The biological processes that are disrupted in the Alzheimer’s disease (AD) brain remain incompletely understood. In this study, we analyzed the proteomes of more than 1,000 brain tissues to reveal new AD-related protein co-expression modules that were highly preserved across cohorts and brain regions. Nearly half of the protein co-expression modules, including modules significantly altered in AD, were not observed in RNA networks from the same cohorts and brain regions, highlighting the proteopathic nature of AD. Two such AD-associated modules unique to the proteomic network included a module related to MAPK signaling and metabolism and a module related to the matrisome. The matrisome module was influenced by the APOE ε4 allele but was not related to the rate of cognitive decline after adjustment for neuropathology. By contrast, the MAPK/metabolism module was strongly associated with the rate of cognitive decline. Disease-associated modules unique to the proteome are sources of promising therapeutic targets and biomarkers for AD.

Alzheimer's disease (AD) is the most common form of dementia, with cerebrospinal fluid (CSF) β-amyloid (Aβ), total Tau, and phosphorylated Tau providing the most sensitive and specific biomarkers for diagnosis. However, these diagnostic biomarkers do not reflect the complex changes in AD brain beyond plaque and tangle pathologies. Here we report a sensitive, quantitative, and scalable targeted proteomics assay of AD biomarkers representing mainly neuronal, glial, vasculature and metabolic pathways. As quality controls (QCs), we pooled CSF from individuals having normal Aβ and Tau levels (AT-), and individuals having low Aβ and high Tau levels (AT+) to determine the coefficient of variation (CV) and fold-change of protein measurements. Additionally, we analyzed 390 CSF samples using selective reaction monitoring-based mass spectrometry (SRM-MS). Following trypsin digestion, 133 controls (cognitively normal and AT-), 127 asymptomatic (cognitively normal and AT+) and 130 symptomatic AD (cognitively impaired and AT+), and 30 pooled CSF samples were analyzed by SRM-MS using a 15-minute targeted liquid chromatography-mass spectrometry method. Isotopically labeled peptide standards were added for relative quantification by reporting the area ratios for each targeted peptide. We reproducibly detected 62 peptides from 51 proteins in all clinical samples with an average CV of approximately 13% across pools. Proteins that could best distinguish AsymAD and AD cases from controls included SMOC1, GDA, 14-3-3 proteins, and proteins involved in glucose metabolism. In contrast, proteins that could best distinguish AD from AsymAD were mainly neuronal/synaptic proteins including VGF, NPTX2, NPTXR, and SCG2. Collectively, this highlights the utility of high-throughput SRM-MS to quantify peptide biomarkers in CSF that can potentially monitor disease progression.