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Record W4416414483 · doi:10.1038/s43856-025-01171-4

APOE ε4 potentiates tau related reactive astrogliosis assessed by cerebrospinal fluid YKL40 in Alzheimer’s disease

2025· article· en· W4416414483 on OpenAlexafffund
Lydia Trudel, Joseph Therriault, Arthur C. Macedo, Marcel S. Woo, Nesrine Rahmouni, Étienne Aumont, Stijn Servaes, Seyyed Ali Hosseini, João Pedro Ferrari‐Souza, Bruna Bellaver, Pâmela C.L. Ferreira, Tevy Chan, Yi‐Ting Wang, Jaime Fernandez‐Arias, Yansheng Zheng, Brandon J. Hall, Jenna Stevenson, Robert Hopewell, Chris Hsiao, Maxime Montembeault, Jesse Klostranec, Yasser Iturria‐Medina, Paolo Vitali, Thomas K. Karikari, Andréa Lessa Benedet, Nicholas J. Ashton, Eduardo R. Zimmer, Serge Gauthier, Tharick A. Pascoal, Henrik Zetterberg, Kaj Blennow, Pedro Rosa‐Neto

Bibliographic record

VenueCommunications Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsMcGill UniversityCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalMcGill University Health CentreMcGill Genome CentreMontreal Neurological Institute and Hospital
FundersNational Institute on AgingCanadian Institutes of Health ResearchFonds de Recherche du Québec - SantéHORIZON EUROPE Framework ProgrammeVetenskapsrådetFondation Brain CanadaEuropean CommissionWeston Brain InstituteConsortium canadien en neurodégénérescence associée au vieillissementAlzheimer's Association
KeywordsNeuroinflammationAstrogliosisApolipoprotein EDiseaseCerebrospinal fluidInflammation

Abstract

fetched live from OpenAlex

Glial responses are involved in neurodegenerative processes, with tau pathology often associated with increased glial inflammatory responses in Alzheimer’s disease (AD). The apolipoprotein E (APOE) ε4 allele, the major genetic susceptibility gene for AD, might contribute to this process by modulating both tau pathology and inflammatory cascades in the brain. We used data from the Translational Biomarkers of Alzheimer’s Disease (TRIAD) cohort (n = 137) to investigate the association between YKL-40, a marker of reactive astrogliosis, and tau burden measured with PET imaging, while also exploring the involvement of APOE ε4 carriership. Statistical analyses included correlation and regression models controlling for age and sex. Here we show that tau pathology is positively associated with YKL-40 levels, reflecting regional patterns of astrocyte activity in the brain. Furthermore, this association is more widespread in individuals carrying the APOE ε4 allele, suggesting a genotype-specific modulation of the glial neuroinflammatory response. Our findings demonstrate a link between tau accumulation and astrocyte-mediated neuroinflammation in AD and highlight the modulatory role of APOE ε4 in this process. Taken together, our findings help inform the multifaceted role of tau-associated neuroinflammation in the progression of AD. Alzheimer’s disease is a brain disorder characterized by the accumulation of abnormal proteins, including tau, which contribute to memory loss and cognitive decline. Brain support cells called astrocytes respond to this protein build-up by becoming reactive, which can lead to inflammation in the brain. In this study, we used brain scans and cerebrospinal fluid samples from 137 participants to examine how astrocyte reactivity, measured by the protein YKL-40, relates to tau accumulation. We also investigated whether carrying a common genetic risk factor, APOE ε4, influences this relationship. We found that higher tau levels are associated with increased astrocyte reactivity, and this association is stronger in people carrying APOE ε4. These findings suggest that genetic risk may amplify inflammation in Alzheimer’s disease. Trudel et al. investigate the relationship between tau pathology and reactive astrogliosis in Alzheimer’s disease using PET imaging and CSF biomarkers. Their findings suggest that APOE ε4 amplifies tau-associated glial inflammation, offering insights into genotype-specific mechanisms driving AD-associated neuroinflammation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.765
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.039
GPT teacher head0.369
Teacher spread0.330 · 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 teacher head, 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

Citations3
Published2025
Admission routes2
Has abstractyes

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