Cell-type-specific transcriptomic signatures associated with Alzheimer’s disease in the ROSMAP cohort: a single-nucleus RNA-seq pseudobulk analysis.

Background Alzheimer’s disease (AD) is a complex neurodegenerative disorder involving interactions between neuronal, glial, and vascular processes. While single-cell and single-nucleus RNA sequencing studies have identified cell-type-specific transcriptional alterations in AD, the extent to which these patterns are consistently associated with disease status at the donor level remains incompletely characterized. Methods We performed a secondary analysis of publicly available single-nucleus RNA sequencing (snRNA-seq) data from the ROSMAP cohort, comprising 188,941 nuclei from 111 post-mortem human donors. Cells were aggregated by donor and major brain cell type to generate normalized pseudobulk expression profiles. For each cell type, regularized logistic regression models were used to evaluate whether transcriptomic patterns differed between AD and cognitively normal control donors. Model performance was assessed using donor-stratified cross-validation across multiple random seeds, permutation testing, and exploratory coefficient analysis. Results Non-neuronal cell types showed more consistent transcriptomic differences between AD and control donors than neuronal populations. Astrocyte-derived profiles demonstrated the strongest association with disease status (maximum AUC = 0.646), followed by microglia/immune cells (mean AUC = 0.574 ± 0.088) and vascular cells (mean AUC = 0.540 ± 0.069). Excitatory and inhibitory neurons exhibited limited disease-associated transcriptomic signal. Genes contributing most strongly to these patterns were functionally enriched in pathways related to neuroinflammation, lipid and cholesterol metabolism, oxidative stress response, and blood–brain barrier integrity. Exploratory in silico perturbation analyses suggested greater model sensitivity to coordinated transcriptomic changes in microglial gene sets. Conclusions Cell-type-specific pseudobulk transcriptomic profiles derived from snRNA-seq data exhibit reproducible associations with Alzheimer’s disease status at the donor level, predominantly driven by glial and vascular cell populations. These findings support a multifactorial view of AD pathophysiology and provide a computational framework for prioritizing biological hypotheses for future experimental validation. This study is exploratory and hypothesis-generating in nature and does not support diagnostic, prognostic, or clinical application.