Understanding the Nature of Face Processing in Early Autism: A Prospective Study

• Published in: Journal of psychopathology and clinical science 2022-08, Vol.131 (6), p.542-555
• Main Authors: Tye, Charlotte, Bussu, Giorgia, Gliga, Teodora, Elsabbagh, Mayada, Pasco, Greg, Johnsen, Kristinn, Charman, Tony, Jones, Emily J. H., Buitelaar, Jan, Johnson, Mark H.
• Format: Article
• Language: English
• Subjects: Autism; Autism Spectrum Disorder - diagnosis; Autism Spectrum Disorders; Autistic Disorder; Bayes Theorem; Bayesian analysis; Clustering; Convergence; Diagnosis; Event-related potentials; Evoked Potentials; Face Perception; Facial Recognition; Female; First year; Human; Humans; Individual Differences; Infancy; Infant; Infants; Machine Learning; Male; Medical diagnosis; Neurocognition; Neurodevelopmental disorders; Pattern recognition; Phenotypes; Prospective Studies; Psychopathology; Special Section: Integrating Development Into the Research Domain Criteria (RDoC); Stratification; Understanding
• ISSN: 2769-7541; 2769-755X; 2769-755X
• DOI: 10.1037/abn0000648

Dimensional approaches to psychopathology interrogate the core neurocognitive domains interacting at the individual level to shape diagnostic symptoms. Embedding this approach in prospective longitudinal studies could transform our understanding of the mechanisms underlying neurodevelopmental disorders. Such designs require us to move beyond traditional group comparisons and determine which domain-specific alterations apply at the level of the individual, and whether they vary across distinct phenotypic subgroups. As a proof of principle, this study examines how the domain of face processing contributes to the emergence of autism spectrum disorder (ASD). We used an event-related potentials (ERPs) task in a cohort of 8-month-old infants with (n = 148) and without (n = 68) an older sibling with ASD, and combined traditional case-control comparisons with machine-learning techniques for prediction of social traits and ASD diagnosis at 36 months, and Bayesian hierarchical clustering for stratification into subgroups. A broad profile of alterations in the time-course of neural processing of faces in infancy was predictive of later ASD, with a strong convergence in ERP features predicting social traits and diagnosis. We identified two main subgroups in ASD, defined by distinct patterns of neural responses to faces, which differed on later sensory sensitivity. Taken together, our findings suggest that individual differences between infants contribute to the diffuse pattern of alterations predictive of ASD in the first year of life. Moving from group-level comparisons to pattern recognition and stratification can help to understand and reduce heterogeneity in clinical cohorts, and improve our understanding of the mechanisms that lead to later neurodevelopmental outcomes. General Scientific Summary This study suggests that neural processing of faces is diffusely atypical in autism spectrum disorder, and that it represents a strong candidate predictor of later social skills and diagnosis at an individual level in the first year of life. Furthermore, a subgroup of infants developing ASD showed reduced neural responses to faces in infancy but increased sensory sensitivity in toddlerhood.