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Rheumatoid arthritis (RA) is an inflammatory autoimmune disease involving symmetric joints and is generally characterized by persistent pain, tenderness, and destruction of joints. The vast majority of RA patients produce autoantibodies, and immune cell involvement in disease development is well recognized, as is the contribution of other types of cells in synovial tissue, like fibroblasts. It is known that there are major genetic associations with the HLA locus, while multiple non-HLA genetic variants display relatively low risk of RA. Both HLA and non-HLA associations suggest that the profiles of genetic associations for autoantibody-positive vs. autoantibody-negative RA are different. Several alleles of HLA-DRB1 are associated with high risk for autoantibody-positive RA, with the strongest risk characterized by valine at position 11 of the protein sequence (HLA-DRB1*04 and *10 alleles). There is a strong protective effect for the risk of autoantibody-positive RA associated with HLA-DRB1*13 alleles. Although major genetic associations have been known for several years, understanding of the specific mechanisms in the development of increased risk of RA for these variations is work in progress. Current studies focus on the binding of immune receptors involved in recognition of putative peptides in activation of T cells, as well as investigation of cell signaling mechanisms. At least a part of RA risk could be explained by gene–gene and gene-environment interactions. There are currently more than 150 candidate loci with polymorphisms that associate with RA, mainly related to seropositive disease, and new discoveries are anticipated in the future from investigation of diverse human populations. This new research will help create a strong foundation for the continuing process of integrating genetic, epigenetic, transcriptomic, and proteomic data in studies of RA.

The diversity in our genome is crucial to understanding the demographic history of worldwide populations. However, we have yet to know whether subtle genetic differences within a population can be disentangled, or whether they have an impact on complex traits. Here we apply dimensionality reduction methods (PCA, t -SNE, PCA- t -SNE, UMAP, and PCA-UMAP) to biobank-derived genomic data of a Japanese population ( n  = 169,719). Dimensionality reduction reveals fine-scale population structure, conspicuously differentiating adjacent insular subpopulations. We further enluciate the demographic landscape of these Japanese subpopulations using population genetics analyses. Finally, we perform phenome-wide polygenic risk score (PRS) analyses on 67 complex traits. Differences in PRS between the deconvoluted subpopulations are not always concordant with those in the observed phenotypes, suggesting that the PRS differences might reflect biases from the uncorrected structure, in a trait-dependent manner. This study suggests that such an uncorrected structure can be a potential pitfall in the clinical application of PRS. Population structure, even subtle differences within seemingly homogenous populations, can have an impact on the accuracy of polygenic prediction. Here, Sakaue et al. use dimensionality reduction methods to reveal fine-scale structure in the Biobank Japan cohort and explore the performance of polygenic risk scores.

Liu et al. use mediation analysis to find changes in DNA methylation that mediate the genetic risk for rheumatoid arthritis. Epigenetic mechanisms integrate genetic and environmental causes of disease, but comprehensive genome-wide analyses of epigenetic modifications have not yet demonstrated robust association with common diseases. Using Illumina HumanMethylation450 arrays on 354 anti-citrullinated protein antibody–associated rheumatoid arthritis cases and 337 controls, we identified two clusters within the major histocompatibility complex (MHC) region whose differential methylation potentially mediates genetic risk for rheumatoid arthritis. To reduce confounding factors that have hampered previous epigenome-wide studies, we corrected for cellular heterogeneity by estimating and adjusting for cell-type proportions in our blood-derived DNA samples and used mediation analysis to filter out associations likely to be a consequence of disease. Four CpGs also showed an association between genotype and variance of methylation. The associations for both clusters replicated at least one CpG ( P < 0.01), with the rest showing suggestive association, in monocyte cell fractions in an independent cohort of 12 cases and 12 controls. Thus, DNA methylation is a potential mediator of genetic risk.

Soumya Raychaudhuri, Paul de Bakker and colleagues report fine mapping of the rheumatoid arthritis associations within the MHC by combining genome-wide SNP data and imputation of classical HLA alleles and SNPs across the MHC. They identify five amino acid positions in HLA-DRβ1, HLA-B and HLA-DPβ1 that together can explain most of the MHC association to seropositive rheumatoid arthritis. The genetic association of the major histocompatibility complex (MHC) to rheumatoid arthritis risk has commonly been attributed to alleles in HLA-DRB1 . However, debate persists about the identity of the causal variants in HLA-DRB1 and the presence of independent effects elsewhere in the MHC. Using existing genome-wide SNP data in 5,018 individuals with seropositive rheumatoid arthritis (cases) and 14,974 unaffected controls, we imputed and tested classical alleles and amino acid polymorphisms in HLA-A , HLA-B , HLA-C , HLA-DPA1 , HLA-DPB1 , HLA-DQA1 , HLA-DQB1 and HLA-DRB1 , as well as 3,117 SNPs across the MHC. Conditional and haplotype analyses identified that three amino acid positions (11, 71 and 74) in HLA-DRβ1 and single–amino-acid polymorphisms in HLA-B (at position 9) and HLA-DPβ1 (at position 9), which are all located in peptide-binding grooves, almost completely explain the MHC association to rheumatoid arthritis risk. This study shows how imputation of functional variation from large reference panels can help fine map association signals in the MHC.

Autoimmune thyroid disease is the most common autoimmune disease and is highly heritable 1 . Here, by using a genome-wide association study of 30,234 cases and 725,172 controls from Iceland and the UK Biobank, we find 99 sequence variants at 93 loci, of which 84 variants are previously unreported 2 – 7 . A low-frequency (1.36%) intronic variant in FLT3 (rs76428106-C) has the largest effect on risk of autoimmune thyroid disease (odds ratio (OR) = 1.46, P  = 2.37 × 10 −24 ). rs76428106-C is also associated with systemic lupus erythematosus (OR = 1.90, P  = 6.46 × 10 −4 ), rheumatoid factor and/or anti-CCP-positive rheumatoid arthritis (OR = 1.41, P  = 4.31 × 10 −4 ) and coeliac disease (OR = 1.62, P  = 1.20 × 10 −4 ). FLT3 encodes fms-related tyrosine kinase 3, a receptor that regulates haematopoietic progenitor and dendritic cells. RNA sequencing revealed that rs76428106-C generates a cryptic splice site, which introduces a stop codon in 30% of transcripts that are predicted to encode a truncated protein, which lacks its tyrosine kinase domains. Each copy of rs76428106-C doubles the plasma levels of the FTL3 ligand. Activating somatic mutations in FLT3 are associated with acute myeloid leukaemia 8 with a poor prognosis and rs76428106-C also predisposes individuals to acute myeloid leukaemia (OR = 1.90, P  = 5.40 × 10 −3 ). Thus, a predicted loss-of-function germline mutation in FLT3 causes a reduction in full-length FLT3, with a compensatory increase in the levels of its ligand and an increased disease risk, similar to that of a gain-of-function mutation. A predicted loss-of-function germline mutation in FLT3 causes a reduction in full-length FLT3, with a compensatory increase in the levels of FLT3 ligand, leading to increased risk of autoimmune thyroid disease.

Background Hormonal reproductive factors have been suggested to play an important role in the etiology of rheumatoid arthritis (RA), an autoimmune inflammatory disorder affecting primarily women. We conducted a two-sample Mendelian randomization (MR) study examining three relevant exposures, age at menarche (AAM), age at natural menopause (ANM), and age at first birth (AFB) with the risk of RA. Methods We collected summary statistics from the hitherto largest GWAS conducted in AAM ( N  = 329,345), ANM ( N  = 69,360), AFB ( N  = 251,151), and RA ( N case  = 14,361, N control  = 43,923), all of European ancestry. We constructed strong instruments using hundreds of exposure-associated genetic variants and estimated causal relationship through different MR approaches including an inverse-variance weighted method, an MR-Egger regression and a weighted median method. We conducted a multivariable MR to control for pleiotropic effect acting in particular through obesity and socioeconomic status. We also performed important sensitivity analyses to verify model assumptions. Results We did not find any evidence in support for a causal association between genetically predicted reproductive factors and risk of RA (OR per-SD increment in AAM  = 1.06 [0.98–1.15]; OR per-SD increment in ANM  = 1.05 [0.98–1.11], OR per-SD increment in AFB  = 0.85 [0.65–1.10]). Results remained consistent after removing palindromic SNPs (OR per-SD increment in AAM  = 1.06 [0.97–1.15], OR per-SD increment in ANM  = 1.05 [0.98–1.13], OR per-SD increment in AFB  = 0.81 [0.61–1.07]) or excluding SNPs associated with potential confounding traits (OR per-SD increment in AAM  = 1.03 [0.94–1.12], OR per-SD increment in ANM  = 1.04 [0.95–1.14]). No outlying instrument was identified through the leave-one-out analysis. Conclusions Our MR study does not convincingly support a casual effect of reproductive factors, as reflected by age at menarche, age at menopause, and age at first birth, on the development of RA. Despite the largely augmented set of instruments we used, these instruments only explained a modest proportion of phenotypic variance of exposures. Our knowledge regarding this topic is still insufficient and future studies with larger sample size should be designed to replicate or dispute our findings.

Background Rheumatoid arthritis (RA) can be divided into two major subsets based on the presence or absence of antibodies to citrullinated peptide antigens (ACPA). Until now, data from genome-wide association studies (GWAS) have only been published from ACPA-positive subsets of RA or from studies that have not separated the two subsets. The aim of the current study is to provide and compare GWAS data for both subsets. Methods and results GWAS using the Illumina 300K chip was performed for 774 ACPA-negative patients with RA, 1147 ACPA-positive patients with RA and 1079 controls from the Swedish population-based case–control study EIRA. Imputation was performed which allowed comparisons using 1 723 056 single nucleotide polymorphisms (SNPs). No SNP achieved genome-wide significance (2.9 × 10–8) in the comparison between ACPA-negative RA and controls. A case–case association study was then performed between ACPA-negative and ACPA-positive RA groups. The major difference in this analysis was in the HLA region where 768 HLA SNPs passed the threshold for genome-wide significance whereas additional contrasting SNPs did not reach genome-wide significance. However, one SNP close to the RPS12P4 locus in chromosome 2 reached a p value of 2 × 106 and this locus can thus be considered as a tentative candidate locus for ACPA-negative RA. Conclusions ACPA-positive and ACPA-negative RA display significant risk allele frequency differences which are mainly confined to the HLA region. The data provide further support for distinct genetic aetiologies of RA subsets and emphasise the need to consider them separately in genetic as well as functional studies of this disease.

Background We aimed to investigate the involvement of the classical/lectin complement pathway in anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) by exploring the complement activation fragment C4d in association to AAV activity. Methods Forty patients with active AAV and twenty population-based controls were included. The study included 27 (67.5%) patients with a diagnosis of GPA and 13 (32.5%) with MPA. Twenty-four patients (60%) were anti-proteinase 3 (PR3)-ANCA positive and 16 (40%) anti-myeloperoxidase (MPO)-ANCA positive. Thirty-three (82.5%) patients had kidney involvement. A follow-up sample obtained after induction therapy (median 6 months) was available for 24 of the patients, of whom 20 were in remission. Plasma C4d was analysed by ELISA detecting an epitope that arises upon complement-mediated cleavage. Plasma complement factor 4 (C4) and the soluble terminal complement complex (sTCC) were analysed by ELISA. The C4d/C4 ratio was calculated. HLA-DRB1-typing and immunohistochemistry for C4d in kidney biopsies were performed. Results Patients with active AAV had higher C4d, sTCC levels and C4d/C4 ratio than controls (p < 0.001, p = 0.004, p < 0.001). C4d, sTCC levels and C4d/C4 ratio all decreased from active disease to remission (p = 0.010, p = 0.009, p = 0.011). C4d levels in AAV patients in remission remained higher than population-based controls (p = 0.026). Active anti-PR3-ANCA patients had higher C4d levels and C4d/C4 ratio than anti-MPO-ANCA patients (p = 0.001, p = 0.007). Patients with active AAV and kidney involvement had lower C4d levels than patients without (p = 0.04). C4d levels and C4d/C4 ratio correlated positively with the percentage of normal glomeruli in kidney biopsies. The immunohistochemistry was negative for C4d in kidney biopsies. Conclusions The specific C4d assay revealed activity in the classical/lectin complement pathway in AAV, which reflected general disease activity, but was not associated specifically with kidney involvement. C4d levels differed depending on anti-PR3/MPO-ANCA subtypes suggesting differences in complement activation and underlying pathogenetic mechanisms. The findings imply that the classical/lectin complement pathway may play a more significant role in AAV pathogenesis than previously reported and that plasma C4d levels and C4d/C4 ratio may be biomarker candidates for disease activity and treatment outcome monitoring.

Background Earlier studies have demonstrated that smoking and genetic risk factors interact in providing an increased risk of rheumatoid arthritis (RA). Less is known on how smoking contributes to RA in the context of genetic variability, and what proportion of RA may be caused by smoking. Objectives To determine the association between the amount of smoking and risk of RA in the context of different HLA-DRB1 shared epitope (SE) alleles, and to estimate proportions of RA cases attributed to smoking. Design, Setting and Participants Data from the Swedish Epidemiological Investigation of Rheumatoid Arthritis (EIRA) case–control study encompassing 1204 cases and 871 controls were analysed. Main Outcome Measure Estimated OR to develop RA and excess fraction of cases attributable to smoking according to the amount of smoking and genotype. Results Smoking was estimated to be responsible for 35% of anticitrullinated protein/peptide antibody (ACPA)-positive cases. For each HLA-DRB1 SE genotype, smoking was dose-dependently associated with an increased risk of ACPA-positive RA (p trend <0.001). In individuals carrying two copies of the HLA-DRB1 SE, 55% of ACPA-positive RA was attributable to smoking. Conclusions Smoking is a preventable risk factor for RA. The increased risk due to smoking is dependent on the amount of smoking and genotype.

Objectives To increase understanding of the aetiology and pathogenesis of rheumatoid arthritis (RA), genetic and environmental risk factors for RA subsets, defined by the presence or absence of different anticitrullinated protein/peptide antibodies (ACPAs) targeting citrullinated peptides from α-enolase, vimentin, fibrinogen and collagen type II, were investigated. Methods 1985 patients with RA and 2252 matched controls from the EIRA case-control cohort were used in the study. Serum samples were assayed by ELISA for the presence of anticyclic citrullinated peptides (anti-CCP) antibodies and four different ACPA fine specificities. Cross-reactivity between ACPAs was examined by peptide absorption experiments. Genotyping was performed for HLA-DRB1 shared epitope (SE) alleles and the PTPN22 gene, while information regarding smoking was obtained by questionnaire. The association of genetic and environmental risk factors with different subsets of RA was calculated by logistic regression analysis. Results Limited cross-reactivity was observed between different ACPA fine specificities. In total, 17 RA subsets could be identified based on their different ACPA fine specificity profiles. Large differences in association with genetic and environmental determinants were observed between subsets. The strongest association of HLA-DRB1 SE, PTPN22 and smoking was identified for the RA subset which was defined by the presence of antibodies to citrullinated α-enolase and vimentin. Conclusion This study provides the most comprehensive picture to date of how HLA-DRB1 SE, PTPN22 and smoking are associated with the presence of specific ACPA reactivities rather than anti-CCP levels. The new data will form a basis for molecular studies aimed at understanding disease development in serologically distinct subsets of RA.