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Data-driven analyses are increasingly valued in modern medicine. We integrate quantitative proteomics and transcriptomics from over 1,000 post-mortem brains from six cohorts representing Alzheimer's disease (AD), asymptomatic AD, progressive supranuclear palsy (PSP), and control patients from the Accelerating Medicines Partnership - Alzheimer's Disease consortium. We define robust co-expression trajectories related to disease progression, including early neuronal, microglial, astrocyte, and immune response modules, and later mRNA splicing and mitochondrial modules. The majority of, but not all, modules are conserved at the transcriptomic level, including module C3, which is only observed in proteome networks and enriched in mitogen-activated protein kinase (MAPK) signaling. Genetic risk enriches in modules changing early in disease and indicates that AD and PSP have distinct causal biological drivers at the pathway level, despite aspects of similar pathology, including synaptic loss and glial inflammatory changes. The conserved, high-confidence proteomic changes enriched in genetic risk represent targets for drug discovery.

A surprising complexity of ubiquitin signaling has emerged with identification of different ubiquitin chain topologies. However, mechanisms of how the diverse ubiquitin codes control biological processes remain poorly understood. Here, we use quantitative whole-proteome mass spectrometry to identify yeast proteins that are regulated by lysine 11 (K11)-linked ubiquitin chains. The entire Met4 pathway, which links cell proliferation with sulfur amino acid metabolism, was significantly affected by K11 chains and selected for mechanistic studies. Previously, we demonstrated that a K48-linked ubiquitin chain represses the transcription factor Met4. Here, we show that efficient Met4 activation requires a K11-linked topology. Mechanistically, our results propose that the K48 chain binds to a topology-selective tandem ubiquitin binding region in Met4 and competes with binding of the basal transcription machinery to the same region. The change to K11-enriched chain architecture releases this competition and permits binding of the basal transcription complex to activate transcription.

Objective: To define tauopathy‐associated changes in the human gray and white matter proteome. Method: We applied tandem mass tagged labeling and mass spectrometry, consensus, and ratio weighted gene correlation network analysis (WGCNA) to gray and white matter sampled from postmortem human dorsolateral prefrontal cortex. The sampled tissues included control as well as Alzheimer's disease, corticobasal degeneration, progressive supranuclear palsy, frontotemporal degeneration with tau pathology, and chronic traumatic encephalopathy. Results: Only eight proteins were unique to gray matter while six were unique to white matter. Comparison of the gray and white matter proteome revealed an enrichment of microglial proteins in the white matter. Consensus WGCNA sorted over 6700 protein isoforms into 46 consensus modules across the gray and white matter proteomic networks. Consensus network modules demonstrated unique and shared disease‐associated microglial and endothelial protein changes. Ratio WGCNA sorted over 6500 protein ratios (white:gray) into 33 modules. Modules associated with mitochondrial proteins and processes demonstrated higher white:gray ratios in diseased tissues relative to control, driven by mitochondrial protein downregulation in gray and upregulation in white. Interpretation: The dataset is a valuable resource for understanding proteomic changes in human tauopathy gray and white matter. The identification of unique and shared disease‐associated changes across gray and white matter emphasizes the utility of examining both tissue types. Future studies of microglial, endothelial, and mitochondrial changes in white matter may provide novel insights into tauopathy‐associated changes in human brain. [ABSTRACT FROM AUTHOR]

Psychosocial experiences affect brain health and aging trajectories, but the molecular pathways underlying these associations remain unclear. Normal brain function relies on energy transformation by mitochondria oxidative phosphorylation (OxPhos). Two main lines of evidence position mitochondria both as targets and drivers of psychosocial experiences. On the one hand, chronic stress exposure and mood states may alter multiple aspects of mitochondrial biology; on the other hand, functional variations in mitochondrial OxPhos capacity may alter social behavior, stress reactivity, and mood. But are psychosocial exposures and subjective experiences linked to mitochondrial biology in the human brain? By combining longitudinal antemortem assessments of psychosocial factors with postmortem brain (dorsolateral prefrontal cortex) proteomics in older adults, we find that higher well-being is linked to greater abundance of the mitochondrial OxPhos machinery, whereas higher negative mood is linked to lower OxPhos protein content. Combined, positive and negative psychosocial factors explained 18 to 25% of the variance in the abundance of OxPhos complex I, the primary biochemical entry point that energizes brain mitochondria. Moreover, interrogating mitochondrial psychobiological associations in specific neuronal and nonneuronal brain cells with single-nucleus RNA sequencing (RNA-seq) revealed strong cell-type-specific associations for positive psychosocial experiences and mitochondria in glia but opposite associations in neurons. As a result, these "mind-mitochondria" associations were masked in bulk RNA-seq, highlighting the likely underestimation of true psychobiological effect sizes in bulk brain tissues. Thus, self-reported psychosocial experiences are linked to human brain mitochondrial phenotypes. [ABSTRACT FROM AUTHOR]

Here, we report proteomic analyses of 129 human cortical tissues to define changes associated with the asymptomatic and symptomatic stages of Alzheimer's disease (AD). Network analysis revealed 16 modules of co-expressed proteins, 10 of which correlated with AD phenotypes. A subset of modules overlapped with RNA co-expression networks, including those associated with neurons and astroglial cell types, showing altered expression in AD, even in the asymptomatic stages. Overlap of RNA and protein networks was otherwise modest, with many modules specific to the proteome, including those linked to microtubule function and inflammation. Proteomic modules were validated in an independent cohort, demonstrating some module expression changes unique to AD and several observed in other neurodegenerative diseases. AD genetic risk loci were concentrated in glial-related modules in the proteome and transcriptome, consistent with their causal role in AD. This multi-network analysis reveals protein- and disease-specific pathways involved in the etiology, initiation, and progression of AD.

Alzheimer's disease (AD) is currently defined by the aggregation of amyloid-β (Aβ) and tau proteins in the brain. Although biofluid biomarkers are available to measure Aβ and tau pathology, few markers are available to measure the complex pathophysiology that is associated with these two cardinal neuropathologies. Here, we characterized the proteomic landscape of cerebrospinal fluid (CSF) changes associated with Aβ and tau pathology in 300 individuals using two different proteomic technologies—tandem mass tag mass spectrometry and SomaScan. Integration of both data types allowed for generation of a robust protein coexpression network consisting of 34 modules derived from 5242 protein measurements, including disease-relevant modules associated with autophagy, ubiquitination, endocytosis, and glycolysis. Three modules strongly associated with the apolipoprotein E ε4 (APOE ε4) AD risk genotype mapped to oxidant detoxification, mitogen-associated protein kinase signaling, neddylation, and mitochondrial biology and overlapped with a previously described lipoprotein module in serum. Alterations of all three modules in blood were associated with dementia more than 20 years before diagnosis. Analysis of CSF samples from an AD phase 2 clinical trial of atomoxetine (ATX) demonstrated that abnormal elevations in the glycolysis CSF module—the network module most strongly correlated to cognitive function—were reduced by ATX treatment. Clustering of individuals based on their CSF proteomic profiles revealed heterogeneity of pathological changes not fully reflected by Aβ and tau. Editor's summary: The use of fluid biomarkers to stratify patients and monitor treatment response can facilitate the development of therapeutics for Alzheimer's disease (AD). To extend the AD marker toolkit, Dammer et al. established an integrated cerebrospinal fluid (CSF) proteomic network and showed that interconnected groups of proteins (modules) were associated with distinct disease aspects such as Aβ and tau pathology, cognitive dysfunction, or APOE E4 status. The M20 glycolysis/redox homeostasis module was elevated in AD and correlated with cognitive dysfunction. M20 was reduced after atomoxetine treatment in CSF from patients participating in a clinical trial. Together, these results could provide a useful resource for AD biomarker development. —Daniela Neuhofer [ABSTRACT FROM AUTHOR]

Our understanding of Alzheimer's disease (AD) pathophysiology remains incomplete. Here we used quantitative mass spectrometry and coexpression network analysis to conduct the largest proteomic study thus far on AD. A protein network module linked to sugar metabolism emerged as one of the modules most significantly associated with AD pathology and cognitive impairment. This module was enriched in AD genetic risk factors and in microglia and astrocyte protein markers associated with an anti-inflammatory state, suggesting that the biological functions it represents serve a protective role in AD. Proteins from this module were elevated in cerebrospinal fluid in early stages of the disease. In this study of >2,000 brains and nearly 400 cerebrospinal fluid samples by quantitative proteomics, we identify proteins and biological processes in AD brains that may serve as therapeutic targets and fluid biomarkers for the disease. Large-scale, comprehensive proteomic profiling of Alzheimer's disease brain and cerebrospinal fluid reveals disease-associated protein coexpression modules and highlights the importance of glia and energy metabolism in disease pathogenesis., Author(s): Erik C. B. Johnson [sup.1] [sup.2] , Eric B. Dammer [sup.1] [sup.3] , Duc M. Duong [sup.1] [sup.3] , Lingyan Ping [sup.1] [sup.2] [sup.3] , Maotian Zhou [sup.1] [sup.2] [...]