Exploring Sex Differences in Autism Spectrum Disorder in the Charge Study

Saturday, May 13, 2017: 12:00 PM-1:40 PM
Golden Gate Ballroom (Marriott Marquis Hotel)
M. White1, C. W. Nordahl2, K. Angkustsiri3, R. Hansen4, D. Harvey5, I. Hertz-Picciotto6 and D. J. Tancredi7, (1)Pediatrics, UC Davis, Sacramento, CA, (2)Department of Psychiatry & Behavioral Sciences, University of California-Davis, Sacramento, CA, (3)University of California at Davis, Sacramento, CA, (4)UCD MIND Institute, Sacramento, CA, (5)Public Health Sciences, Division of Biostatistics, UC Davis, Davis, CA, (6)University of California at Davis, Davis, CA, (7)UC Davis School of Medicine, Sacramento, CA
Background:  Autism spectrum disorder (ASD) is more prevalent in males than females. Understanding the phenotypic differences between males and females may allow for insight into the etiology of ASD, which could guide sex specific screening, diagnostic and treatment pathways.

Objectives:  To evaluate sex differences in developmental and adaptive function of young children with autism spectrum disorder (ASD)

Methods: The Childhood Autism Risk from Genetics and the Environment (CHARGE) study is an ongoing, population-based case-control study. Participants include children ages 2-5 years old with ASD and typically developing (TD) controls. TD children were age and location matched using birth certificate data.

For this analysis, all children who met criteria for ASD based on the Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) and Autism Diagnostic Interview – Revised (ADI-R) were included. Any child with a known genetic syndrome was excluded.

We evaluated developmental and adaptive function in 724 children with ASD (612 M, 112 F) and 482 TD controls (397 M, 85 F) with a mean age of 44.1 months. Chi-square tests, ANOVA or logistic regression were used to evaluate differences in baseline demographics. T-tests, ANOVA, or Chi-square tests were used to assess differences in autism characteristics, including age at diagnosis, ADOS-2 comparison score, ADI-R scores and percentage of children enrolled in services. A 2X2 factorial ANOVA was used to estimate the interaction between diagnosis and sex for developmental and adaptive measures.

Results:  There were no significant sex by diagnosis interactions in demographics. However, age at clinic visit and maternal education were both approaching significance. On further analysis, there was a main effect of diagnosis on both age (TDs younger, p=.005) and maternal education (TDs with more educated mothers, p=.01). Autism characteristics did not differ between males and females. As the outcome measures are standardized for age, only maternal education was used as a covariate in the following analyses. On the MSEL, there was a main effect of sex on visual reception (p=.01), receptive language (p=.02), expressive language (p=.02), fine motor (p=.003), and the early learning composite (p=.04) with females scoring higher than males in both ASD and TD groups. There were no significant sex by diagnosis interactions on the MSEL. On the VABS, there was a main effect of sex on communication (p=.02), daily living skills (p=.01), socialization (p=.03), and the composite (p=.02). There were also significant sex by diagnosis interactions in daily living skills (p=.001), socialization (p=.04), and the composite (p=.009). TD females tended to score higher than TD males, while males and females with ASD had similar adaptive skills.

Conclusions:  Females scored higher than males in all aspects of developmental functioning in this sample, regardless of whether they were ASD or TD. However, only TD females outscored their male counterparts in adaptive skills. Therefore, a developmental advantage does not translate into superior adaptive functioning in females with ASD in this sample.