Review Addressing the HLADR3 and HLA-DR4 Haplotypes in the Susceptibility of Type 1 Diabetes: A Bioinformatic Analysis View Full-Text

Document Type : Review Article

Authors

1 Zist Fanavari Novin Biotechnology Institute, Iran Technical and Vocational Training Organization, Isfahan, Iran

2 Isfahan University of Medical Sciences, Isfahan, Iran

Abstract

Background: Type 1 diabetes (T1D) is a multifactorial autoimmune disease characterized immune-mediated destruction of pancreatic β-cells and influenced by a combination of genetic and environmental factors. Among the genetic factors, the human leukocyte antigen (HLA) region, especially the HLA-DR3 and HLA-DR4 haplotypes, plays a key role in increasing disease susceptibility. These haplotypes are thought to mediate increased auto-antigen presentation to autoreactive CD4⁺ T-helper cells leading to β-cell destruction.
Methods: This review study examines the bioinformatic perspective of SNPs and ncRNAs related to the HLA region in T1D and analyzes studies published between 2015 and 2025. The dbSNP and ClinVar databases were used to identify four key SNPs: rs3135002, rs9260151, rs9271365, and rs9273364, all located within or near the major histocompatibility complex (MHC) class II region. Although their clinical significance is not definitively confirmed in ClinVar, data from GWAS suggest their potential association with T1D. Analysis using the miRWalk tool indicated that hsa-miR-5585-3p may target the HLA-DQA1 gene, and results from lncRRIsearch suggested that lncRNA RP11-573D15.8-018 may also interact with this same gene.
Findings: Although their clinical significance is not definitively confirmed in ClinVar, data from GWAS suggest their potential association with T1D. Analysis using the miRWalk tool indicated that hsa-miR-5585-3p may target the HLA-DQA1 gene, and results from lncRRIsearch suggested that lncRNA RP11-573D15.8-018 may also interact with this same gene.
Conclusion: The present review focuses on the importance of HLA-DR3 and HLA-DR4 haplotypes in increasing susceptibility to type 1 diabetes and points to the potential regulatory effects of specific SNPs, microRNAs, and lncRNAs in HLA-DQA1 gene expression. These results underscore the utility of bioinformatics for revealing molecular mechanisms of T1D and possibly for designing personalized diagnostic and therapeutic approaches.

Highlights

Mansoureh Azadeh: Google Scholar 

Marjan Zareian Jahromi: Google Scholar

Keywords

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Journal of Isfahan Medical School
Volume 43, Issue 815
3rd Week, July
July and August 2025
Pages 527-532

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History

  • Receive Date: 03 June 2025
  • Accept Date: 12 August 2025

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