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The relevance of transdiagnostic shared networks to the severity of symptoms and cognitive deficits in schizophrenia: a multimodal brain imaging fusion study
Qi, Shile1; Bustillo, Juan2; Turner, Jessica A.1,3; Jiang, Rongtao4,5,6; Zhi, Dongmei4,5,6; Fu, Zening1; Deramus, Thomas P.1; Vergara, Victor1; Ma, Xiaohong7,8,9; Yang, Xiao7,8,9; Stevens, Mike10; Zhuo, Chuanjun11; Xu, Yong12; Calhoun, Vince D.1,3; Sui, Jing4,5,6,13
Source PublicationTRANSLATIONAL PSYCHIATRY
ISSN2158-3188
2020-05-18
Volume10Issue:1Pages:10
Abstract

Schizophrenia (SZ) is frequently concurrent with substance use, depressive symptoms, social communication and attention deficits. However, the relationship between common brain networks (e.g., SZ vs. substance use, SZ vs. depression, SZ vs. developmental disorders) with SZ on specific symptoms and cognition is unclear. Symptom scores were used as a reference to guide fMRI-sMRI fusion for SZ (n=94), substance use with drinking (n=313), smoking (n=104), major depressive disorder (MDD, n=260), developmental disorders with autism spectrum disorder (ASD, n=421) and attention-deficit/hyperactivity disorder (ADHD, n=244) respectively. Common brain regions were determined by overlapping the symptom-related components between SZ and these other groups. Correlation between the identified common brain regions and cognition/symptoms in an independent SZ dataset (n=144) was also performed. Results show that (1): substance use was related with cognitive deficits in schizophrenia through gray matter volume (GMV) in anterior cingulate cortex and thalamus; (2) depression was linked to PANSS negative dimensions and reasoning in SZ through a network involving caudate-thalamus-middle/inferior temporal gyrus in GMV; (3) developmental disorders pattern was correlated with poor attention, speed of processing and reasoning in SZ through inferior temporal gyrus in GMV. This study reveals symptom driven transdiagnostic shared networks between SZ and other mental disorders via multi-group data mining, indicating that some potential common underlying brain networks associated with schizophrenia differently with respect to symptoms and cognition. These results have heuristic value and advocate specific approaches to refine available treatment strategies for comorbid conditions in schizophrenia.

Keywordschizophrenia multimodal fusion
DOI10.1038/s41398-020-0834-6
WOS KeywordMAJOR PSYCHIATRIC-DISORDERS ; ONSET SCHIZOPHRENIA ; COMORBIDITIES ; CONNECTIVITY ; IDENTIFICATION ; CANNABIS ; ALCOHOL ; AUTISM ; VOLUME ; RISK
Indexed BySCI
Language英语
Funding ProjectStrategic Priority Research Program of the Chinese Academy of Sciences[XDBS32040100] ; China Natural Science Foundation[61773380] ; Beijing Municipal Science and Technology Commission[Z181100001518005] ; National Institute of Health[1R01MH117107] ; National Institute of Health[R01EB020407] ; National Institute of Health[R01MH118695] ; National Institute of Health[1R01EB005846] ; National Institute of Health[1R01MH094524] ; National Institute of Health[P20GM103472] ; National Institute of Health[P30GM122734] ; National Science Foundation[1539067]
Funding OrganizationStrategic Priority Research Program of the Chinese Academy of Sciences ; China Natural Science Foundation ; Beijing Municipal Science and Technology Commission ; National Institute of Health ; National Science Foundation
WOS Research AreaPsychiatry
WOS SubjectPsychiatry
WOS IDWOS:000536853000001
PublisherNATURE PUBLISHING GROUP
Sub direction classification医学影像处理与分析
Citation statistics
Cited Times:6[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/39533
Collection脑网络组研究
Corresponding AuthorCalhoun, Vince D.; Sui, Jing
Affiliation1.Emory Univ, Georgia State Univ, Georgia Inst Technol, Triinst Ctr Translat Res Neuroimaging & Data Sci, Atlanta, GA 30303 USA
2.Univ New Mexico, Dept Psychiat, Albuquerque, NM 87131 USA
3.Georgia State Univ, Dept Psychol, Atlanta, GA 30302 USA
4.Chinese Acad Sci, Brainnetome Ctr, Inst Automat, Beijing 100190, Peoples R China
5.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
6.Univ Chinese Acad Sci, Beijing 100190, Peoples R China
7.Sichuan Univ, West China Hosp, Psychiat Lab, Chengdu 610041, Peoples R China
8.Sichuan Univ, West China Hosp, State Key Lab Biotherapy, Mental Hlth Ctr, Chengdu 610041, Peoples R China
9.Sichuan Univ, West China Hosp, Huaxi Brain Res Ctr, Chengdu 610041, Peoples R China
10.Olin Neuropsychiat Res Ctr, Hartford, CT 06106 USA
11.Nankai Univ, Affiliated Anding Hosp, Dept Psychiat, Tianjin 300222, Peoples R China
12.Shanxi Med Univ, Dept Humanities & Social Sci, Taiyuan 030001, Peoples R China
13.Chinese Acad Sci, Inst Automat, Ctr Excellence Brain Sci, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China;  Institute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Qi, Shile,Bustillo, Juan,Turner, Jessica A.,et al. The relevance of transdiagnostic shared networks to the severity of symptoms and cognitive deficits in schizophrenia: a multimodal brain imaging fusion study[J]. TRANSLATIONAL PSYCHIATRY,2020,10(1):10.
APA Qi, Shile.,Bustillo, Juan.,Turner, Jessica A..,Jiang, Rongtao.,Zhi, Dongmei.,...&Sui, Jing.(2020).The relevance of transdiagnostic shared networks to the severity of symptoms and cognitive deficits in schizophrenia: a multimodal brain imaging fusion study.TRANSLATIONAL PSYCHIATRY,10(1),10.
MLA Qi, Shile,et al."The relevance of transdiagnostic shared networks to the severity of symptoms and cognitive deficits in schizophrenia: a multimodal brain imaging fusion study".TRANSLATIONAL PSYCHIATRY 10.1(2020):10.
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