MG-127 Diagnostic accuracy of chromosome microarray in children with epilepsy and neurological abnormalities of unknown aetiology
Bibliographic record
Abstract
<h3>Background</h3> Chromosome MicroArray-based genomic copy-number analysis (CMA) has an important role in the discovery of both novel and recurrent epilepsy-associated copy number variants (CNVs) in patients with epilepsy. In case of an additional neuro-developmental disorder the diagnostic accuracy may be as high as 15%. <h3>Objectives</h3> The purpose of this study is to describe the results of performed CMA on 706 children with unexplained epilepsy associated with developmental delay/intellectual disability, autism spectrum disorders and/or multiple congenital anomalies (‘epilepsy plus’). <h3>Design/method</h3> Retrospective chart review on clinical and genetic aspects of CNVs identified in 706 patients with ‘epilepsy plus’, seen at the Vancouver BC Children’s Hospital from 2009 to 2014. All patients had CMA performed using Affymetrix Genome-Wide Human SNP Array 6.0 or CytoScanHD®. <h3>Results</h3> Abnormal CMA results were identified in 191 out of 706 children with ‘epilepsy plus’. 122/706 (17.3%) patients had variants of unknown significance (VUS), and 80/706 (11.3%) patients had pathogenic CNVs. This group included 19 patients that had CNVs in genomic “hotspots” predisposing to epilepsy, including 1q21.1 (n = 1), 15q11.2 (n = 2), 15q13.3 (n = 4), 15q11-q13 (n = 3), 16p11.2 (n = 1046), and 16p13.11 (n = 3). Among other known microdeletion/microduplication syndromes (n = 20) was 22q13.3 deletion (Phelan-McDermid Syndrome) (n = 4). One of the four 22q13.3 deletion patients had treatment resistant epilepsy and a small deletion (47kb) of the SHANK3 gene. <h3>Conclusions</h3> CMA revealed pathogenic CNVs in epilepsy “hotspots”, and known microdeletion syndromes like Phelan-McDermid syndrome in 11.3% of children with ‘epilepsy plus’. Examination of CNVs also plays an important role in the identification of possible epilepsy genes i.g. SHANK3 mutations in patients with 22q13.3 deletions.
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How this classification was reachedexpand
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 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".