Recurrent duplications of the annexin A1 gene (ANXA1) in autism spectrum disorders
Bibliographic record
Abstract
BACKGROUND: Validating the potential pathogenicity of copy number variants (CNVs) identified in genome-wide studies of autism spectrum disorders (ASD) requires detailed assessment of case/control frequencies, inheritance patterns, clinical correlations, and functional impact. Here, we characterize a small recurrent duplication in the annexin A1 (ANXA1) gene, identified by the Autism Genome Project (AGP) study. METHODS: From the AGP CNV genomic screen in 2,147 ASD individuals, we selected for characterization an ANXA1 gene duplication that was absent in 4,964 population-based controls. We further screened the duplication in a follow-up sample including 1,496 patients and 410 controls, and evaluated clinical correlations and family segregation. Sequencing of exonic/downstream ANXA1 regions was performed in 490 ASD patients for identification of additional variants. RESULTS: The ANXA1 duplication, overlapping the last four exons and 3'UTR region, had an overall prevalence of 11/3,643 (0.30%) in unrelated ASD patients but was not identified in 5,374 controls. Duplication carriers presented no distinctive clinical phenotype. Family analysis showed neuropsychiatric deficits and ASD traits in multiple relatives carrying the duplication, suggestive of a complex genetic inheritance. Sequencing of exonic regions and the 3'UTR identified 11 novel changes, but no obvious variants with clinical significance. CONCLUSIONS: We provide multilevel evidence for a role of ANXA1 in ASD etiology. Given its important role as mediator of glucocorticoid function in a wide variety of brain processes, including neuroprotection, apoptosis, and control of the neuroendocrine system, the results add ANXA1 to the growing list of rare candidate genetic etiological factors for ASD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".