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Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants
Published on: February 21, 2015
Diagnostic yield and copy number variants findings in 219 adult patients with developmental and epileptic
Laura Licchetta1,2, Giulia Bruschi3, Tania Giangregorio4
1IRCCS Istituto Delle Scienze Neurologiche di Bologna, full member of European Reference Network EpiCARE, Bologna, Italy.
Abstract:
In a clinical setting, exome sequencing (ES) with copy number variant (CNV) analysis is currently the most effective approach for developmental and epileptic encephalopathies (DEE). However, trio-based ES is often not feasible in adults, its costs remain prohibitive in certain health care settings, and computational tools for CNV calling still lack sufficient accuracy. Chromosomal microarray (CMA) is indicated as a first-tier test for CNV detection in patients with DEE, dysmorphisms, and comorbidities. We investigate the role of CNVs in the etiology of DEE in an adult cohort, to define the most appropriate diagnostic approach in this population. A total of 219 patients (male/female: 104/115) with undiagnosed DEE underwent array-based comparative genomic hybridization/single nucleotide polymorphism arrays as adults. Causative CNVs were identified in 18 patients (8.2%); 14 were deletions (mean size ≈ 2.96 Mb), and four were duplications/triplications (mean size ≈ 3.63 Mb). Thirteen were responsible for known deletion/microduplication syndromes, and four were deletions involving haploinsufficient genes associated with epilepsy/neurodevelopmental disorders. For one deletion, population evidence, reports with overlapping deletions, and clinical databases support a likely pathogenic role. The mean age at CMA diagnosis was 32.4 ± 13 years. An additional 46 patients (21%) then received a molecular diagnosis through alternative approaches. Despite a diagnostic delay of 24.2 ± 14.5 years, CMA enabled a genetic diagnosis in 8.2% of our adult DEE patients, especially in those with dysmorphisms. The diagnostic yield rises to 10.4% when excluding patients diagnosed using other methods. A total of 66.7% of solved cases had direct implications from the diagnosis, supporting the clinical utility of CNV analysis inclusion in the diagnostic workflow for adult patients with DEE.
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