Causal effects of plasma metabolites on chronic kidney diseases and renal function: a bidirectional Mendelian randomization study.

Despite the potential demonstrated by targeted plasma metabolite modulators in halting the progression of chronic kidney disease (CKD), a lingering uncertainty persists concerning the causal relationship between distinct plasma metabolites and the onset and progression of CKD. A genome-wide association study was conducted on 1,091 metabolites and 309 metabolite ratios derived from a cohort of 8,299 unrelated individuals of European descent. Employing a bidirectional two-sample Mendelian randomization (MR) analysis in conjunction with colocalization analysis, we systematically investigated the associations between these metabolites and three phenotypes: CKD, creatinine-estimated glomerular filtration rate (creatinine-eGFR), and urine albumin creatinine ratio (UACR). In the MR analysis, the primary analytical approach employed was inverse variance weighting (IVW), and sensitivity analysis was executed utilizing the MR-Egger method and MR-pleiotropy residual sum and outlier (MR-PRESSO). Heterogeneity was carefully evaluated through Cochrane's Q test. To ensure the robustness of our MR results, the leave-one-out method was implemented, and the strength of causal relationships was subjected to scrutiny via Bonferroni correction. Our thorough MR analysis involving 1,400 plasma metabolites and three clinical phenotypes yielded a discerning identification of 21 plasma metabolites significantly associated with diverse outcomes. Specifically, in the forward MR analysis, 6 plasma metabolites were determined to be causally associated with CKD, 16 with creatinine-eGFR, and 7 with UACR. Substantiated by robust evidence from colocalization analysis, 6 plasma metabolites shared causal variants with CKD, 16 with creatinine-eGFR, and 7 with UACR. In the reverse analysis, a diminished creatinine-eGFR was linked to elevated levels of nine plasma metabolites. Notably, no discernible associations were observed between other plasma metabolites and CKD, creatinine-eGFR, and UACR. Importantly, our analysis detected no evidence of horizontal pleiotropy. This study elucidates specific plasma metabolites causally associated with CKD and renal functions, providing potential targets for intervention. These findings contribute to an enriched understanding of the genetic underpinnings of CKD and renal functions, paving the way for precision medicine applications and therapeutic strategies aimed at impeding disease progression.

Zhao X ，Gao J ，Kou K ，Wang X ，Gao X ，Wang Y ，Zhou H ，Li F ... -  《Frontiers in Endocrinology》

Causal Effects of Specific Gut Microbiota on Chronic Kidney Diseases and Renal Function-A Two-Sample Mendelian Randomization Study.

Li N ，Wang Y ，Wei P ，Min Y ，Yu M ，Zhou G ，Yuan G ，Sun J ，Dai H ，Zhou E ，He W ，Sheng M ，Gao K ，Zheng M ，Sun W ，Zhou D ，Zhang L ... -  《Nutrients》

Causal effects of systemic inflammatory regulators on chronic kidney diseases and renal function: a bidirectional Mendelian randomization study.

While targeted systemic inflammatory modulators show promise in preventing chronic kidney disease (CKD) progression, the causal link between specific inflammatory factors and CKD remains uncertain. Using a genome-wide association study of 41 serum cytokines from 8,293 Finnish individuals, we conducted a bidirectional two-sample Mendelian randomization (MR) analysis. In addition, we genetically predicted causal associations between inflammatory factors and 5 phenotypes, including CKD, estimated glomerular filtration rate (eGFR), dialysis, rapid progression of CKD, and rapid decline in eGFR. Inverse variance weighting (IVW) served as the primary MR method, while MR-Egger, weighted median, and MR-pleiotropy residual sum and outlier (MR-PRESSO) were utilized for sensitivity analysis. Cochrane's Q test for heterogeneity. Leave-one-out method ensured stability of MR results, and Bonferroni correction assessed causal relationship strength. Seventeen cytokines were associated with diverse renal outcomes. Among them, after Bonferroni correction test, higher tumor necrosis factor alpha levels were associated with a rapid decrease in eGFR (OR = 1.064, 95% CI 1.028 - 1.103, P = 0.001), higher interleukin-4 levels were associated with an increase in eGFR (β = 0.003, 95% CI 0.001 - 0.005, P = 0.002), and higher growth regulated oncogene alpha (GROα) levels were associated with an increased risk of CKD (OR=1.035, 95% CI 1.012 - 1.058, P = 0.003). In contrast, genetic susceptibility to CKD was associated with an increase in GROa, and a decrease in eGFR may lead to an increase in stem cell factor. We did not find the presence of horizontal pleiotropy during the analysis. We discovered causally related inflammatory factors that contribute to the initiation and progression of CKD at the genetic prediction level.

Li H ，Li M ，Liu C ，He P ，Dong A ，Dong S ，Zhang M ... -  《Frontiers in Immunology》

Blood metabolites and chronic kidney disease: a Mendelian randomization study.

Human blood metabolites have demonstrated close associations with chronic kidney disease (CKD) in observational studies. Nonetheless, the causal relationship between metabolites and CKD is still unclear. This study aimed to assess the associations between metabolites and CKD risk. We applied a two-sample Mendelian randomization (MR) analysis to evaluate relationships between 1400 blood metabolites and eight phenotypes (outcomes) (CKD, estimated glomerular filtration rate(eGFR), urine albumin to creatinine ratio, rapid progress to CKD, rapid decline of eGFR, membranous nephropathy, immunoglobulin A nephropathy, and diabetic nephropathy). The inverse variance weighted (IVW), MR-Egger, and weighted median were used to investigate the causal relationship. Sensitivity analyses were performed with Cochran's Q, MR-Egger intercept, MR-PRESSO Global test, and leave-one-out analysis. Bonferroni correction was used to test the strength of the causal relationship. Through the MR analysis of 1400 metabolites and eight clinical phenotypes, a total of 48 metabolites were found to be associated with various outcomes. Among them, N-acetylleucine (OR = 0.923, 95%CI: 0.89-0.957, PIVW = 1.450 × 10-5) has a strong causal relationship with lower risk of CKD after the Bonferroni-corrected test, whereas Glycine to alanine ratio has a strong causal relationship with higher risk of CKD (OR = 1.106, 95%CI: 1.063-1.151, PIVW = 5.850 × 10-7). No horizontal pleiotropy and heterogeneity were detected. Our study offers groundbreaking insights into the integration of metabolomics and genomics to reveal the pathogenesis of and therapeutic strategies for CKD. It underscores 48 metabolites as potential causal candidates, meriting further investigation.

Hou Y ，Xiao Z ，Zhu Y ，Li Y ，Liu Q ，Wang Z ... -  《BMC Medical Genomics》

Causality of Genetically Determined Metabolites on Chronic Kidney Disease: A Two-Sample Mendelian Randomization Study In Silico.

Zhang Z ，Cao B ，Wu Q 《-》