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.
| Original language | English (US) |
|---|---|
| Journal | Human Brain Mapping |
| DOIs | |
| State | Accepted/In press - Jan 1 2018 |
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Keywords
- autism spectrum disorder
- data-driven
- neuroanatomical heterogeneity
- searchlight classification
ASJC Scopus subject areas
- Anatomy
- Radiological and Ultrasound Technology
- Radiology Nuclear Medicine and imaging
- Neurology
- Clinical Neurology
Cite this
Parsing brain structural heterogeneity in males with autism spectrum disorder reveals distinct clinical subtypes. / Chen, Heng; Uddin, Lucina Q; Guo, Xiaonan; Wang, Jia; Wang, Runshi; Wang, Xiaomin; Duan, Xujun; Chen, Huafu.
In: Human Brain Mapping, 01.01.2018.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Parsing brain structural heterogeneity in males with autism spectrum disorder reveals distinct clinical subtypes
AU - Chen, Heng
AU - Uddin, Lucina Q
AU - Guo, Xiaonan
AU - Wang, Jia
AU - Wang, Runshi
AU - Wang, Xiaomin
AU - Duan, Xujun
AU - Chen, Huafu
PY - 2018/1/1
Y1 - 2018/1/1
N2 - 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.
AB - 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.
KW - autism spectrum disorder
KW - data-driven
KW - neuroanatomical heterogeneity
KW - searchlight classification
UR - http://www.scopus.com/inward/record.url?scp=85053764060&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85053764060&partnerID=8YFLogxK
U2 - 10.1002/hbm.24400
DO - 10.1002/hbm.24400
M3 - Article
C2 - 30251763
AN - SCOPUS:85053764060
JO - Human Brain Mapping
JF - Human Brain Mapping
SN - 1065-9471
ER -