Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China (He, Wei, W. Yang, Zhuang, Q. Chen, Ren, Y. Li, Wang, Mao, Z. Chen, Q. He, Lei, T. Feng, H. Chen, Qiu); Guangdong Mental Health Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China (F. Yang); Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China (Zhang, Cheng, J. Feng); Department of Psychiatry, the Second Xiangya Hospital of Central South University, Changsha, China (Liao, Su, L. Li,); Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China (Cui, C. Li); Department of Neurology, First Affiliated Hospital of Chongqing Medical University, Chongqing, China (Xie); Oxford Center for Computational Neuroscience, Oxford, U.K. (Rolls); Department of Computer Science, University of Warwick, Coventry, U.K. (Rolls); and Southwest University Branch, Collaborative Innovation Center of Assessment Toward Basic Education Quality, Beijing Normal University, Beijing, China (Qiu).
Am J Psychiatry. 2021 Jun;178(6):530-540. doi: 10.1176/appi.ajp.2020.20070979. Epub 2021 Apr 26.
Increased anxiety in response to the COVID-19 pandemic has been widely noted. The purpose of this study was to test whether the prepandemic functional connectome predicted individual anxiety induced by the pandemic.
Anxiety scores from healthy undergraduate students were collected during the severe and remission periods of the pandemic (first survey, February 22-28, 2020, N=589; second survey, April 24 to May 1, 2020, N=486). Brain imaging data and baseline (daily) anxiety ratings were acquired before the pandemic. The predictive performance of the functional connectome on individual anxiety was examined using machine learning and was validated in two external undergraduate student samples (N=149 and N=474). The clinical relevance of the findings was further explored by applying the connectome-based neuromarkers of pandemic-related anxiety to distinguish between individuals with specific mental disorders and matched healthy control subjects (generalized anxiety disorder, N=43; major depression, N=536; schizophrenia, N=72).
Anxiety scores increased from the prepandemic baseline to the severe stage of the pandemic and remained high in the remission stage. The prepandemic functional connectome predicted pandemic-related anxiety and generalized to the external sample but showed poor performance for predicting daily anxiety. The connectome-based neuromarkers of pandemic-related anxiety further distinguished between participants with generalized anxiety and healthy control subjects but were not useful for diagnostic classification in major depression and schizophrenia.
These findings demonstrate the feasibility of using the functional connectome to predict individual anxiety induced by major stressful events (e.g., the current global health crisis), which advances our understanding of the neurobiological basis of anxiety susceptibility and may have implications for developing targeted psychological and clinical interventions that promote the reduction of stress and anxiety.
人们广泛注意到，对 COVID-19 大流行的反应会出现焦虑增加。本研究旨在检验大流行前的功能连接组是否可预测大流行引起的个体焦虑。
在大流行的严重期和缓解期（第一次调查，2020 年 2 月 22 日至 28 日，N=589；第二次调查，2020 年 4 月 24 日至 5 月 1 日，N=486），从健康的大学生中收集焦虑评分。在大流行之前获得了大脑成像数据和基线（日常）焦虑评分。使用机器学习来检验功能连接组对个体焦虑的预测性能，并在两个大学生外部样本（N=149 和 N=474）中进行验证。通过应用与大流行相关的焦虑的基于连接组的神经标志物来区分特定精神障碍的个体与匹配的健康对照者（广泛性焦虑障碍，N=43；重度抑郁症，N=536；精神分裂症，N=72），进一步探讨了这些发现的临床相关性。
焦虑评分从大流行前的基线水平上升到大流行的严重阶段，在缓解阶段仍然很高。大流行前的功能连接组可预测与大流行相关的焦虑，并推广到外部样本，但预测日常焦虑的性能较差。与大流行相关的焦虑的基于连接组的神经标志物可进一步区分广泛性焦虑障碍的参与者和健康对照者，但对于重度抑郁症和精神分裂症的诊断分类没有用处。
这些发现表明，使用功能连接组来预测重大应激事件（例如当前的全球健康危机）引起的个体焦虑是可行的，这增进了我们对焦虑易感性的神经生物学基础的理解，并且可能对开发靶向心理和临床干预措施具有意义，这些措施可以促进减轻压力和焦虑。
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