Diagnostic Classification for Human Autism and Obsessive-Compulsive Disorder Based on Machine Learning From a Primate Genetic Model | |
Zhan, Yafeng1,2; Wei, Jianze3,4; Liang, Jian4; Xu, Xiu5; He, Ran4; Robbins, Trevor W.6,7; Wang, Zheng1,2,8,9 | |
发表期刊 | AMERICAN JOURNAL OF PSYCHIATRY |
ISSN | 0002-953X |
2021 | |
卷号 | 178期号:1页码:65-76 |
摘要 | Objective: Psychiatric disorders commonly comprise comorbid symptoms, such as autism spectrum disorder (ASD), obsessive-compulsive disorder (OCD), and attention deficit hyperactivity disorder (ADHD), raising controversies over accurate diagnosis and overlap of their neural underpinnings. The authors used non invasive neuroimaging in humans and nonhuman primates to identify neural markers associated with DSM-5 diagnoses and quantitative measures of symptom severity. Methods: Resting-state functional connectivity data obtained from both wild-type and methyl-CpG binding protein 2 (MECP2) transgenic monkeys were used to construct monkey-derived classifiers for diagnostic classification in four human data sets (ASD: Autism Brain Imaging Data Exchange [ABIDE-I], N=1,112; ABIDE-II, N=1,114; ADHD-200 sample: N=776; OCD local institutional database: N=186). Stepwise linear regression models were applied to examine associations between functional connections of monkey-derived classifiers and dimensional symptom severity of psychiatric disorders. Results: Nine core regions prominently distributed in frontal and temporal cortices were identified in monkeys and used as seeds to construct the monkey-derived classifier that informed diagnostic classification in human autism. This same set of core regions was useful for diagnostic classification in the OCD cohort but not the ADHD cohort. Models based on functional connections of the right ventrolateral prefrontal cortex with the left thalamus and right prefrontal polar cortex predicted communication scores of ASD patients and compulsivity scores of OCD patients, respectively. Conclusions: The identified core regions may serve as a basis for building markers for ASD and OCD diagnoses, as well as measures of symptom severity. These findings may inform future development of machine-learning models for psychiatric disorders and may improve the accuracy and speed of clinical assessments. |
DOI | 10.1176/appi.ajp.2020.19101091 |
关键词[WOS] | SPECTRUM DISORDERS ; BRAIN ; ANXIETY ; BEHAVIOR ; CONNECTIVITY ; IMPULSIVITY ; REGRESSION ; SELECTION ; SYMPTOMS ; CHILDREN |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key R&D Program of China[2017YFC1310400] ; National Key R&D Program of China[2018YFC1313803] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB32030000] ; Shanghai Municipal Science and Technology Major Project[2018SHZDZX05] ; National Natural Science Foundation[81571300] ; National Natural Science Foundation[81527901] ; National Natural Science Foundation[31771174] ; Key Realm R&D Program of Guangdong Province[2019B030335001] ; Wellcome Trust[104631/Z/12/Z] |
项目资助者 | National Key R&D Program of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Shanghai Municipal Science and Technology Major Project ; National Natural Science Foundation ; Key Realm R&D Program of Guangdong Province ; Wellcome Trust |
WOS研究方向 | Psychiatry |
WOS类目 | Psychiatry |
WOS记录号 | WOS:000604750700010 |
出版者 | AMER PSYCHIATRIC PUBLISHING, INC |
七大方向——子方向分类 | 机器学习 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/42570 |
专题 | 智能感知与计算研究中心 |
通讯作者 | He, Ran; Wang, Zheng |
作者单位 | 1.Chinese Acad Sci, State Key Lab Neurosci, Key Lab Primate Neurobiol, Inst Neurosci,Ctr Excellence Brain Sci & Intellig, Shanghai, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 4.Chinese Acad Sci, Inst Automat, Ctr Excellence Brain Sci & Intelligence Technol, Natl Lab Pattern Recognit, Beijing, Peoples R China 5.Fudan Univ, Dept Child Hlth Care, Childrens Hosp, Shanghai, Peoples R China 6.Univ Cambridge, Dept Psychol, Behav & Clin Neurosci Inst, Cambridge, England 7.Fudan Univ, Inst Sci & Technol Brain Inspired Intelligence, Shanghai, Peoples R China 8.Shanghai Ctr Brain Sci & Brain Inspired Intellige, Shanghai, Peoples R China 9.Chinese Acad Sci, Kunming Inst Zool, Kunming, Yunnan, Peoples R China |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Zhan, Yafeng,Wei, Jianze,Liang, Jian,et al. Diagnostic Classification for Human Autism and Obsessive-Compulsive Disorder Based on Machine Learning From a Primate Genetic Model[J]. AMERICAN JOURNAL OF PSYCHIATRY,2021,178(1):65-76. |
APA | Zhan, Yafeng.,Wei, Jianze.,Liang, Jian.,Xu, Xiu.,He, Ran.,...&Wang, Zheng.(2021).Diagnostic Classification for Human Autism and Obsessive-Compulsive Disorder Based on Machine Learning From a Primate Genetic Model.AMERICAN JOURNAL OF PSYCHIATRY,178(1),65-76. |
MLA | Zhan, Yafeng,et al."Diagnostic Classification for Human Autism and Obsessive-Compulsive Disorder Based on Machine Learning From a Primate Genetic Model".AMERICAN JOURNAL OF PSYCHIATRY 178.1(2021):65-76. |
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