Transitional Neuronal States Suggest Divergent Trajectories of Resilience and Neurodegeneration in an Alzheimer’s Disease Mouse Model

Background: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder where early molecular disruptions precede overt pathology and neuronal loss. To identify transcriptional events that bias neurons toward degeneration or resilience, we reanalyzed two single-nucleus RNA-sequencing datasets originally generated to investigate glial responses in an established AD murine model. Methods: Using a neuron-centric analytical framework, excitatory neuronal cells were selected for downstream bioinformatics involving unsupervised clustering, trajectory inference, and functional analyses. Results: This approach revealed neuronal heterogeneity and enabled reconstruction of inferred transcriptional trajectories in a discovery dataset. Three distinct neuronal states along an inferred continuum from stability to degeneration were identified: a homeostatic state, a transitional stress-adaptive state, and an AD-associated state. The transitional state was positioned near a trajectory bifurcation point, indicating divergence toward either partial resilience or an AD-like trajectory. Differential gene expression and pathway analyses revealed RNA-processing dysregulation in the transitional state, suggesting that early alterations in RNA metabolism may play a key role in biasing neurons toward pathological progression. The homeostatic and transitional neuronal states were independently validated, whereas the AD-associated state was not, potentially reflecting differences in brain-region sampling, sequencing strategies, and/or the transient nature of the disease-associated state. Conclusions: This study identified distinct neuronal transcriptional states and inferred trajectories associated with AD-related vulnerability, highlighting RNA-processing dysfunction as a candidate mechanistic contributor of neuronal fate divergence in AD progression. This work provides a foundation for future studies to define cell-type-specific RNA dysregulation in relevant animal models and human postmortem brain tissues to determine whether early RNA-metabolic imbalance and upstream signaling drivers can serve as mechanistic biomarkers or therapeutic intervention points in AD.