Abstract
BACKGROUND
Late-onset Alzheimer’s disease (AD) exhibits substantial biological heterogeneity. We developed a framework linking cell-type–specific polygenic risk profiles to precision medicine in AD.
METHODS
Cell-based polygenic risk scores (cbPRSs) derived from single-nucleus RNA-seq co-expression networks were evaluated in Alzheimer’s Disease Neuroimaging Initiative (ADNI) and Framingham Heart Study (FHS) cohorts. Network hubs were prioritized using a graph-based PageRank algorithm and candidate drugs were validated in human-induced pluripotent stem cell (hiPSC)–derived astrocytes.
RESULTS
Cell-based PRS analysis identified two genetic risk axes independent of network cell-type labels: an apolipoprotein E (APOE)–concentrated axis (Ast-M2/Oli-M45) and an APOE-independent axis (Ast-M10/Oli-M50), which predicted accelerated progression to AD (hazard ratio: 1.25–2.02) and correlated with localized temporal lobe atrophy, reduced glucose metabolism, and global amyloid burden. High-risk status specifically upregulated complement C4a protein expression in postmortem brains. PageRank network analysis identified four candidate drugs targeting the APOE-containing astrocyte network. Experimental treatment with estradiol and levetiracetam significantly reduced APOE and complement C4 gene expression in hiPSC-derived astrocytes.
DISCUSSION
By integrating cell-based genetic risk with network-level target prioritization, this framework enables robust patient stratification and experimental target validation.
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This post is Copyright: | October 6, 2026
Neuro-Dementia