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Large-scale analyses of the relationship between sex, age and intelligence quotient heterogeneity and cortical morphometry in autism spectrum disorder

自闭症谱系障碍 心理学 颞上沟 脑形态计量学 神经影像学 神经科学 自闭症 大脑定位 智商 细胞结构 磁共振成像 临床心理学 发展心理学 功能磁共振成像 医学 认知 放射科
作者
Saashi A. Bedford,Min Tae M Park,Gabriel A. Devenyi,Stéphanie Tullo,Jürgen Germann,Raihaan Patel,Evdokia Anagnostou,Simon Baron‐Cohen,Edward T. Bullmore,Lindsay R. Chura,Michael Craig,Christine Ecker,Dorothea L. Floris,Rosemary Holt,Rhoshel Lenroot,Jason P. Lerch,Michael Lombardo,Declan Murphy,Armin Raznahan,Amber Ruigrok
出处
期刊:Molecular Psychiatry [Springer Nature]
卷期号:25 (3): 614-628 被引量:185
标识
DOI:10.1038/s41380-019-0420-6
摘要

Significant heterogeneity across aetiologies, neurobiology and clinical phenotypes have been observed in individuals with autism spectrum disorder (ASD). Neuroimaging-based neuroanatomical studies of ASD have often reported inconsistent findings which may, in part, be attributable to an insufficient understanding of the relationship between factors influencing clinical heterogeneity and their relationship to brain anatomy. To this end, we performed a large-scale examination of cortical morphometry in ASD, with a specific focus on the impact of three potential sources of heterogeneity: sex, age and full-scale intelligence (FIQ). To examine these potentially subtle relationships, we amassed a large multi-site dataset that was carefully quality controlled (yielding a final sample of 1327 from the initial dataset of 3145 magnetic resonance images; 491 individuals with ASD). Using a meta-analytic technique to account for inter-site differences, we identified greater cortical thickness in individuals with ASD relative to controls, in regions previously implicated in ASD, including the superior temporal gyrus and inferior frontal sulcus. Greater cortical thickness was observed in sex specific regions; further, cortical thickness differences were observed to be greater in younger individuals and in those with lower FIQ, and to be related to overall clinical severity. This work serves as an important step towards parsing factors that influence neuroanatomical heterogeneity in ASD and is a potential step towards establishing individual-specific biomarkers.
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