Causal inference of metabolites in autoimmune liver diseases: A Mendelian randomization analysis

Autoimmune liver disease (AILD) is a chronic and insidious liver disease that can lead to cirrhosis. Metabolites have been shown to play an essential role in autoimmune diseases, but the causality between metabolites and AILD has not been completely investigated. This Mendelian randomization (MR) analysis was conducted to evaluate the causal relationship of metabolites on AILD. A genome-wide association study was conducted using 1400 metabolites as the exposure, and 3 AILD phenotypes primarily from European sources were identified as the results. Inverse-variance weighted method was implemented to obtain the primary causal estimates. Inverse-variance weighted, MR-Egger, weighted median and MR-PRESSO methods were employed for sensitivity analysis. In addition, metabolic pathway analysis was conducted with the utilization of MetaboAnalyst 6.0. All of the statistical analysis was carried out using the R software. In our 2-sample MR analysis, 262 metabolites that may be causally related to the pathogenesis of AILD were identifie. Metabolites strongly associated with the development of AILD, such as plasma free proline, spermidine to N-acetylputrescine ratio and hexadecanedioate (C16-DC) were identified by sensitivity analysis. Metabolic pathway analysis detected 31 prominent metabolic pathways in AILD. Our study provides new evidence for the association between 1400 metabolites and 3 types of AILD. It is worthy of exploration whether metabolites with causality can serve as biomarkers to distinguish patients at high risk of AILD.