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Record W4390192033 · doi:10.1002/alz.082953

Plasma pTau217: single vs multiple phospho‐site assays.

2023· article· en· W4390192033 on OpenAlexaff
Andréa Lessa Benedet, Ilaria Pola, Gallen Triana‐Baltzer, Guglielmo Di Molfetta, Burak Arslan, Nesrine Rahmouni, Cécile Tissot, Joseph Therriault, Stijn Servaes, Tharick A. Pascoal, Hartmuth C. Kolb, Andreas Jeromin, Kaj Blennow, Henrik Zetterberg, Nicholas J. Ashton, Pedro Rosa‐Neto

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiomarkerContext (archaeology)OncologyInternal medicineMedicineCohortAmyloid (mycology)PhosphorylationPathologyChemistryBiologyBiochemistry

Abstract

fetched live from OpenAlex

Abstract Background Blood biomarkers have gained much attention in recent years given their increasing ability to indicate amyloid pathology and excellent performance in distinguishing diagnostic groups in the context of Alzheimer’s disease (AD). Plasma pTau217 has been considered the best candidate biomarker to serve as diagnostic and prognostic tool for clinical trials. However, biomarker assays targeting tau phosphorylation on Thr217 may differ because of their composition (e.g., targeting multiple or single phosphorylation sites) which may lead to distinct associations with pathology. Thus, we aimed to compare two plasma pTau217 immunoassays that differ in regard to their target specificity. Method Participants from the TRIAD cohort with available cross‐sectional plasma and imaging data, incorporating within the AD spectrum, were included in this study (Young = 25;CU‐ = 107;CU+ = 32;MCI+ = 42;AD+ = 47;MCI‐ = 19). Plasma pTau was quantified using the assays from Janssen (pTau217+; which exhibits enhanced signal with co‐phosphorylation of pTau212) and from ALZpath (single phosphorylation on pTau217), both performed on the Simoa platform. Amyloid and tau pathologies were indexed by PET using [18F]AZD4694 and [18F]MK6240, respectively. ANCOVA compared biomarker values across groups, Spearman rank tested the correlations between them. Linear regression models (LM) evaluated the association between plasma and PET biomarkers globally and at the voxel level. Result Biomarker levels (fold mean of CU‐) were comparable across diagnostic groups, showing the expected increases in amyloid positive groups. Both plasma assays were highly correlated with amyloid (Fig.1), which was also observed on the LM adjusted by age and sex, and on the voxel‐wise analysis (Fig.2). Associations with tau PET SUVR (medial temporal) were also significant and showed similar distribution between the two pTau assays. When neocortical tau was evaluated, however, pTau217+ had a better association as well as higher correlation coefficients within amyloid+ (Fig.3) and neocortical tau+ groups than did ALZpath pTau217. Conclusion In general, pTau217 assays with different antibody specificity showed very similar associations with PET. However, pTau217+ achieved a better association with neocortical tau as compared to ALZpath pTau217. A biomarker targeting multiple phosphorylation sites might be a better proxy of advanced tau, therefore may offer improved ability to detect and exclude participants with advanced AD pathology for 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)0.002
metaresearch head score (Gemma)0.003
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.230
Teacher spread0.212 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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