Mapping structural covariance networks of emotional withdrawal symptoms in males with methamphetamine use disorder during abstinence

Author:

Mo Xian12,Jiang Ping345,Sun Jiayu6,Lu Lu35,Li Lei35,Huang Xiaoqi35ORCID,Xu Jiajun7,Li Jing7,Zhang Junran2ORCID,Gong Qiyong35ORCID

Affiliation:

1. West China Biomedical Big Data Center, West China Hospital Sichuan University Chengdu China

2. College of Electrical Engineering Sichuan University Chengdu China

3. Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital Sichuan University Chengdu China

4. West China Medical Publishers, West China Hospital Sichuan University Chengdu China

5. Research Unit of Psychoradiology Chinese Academy of Medical Sciences Chengdu China

6. Department of Radiology West China Hospital of Sichuan University Chengdu China

7. Mental Health Center West China Hospital of Sichuan University Chengdu China

Abstract

AbstractIndividuals with methamphetamine use disorder (MUD) often experience anxiety and depressive symptoms during abstinence, which can worsen the likelihood of relapse. Thus, it is essential to understand the neuro‐mechanism behind methamphetamine use and its associated emotional withdrawal symptoms in order to develop effective clinical strategies. This study aimed to evaluate associations between emotional withdrawal symptoms and structural covariance networks (SCNs) based on cortical thickness (CTh) across the brain. The CTh measures were obtained from Tl‐weighted MRI data from a sample of 48 males with MUD during abstinence and 48 male healthy controls. The severity of anxiety and depressive symptoms was assessed by the Hamilton Anxiety Scale (HAMA) and depression (HAMD) scales. Two important nodes belonging to the brain reward system, the right rostral anterior cingulate cortex (rACC) and medial prefrontal cortex (medPFC), were selected as seeds to conduct SCNs and modulation analysis by emotional symptoms. MUDs showed higher structural covariance between the right rACC and regions in the dorsal attention, right frontoparietal, auditory, visual and limbic networks. They also displayed higher structural covariance between the right medPFC and regions in the limbic network. Moreover, the modulation analysis showed that higher scores on HAMA were associated with increased covariance between the right rACC and the left parahippocampal and isthmus cingulate cortex in the default mode network. These outcomes shed light on the complex neurobiological mechanisms underlying methamphetamine use and its associated emotional withdrawal symptoms and may provide new insights into the development of effective treatments for MUD.

Funder

Sichuan Province Science and Technology Support Program

Publisher

Wiley

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