Whole‐exome sequencing in 20,197 persons for rare variants in Alzheimer's disease
Bibliographic record
Abstract
Abstract Objective The genetic bases of Alzheimer's disease remain uncertain. An international effort to fully articulate genetic risks and protective factors is underway with the hope of identifying potential therapeutic targets and preventive strategies. The goal here was to identify and characterize the frequency and impact of rare and ultra‐rare variants in Alzheimer's disease, using whole‐exome sequencing in 20,197 individuals. Methods We used a gene‐based collapsing analysis of loss‐of‐function ultra‐rare variants in a case–control study design with data from the Washington Heights‐Inwood Columbia Aging Project, the Alzheimer's Disease Sequencing Project and unrelated individuals from the Institute of Genomic Medicine at Columbia University. Results We identified 19 cases carrying extremely rare SORL 1 loss‐of‐function variants among a collection of 6,965 cases and a single loss‐of‐function variant among 13,252 controls ( P = 2.17 × 10 −8 ; OR : 36.2 [95% CI : 5.8–1493.0]). Age‐at‐onset was 7 years earlier for patients with SORL 1 qualifying variant compared with noncarriers. No other gene attained a study‐wide level of statistical significance, but multiple top‐ranked genes, including GRID 2 IP , WDR 76 and GRN , were among candidates for follow‐up studies. Interpretation This study implicates ultra‐rare, loss‐of‐function variants in SORL 1 as a significant genetic risk factor for Alzheimer's disease and provides a comprehensive dataset comparing the burden of rare variation in nearly all human genes in Alzheimer's disease cases and controls. This is the first investigation to establish a genome‐wide statistically significant association between multiple extremely rare loss‐of‐function variants in SORL 1 and Alzheimer's disease in a large whole‐exome study of unrelated cases and controls.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".