Genetic Comparison of Symptomatic and Asymptomatic Persons With Alzheimer Disease Neuropathology
Bibliographic record
Abstract
OBJECTIVE: The objective was to determine whether symptomatic and asymptomatic persons with Alzheimer disease (AD) neuropathology have different allele counts for single-nucleotide polymorphisms that have been associated with clinical late-onset AD. METHODS: Data came from the National Alzheimer's Coordinating Center Uniform Data Set and Neuropathology Data Set, and the Alzheimer's Disease Genetics Consortium (ADGC). Participants had low to high AD neuropathologic change. The 22 known/suspected genes associated with late-onset AD were considered. "Symptomatic" was defined as Clinical Dementia Rating global score >0. RESULTS: Sixty-eight asymptomatic and 521 symptomatic participants met inclusion criteria. Single-nucleotide polymorphisms associated with ABCA7 [odds ratio (OR)=1.66; 95% confidence interval (CI), 1.03-2.85] and MAPT (OR=2.18; CI, 1.26-3.77) were associated with symptomatic status. In stratified analyses, loci containing CD2AP (OR=0.35; 95% CI, 0.16-0.74), ZCWPW1 (OR=2.98; 95% CI, 1.34-6.86), and MAPT (OR=3.73, 95% CI, 1.30-11.76) were associated with symptomatic status in APOE e4 carriers. CONCLUSIONS: These findings potentially explain some of the variation in whether a person with AD neuropathology expresses symptoms. Understanding why some people remain cognitively normal despite having AD neuropathology could identify pathways to disease heterogeneity and guide treatment trials.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".