No clear evidence for relationships of Apolipoprotein E genotype with measures of common infections in three UK cohorts
Bibliographic record
Abstract
Abstract APOE genotype is a very strong genetic risk factor for late-onset Alzheimer’s disease (AD). This relationship may involve mediation by common infections—several of which are also dementia risk factors. We investigated associations of APOE ε2 and ε4 carriage with serostatus and antibody titres to 14 common pathogens in three population-based cohorts (UK Biobank, National Survey of Health and Development, Southall and Brent Revisited). We conducted analyses in each cohort using mixed models, including age, sex and genetic principal components as fixed effects, and genetic relatedness as a random effect. In secondary analyses, we additionally assessed (i) relationships of APOE ε2 and ε4 dosage (i.e. number of copies of the allele of interest), and (ii) relationships of APOE genotype with continuous antibody titres (rank-based inverse normal transformed). Findings were meta-analysed across cohorts (n = 10,059) using random-effects models and corrected for multiple tests using the false discovery rate. We found no clear evidence of relationships between APOE genotype and serostatus or antibody titres to any pathogen, with no associations observed in any of our analyses following multiple testing correction. These findings do not support roles for various common infections found in the UK as mediators of APOE effects on AD risk.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".