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Record W4206521159 · doi:10.1002/alz.057860

Plasma p‐Tau181 and p‐Tau231 offer complementary information to identify Alzheimer's disease pathophysiology

2021· article· en· W4206521159 on OpenAlexaffabout
Pâmela C.L. Ferreira, Wagner S. Brum, João Pedro Ferrari‐Souza, Cécile Tissot, Bruna Bellaver, Joseph Therriault, Andréa Lessa Benedet, Nicholas J. Ashton, Stijn Servaes, Firoza Z Lussier, Mira Chamoun, Jenna Stevenson, Nesrine Rahmouni, Serge Gauthier, Eugeen Vanmechelen, Henrik Zetterberg, Kaj Blennow, Eduardo R. Zimmer, Thomas K. Karikari, Pedro Rosa‐Neto, Tharick A. Pascoal

Bibliographic record

VenueAlzheimer s & Dementia · 2021
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsDouglas Mental Health University InstituteDouglas CollegeMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsPathophysiologyBiomarkerMedicineInternal medicineCohortPositron emission tomographyOncologyGastroenterologyNuclear medicineChemistry

Abstract

fetched live from OpenAlex

Abstract Background Pathophysiological detection of Alzheimer’s disease (AD) is commonly made using cerebrospinal fluid (CSF) and positron emission tomography (PET). However, these methods are invasive and expensive, limiting their use in clinical settings Blood‐based biomarkers, mainly measuring phosphorylated tau epitopes at threonine 181 (p‐tau181), threonine 217 (p‐tau217), threonine 231 (p‐tau231), have shown promising results in detecting AD. However, it is still unknown whether the use of different plasma p‐Tau epitopes offer overlap or complementary information. Here, we tested the hypothesis that plasma p‐Tau181 and p‐Tau231 markers provide complementary information to each other to identify AD pathophysiology. Methods Plasma p‐Tau181, p‐Tau231, [18F]AZD4694 amyloid‐PET, [18F]MK6240 tau‐PET, MRI and cognitive assessment from 284 individuals [30 cognitively unimpaired (CU) young, 155 CU), 54 mild cognitive impairment (MCI) and 38 AD] were obtained from the McGill TRIAD cohort. The individuals with diagnose of AD or MCI was classified as cognitively impaired (CI). Maximum Youden Index were used to determine cut‐offs for plasma p‐Tau181 (11.1 ng/mL) and plasma p‐Tau231 (11.8 ng/mL) considering CU young adults as controls. We classified the individual as positive or negative using plasma for each p‐Tau biomarker. Individuals were divided in the four possible groups (p‐Tau181‐/p‐Tau231‐, p‐Tau181+/p‐Tau231‐, p‐Tau181‐/p‐Tau231+ and p‐Tau181+/p‐Tau231+) and compared to assess differences in cognition and other biomarkers. Results Plasma p‐tau p‐Tau181 and p‐Tau231 showed moderate correlation with each other (r = 0.64, p <0.0001) (Figure 1). The p‐Tau181+/p‐Tau231+ group presented higher tau PET and amyloid PET uptake compared to groups negative for both or only one p‐tau biomarker (all p<0.01) (Figure 2A, B). Similarly, p‐Tau181+/p‐Tau231+ group showed worse cognitive performance and hippocampal atrophy than individuals with at least one p‐tau biomarker negative (Figure 2C‐E). Conclusion These findings highlight ‐ for the first time ‐ that individuals positive for both p‐tau231 and p‐tau181 show worse cognitive performance, higher amyloid and tau burden, and lower hippocampus volume than individuals positive for only one of these markers. Our results have important implications for the use of plasma p‐tau biomarker in clinical trials and practice, suggesting that the quantification of more than one plasma p‐tau epitope may be useful to identify individuals on an AD pathway.

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)0.001
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.000

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 head0.033
GPT teacher head0.328
Teacher spread0.295 · 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

Citations4
Published2021
Admission routes2
Has abstractyes

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