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Record W4312086710 · doi:10.1002/alz.067639

Amyloid and tau pathologies associate with distinct aspects of the inflammatory cascade

2022· article· en· W4312086710 on OpenAlexaffabout
Bruna Bellaver, Douglas Teixeira Leffa, Pâmela C.L. Ferreira, João Pedro Ferrari‐Souza, Marco Antônio De Bastiani, Cécile Tissot, Firoza Z Lussier, Joseph Therriault, Andréa Lessa Benedet, Stijn Servaes, Mira Chamoun, Jenna Stevenson, Nesrine Rahmouni, Serge Gauthier, Michael Schöll, Nicholas J. Ashton, Eduardo R. Zimmer, Henrik Zetterberg, Thomas K. Karikari, Pedro Rosa‐Neto, Tharick A. Pascoal

Bibliographic record

VenueAlzheimer s & Dementia · 2022
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsMcGill University
Fundersnot available
KeywordsInflammationPsychologyTau proteinReceiver operating characteristicNeurosciencePathologyDiseaseMedicineAlzheimer's diseaseInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Inflammation has long been pointed out as a key feature in Alzheimer’s disease (AD). However, the heterogeneity of AD pathology might trigger different aspects of the immune response. Here, we aimed to study the association of the newly proposed concept of inflammatory composite indexes with Aβ and tau pathologies across the aging and AD spectra. We hypothesize that distinct inflammatory pathways are associated with the different hallmarks of AD. Method A panel of 92 inflammation‐related markers was measured in the CSF of 60 individuals (35 cognitively unimpaired and 25 cognitively impaired) from the McGill TRIAD cohort. These 92 proteins were clustered by ontogenetic similarity and physical interaction using STRING. A z‐scored composite value representing each cluster was created for each individual. Individuals were classified as Aβ‐ and tau‐positive using global [18F]AZD4694 and temporal meta‐ROI [18F]MK6240 PET, respectively. Linear regressions (corrected by diagnosis, age, sex, and APOEɛ4 status) and receiver operating characteristic (ROC) analyses evaluated clusters’ performance. Result Of the six clusters identified in our protein network analysis, three positively correlated with global Aβ‐PET (C4,C5, and C6) and three with meta‐ROI tau PET (C2,C4, and C5;Fig.1). However, controlling for Aβ PET, tau PET was only associated with C2, indicating that the association with the other two clusters (C4 and C5) was dependent of Aβ pathology. The cluster exclusively associated with tau (C2), represents tumor necrosis factor‐mediated signaling pathways. On the other hand, C6, related to the stimulation of interferon‐gamma production, and C5, related to glial cell‐derived neurotrophic receptor binding, are exclusively associated with Aβ. ROC analysis showed that all clusters presented a better performance predicting Aβ‐PET positivity than tau‐PET positivity (Fig.2A,B). Additionally, overall the clusters showed a better performance than sTREM2, a classical inflammatory biomarker. Conclusion Our novel clustering approach supports that Aβ and tau proteinopathies are associated with distinct aspects of the inflammatory cascade. Our results suggest that a composite of inflammatory proteins better identifies AD pathology than a single marker. Finally, this suggested cluster approach helps to understand the inflammatory response to Aβ and tau and can uncover inflammation‐related AD pathways.

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.019
GPT teacher head0.267
Teacher spread0.248 · 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
Published2022
Admission routes2
Has abstractyes

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