Yonghui Yang, Shan Yuan, Meihua Che, Haiyin Jing, Limin Yuan, Kuaini Dong, Tianbo Jin
Molecular genetics & genomic medicine 2019 JulThe biological mechanisms driving disease chronicity in rheumatoid arthritis (RA) are largely unidentified. Therefore, we aimed to determine genetic risk factors for RA. In this case-control study, which includes samples from 499 patients and 507 healthy controls, six single-nucleotide polymorphisms (SNPs) in interleukin-2 receptor subunit alpha (IL2RA) and IL2RB were selected. Genotyping was performed using the Agena MassARRAY platform, and the statistical analyses were performed using the chi-squared and Fisher's exact tests, genetic model analysis, and haplotype analysis. In the allele model, using the chi-squared test, the result showed that rs791588 in IL2RA was associated with a decreased RA risk (odds ratios [OR] = 0.74, 95% confidence intervals [CI] = 0.62-0.89, p = 0.0014) after adjusting for age and gender. In the genetic model, logistic regression analyses revealed that rs791588 was associated with a decreased risk of RA under the codominant model, dominant model, recessive model, and log-additive model. Stratification analysis revealed that two SNPs (rs791588 and rs2281089) were significantly associated with a reduced RA risk in an allele and genetic model after stratification by gender or age (p < 0.05). In addition, the haplotypes "Crs12569923 Grs791588 " and "Crs12569923 Trs791588 " of IL2RA was associated with an increased risk of RA adjusted by age and gender (OR = 1.35, 95% CI: 1.12-1.64, p = 0.0016; OR = 1.24, 95% CI: 1.03-1.48, p = 0.021). This finding indicates that the inherited altered genetic constitution at IL2RA may predispose to a less destructive course of RA. © 2019 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.
Yonghui Yang, Shan Yuan, Meihua Che, Haiyin Jing, Limin Yuan, Kuaini Dong, Tianbo Jin. Genetic analysis of the relation between IL2RA/IL2RB and rheumatoid arthritis risk. Molecular genetics & genomic medicine. 2019 Jul;7(7):e00754
PMID: 31134763
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