Partial microduplication in the histone acetyltransferase complex member KANSL1 is associated with congenital heart defects in 22q11.2 microdeletion syndrome patients
Bibliographic record
Abstract
22q11.2 microdeletion syndrome (22q11.2DS) is the most common microdeletion disorder in humans, with an incidence of 1/4000 live births. It is caused by a heterozygous deletion of 1.5-3 Mb on chromosome region 22q11.2. Patients with the deletion present features that include neuropsychiatric problems, craniofacial abnormalities and cardiovascular malformations. However, the phenotype is highly variable and the factors related to the clinical heterogeneity are not fully understood. About 65% of patients with 22q11.2DS have congenital heart defects (CHD). The main goal of this study was to identify common CNVs in 22q11.2DS patients that could be associated with the incomplete penetrance of CHD. Analysis of genomic DNA from 253 patients with 22q11.2DS using array technology showed an association between a microduplication located in region 17q21.31 and CHD (p-value = 0.023, OR = 2.75, 95% CI = 1.17-7.03). This region includes the first three exons of KANSL1 gene. Bioinformatic analysis showed that KANSL1 and CRKL, a gene in the commonly deleted region of 22q11.2DS, are part of the same regulatory module in a miRNA-mRNA network. These results show that a KANSL1 microduplication, in combination with the 22q11.2 deletion, is associated with increased risk of CHD in these patients, suggesting that KANSL1 plays a role as a modifier gene in 22q11.2DS patients.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 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".