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Background <p>Genome-wide association studies (GWASs) have identified over 100 loci associated with rheumatoid arthritis (RA) risk. Nonetheless, the contribution of these loci to RA risk remains largely unknown, hampering the development of new therapeutics. As proteins are direct effectors of disease processes, we conducted the first large-scale proteome-wide association study (PWAS) to prioritize RA risk genes based on their effects on plasma protein abundance.</p> Methods <p>We integrated RA GWAS summary statistics (discovery: 22,350 cases and 74,823 controls; replication: 31,313 cases and 995,377 controls) with precomputed protein expression weights generated from the Atherosclerosis Risk in Communities (ARIC) study (<i>N</i> = 7,213) and INTERVAL study (<i>N</i> = 3,301). Causal inference was performed using Mendelian randomization (MR) and colocalization analyses. Druggable target exploration was conducted to identify potential therapeutic targets for RA.</p> Results <p>A total of 35 genetically regulated proteins associated with RA risk, including 10 potentially causal candidates, were identified. Notably, six potentially causal proteins (FCRL3, ICOSLG, MAPK3, WISP1, FAM213A, and IL1RN) were not implicated in the original GWASs. Druggable target exploration identified 160 drug-gene interactions, including a drug, AMG-557, targeting the PWAS protein ICOSLG, which possesses superior anti-inflammatory and anti-rheumatic activity in autoimmune diseases and may therefore be a candidate for RA treatment.</p> Conclusions <p>Our results provide novel insights into RA pathogenesis and suggest promising targets for further mechanistic investigation and drug development.</p>

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Integrating human plasma proteomes with genome-wide association data implicates novel proteins and drug targets for rheumatoid arthritis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月15日

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  • Xin Ke,
  • Shi Yao,
  • Hao Wu,
  • Xi Zheng,
  • Tian-Yue Liu,
  • Feng-Fan Yang,
  • Kui Zhang,
  • Zhao-Hui Zheng,
  • Ping Zhu

摘要

Background

Genome-wide association studies (GWASs) have identified over 100 loci associated with rheumatoid arthritis (RA) risk. Nonetheless, the contribution of these loci to RA risk remains largely unknown, hampering the development of new therapeutics. As proteins are direct effectors of disease processes, we conducted the first large-scale proteome-wide association study (PWAS) to prioritize RA risk genes based on their effects on plasma protein abundance.

Methods

We integrated RA GWAS summary statistics (discovery: 22,350 cases and 74,823 controls; replication: 31,313 cases and 995,377 controls) with precomputed protein expression weights generated from the Atherosclerosis Risk in Communities (ARIC) study (N = 7,213) and INTERVAL study (N = 3,301). Causal inference was performed using Mendelian randomization (MR) and colocalization analyses. Druggable target exploration was conducted to identify potential therapeutic targets for RA.

Results

A total of 35 genetically regulated proteins associated with RA risk, including 10 potentially causal candidates, were identified. Notably, six potentially causal proteins (FCRL3, ICOSLG, MAPK3, WISP1, FAM213A, and IL1RN) were not implicated in the original GWASs. Druggable target exploration identified 160 drug-gene interactions, including a drug, AMG-557, targeting the PWAS protein ICOSLG, which possesses superior anti-inflammatory and anti-rheumatic activity in autoimmune diseases and may therefore be a candidate for RA treatment.

Conclusions

Our results provide novel insights into RA pathogenesis and suggest promising targets for further mechanistic investigation and drug development.