Yuan Li-Yun, Su Wang-Ming, Li Liang-Pin, Tian Xiao-Feng, Zheng Xue-Li, Yuan Xiao-Yong
School of Medicine, Nankai University, Tianjin 300071, China.
Tianjin Key Laboratory of Ophthalmology and Visual Science, Tianjin Eye Institute, Tianjin Eye Hospital, Tianjin 300020, China.
Int J Ophthalmol. 2025 Jul 18;18(7):1307-1316. doi: 10.18240/ijo.2025.07.14. eCollection 2025.
To elucidate causal pathways between oxidative biomarkers and age-related macular degeneration (AMD) phenotypes.
A bidirectional Mendelian randomization (MR) analytical protocol was implemented, which utilized genome-wide association study (GWAS) summary statistics derived from the IEU OpenGWAS repositories. The investigation focused on 11 oxidative stress markers and AMD phenotypes, encompassing both wet and dry subtypes. The MR methodology incorporated inverse-variance weighted (IVW) calculations, MR-Egger statistical regression, weighted median approximation, and weighted mode assessments to estimate causative relationships. Sensitivity evaluations were conducted to verify result robustness and identify potential pleiotropy.
Genetically predicted elevated catalase (CAT) concentrations demonstrated significant associations with heightened risks of overall AMD (IVW OR=1.084, 95%CI: 1.021-1.151, =0.008) and wet AMD phenotype (IVW OR=1.113, 95%CI: 1.047-1.247, =0.007). Higher genetically predicted albumin concentrations corresponded with reduced AMD risk (IVW OR=0.827, 95%CI: 0.715-0.957, =0.013) but increased wet AMD risk (IVW OR=1.229, 95%CI: 1.036-1.458, =0.018). Reverse MR analysis revealed that genetically predicted dry AMD exhibited significant association with reduced albumin levels (IVW OR=0.987, 95%CI: 0.979-0.996, =0.004), while wet AMD corresponded with decreased total bilirubin (TBIL) and paraoxonase (PON) activity.
The results offer strong support for a causal link between markers of oxidative stress and the development of AMD, indicating that oxidative processes play a role in driving the disease progression.
阐明氧化生物标志物与年龄相关性黄斑变性(AMD)表型之间的因果途径。
实施了双向孟德尔随机化(MR)分析方案,该方案利用了来自IEU OpenGWAS存储库的全基因组关联研究(GWAS)汇总统计数据。研究重点关注11种氧化应激标志物和AMD表型,包括湿性和干性亚型。MR方法采用逆方差加权(IVW)计算、MR-Egger统计回归、加权中位数近似和加权模式评估来估计因果关系。进行了敏感性评估以验证结果的稳健性并识别潜在的多效性。
基因预测的过氧化氢酶(CAT)浓度升高与总体AMD风险增加显著相关(IVW OR = 1.084,95%CI:1.021 - 1.151,P = 0.008)以及湿性AMD表型风险增加(IVW OR = 1.113,95%CI:1.047 - 1.247,P = 0.007)。基因预测的白蛋白浓度较高与AMD风险降低相关(IVW OR = 0.827,95%CI:0.715 - 0.957,P = 0.013),但湿性AMD风险增加(IVW OR = 1.229,95%CI:1.036 - 1.458,P = 0.018)。反向MR分析显示,基因预测的干性AMD与白蛋白水平降低显著相关(IVW OR = 0.987,95%CI:0.979 - 0.996,P = 0.004),而湿性AMD与总胆红素(TBIL)和对氧磷酶(PON)活性降低相关。
结果为氧化应激标志物与AMD发展之间的因果联系提供了有力支持,表明氧化过程在推动疾病进展中起作用。