.