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ObjectivesNearly 110 susceptibility loci for rheumatoid arthritis (RA) with modest effect sizes have been identified by population-based genetic association studies, suggesting a large number of undiscovered variants behind a highly polygenic genetic architecture of RA. Here, we performed the largest-ever trans-ancestral meta-analysis with the aim to identify new RA loci and to better understand RA biology underlying genetic associations.MethodsGenome-wide RA association summary statistics in three large case–control collections consisting of 311 292 individuals of Korean, Japanese and European populations were used in an inverse-variance-weighted fixed-effects meta-analysis. Several computational analyses using public omics resources were conducted to prioritise causal variants and genes, RA variant-implicating features (tissues, pathways and transcription factors) and potentially repurposable drugs for RA treatment.ResultsWe identified 11 new RA susceptibility loci that explained 6.9% and 1.8% of the single-nucleotide polymorphism-based heritability in East Asians and Europeans, respectively, and confirmed 71 known non-human leukocyte antigens (HLA) susceptibility loci, identifying 90 independent association signals. The RA variants were preferentially located in binding sites of various transcription factors and in cell type-specific transcription–activation histone marks that simultaneously highlighted the importance of CD4+ T-cell activation and the potential role of non-immune organs in RA pathogenesis. A total of 615 plausible effector genes, based on gene-based associations, expression-associated variants and chromatin interaction, included targets of drugs approved for RA treatments and potentially repurposable drugs approved for other indications.ConclusionOur findings provide useful insights regarding RA genetic aetiology and variant-driven RA pathogenesis.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease of complex etiology that primarily affects women of childbearing age. The development of SLE is attributed to the breach of immunological tolerance and the interaction between SLE-susceptibility genes and various environmental factors, resulting in the production of pathogenic autoantibodies. Working in concert with the innate and adaptive arms of the immune system, lupus-related autoantibodies mediate immune-complex deposition in various tissues and organs, leading to acute and chronic inflammation and consequent end-organ damage. Over the past two decades or so, the impact of genetic susceptibility on the development of SLE has been well demonstrated in a number of large-scale genetic association studies which have uncovered a large fraction of genetic heritability of SLE by recognizing about a hundred SLE-susceptibility loci. Integration of genetic variant data with various omics data such as transcriptomic and epigenomic data potentially provides a unique opportunity to further understand the roles of SLE risk variants in regulating the molecular phenotypes by various disease-relevant cell types and in shaping the immune systems with high inter-individual variances in disease susceptibility. In this review, the catalogue of SLE susceptibility loci will be updated, and biological signatures implicated by the SLE-risk variants will be critically discussed. It is optimistically hoped that identification of SLE risk variants will enable the prognostic and therapeutic biomarker armamentarium of SLE to be strengthened, a major leap towards precision medicine in the management of the condition.

The lung is recognized as a site for initiating the formation of self-antigen and autoimmune responses in rheumatoid arthritis (RA). We aimed to investigate the association of upper respiratory microbiota with RA, autoantibody production, and disease activity. Forty-six patients with RA and 17 controls were examined. Nasopharyngeal swab samples were sequenced for microbiome profiling using the V3–V4 region of the 16S rRNA gene. The microbial diversity and relative abundance were compared between RA patients and controls. Correlation analyses were conducted to evaluate the relationship between microbial abundance and clinical markers such as autoantibodies and disease activity. Microbial diversity analysis revealed no major differences between RA patients and healthy controls. However, beta diversity analysis indicated a subtle distinction in microbial composition (unweighted UniFrac distance) between the two groups ( P = 0.03), hinting at a minor subset of microbiota associated with disease status. Differential abundance analysis uncovered specific taxa at various taxonomic levels, including Saccharibacteria (TM7) [O-1] ( P FDR = 2.53 × 10 −2 ), TM7 [F-1] ( P FDR = 5.20 × 10 −3 ), Microbacterium ( P FDR = 3.37 × 10 −4 ), and Stenotrophomonas ( P FDR = 2.57 × 10 −3 ). The relative abundance of ten genera correlated significantly with anti-cyclic citrullinated peptide (anti-CCP) antibody levels ( P FDR < 0.05) and 11 genera were significantly associated with disease activity markers, including ESR, CRP, DAS28-ESR, and DAS-CRP ( P FDR < 0.05). In particular, Saccharibacteria TM7 [G-3] and Peptostreptococcaceae [XI] [G-1] were correlated with all disease activity biomarkers. Dysbiosis in the upper respiratory mucosa is associated with RA, anti-CCP antibody levels, and disease activity.

Genetic association of the major histocompatibility complex (MHC) locus is well established in systemic lupus erythematosus (SLE), but the causal functional variants in this region have not yet been discovered. Here we conduct the first fine-mapping study, which thoroughly investigates the SLE–MHC associations down to the amino acid level of major HLA genes in 5,342 unrelated Korean case–control subjects, taking advantages of HLA imputation with a newly constructed Asian HLA reference panel. The most significant association is mapped to amino acid position 13 of HLA-DRβ1 ( P= 2.48 × 10 −17 ) and its proxy position 11 ( P= 4.15 × 10 −17 ), followed by position 26 in a stepwise conditional analysis ( P= 2.42 × 10 −9 ). Haplotypes defined by amino acid positions 11–13–26 support the reported effects of most classical HLA-DRB1 alleles in Asian and European populations. In conclusion, our study identifies the three amino acid positions at the epitope-binding groove of HLA-DRβ1 that are responsible for most of the association between SLE and MHC. Systemic lupus erythematosus (SLE) is an autoimmune disease with a complex genetic basis. Here the authors carry out a fine-mapping analysis of the major histocompatibility complex region and identify amino acids that have a causal role in SLE aetiology.

Background The association of HLA-B*27 with AS is amongst the strongest of any known association of a common variant with any human disease. Nonetheless, there is strong evidence indicating that other HLA-B alleles are involved in the disease. European ethnicity studies have demonstrated risk associations with HLA-B*40 and multiple other HLA-B, HLA-A, and HLA class II alleles, and demonstrated that in that ethnic group, the amino acid sequence at position 97 in HLA-B is the key determinant of HLA associations with AS. A recent study in Korean AS cases and controls additionally identified association at HLA-C*15:02. In the current study, we examined the MHC associations of AS in an expanded East Asian cohort. Methods A total of 1637 Chinese, Taiwanese, and Korean AS cases meeting the modified New York Criteria for AS, and 1589 ethnically matched controls, were genotyped with the Illumina Immunochip, including a dense coverage of the MHC region. HLA genotypes and amino acid composition were imputed using the SNP2HLA programme using the Han-MHC reference panel based on the data of Han Chinese subjects ( n  = 9689), and association tested using logistic regression controlling for population stratification effects. Results A strong association was seen with HLA-B*27 (odds ratio (OR) = 205.3, P  = 5.76 × 10 −244 ). Controlling for this association, the strongest risk association is seen with HLA-C*15 at genome-wide significant level (OR = 7.62, P  = 9.30 × 10 −19 ), and confirmed association is also seen with HLA-B*40 at suggestive level (OR = 1.65, P  = 2.54 × 10 −4 ). At amino acid level, the strongest association seen in uncontrolled analysis was with histidine at position 114 in HLA-B ( P  = 7.24 × 10 −241 ), but conditional analyses suggest that the primary amino acid associations are with lysine at position 70 and asparagine at position 97. Restriction of the ERAP1 association with HLA-B27-positive AS, previously reported in European subjects, was confirmed in East Asians. Conclusions This study confirms in East Asians that the HLA associations of AS are multiple, including previously reported associations at HLA-B*27 , HLA-B*40 , and HLA-C*15 , as well as novel association with HLA-DQB1*04 . The HLA-B associations are driven by the amino acids at positions 70 and 97, in the B pocket of HLA-B.

ObjectiveGenome-wide association studies (GWAS) in rheumatoid arthritis (RA) have discovered over 100 RA loci, explaining patient-relevant RA pathogenesis but showing a large fraction of missing heritability. As a continuous effort, we conducted GWAS in a large Korean RA case–control population.MethodsWe newly generated genome-wide variant data in two independent Korean cohorts comprising 4068 RA cases and 36 487 controls, followed by a whole-genome imputation and a meta-analysis of the disease association results in the two cohorts. By integrating publicly available omics data with the GWAS results, a series of bioinformatic analyses were conducted to prioritise the RA-risk genes in RA loci and to dissect biological mechanisms underlying disease associations.ResultsWe identified six new RA-risk loci (SLAMF6, CXCL13, SWAP70, NFKBIA, ZFP36L1 and LINC00158) with pmeta<5×10−8 and consistent disease effect sizes in the two cohorts. A total of 122 genes were prioritised from the 6 novel and 13 replicated RA loci based on physical distance, regulatory variants and chromatin interaction. Bioinformatics analyses highlighted potentially RA-relevant tissues (including immune tissues, lung and small intestine) with tissue-specific expression of RA-associated genes and suggested the immune-related gene sets (such as CD40 pathway, IL-21-mediated pathway and citrullination) and the risk-allele sharing with other diseases.ConclusionThis study identified six new RA-associated loci that contributed to better understanding of the genetic aetiology and biology in RA.

Strong genetic associations in the region containing human leukocyte antigen (HLA) genes have been well-documented in various human immune disorders. Imputation methods to infer HLA variants from single nucleotide polymorphism (SNP) genotypes are currently used to understand HLA associations with a trait of interest. However, it is challenging for some researchers to obtain individual-level SNP genotype data or reference haplotype data. In this study, we developed and evaluated a new method, DISH ( d irect i mputing s ummary association statistics of H LA variants), for imputing summary association statistics of HLA variants from SNP summary association statistics based on linkage disequilibria in Asian and European populations. Disease association Z scores in DISH were highly correlated with those from imputed HLA genotypes in null model datasets (r = 0.934 in Asians; r = 0.960 in Europeans). We applied DISH to two previous GWAS datasets in Asian systemic lupus erythematosus and European rheumatoid arthritis populations. There was a high correlation between Z scores in the DISH and HLA genotype imputations, showing the same disease-susceptible and protective alleles. This study illustrated the usefulness of the DISH method in understanding and identifying disease-associated HLA variants in human diseases while maintaining individual-level data security.

[...]a recent paper by Diaz-Gallo et al 1 reported significant additive interactions between the HLA-DRB1 shared-epitope allele and numerous non-HLA rheumatoid arthritis (RA) risk variants (eg, PTPN22 variants) in anti-citrullinated protein antibody–positive (ACPA-positive) RA.SP110.1136/annrheumdis-2018-214297.supp1 Supplementary data This study investigated the validity of the additive interaction model in assessing gene–gene interactions. [...]cohort datasets were simulated 1000 times with three disease-risk factors that follow the null model of Rothman’s additive interaction, given the population size (n=100 000), the disease prevalence (≈0.01) and the dominant-model relative risk (RR≈5, 2 or 1.5) of each risk variant with a fixed carrier frequency (≈0.4, 0.2 or 0.1, respectively) (online supplementary text). The results showed that the null model required negative correlation between the risk factors in the patient group (eg, average correlation coefficient=–0.25 between two variants with RR≈5 and 2; figure 2), in which two risk genetic variants actually have no or little correlation in the human genome when they are far apart or in different chromosomes.

Objectives To identify novel genetic candidates for systemic lupus erythematosus (SLE) in the Korean population, and to validate the risk loci for SLE identified in previous genome-wide association studies (GWAS). Methods We performed a GWAS in 400 Korean female SLE patients and 445 controls. Selected single-nucleotide polymorphisms (SNP) were then replicated in an independent cohort of 385 SLE patients and 583 controls (replication cohort 1), and in a further 811 SLE patients and 1502 controls (replication cohort 2). Results In the GWAS phase, rs9275428 located near HLA-DQB1 showed the strongest association with SLE (OR 0.50, false discovery rate (FDR) p=3.07×10−6). Although no loci reached genome-wide significance outside major histocompatibility complex (MHC), C8orf13-BLK, STAT4, CSMD1, DIAPH3, GLDC and TNFSF4 showed FDR p < 0.05. Our results suggest that STAT4, BLK, IRF5, PTTG1-miR-146a, UBE2L3 and TNFAIP3 are shared susceptibility loci among Caucasians and Asians, while ETS1, IKZF1, SLC15A4 are likely to be Asian-specific loci. In a combined analysis of 1596 SLE patients and 2540 controls for selected 22 candidate SNP, STAT4 and BLK as positive controls showed a strong association with SLE (FDR p=9.85×10−13 and 2.28×10−8, respectively). Of these, 16 candidates (PEX5L, TRAJ50, MYO18B, SOS1, ARHGAP26, SMURF1, CADPS, HAND1, FAM78B, DIAPH3, TBL1XR1, CSMD1, ZBTB20, C3orf21, HIPK1 and AP001042.1) showed only nominal significance (7.05×10−4≤FDR p≤4.38×10−2). Conclusions There are similarities and differences in genetic susceptibility for SLE between Caucasian and Asian ethnic groups. Although 16 putative novel loci for SLE have been suggested in the Korean population, further research on a larger sample is required to discriminate truth from error.

Key Points The highly polygenic aetiology of rheumatoid arthritis (RA) is well characterized in population genetic studies, with >100 susceptibility loci reported Genetic variants affecting the structure of epitope-binding sites of HLA molecules exhibit the strongest contributions to RA development; log-additive and non-log-additive effects of HLA alleles explain HLA–RA associations The majority of non-HLA associations are mapped at noncoding variants that colocalize with cell-type-specific characteristics (for example, histone markers or enhancers) in CD4 + T cells Pinpointing a single causal gene in a locus that contains multiple genes usually requires additional 'omics' data RA-risk loci generally contain genes related to T-cell and B-cell pathways, cytokine signalling pathways, proliferation and/or impaired haematopoietic and immune systems Many proteins encoded within RA-risk loci, and their interaction partners, are the targets of currently approved therapies, implicating a potential guiding role for human RA genetics data in drug discovery and repurposing Genetic association studies have uncovered more than 100 genetic loci related to susceptibility to rheumatoid arthritis. This Review discusses the latest insights into rheumatoid arthritis pathogenesis gained from genetic studies and their application for drug discovery and development. Human genetic studies into rheumatoid arthritis (RA) have uncovered more than 100 genetic loci associated with susceptibility to RA and have refined the RA-association model for HLA variants. The majority of RA-risk variants are highly shared across multiple ancestral populations and are located in noncoding elements that might have allele-specific regulatory effects in relevant tissues. Emerging multi-omics data, high-density genotype data and bioinformatic approaches are enabling researchers to use RA-risk variants to identify functionally relevant cell types and biological pathways that are involved in impaired immune processes and disease phenotypes. This Review summarizes reported RA-risk loci and the latest insights from human genetic studies into RA pathogenesis, including how genetic data has helped to identify currently available drugs that could be repurposed for patients with RA and the role of genetics in guiding the development of new drugs.