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Gene panel analysis for nonsyndromic cryptogenic neonatal/infantile epileptic encephalopathy

OBJECTIVE: Epileptic encephalopathy (EE) is a heterogeneous condition associated with deteriorations of cognitive, sensory and/or motor functions as a consequence of epileptic activity. The phenomenon is the most common and severe in infancy and early childhood. Genetic‐based diagnosis in EE patient...

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Autores principales: Fung, Cheuk‐Wing, Kwong, Anna Ka‐Yee, Wong, Virginia Chun‐Nei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5719849/
https://www.ncbi.nlm.nih.gov/pubmed/29588952
http://dx.doi.org/10.1002/epi4.12055
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author Fung, Cheuk‐Wing
Kwong, Anna Ka‐Yee
Wong, Virginia Chun‐Nei
author_facet Fung, Cheuk‐Wing
Kwong, Anna Ka‐Yee
Wong, Virginia Chun‐Nei
author_sort Fung, Cheuk‐Wing
collection PubMed
description OBJECTIVE: Epileptic encephalopathy (EE) is a heterogeneous condition associated with deteriorations of cognitive, sensory and/or motor functions as a consequence of epileptic activity. The phenomenon is the most common and severe in infancy and early childhood. Genetic‐based diagnosis in EE patients is challenging owing to genetic and phenotypic heterogeneity of numerous monogenic disorders and the fact that thousands of genes are involved in neurodevelopment. Therefore, high‐throughput next‐generation sequencing (NGS) was used to investigate the genetic causes of non‐syndromic cryptogenic neonatal/infantile EE (NIEE). METHODS: We have selected a cohort of 31 patients with seizure cryptogenic NIEE and seizure onset before 24 months. All investigations including metabolic work‐up, were negative. Using NGS, we distinguished a panel of 430 epilepsy‐associated genes by NGS was utilized to identify possible pathogenic variants in the patients. Segregation analysis and multiple silico analysis prediction tools were used for pathogenicity assessment. The identified variants were classified as “pathogenic,” “likely pathogenic” and “uncertain significance,” according to the American College of Medical Genetics (ACMG) guidelines. RESULTS: Pathogenic or likely pathogenic variants were identified in six genes (ALG13 [1], CDKL5 [2], KCNQ2 [2], PNPO [1], SCN8A [1], SLC9A6 [2]) in 9 NIEE patients (9/31; 29%). Variants of uncertain significance (VUS) were found in DNM1 and TUBA8 in 2 NIEE patients (2/31; 6%). Most phenotypes in our cohort matched with those reported cases. SIGNIFICANCE: The diagnostic rate (29%) of pathogenic and likely pathogenic variants was comparable to the recent studies of early‐onset epileptic encephalopathy, indicating that gene panel analysis through NGS is a powerful tool to investigate cryptogenic NIEE in patients. Six percent of patients had neurometabolic disorders. Some of our diagnosed cases illustrated that successful molecular investigation may allow a better treatment strategy and avoid unnecessary and even invasive investigations. Functional analysis could be performed to further study the pathogenicity of the VUS identified in DNM1 and TUBA8.
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spelling pubmed-57198492018-03-27 Gene panel analysis for nonsyndromic cryptogenic neonatal/infantile epileptic encephalopathy Fung, Cheuk‐Wing Kwong, Anna Ka‐Yee Wong, Virginia Chun‐Nei Epilepsia Open Full‐length Original Research OBJECTIVE: Epileptic encephalopathy (EE) is a heterogeneous condition associated with deteriorations of cognitive, sensory and/or motor functions as a consequence of epileptic activity. The phenomenon is the most common and severe in infancy and early childhood. Genetic‐based diagnosis in EE patients is challenging owing to genetic and phenotypic heterogeneity of numerous monogenic disorders and the fact that thousands of genes are involved in neurodevelopment. Therefore, high‐throughput next‐generation sequencing (NGS) was used to investigate the genetic causes of non‐syndromic cryptogenic neonatal/infantile EE (NIEE). METHODS: We have selected a cohort of 31 patients with seizure cryptogenic NIEE and seizure onset before 24 months. All investigations including metabolic work‐up, were negative. Using NGS, we distinguished a panel of 430 epilepsy‐associated genes by NGS was utilized to identify possible pathogenic variants in the patients. Segregation analysis and multiple silico analysis prediction tools were used for pathogenicity assessment. The identified variants were classified as “pathogenic,” “likely pathogenic” and “uncertain significance,” according to the American College of Medical Genetics (ACMG) guidelines. RESULTS: Pathogenic or likely pathogenic variants were identified in six genes (ALG13 [1], CDKL5 [2], KCNQ2 [2], PNPO [1], SCN8A [1], SLC9A6 [2]) in 9 NIEE patients (9/31; 29%). Variants of uncertain significance (VUS) were found in DNM1 and TUBA8 in 2 NIEE patients (2/31; 6%). Most phenotypes in our cohort matched with those reported cases. SIGNIFICANCE: The diagnostic rate (29%) of pathogenic and likely pathogenic variants was comparable to the recent studies of early‐onset epileptic encephalopathy, indicating that gene panel analysis through NGS is a powerful tool to investigate cryptogenic NIEE in patients. Six percent of patients had neurometabolic disorders. Some of our diagnosed cases illustrated that successful molecular investigation may allow a better treatment strategy and avoid unnecessary and even invasive investigations. Functional analysis could be performed to further study the pathogenicity of the VUS identified in DNM1 and TUBA8. John Wiley and Sons Inc. 2017-05-04 /pmc/articles/PMC5719849/ /pubmed/29588952 http://dx.doi.org/10.1002/epi4.12055 Text en © 2017 The Authors. Epilepsia Open published by Wiley Periodicals Inc. on behalf of International League Against Epilepsy. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs (http://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Full‐length Original Research
Fung, Cheuk‐Wing
Kwong, Anna Ka‐Yee
Wong, Virginia Chun‐Nei
Gene panel analysis for nonsyndromic cryptogenic neonatal/infantile epileptic encephalopathy
title Gene panel analysis for nonsyndromic cryptogenic neonatal/infantile epileptic encephalopathy
title_full Gene panel analysis for nonsyndromic cryptogenic neonatal/infantile epileptic encephalopathy
title_fullStr Gene panel analysis for nonsyndromic cryptogenic neonatal/infantile epileptic encephalopathy
title_full_unstemmed Gene panel analysis for nonsyndromic cryptogenic neonatal/infantile epileptic encephalopathy
title_short Gene panel analysis for nonsyndromic cryptogenic neonatal/infantile epileptic encephalopathy
title_sort gene panel analysis for nonsyndromic cryptogenic neonatal/infantile epileptic encephalopathy
topic Full‐length Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5719849/
https://www.ncbi.nlm.nih.gov/pubmed/29588952
http://dx.doi.org/10.1002/epi4.12055
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