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Open AccessJournal ArticleDOI

Integrated Proteomics Reveals Brain-Based Cerebrospinal Fluid Biomarkers in Asymptomatic and Symptomatic Alzheimer’s Disease

TLDR
Results are a promising step toward a network-based biomarker tool for AD clinical applications and identify cerebrospinal fluid biomarkers representing a wide spectrum of AD pathophysiology.
Abstract
Alzheimer's disease (AD) lacks protein biomarkers reflective of its diverse underlying pathophysiology, hindering diagnostic and therapeutic advancements. Here, we used integrative proteomics to identify cerebrospinal fluid (CSF) biomarkers representing a wide spectrum of AD pathophysiology. Multiplex mass spectrometry identified ~3500 and ~12,000 proteins in AD CSF and brain, respectively. Network analysis of the brain proteome resolved 44 biologically diverse modules, 15 of which overlapped with the CSF proteome. CSF AD markers in these overlapping modules were collapsed into five protein panels representing distinct pathophysiological processes. Synaptic and metabolic panels were decreased in AD brain but increased in CSF, while glial-enriched myelination and immunity panels were increased in brain and CSF. The consistency and disease specificity of panel changes were confirmed in >500 additional CSF samples. These panels also identified biological subpopulations within asymptomatic AD. Overall, these results are a promising step toward a network-based biomarker tool for AD clinical applications.

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Posttranslational Modifications Mediate the Structural Diversity of Tauopathy Strains.

TL;DR: Cryo-electron microscopy is used to determine the structures of tau filaments from corticobasal degeneration (CBD) human brain tissue and proposes a structure-based model in which cross-talk between PTMs influences tau filament structure, contributing to the structural diversity of tauopathy strains.
Journal ArticleDOI

Artificial intelligence for proteomics and biomarker discovery

TL;DR: In this paper, the authors focus on mass spectrometry (MS)-based proteomics and describe how machine learning and, in particular, deep learning now predicts experimental peptide measurements from amino acid sequences alone.
Journal ArticleDOI

Global quantitative analysis of the human brain proteome and phosphoproteome in Alzheimer's disease.

TL;DR: An unbiased multiplex quantitative proteomic and phosphoproteomic analysis using tandem mass tag isobaric labeling of human post-mortem cortex across pathology-free controls, AsymAD and symptomatic AD individuals is reported.
Journal ArticleDOI

Systems-based proteomics to resolve the biology of Alzheimer’s disease beyond amyloid and tau

TL;DR: How network-based proteomics has emerged as a powerful tool and how its application to the AD brain has provided an informative framework for the complex protein pathophysiology underlying the disease is described.
References
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Journal ArticleDOI

WGCNA: an R package for weighted correlation network analysis.

TL;DR: The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis that includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software.
Journal ArticleDOI

Neuropathological stageing of Alzheimer-related changes.

Heiko Braak, +1 more
TL;DR: The investigation showed that recognition of the six stages required qualitative evaluation of only a few key preparations, permitting the differentiation of six stages.
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The Consortium to Establish a Registry for Alzheimer's Disease (CERAD): Part II. Standardization of the neuropathologic assessment of Alzheimer's disease

TL;DR: The Neuropathology Task Force of the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) has developed a practical and standardized neuropathology protocol for the postmortem assessment of dementia and control subjects, which provides neuropathologic definitions of such terms as “definite Alzheimer's disease” (AD), “probable AD,” “possible AD” and “normal brain” to indicate levels of diagnostic certainty.
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