Distinctive associations between plasma p-tau181 levels and hippocampal subfield volume across the Alzheimer’s disease continuum
Bibliographic record
Abstract
Background: Plasma p-tau181 is a promising diagnostic marker of Alzheimer's disease (AD) pathology, reflecting amyloid accumulation, tau deposition, and downstream neurodegeneration that leads to cognitive impairment. However, the specificity of plasma p-tau181 to AD-related tau pathology remains unclear. Objective: To assess whether plasma p-tau181 is differentially associated with volumetric changes in distinct hippocampal subfields and whether they mediate the relationship between plasma p-tau181 and cognition across the AD continuum. Methods: 213 participants with normal cognition (N=57), mild cognitive impairment (N=109), and AD (N=47) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were included for cross-sectional analyses of hippocampal subfield volume that was quantified using the Automatic Segmentation of Hippocampal Subfields (ASHS) software. A subset (n=89) was evaluated for one-year longitudinal changes in hippocampal subfield volume. Results: < 0.05). Additionally, volumes of these subfields partially mediated the relationship between plasma p-tau181 and ADNI memory and executive function composite scores. Baseline plasma p-tau181, however, did not predict longitudinal atrophy of hippocampal subfields across diagnostic groups. Conclusions: Plasma p-tau181 is differentially associated with hippocampal subfields that are closely related to both age- and AD-related neurodegeneration. Elevated plasma p-tau181 levels may reflect tau accumulation, and volumetric changes in CA1 and DG may mediate the detrimental effect of tau pathology on cognition.
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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 | 0.000 |
| 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) | 0.001 | 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".