<i>APOE</i> ε4 carrier status modifies plasma p‐tau181 concentrations in cognitively healthy super‐seniors
Bibliographic record
Abstract
INTRODUCTION: This study investigates the effect of apolipoprotein E (APOE) genotype on neurology plasma biomarkers in cognitively healthy Super-Seniors. METHODS: Three hundred seventy plasma specimens from Super-Senior participants ≥ 85 years old, who have never been diagnosed with dementia, cancer, diabetes, cardiovascular, or major pulmonary disease, were analyzed on the Quanterix Simoa HD-X analyzer using commercial Neurology 4-plex E and phosphorylated tau (p-tau)181 assays. RESULTS: Eighty (22%) participants were APOE ε4 carriers and 290 (73%) were non-carriers. No significant differences were found between APOE ε4 carriers and non-carriers regarding age, sex, or Mini-Mental State Examination scores. In APOE ε4 carriers, plasma amyloid beta 42/40 was lower and p-tau181 and glial fibrillary acidic protein were higher compared to non-APOE ε4 carriers. After adjusting for demographic variables, p-tau181 was the only biomarker to remain significantly associated with APOE ε4 carrier status. DISCUSSION: APOE ε4 genotype modifies plasma p-tau181 concentration in seniors resilient to age-related clinical disease, suggesting that some Super-Seniors may have Alzheimer's disease pathology without progressing to cognitive decline. HIGHLIGHTS: Healthy seniors enable identification of associations that may be masked by disease. Plasma phosphorylated tau (p-tau)181 concentrations associate with apolipoprotein E (APOE) ε4 carriership in healthy seniors. APOE should be accounted for when interpreting p-tau181, regardless of disease.
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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 | 0.000 | 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) | 0.002 | 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".