Identifying Language and Cognitive Profiles in Children With ASD via a Cluster Analysis Exploration
on the February 6, 2020
Collaborative research project led by Prof. Laurice Tuller
Identifying Language and Cognitive Profiles in Children With ASD via a Cluster Analysis Exploration: Implications for the New ICD-11
Abstract
The new version of the International Classification of Diseases (ICD-11) mentions the existence of four different profiles in the verbal part of the Autism Spectrum Disorder (ASD), describing them as combinations of either spared or impaired functional language and intellectual abilities. The aim of the present study was to put ASD heterogeneity to the forefront by exploring whether clear profiles related to language and intellectual abilities emerge when investigation is extended to the entire spectrum, focusing on verbal children. Our study proposed a systematic investigation of both language (specifically, structural language abilities) and intellectual abilities (specifically, nonverbal cognitive abilities) in 51 6- to 12-year-old verbal children with ASD based on explicitly motivated measures. For structural language abilities, sentence repetition and nonword repetition tasks were selected; for nonverbal cognitive abilities, we chose Raven's Progressive Matrices, as well as Matrix Reasoning and Block Design from the Wechsler Scales. An integrative approach based on cluster analyses revealed five distinct profiles. Among these five profiles, all four logically possible combinations of structural language and nonverbal abilities mentioned in the ICD-11 were detected. Three profiles emerged among children with normal language abilities and two emerged among language-impaired children. Crucially, the existence of discrepant profiles of abilities suggests that children with ASD can display impaired language in presence of spared nonverbal intelligence or spared language in the presence of impaired nonverbal intelligence, reinforcing the hypothesis of the existence of a separate language module in the brain. LAY SUMMARY: The present work put Autism Spectrum Disorder heterogeneity to the forefront by exploring whether clear profiles related to language and cognitive abilities emerge when investigation is extended to the entire spectrum (focusing on verbal children). The use of explicitly motivated measures of both language and cognitive abilities and of an unsupervised machine learning approach, the cluster analysis, (a) confirmed the existence of all four logically possible profiles evoked in the new ICD-11, (b) evoked the existence of (at least) a fifth profile of language/cognitive abilities, and (c) reinforced the hypothesis of a language module in the brain. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.
© 2020 International Society for Autism Research, Wiley Periodicals, Inc.
