Comprehensive bioinformatics analysis of HLA-DRB1 in multiple sclerosis and immune regulation: insights into transcription factors, genetic variants, and disease associations

Abstract

HLA-DRB1, a highly polymorphic gene within the major histocompatibility complex class II (MHC-II) region, plays a central role in adaptive immune responses by presenting antigens to CD4⁺ T cells. Its strong genetic association with multiple sclerosis (MS) and other autoimmune diseases is well-documented, particularly through specific alleles such as HLA-DRB1∗15:01. However, the transcriptional regulation mechanisms and broader functional implications of non-coding polymorphisms remain insufficiently characterized. In this study, we employed a comprehensive in silico bioinformatics approach to: (1) identify transcription factors (TFs) involved in the regulation of HLA-DRB1 expression in MS, and (2) characterize genetic variants influencing disease susceptibility. Using sequence motif analysis, expression databases (GTEx, ExpressionAtlas, Bgee), and transcription factor binding site (TFBS) prediction tools (e.g., MatInspector), we identified HOXF, ABDB, ETS1, and ETV1 as potential regulators contributing to aberrant HLA-DRB1 expression. This transcriptional dysregulation may contribute to immune activation in MS. We further analyzed polymorphisms located in regulatory regions (e.g., 5′UTR, 3′UTR) and presented their statistical associations with MS risk, including odds ratios, confidence intervals, and p-values from genome-wide association studies. Notably, HLA-DRB1 variants not only influence autoimmune disease risk but may also impact immune evasion mechanisms in cancer, implicating the gene in tumor immunology. These findings enhance the understanding of HLA-DRB1’s regulatory complexity and highlight its potential as a therapeutic target. The study provides a reproducible computational framework for investigating MHC gene regulation, with implications for both autoimmunity and oncology.