Pre-COVID brain network topology prospectively predicts social anxiety alterations during the COVID-19 pandemic

IF 4.3 2区 医学 Q1 NEUROSCIENCES Neurobiology of Stress Pub Date : 2023-10-01 DOI:10.1016/j.ynstr.2023.100578
Qingyuan Li , Xun Zhang , Xun Yang , Nanfang Pan , Xiao Li , Graham J. Kemp , Song Wang , Qiyong Gong
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Abstract

Background

Social anxiety (SA) is a negative emotional response that can lead to mental health issues, which some have experienced during the coronavirus disease 2019 (COVID-19) pandemic. Little attention has been given to the neurobiological mechanisms underlying inter-individual differences in SA alterations related to COVID-19. This study aims to identify neurofunctional markers of COVID-specific SA development.

Methods

110 healthy participants underwent resting-state magnetic resonance imaging and behavioral tests before the pandemic (T1, October 2019 to January 2020) and completed follow-up behavioral measurements during the pandemic (T2, February to May 2020). We constructed individual functional networks and used graph theoretical analysis to estimate their global and nodal topological properties, then used Pearson correlation and partial least squares correlations examine their associations with COVID-specific SA alterations.

Results

In terms of global network parameters, SA alterations (T2-T1) were negatively related to pre-pandemic brain small-worldness and normalized clustering coefficient. In terms of nodal network parameters, SA alterations were positively linked to a pronounced degree centrality pattern, encompassing both the high-level cognitive networks (dorsal attention network, cingulo-opercular task control network, default mode network, memory retrieval network, fronto-parietal task control network, and subcortical network) and low-level perceptual networks (sensory/somatomotor network, auditory network, and visual network). These findings were robust after controlling for pre-pandemic general anxiety, other stressful life events, and family socioeconomic status, as well as by treating SA alterations as categorical variables.

Conclusions

The individual functional network associated with SA alterations showed a disrupted topological organization with a more random state, which may shed light on the neurobiological basis of COVID-related SA changes at the network level.

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COVID-19前大脑网络拓扑可预测COVID-19大流行期间社交焦虑的变化
背景社交焦虑(SA)是一种负面情绪反应,可能导致心理健康问题,一些人在2019冠状病毒病(新冠肺炎)大流行期间曾经历过这种情况。很少关注与新冠肺炎相关的SA改变个体间差异的神经生物学机制。本研究旨在确定新冠肺炎特异性SA发展的神经功能标志物。方法110名健康参与者在疫情前(2019年10月T1至2020年1月)接受了静息状态磁共振成像和行为测试,并在疫情期间(2020年2月T2至5月)完成了后续行为测量。我们构建了单个函数网络,并使用图论分析来估计它们的全局和节点拓扑性质,然后使用Pearson相关性和偏最小二乘相关性来检查它们与新冠病毒特异性SA变化的关联。结果在全局网络参数方面,SA改变(T2-T1)与疫情前大脑小世界度和归一化聚类系数呈负相关。在节点网络参数方面,SA的改变与显著的程度中心性模式呈正相关,包括高级认知网络(背侧注意网络、扣带回盖任务控制网络、默认模式网络、记忆检索网络、额顶叶任务控制网络和皮层下网络)和低级感知网络(感觉/体动网络、听觉网络和视觉网络)。在控制了疫情前的普遍焦虑、其他压力生活事件和家庭社会经济地位,并将SA变化视为分类变量后,这些发现是有力的。结论与SA改变相关的个体功能网络表现出一种更随机的拓扑组织破坏,这可能为新冠肺炎相关SA改变在网络水平上的神经生物学基础提供线索。
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来源期刊
Neurobiology of Stress
Neurobiology of Stress Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
9.40
自引率
4.00%
发文量
74
审稿时长
48 days
期刊介绍: Neurobiology of Stress is a multidisciplinary journal for the publication of original research and review articles on basic, translational and clinical research into stress and related disorders. It will focus on the impact of stress on the brain from cellular to behavioral functions and stress-related neuropsychiatric disorders (such as depression, trauma and anxiety). The translation of basic research findings into real-world applications will be a key aim of the journal. Basic, translational and clinical research on the following topics as they relate to stress will be covered: Molecular substrates and cell signaling, Genetics and epigenetics, Stress circuitry, Structural and physiological plasticity, Developmental Aspects, Laboratory models of stress, Neuroinflammation and pathology, Memory and Cognition, Motivational Processes, Fear and Anxiety, Stress-related neuropsychiatric disorders (including depression, PTSD, substance abuse), Neuropsychopharmacology.
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