Mining Alzheimer's Interactomes, Macromolecular Complexes and Pathways for Drug Discovery.

Abstract

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that leads to dementia. Many cases are diagnosed annually and there is no currently available cure. Understanding the underlying disease biology of AD through the study of molecular networks, particularly by mapping clinical variants to tissue-specific interactomes and regulatory macromolecular assemblies, offers a promising avenue to elucidate altered disease pathways. In this study, we applied differential interactome analysis using a manually curated AD dataset to identify how disease-associated mutations alter both transient and stable protein interactions. By focussing on variant-specific associations detected in brain-relevant tissues, we mapped disruptions in stable macromolecular assemblies and performed Reactome enrichment analysis to uncover perturbed pathways unique to each variant. Additionally, we explored therapeutic insights through the analysis of amyloid precursor protein (APP) physical interactors, identifying potential intervention points that influence amyloidogenic processing. Complementing protein-level data, we integrated microRNA (miRNA)-mediated regulatory interactions, revealing an additional layer of posttranscriptional control over key AD genes. Together, this multilayered strategy provides a framework for precision therapeutics in AD.