Characterization of plasma biomarkers of individuals with amyloid‐independent increased tau positron‐emission tomography uptake
Bibliographic record
Abstract
Abstract Background Increased uptake on Tau positron‐emission tomography (PET) is sometimes observed in the absence of amyloid ß accumulation. This A‐T+ PET profile might represent primary age‐related tauopathy (PART), an amyloid ß‐independent 3R/4R tauopathy observed in aging brains. Although A‐T+ individuals have been shown to follow a different cognitive trajectory compared to A‐T‐ and A+T+ individuals, it remains unknown how they differ in terms of plasma biomarkers. Here, we aim to characterize the plasma biomarkers of A‐T+ individuals. Method This is a cross‐sectional study with data from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort. Participants were classified into four categories based on their amyloid ß ([18F]AZD4694) and Tau ([18F]MK6240) PET status (A‐T‐, A+T‐, A+T+ and A‐T+). Plasma biomarkers phosphorylated tau (p‐tau)181, p‐tau217, p‐tau231, total tau (t‐tau), neurofilament light (NfL) and GFAP were compared using the Kruskal‐Wallis test with post hoc Benjamini‐Hochberg (BH) correction. Discriminative performance was assessed using the area under the receiver operating characteristic curve (AUROC). Result Among the total 468 participants, 64 (13.7%) had A‐T+ PET status. The A‐T+ PET participants had a mean age 66.9 years (SD: 12.8), with 62.5% women and 39.1% showing cognitive impairment. Plasma p‐tau181, p‐tau217, p‐tau231 and GFAP were significantly higher in A+T+ individuals compared to A‐T+ (all p < 0.001). On the other hand, plasma p‐tau181 and 217 were significantly different between A‐T‐ vs A‐T+ (p<0.05), but not p‐tau231 and plasma GFAP. No significant differences were found in t‐tau or NfL regarding A‐T‐. Plasma p‐tau217 and plasma GFAP had the highest discriminative accuracies for A‐T+ vs A+T+ (AUROC: 0.860 and 0.836 respectively). Conclusion Our data suggest that individuals with an A‐T+ PET status exhibit a different plasma biomarker profile than those with A+T+ and A‐T‐ status. Further characterization of fluid biomarkers could help identify this group of individuals and facilitate the differential diagnosis of adults with cognitive impairment. Furthermore, our results lend support to the use of plasma biomarkers for identifying amyloid ß PET positivity.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".