Integrative Metabolomic Evidence of Bioactive Food-Derived Compounds Targeting Alzheimer’s Disease: A Cross-Study Analysis in Caenorhabditis elegans

Alzheimer’s disease (AD) is a major neurodegenerative condition with limited treatment options. Applications of food-derived products rich in bioactive compounds have emerged as promising strategies, yet comparative evidence across different matrices remains scarce. Here, we present an integrative metabolomic analysis of eleven food extracts previously tested in Caenorhabditis elegans models of AD. By combining chemical fingerprints and functional bioassay data—including oxidative stress resistance, β-amyloid-induced paralysis, and tau-associated locomotion—we employed multivariate statistics to uncover common patterns and correlations. Principal Component Analysis, PLS-DA, and hierarchical clustering revealed distinct groupings of extracts based on metabolite profiles and neuroprotective effects. Polyphenols, flavonoids, and iridoids were consistently associated with beneficial outcomes, while antioxidant capacity and acetylcholinesterase inhibition emerged as key functional traits. Correlation heatmaps highlighted extract-specific strengths, suggesting potential for rational combinations targeting complementary bioactivities. This work underscores the value of integrating metabolomics and functional biology to inform the design of food-based interventions for neurodegenerative diseases, paving the way for evidence-based innovation in brain health.