Prediction of Neurodevelopment in Infants With Tuberous Sclerosis Complex Using Early EEG Characteristics
Tuberous Sclerosis Complex (TSC) is a multisystem genetic disorder with a high risk of early-onset epilepsy and a high prevalence of neurodevelopmental comorbidities, including intellectual disability and autism spectrum disorder (ASD). Therefore, TSC is an interesting disease model to investigate e...
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Format: | Article |
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Frontiers Media S.A.
2020-10-01
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Series: | Frontiers in Neurology |
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Online Access: | https://www.frontiersin.org/article/10.3389/fneur.2020.582891/full |
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record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jessie De Ridder Mario Lavanga Birgit Verhelle Jan Vervisch Katrien Lemmens Katarzyna Kotulska Romina Moavero Romina Moavero Paolo Curatolo Bernhard Weschke Kate Riney Kate Riney Martha Feucht Pavel Krsek Rima Nabbout Anna C. Jansen Konrad Wojdan Konrad Wojdan Dorota Domanska-Pakieła Magdalena Kaczorowska-Frontczak Christoph Hertzberg Cyrille H. Ferrier Sharon Samueli Barbora Benova Eleonora Aronica Eleonora Aronica David J. Kwiatkowski Floor E. Jansen Sergiusz Jóźwiak Sergiusz Jóźwiak Sabine Van Huffel Lieven Lagae |
spellingShingle |
Jessie De Ridder Mario Lavanga Birgit Verhelle Jan Vervisch Katrien Lemmens Katarzyna Kotulska Romina Moavero Romina Moavero Paolo Curatolo Bernhard Weschke Kate Riney Kate Riney Martha Feucht Pavel Krsek Rima Nabbout Anna C. Jansen Konrad Wojdan Konrad Wojdan Dorota Domanska-Pakieła Magdalena Kaczorowska-Frontczak Christoph Hertzberg Cyrille H. Ferrier Sharon Samueli Barbora Benova Eleonora Aronica Eleonora Aronica David J. Kwiatkowski Floor E. Jansen Sergiusz Jóźwiak Sergiusz Jóźwiak Sabine Van Huffel Lieven Lagae Prediction of Neurodevelopment in Infants With Tuberous Sclerosis Complex Using Early EEG Characteristics Frontiers in Neurology tuberous sclerosis complex (TSC) EEG biomarker neurodeveloment autism (ASD) TAND profile |
author_facet |
Jessie De Ridder Mario Lavanga Birgit Verhelle Jan Vervisch Katrien Lemmens Katarzyna Kotulska Romina Moavero Romina Moavero Paolo Curatolo Bernhard Weschke Kate Riney Kate Riney Martha Feucht Pavel Krsek Rima Nabbout Anna C. Jansen Konrad Wojdan Konrad Wojdan Dorota Domanska-Pakieła Magdalena Kaczorowska-Frontczak Christoph Hertzberg Cyrille H. Ferrier Sharon Samueli Barbora Benova Eleonora Aronica Eleonora Aronica David J. Kwiatkowski Floor E. Jansen Sergiusz Jóźwiak Sergiusz Jóźwiak Sabine Van Huffel Lieven Lagae |
author_sort |
Jessie De Ridder |
title |
Prediction of Neurodevelopment in Infants With Tuberous Sclerosis Complex Using Early EEG Characteristics |
title_short |
Prediction of Neurodevelopment in Infants With Tuberous Sclerosis Complex Using Early EEG Characteristics |
title_full |
Prediction of Neurodevelopment in Infants With Tuberous Sclerosis Complex Using Early EEG Characteristics |
title_fullStr |
Prediction of Neurodevelopment in Infants With Tuberous Sclerosis Complex Using Early EEG Characteristics |
title_full_unstemmed |
Prediction of Neurodevelopment in Infants With Tuberous Sclerosis Complex Using Early EEG Characteristics |
title_sort |
prediction of neurodevelopment in infants with tuberous sclerosis complex using early eeg characteristics |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Neurology |
issn |
1664-2295 |
publishDate |
2020-10-01 |
description |
Tuberous Sclerosis Complex (TSC) is a multisystem genetic disorder with a high risk of early-onset epilepsy and a high prevalence of neurodevelopmental comorbidities, including intellectual disability and autism spectrum disorder (ASD). Therefore, TSC is an interesting disease model to investigate early biomarkers of neurodevelopmental comorbidities when interventions are favourable. We investigated whether early EEG characteristics can be used to predict neurodevelopment in infants with TSC. The first recorded EEG of 64 infants with TSC, enrolled in the international prospective EPISTOP trial (recorded at a median gestational age 42 4/7 weeks) was first visually assessed. EEG characteristics were correlated with ASD risk based on the ADOS-2 score, and cognitive, language, and motor developmental quotients (Bayley Scales of Infant and Toddler Development III) at the age of 24 months. Quantitative EEG analysis was used to validate the relationship between EEG background abnormalities and ASD risk. An abnormal first EEG (OR = 4.1, p-value = 0.027) and more specifically a dysmature EEG background (OR = 4.6, p-value = 0.017) was associated with a higher probability of ASD traits at the age of 24 months. This association between an early abnormal EEG and ASD risk remained significant in a multivariable model, adjusting for mutation and treatment (adjusted OR = 4.2, p-value = 0.029). A dysmature EEG background was also associated with lower cognitive (p-value = 0.029), language (p-value = 0.001), and motor (p-value = 0.017) developmental quotients at the age of 24 months. Our findings suggest that early EEG characteristics in newborns and infants with TSC can be used to predict neurodevelopmental comorbidities. |
topic |
tuberous sclerosis complex (TSC) EEG biomarker neurodeveloment autism (ASD) TAND profile |
url |
https://www.frontiersin.org/article/10.3389/fneur.2020.582891/full |
work_keys_str_mv |
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doaj-5e5b31c5c880467a8726961a4a17973e2020-11-25T03:41:11ZengFrontiers Media S.A.Frontiers in Neurology1664-22952020-10-011110.3389/fneur.2020.582891582891Prediction of Neurodevelopment in Infants With Tuberous Sclerosis Complex Using Early EEG CharacteristicsJessie De Ridder0Mario Lavanga1Birgit Verhelle2Jan Vervisch3Katrien Lemmens4Katarzyna Kotulska5Romina Moavero6Romina Moavero7Paolo Curatolo8Bernhard Weschke9Kate Riney10Kate Riney11Martha Feucht12Pavel Krsek13Rima Nabbout14Anna C. Jansen15Konrad Wojdan16Konrad Wojdan17Dorota Domanska-Pakieła18Magdalena Kaczorowska-Frontczak19Christoph Hertzberg20Cyrille H. Ferrier21Sharon Samueli22Barbora Benova23Eleonora Aronica24Eleonora Aronica25David J. Kwiatkowski26Floor E. Jansen27Sergiusz Jóźwiak28Sergiusz Jóźwiak29Sabine Van Huffel30Lieven Lagae31Pediatric Neurology, Department of Development and Regeneration, University of Leuven KU Leuven, Leuven, BelgiumDepartment of Electrical Engineering (ESAT), STADIUS Centre for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, BelgiumPediatric Neurology, Department of Development and Regeneration, University of Leuven KU Leuven, Leuven, BelgiumPediatric Neurology, Department of Development and Regeneration, University of Leuven KU Leuven, Leuven, BelgiumPediatric Neurology, Department of Development and Regeneration, University of Leuven KU Leuven, Leuven, BelgiumDepartment of Neurology and Epileptology, The Children's Memorial Health Institute, Warsaw, PolandChild Neurology and Psychiatry Unit, Systems Medicine Department, Tor Vergata University, Rome, ItalyChild Neurology Unit, Neuroscience and Neurorehabilitation Department, “Bambino Gesù” Children's Hospital, Rome, ItalyChild Neurology and Psychiatry Unit, Systems Medicine Department, Tor Vergata University, Rome, ItalyDepartment of Child Neurology, Charité University Medicine Berlin, Berlin, GermanyNeuroscience Unit, Queensland Children's Hospital, Brisbane, QLD, AustraliaUniversity of Queensland School of Clinical Medicine, Brisbane, QLD, AustraliaDepartment of Pediatrics, Medical University Vienna, Vienna, Austria0Department of Paediatric Neurology, Charles University, Second Faculty of Medicine, Motol University Hospital, Prague, Czechia1Department of Pediatric Neurology, Reference Centre for Rare Epilepsies, Imagine Institute, Necker- Enfants Malades Hospital, University Paris Descartes, Paris, France2Pediatric Neurology Unit, Universitair Ziekenhuis Brussel, Brussels, Belgium3Transition Technologies, Warsaw, Poland4Institute of Heat Engineering, Warsaw University and Technology, Warsaw, PolandDepartment of Neurology and Epileptology, The Children's Memorial Health Institute, Warsaw, PolandDepartment of Neurology and Epileptology, The Children's Memorial Health Institute, Warsaw, Poland5Diagnose und Behandlungszentrum für Kinder und Jugendliche, Vivantes Klinikum Neuköln, Berlin, Germany6Department of Child Neurology, Brain Centre, University Medical Centre Utrecht, Utrecht, NetherlandsDepartment of Pediatrics, Medical University Vienna, Vienna, Austria0Department of Paediatric Neurology, Charles University, Second Faculty of Medicine, Motol University Hospital, Prague, Czechia7Department of (Neuro)Pathology, Amsterdam Universitair Medisch Centrum, University of Amsterdam, Amsterdam, Netherlands8Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, Netherlands9Harvard Medical School, Brigham and Women's Hospital, Boston, MA, United States6Department of Child Neurology, Brain Centre, University Medical Centre Utrecht, Utrecht, NetherlandsDepartment of Neurology and Epileptology, The Children's Memorial Health Institute, Warsaw, Poland0Department of Child Neurology, Medical University of Warsaw, Warsaw, PolandDepartment of Electrical Engineering (ESAT), STADIUS Centre for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, BelgiumPediatric Neurology, Department of Development and Regeneration, University of Leuven KU Leuven, Leuven, BelgiumTuberous Sclerosis Complex (TSC) is a multisystem genetic disorder with a high risk of early-onset epilepsy and a high prevalence of neurodevelopmental comorbidities, including intellectual disability and autism spectrum disorder (ASD). Therefore, TSC is an interesting disease model to investigate early biomarkers of neurodevelopmental comorbidities when interventions are favourable. We investigated whether early EEG characteristics can be used to predict neurodevelopment in infants with TSC. The first recorded EEG of 64 infants with TSC, enrolled in the international prospective EPISTOP trial (recorded at a median gestational age 42 4/7 weeks) was first visually assessed. EEG characteristics were correlated with ASD risk based on the ADOS-2 score, and cognitive, language, and motor developmental quotients (Bayley Scales of Infant and Toddler Development III) at the age of 24 months. Quantitative EEG analysis was used to validate the relationship between EEG background abnormalities and ASD risk. An abnormal first EEG (OR = 4.1, p-value = 0.027) and more specifically a dysmature EEG background (OR = 4.6, p-value = 0.017) was associated with a higher probability of ASD traits at the age of 24 months. This association between an early abnormal EEG and ASD risk remained significant in a multivariable model, adjusting for mutation and treatment (adjusted OR = 4.2, p-value = 0.029). A dysmature EEG background was also associated with lower cognitive (p-value = 0.029), language (p-value = 0.001), and motor (p-value = 0.017) developmental quotients at the age of 24 months. Our findings suggest that early EEG characteristics in newborns and infants with TSC can be used to predict neurodevelopmental comorbidities.https://www.frontiersin.org/article/10.3389/fneur.2020.582891/fulltuberous sclerosis complex (TSC)EEGbiomarkerneurodevelomentautism (ASD)TAND profile |