The global burden and biomarkers of cardiovascular disease attributable to ambient particulate matter pollution

作者：Haoxian Tang, Jingtao Huang, Hanyuan Lin, Xuan Zhang, Qinglong Yang, Nan Luo, Mengyue Lin, Cuihong Tian, Shiwan Wu, Jianan Hong, Jiasheng Wen, Liwen Jiang, Pan Chen, Xiaojing Chen, Junshuang Tang, Youti Zhang, Kaihong Yi, Xuerui Tan, Yequn Chen · 发表于：Journal of Translational Medicine · 年份：2025 · DOI：10.1186/s12967-025-06375-9 · 被引用次数：14 · 研究领域：Air Quality and Health Impacts、Health, Environment, Cognitive Aging、Atmospheric chemistry and aerosols

Understanding the evolving patterns of cardiovascular disease (CVD) burden attributable to ambient particulate matter pollution (APMP) is essential. Furthermore, research on the underlying mechanisms has mostly been limited to laboratory and animal models, with few large-scale population-based studies. Using data from the Global Burden of Disease Study (GBD) 2021, we analyzed disability-adjusted life years and mortality for CVD attributable to APMP (measured as particulate matter [PM] 2.5 ) from 1990 to 2021. We examined shifts in burden between APMP and household air pollution (HAP), regional disparities by socio-demographic index (SDI), and predicted trends using a Bayesian age-period-cohort model. Additionally, we used UK Biobank (UKB) data (metabolomics: 230,000 + participants; proteomics: 50,000 +) to identify biomarkers mediating the association between PM 2.5 exposure and CVD outcomes, and further analyzed their biological roles. Metabolic and proteomic signatures were constructed using regression and elastic net models, with predictive performance assessed via time-dependent receiver operating characteristic analysis. Life expectancy was evaluated using flexible parametric survival models. Subgroup analysis was conducted by age, sex, lifestyle, socioeconomic status, and genetic susceptibility. In 2021, the global CVD absolute burden attributable to APMP was more than double that of 1990, with significant regional disparities. The burden shifted from HAP to APMP, with ...