Exome analysis of 22,319 individuals links extremely rare CNVs and 22q11.21 dosage to Alzheimer’s risk
Bibliographic record
Abstract
Abstract Copy number variants (CNVs), defined as deletions or duplications of genomic segments >100 bp, are major contributors to human disease, yet their role in non-monogenic Alzheimer disease (AD) remains poorly characterized. We analyzed rare CNVs from 22,319 exomes, including 4,150 early-onset AD (EOAD), 8,519 late-onset AD and 9,650 unaffected controls. EOAD cases showed increased burdens of rare CNVs, particularly rare deletions within AD-related genes. Loss-of-function analyses implicated deletions in ABCA1 and ABCA7 and identified CTSB as a candidate locus . Exome-wide gene-level dosage analysis highlighted 18 genes across five loci , including chr22q11.21, where deletions were restricted to EOAD and duplications enriched in controls. Replication in 33,992 cases and 362,305 controls confirmed AD-risk reduction in 22q11.21 duplication carriers (mega-analysis dosage OR(SCARF2)=0.34, p=5.52×10 -7 ). SCARF2 overexpression increased amyloid-β uptake in vitro , supporting a functional link. These findings highlight CNVs as contributors to AD risk and identify 22q11.21 dosage as a strong genetic determinant.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".