Liu Yuqing, Ling Lilu, Shen Yue, Bi Xiao
Department of Nephrology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
Division of Nephrology, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.
Front Nutr. 2024 Apr 24;11:1371995. doi: 10.3389/fnut.2024.1371995. eCollection 2024.
Chronic kidney disease (CKD) is a common public health problem, which is characterized as impairment of renal function. The associations between blood metabolites and renal function remained unclear. This study aimed to assess the causal effect of various circulation metabolites on renal function based on metabolomics.
We performed a two-sample Mendelian randomization (MR) analysis to estimate the causality of genetically determined metabolites on renal function. A genome-wide association study (GWAS) of 486 metabolites was used as the exposure, while summary-level data for creatinine-based estimated glomerular filtration rate (eGFR) or CKD occurrence were set the outcomes. Inverse variance weighted (IVW) was used for primary causality analysis and other methods including weight median, MR-egger, and MR-PRESSO were applied as complementary analysis. Cochran Q test, MR-Egger intercept test, MR-PRESSO global test and leave-one-out analysis were used for sensitivity analysis. For the identified metabolites, reverse MR analysis, linkage disequilibrium score (LDSC) regression and multivariable MR (MVMR) analysis were performed for further evaluation. The causality of the identified metabolites on renal function was further validated using GWAS data for cystatin-C-based eGFR. All statistical analyses were performed in R software.
In this MR analysis, a total of 44 suggestive associations corresponding to 34 known metabolites were observed. After complementary analysis and sensitivity analysis, robust causative associations between two metabolites (betaine and N-acetylornithine) and renal function were identified. Reverse MR analysis showed no causal effects of renal function on betaine and N-acetylornithine. MVMR analysis revealed that genetically predicted betaine and N-acetylornithine could directly influence independently of each other. The causal effects of betaine and N-acetylornithine were also found on cystatin-C-based eGFR.
Our study provided evidence to support the causal effects of betaine and N-acetylornithine on renal function. These findings required further investigations to conduct mechanism exploration and drug target selection of these identified metabolites.
慢性肾脏病（CKD）是一个常见的公共卫生问题，其特征为肾功能受损。血液代谢物与肾功能之间的关联仍不明确。本研究旨在基于代谢组学评估各种循环代谢物对肾功能的因果效应。
我们进行了两样本孟德尔随机化（MR）分析，以估计基因决定的代谢物对肾功能的因果关系。一项对486种代谢物的全基因组关联研究（GWAS）用作暴露因素，而基于肌酐的估计肾小球滤过率（eGFR）或CKD发生情况的汇总数据则设定为结局。采用逆方差加权（IVW）进行主要因果分析，并应用包括加权中位数、MR-egger和MR-PRESSO在内的其他方法作为补充分析。使用Cochran Q检验、MR-Egger截距检验、MR-PRESSO全局检验和留一法分析进行敏感性分析。对于鉴定出的代谢物，进行反向MR分析、连锁不平衡评分（LDSC）回归和多变量MR（MVMR）分析以作进一步评估。使用基于胱抑素C的eGFR的GWAS数据进一步验证鉴定出的代谢物对肾功能的因果关系。所有统计分析均在R软件中进行。
在本次MR分析中，共观察到44个与34种已知代谢物对应的提示性关联。经过补充分析和敏感性分析后，确定了两种代谢物（甜菜碱和N-乙酰鸟氨酸）与肾功能之间存在稳健的因果关联。反向MR分析表明肾功能对甜菜碱和N-乙酰鸟氨酸无因果效应。MVMR分析显示，基因预测的甜菜碱和N-乙酰鸟氨酸可相互独立地直接影响。还发现甜菜碱和N-乙酰鸟氨酸对基于胱抑素C的eGFR有因果效应。
我们的研究提供了证据支持甜菜碱和N-乙酰鸟氨酸对肾功能的因果效应。这些发现需要进一步研究以对这些鉴定出的代谢物进行机制探索和药物靶点选择。
