An Li, Ren Xiaomei, Pan Ye, Gao Wei, Ren Liqun, Wang Jing, Wang Yao
Department of Geriatrics, ZhongDa Hospital, Southeast University School of Medicine, Nanjing, 210009, People's Republic of China.
Department of Endocrine, ZhongDa Hospital, Southeast University School of Medicine, Nanjing, 210009, People's Republic of China.
Diabetes Metab Syndr Obes. 2024 Feb 22;17:851-856. doi: 10.2147/DMSO.S452227. eCollection 2024.
The impact of inflammatory factors on the risk of diabetic nephropathy (DN) is inconsistent. Two-sample Mendelian randomization (MR) analyses were used to detect the causal role of inflammatory factors in DN risk.
Inflammatory factor GWAS summary data were collected from a meta-analysis including 8,293 Finnish participants, and DN information was extracted from a GWAS of 213,746 individuals from FinnGen. The MR Pleiotropy Residual Sum and Outlier (MR-PRESSO) outlier test was used for the removal of horizontal pleiotropic outliers. Multivariable MR analysis was also used to adjust for pleiotropy.
IFN-γ [OR: 1.33; 95% CI: 1.09-1.63; =0.005] and SCF [OR: 1.25, 1.02-1.52; = 0.027] were associated with an increased risk of DN. MIP1b [OR: 0.92; 95% CI: 0.85-0.98; = 0.022] and IL-16 [OR: 0.89, 0.81-0.99; = 0.043] showed negative associations with the risk of DN. We validated our MR results with MR-PRESSO analyses. Significant horizontal pleiotropy was not found. Moreover, in the multivariable MR analysis, the associations between cytokines and DN risk remained.
Our MR results based on genetic data contribute to a better understanding of the pathogenesis of DN and provide evidence for a causal effect of inflammatory factors on DN. These findings support targeting specific inflammatory factors to alleviate DN risk.
炎症因子对糖尿病肾病(DN)风险的影响并不一致。采用两样本孟德尔随机化(MR)分析来检测炎症因子在DN风险中的因果作用。
从一项纳入8293名芬兰参与者的荟萃分析中收集炎症因子全基因组关联研究(GWAS)汇总数据,并从FinnGen的213746名个体的GWAS中提取DN信息。使用MR多效性残差和异常值(MR-PRESSO)异常值检验来去除水平多效性异常值。还采用多变量MR分析来调整多效性。
干扰素-γ[比值比(OR):1.33;95%置信区间(CI):1.09-1.63;P=0.005]和干细胞因子(SCF)[OR:1.25,1.02-1.52;P=0.027]与DN风险增加相关。巨噬细胞炎性蛋白1β(MIP1b)[OR:0.92;95%CI:0.85-0.98;P=0.022]和白细胞介素-16(IL-16)[OR:0.89,0.81-0.99;P=0.043]与DN风险呈负相关。我们通过MR-PRESSO分析验证了我们的MR结果。未发现显著的水平多效性。此外,在多变量MR分析中,细胞因子与DN风险之间的关联仍然存在。
我们基于遗传数据的MR结果有助于更好地理解DN的发病机制,并为炎症因子对DN的因果效应提供证据。这些发现支持针对特定炎症因子以降低DN风险。