Dataset Information

Proteome profiling of cerebrospinal fluid and machine learning reveal biomarkers of two forms of Alzheimer’s disease characterized by increased or not altered levels of tau

ABSTRACT: Alzheimer's disease (AD) is a progressive neurodegenerative disorder that impairs memory, cognition, behavior, and other cognitive functions. Despite significant advances in understanding its molecular mechanisms, a definitive cure remains elusive. However, some treatments have the potential to slow disease progression if applied before brain damage occurs. Therefore, the identification of reliable biomarkers is critical for early diagnosis of AD and effective intervention. Recent advances in proteomics and the increased accuracy of machine learning algorithms have enhanced biomarker discovery and validation. In this study, we used a newly developed proteomic pipeline to analyse cerebrospinal fluid (CSF) to profile the proteome of AD patients, which included two different subgroups based on their CSF levels of tau. Then, machine learning was used to identify proteins that best classified the two subgroups of AD patients compared to non-AD controls. The resulting model, based on few CSF proteins, demonstrated high accuracy in predicting AD and differentiating patients with elevated or normal CSF tau levels. These protein classifiers, detectable in the preclinical stages of AD, were further validated in silico using larger, publicly available proteomic datasets, confirming their potential as early diagnostic tools.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cerebrospinal Fluid

DISEASE(S): Alzheimer's Disease

SUBMITTER: Margot Lo Pinto

LAB HEAD: Simone Dario Scilabra

PROVIDER: PXD063058 | Pride | 2025-08-25

REPOSITORIES: Pride

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Proteome Profiling of Cerebrospinal Fluid and Machine Learning Reveal Protein Classifiers of Two Forms of Alzheimer's Disease Characterized by Increased or Not Altered Levels of Tau.

Scalia Elisabetta E Calligaris Matteo M Lo Pinto Margot M Castelbuono Salvatore S Iemmolo Matilda M Lo Re Vincenzina V Bivona Giulia G Piccoli Tommaso T Ghersi Giulio G Scilabra Simone Dario SD

Molecular & cellular proteomics : MCP 20250630 8

Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder that presents with heterogeneous clinical and pathological features, necessitating improved biomarkers for accurate diagnosis and patient stratification. In this study, we applied a data-independent acquisition-based proteomics workflow to cerebrospinal fluid (CSF) samples from 138 individuals, including AD patients with high (Aβ+/tau+) or normal (Aβ+/tau-) CSF tau levels, and non-AD controls. Analysis using an Astral mass s ...[more]

PMID: 40602528

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Project description:HIGHTLIGHTS-Improved protocol for ISF collection using microdialysis and CSF sampling in mice.-Combined LC‒MS/MS proteomics ISF and CSF analyses for the validation and description of potential new AD biomarkers.-ISF proteomics analysis to track disease progression at the neuronal and glial levels.-Identification of new biomarker candidates for Alzheimer’s disease.ABSTRACTBackground: Mass spectrometry (MS)-based cerebrospinal fluid (CSF) proteomics is an important method for discovering biomarkers of neurodegenerative diseases. CSF serves as a reservoir for interstitial fluid (ISF), and extensive communication between the two fluid compartments helps to remove waste products from the brain.New method: We performed proteomic analyses of both CSF and ISF fluid compartments using intracerebral microdialysis to validate and detect novel biomarkers of Alzheimer's disease (AD) in APPtg and C57Bl/6J control mice.Results: We identified up to 625 proteins in ISF and 4,483 proteins in CSF samples. By comparing the biofluid profiles of APPtg and C57Bl/6J mice, we detected 37 and 108 significantly up- and downregulated candidates, respectively. In ISF, 7 highly regulated proteins, such as Gfap, Aldh1l1, Gstm1, and Txn, have already been implicated in AD progression, whereas in CSF, 9 out of 14 highly regulated proteins, such as Apba2, Syt12, Pgs1 and Vsnl1, have also been validated to be involved in AD pathogenesis. In addition, we also detected new interesting regulated proteins related to the control of synapses and neurotransmission (Kcna2, Cacng3, and Clcn6) whose roles as AD biomarkers should be further investigated.Comparison with existing methods: This newly established combined protocol provides better insight into the mutual communication between ISF and CSF as an analysis of tissue or CSF compartments alone.Conclusions: The use of multiple fluid compartments, ISF and CSF, for the detection of their biological communication enables better detection of new promising AD biomarkers.KEYWORDSAlzheimer’s disease, CSF, ISF, proteomics, biomarkers, microdialysis, mass spectrometry, protein identification, neurodegeneration, brain fluids, expression profilesDATA AVAILABILITYDOI: 10.17605/OSF.IO/VWQ58PUBLICATIONS using this dataset:1)Gorska et al. 2024, Journal of Neuroscience Methodshttps://doi.org/10.1016/j.jneumeth.2024.1102392) to come

Project description:s synapse degeneration is an early event in Alzheimer’s disease (AD) pathophysiology, a biofluid marker of synapse loss in living patients could be a surrogate marker of disease prognosis and therefore would be an excellent addition to the AD biomarker arsenal. With direct access to the brain interstitial fluid, the cerebrospinal fluid (CSF) is a potential source of synapse-derived proteins that could be potential biomarkers of underlying synapse degeneration. The aim of this study was to identify, verify and evaluate a set of synaptic proteins as surrogate CSF markers of underlying synapse loss in AD patients. In the Discovery Stage, we combined high-throughput shotgun proteomics of the CSF with an exhaustive search of the literature and public databases for proteomic studies of the CSF and synapse. A thorough characterization of the synaptic component of the CSF identified 210 synaptic proteins that are detectable in human CSF. We selected an initial panel of 22 candidate biomarkers for evaluation. In the Verification Stage, 12 proteins were discarded due to poor detection by targeted mass spectrometry (Selected Reaction Monitoring, SRM). We confirmed the expression of the remaining 10 proteins either directly at (Calsynytenin-1, GluR2, GluR4, Neurexins 2A and 3A, Neuroligin-2, Syntaxin-1B, Thy-1 and Vamp-2), or surrounding (Tenascin-R), the human synapse using Array Tomography microscopy and biochemical fractionation methods. We quantified the synaptic panel by SRM in CSF samples from 2 independent clinical cohorts of cognitively normal controls and all clinical stages of AD (n=140). A set of the panel proteins demonstrated a non-linear profile distinct to that of existing biomarkers whereby the CSF levels were decreased at the earliest preclinical stage of AD, reflecting reduced synaptic density in these asymptomatic individuals and elevated at later symptomatic stages when neurodegeneration is widespread. In conclusion, we have identified a set of novel synapse-specific proteins that could have clinical value for assessing disease progression in individuals at-risk for AD and potentially in other neurological disorders characterized by early synapse loss.

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