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Multivariate Classification Based on Large-Scale Brain Networks During Early Abstinence Predicted Relapse Among Male Detoxified Alcohol- Dependent Patients

19 Pages Posted: 14 Mar 2022

See all articles by Xia Yang

Xia Yang

affiliation not provided to SSRN

Hong-ru Zhu

affiliation not provided to SSRN

Ren-hao Deng

affiliation not provided to SSRN

Shi-wan Tao

affiliation not provided to SSRN

Yu-jie Tao

affiliation not provided to SSRN

Yajing Meng

Sichuan University - Department of Psychiatry

Hui-yao Wang

affiliation not provided to SSRN

Xiao-jing Li

affiliation not provided to SSRN

Wei Wei

Sichuan University - Mental Health Center

Hua Yu

Zhejiang University

Qiang Wang

Sichuan University - Mental Health Center

Wei Deng

Zhejiang University - Affiliated Mental Health Center

Lian-sheng Zhao

affiliation not provided to SSRN

Xiaohong Ma

Sichuan University - Psychiatric Laboratory

Ming-li Li

affiliation not provided to SSRN

Jiajun Xu

Sichuan University - Mental Health Center

Jing Li

affiliation not provided to SSRN

Yansong Liu

affiliation not provided to SSRN

Zhen Tang

affiliation not provided to SSRN

Xiang-dong Du

Soochow University - Suzhou Psychiatric Hospital

Jeremy Coid

Sichuan University - West China Brain Research Centre

Andrew J. Greenshaw

University of Alberta

Tao Li

Sichuan University - Mental Health Center

Yu Zhang

Lehigh University

Wan Jun Guo

Zhejiang University - Affiliated Mental Health Center

More...

Abstract

Objective: Identification of biomarkers to predict relapse of alcohol-dependent (AD) patients remains remarkably challenging. The current study aimed to identify neurobiological features based on connectivity of brain networks that may be predictive of relapse after detoxification.

Methods: Sixty-six male AD patients in the early-abstinence stage after hospitalized detoxification underwent resting-state functional magnetic resonance imaging. We used both traditional analysis (ANOVA) and multivariate pattern analysis with a relevance vector machine (RVM) on large-scale brain networks with a novel-created dimensionality of 2,178 (242 nodes × 9 networks) connections to predict a relapse during the 6-month follow-up.

Results: During a 6-month follow-up, 38 (57.6%) of the AD patients drank again. Although ANOVA did not reveal any significant indicators based on connectome analysis for differentiation of relapsing vs. abstinent patients, RVM analysis yielded a model with high predictive performance (area under ROC curve =0.912). The accuracy of the RVM model documented by leave-one-out cross-validation was 0.833. The most heavily weighted connections for the relapse classification were among the limbic network (LIM), visual network (VIS), dorsal attention network, subcortical network (Sub) and cerebellum network. In addition, the intra-connections of VIS with LIM ( r = 0.44, p = 0.005) and Sub ( r = -0.46, p =0.004) were significantly associated with severity of relapse.

Conclusions: Application of RVM model in this study provided an elegant and efficient way to capture key information about neuroimaging biomarkers for AD prognosis, which indicates that deficits in networks of visual attention and the affective cognition behavior system could be predictors of relapse respect to AD patients.

Funding: The study was partly supported by grants from the National Natural Science Foundation (grant no. 81571305), the Department of Science and Technology of Sichuan provincial government (grant no. 2019YFS0153), the “1.3.5” project for disciplines of excellence, West China Hospital, Sichuan University (grant no. 2019HXFH026), and the Introduction Project of Suzhou Clinical Expert Team (grant no. SZYJTD201715).

Declaration of Interest: The authors declare no conflicts of interest.

Ethical Approval: This longitudinal study was approved by the Ethics Committee of West China Hospital of Sichuan University in 2016 (NO. 22). Informed written consent was obtained from every participant in this study

Keywords: alcohol dependence, relapse, predictor, rest-functional magnetic resonance imaging (rs-fMRI), relevance vector machine, multivariate pattern analysis

Suggested Citation

Yang, Xia and Zhu, Hong-ru and Deng, Ren-hao and Tao, Shi-wan and Tao, Yu-jie and Meng, Yajing and Wang, Hui-yao and Li, Xiao-jing and Wei, Wei and Yu, Hua and Wang, Qiang and Deng, Wei and Zhao, Lian-sheng and Ma, Xiaohong and Li, Ming-li and Xu, Jiajun and Li, Jing and Liu, Yansong and Tang, Zhen and Du, Xiang-dong and Coid, Jeremy and Greenshaw, Andrew J. and Li, Tao and Zhang, Yu and Guo, Wan Jun, Multivariate Classification Based on Large-Scale Brain Networks During Early Abstinence Predicted Relapse Among Male Detoxified Alcohol- Dependent Patients. Available at SSRN: https://ssrn.com/abstract=4057126 or http://dx.doi.org/10.2139/ssrn.4057126

Xia Yang

affiliation not provided to SSRN ( email )

No Address Available

Hong-ru Zhu

affiliation not provided to SSRN ( email )

No Address Available

Ren-hao Deng

affiliation not provided to SSRN ( email )

No Address Available

Shi-wan Tao

affiliation not provided to SSRN ( email )

No Address Available

Yu-jie Tao

affiliation not provided to SSRN ( email )

No Address Available

Yajing Meng

Sichuan University - Department of Psychiatry ( email )

No. 24 South Section1, Yihuan Road,
Chengdu, 610064
China

Hui-yao Wang

affiliation not provided to SSRN ( email )

No Address Available

Xiao-jing Li

affiliation not provided to SSRN ( email )

No Address Available

Wei Wei

Sichuan University - Mental Health Center ( email )

Hua Yu

Zhejiang University ( email )

Qiang Wang

Sichuan University - Mental Health Center ( email )

Wei Deng

Zhejiang University - Affiliated Mental Health Center ( email )

Lian-sheng Zhao

affiliation not provided to SSRN ( email )

No Address Available

Xiaohong Ma

Sichuan University - Psychiatric Laboratory ( email )

China

Ming-li Li

affiliation not provided to SSRN ( email )

No Address Available

Jiajun Xu

Sichuan University - Mental Health Center ( email )

Sichuan
China

Jing Li

affiliation not provided to SSRN ( email )

No Address Available

Yansong Liu

affiliation not provided to SSRN ( email )

No Address Available

Zhen Tang

affiliation not provided to SSRN ( email )

No Address Available

Xiang-dong Du

Soochow University - Suzhou Psychiatric Hospital ( email )

Jeremy Coid

Sichuan University - West China Brain Research Centre ( email )

Sichuan
China

Andrew J. Greenshaw

University of Alberta ( email )

Edmonton, T6G 2R3
Canada

Tao Li

Sichuan University - Mental Health Center ( email )

Yu Zhang

Lehigh University ( email )

621 Taylor Street
Bethlehem, PA 18015
United States

Wan Jun Guo (Contact Author)

Zhejiang University - Affiliated Mental Health Center ( email )

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