Multi-Omics Analysis Revealed the rSNPs Potentially Involved in T2DM Pathogenic Mechanism and Metformin Response

Area of Science:

• Genetics and Bioinformatics
• Molecular Biology
• Pharmacogenomics

Background:

• Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder with a significant genetic component.
• Identifying functional single nucleotide polymorphisms (SNPs) is crucial for understanding T2DM development and personalized treatment responses to antihyperglycemic medications like metformin.

Purpose of the Study:

• To identify and functionally assess regulatory SNPs (rSNPs) associated with T2DM and metformin response.
• To provide a molecular basis for T2DM genetic associations and guide pharmacogenomic strategies.

Main Methods:

• Bioinformatics analysis of ChIP-seq and RNA-seq data from human peripheral blood mononuclear cells (PBMCs).
• Integration with public datasets including Genome-Wide Association Studies (GWAS), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO).
• Analysis of differentially expressed genes (DEGs) and regulatory SNPs using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment.

Main Results:

• Identified 14,796 rSNPs in PBMC gene promoters, with 4,280 associated with T2DM traits and expression quantitative trait loci (eQTLs).
• Discovered 3,810 rSNPs in DEGs between T2DM patients and controls, highlighting 31 upregulated hub genes involved in inflammation, obesity, and insulin resistance.
• Found 367 rSNPs in DEGs between metformin responders and non-responders, with transcription factors being a prominent gene group.

Conclusions:

• The study provides a list of human rSNPs that functionally interpret GWAS signals for T2DM.
• Identified candidate causal regulatory variants for T2DM, enriched in pathways critical for glucose metabolism, inflammation, and metformin action.
• These findings support personalized medicine approaches for T2DM management.