Investigation of 15 of the top candidate genes for late-onset Alzheimer’s disease
Bibliographic record
Abstract
The 12 genome-wide association studies (GWAS) published to-date for late-onset Alzheimer's disease (LOAD) have identified over 40 candidate LOAD risk modifiers, in addition to apolipoprotein (APOE) ε4. A few of these novel LOAD candidate genes, namely BIN1, CLU, CR1, EXOC3L2 and PICALM, have shown consistent replication, and are thus credible LOAD susceptibility genes. To evaluate other promising LOAD candidate genes, we have added data from our large, case-control series (n=5,043) to meta-analyses of all published follow-up case-control association studies for six LOAD candidate genes that have shown significant association across multiple studies (TNK1, GAB2, LOC651924, GWA_14q32.13, PGBD1 and GALP) and for an additional nine previously suggested candidate genes. Meta-analyses remained significant at three loci after addition of our data: GAB2 (OR=0.78, p=0.007), LOC651924 (OR=0.91, p=0.01) and TNK1 (OR=0.92, p=0.02). Breslow-Day tests revealed significant heterogeneity between studies for GAB2 (p<0.0001) and GWA_14q32.13 (p=0.006). We have also provided suggestive evidence that PGBD1 (p=0.04) and EBF3 (p=0.03) are associated with age-at-onset of LOAD. Finally, we tested for interactions between these 15 genes, APOE ε4 and the five novel LOAD genes BIN1, CLU, CR1, EXOC3L2 and PICALM but none were significant after correction for multiple testing. Overall, this large, independent follow-up study for 15 of the top LOAD candidate genes provides support for GAB2 and LOC651924 (6q24.1) as risk modifiers of LOAD and novel associations between PGBD1 and EBF3 with age-at-onset.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".