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Record W4390198667 · doi:10.1002/alz.081771

Amyloid β‐dependent tau phosphorylation is triggered by reactive astrocytes in preclinical Alzheimer’s disease

2023· article· en· W4390198667 on OpenAlexaff
Bruna Bellaver, Guilherme Povala, Pâmela C.L. Ferreira, João Pedro Ferrari‐Souza, Douglas Teixeira Leffa, Firoza Z Lussier, Andréa Lessa Benedet, Nicholas J. Ashton, Cécile Tissot, Joseph Therriault, Stijn Servaes, Jenna Stevenson, Nesrine Rahmouni, Oscar L. López, Dana Tudorascu, Victor L. Villemagne, Miloš D. Ikonomović, Serge Gauthier, Eduardo R. Zimmer, Henrik Zetterberg, Kaj Blennow, Howard Aizenstein, William E. Klunk, Beth E. Snitz, Pauline M. Maki, Rebecca C. Thurston, Ann D. Cohen, Mary Ganguli, Thomas K. Karikari, Pedro Rosa‐Neto, Tharick A. Pascoal

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsMcGill University Health CentreMcGill University
Fundersnot available
KeywordsAstrocyteInternal medicinePsychologyEndocrinologyPathologicalPopulationAlzheimer's diseasePhosphorylationMedicineDiseaseOncologyChemistryPathologyCentral nervous systemBiochemistry

Abstract

fetched live from OpenAlex

Abstract Background A significant percentage of Aß‐positive cognitively unimpaired (CU) individuals do not develop detectable downstream tau pathology and, consequently, cognitive decline.Experimental literature suggest that reactive astrocytes are necessary to unleashing Aß effects in pathological tau phosphorylation.Here we aimed to investigate whether astrocyte reactivity is key to determining the association of Aß burden with early tau phosphorylation in preclinical Alzheimer’s disease (AD). Method We assessed 1,016 CU individuals from two research and one population‐based cohort (TRIAD, Pittsburgh and MYHAT) with Aß (plasma or PET), plasma p‐tau and GFAP measures. Individuals were classified as positive (Ast+) or negative (Ast‐) for astrocyte reactivity using a cutoff based on plasma GFAP of younger Aß‐ individuals.Lowess method and linear regressions accounting for age and sex were used to model the trajectories of plasma p‐tau epitopes as a function of Aß burden. Cohen’s d corrected for age and sex was used to estimate effect sizes between groups. Result We observed that plasma p‐tau181 levels increased as a function of Aß only in CU Ast+ individuals from Pittsburgh (ß = ‐0.35,t = 3.10,p = 0.003,Fig.1a,b), MYHAT (ß = ‐0.20,t = 2.26,p = 0.026, Fig.1d,e) and TRIAD (ß = 0.46,t = 2.92,p = 0.004;Fig.1g,h) cohorts. A significant interaction between Aß burden and astrocyte reactivity status on plasma p‐tau181 levels was observed in the Pittsburgh (ß = ‐0.29,t = 2.30,p = 0.022;Fig.1b), MYHAT (ß = ‐0.19,t = 2.07,p = 0.038;Fig.1e) and TRIAD (ß = 0.46,t = 2.92,p = 0.004;Fig.1h) cohorts.Cohen’s d analysis revealed that the presence of Aß+ and Ast+ has a large magnitude of effect on tau phosphorylation (Cohen’s d:Pittsburgh = 0.67; MYHAT = 0.69;TRIAD = 0.98;Fig.1c,f,i), whereas Aß+ in the absence of Ast+ presented a negligible effect size. Similar results were observed for plasma p‐tau231 and p‐tau217.Voxel‐wise analysis confirmed that Aß levels in brain regions known to present early Aß accumulation in AD associated with plasma p‐tau181 only in Ast+ individuals (Fig.2).Tau‐PET deposition occurred as a function of Aß burden only in CU Ast+ (Fig.3a), affecting 100% and 62% of the extension of the Braak I and II regions, respectively (Fig.3b) Conclusion We observed biomarker evidence across multiple cohorts that the presence of astrocyte reactivity, measured by plasma GFAP, plays a key role in the association of Aß with early tau pathology in preclinical AD.Our results might have implications for the biological definition of preclinical AD and selecting individuals for early preventive clinical trials.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.056
GPT teacher head0.354
Teacher spread0.297 · 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 designBench or experimental
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
Published2023
Admission routes1
Has abstractyes

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