In Silico Analysis: HLA-DRB1 Gene’s Variants and Their Clinical Impact

Abstract

The HLA-DRB1 gene encodes a protein that is essential for the immune system. This gene is important in organ transplant rejection and acceptance, as well as multiple sclerosis, systemic lupus erythematosus, Addison’s disease, rheumatoid arthritis, caries susceptibility, and Aspirin-exacerbated respiratory disease. The following Homo sapiens variants were investigated: single-nucleotide variants (SNVs), multi-nucleotide variants (MNVs), and small insertions–deletions (Indels) in the HLA-DRB1 gene via coding and untranslated regions. The current study sought to identify functional variants that could affect gene expression and protein product function/structure. ALL target variants available until April 14, 2022, were obtained from the Single Nucleotide Polymorphism database (dbSNP). Out of all the variants in the coding region, 91 nsSNVs were considered highly deleterious by seven prediction tools and instability index; 25 of them are evolutionary conserved and located in domain regions. Furthermore, 31 indels were predicted as harmful, potentially affecting a few amino acids or even the entire protein. Last, within the coding sequence (CDS), 23 stop-gain variants (SNVs/indels) were predicted as high impact. High impact refers to the assumption that the variant will have a significant (disruptive) effect on the protein, likely leading to protein truncation or loss of function. For untranslated regions, functional 55 single-nucleotide polymorphisms (SNPs), and 16 indels located within microRNA binding sites, furthermore, 10 functionally verified SNPs were predicted at transcription factor-binding sites. The findings demonstrate that employing in silico methods in biomedical research is extremely successful and has a major influence on the capacity to identify the source of genetic variation in diverse disorders. In conclusion, these previously functional identified variants could lead to gene alteration, which may directly or indirectly contribute to the occurrence of many diseases. The study’s results could be an important guide in the research of potential diagnostic and therapeutic interventions that require experimental mutational validation and large-scale clinical trials.