2025/09/25 by Erming Wang, Kaiwen Yu, Jiqing Cao +31 · 2 citations
Biochemistry, Genetics and Molecular Biology · Medicine · Computer Science · #Bioinformatics and Genomic Networks #Alzheimer's disease research and treatments #Computational Drug Discovery Methods
paper · pdf · doi:10.1016/j.cell.2025.08.038
The molecular mechanisms underlying the pathogenesis of Alzheimer's disease (AD), the most common form of dementia, remain poorly understood. Proteomics offers a crucial approach to elucidating AD pathogenesis, as alterations in protein expression are more directly linked to phenotypic outcomes than changes at the genetic or transcriptomic level. In this study, we develop multiscale proteomic network models for AD by integrating large-scale matched proteomic and genetic data from brain regions vulnerable to the disease. These models reveal detailed protein interaction structures and identify putative key driver proteins (KDPs) involved in AD progression. Notably, the network analysis uncovers an AD-associated subnetwork that captures glia-neuron interactions. AHNAK, a top KDP in this glia-neuron network, is experimentally validated in human induced pluripotent stem cell (iPSC)-based models of AD. This systematic identification of dysregulated protein regulatory networks and KDPs lays down a foundation for developing innovative therapeutic strategies for AD.