ArticleMolecular neurodegeneration2025
Large-scale CSF proteome profiling identifies biomarkers for accurate diagnosis of frontotemporal dementia.
Article in Molecular neurodegeneration, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Effects of the novel phosphodiesterase 9 inhibitor irsenontrine on CSF proteomics profile in AβAlzheimer's research & therapy · 2026Trial
- Distinct proteomic CSF profiles in genetic frontotemporal lobar degeneration.Brain : a journal of neurology · 2026Article
- Plasma proteome profiling identified biomarkers for the differential diagnosis and molecular staging of neurodegenerative dementias.Nature aging · 2026Article
- Analytical and clinical validation of a novel proximity extension assay-based plasma biomarker panel in a cohort of prevalent neurodegenerative dementias.Alzheimer's research & therapy · 2026Article
- An acetylated Tau-174 CSF biomarker discriminates between TDP-43 and tau pathology in patients with frontotemporal lobar degeneration.Nature medicine · 2026Article
- Article
- Tissue-specific immune and MAPK signatures in models of reduced Progranulin and Western diet.Neurobiology of disease · 2026Article
- Understanding Neurodegenerative Diseases From the -Omics Perspective: Lessons Learnt.Annals of neurology · 2026Review
- Microglia Mitochondrial Metabolism in Neurological Diseases.Molecular neurobiology · 2026Review
- Protein-based Diagnosis and Analysis of Co-pathologies Across Neurodegenerative Diseases: Large-Scale AI-Boosted CSF and Plasma Classification.Research square · 2025Article
- CHIT1 and DDAH1 levels relate to amyloid-related imaging abnormalities risk profile in Alzheimer's disease patients.Alzheimer's research & therapy · 2025Article
- Protein-based Diagnosis and Analysis of Co-pathologies Across Neurodegenerative Diseases: Large-Scale AI-Boosted CSF and Plasma Classification.medRxiv : the preprint server for health sciences · 2025Article
- Benchmarking the AI-based diagnostic potential of plasma proteomics for neurodegenerative disease in 17,170 people.medRxiv : the preprint server for health sciences · 2025Article
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20 authors.
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Abstract
backgroundDiagnosis of Frontotemporal dementia (FTD) and its specific underlying neuropathologies (frontotemporal lobar degeneration; FTLD-Tau and FTLD-TDP) are challenging, and thus, fluid biomarkers are needed to improve diagnostic accuracy.
methodsWe used proximity extension assays to analyze 665 proteins in cerebrospinal fluid (CSF) samples from a multicenter cohort, which included patients with FTD (n = 189), Alzheimer’s Disease dementia (AD; n = 232), and cognitively unimpaired individuals (n = 196). In a subset, FTLD neuropathology was determined based on phenotype or genotype (FTLD-Tau = 87 and FTLD-TDP = 67). Differences in protein expression profiles were analyzed using nested linear models. Penalized generalized linear modeling was used to identify classification protein panels, which were translated to custom multiplex assays and validated in two clinical cohorts (cohort 1: n = 161; cohort 2: n = 162), one autopsy-confirmed cohort (n = 100), and one genetic cohort (n = 55).
resultsForty-three proteins were differentially regulated in FTD compared to controls and AD, reflecting axon development, regulation of synapse assembly, and cell-cell adhesion mediator activity pathways. Classification analysis identified a 14- and 13-CSF protein panel that discriminated FTD from controls (FTD diagnostic panel, AUC: 0.96) or AD (FTD differential diagnostic panel, AUC: 0.91). Custom multiplex panels confirmed the strong discriminative performancen between FTD and controls (AUCs > 0.96) and between FTD and AD (AUCs > 0.88) across three validation cohorts, including one with autopsy confirmation (AUCs > 0.90). Validation in genetic FTD (including C9orf72, GRN, and MAPT mutation carriers) revealed high accuracy of the FTD diagnostic panel in identifying both the presymptomatic (AUCs > 0.95) and symptomatic (AUC: 1) stages. Six proteins were differentially regulated between FTLD-TDP and FTLD-Tau. However, a reproducible classification model could not be generated (AUC: 0.80).
conclusionsOverall, this study introduces novel FTD-specific biomarker panels with potential use in diagnostic settings.
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