Aug 2026· Ecotoxicology and Environmental Safety· Vol 323, pp.
120666
· 0 citations· 34 references
Medicine
Abstract
Background
Air pollution is a major environmental risk factor for Atrial Fibrillation (AF). We aimed to derive robust, pollutant-specific proteomic signatures to elucidate the biological mechanisms and evaluate their potential risk-stratification utility.
Methods
We analyzed plasma levels of approximately 2900 proteins in relation to long-term exposure to seven major air pollutants (PM2.5, PM10, NO2, NOx, SO2, benzene, and O3) within the UK Biobank cohort. A rigorous two-step strategy was employed: (1) proteome-wide screening with Bonferroni correction to identify high-confidence candidates, followed by (2) elastic net regularization to construct pollutant-specific proteomic signatures. Associations with incident AF were assessed using Cox proportional hazards models over a median follow-up of 13.53 years. High-throughput mediation analysis and comprehensive sensitivity analyses were performed to verify robustness.
Results
We derived distinct proteomic signatures for all seven pollutants, which demonstrated superior predictive value for incident AF compared to traditional external exposure metrics. Mediation analysis identified specific pathogenic axes, highlighting ANGPT2, GDF15, and PLAUR as candidate molecular transducers linking pollution to AF risk. Survival analysis further revealed that individuals with high proteomic risk (top 50%) experienced an estimated loss of 1.15-1.25 years of AF-free life compared to low-risk peers. This risk stratification remained significant even after adjusting for ambient pollution concentrations.
Conclusions
We identified robust pollutant-specific proteomic signatures that effectively bridge the gap between environmental stress and clinical arrhythmia. These signatures offer candidate pathway-level markers for refining AF risk stratification and shifting public health strategies from reactive management toward precision prevention.
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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 par...
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OBJECTIVE
As global smoking rates decline, Lung Cancer in Never-Smokers (LCINS) has emerged as a distinct and increasingly important clinical entity. However, its underlying pathogenesis remains poorly understood, highlighting the need to identify circulating molecular determinants and candidate biomarkers.
METHODS
G...
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