<i>APOE4</i> Carrier Status Modifies Alzheimer’s Disease Plasma Biomarker Concentrations in Healthy Adults Over 85 Years Old
Bibliographic record
Abstract
Abstract Background Many blood‐based biomarkers have been thoroughly investigated in the context of Alzheimer’s disease (AD) and other dementias. However, few studies have examined these biomarkers in healthy seniors in the absence of dementia or other age associated morbidities. Investigating biomarkers in a healthy geriatric population allows for the identification of novel biological associations that might otherwise be masked by presence of disease. This study will investigate the effect of APOE genotype on plasma biomarkers of AD to determine whether carrying the APOE4 allele, which increases risk of AD, modifies biomarker concentrations in healthy seniors. Plasma biomarkers analyzed include: amyloid beta 42/40 (Aβ42/40), phosphorylated tau‐181 (p‐tau‐181), neurofilament light (NF‐L), and glial fibrillary acidic protein (GFAP). Methods 370 plasma specimens from the Super Seniors study, which enrolled participants ≥85 years old who have never been diagnosed dementia, cancer, diabetes, cardiovascular or major pulmonary disease; were used. Biomarkers were analysed on the Quanterix Simoa HD‐X analyzer using commercial Neurology 4‐plex E and p‐tau‐181 assays. Group comparisons were performed using a Mann‐Whitney test for continuous variables and a Fisher’s exact test for categorical variables. The association between APOE genotype and biomarker concentration was analyzed using multivariable linear regression. Results 80 (22%) participants were APOE4 carriers (E3E4 N = 71, E4E4 N = 3, E2E4 N = 6) and 290 (73%) were non‐carriers (E2E2 N = 3, E2E3 N = 58, E3E3 N = 229). No significant differences were found between APOE4 carriers and non‐carriers in age (p = 0.3215), sex (p>0.9999), or mini mental state exam scores (p = 0.1327). In APOE4 carriers, Aβ42/40 is lower (0.0596 vs 0.0618 pg/ml, p = 0.0462), and p‐tau‐181 (3.24 vs 2.78 pg/ml, p = 0.0069) and GFAP (196 vs 172 pg/ml, p = 0.0474) are higher than in non‐APOE4 carriers. NF‐L had no significant difference between carrier status (p = 0.1188). After adjusting for age and sex, p‐tau‐181 remains significantly associated with APOE4 carrier status (β = 0.066, p = 0.0112), while Aβ42/40 and GFAP no longer have significant associations. Conclusions p‐tau‐181 concentration is associated with APOE4 genotype in healthy seniors, making it an important variable to account for in future analysis.
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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 | 0.001 |
| 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".