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.
Jin Feng, Xue-Na Yang, Shiqiang Cheng et al.· Joint Bone Spine· 0 citations
Air pollution is a recognized contributor to the global burden of disease, but its association with incident substance use disorders (SUD) remains poorly characterized. Whether residential greenness modifies this association is also unclear. We addressed both questions in a large prospective cohort.
We analyzed 247,138 UK Biobank participants without SUD at baseline. Five ambient air pollutants (PM
2.5
, PM
2.5−10
, PM
10
, NO
2
, NO
X
) and three measures of 300-m residential greenness (green space, domestic garden, natural environment) were modelled using Land Use Regression and the 2005–2007 Land Cover Map. Cox proportional hazards models estimated hazard ratios with 95% confidence intervals. Effect modification by greenness was tested using cross-product terms and likelihood-ratio tests. Sensitivity analyses restricted to long-term residents, used alternative outcome definitions (F10-F19 and F11-F19), and recomputed greenness at a 1000-m buffer.
Over a median follow-up of 10.9 years, 4,982 participants developed SUD. All five air pollutants were positively associated with incident SUD in fully adjusted models. PM
2.5
showed the strongest effect (HR = 1.111, 95% CI: 1.081–1.142), followed by PM
10
(HR = 1.070, 95% CI: 1.054–1.086). Green space (HR = 0.997, 95% CI: 0.996–0.998) and natural environment (HR = 0.997, 95% CI: 0.995–0.998) were inversely associated. Domestic garden attenuated the pollutant associations in the high-exposure subgroup, with cross-product terms of 0.979 (95% CI: 0.963–0.996) for PM
2.5
and 0.987 (95% CI: 0.980–0.995) for PM
10
. The positive air-pollution associations were strongest among males, participants aged ≥ 65 years, and individuals with a history of smoking.
Long-term exposure to ambient air pollutants was associated with a higher risk of incident SUD, and residential greenness showed protective associations. These patterns were most pronounced in older males and in individuals with a smoking history. The findings support integrating greenness exposure into environmental frameworks for SUD prevention.
Not applicable.
Huan Liu, B. Cheng, Wen-Ming Wei et al.· BMC Psychiatry· 0 citations
Abstract Background Although adolescent depression has been linked to individual chronic conditions, its broader role in shaping multimorbidity risk remains understudied. Methods A total of 87,562 UK Biobank participants were included, of whom 18,851 had documented adolescent depression. Cox proportional hazards models were applied to evaluate associations between adolescent depression and 24 chronic diseases, followed by stratified analyses by sex and age. Two-sample Mendelian randomization (MR) was then conducted to infer causality for diseases showing significant associations. Genomic colocalization analyses were performed using relevant GWAS data to identify shared causal variants. Mediation analyses were performed to detect possible mediating factors, including the frailty index, KDM biological age acceleration, allostatic load and 30 circulating biomarkers. Results Adolescent depression was associated with elevated risk for 12 chronic diseases, with strongest associations for hypothyroidism (HR = 1.29 [1.18–1.42]), diabetes (HR = 1.25 [1.13–1.38]) and chronic obstructive pulmonary disease (COPD) (HR = 1.74 [1.50–2.01]). Risks were notably higher among females and younger adults. MR confirmed likely causal relationships for hypothyroidism (OR = 1.45 [1.03–2.05]), diabetes (OR = 1.01 [1.01–1.02]) and COPD (OR = 1.04 [1.02–1.06]). Genomic colocalization revealed a shared genetic signal at the CDSN/PSORS1C1 locus between adolescent depression and hypothyroidism. Mediation analyses revealed disease-specific pathways: creatinine for hypothyroidism, testosterone for diabetes, KDM biological ageing for COPD and frailty index across all three conditions. Conclusions Adolescent depression confers systemic vulnerability through genetic and metabolic mechanisms, with amplified risks in females and individuals aged ≤55 years. These findings support early, integrated interventions to mitigate long-term multimorbidity.
Wen-Ming Wei, B. Cheng, X. Qi et al.· Epidemiology and Psychiatric...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
