AI guided discovery of a murine model of asymptomatic Alzheimer's disease.

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder defined by extracellular deposition of amyloid-β (Aβ) plaques and intracellular accumulation of hyperphosphorylated Tau in neurofibrillary tangles (NFTs). Notably, approximately 20–30% of older individuals harbor substantial amyloid and Tau pathology yet remain cognitively intact, a clinically silent state referred to as asymptomatic Alzheimer’s disease (AsymAD). The biological basis of this cognitive resilience remains poorly understood, in large part due to the absence of mechanistic frameworks and preclinical models that dissociate neuropathology from cognitive decline. Here, we integrate systems-level Boolean network modeling with in vivo validation to define the transcriptomic logic of AsymAD and establish an experimentally tractable murine model of cognitive resilience. Boolean implication networks trained on large-scale human cortical RNA-sequencing datasets identified a robust, invariant AD gene signature that accurately stratified disease states across multiple independent cohorts. Reverse translation of this signature to transgenic mouse models revealed a striking dissociation between molecular pathology and behavioral outcome in Chromogranin A (CgA)–deficient PS19 mice (CgA-KO/PS19). Male CgA-KO/PS19 mice exhibited AD-like transcriptomic and neuropathological features in the prefrontal cortex while retaining intact learning and memory. Female CgA-KO/PS19 mice demonstrated even greater resilience, characterized by suppression of Tau aggregation and preservation of synaptic ultrastructure. Together, these findings establish a validated murine model of AsymAD and identify CgA as a modifiable molecular node linking neuroendocrine signaling, Tauopathy, and cognitive preservation. This integrative computational–experimental framework provides a scalable and generalizable platform for dissecting sex-specific mechanisms of cognitive resilience, identifying early biomarkers of disease trajectory, and enabling mechanism-guided development of preventive therapeutic strategies for AD.