SynthesisCell reports. Medicine2023
Meta-analysis of published cerebrospinal fluid proteomics data identifies and validates metabolic enzyme panel as Alzheimer's disease biomarkers.
Synthesis in Cell reports. Medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Comprehensive Meta-Analysis of Differentially Expressed Proteins in Cerebrospinal Fluid Associated with Multiple Sclerosis.International journal of molecular sciences · 2025Pooled it
- In vivo profiling of astrocyte secretome reveals brain-region specific regulatory networks in a mouse model of amyloid pathology.Molecular neurodegeneration · 2026Article
- Reproducibility-driven discovery and systematic benchmarking reveal a robust cerebrospinal fluid proteomic signature in Alzheimer's disease.medRxiv : the preprint server for health sciences · 2026Article
- The Energetic Collapse of the Alzheimer's Brain: Metabolic Inflexibility Across Cells and Networks.Journal of neurochemistry · 2025Review
- Proteomic landscape of Alzheimer's disease: emerging technologies, advances and insights (2021 - 2025).Molecular neurodegeneration · 2025Review
- CAA proteomics meta-analysis reveals novel targets, key players, and the effects of sex, APOE, and brain region in humans.Acta neuropathologica · 2025Article
- Review
- High-Throughput Human Cerebrospinal Fluid Proteome Analysis with Direct Data-Independent Acquisition (dDIA).Methods in molecular biology (Clifton, N.J.) · 2025Article
- A compilation of reported alterations in the cerebrospinal fluid proteome in Alzheimer's disease.Brain communications · 2025Review
- Unraveling Potential Tauopathy Biomarkers in Cerebrospinal Fluid: Insights from Olfactory Tract Data.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Integrating amyloid and tau imaging with proteomics and genomics in Alzheimer's disease.Cell reports. Medicine · 2024Review
- Integrative proteomics identifies a conserved Aβ amyloid responsome, novel plaque proteins, and pathology modifiers in Alzheimer's disease.Cell reports. Medicine · 2024Article
- Are We Ready to Reclassify Crohn's Disease Using Molecular Classification?Journal of clinical medicine · 2023Article
- Potential diagnostic value of CSF metabolism-related proteins across the Alzheimer's disease continuum.Alzheimer's research & therapy · 2023Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
To develop therapies for Alzheimer's disease, we need accurate in vivo diagnostics. Multiple proteomic studies mapping biomarker candidates in cerebrospinal fluid (CSF) resulted in little overlap. To overcome this shortcoming, we apply the rarely used concept of proteomics meta-analysis to identify an effective biomarker panel. We combine ten independent datasets for biomarker identification: seven datasets from 150 patients/controls for discovery, one dataset with 20 patients/controls for down-selection, and two datasets with 494 patients/controls for validation. The discovery results in 21 biomarker candidates and down-selection in three, to be validated in the two additional large-scale proteomics datasets with 228 diseased and 266 control samples. This resulting 3-protein biomarker panel differentiates Alzheimer's disease (AD) from controls in the two validation cohorts with areas under the receiver operating characteristic curve (AUROCs) of 0.83 and 0.87, respectively. This study highlights the value of systematically re-analyzing previously published proteomics data and the need for more stringent data deposition.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.