Growing evidence suggests that exposure to fine particulate matter (PM_2.5) may reduce life expectancy; however, the causal pathways of PM_2.5 exposure affecting life expectancy remain unknown. Here, we assess the causal effects of genetically predicted PM_2.5 concentration on common chronic diseases and longevity using a Mendelian randomization (MR) statistical framework based on large-scale genome-wide association studies (GWAS) (>400,000 participants). After adjusting for other types of air pollution and smoking, we find significant causal relationships between PM_2.5 concentration and angina pectoris, hypercholesterolaemia and hypothyroidism, but no causal relationship with longevity. Mediation analysis shows that although the association between PM_2.5 concentration and longevity is not significant, PM_2.5 exposure indirectly affects longevity via diastolic blood pressure (DBP), hypertension, angina pectoris, hypercholesterolaemia and Alzheimer’s disease, with a mediated proportion of 31.5, 70.9, 2.5, 100, and 24.7%, respectively. Our findings indicate that public health policies to control air pollution may help improve life expectancy.

越来越多的证据表明，接触细颗粒物 (PM_2.5) 可能会缩短预期寿命；然而，PM_2.5接触影响预期寿命的因果途径仍不清楚。在这里，我们使用基于大数据的孟德尔随机化 (MR) 统计框架来评估基因预测的 PM_2.5 浓度对常见慢性疾病和寿命的因果影响。大规模全基因组关联研究（GWAS）（超过 400,000 名参与者）。在调整其他类型的空气污染和吸烟后，我们发现PM_2.5浓度与心绞痛、高胆固醇血症和甲状腺功能减退症之间存在显着因果关系，但没有因果关系与长寿。中介分析显示，虽然 PM_2.5 浓度与寿命之间的相关性并不显着，但 PM_2.5 暴露通过舒张压 (DBP)、高血压、心绞痛、高胆固醇血症和阿尔茨海默病间接影响寿命，介导比例分别为 31.5%、70.9%、2.5%、100% 和 24.7%。我们的研究结果表明，控制空气污染的公共卫生政策可能有助于提高预期寿命。