目的：关于大气污染物是否与年龄相关性白内障有关联的研究有限，以往的研究结果也不一致。本研究旨在评估多种大气污染物与年龄相关性白内障之间的关系。方法：采用双样本孟德尔随机化（Mendelian Randomization, MR）设计，并使用了来自亚洲及欧洲两个人群的独立全基因组关联研究（Genome-Wide Association Study, GWAS）的汇总统计数据。大气污染物数据包括颗粒物2.5（particulate matter_2.5, PM_2.5）、PM_2.5-10、PM₁₀、二氧化氮和氮氧化物。主要分析方法是逆方差加权（inverse variance weighted, IVW）法，辅以多变量孟德尔随机化分析（multivariable Mendelian randomization, MVMR）校正污染物间混杂效应，并通过敏感性分析验证结果的稳健性。Cochran Q检验法被用来评估各个单核苷酸多态性（single nucleotide polymorphism, SNP）之间是否存在显著的异质性。并采用MR PRESSO方法来识别并排除SNP中的异常值，同时利用MR Egger回归模型评估SNP之间可能存在的多效性，并通过逐一排除每个SNP进行敏感性分析，以确保MR分析结果不受单一SNP的显著影响。结果：关于5种大气污染物特征，亚洲人群结果中，二氧化氮暴露与年龄相关性白内障存在正相关（OR=1.03, 95%CI 1.00~1.06，P=0.026），但在多变量分析中效应方向反转（OR=0.86, 95%CI 0.77~0.97, P=0.013）；在欧洲人群中，PM_2.5-10与年龄相关性白内障显著相关（OR=1.35, 95%CI 1.12~1.62，P=0.002），且在多变量分析中因果效应依然显著（OR=1.58, 95%CI 1.27~3.70, P=0.03）。敏感性分析支持结果的稳健性，未发现异质性或多效性偏倚。结论：环境中PM_2.5-10和二氧化氮与年龄相关性白内障存在复杂因果关系，且因人群而异。亚洲人群中，二氧化氮单变量分析呈正相关，多变量分析效应反转，倾向多变量分析结果，即其降低年龄相关性白内障风险；欧洲人群中，PM_2.5-10单、多变量分析均呈正相关，显示其会增加年龄相关性白内障风险。

Objective: Research exploring the association between atmospheric pollutants and age-related cataracts is scarce, and previous studies have yielded inconsistent findings. This study aims to assess the relationship between various atmospheric pollutants and age-related cataracts. Methods: We adopted a two-sample Mendelian randomization (MR) design, using summary statistics from independent genome-wide association studies (GWAS) conducted on Asian and European populations. The atmospheric pollutant considered in this study included PM_2.5, PM_2.5-10, PM₁₀, nitrogen dioxide, and nitrogen oxides. The primary analysis method was the inverse variance weighted (IVW) approach. Additionally, multivariable MR (MVMR) was used to adjust for confounding effects among pollutants. Sensitivity analyses were conducted to verify the robustness of the results. The Cochran Q test was employed to assess significant heterogeneity among SNPs. The MR PRESSO method was applied to identify and exclude outliers SNPs, while the MR Egger regression model was used to evaluate potential pleiotropy among SNPs. Furthermore, sensitivity analyses were performed by excluding each SNP one by one to ensure that the MR analysis results were not significantly influenced by a single SNP. Results: Among the five atmospheric pollutants studied, we discovered a significant positive correlation between nitrogen dioxide exposure and age-related cataracts in the Asian population (OR=1.03, 95%CI 1.00-1.06, P=0.026). However, the direction of the effect was reversed in the multivariable analysis (OR=0.86, 95%CI 0.77-0.97, P=0.013). In the European population, PM_2.5-10 was significantly associated with age-related cataracts (OR=1.35, 95%CI 1.12-1.62, P=0.002), and the causal effect remained significant in the multivariable analysis (OR=1.58, 95%CI 1.27-3.70, P=0.03). Sensitivity analyses supported the robustness of the results, with no evidence of heterogeneity or pleiotropy bias. Conclusions: This study revealed a complex causal relationship between environmental PM_2.5-10 and NO₂ and age-related cataracts, which varied across populations. In Asian populations, the univariate analysis of nitrogen dioxide showed a positive correlation, but the effect was reversed in multivariate analysis, leaning towards the multivariate results and indicating a reduced risk of age-related cataracts. In European populations, both univariate and multivariate analyses of PM_2.5-10 showed a positive correlation, increasing the risk of age-related cataracts. The study provides genetic evidence for the prevention and control of air pollution and highlights the importance of using multi-pollutant models to assess environmental health effects.