The Impacts of IL1R1 and IL1R2 Genetic Variants on Rheumatoid Arthritis Risk in the Chinese Han Population: A Case-Control Study

Int J Gen Med. 2021 May 28:14:2147-2159. doi: 10.2147/IJGM.S291395. eCollection 2021.

Abstract

Background: Rheumatoid arthritis (RA), an autoimmune systemic inflammatory disease, largely resulted from genetic factor. Our purpose was to explore the association for IL1R1 and IL1R2 genetic variants with RA susceptibility in the Chinese Han population.

Patients and methods: A total of 508 RA patients and 494 controls were involved in this case-control study; single-nucleotide polymorphisms (SNPs) genotyping was identified by the Agena MassARRAY platform. The relationship between polymorphisms and RA susceptibility was calculated using the Pearson's Chi-square test with odds ratios and 95% confidence intervals (CIs) in multiple genetic models. The Pearson's Chi-square test and Student's t-test were used for sample basic characteristic analysis. And linkage disequilibrium (LD) analysis and haplotype analysis were performed by logistic regression analysis.

Results: The result from this study showed that rs2072472 (IL1R2) was an increased risk factor of RA (adjusted OR = 1.41, p = 0.011). Stratified analysis indicated SNPs rs10490571, rs956730, rs3917318 of IL1R1, and SNPs rs4851527, rs719250, rs3218896, rs3218977, rs2072472 of IL1R2 had impacts on RA risk after stratification based on gender and average age (54 years). Finally, haplotype analysis revealed that Ars3218977Ars2072472 haplotype in IL1R2 was related to a decreased RA risk (adjusted OR = 0.79; 95% CI = 0.65-0.94; p = 0.010). Yet, rs3917225(IL1R1) and rs11674595(IL1R2) were not significant in RA association analysis.

Conclusion: We determined SNPs (rs3917318, rs956730, rs1049057) of IL1R1 and SNPs (rs3218977, rs719250, rs4851527, rs3218896, rs2072472) of IL1R2 were correlated with the RA susceptibility in the Chinese Han population.

Keywords: IL1R1/IL1R2; RA; SNP; rheumatoid arthritis; single-nucleotide polymorphism; susceptibility.

Grants and funding

We acknowledge financial support from the Natural Science Foundation of Tibet Autonomous Region (Grant No. xz2019zrg-28 (z)) and the National Natural Science Foundation of China (Grant No. 81960291).