Fig. 1: Unbiased network-based proteomics to characterize the complex biochemical and cellular endophenotypes of Alzheimer’s disease (AD).
From: Systems-based proteomics to resolve the biology of Alzheimer’s disease beyond amyloid and tau
Traditional “bottom-up” mass spectrometry (MS)-based techniques, such as label-free quantitation (LFQ) or isobaric labeling, are used for protein identification and quantification in a large cohort of postmortem brain tissues from control, asymptomatic AD (AsymAD), and AD cases. Following fractionation, the deep discovery proteomic data generated from these large cohorts are organized into biologically meaningful groups, or modules, of proteins with sophisticated analytical methods, such as weighted gene correlation network analysis (WGCNA). The co-expression modules are assessed for enrichment with specific cell types, organelles, biological pathways, and genetic risk factors generated from genome-wide association studies (GWAS). In addition, abundance changes at the module level can be correlated with disease status, clinical features, and neuropathological measures. Using this framework, six core and highly conserved modules across AsymAD and AD cohorts with reproducible links to specific cell types, organelles, and biological functions have been identified. Three of the modules are consistently increased in the AD brain network proteome: inflammatory, myelination, and RNA binding/splicing, while the remaining three are consistently decreased: synaptic, mitochondrial, and cytoskeleton.
