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Title: Diagnostic implications of genetic copy number variation in epilepsy plus
Summary Objective

Copy number variations (CNVs) represent a significant genetic risk for several neurodevelopmental disorders including epilepsy. As knowledge increases, reanalysis of existing data is essential. Reliable estimates of the contribution ofCNVs to epilepsies from sizeable populations are not available.

Methods

We assembled a cohort of 1255 patients with preexisting array comparative genomic hybridization or single nucleotide polymorphism array basedCNVdata. All patients had “epilepsy plus,” defined as epilepsy with comorbid features, including intellectual disability, psychiatric symptoms, and other neurological and nonneurological features.CNVclassification was conducted using a systematic filtering workflow adapted to epilepsy.

Results

Of 1097 patients remaining after genetic data quality control, 120 individuals (10.9%) carried at least one autosomalCNVclassified as pathogenic; 19 individuals (1.7%) carried at least one autosomalCNVclassified as possibly pathogenic. Eleven patients (1%) carried more than one (possibly) pathogenicCNV. We identifiedCNVs covering recently reported (HNRNPU)or emerging (RORB) epilepsy genes, and further delineated the phenotype associated with mutations of these genes. Additional novel epilepsy candidate genes emerge from our study. Comparing phenotypic features of pathogenicCNVcarriers to those of noncarriers of pathogenicCNVs, we show that patients with nonneurological comorbidities, especially dysmorphism, were more likely to carry pathogenicCNVs (odds ratio = 4.09, confidence interval = 2.51‐6.68;P = 2.34 × 10−9). Meta‐analysis including data from published control groups showed that the presence or absence of epilepsy did not affect the detected frequency ofCNVs.

Significance

The use of a specifically adapted workflow enabled identification of pathogenic autosomalCNVs in 10.9% of patients with epilepsy plus, which rose to 12.7% when we also considered possibly pathogenicCNVs. Our data indicate that epilepsy with comorbid features should be considered an indication for patients to be selected for a diagnostic algorithm includingCNVdetection. Collaborative large‐scaleCNVreanalysis leads to novel declaration of pathogenicity in unexplained cases and can promote discovery of promising candidate epilepsy genes.

 
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NSF-PAR ID:
10459991
Author(s) / Creator(s):
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Publisher / Repository:
Wiley-Blackwell
Date Published:
Journal Name:
Epilepsia
Volume:
60
Issue:
4
ISSN:
0013-9580
Page Range / eLocation ID:
p. 689-706
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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