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Prediction of Neurodevelopment in Infants With Tuberous Sclerosis Complex Using Early EEG Characteristics
Jessie De Ridder1, Mario Lavanga2, Birgit Verhelle1
1Pediatric Neurology, Department of Development and Regeneration, University of Leuven KU Leuven, Leuven, Belgium.
Insights
Early EEG patterns in infants with Tuberous Sclerosis Complex (TSC) can predict autism spectrum disorder (ASD) risk and developmental delays. Abnormal or dysmature EEG backgrounds are linked to higher ASD probability and lower cognitive, language, and motor development.
Area of Science:
- Neuroscience
- Genetics
- Developmental Pediatrics
Background:
- Tuberous Sclerosis Complex (TSC) is a genetic disorder associated with significant neurodevelopmental challenges.
- Early identification of neurodevelopmental comorbidities in TSC is crucial for timely interventions.
Purpose of the Study:
- To investigate if early electroencephalogram (EEG) characteristics in infants with TSC can predict neurodevelopmental outcomes.
- To assess the association between EEG findings and the risk of autism spectrum disorder (ASD) and developmental quotients.
Main Methods:
- Visual assessment of the first EEG in 64 infants with TSC from the EPISTOP trial.
- Correlation of EEG characteristics with ASD risk (ADOS-2) and developmental quotients (Bayley Scales III) at 24 months.
- Quantitative EEG analysis to validate findings.
Main Results:
- An abnormal or dysmature EEG background in infancy was significantly associated with a higher probability of ASD traits at 24 months.
- This association remained significant after adjusting for mutation and treatment.
- A dysmature EEG background also correlated with lower cognitive, language, and motor developmental quotients.
Conclusions:
- Early EEG characteristics in infants with TSC serve as potential predictors for neurodevelopmental comorbidities.
- EEG analysis offers a valuable tool for early risk stratification in TSC for conditions like ASD and developmental delays.
Abstract:
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.
