Use of longitudinal EEG measures in estimating language development in infants with and without familial risk for autism spectrum disorder

Abstract

Language development in children with autism spectrum disorder (ASD) varies greatly among affected individuals and is a strong predictor of later outcomes. Younger siblings of children with ASD have increased risk of ASD, but also language delay. Identifying neural markers of language outcomes in infant siblings could facilitate earlier intervention and improved outcomes. This study aimed to determine whether EEG measures from the first 2-years of life can explain heterogeneity in language development in children at low- and high-risk for ASD, and to determine whether associations between EEG measures and language development are different depending on ASD risk status or later ASD diagnosis. In this prospective longitudinal study EEG measures collected between 3-24 months were used in a multivariate linear regression model to estimate participants' 24-month language development. Individual baseline longitudinal EEG measures included (1) the slope of EEG power across 3-12 months or 3-24 months of life for 6 canonical frequency bands, (2) estimated EEG power at age 6-months for the same frequency bands, and (3) terms representing the interaction between ASD risk status and EEG power measures. Modeled 24-month language scores using EEG data from either the first 2-years (Pearson R = 0.70, 95% CI 0.595-0.783, P=1x10^-18) or the first year of life (Pearson R=0.66, 95% CI 0.540-0.761, P=2.5x10^-14) were highly correlated with observed scores. All models included significant interaction effects of risk on EEG measures, suggesting that EEG-language associations are different depending on risk status, and that different brain mechanisms effect language development in low-versus high-risk infants.

Figure 1.

Developmental trajectories of frontal electroencephalography (EEG) power across multiple frequency bands from 3 to 24 months. Longitudinal trajectories of log 10 transformed absolute frontal EEG power across six frequency bands for individuals from low-risk (LR; green, n = 58), high-risk without ASD (HR-NoASD; orange, n = 51), and high-risk with ASD (HR-ASD; blue, n = 21) are shown. Both individual and mean trajectories by group are shown. Shaded regions represent the 95% confidence interval.

Figure 2.

Correlations of observed and model estimated verbal developmental quotient (VDQ). Observed and estimated Mullen Scales for Early Learning VDQ for each model. Adjusted models include sex and parental education as covariates. Regression line shown represents estimate based on all individuals included in the model. Each data point is colored based on the independent variable included in the model (Models 1 and 2 = risk status; Model 3 = ASD diagnosis).