Enrichment Analysis of Significant Variants from Multiple GWAS Datasets for Type 1 Diabetes Mellitus

Selvaraj, Naga Vignesh; Ghone, Nalinkanth Veerabadran

doi:10.30491/jabr.2024.470731.1767

Enrichment Analysis of Significant Variants from Multiple GWAS Datasets for Type 1 Diabetes Mellitus

Document Type : Original Article

Authors

Naga Vignesh Selvaraj ¹

Nalinkanth Veerabadran Ghone ²

¹ Department of Biotechnology, Sri Venkateswara College of Engineering, Post Bag No.1, Sriperumbudur Taluk - 602117, Kancheepuram, Tamil Nadu, India

² Department of Chemical Engineering, Sri Sivasubramaniya Nadar College of Engineering, Rajiv Gandhi Salai (OMR), Kalavakkam - 603110, Tamil Nadu, India

10.30491/jabr.2024.470731.1767

Abstract

Introduction: Genome-wide association studies (GWAS) have identified numerous genetic variants associated with Type 1 Diabetes Mellitus (T1DM). However, GWAS has limitations in detecting the cumulative effects of these variants. The current study aims to understand T1DM genetic architecture based on the cumulative effects of significant genetic variants from GWAS summary statistics, their corresponding genes and their association with regulatory pathways.
Materials and Methods: Understanding the cumulative effects of SNPs in pathways requires an integrated approach of combining results of multiple GWAS studies to perform Over-representation analysis and Gene Ontology enrichment analysis. Based on large sample sizes, 12 independent GWAS summary datasets were selected from the GWAS central database. Enrichment analyses were performed using the WEB-based Gene SeT AnaLysis Toolkit.
Results: Preliminary pathway enrichment analysis results containing 119 variants from the HLA region and 238 variants from other chromosomal regions show 49 gene ontology and four functional pathways as enriched categories. After assigning gene ID to noncoding variants, the pathway enrichment analysis identified 65 gene ontology and 15 functional pathways as enriched categories. Overall results emphasize the role of human leukocyte antigen class II and other significant variants from non-HLA regions correspondingly in immune response pathways and T cell differentiation, cytokine signalling, and immune system regulation pathways.
Conclusions: This study provides a foundation for future studies in understanding T1DM pathogenesis. Further investigation is needed to identify novel genetic signatures to reveal the T1DM pathogenesis mechanisms and detection at the genetic level.

Keywords

Type 1 Diabetes Mellitus

Genome Wide Association Studies

Pathway Enrichment Analysis

Over Representation Analysis

Gene Ontology