Prevalence of Alzheimer’s Pathologic Endophenotypes in Asymptomatic and Mildly Impaired First-Degree Relatives
Bibliographic record
Abstract
OBJECTIVE: A positive family history (FH) is a risk factor for late-onset Alzheimer's disease (AD). Our aim was to examine the effects of FH on pathological and neuronal loss biomarkers across the cognitive spectrum. DESIGN: Cross-sectional analyses of data from a national biomarker study. SETTING: The Alzheimer's Disease Neuroimaging Initiative national study. PATIENTS: 257 subjects (ages 55-89), divided into cognitively normal (CN), mild cognitive impairment (MCI), and AD groups, with CSF and FH data. OUTCOME MEASURES: Cerebrospinal fluid (CSF) Aβ42, tau, and tau/Aβ42 ratio, MRI-measured hippocampal volumes. STATISTICS: Univariate and multivariate analyses. RESULTS: In MCI, CSF Aβ42 was lower (p = .005), t-tau was higher (p = 0.02) and t-tau/Aβ42 ratio was higher (p = 0.002) in FH+ than FH- subjects. A significant residual effect of FH on pathologic markers in MCI remained after adjusting for ApoE4 (p<0.05). Among CN, 47% of FH+ exhibited "pathologic signature of AD" (CSF t-tau/Aβ42 ratio >0.39) versus 21% of FH- controls (p = 0.03). The FH effect was not significant in AD subjects. Hippocampal and intracranial volumes did not differ between FH+ and FH- subjects in any group. CONCLUSIONS: A positive family history of late-onset AD is associated with a higher prevalence of an abnormal cerebral beta-amyloid and tau protein phenotype in MCI. The unexplained genetic heritability in family history is about the half the size of the ApoE4 effect. Longitudinal studies are warranted to more definitively examine this issue.
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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 | 0.002 |
| 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 | 0.000 | 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".