Demographic and Clinical Correlates of Proposed DSM-5 Autism Symptom Domains and Diagnosis

Background:  

Understanding the demographic and clinical factors associated with autism symptoms and diagnosis has both conceptual and practical implications relevant to assessment and future research strategies. Specifically, understanding the pattern of autism symptoms across single and multiple incidence families can inform the genetic epidemiology of autism spectrum disorders (ASD). Additionally, distinct patterns of correlates across proposed DSM-5 social communication/interaction (SCI) and restricted/repetitive behavior (RRB) domains may imply the need for separate consideration of symptoms, as opposed to only global symptom severity. Lastly, and most practically, demographic and clinical correlates may be important factors to consider when developing or revising measures. 

Objectives:  

The first aim of this study was to determine the influence of demographic and clinical correlates on SCI and RRB symptoms, before and after accounting for ASD diagnosis. The second aim was to determine whether caregiver-reported SCI and RRB symptoms, considered separately, provided incremental validity in the prediction of ASD diagnosis.

Methods:  

We analyzed data from 7,352 siblings included in the Interactive Autism Network registry. SCI and RRB symptoms were obtained using caregiver-reports on the Social Responsiveness Scale. Demographic and clinical correlates were covariates in separate mixed effects regression models predicting SCI and RRB symptoms. Demographic and clinical correlates included: age, sex, race/ethnicity, birth order, and family type (single vs. multiple incidence), any ADHD, any anxiety disorder, or intellectual disability. The models were estimated with and without ASD diagnosis as an additional covariate to examine whether correlates persisted in influencing SCI and RRB levels even after accounting for ASD diagnosis (aim 1). Logistic regression and receiver operating characteristic curve analyses estimated the incremental validity of SCI and RRB domains over and above global autism symptoms in the prediction of ASD diagnosis (aim 2). 

Results:  

ASD diagnosis was the strongest correlate of caregiver-reported SCI and RRB symptoms. The presence of any ADHD, anxiety disorder, or intellectual disability diagnosis also increased SCI and RRB symptoms, even after accounting for ASD diagnosis. Non-ASD siblings of multiple incidence families had elevated symptom levels. However, ASD-affected siblings from multiple-incidence families had fewer symptoms than ASD-affected siblings from single incidence families. SCI and RRB symptoms provided incremental validity in predicting diagnosis above and beyond global autism symptoms. 

Conclusions:

These findings suggest that ASD diagnosis is by far the largest determinant of quantitatively-measured autism symptoms. Externalizing and internalizing behavior, cognitive disability, and demographic factors may confound caregiver-report of autism symptoms, necessitating a continuous norming approach to the development and revision of symptom measures. SCI and RRB symptoms may provide incremental utility in the screening and diagnosis of ASD. Several alternative explanations for the autism symptom pattern across single and multiple incidence families should be considered, including rater effects and the possibility of unique mixture of genomic mechanisms across these family types. Future studies using blinded clinician ratings are needed to tease apart these alternatives. Additional studies replicating the pattern of clinical correlates and examining the incremental validity of SCI and RRB symptoms are needed to enhance the screening and diagnosis of ASD.