Intragenic CNVs for epigenetic regulatory genes in intellectual disability: Survey identifies pathogenic and benign single exon changes
Bibliographic record
Abstract
The disruption of genes involved in epigenetic regulation is well known to cause Intellectual Disability (ID). We reported a custom microarray study that interrogated among others, the epigenetic regulatory gene-class, at single exon resolution. Here we elaborate on identified intragenic CNVs involving epigenetic regulatory genes; specifically discussing those in three genes previously unreported in ID etiology-ARID2, KDM3A, and ARID4B. The changes in ARID2 and KDM3A are likely pathogenic while the ARID4B variant is uncertain. Previously, we found a CNV involving only exon 6 of the JARID2 gene occurred apparently de novo in seven patients. JARID2 is known to cause ID and other neurodevelopmental conditions. However, exon 6 of this gene encodes one of a series of repeated motifs. We therefore, investigated the impact of this variant in two cohorts and present a genotype-phenotype assessment. We find the JARID2 exon 6 CNV is benign, with a high population frequency (>14%), but nevertheless could have a contributory effect. We also present results from an interrogation of the exomes of 2,044 patients with neurocognitive phenotypes for the incidence of potentially damaging mutation in the epigenetic regulatory gene-class. This paper provides a survey of the fine-scale CNV landscape for epigenetic regulatory genes in the context of ID, describing likely pathogenic as well as benign single exon imbalances. © 2016 Wiley Periodicals, Inc.
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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 | 0.003 | 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) | 0.002 | 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".