ASSOCIATION OF TYPE 1 DIABETES WITH POLYMORPHIC ALLIES OF HLA CLASS II GENES IN POPULATION OF YAKUTS
For the first time, a molecular genetic analysis of the frequency distribution of alleles and genotypes of polymorphisms rs3104413, rs2854275 and rs9273363 of the HLA-DQA1 and HLA-DQB1 genes, respectively, was carried out in the Yakut population. 92 patients diagnosed with type 1 diabetes were tested, 44 of which belonged to men and 48 women. The average age of patients was 23.04 ± 0.27 years (from 4 to 56 years). A sample of 210 healthy volunteers was formed as a comparison group. Amplification of the HLA-DQA1 gene region containing the single nucleotide polymorphism rs3104413 was carried out in the process of real-time PCR, the HLA-DQB1 gene containing the rs2854275 and rs9273363 polymorphisms - allele specific PCR. Analysis of the distribution of genotypes showed that the most common genotype for the rs3104413 polymorphism in the group of patients with type 1 diabetes is C / C (69.6%), whereas in the control group the homozygous G / G variant was more common (41.1%). It was revealed that the most common genotype of the polymorphic variant rs2854275 in the control group is the homozygous genotype G / G (88.5%), and in the group of patients with type 1 diabetes the genotype G / T (56.3%). The polymorphic variant rs9273363 was characterized by a significantly low frequency of allele A (1.5%) in the group of healthy individuals compared with the group of patients with type 1 diabetes (53.6%). The highest relative risk indicators (RR) among the genotypes were found for the combination of the C / C genotype of the rs3104413 polymorphism with the heterozygous G / T genotype of the rs2854275 - RR polymorphism of 4.234 (p <0.001); for a combination of the C / C genotype of the rs3104413 polymorphism with the T / T genotype of the rs2854275 polymorphism - RR = 3.692 (p <0.001); for a combination of the G / G polymorphism rs3104413 genotype and the A / C genotype, the rs9273363 polymorphism corresponded to RR = 3.625 (p <0.001). The obtained data can be used as biological predictors of the development of type 1 diabetes in order to conduct timely personalized preventive measures.