Regulon Reconstruction Uncovers Novel Deregulated Factors in Alzheimer's Disease.

Belém-Souza MV, Barra-Matos G, de Araújo GS
Molecular neurobiology 2026
Open on PubMed

Alzheimer's disease (AD) is a progressive neurodegenerative age-related disorder characterized by widespread transcriptional deregulation across multiple brain regions. Among the molecular players involved, the transcription factors (TFs) can regulate the expression of AD-related peptides (β-amyloid and tau). We aim to unveil reconstructed TF-centered networks and their dynamics across multiple brain regions. In this study, we conducted an exhaustive differential gene expression analysis, reconstructed TF-TF-centered regulatory networks, and performed master-regulation analyses across multiple regions. We used bulk RNA-seq data from 2,229 post-mortem samples from the ROSMAP, MAYO, and MSBB cohorts. To place these regulatory programs in a disease-relevant context, we integrated protein-protein interaction (PPI) data, experimental TF-target data, and AD-associated genetic risk loci as a translational layer. We assessed TF-centered regulons for 1,605 TFs and identified 354 master-regulators (MR-TFs) across multiple brain regions, including the parahippocampal gyrus, temporal cortex, and cerebellum, which exhibited the highest numbers of regulons. Overall, regulons fell within a moderate size range (median 55 targets), rather than into extensive large networks. Novel MR-TFs, including ADCYAP1, TEAD2, BCL6, MAFF, NFKBIA, were consistently identified as MR-TFs across tissues in AD. Furthermore, GUCY1B1, RBFOX2, and MEF2C were found conserved in the parahippocampal gyrus, inferior frontal gyrus, and posterior cingulate cortex. Additionally, our work identified the well-known AD-related genes BIN1, EGFR, and SPI1 as MR-TFs, reinforcing their functional roles as susceptibility risk markers in AD. This work established an MR-TF-centered integrated regulatory network map of AD, revealing MR-TFs as factors that orchestrate gene deregulation in a region- and cell-context-dependent approach, and providing a robust foundation for mechanistic and translational investigations in neurodegeneration.