Dataset Information

RAvariome: a genetic risk variants database for rheumatoid arthritis based on assessment of reproducibility between or within human populations.

ABSTRACT: Rheumatoid arthritis (RA) is a common autoimmune inflammatory disease of the joints and is caused by both genetic and environmental factors. In the past six years, genome-wide association studies (GWASs) have identified many risk variants associated with RA. However, not all associations reported from GWASs are reproduced when tested in follow-up studies. To establish a reliable set of RA risk variants, we systematically classified common variants identified in GWASs by the degree of reproducibility among independent studies. We collected comprehensive genetic associations from 90 papers of GWASs and meta-analysis. The genetic variants were assessed according to the statistical significance and reproducibility between or within nine geographical populations. As a result, 82 and 19 single nucleotide polymorphisms (SNPs) were confirmed as intra- and inter-population-reproduced variants, respectively. Interestingly, majority of the intra-population-reproduced variants from European and East Asian populations were not common in two populations, but their nearby genes appeared to be the components of common pathways. Furthermore, a tool to predict the individual's genetic risk of RA was developed to facilitate personalized medicine and preventive health care. For further clinical researches, the list of reliable genetic variants of RA and the genetic risk prediction tool are provided by open access database RAvariome. DATABASE URL: http://hinv.jp/hinv/rav/.

SUBMITTER: Nagai Y

PROVIDER: S-EPMC3807080 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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RAvariome: a genetic risk variants database for rheumatoid arthritis based on assessment of reproducibility between or within human populations.

Nagai Yoko Y Imanishi Tadashi T

Database : the journal of biological databases and curation 20131023

Rheumatoid arthritis (RA) is a common autoimmune inflammatory disease of the joints and is caused by both genetic and environmental factors. In the past six years, genome-wide association studies (GWASs) have identified many risk variants associated with RA. However, not all associations reported from GWASs are reproduced when tested in follow-up studies. To establish a reliable set of RA risk variants, we systematically classified common variants identified in GWASs by the degree of reproducibi ...[more]

PMID: 24158836

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Project description:Background Patients with rheumatoid arthritis (RA) have a 2- to 10-fold increased risk of cardiovascular disease (CVD), but the biological mechanisms and existence of causality underlying such associations remain to be investigated. We aimed to investigate the genetic associations and underlying mechanisms between RA and CVD by leveraging large-scale genomic data and genetic cross-trait analytic approaches. Methods and Results Within UK Biobank data, we examined the genetic correlation, shared genetics, and potential causality between RA (Ncases=6754, Ncontrols=452 384) and cardiovascular diseases (CVD, Ncases=44 238, Ncontrols=414 900) using linkage disequilibrium score regression, cross-trait meta-analysis, and Mendelian randomization. We observed significant genetic correlations of RA with myocardial infarction (rg:0.40 [95% CI, 0.24-0.56), angina (rg:0.42 [95% CI, 0.28-0.56]), coronary heart diseases (rg:0.41 [95% CI, 0.27-0.55]), and CVD (rg:0.43 [95% CI, 0.29-0.57]) after correcting for multiple testing (P<0.05/5). When stratified by frequent use of analgesics, we found increased genetic correlation between RA and CVD among participants without aspirin usage (rg:0.54 [95% CI, 0.30-0.78] for angina; Pvalue=6.69×10-6) and among participants with paracetamol usage (rg:0.75 [95% CI, 0.20-1.29] for myocardial infarction; Pvalue=8.90×10-3), whereas others remained similar. Cross-trait meta-analysis identified 9 independent shared loci between RA and CVD, including PTPN22 at chr1p13.2, BCL2L11 at chr2q13, and CCR3 at chr3p21.31 (Psingle trait<1×10-3 and Pmeta<5×10-8), highlighting potential shared pathogenesis including accelerating atherosclerosis, upregulating oxidative stress, and vascular permeability. Finally, Mendelian randomization estimates showed limited evidence of causality between RA and CVD. Conclusions Our results supported shared genetic pathogenesis rather than causality in explaining the observed association between RA and CVD. The identified shared genetic factors provided insights into potential novel therapeutic target for RA-CVD comorbidities.

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.

Dataset Information

RAvariome: a genetic risk variants database for rheumatoid arthritis based on assessment of reproducibility between or within human populations.

Publications

RAvariome: a genetic risk variants database for rheumatoid arthritis based on assessment of reproducibility between or within human populations.

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