Assessing the causal relationships between human blood metabolites and the risk of NAFLD: A comprehensive mendelian randomization study

Front Genet. 2023 Mar 28:14:1108086. doi: 10.3389/fgene.2023.1108086. eCollection 2023.

Abstract

Background: Non-alcoholic fatty liver disease (NAFLD) is a liver disease associated with obesity, insulin resistance, type 2 diabetes mellitus (T2DM), and metabolic syndrome. The risk factors for NAFLD have not been identified. Metabolic dysfunction has been found to be an important factor in the pathogenesis and progression of NAFLD. However, the causal impact of blood metabolites on NAFLD is unclear. Methods: We performed a two-sample Mendelian randomization (MR) study. A genome-wide association study (GWAS) with 7824 participants provided data on 486 human blood metabolites. Outcome information was obtained from a large-scale GWAS meta-analysis of NAFLD, which contained 8,434 cases and 770,180 controls of Europeans. The inverse variance weighted (IVW) model was chosen as the primary two-sample MR analysis approach, followed by sensitivity analyses such as the heterogeneity test, horizontal pleiotropy test, and leave-one-out analysis. In addition, we performed replication, meta-analysis, and metabolic pathway analysis. We further conducted colocalization analysis to deeply reflect the causality. Results: After rigorous genetic variant selection, IVW, sensitivity analysis, replication, and meta-analysis, two known metabolites were identified as being associated with the development of NAFLD [biliverdin: OR = 1.45; 95% CI 1.20-1.75; p = 0.0001; myristoleate: OR = 0.57; 95% CI 0.39-0.83; p = 0.0030]. Conclusion: By combining genomics with metabolomics, our findings provide a new perspective on the underlying mechanisms of NAFLD and have important implications for the screening and prevention of NAFLD.

Keywords: biliverdin; blood metabolites; causality; mendelian randomization; non-alcoholic fatty liver disease.

Grants and funding

This work was supported by the National Science and Technology Major Project “13th Five-Year” (2018ZX10725505), the National Natural Science Foundation of China (NSFC Grant No. 82174341) and the New teacher Start-up Fund Project of the Beijing University of Chinese Medicine (2022-JYB-XJSJJ-050).