Cross-Species Aging Knowledge Integration into Agentic AI Platform Uncovers Conserved Mechanisms

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Abstract

Aging research has been advanced largely through the use of model organisms, where short lifespans and genetic tractability enable the systematic discovery of molecular pathways influencing longevity and age-related decline. However, knowledge about aging remains fragmented across species-specific repositories and domain-focused databases, limiting our ability to identify evolutionarily conserved mechanisms and translate findings to human biology. To address this gap, we developed EvoAge, a unified, multi-species knowledge graph that integrates aging-specific and general biomedical resources into a systems-level framework. EvoAge harmonizes 48 public datasets into a graph comprising 1.04 billion triples across six key species. A human-centric orthology framework reconciles more than 80,000 gene entries, expanding accessible organism-level aging knowledge by up to 1,700-fold compared with existing resources. To operationalize the graph for biological reasoning, we optimized knowledge graph embedding models and deployed a large language model (LLM)-assisted agentic interface that supports natural-language querying, link prediction, and hypothesis testing. In internal benchmarking using recent pre-print aging literature, EvoAge significantly outperformed state-of-the-art LLMs in distinguishing biologically plausible from implausible hypotheses. Importantly, EvoAge recommended a previously unrecognized Alzheimer’s disease (AD) mechanism involving nanoscale redistribution of BACE1 within synaptic compartments. We experimentally validated this EvoAge-supported prediction using patient-derived iPSCs carrying a familial PSEN1 mutation, demonstrating disease-associated remodeling of β-secretase, defined by altered localization, nanoscale clustering, and compartment-specific enrichment. We further confirmed the predicted evolutionary conservation of this BACE1–pathology relationship in additional AD systems, including transgenic mice and postmortem human brain tissue.

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