Universität zu Köln

Brunklaus, Andreas ORCID: 0000-0002-7728-6903, Perez-Palma, Eduardo, Ghanty, Ismael, Xinge, Ji, Brilstra, Eva, Ceulemans, Berten ORCID: 0000-0001-7818-0679, Chemaly, Nicole, de Lange, Iris, Depienne, Christel ORCID: 0000-0002-7212-9554, Guerrini, Renzo ORCID: 0000-0002-7272-7079, Mei, Davide, Moller, Rikke S. ORCID: 0000-0002-9664-1448, Nabbout, Rima, Regan, Brigid M., Schneider, Amy L., Scheffer, Ingrid E., Schoonjans, An-Sofie, Symonds, Joseph D., Weckhuysen, Sarah ORCID: 0000-0003-2878-1147, Kattan, Michael W., Zuberi, Sameer M. and Lal, Dennis (2022). Development and Validation of a Prediction Model for Early Diagnosis of SCN1A-Related Epilepsies. Neurology, 98 (11). S. E1163 - 12. PHILADELPHIA: LIPPINCOTT WILLIAMS & WILKINS. ISSN 1526-632X

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Abstract

Background and Objectives Pathogenic variants in the neuronal sodium channel alpha 1 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. Methods We performed a retrospective multicenter cohort study comprising data from patients with SCN1A-positive Dravet syndrome and patients with GEFS+ consecutively referred for genetic testing (March 2001-June 2020) including age at seizure onset and a newly developed SCN1A genetic score. A training cohort was used to develop multiple prediction models that were validated using 2 independent blinded cohorts. Primary outcome was the discriminative accuracy of the model predicting Dravet syndrome vs other GEFS+ phenotypes. Results A total of 1,018 participants were included. The frequency of Dravet syndrome was 616/743 (83%) in the training cohort, 147/203 (72%) in validation cohort 1, and 60/72 (83%) in validation cohort 2. A high SCN1A genetic score (133.4 [SD 78.5] vs 52.0 [SD 57.5]; p < 0.001) and young age at onset (6.0 [SD 3.0] vs 14.8 [SD 11.8] months; p < 0.001) were each associated with Dravet syndrome vs GEFS+. A combined SCN1A genetic score and seizure onset model separated Dravet syndrome from GEFS+ more effectively (area under the curve [AUC] 0.89 [95% CI 0.86-0.92]) and outperformed all other models (AUC 0.79-0.85; p < 0.001). Model performance was replicated in both validation cohorts 1 (AUC 0.94 [95% CI 0.91-0.97]) and 2 (AUC 0.92 [95% CI 0.82-1.00]). Discussion The prediction model allows objective estimation at disease onset whether a child will develop Dravet syndrome vs GEFS+, assisting clinicians with prognostic counseling and decisions on early institution of precision therapies (http://scn1a-prediction-modelbroadinstitute.org/). Classification of Evidence This study provides Class II evidence that a combined SCN1A genetic score and seizure onset model distinguishes Dravet syndrome from other GEFS+ phenotypes.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Brunklaus, Andreas UNSPECIFIED orcid.org/0000-0002-7728-6903 UNSPECIFIED Perez-Palma, Eduardo UNSPECIFIED UNSPECIFIED UNSPECIFIED Ghanty, Ismael UNSPECIFIED UNSPECIFIED UNSPECIFIED Xinge, Ji UNSPECIFIED UNSPECIFIED UNSPECIFIED Brilstra, Eva UNSPECIFIED UNSPECIFIED UNSPECIFIED Ceulemans, Berten UNSPECIFIED orcid.org/0000-0001-7818-0679 UNSPECIFIED Chemaly, Nicole UNSPECIFIED UNSPECIFIED UNSPECIFIED de Lange, Iris UNSPECIFIED UNSPECIFIED UNSPECIFIED Depienne, Christel UNSPECIFIED orcid.org/0000-0002-7212-9554 UNSPECIFIED Guerrini, Renzo UNSPECIFIED orcid.org/0000-0002-7272-7079 UNSPECIFIED Mei, Davide UNSPECIFIED UNSPECIFIED UNSPECIFIED Moller, Rikke S. UNSPECIFIED orcid.org/0000-0002-9664-1448 UNSPECIFIED Nabbout, Rima UNSPECIFIED UNSPECIFIED UNSPECIFIED Regan, Brigid M. UNSPECIFIED UNSPECIFIED UNSPECIFIED Schneider, Amy L. UNSPECIFIED UNSPECIFIED UNSPECIFIED Scheffer, Ingrid E. UNSPECIFIED UNSPECIFIED UNSPECIFIED Schoonjans, An-Sofie UNSPECIFIED UNSPECIFIED UNSPECIFIED Symonds, Joseph D. UNSPECIFIED UNSPECIFIED UNSPECIFIED Weckhuysen, Sarah UNSPECIFIED orcid.org/0000-0003-2878-1147 UNSPECIFIED Kattan, Michael W. UNSPECIFIED UNSPECIFIED UNSPECIFIED Zuberi, Sameer M. UNSPECIFIED UNSPECIFIED UNSPECIFIED Lal, Dennis UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-696377
DOI:	10.1212/WNL.0000000000200028
Journal or Publication Title:	Neurology
Volume:	98
Number:	11
Page Range:	S. E1163 - 12
Date:	2022
Publisher:	LIPPINCOTT WILLIAMS & WILKINS
Place of Publication:	PHILADELPHIA
ISSN:	1526-632X
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language SEIZURES; PHENOTYPES Multiple languages Clinical Neurology Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/69637