Abstract
BACKGROUND: Ischemic stroke functional outcomes are critical determinants of recovery quality; however, our understanding of the underlying metabolic influences remains incomplete. Mendelian randomization (MR) is ideal for inferring causal links between metabolites and ischemic stroke outcomes by using genetic variants to reduce confounding and reverse causality. This study explored the causal relationships between genetically determined metabolites and functional recovery after stroke. METHODS: In this study, we employed a two-sample MR framework to investigate the influence of plasma metabolites on ischemic stroke functional outcomes. We analyzed outcome data derived from a comprehensive genome-wide association study (GWAS) that included 6,165 stroke patients. The baseline group data were adjusted for ancestry, age, sex, and ischemic stroke severity using the National Institutes of Health Stroke Scale (NIHSS). The primary outcome was 3-month dependence or death defined as a modified Rankin Scale (mRS) of 3-6. The exposures consisted of a comprehensive set of 1,400 metabolites and instrumental variables (IVs) that exhibited strong genetic associations with minimal indications of pleiotropic effects were selected. IVs are selected based on genomic significance level P<1×10(-6). These IVs were then correlated with the patient data in the adjusted group to conduct MR analyses using the inverse-variance weighted (IVW), MR-Egger regression, weighted-median, weighted-mode, and simple-mode methods. To ensure the reliability of our findings, the MR analysis was repeated in the baseline group to confirm the consistence of the identified causality. Moreover, various sensitivity analyses were conducted, such as tests for horizontal pleiotropy, heterogeneity, and leave-one-out analyses, to further confirm the robustness of our results. RESULTS: Using the IVW method, our study identified 59 metabolites with potentially causal relationships to ischemic stroke functional outcomes. Notably, the positive causal link between X-17146 and ischemic stroke functional outcomes, which had an odds ratio (OR) of 0.48 [95% confidence interval (CI): 0.35-0.68, P<0.001], remained significant even after applying false discovery rate (FDR) corrections (P(FDR)=0.02). And only X-17146 remained significant after FDR. Eight metabolites or ratios demonstrated a causal relationship with post-stroke functional outcomes in both the adjusted and baseline groups. Sensitivity tests showed a lack of heterogeneity and pleiotropy in all positive results of the above main analyses. CONCLUSIONS: Our findings suggest that specific metabolites have a causative impact on the functional recovery process ischemic stroke, and provide a foundation for further research into personalized treatment strategies that address these metabolic pathways. Future studies should aim to validate these results using diverse population samples and experimental models to enhance the clinical applicability of the findings.