Causal relationship between metabolites and embolic stroke: based on Mendelian randomization and metabolomics

Front Neurol. 2024 Oct 11:15:1460852. doi: 10.3389/fneur.2024.1460852. eCollection 2024.

Abstract

Purpose: This research employed Mendelian randomization (MR) methods to explore whether metabolites are causally associated with embolic stroke of undetermined source (ESUS).

Methods: Genome-Wide Association Study (GWAS) data regarding metabolites and ESUS were downloaded from the database. Metabolites were employed as exposure factors, ESUS served as the outcome variable, and single nucleotide polymorphisms (SNPs) exhibiting significant association with ESUS were chosen as instrumental variables. The causal association between exposure factor metabolites and the outcome variable ESUS was assessed using two methods: MR-Egger regression and inverse variance-weighted (IVW) analysis.

Results: A causal relationship was observed between X-11593--O-methylascorbate* and ESUS, indicating a protective factor. Moreover, a causal relationship was identified between cholesterol esters in large very-low-density lipoprotein (VLDL), cholesterol esters in medium low-density lipoprotein (LDL), concentration of medium LDL particles, phospholipids in medium LDL, phenylalanine, total cholesterol in small LDL, total lipids in medium LDL and ESUS, representing risk factor. Funnel plots exhibited a symmetrical distribution of SNPs, while pleiotropic tests (p > 0.05) and leave-one-out tests indicated that the results were relatively stable.

Conclusion: Metabolites are causally associated with ESUS. LDL and VLDL-related metabolites are identified as risk factors for ESUS.

Keywords: Mendelian randomization; embolic stroke of undetermined source; genome-wide association study; inverse variance-weighted; metabolite.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was supported by Key Project of Nanjing Medical Science and Technology Program, no. ZKX21015.