EEG Endophenotypes in Autism Spectrum Disorder
Objectives: The purpose of the study was to identify the presence of epilepsy and EEG abnormalities among youth with well-characterized ASD in order to determine the relationship between epileptiform discharges and specific disease-associated impairments in ASD.
Methods: Data was collected from medical records of patients at Cincinnati Children’s Hospital Medical Center, ages 2 years to 6 years, with well-characterized ASD. These patients were sub-divided into four groups: ASD/abnormal EEG, ASD/normal EEG, ASD/no EEG, and ASD/epilepsy. Phenotypic data was collected, including cognitive and behavioral measures (Mullen Scales of Infant Development, Stanford-Binet, Vineland Adaptive Behavior Scales, Child Behavior Checklist), language testing (Preschool Language Scales), ADOS scores, birth and developmental history, medications, and medical comorbidities. EEG data was abstracted from reports and included presence, characterization, and localization of abnormalities.
Results: We now report on data from an initial group of 534 consecutively treated patients with ASD drawn from a larger 3,800 subject data set. From this initial group, analysis was carried out on 168 patients with ASD who had an EEG. Thirty-seven (24.5%) had an abnormal EEG and no history of seizures. Of these, 17 (46%) were epileptiform. Patients with epilepsy exhibited higher scores on the Anxious/Depressed subscale of the CBCL compared to the other patient groups, which reached statistical significance when compared to patients with abnormal EEGs (p=0.01). Patients with abnormal EEGs exhibited NVIQ scores 14 points lower than patients with normal EEGs on the Stanford-Binet. Although differences were not statistically significant, significance may be attained with larger sample size. For these two groups, a sample size of 45 in each group will have 80% power to detect a difference in means of 15.0 in NVIQ with a standard deviation of 25.0 using a two group t-test with a 0.050 two-sided significance level, yielding an effect size of 0.4. Patients with epilepsy performed worse on all IQ measures on the Stanford-Binet compared to the abnormal EEG group. Though the differences were not statistically significant, significance may be attained with larger sample size. For these two groups, a sample size of 26 in each group will have 80% power to detect a difference in means of 19.3 with a standard deviation of 24.0 using a two group t-test with a 0.05 two-sided significance level, yielding an effect size of 0.8. Based on our identified sample size, we are confident that we will have the power to detect a significant difference between groups.
Conclusions: Preliminary analysis suggests that the presence of an abnormal EEG or epilepsy in the setting of ASD confers worse cognitive and behavioral outcomes. Further analysis will further help to clarify these associations and may offer insight into treatment for this sub-population.