Risk of Erythritol-Associated Ischemic Stroke: Integrated Genetic, Transcriptomic, and Machine Learning Evidence

Erythritol is a widely used low-calorie sugar substitute, but its relationship with cerebrovascular risk remains uncertain. We investigated the association between genetically predicted erythritol levels and ischemic stroke and explored stroke-related molecular features using an integrative bioinformatics framework. Two-sample and multivariable Mendelian randomization were performed across cardiovascular-kidney-metabolic outcomes, followed by target prediction, enrichment and protein-protein interaction analyses, transcriptomic profiling, machine-learning feature selection, SHAP interpretation, immune-cell analysis, gene set variation analysis, and exploratory molecular docking. Genetically predicted erythritol showed the strongest association with stroke among the tested sweetener-related traits (OR = 1.246, 95% CI: 1.101-1.410, p < 0.001) and remained significant after adjustment for selected hemodynamic, glycometabolic, and lipid-related traits. Downstream analyses highlighted inflammatory, oxidative-stress, hypoxic, and vascular-injury pathways and prioritized MMP9, TLR4, and HIF1A as a reproducible stroke-related three-gene signature. These downstream bioinformatic findings are exploratory and do not establish erythritol-specific molecular regulation. Overall, the results support an association between genetically predicted erythritol levels and ischemic stroke and identify candidate pathways and genes for further investigation; the MR exposure should not be interpreted as direct evidence that dietary erythritol intake causes stroke.