Network Medicine Approach Unravels Endophenotype Signature in Alzheimer’s Disease through Large-Scale Comparative Proteomics Analysis: Vascular Dysfunction as a Prime Example

Alzheimer’s disease (AD) is the most common neurodegenerative
disease burdening public health. We proposed a network-based infrastructure
to identify protein signatures for five AD pathological endophenotypes:
amyloidosis, tauopathy, vascular dysfunction, lysosomal dysfunction,
and neuroinflammation. We analyzed 23 proteomic data sets from AD
patients and transgenic mouse models, using network proximity to measure
associations between endophenotype modules and differentially expressed
proteins (DEPs) in the integrated AD proteome. We focused on the vascular
dysfunction signature with 21 DEPs by integrating RNA-seq, single-cell
transcriptomics, GWAS, and literature. Experiments on APP/PS1 and
MCAO models highlighted three proteins (SEPT5, SNAP25, STXBP1) as
novel AD biomarker candidates. This study demonstrates a network medicine
framework for deciphering endophenotype signatures in AD.