Cortical thickness distinguishes between major depression and schizophrenia in adolescents

作者全名："Zhou, Zheyi; Wang, Kangcheng; Tang, Jinxiang; Wei, Dongtao; Song, Li; Peng, Yadong; Fu, Yixiao; Qiu, Jiang"

作者地址："[Zhou, Zheyi; Wei, Dongtao; Song, Li; Qiu, Jiang] Minist Educ, Key Lab Cognit & Personal SWU, Chongqing 400715, Peoples R China; [Zhou, Zheyi; Wei, Dongtao; Song, Li; Qiu, Jiang] Southwest Univ, Fac Psychol, 2 Tiansheng Rd, Chongqing 400715, Peoples R China; [Wang, Kangcheng] Shandong Normal Univ, Fac Psychol, Jinan 250014, Shandong, Peoples R China; [Tang, Jinxiang; Peng, Yadong; Fu, Yixiao] Chongqing Med Univ, Dept Psychiat, Affiliated Hosp 1, 1 Yixueyuan Rd, Chongqing 400016, Peoples R China; [Tang, Jinxiang] Bishan Hosp Chongqing, Sleep & Psychol Ctr, Chongqing 402760, Peoples R China; [Peng, Yadong] Chongqing Hlth Ctr Women & Children, Dept Psychol, Chongqing 401147, Peoples R China; [Qiu, Jiang] Beijing Normal Univ, Southwest Univ Branch, Collaborat Innovat Ctr Assessment Basic Educ Qual, Beijing 100875, Peoples R China"

通信作者："Qiu, J (corresponding author), Minist Educ, Key Lab Cognit & Personal SWU, Chongqing 400715, Peoples R China.; Fu, YX (corresponding author), Chongqing Med Univ, Dept Psychiat, Affiliated Hosp 1, 1 Yixueyuan Rd, Chongqing 400016, Peoples R China."

来源：BMC PSYCHIATRY

ESI学科分类：PSYCHIATRY/PSYCHOLOGY

WOS号：WOS:000677515100001

JCR分区：Q2

影响因子：4.4

年份：2021

卷号：21

期号：1

开始页：　

结束页：　

文献类型：Article

关键词：Depression; Schizophrenia; Adolescence; Cortical thickness; Machine learning

摘要："Background Early diagnosis of adolescent psychiatric disorder is crucial for early intervention. However, there is extensive comorbidity between affective and psychotic disorders, which increases the difficulty of precise diagnoses among adolescents. Methods We obtained structural magnetic resonance imaging scans from 150 adolescents, including 67 and 47 patients with major depressive disorder (MDD) and schizophrenia (SCZ), as well as 34 healthy controls (HC) to explore whether psychiatric disorders could be identified using a machine learning technique. Specifically, we used the support vector machine and the leave-one-out cross-validation method to distinguish among adolescents with MDD and SCZ and healthy controls. Results We found that cortical thickness was a classification feature of a) MDD and HC with 79.21% accuracy where the temporal pole had the highest weight; b) SCZ and HC with 69.88% accuracy where the left superior temporal sulcus had the highest weight. Notably, adolescents with MDD and SCZ could be classified with 62.93% accuracy where the right pars triangularis had the highest weight. Conclusions Our findings suggest that cortical thickness may be a critical biological feature in the diagnosis of adolescent psychiatric disorders. These findings might be helpful to establish an early prediction model for adolescents to better diagnose psychiatric disorders."

基金机构："National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [31771231, 32071070, 32000760]; Chongqing Science and Technology CommissionNatural Science Foundation Project of CQ CSTC [2019MSXM045, cstc2018jcyjAX0252, cstc2016shmszx130051]; Chongqing Municipal Education Commission [2017SKG017]; Chongqing Health Commission; Natural Science Foundation of ChongqingNatural Science Foundation of Chongqing [cstc2019jcyj-msxmX0520, cstc2020jcyj-msxmX0299]; China Postdoctoral Science FoundationChina Postdoctoral Science Foundation [2019 M662433]; Fundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central Universities [SWU119007]; Postdoctoral Innovation Project in Shandong Province; Chang Jiang Scholars ProgramProgram for Changjiang Scholars & Innovative Research Team in University (PCSIRT); National Outstanding Young People Plan; Chongqing Talent Program; planned project of Chongqing humanities and Social Sciences [2018PY80, 2019PY51]"

基金资助正文："This work was supported by the National Natural Science Foundation of China [31771231, 32071070, 32000760], Chongqing Science and Technology Commission [cstc2018jcyjAX0252, cstc2016shmszx130051], Chongqing Municipal Education Commission [2017SKG017], Chongqing Health Commission and Chongqing Science and Technology Commission [2019MSXM045], Natural Science Foundation of Chongqing [cstc2019jcyj-msxmX0520, cstc2020jcyj-msxmX0299], the planned project of Chongqing humanities and Social Sciences [2018PY80, 2019PY51], China Postdoctoral Science Foundation Funded Project [2019 M662433], Fundamental Research Funds for the Central Universities [SWU119007], Postdoctoral Innovation Project in Shandong Province, Chang Jiang Scholars Program, National Outstanding Young People Plan, Chongqing Talent Program."