Phenotypic Heterogeneity of Genomic Disorders and Rare Copy-Number Variants
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Some copy-number variants are associated with genomic disorders with extreme phenotypic heterogeneity. The cause of this variation is unknown, which presents challenges in genetic diagnosis, counseling, and management. METHODS: We analyzed the genomes of 2312 children known to carry a copy-number variant associated with intellectual disability and congenital abnormalities, using array comparative genomic hybridization. RESULTS: Among the affected children, 10.1% carried a second large copy-number variant in addition to the primary genetic lesion. We identified seven genomic disorders, each defined by a specific copy-number variant, in which the affected children were more likely to carry multiple copy-number variants than were controls. We found that syndromic disorders could be distinguished from those with extreme phenotypic heterogeneity on the basis of the total number of copy-number variants and whether the variants are inherited or de novo. Children who carried two large copy-number variants of unknown clinical significance were eight times as likely to have developmental delay as were controls (odds ratio, 8.16; 95% confidence interval, 5.33 to 13.07; P=2.11×10(-38)). Among affected children, inherited copy-number variants tended to co-occur with a second-site large copy-number variant (Spearman correlation coefficient, 0.66; P<0.001). Boys were more likely than girls to have disorders of phenotypic heterogeneity (P<0.001), and mothers were more likely than fathers to transmit second-site copy-number variants to their offspring (P=0.02). CONCLUSIONS: Multiple, large copy-number variants, including those of unknown pathogenic significance, compound to result in a severe clinical presentation, and secondary copy-number variants are preferentially transmitted from maternal carriers. (Funded by the Simons Foundation Autism Research Initiative and the National Institutes of Health.).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it