Parsing brain structural heterogeneity in males with autism spectrum disorder reveals distinct clinical subtypes

Abstract

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with considerable neuroanatomical heterogeneity. Thus, how and to what extent the brains of individuals with ASD differ from each other is still unclear. In this study, brain structural MRI data from 356 right-handed, male subjects with ASD and 403 right-handed male healthy controls were selected from the Autism Brain Image Data Exchange database (age range 5-35 years old). Voxel-based morphometry preprocessing steps were conducted to compute the gray matter volume maps for each subject. Individual neuroanatomical difference patterns for each ASD individual were calculated. A data-driven clustering method was next utilized to stratify individuals with ASD into several subtypes. Whole-brain functional connectivity and clinical severity were compared among individuals within the ASD subtypes identified. A searchlight analysis was applied to determine whether subtyping ASD could improve the classification accuracy between ASD and healthy controls. Three ASD subtypes with distinct neuroanatomical difference patterns were revealed. Different degrees of clinical severity and atypical brain functional connectivity patterns were observed among these three subtypes. By dividing ASD into three subtypes, the classification accuracy between subjects of two out of the three subtypes and healthy controls was improved. The current study confirms that ASD is not a disorder with a uniform neuroanatomical signature. Understanding neuroanatomical heterogeneity in ASD could help to explain divergent patterns of clinical severity and outcomes.

Keywords: autism spectrum disorder; data-driven; neuroanatomical heterogeneity; searchlight classification.

Figure 1

Data analysis flowchart analysis flowchart. (a) For each subject, a VBM map was calculated. For each ASD subject, 20 HC subjects who were most matched with the corresponding ASD subject were selected (see Methods: Structural difference map). In panel a, HC subjects with the same color with ASD subjects were selected as the most matched HC subjects. (b) For each ASD subject, a structural difference map was calculated. Then the structural difference maps were divided into positive and negative (see Methods: Structural difference map). (c) A non‐negative matrix factorization (NMF) method was used to reduce the feature dimensions. Red cells represent the coefficients of positive components and blue cells represent the coefficients of negative components. (d) The coefficients corresponding to the NMF components of each subject were used as features in cluster analyses (see Methods: Cluster analysis). (e) Subsequent analyses compared the behavior and brain functional traits of ASD subtypes (see Methods: Clinical severity and neuroanatomical subtypes of ASD and methods: Functional connectivity and neuroanatomical subtypes of ASD), and explored the advantages of subtyping ASD to classify ASD and HC based on the neuroanatomical images (see Method: Classification between subtypes of ASD and HC) [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 2

Distinct neuroanatomical difference patterns across three ASD subtypes. (a) Force‐directed graph of all ASD subjects created using d3.Js (https://d3js.org/). Green nodes represent ASD subjects belonging to subtype1; blue nodes represent ASD subjects belonging to subtype2; red nodes represent ASD subjects belonging to subtype3. Details of the force‐directed graph construction are in Supporting Information. (b) One‐sample t‐test of the neuroanatomical difference maps of each ASD subtype. Green box represents subtype1; blue box represents subtype2; red box represent subtype3 [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 3

Different clinical symptom severity across three ASD subtypes. Mean ADOS scores for each ASD subtype. Error bars represent the standard error of the ADOS scores for each ASD subtype. * represents significant differences (two‐sample t‐test, p < .05) [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 4

Different atypical functional connectivity patterns across three ASD subtypes. (a) Different atypical functional connectivity patterns between HC and ASD subtypes. Blue cells in the functional connectivity matrix represent the connectivity of ASD subtype, which is lower than HCs. The nodes in the brain maps represent the ROIs located in different sub‐networks: Red nodes represent ROIs in default mode network; yellow nodes represent ROIs in fronto‐parietal network; green nodes represent ROIs in cingulo‐opercular network; blue nodes represent ROIs in sensori‐motor network and purple nodes represent ROIs in occipital network. We found no FC clusters showing significant differences between ASD subtype2 and HC. (b) Local efficiency among three ASD subtypes. Red stars represent significant differences found at corresponding cost. Error bars represent the standard error [Color figure can be viewed at http://wileyonlinelibrary.com]