Multi‐ancestry meta‐analysis identifies genetic modifiers of age‐at‐onset of Alzheimer's disease at known and novel loci
Bibliographic record
Abstract
Abstract INTRODUCTION Much of Alzheimer's disease (AD) risk is explained by age, apolipoprotein E ( APOE ) genotype, and sex. We sought to identify genetic modifiers of age at onset (AAO) of AD while probing the influence of sex and APOE among those with diverse ancestry. METHODS We performed genome‐wide association studies (GWASs) of AAO in two diverse samples followed by meta‐analysis, contrasting results with and without adjustment for sex and APOE . Genome‐wide significance was set to p < 5×10 −8 . RESULTS GWASs adjusting for sex, APOE , population structure, and relatedness revealed 17 significant loci including independent associations at AD risk loci and four novel signals. APOE adjustment influenced GWAS effect sizes across the genome while sex adjustment had minimal effect. DISCUSSION We identified association signals within a diverse but relatively small sample, replicating loci recently discovered in large European ancestry‐only GWASs, and illustrated the power of using a quantitative trait like AAO over a binary diagnosis trait. Highlights Survival analysis approach identified known and novel genetic modifiers of Alzheimer's disease (AD). Multi‐ancestry analyses revealed independent signals at known AD loci. Apolipoprotein E adjustment influenced variant effects across the genome.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".