Pathogenic variants in the neuronal sodium channel α1 subunit gene (SCN1A) are the most frequent monogenic cause of epilepsy. Phenotypes comprise a wide clinical spectrum, including severe childhood epilepsy; Dravet syndrome, characterized by drug-resistant seizures, intellectual disability, and high mortality; and the milder genetic epilepsy with febrile seizures plus (GEFS+), characterized by normal cognition. Early recognition of a child's risk for developing Dravet syndrome vs GEFS+ is key for implementing disease-modifying therapies when available before cognitive impairment emerges. Our objective was to develop and validate a prediction model using clinical and genetic biomarkers for early diagnosis of SCN1A-related epilepsies.

Development and Validation of a Prediction Model for Early Diagnosis of SCN1A-Related Epilepsies / Andreas Brunklaus , Eduardo Pérez-Palma , Ismael Ghanty , Ji Xinge , Eva Brilstra , Berten Ceulemans , Nicole Chemaly , Iris de Lange , Christel Depienne , Renzo Guerrini , Davide Mei , Rikke S Møller , Rima Nabbout , Brigid M Regan , Amy L Schneider , Ingrid E Scheffer , An-Sofie Schoonjans , Joseph D Symonds , Sarah Weckhuysen , Michael W Kattan , Sameer M Zuberi , Dennis Lal. - In: NEUROLOGY. - ISSN 0028-3878. - ELETTRONICO. - (2022), pp. 1163-1174. [10.1212/WNL.0000000000200028]

Development and Validation of a Prediction Model for Early Diagnosis of SCN1A-Related Epilepsies

Renzo Guerrini;
2022

Abstract

Pathogenic variants in the neuronal sodium channel α1 subunit gene (SCN1A) are the most frequent monogenic cause of epilepsy. Phenotypes comprise a wide clinical spectrum, including severe childhood epilepsy; Dravet syndrome, characterized by drug-resistant seizures, intellectual disability, and high mortality; and the milder genetic epilepsy with febrile seizures plus (GEFS+), characterized by normal cognition. Early recognition of a child's risk for developing Dravet syndrome vs GEFS+ is key for implementing disease-modifying therapies when available before cognitive impairment emerges. Our objective was to develop and validate a prediction model using clinical and genetic biomarkers for early diagnosis of SCN1A-related epilepsies.
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Andreas Brunklaus , Eduardo Pérez-Palma , Ismael Ghanty , Ji Xinge , Eva Brilstra , Berten Ceulemans , Nicole Chemaly , Iris de Lange , Christel Depienne , Renzo Guerrini , Davide Mei , Rikke S Møller , Rima Nabbout , Brigid M Regan , Amy L Schneider , Ingrid E Scheffer , An-Sofie Schoonjans , Joseph D Symonds , Sarah Weckhuysen , Michael W Kattan , Sameer M Zuberi , Dennis Lal
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2158/1280422
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