Plasma p‐tau231, p‐tau181, <scp>PET</scp> Biomarkers, and Cognitive Change in Older Adults
Bibliographic record
Abstract
Objective The objective of this study was to evaluate novel plasma p‐tau231 and p‐tau181, as well as Aβ 40 and Aβ 42 assays as indicators of tau and Aβ pathologies measured with positron emission tomography (PET), and their association with cognitive change, in cognitively unimpaired older adults. Methods In a cohort of 244 older adults at risk of Alzheimer's disease (AD) owing to a family history of AD dementia, we measured single molecule array (Simoa)‐based plasma tau biomarkers (p‐tau231 and p‐tau181), Aβ 40 and Aβ 42 with immunoprecipitation mass spectrometry, and Simoa neurofilament light (NfL). A subset of 129 participants underwent amyloid‐β ( 18 F‐NAV4694) and tau ( 18 F‐flortaucipir) PET assessments. We investigated plasma biomarker associations with Aβ and tau PET at the global and voxel level and tested plasma biomarker combinations for improved detection of Aβ‐PET positivity. We also investigated associations with 8‐year cognitive change. Results Plasma p‐tau biomarkers correlated with flortaucipir binding in medial temporal, parietal, and inferior temporal regions. P‐tau231 showed further associations in lateral parietal and occipital cortices. Plasma Aβ 42/40 explained more variance in global Aβ‐PET binding than Aβ 42 alone. P‐tau231 also showed strong and widespread associations with cortical Aβ‐PET binding. Combining Aβ 42/40 with p‐tau231 or p‐tau181 allowed for good distinction between Aβ‐negative and ‐positive participants (area under the receiver operating characteristic curve [AUC] range = 0.81–0.86). Individuals with low plasma Aβ 42/40 and high p‐tau experienced faster cognitive decline. Interpretation Plasma p‐tau231 showed more robust associations with PET biomarkers than p‐tau181 in presymptomatic individuals. The combination of p‐tau and Aβ 42/40 biomarkers detected early AD pathology and cognitive decline. Such markers could be used as prescreening tools to reduce the cost of prevention trials. ANN NEUROL 2022;91:548–560
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".