Background: Histone deacetylase (HDAC) inhibition has emerged as one potential mechanism for modulating disease-associated transcriptional changes in Alzheimer's disease (AD). Previous work from our laboratory demonstrated that the HDAC inhibitor trichostatin A (TSA) reduces amyloid-beta accumulation in iPSC-derived cortical neurons.

Objective: We aimed to determine whether transcriptomic changes associated with TSA treatment could be leveraged to identify candidate genes that are consistently dysregulated across independent Alzheimer's disease datasets.

Methods: Differential expression analysis was performed on a TSA perturbation dataset and four independent AD transcriptomic datasets representing diverse disease models. Genes exhibiting a TSA rescue signature were intersected with AD-associated differential expression to prioritize consistently dysregulated candidate genes. Downstream analyses included Gene Ontology enrichment, literature review, cell-type expression profiling, and therapeutic target prioritization.

Results: Cross-dataset transcriptomic analyses identified GPC4 as the strongest candidate gene, with additional support for MEGF10, PHLDB2, and S1PR1. Candidate genes were enriched for biological pathways relevant to AD, including neuronal connectivity, transcriptional regulation, and extracellular matrix organization.

Conclusions: Intersecting perturbation transcriptomics with independent Alzheimer's disease datasets provides a framework for prioritizing biologically relevant candidate genes for future functional validation.