Dataset Information

Genetic analysis of the relation between IL2RA/IL2RB and rheumatoid arthritis risk.

ABSTRACT: BACKGROUND:The biological mechanisms driving disease chronicity in rheumatoid arthritis (RA) are largely unidentified. Therefore, we aimed to determine genetic risk factors for RA. METHODS: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. RESULT: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). CONCLUSION:This finding indicates that the inherited altered genetic constitution at IL2RA may predispose to a less destructive course of RA.

SUBMITTER: Yang Y

PROVIDER: S-EPMC6625105 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Genetic analysis of the relation between IL2RA/IL2RB and rheumatoid arthritis risk.

Yang Yonghui Y Yuan Shan S Che Meihua M Jing Haiyin H Yuan Limin L Dong Kuaini K Jin Tianbo T

Molecular genetics & genomic medicine 20190527 7

<h4>Background</h4>The biological mechanisms driving disease chronicity in rheumatoid arthritis (RA) are largely unidentified. Therefore, we aimed to determine genetic risk factors for RA.<h4>Methods</h4>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 anal ...[more]

PMID: 31134763

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Project description:IntroductionAlthough rheumatoid arthritis (RA) is generally a chronic disease, a proportion of RA-patients achieve disease-modifying antirheumatic drug (DMARD)-free sustained remission, reflecting loss of disease-persistence. To explore mechanisms underlying RA-persistence, we performed a candidate gene study. We hypothesized that variants associating with lack of radiographic progression also associate with DMARD-free sustained remission.Methods645 Dutch RA-patients were studied on DMARD-free sustained remission during a maximal follow-up duration of 10-years. Variants associated with radiographic progression under an additive model in the total RA-population (Human Leukocyte Antigens (HLA)-DRB1-shared epitope (SE), Dickkopf-1 (DKK1)-rs1896368, DKK1-rs1896367, DKK1-rs1528873, C5Orf30-rs26232, Interleukin-2 receptor-α (IL2RA)-rs2104286, Matrix metalloproteinase-9 (MMP-9)-rs11908352, rs451066 and Osteoprotegerin (OPG)-rs1485305) were studied. Cox-regression analyses were performed and Bonferroni correction applied. Soluble IL2Rα (sIL2Rα)-levels were studied. For replication, 622 RA-patients included in the French Evaluation et Suivi de POlyarthrites Indifférenciées Récentes cohort (ESPOIR)-cohort were investigated. Results were combined in inverse-variance weighted meta-analysis.ResultsSimilar as previously reported, the SE-alleles associated with less remission (hazard ratio (HR) = 0.57, 95 % confidence interval (95 % CI) = 0.42-0.77, p = 2.72×10(-4)). Variants in DKK-1, C5orf30, MMP-9 and OPG were not associated with remission. The IL2RA-rs2104286 minor allele associated with a higher chance on remission (HR = 1.52, 95 % CI = 1.16-1.99, p = 2.44×10(-3)). The rs2104286 minor allele associated with lower sIL2Rα-levels (p = 1.44×10(-3)); lower sIL2Rα-levels associated with a higher chance on remission (HR per 100 pg/L = 0.81, 95 % CI = 0.68-0.95, p = 0.012). When including rs2104286 and sIL2Rα-levels in one analysis, the HR for rs2104286 was 2.27 (95 % CI = 1.06-4.84, p = 0.034) and for sIL2Rα 0.83 (95 % CI = 0.70-0.98, p = 0.026). Within ESPOIR, the HR of rs2104286 was 1.31 (95 % CI = 0.90-1.90). The meta-analysis revealed a p-value of 1.01×10(-3).ConclusionIL2RA-rs2104286 and sIL2Rα-level associated with RA-persistence. IL2RA variants are known to protect against multiple sclerosis, diabetes mellitus and RA. Besides HLA-SE, IL2RA-rs2104286 is thus far the only known genetic variant associated with both joint destruction and RA-persistence. This underlines the relevance of IL2RA for RA.

Project description:BackgroundThe pathogenesis of rheumatoid arthritis (RA) is an immune imbalance, in which various inflammatory immune cells and pro-inflammatory factors are involved. Interleukin-17 (IL-17), a potent pro-inflammatory cytokine, has been found to have increased expression in the joints of patients with RA compared to healthy individuals. However, the causal relationship between the expression level of IL-17 or IL-17 receptor (IL-17R) and RA remained unknown. In this study, two-sample Mendelian randomization (MR) was used to investigate the causal relationship between IL-17 and RA.MethodsSummary statistics for RA (14,361 RA cases and 43,923 healthy controls) and IL-17 (3,301 samples) were obtained from an available meta-analysis of published genome-wide association studies (GWAS). Relevant single nucleotide polymorphisms (SNPs) were selected by executing quality control steps from the GWAS summary results. Then we used bi-directional two-sample Mendelian randomization (MR) and multi-variable MR (MVMR) analysis to examine evidence of causality. MR and MVMR analyses progressed mainly using inverse variance weighted (IVW), weighted median (WM), and MR-Egger regression methods, which were applied to the genetic instrumental variables (IVs) of IL-17A/IL-17 RA, IL-17C/IL-17 RC, and IL-17D/IL-17RD and RA. For assessing the robustness of the results, we also carried out a sensitivity analysis to assess heterogeneity and pleiotropy, such as MR-Egger, leave-one-out, and MR pleiotropy residual sum and outlier (MR-PRESSO).ResultsTwo-sample MR Analysis showed the causal relationship between IL-17A/IL-17RA and RA. The presence of genetically high IL-17A/IL-17RA may increase the risk of RA (IL-17A(OR = 1.095; 95% C.I., 0.990-1.210, p.adj = 0.013), IL-17RA(OR = 1.113, 95%CI = 1.006-1.231, p.adj = 0.006)). However, the results indicated that IL-17C/IL-17RC, and IL-17D/IL-17RD demonstrated no causal impact on RA (IL-17C(OR = 1.007, 95%CI = 0.890-1.139, p.adj = 0.152), IL-17RC(OR = 1.006, 95%CI = 0.904-1.119, p.adj = 0.152), IL-17D(OR = 0.979, 95%CI = 0.843-1.137, p.adj = 0.130), IL-17RD(OR = 0.983, 95%CI = 0.876-1.104, p.adj = 0.129)). Furthermore, MVMR analysis shown that IL-17RA(OR = 1.049, 95% CI: 0.997-1.102, p.adj = 0.014) was associated with increased risk of RA. Sensitivity analysis showed no heterogeneity and pleiotropy, suggesting that the above results were robust and reliable.ConclusionThe MR analysis provides evidence that IL-17A/IL-17RA are risk factors for RA. This emphasizes the importance of intervention on IL-17A/IL-17RA in patients with RA. Developing drugs that limit IL-17A may reduce the risk of RA.

Project description:BackgroundRheumatoid arthritis (RA) shares genetic variants with other autoimmune conditions, but existing studies test the association between RA variants with a pre-defined set of phenotypes. The objective of this study was to perform a large-scale, systemic screen to determine phenotypes that share genetic architecture with RA to inform our understanding of shared pathways.MethodsIn the UK Biobank (UKB), we constructed RA genetic risk scores (GRS) incorporating human leukocyte antigen (HLA) and non-HLA risk alleles. Phenotypes were defined using groupings of International Classification of Diseases (ICD) codes. Patients with an RA code were excluded to mitigate the possibility of associations being driven by the diagnosis or management of RA. We performed a phenome-wide association study, testing the association between the RA GRS with phenotypes using multivariate generalized estimating equations that adjusted for age, sex, and first five principal components. Statistical significance was defined using Bonferroni correction. Results were replicated in an independent cohort and replicated phenotypes were validated using medical record review of patients.FindingsWe studied n = 316,166 subjects from UKB without evidence of RA and screened for association between the RA GRS and n = 1317 phenotypes. In the UKB, 20 phenotypes were significantly associated with the RA GRS, of which 13 (65%) were immune mediated conditions including polymyalgia rheumatica, granulomatosis with polyangiitis (GPA), type 1 diabetes, and multiple sclerosis. We further identified a novel association in Celiac disease where the HLA and non-HLA alleles had strong associations in opposite directions. Strikingly, we observed that the non-HLA GRS was exclusively associated with greater risk of the validated conditions, suggesting shared underlying pathways outside the HLA region.InterpretationThis study replicated and identified novel autoimmune phenotypes verified by medical record review that share immune pathways with RA and may inform opportunities for shared treatment targets, as well as risk assessment for conditions with a paucity of genomic data, such as GPA.FundingThis research was funded by the US National Institutes of Health (P30AR072577, R21AR078339, R35GM142879, T32AR007530) and the Harold and DuVal Bowen Fund.

Project description:Background Rheumatoid arthritis (RA) and Parkinson's disease (PD) are two common chronic diseases worldwide, and any potential link between the two would significantly impact public health practice. Considering the current inconsistent evidence, we conducted a meta-analysis and systematic review to examine the risk of PD in patients with RA. Methods Two investigators (DL and XH) conducted a comprehensive search of PubMed, Embase, and Web of Science using medical subject headings terms combined with free words to identify relevant papers published from inception through December 31, 2021. All studies that explored the relationship between RA and PD were included for quantitative analysis and qualitative review. Random- and fixed-effects models were used to pool the risk ratios (RRs) of PD in patients with RA. The Newcastle-Ottawa scale was used to assess the quality of included studies. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guideline. Results Four population-based studies involving 353,246 patients and one Mendelian randomized study were included in our study. The pooled result showed a significantly reduced risk of PD in patients with RA than in the general population (RR = 0.74, 95% CI: 0.56-0.98, P = 0.034). No apparent effects of gender, age, region, follow-up time, or study design on PD risk were observed. Sensitivity analysis showed that pooled results were relatively stable, and no publication bias was detected. The Mendelian randomization study indicated a significant inverse association between RA and PD (genetic correlation: −0.10, P = 0.0033) and that each one standard deviation increase in the risk of RA was significantly associated with a lower risk of PD. Of note, the current study is limited by the relatively small number of included studies and unmeasured confounding factors, especially for RA-related anti-inflammatory agents. Conclusions This study supports that people with RA had a lower PD risk than those without RA. Further studies are needed to explore the underlying molecular mechanisms of the interaction between the two diseases.

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Genetic analysis of the relation between IL2RA/IL2RB and rheumatoid arthritis risk.

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Genetic analysis of the relation between IL2RA/IL2RB and rheumatoid arthritis risk.

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