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Record W7119125661 · doi:10.1002/alz70856_106436

Novel CSF astrocyte biomarkers are associated with amyloid load in Alzheimer's disease

2025· article· en· W7119125661 on OpenAlexaff
Luiza Santos Machado, Guilherme Povala, Ilaria Pola, Dzeneta Vizlin‐Hodzic, Pedro Rosa‐Neto, Kaj Blennow, Eduardo R. Zimmer, Henrik Zetterberg, Andrea L. Benedet, Nicholas J. Ashton

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiomarkerAstrocytePathologicalDiseaseCohortCerebrospinal fluidAmyloid (mycology)Alzheimer's Disease Neuroimaging Initiative

Abstract

fetched live from OpenAlex

Abstract Background Astrocytes are highly involved in Alzheimer's disease (AD) pathophysiology. GFAP, an astrocyte‐enriched protein, increases in response to amyloid (Aβ) pathology and is used as a fluid biomarker of astrocyte reactivity in AD. However, GFAP does not fully reflect the astrocytic dynamics in response to the disease. Thus, we aimed to identify novel astrocyte biomarkers in CSF that contribute to the understanding of the pathological changes in AD. Method We analyzed CSF proteomic data from 728 individuals in the ADNI cohort (SomaLogic). A pre‐defined list of 30 astrocyte‐enriched genes was contrasted with the available ADNI CSF proteomic data, resulting in eight proteins of interest, including GFAP. We examined their CSF levels across cognitively unimpaired (CU), mild cognitively impaired (MCI), and AD individuals (Figure 1a). The proteins levels in CSF were further investigated in CU and cognitively impaired (CI) individuals who were also categorized according to their Aβ status (ptau181/Aβ42 ratio cut‐off=0.028, Figure 1b). Voxelwise models assessed associations between the selected proteins and [ 18 F]Florbetapir‐PET, a biomarker of Aβ deposition, in a subset of the individuals ( n = 461), and CU and CI individuals separately. Models also included age and sex, and RFT was used for multiple comparisons correction in the imaging analyses. Result CSF NCAN was significantly reduced in AD individuals compared to CU and MCI (Figure 1a). Further analysis revealed elevated CSF GPC5 levels in Aβ‐positive CI (CI Aβ+) compared to Aβ‐negative CU (CU Aβ‐) and CI (CI Aβ‐) groups. In contrast, CSF LRIG1 and NCAN were only increased in CI+ compared to CI‐ individuals (Figure 1b). Positive associations were observed between CSF GPC5, LRIG1, and NCAN, and [ 18 F]Florbetapir‐PET, with GPC5 showing the most widespread cortical associations, particularly in CI individuals (Figure 2). Conclusion This study identifies GPC5, LRIG1, and NCAN as CSF astrocyte biomarkers altered across AD cognitive status and amyloid pathology. GPC5, in particular, showed the most widespread cortical association with Aβ deposition, consistent with its role in synaptic maturation and stabilization. Given that GPC5 is highly expressed in cortical astrocytes, these findings highlight its potential as a novel astrocytic biomarker in AD. Further validation will be conducted in an external cohort.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.293
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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