Plasma Metabolic and Proteomic Signatures of Mixed Exposure to Ambient Air Pollutants Associated with Incident Arthritis Subtypes

Objectives: The associations between ambient air pollution mixtures, related metabolic and proteomic signatures, and arthritis subtypes, including rheumatoid arthritis (RA), osteoarthritis (OA), gout, and psoriatic arthritis (PsA), remain unclear.
Methods: This prospective cohort study included 401,676 UK Biobank participants free of arthritis at baseline. Air pollution mixture exposure was quantified using Weighted Quantile Sum (WQS) regression. Metabolic and proteomic signatures were derived using multivariable linear and elastic net regression. Associations with incident arthritis were evaluated using Cox proportional hazards models and generalized propensity score approaches. Causal mediation analysis was performed to assess mediating effects.
Results: Over a median follow-up of 13 years, 78,188 any type of arthritis cases were identified. The primary contributors to the WQS mixture index were NOx and NO₂ for RA, PM2.5 for OA, NOx and PM2.5 for gout, and PM2.5 and PM10 for PsA. Higher WQS index scores and their associated metabolic and proteomic signatures were associated with increased risks of arthritis subtypes. These signatures mediated the associations between air pollution mixtures and arthritis risk, with mediation proportions ranging from 4.92% to 35.05%. Top 10 mediating metabolites and proteins showed partial overlap, alongside disease-specific profiles across arthritis subtypes.
Conclusion: Air pollution mixtures were associated with increased risks of arthritis subtypes, potentially through both shared and disease-specific metabolic and proteomic pathways, highlighting the importance of considering pollutant mixtures and disease heterogeneity in arthritis research and prevention.