Investigating Phenotypic Heterogeneity in Children with Autism Spectrum Disorder: A Factor Mixture Modelling Approach

Background: Autism Spectrum Disorder (ASD) is a complex disorder characterized by notable phenotypic heterogeneity, which is often viewed as an obstacle to the study of its etiology, diagnosis, treatment and outcomes.  Until recently researchers have debated whether ASD should be conceptualized as categorical or as dimensional to better capture this heterogeneity. However, it is possible that a complementary model that integrates categorical and dimensional elements might be the best approach in delineating the ASD symptom phenotype.

Objectives: The current study uses the novel method of Factor Mixture Modelling (FMM) that allows for the integration of categories and dimensions, to stratify children with ASD into homogeneous sub-groups, based on their scores on the symptom dimensions of Social Communication Deficits (SCD) and Fixated Interests and Repetitive Behaviours (FIRB).  

Methods: The study sample consisted of 391 newly-diagnosed children (mean age 38.3 months; 330 males) participating in a longitudinal study of ASD developmental trajectories. Data from the Autism Diagnostic Interview-Revised indexing the SCD and FIRB symptom dimensions were used in Factor Mixture Modeling to derive subgroups of children. 

Results: Competing models were fit to the data and tested using a set of goodness-of-fit criteria. Results showed that a “2-factor/3-class” factor mixture model provided the best fit to the data. This model describes ASD using three subgroups/classes (Class 1: 34%, Class 2: 10%, Class 3: 56% of the sample) based on differential severity gradients on the SCD and FIRB symptom dimensions. Children within these subgroups were diagnosed at different mean ages and were functioning at different mean adaptive, language, and cognitive levels.

Conclusions: Factor Mixture Modeling is a useful method for understanding the phenotypic structure of a complex, heterogeneous disorder such as ASD. Study findings suggest that the two symptom severity dimensions of SCD and FIRB proposed for the DSM 5 can be used to stratify preschool children with ASD empirically into three homogeneous subgroups. Clinical and research implications are discussed.