Integrated bioinformatics approach reveals potential key genetic biomarkers and therapeutic targets in Alzheimer’s disease

Objective Alzheimer’s disease is a complex neurodegenerative disorder that necessitates integrative approaches to elucidate the mechanisms underlying disease-associated transcriptional dysregulation. The study aimed to explore disease-associated gene expression patterns, identify putative regulatory mechanisms, and contextualize these findings within known biological pathways relevant to Alzheimer’s disease. Methods We performed a comprehensive reanalysis of publicly available single-nucleus RNA sequencing data from the human cortex to explore disease-related gene expression patterns in Alzheimer’s disease within a cell-type–resolved framework. Results This approach revealed modest yet consistent transcriptional differences between Alzheimer’s disease and control samples, without evidence of widespread differential expression. Exploratory analyses highlighted genes and pathways associated with neuronal signaling, immune-related processes, and cellular stress responses, providing insight into disease-associated molecular trends. Network-based analyses further contextualized these findings within protein–protein interaction and regulatory frameworks. Given the limited number of biological samples, all results are interpreted as exploratory and hypothesis-generating rather than diagnostic in nature. Conclusion This integrative single-nucleus transcriptomic analysis provides a rigorously corrected and biologically informed perspective on transcriptional alterations in Alzheimer’s disease, offering a foundation for future validation studies and mechanistic investigations.