Association Between the Probability of Autism Spectrum Disorder and Normative Sex-Related Phenotypic Diversity in Brain Structure

Abstract

Importance: Autism spectrum disorder (ASD) is 2 to 5 times more common in male individuals than in female individuals. While the male preponderant prevalence of ASD might partially be explained by sex differences in clinical symptoms, etiological models suggest that the biological male phenotype carries a higher intrinsic risk for ASD than the female phenotype. To our knowledge, this hypothesis has never been tested directly, and the neurobiological mechanisms that modulate ASD risk in male individuals and female individuals remain elusive.

Objectives: To examine the probability of ASD as a function of normative sex-related phenotypic diversity in brain structure and to identify the patterns of sex-related neuroanatomical variability associated with low or high probability of ASD.

Design, setting, and participants: This study examined a cross-sectional sample of 98 right-handed, high-functioning adults with ASD and 98 matched neurotypical control individuals aged 18 to 42 years. A multivariate probabilistic classification approach was used to develop a predictive model of biological sex based on cortical thickness measures assessed via magnetic resonance imaging in neurotypical controls. This normative model was subsequently applied to individuals with ASD. The study dates were June 2005 to October 2009, and this analysis was conducted between June 2015 and July 2016.

Main outcomes and measures: Sample and population ASD probability estimates as a function of normative sex-related diversity in brain structure, as well as neuroanatomical patterns associated with low or high ASD probability in male individuals and female individuals.

Results: Among the 98 individuals with ASD, 49 were male and 49 female, with a mean (SD) age of 26.88 (7.18) years. Among the 98 controls, 51 were male and 47 female, with a mean (SD) age of 27.39 (6.44) years. The sample probability of ASD increased significantly with predictive probabilities for the male neuroanatomical brain phenotype. For example, biological female individuals with a more male-typic pattern of brain anatomy were significantly (ie, 3 times) more likely to have ASD than biological female individuals with a characteristically female brain phenotype (P = .72 vs .24, respectively; χ21 = 20.26; P < .001; difference in P values, 0.48; 95% CI, 0.29-0.68). This finding translates to an estimated variability in population prevalence from 0.2% to 1.3%, respectively. Moreover, the patterns of neuroanatomical variability carrying low or high ASD probability were sex specific (eg, in inferior temporal regions, where ASD has different neurobiological underpinnings in male individuals and female individuals).

Conclusions and relevance: These findings highlight the need for considering normative sex-related phenotypic diversity when determining an individual's risk for ASD and provide important novel insights into the neurobiological mechanisms mediating sex differences in ASD prevalence.

Figure 1.. Gaussian Process Classification of Biological Sex

A, Gaussian process classification between male and female typically developing (TD) control individuals based on normative (ie, neurotypical) variability in cortical thickness. The x-axis indicates predictive class probabilities. Therefore, a class probability of 0.5 served as a binary cutoff separating male individuals from female individuals. The y-axis indicates the position of each individual on the normative axis of sex-related phenotypic diversity in brain structure (lower panel). The upper panel shows the density (ie, frequency) of male individuals and female individuals along the normative axis of class probabilities. B, Probabilistic predictions for male individuals and female individuals with autism spectrum disorder (ASD) using the normative model for biological sex. The density functions for male individuals and female individuals with ASD (upper panel) show the phenotypic shift of the brain in female individuals with ASD toward a more male phenotypic presentation. Of 49 female individuals with ASD, 39 (79.6%) fell within the category of phenotypic male individuals (lower panel).

Figure 2.. Neuroanatomical Patterns Associated With Low and High Autism Spectrum Disorder (ASD) Probability

Predictive maps (ie, w × CT) associated with low and high probability of ASD in female individuals (A) and male individuals (B). Low ASD probability maps were computed across all male individuals (or female individuals) with predictive probabilities lower than 0.5 (ie, biological male individuals or female individuals falling into the category of phenotypic female individuals). High ASD probability maps were computed across all male individuals (or female individuals) with predictive probabilities larger than 0.5 (ie, biological male individuals or female individuals falling into the category of phenotypic male individuals). At each vertex, the color scale thus indicates the product of the weight vector w and cortical thickness (CT), averaged across all individuals within the 4 probability groups. The probability of ASD was determined as the number of male individuals (or female individuals) with ASD relative to the total number of individuals within predictive probability bins.

Figure 3.. Significant Group × Sex Interactions

A, Clusters with significant group × sex interactions in cortical thickness (CT) as examined by a conventional general linear model–type approach. In these regions, the difference in CT between female individuals with autism spectrum disorder (ASD) and female control individuals significantly exceeded the difference between male individuals with ASD and male controls (statistical details are available in eTable 4 in the Supplement). The group × sex interactions were driven by reduced CT in female individuals with ASD relative to female controls and increased CT in male individuals with ASD relative to male controls (eFigure 6 in the Supplement). B, Clusters with significantly increased CT in male individuals with ASD relative to male controls (random field theory–based, cluster-corrected P < .05). C, Clusters with significantly reduced CT in female individuals with ASD relative to female controls (random field theory–based, cluster-corrected P < .05). eFigure 5 in the Supplement shows results of the permutation-based cluster thresholding of the same contrasts. TD indicates typically developing.