Investigating the causal relationship between genetically determined metabolites and ischemic stroke functional outcomes: a Mendelian randomization study
Year: 2025
Type: article
Study design: Observational Study
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: . 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: =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.
DOI: 10.21037/cdt-24-369
Authors: Xiaobei Zhang, Gehong Liang, Ying Zheng, Xiaokun Wang, Weihao Luo, Guiyue Wang, Yiqing Yin
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W4409353446