Genetics of rheumatoid arthritis contributes to biology and drug discovery

Abstract

A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological datasets 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 (GWAS) 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 (SNPs). We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 1012–4. We devised an in-silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci (cis-eQTL)6, and pathway analyses7–9 – as well as novel methods based on genetic overlap with human primary immunodeficiency (PID), hematological cancer somatic mutations and knock-out 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.

10 Years of GWAS Discovery: Biology, Function, and Translation

“…For example, Okada et al screened the overlap between genetic associations and known drug targets to demonstrate that existing RA therapies disproportionately target RA-associated gene products and their interacting protein partners. 108 From this, they extrapolated that other agents with high levels of effects on these proteins would be enriched with potential new RA therapies and provided suggestive evidence that CDK4 and CDK6 inhibitors already in use, particularly in oncology, could be effective in RA. These agents have been shown to be effective in the collagen-induced arthritis model of RA and are now in human trials in RA in Japan.…”

Dissection of a complex disease susceptibility region using a Bayesian stochastic search approach to fine mapping

“…Informative approaches to understanding disease etiology have recently been developed based on looking for enrichment of the cell-specific chromatin marks localising to likely causal variants, and these are being used to highlight disease relevant cells [23,50]. Here, again, more accurate identification of causal variants will lead to more powerful and precise comparisons, and our approach, which is associated to a more accurate estimation of posterior probabilities for the SNPs in the considered region, should be readily adaptable to the growing set of methods that aim to examine enrichment [5] or colocalisation [6] by model averaging over the posterior probabilities that a SNP is causal.…”

The low EOMES/TBX21 molecular phenotype in multiple sclerosis reflects CD56+ cell dysregulation and is affected by immunomodulatory therapies

“…Their expression is positively correlated with expression of other transcription factor genes, notably RUNX3 and TOX; and with the chemokine ligand gene CCL5 -suggesting a particular blood immune cell subset(s) with the gene expression signature of these genes is either driving MS susceptibility or represents a disease effect in ETlow individuals. Autoimmune conditions are over-represented in MS families [16], and since EOMES is also associated with at least one other autoimmune condition, rheumatoid arthritis [17], the ETlow phenotype may indicate risk to this and other conditions.…”