Evidence map›Paper›PMID 40145305›Full record

ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2025

Novel blood-based proteomic signatures across multiple neurodegenerative diseases.

Robert Durcan, Amanda Heslegrave, Peter Swann, Julia Goddard, Leonidas Chouliaras, Alexander G Murley, George Savulich, W Richard Bevan-Jones, Owen Swann, Nicholas J Ashton and 6 more

Abstract read
In one paragraph

Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Systematic Review with Meta-Analysis of Biofluid Markers for Huntington's Disease.Movement disorders : official journal of the Movement Disorder Society · 2025
    Pooled it
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  8. Inflammation profiles in Alzheimer's disease relate to cognition and neurodegeneration.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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  11. Dementia etiology classification using NULISA plasma biomarkers and machine learning.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Robert DurcanDepartment of Clinical Neurosciences, University of Cambridge and Cambridge University Hospitals NHS Trust, Cambridge, UK.
Amanda HeslegraveUK Dementia Research Institute, University College London, London, UK.
Peter SwannDepartment of Psychiatry, University of Cambridge, Cambridge, UK.
Julia GoddardDepartment of Clinical Neurosciences, University of Cambridge and Cambridge University Hospitals NHS Trust, Cambridge, UK.
Leonidas ChouliarasDepartment of Psychiatry, University of Cambridge, Cambridge, UK.
Alexander G MurleyDepartment of Clinical Neurosciences, University of Cambridge and Cambridge University Hospitals NHS Trust, Cambridge, UK.
George SavulichDepartment of Psychiatry, University of Cambridge, Cambridge, UK.
W Richard Bevan-JonesDepartment of Psychiatry, University of Cambridge, Cambridge, UK.
Owen SwannUK Dementia Research Institute, University College London, London, UK.
Nicholas J AshtonDepartment of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden.
Kaj BlennowDepartment of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden.
William McEwanUK Dementia Research Institute, University of Cambridge, Cambridge, UK.
Henrik ZetterbergUK Dementia Research Institute, University College London, London, UK.
James B RoweDepartment of Clinical Neurosciences, University of Cambridge and Cambridge University Hospitals NHS Trust, Cambridge, UK.
John T O'BrienDepartment of Psychiatry, University of Cambridge, Cambridge, UK.
Maura MalpettiDepartment of Clinical Neurosciences, University of Cambridge and Cambridge University Hospitals NHS Trust, Cambridge, UK.

Funding

Cambridge University Centre for Parkinson-PlusCurePSP 689-2024-01-PipelineDementias Platform UKHORIZON EUROPE European Innovation Council 101053962Medical Research Council MC_UU_00030/14;MR/T033371/1NIHR Cambridge Biomedical Research Centre BRC-1215-20014;NIHR203312Progressive Supranuclear Palsy AssociationPSP AssociationRace Against Dementia Alzheimer's Research UK ARUK-RADF2021A-010Swedish Research Council #2019-02397Swedish Research Council #2022-01018Swedish Research Council #2023-00356Swedish State Support for Clinical Research #ALFGBG-71320The Galen and Hilary Weston FoundationUK Dementia Research InstituteWellcome TrustWellcome Trust 103838Wellcome Trust 220258
6 · The paper itself

Abstract

introductionBlood-based biomarkers have the potential to support early and accurate diagnoses of neurodegenerative diseases, which are sensitive to molecular pathology and are predictive of outcome. We evaluated a novel multiplex proteomic method in people with diverse neurodegenerative diseases.

methodsSerum from people with Alzheimer's disease (N = 36), Lewy body dementia (N = 34), frontotemporal dementia (N = 36), and progressive supranuclear palsy (N = 36) and age-matched controls (N = 30) was analyzed with the nucleic acid linked immuno-sandwich assay (NULISA) central nervous system panel (≈ 120 analytes) and inflammation panel (250 analytes). Biomarkers were compared across groups and included as predictors of survival.

resultsThe NULISA panels demonstrated high sensitivity and reliability for detecting multiple biomarkers across neurodegenerative disorders. There were condition-specific proteomic biomarkers, while neurofilament light chain, corticotropin-releasing hormone, CD276, and a data-driven inflammation pattern were significant transdiagnostic outcome predictors. DISCUSSION: The sensitive NULISA multiplex approach supports differential diagnosis and target identification, with prognostically informative dementia-related biomarkers. HIGHLIGHTS: We tested the novel technology nucleic acid linked immuno-sandwich assay (NULISA) in people with diverse neurodegenerative diseases, which demonstrated high sensitivity and reliability for detecting multiple biomarkers in serum samples. We compared the NULISA central nervous system serum results to single molecule array (Simoa) plasma assays for phosphorylated tau (p-tau)217, p-tau231, neurofilament light chain (NfL), and glial fibrillary acidic protein, finding strong correlations. Increased levels of serum NfL were identified across all patient groups and most elevated in the frontotemporal dementia (FTD) and progressive supranuclear palsy (PSP) cohorts, while p-tau epitopes were the most significant markers in patients with Alzheimer's disease (AD) and Lewy body dementia. Patients with FTD and PSP showed upregulation of many inflammation markers, compared to controls and patients with AD. We found condition-specific proteomic biomarkers, while NfL, corticotropin-releasing hormone, CD276, and data-driven immune signatures were significant transdiagnostic predictors of clinical outcomes (survival rates).

Indexed as

Alzheimer DiseaseNeurodegenerative DiseasesProteomicsAgedBiomarkersFemaleFrontotemporal DementiaHumansLewy Body DiseaseMaleMiddle AgedReproducibility of ResultsSupranuclear Palsy, ProgressiveBiomarkersblood‐based biomarkersdementiamultiplex assaysnon–Alzheimer's disease neurodegenerative diseasesnucleic acid linked immuno‐sandwich assay

Identifiers

PMID40145305
PMCPMC11947754

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Registered trials

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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.