Epidemiol Health System J. 2023;10(4): 170-174.
doi: 10.34172/ehsj.26068
  Abstract View: 439
  PDF Download: 199

Original Article

Association of HLA rs3135388 and rs9271366 Single-Nucleotide Polymorphisms With Multiple Sclerosis in the Chaharmahal and Bakhtiari Province, Iran

Shahrbanou Parchami Barjui 1 ORCID logo, Zahra Forouzandeh Shahrakei 2 ORCID logo, Nahid Jivad 1* ORCID logo

1 Cellular and Molecular Research Center, Basic Health Sciences Institute, Shahrekord University of Medical Sciences, Shahrekord, Iran
2 Deputy of Research and Technology, Shahrekord University of Medical Science, Shahrekord, Iran
*Corresponding Author: Nahid Jivad, Email: jivad_395@yahoo.com


Background and aims: Genetics and environment are synergistic in multiple sclerosis (MS). Human leukocyte antigen (HLA) class II has a strong genetic association with MS. The aim of this study was to determine the association of HLA rs3135388 and rs9271366 single-nucleotide polymorphisms (SNPs) with MS.

Methods: The rs3135388, rs9271366, and rs422951 SNPs were genotyped in 173 Iranian relapsing-remitting MS (RRMS) patients and 200 matched healthy controls, using the polymerase chain reaction-restriction fragment length polymorphism method. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using statistical software to estimate the risk factor for disease. The allele and genotype frequencies of SNPs were determined based on data analysis using SPSS, version 20.

Results: Our results identified a strong association in the allele distribution for both rs3135388 and rs9271366 SNP, such that the A allele of rs3135388 (OR=1.765; 95% CI: 1.071–2.909) and the G allele of rs9271366 were found to be more frequent in MS patients than in healthy controls (OR=1.861; 95% CI: 1.025–3.3378). The mutated G allele for rs422951 SNP was relatively frequent (OR=1.128; 95% CI: 0.745–1.707).

Conclusion: Our findings revealed the critical role of the rs3135388 and rs9271366 SNPs in MS disease progression. Genotyping MS patients could facilitate personalized medical management.

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Submitted: 04 Oct 2023
Revision: 26 Nov 2023
Accepted: 26 Nov 2023
ePublished: 29 Dec 2023
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