Abstract：
OBJECTIVE: To explore the causal relationship between cystatin C levels and different stages of diabetic retinopathy through Mendelian randomization (MR).
METHODS: The MRC Integrative Epidemiology Unit provided the Genome-wide association studies (GWAS) data related to cystatin C (exposure). GWAS data for outcomes [DR, proliferative diabetic retinopathy (PDR), severe non-proliferative background diabetic retinopathy (SNPBDR)] were sourced from the FinnGen. Adopted Inverse Variance Weighting (IVW), MR-Egger regression MR-PRESSO, Weighted Median, Constrained Maximum Likelihood and Model Averaging (cML-MA), Weighted model, Radial MR, and MR-Lasso to estimate the causal relationship between cystatin C and diabetic retinopathy. We conducted multivariable MR analysis to evaluate the independent causal effects of cystatin C levels on diabetic retinopathy.
RESULTS: Based on the IVW method, we observed a causal relationship between cystatin C and diabetic retinopathy [odds ratio (OR)random effect = 1.137, 95% confidence interval (CI): 1.035-1.250]/PDR (ORrandom effect = 1.123, 95%CI: 1.004-1.255)/SNPBDR (ORfixed effect = 2.002, 95%CI: 1.343-2.986). Consistent findings were obtained through the cML-MA method. Cochran\'s Q test suggested the presence of heterogeneity between the cystatin C level and instrumental variables in relation to diabetic retinopathy and proliferative diabetic retinopathy, respectively. After adjusting for outliers using MR-PRESSO and Radial MR, it was observed that the statistical significance of the association between cystatin C level and diabetic retinopathy persists. Reverse MR analysis indicated that genetically related SNPBDR may influence the cystatin C level. In multivariable MR analysis, there were indications suggesting a causal relationship of cystatin C with the risk of DR/PDR/SNPBDR adjusting for confounders.
CONCLUSIONS: This study utilizes Mendelian randomization analyses to establish a causal relationship between cystatin C and diabetic retinopathy, and reveals the impact of cystatin C on the risk of diabetic retinopathy, thus providing new evidence for clinical intervention of diabetic retinopathy.
METHODS: The MRC Integrative Epidemiology Unit provided the Genome-wide association studies (GWAS) data related to cystatin C (exposure). GWAS data for outcomes [DR, proliferative diabetic retinopathy (PDR), severe non-proliferative background diabetic retinopathy (SNPBDR)] were sourced from the FinnGen. Adopted Inverse Variance Weighting (IVW), MR-Egger regression MR-PRESSO, Weighted Median, Constrained Maximum Likelihood and Model Averaging (cML-MA), Weighted model, Radial MR, and MR-Lasso to estimate the causal relationship between cystatin C and diabetic retinopathy. We conducted multivariable MR analysis to evaluate the independent causal effects of cystatin C levels on diabetic retinopathy.
RESULTS: Based on the IVW method, we observed a causal relationship between cystatin C and diabetic retinopathy [odds ratio (OR)random effect = 1.137, 95% confidence interval (CI): 1.035-1.250]/PDR (ORrandom effect = 1.123, 95%CI: 1.004-1.255)/SNPBDR (ORfixed effect = 2.002, 95%CI: 1.343-2.986). Consistent findings were obtained through the cML-MA method. Cochran\'s Q test suggested the presence of heterogeneity between the cystatin C level and instrumental variables in relation to diabetic retinopathy and proliferative diabetic retinopathy, respectively. After adjusting for outliers using MR-PRESSO and Radial MR, it was observed that the statistical significance of the association between cystatin C level and diabetic retinopathy persists. Reverse MR analysis indicated that genetically related SNPBDR may influence the cystatin C level. In multivariable MR analysis, there were indications suggesting a causal relationship of cystatin C with the risk of DR/PDR/SNPBDR adjusting for confounders.
CONCLUSIONS: This study utilizes Mendelian randomization analyses to establish a causal relationship between cystatin C and diabetic retinopathy, and reveals the impact of cystatin C on the risk of diabetic retinopathy, thus providing new evidence for clinical intervention of diabetic retinopathy.
摘要：
目的：通过孟德尔随机化(MR)探讨胱抑素C水平与糖尿病视网膜病变不同分期的因果关系。
方法：MRC综合流行病学单元提供了与胱抑素C（暴露）相关的全基因组关联研究（GWAS）数据。结果的GWAS数据[DR，增殖性糖尿病视网膜病变（PDR），重度非增殖性背景糖尿病性视网膜病变(SNPBDR)]来源于FinnGen.采用逆方差加权(IVW)，MR-Egger回归MR-PRESSO，加权中位数，约束最大似然和模型平均(CML-MA)，加权模型，径向MR,和MR-Lasso估计胱抑素C与糖尿病视网膜病变之间的因果关系。我们进行了多变量MR分析，以评估胱抑素C水平对糖尿病视网膜病变的独立因果关系。
结果：基于IVW方法，我们观察到胱抑素C与糖尿病视网膜病变之间存在因果关系[比值比(OR)随机效应=1.137,95%置信区间(CI):1.035~1.250]/PDR(OR随机效应=1.123,95CI:1.004~1.255)/SNPBDR(ORfixed效应=2.002,95CI:1.343~2.986).通过cML-MA方法获得一致的发现。Cochran的Q检验表明，胱抑素C水平和工具变量之间存在异质性，与糖尿病性视网膜病变和增殖性糖尿病性视网膜病变有关，分别。使用MR-PRESSO和径向MR调整异常值后，观察到胱抑素C水平与糖尿病性视网膜病变之间的相关性具有统计学意义。反向MR分析表明，遗传相关的SNPBDR可能会影响胱抑素C水平。在多变量MR分析中，有迹象表明,在校正混杂因素后,胱抑素C与DR/PDR/SNPBDR风险存在因果关系.
结论：本研究利用孟德尔随机化分析来建立胱抑素C与糖尿病视网膜病变之间的因果关系。并揭示了胱抑素C对糖尿病视网膜病变风险的影响，从而为糖尿病视网膜病变的临床干预提供新的证据。
方法：MRC综合流行病学单元提供了与胱抑素C（暴露）相关的全基因组关联研究（GWAS）数据。结果的GWAS数据[DR，增殖性糖尿病视网膜病变（PDR），重度非增殖性背景糖尿病性视网膜病变(SNPBDR)]来源于FinnGen.采用逆方差加权(IVW)，MR-Egger回归MR-PRESSO，加权中位数，约束最大似然和模型平均(CML-MA)，加权模型，径向MR,和MR-Lasso估计胱抑素C与糖尿病视网膜病变之间的因果关系。我们进行了多变量MR分析，以评估胱抑素C水平对糖尿病视网膜病变的独立因果关系。
结果：基于IVW方法，我们观察到胱抑素C与糖尿病视网膜病变之间存在因果关系[比值比(OR)随机效应=1.137,95%置信区间(CI):1.035~1.250]/PDR(OR随机效应=1.123,95CI:1.004~1.255)/SNPBDR(ORfixed效应=2.002,95CI:1.343~2.986).通过cML-MA方法获得一致的发现。Cochran的Q检验表明，胱抑素C水平和工具变量之间存在异质性，与糖尿病性视网膜病变和增殖性糖尿病性视网膜病变有关，分别。使用MR-PRESSO和径向MR调整异常值后，观察到胱抑素C水平与糖尿病性视网膜病变之间的相关性具有统计学意义。反向MR分析表明，遗传相关的SNPBDR可能会影响胱抑素C水平。在多变量MR分析中，有迹象表明,在校正混杂因素后,胱抑素C与DR/PDR/SNPBDR风险存在因果关系.
结论：本研究利用孟德尔随机化分析来建立胱抑素C与糖尿病视网膜病变之间的因果关系。并揭示了胱抑素C对糖尿病视网膜病变风险的影响，从而为糖尿病视网膜病变的临床干预提供新的证据。
