Comparing tau status determined via plasma pTau181, pTau231 and [18F]MK6240 tau-PET
Bibliographic record
Abstract
Background Tau in Alzheimer's disease (AD) is assessed via cerebrospinal fluid (CSF) and Positron emission tomography (PET). Novel methods to detect phosphorylated tau (pTau) in blood have been recently developed. We aim to investigate agreement of tau status as determined by [ 18 F]MK6240 tau-PET, plasma pTau181 and pTau231. Methods We assessed cognitively unimpaired young, cognitively unimpaired, mild cognitive impairment and AD individuals with [ 18 F]MK6240, plasma pTau181, pTau 231, [ 18 F]AZD4694 amyloid-PET and MRI. A subset underwent CSF assessment. We conducted ROC curves to obtain cut-off values for plasma pTau epitopes. Individuals were categorized as positive or negative in all biomarkers. We then compared the distribution among concordant and discordant groups in relation to diagnosis, Aβ status, APOE ε4 status, [ 18 F]AZD4694 global SUVR, hippocampal volume and CSF pTau181. Findings The threshold for positivity was 15.085 pg/mL for plasma pTau181 and 17.652 pg/mL for plasma pTau231. Most individuals had concordant statuses, however, 18% of plasma181/PET, 26% of plasma231/PET and 25% of the pTau231/pTau181 were discordant. Positivity to at least one biomarker was often accompanied by diagnosis of cognitive impairment, Aβ positivity, APOE ε4 carriership, higher levels of [ 18 F]AZD4694 global SUVR, hippocampal atrophy and CSF pTau181. Interpretation Plasma pTau181, pTau231 and [ 18 F]MK6240 seem to reflect different stages of tau progression. Plasma biomarkers can be useful in the context of diagnostic information and clinical trials, to evaluate the disease stage. Moreover, they seem to confidently evaluate tau-PET positivity. Funding Moreover, this study was supported by Weston Brain Institute, Canadian Institute of Health Research and Fonds de Recherche du Québec.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".