Mass spectrometric simultaneous quantification of tau species in plasma shows differential associations with amyloid and tau pathologies
Bibliographic record
Abstract
Blood phosphorylated tau (p-tau) biomarkers, at differing sites, demonstrate high accuracy to detect Alzheimer's disease (AD). However, knowledge on the optimal marker for disease identification across the AD continuum and the link to pathology is limited. This is partly due to heterogeneity in analytical methods. In this study, we employed an immunoprecipitation mass spectrometry method to simultaneously quantify six phosphorylated (p-tau181, p-tau199, p-tau202, p-tau205, p-tau217 and p-tau231) and two non-phosphorylated plasma tau peptides in a total of 214 participants from the Paris Lariboisière and Translational Biomarkers of Aging and Dementia cohorts. Our results indicate that p-tau217, p-tau231 and p-tau205 are the plasma tau forms that best reflect AD-related brain changes, although with distinct emergences along the disease course and correlations with AD features-amyloid and tau. These findings support the differential association of blood p-tau variants with AD pathology, and our method offers a potential tool for disease staging in clinical trials.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".