目的：利用双向孟德尔随机化方法(mendelian randomization,MR)探索骨关节炎与青光眼的潜在因果关系。方法：使用全基因组关联研究(genome-wide association studies,GWAS)数据，挑选出与骨关节炎和青光眼高度相关的单核苷酸多态性(single nucleotide polymorphism,SNP)作为工具变量。本研究以逆方差加权法(inverse variance weighted,IVW)作为主要的分析手段，以加权中位数法、加权模型法、简单众数法及MR-Egger回归法作为辅助方法，采用F统计量、Cochran Q检验、MR Egger截距测试、留一法(leave one out)及多效性残差和离群值法(mendelian randomization pleiotropy RESidual sum and outliers,MR-PRESSO)进行敏感性分析。本研究采用比值比(odds ratio,OR)作为主要的效应量度指标，以95%置信区间(confidence interval,CI)评估关联强度，探讨骨关节炎与青光眼的双向因果关系。结果：IVW结果表明骨关节炎可增加青光眼的患病风险(95%CI: 1.00~1.20，OR=1.10，P=0.043)，辅助方法的结果显示了相同的因果方向，但无统计学意义。在反向MR分析中，IVW结果表明，青光眼不会增加患骨关节炎的风险(OR=1.02，95%CI: 0.97~1.08)，4种辅助方法均支持IVW结果。所选SNP的F统计量均超过10，无弱工具变量。Cochran Q检验、MR-Egger截距检验以及MR-PRESSO分析结果均未显示所选SNP之间存在异质性或水平多效性。反向MR分析结果显示Cochran Q检验有异质性，但未发现水平多效性。留一法结果显示没有对整体分析结果产生了显著影响的SNP。结论：正向MR分析表明骨关节炎可能会增加患青光眼的风险，二者之间存在正相关。反向MR分析结果表明，青光眼对骨关节炎无因果效应。

Objective: To investigate the potential bidirectional causal association between osteoarthritis and glaucoma through the application of bidirectional Mendelian randomization (MR). Methods: Instrumental variables were selected in this study based on single nucleotide polymorphisms (SNP) strongly associated with osteoarthritis and glaucoma, as utilizing genome-wide association studies (GWAS) data. The inverse variance weighting (IVW) method was served as the primary analytical approach, while the weighted median mode, simple plurality and MR-Egger regression methods were employed as complementary methods. Sensitivity analyses were conducted using F-statistic, Cochran Q-test, MR Egger's intercept test, leave-one-out, and multiplicity of residuals and outliers method (MR-PRESSO). The ratio of odds ratios (OR) was adopted as the primary effect estimate, and the strength of association was evaluated by 95% confidence interval (CI) to explore the bidirectional causal relationship between osteoarthritis and glaucoma. Results: The IVW analysis revealed that osteoarthritis elevates the risk of glaucoma with an odds ratio of (OR) of 1.10(95% CI: 1.00-1.20). While the adjunctive methods concurred with this causal direction, their findings did not reach statistical significance. In contrast, the inverse Mendelian randomization (MR) analysis utilizing the inverse variance weighting method demonstrated that glaucoma does not enhance the risk of developing osteoarthritis (OR=1.02, 95% CI: 0.97-1.08). This conclusion was upheld by all four auxiliary methods. The F-statistic values for the selected SNP exceeded 10, indicating the absence of weak instrumental variables. Furthermore, the Cochran Q test, MR-Egger intercept test, and MR- PRESSO analyses revealed no evidence of heterogeneity or horizontal pleiotropy among the SNP. However, the inverse MR analysis displayed heterogeneity in the Cochran Q test, yet no horizontal pleiotropy was detected. The leave-one-out method analysis identified no significant influence of any individual SNP on the overall results. Conclusions: Forward MR analyses indicated that osteoarthritis may serve as a risk factor for glaucoma, indicating a positive correlation between the two conditions. Conversely, reverse MR analysis failed to establish a causal link between glaucoma and osteoarthritis.

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.