Genomics-driven drug discovery holds significant promise in identifying and developing novel therapeutic targets. Here, we utilized large-scale genomic data including genome-wide association studies (GWAS), rare variant burden tests in exome sequencing studies (Exome), and protein quantitative trait loci (pQTL), to prioritize therapeutic targets or repurpose drugs in rheumatoid arthritis (RA). We found that prioritized genes covering two approved RA treatment targets (IL6R and CD86), along with several targets currently undergoing active clinical trials for RA. Fifteen proteins were identified as having causalities with RA risk, and three out of them showed strong support for colocalization. BRD2 was nominated as one of the most promising candidates for clinical translation as its wide expression in joint synovial tissues and validation in observational analyses associating with RA incidence. Collectively, our systematic prioritization of drug targets from different genetically informed approaches, and provided a comprehensive insight into therapeutic strategies for RA.

The authors have declared no competing interest.

This study was supported by Research Funds of Joint Research Center for Occupational Medicine and Health of IHM(OMH-2023-01;OMH-2023-08) and Anhui Province clinical medical research transformation project（NO.202304295107020041; NO.202304295107020048）

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

All participants gave their written consent and UK Biobank received ethical approval from the NHS Research Ethics Service (11/NW/0382). Our analysis was conducted under UK Biobank application number 62663.

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The RA GWAS summary statistics and whole exome gene burden tests are publicly available at https://www.ebi.ac.uk/gwas/summary-statistics. Plasma pQTL summary statistics are obtained from deCODE study at https://www.decode.com/summarydata/ . The genetic and phenotypic UK Biobank data are available on application to the UK Biobank to any researcher worldwide (www.ukbiobank.ac.uk). The genomics-driven drug discovery analysis was conducted using the following publicly available tools: MAGMA (https://ctg.cncr.nl/software/magma), DEPICT (https://data.broadinstitute.org/mpg/depict/), PoPS (https://github.com/FinucaneLab/pops), FOCUS (https://github.com/bogdanlab/focus), GREP (https://github.com/saorisakaue/GREP), SMR (https://yanglab.westlake.edu.cn/software/smr/), ezQTL (https://analysistools.cancer.gov/ezqtl ), GeneMANIA (https://genemania.org/), FUMA (https://fuma.ctglab.nl/), PheWAS (https://azphewas.com/) and the Pi and coloc R packages.