Prioritizing Candidate Genes for Type 2 Diabetes Mellitus using Integrated Network and Pathway Analysis

Area of Science:

• Genetics
• Molecular Biology
• Bioinformatics

Background:

• Type 2 Diabetes Mellitus (T2DM) is a global health crisis with significant mortality and socioeconomic impact.
• Understanding the genetic basis of T2DM is crucial for developing effective treatments.
• Millions in India suffer from T2DM, highlighting the need for targeted management strategies.

Purpose of the Study:

• To identify candidate genes and molecular pathways underlying Type 2 Diabetes Mellitus.
• To prioritize genes associated with T2DM through integrated network and pathway analysis.
• To uncover potential therapeutic targets for T2DM management.

Main Methods:

• Utilized integrated gene network and ontology analyses.
• Performed sequential interaction network and gene set enrichment analysis on T2DM-associated genes.
• Assessed interrelations between high-ranking network clusters and biological pathways.

Main Results:

• Prioritized 23 significant candidate genes from 615 T2DM-associated genes.
• Identified overrepresentation in pathways critical to insulin resistance and T2DM.
• Highlighted signaling cascades including insulin receptor, PI3K, IGFR, ERBB, and MAPK pathways.

Conclusions:

• Identified EGFR and IGF1R tyrosine kinase receptor genes as common nodes.
• These genes represent significant candidates for T2DM.
• Findings provide a foundation for understanding T2DM molecular mechanisms and potential interventions.