Understanding the nature of face processing in early autism: a prospective study

Dimensional approaches to psychopathology interrogate the core neurocognitive domains interactingat the individual level to shape diagnostic symptoms. Embedding this approach in prospective longitudinal studies couldtransform 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 studyexamineshow the domain of face processingcontributes to the emergenceof Autism Spectrum Disorder (ASD). We used an event-related potentials (ERPs) task in a cohort of 8-month-oldinfants with (n=148) and without (n=68) an older sibling withASD, andcombined traditional case-control comparisonswith machine-learningtechniques for prediction of social traits and ASD diagnosisat 36 months,and Bayesian hierarchical clustering for stratification into subgroups. Abroad profile of alterations in the time-course of neural processing of faces in infancy was predictive oflaterASD, with a strong convergence in ERP features predicting social traits and diagnosis.We identified two main subgroups in ASD,defined by distinct patternsof neural responsestofaces,which differed on latersensory sensitivity. Taken together, our findings suggest that individual differences between infantscontribute 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