A Genetic Atlas of Rheumatoid Arthritis Integrating Immune Traits and Plasma Proteins Identifies Genetically Supported Candidate Effectors along the Coagulation-Inflammation Axis.

INTRODUCTION

The upstream immunological drivers of rheumatoid arthritis (RA) and their downstream proteomic effectors remain incompletely resolved. We implemented an integrated, two-layer Mendelian randomization (MR) atlas to systematically map genetically supported causal influences across immune traits and plasma proteins, nominating candidates relevant to RA pathogenesis.

METHODS

In layer 1, we evaluated the causal relevance of 731 immune-cell phenotypes to RA using two-sample MR with stringent instrument filters and multiple-testing correction. In layer 2, we integrated cis-pQTLs of 4,907 plasma proteins with RA through MR and Bayesian colocalization, followed by replication in the UK Biobank, reverse MR, and transcriptomic validation in three independent RA datasets. Drug-target mapping was followed by in silico docking as a pipeline proof-of-concept rather than functional validation.

RESULTS

Layer-1 implicated myeloid antigen-presenting were risk-enhancing, whereas adenosinergic (CD39-axis) and RAGE-axis traits showed protective directionality. Layer-2 convergently prioritized thrombin/prothrombin (F2), indicating a coagulation-inflammation coupling as a causal RA driver, coherent with known thrombo-inflammatory amplification and excess cardiovascular risk in RA. Transcriptomic validation demonstrated consistent, directionally concordant upregulation of BRD2 and MICB across all three independent RA cohorts. As a benchmark of the computational pipeline, bortezomib (BTZ) to F2 suggested structural compatibility without implying druggability (binding energy: -5.53 kcal·mol-1).

CONCLUSIONS

Genetic evidence supports an immune→coagulation causal axis in RA, nominating thrombin/F2 as a translational node and motivating a dual therapeutic rationale: suppressing procoagulant inflammation while enhancing genetically protective pathways (e.g., CD39+ and sRAGE). These findings provide a genetically anchored prioritization framework and motivate subsequent experimental and trial-proximal validation.