Alzheimer's disease biological domain sub‐stratification enhances the precision of functional analyses

INTRODUCTION: The Target Enablement to Accelerate Therapy Development for AD (TREAT-AD) bioinformatics pipeline employs a rank-and-organize strategy. Disease-associated genes drive enrichment of large AD-linked endophenotypes. However, these biological areas were too large to promote hypothesis development or target identification. Here we delineate subdomains that map to, and enrich, specific biological processes. METHODS: To refine the biodomains into more focused areas, we built κ networks out of the Gene Ontology terms in the biodomain and employ shared gene annotation between terms to determine edge weights. κ-value filtration enabled us to identify data-driven subdomains, which we employed in an analysis of TREAT-AD harmonized datasets. RESULTS: The subdomain enrichment highlights core areas of biological impairment within the biodomain space and facilitates a deeper interpretation of large-scale multiomic datasets. DISCUSSION: The subdomain mapping of AD-risk-associated processes may facilitate an open-source, open-science shareable resource for the comparison of large datasets for the formulation of future hypotheses and identification of therapeutic targets.