A genome-wide association study meta-analysis of more than 100,000 subjects of European and Asian ancestries reveals 42 new risk loci for rheumatoid arthritis, with follow-up studies identifying 98 biological candidate genes that are either already being targeted by drugs or could be in the future. Virtual screening in a genome-wide association study (GWAS) meta-analysis of more than 100,000 subjects of European and Asian ancestries has revealed 42 previously unknown risk loci for rheumatoid arthritis (RA). As a follow-up, the authors developed a new in silico pipeline to identify 98 biological candidate genes at all known RA risk loci. They show that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ∼10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci6 and pathway analyses7,8,9—as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes—to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.

Jane Worthington and colleagues use a high-density genotyping chip to identify new susceptibility loci for rheumatoid arthritis and examine genetic overlap with other autoimmune diseases. Their results increase the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry and refine the location of many previously identified association signals to single genes. Using the Immunochip custom SNP array, which was designed for dense genotyping of 186 loci identified through genome-wide association studies (GWAS), we analyzed 11,475 individuals with rheumatoid arthritis (cases) of European ancestry and 15,870 controls for 129,464 markers. We combined these data in a meta-analysis with GWAS data from additional independent cases (n = 2,363) and controls (n = 17,872). We identified 14 new susceptibility loci, 9 of which were associated with rheumatoid arthritis overall and five of which were specifically associated with disease that was positive for anticitrullinated peptide antibodies, bringing the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at 6 loci and identified association to low-frequency variants at 4 loci. Bioinformatic analyses generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations.

Introduction: The severity of joint damage progression in rheumatoid arthritis (RA) is heritable. Several genetic variants have been identified, but together explain only part of the total genetic effect. Variants in Interleukin-6 (IL-6), Interleukin-10 (IL-10), C5-TRAF1, and Fc-receptor-like-3 (FCRL3) have been described to associate with radiographic progression, but results of different studies were incongruent. We aimed to clarify associations of these variants with radiographic progression by evaluating six independent cohorts. Methods: In total 5,895 sets of radiographs of 2,493 RA-patients included in six different independent datasets from the Netherlands, Sweden, Spain and North-America were studied in relation to rs1800795 (IL-6), rs1800896 (IL-10), rs2900180 (C5-TRAF1) and rs7528684 (FCRL3). Associations were tested in the total RA-populations and in anti-citrullinated peptide antibodies (ACPA)-positive and ACPA-negative subgroups per cohort, followed by meta-analyses. Furthermore, the associated region C5-TRAF1 was fine-mapped in the ACPA-negative Dutch RA-patients. Results: No associations were found for rs1800795 (IL-6), rs1800896 (IL-10) and rs7528684 (FCRL3) in the total RA-population and after stratification for ACPA. Rs2900180 in C5-TRAF1 was associated with radiographic progression in the ACPA-negative population (P-value meta-analysis = 5.85 × 10⁻⁷); the minor allele was associated with more radiographic progression. Fine-mapping revealed a region of 66Kb that was associated; the lowest P-value was for rs7021880 in TRAF1. The P-value for rs7021880 in meta-analysis was 6.35 × 10⁻⁸. Previous studies indicate that the region of rs7021880 was associated with RNA expression of TRAF1 and C5. Conclusion: Variants in IL-6, IL-10 and FCRL3 were not associated with radiographic progression. Rs2900180 in C5-TRAF1 and linked variants in a 66Kb region were associated with radiographic progression in ACPA-negative RA.

Objectives To describe patients with autoimmune inflammatory rheumatic diseases (AIRD) who had COVID-19 disease; to compare patients who required hospital admission with those who did not and assess risk factors for hospital admission related to COVID-19. Methods An observational longitudinal study was conducted during the pandemic peak of severe acute respiratory syndrome coronavirus 2 (1 March 2020 to 24 April). All patients attended at the rheumatology outpatient clinic of a tertiary hospital in Madrid, Spain with a medical diagnosis of AIRD and with symptomatic COVID-19 were included. The main outcome was hospital admission related to COVID-19. The covariates were sociodemographic, clinical and treatments. We ran a multivariable logistic regression model to assess risk factors for the hospital admission. Results The study population included 123 patients with AIRD and COVID-19. Of these, 54 patients required hospital admission related to COVID-19. The mean age on admission was 69.7 (15.7) years, and the median time from onset of symptoms to hospital admission was 5 (3–10) days. The median length of stay was 9 (6–14) days. A total of 12 patients died (22%) during admission. Compared with outpatients, the factors independently associated with hospital admission were older age (OR: 1.08; p=0.00) and autoimmune systemic condition (vs chronic inflammatory arthritis) (OR: 3.55; p=0.01). No statistically significant findings for exposure to disease-modifying antirheumatic drugs were found in the final model. Conclusion Our results suggest that age and having a systemic autoimmune condition increased the risk of hospital admission, whereas disease-modifying antirheumatic drugs were not associated with hospital admission.