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BACKGROUND: In early development autism can be stratified into subtypes differentiated by non-core language, intellectual, motor, and adaptive functioning features. In toddlerhood, these subtypes show different genomic patterning effects on brain structure and function that follow early primary axes of neurodevelopmental organization. This leads to the hypothesis that early cortical patterning differences may continue to be evident between subtypes in later development within hierarchical organization along the sensorimotor-association (S-A) axis. METHODS: Standardized phenotypic measures from the National Institute of Mental Health Data Archive (NDA; n=419) were used in unsupervised data-driven clustering analyses to build a phenotypic stratification model based on language, intellectual, and adaptive functioning (LIAF) features. This stratification model was then applied to independent multi-site resting state fMRI (rsfMRI) datasets (autism n=174; typically-developing (TD) n = 185) to test for subtype differences in global functional connectivity. Mass univariate and multivariate patterning analyses were used to test for differences between TD and autism subtypes. RESULTS: Clustering revealed 2 phenotypically distinct autism subtypes (high versus low) in late childhood to adulthood that generalize in independent data with 92% accuracy. Autism was associated with hyper-connectivity in association areas alongside hypo-connectivity in sensorimotor areas. However, these differences were most pronounced in the TD versus autism low LIAF group comparison and resemble patterning effects that follow the S-A axis. CONCLUSIONS: These findings suggest that cortical patterning of global functional connectivity along the S-A axis is different in autism relative to TD and may be relatively more pronounced in autism with low LIAF features.
Severino et al. (Mon,) studied this question.