Copy number variation in fetal alcohol spectrum disorder
Bibliographic record
Abstract
Fetal alcohol spectrum disorder (FASD) is characterized by a combination of neurological, developmental, and congenital defects that may occur as a consequence of prenatal alcohol exposure. Earlier reports showed that large chromosomal anomalies may link to FASD. Here, we examined the prevalence and types of copy number variations (CNVs) in FASD cases previously diagnosed by a multidisciplinary FASD team in sites across Canada. We genotyped 95 children with FASD and 87 age-matched, typically developing controls on the Illumina Human Omni2.5 SNP (single nucleotide polymorphisms) array platform. We compared their CNVs with those of 10 851 population controls to identify rare CNVs (<0.1% frequency), which may include large unbalanced chromosomal abnormalities, that might be relevant to FASD. In 12/95 (13%) of the FASD cases, rare CNVs were found that impact potentially clinically relevant developmental genes, including the CACNA1H involved in epilepsy and autism, the 3q29 deletion disorder, and others. Our results show that a subset of children diagnosed with FASD have chromosomal deletions and duplications that may co-occur or explain the neurodevelopmental impairments in a diagnosed cohort of FASD individuals. Children suspected to have FASD with or without sentinel facial features of fetal alcohol syndrome and neurodevelopmental delays should potentially be evaluated by a clinical geneticist and possibly have genetic investigations as appropriate to exclude other etiologies.
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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 | 0.000 | 0.000 |
| 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".