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All Journal The ASEAN Journal of Military and Preventive Medicine
Putrya Hawa
Faculty of Military Medicine, Republic of Indonesia Defense University, Bogor, Indonesia

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Human PPARG Gene Mutation as Risk Factor for Type 2 Diabetes Melitus: In Silico Analysis Naufal Yafi Rais Wiguna; Taufik Hidayat B; Putrya Hawa; Jonny Jonny
The ASEAN Journal of Military and Preventive Medicine Vol. 1 No. 1 (2024): January
Publisher : Perkumpulan Kedokteran Militer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47353/ajmpm.v1i1.1

Abstract

Introduction: Type 2 diabetes (T2DM) involves genetic and environmental factors. PPARG, encoding peroxisome proliferator-activated receptor gamma, is one of the key gene in T2DM development. Our study investigates PPARG variants' role as risk factor for T2DM by in silico analysis. Methods: We identified Single Nucleotide Polymorphisms (SNPs) within the PPARG gene via UniProt and analyzed their effects using Ensembl Variant Effect Predictor (VEP). The VEP analysis provided us four important indicators: impact assessment, Sorting Intolerant from Tolerant (SIFT) score, PolyPhen score, and clinical significance. We also investigated PPARG's interactions with other T2DM-related genes using StringDB. Results: In our analysis of 35 UniProt-sourced SNPs, 32 underwent successful VEP analysis.The SIFT indicators identified 23 of SNPs as deleterious, The PolyPhen identified 18 of SNPs as probably damaging . Impact assessments revealed that 27 had a moderate impact on gene function. Clinically, 8 of the SNPs were considered pathogenic and rs1805192 emerged as a notable risk factor for T2DM. Additionally, StringDB analysis confirmed PPARG's role in the T2DM-associated gene network, from the 25 proteins involved in T2DM, 21 of them exhibit correlations with PPARG. Discussion: PPARG SNPs variant has a significant impact on T2DM as a risk factor. However, SNPs associated with T2DM vary across different populations. Conclusion: Analysis of PPARG genetic variations highlights their significant association with T2DM susceptibility in specific populations. Bioinformatics tools are useful for investigating genetic mutations but require additional research, such as functional studies, to improve reliability as their outcomes are primarily predictions.
Co-Authors Jonny Jonny Naufal Yafi Rais Wiguna Taufik Hidayat B