The COVID-19 pandemic widely and rapidly spread around the world, and it had a profound impact on public mental health (1–3). During the COVID-19 crisis, people were exposed to an unprecedented environment of threats and uncertainties. Facing physical and social isolation (as most people were under stay-at-home orders), the uncertainty of infection, and other stressors, people may be especially susceptible to anxiety-related symptoms (3–6) and exhibit individualized behavioral and emotional responses in the face of the pandemic-induced changes and restrictions, which were unlikely in daily life before the pandemic. In addition, there may be great individual differences in levels of anxiety related to the pandemic. In these circumstances, it is helpful to explore brain-based predictors of anxiety, which would advance the understanding of the neural basis of anxiety and may have implications for clinical practice.
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The functional connectome is like a fingerprint of the brain and shows highly individualized functional connectivity profiles that successfully distinguish individuals with high accuracy (7). Emerging evidence based on machine-learning approaches suggests that the individualized functional connectome can be used to predict individual differences in cognition (8), personality (9), and mental disorder symptoms (10). However, results from recent studies have been inconsistent on the prediction of the functional connectome on individual anxiety (11, 12), partly because individual differences in anxiety may not be well measured in the absence of large stressful events and threatening stimuli in daily life. Instead, researchers have tended to provoke anxiety in individuals through experimental manipulation, such as exposure to aversive stimuli (13). Compared with traditional experimental manipulation, the unprecedented uncertainties and stresses caused by this global health crisis may have higher ecological validity that amplified individual differences in anxiety during the pandemic (14), which has enabled us to use a considerable number of participants to investigate the neural correlates of both pandemic-related anxiety and daily anxiety, as well as to further identify potential connectome-based neuromarkers. Thus, we hypothesized that the prepandemic functional connectome could predict individuals’ pandemic-related anxiety but may show poor performance for predicting daily anxiety. Moreover, to investigate the continuous effect of the pandemic on mental health and further examine the reliability of the neuromarkers of pandemic-related anxiety, we utilized data from a longitudinal cohort study with brain imaging data and daily anxiety scores collected before the pandemic and pandemic-related anxiety scores collected during the severe and remission periods of the pandemic.
The acute and persistent panic and fear caused by this crisis also resulted in some psychopathology symptoms (15), and recent national cohort studies have reported that people are more likely to screen positive for mental disorders (e.g., pathological anxiety) during the pandemic (6, 16). It is possible that the identified connectome-based neural correlates of pandemic-related anxiety have the potential to be used for risk assessment of common mental disorders. To explore this possibility, three independent clinical data sets were applied to investigate whether the neuromarkers of pandemic-related anxiety could be generalized to participants with generalized anxiety disorder, major depression, or schizophrenia.
Three independent undergraduate student data sets (main data set: N=589; two validation data sets: N=474 and N=149) were included in this study (Table 1). The main data set comprises individuals in our ongoing project, the Behavioral Brain Research Project of Chinese Personality (BBP), which was used to investigate the predictive performance of the functional connectome on daily anxiety and pandemic-related anxiety, as well as to identify the connectome-based neuromarkers of pandemic-related anxiety. Two other undergraduate student data sets were used to validate the prediction results. We also included three independent mental disorder data sets (generalized anxiety disorder data set: N=43; major depression data set: N=536; schizophrenia data set: N=72) to examine the clinical relevance of the neuromarkers of pandemic-related anxiety (Table 1).
|First pandemic survey
|Second pandemic survey
|Generalized anxiety disorder
|Healthy control group
|Major depressive disorder
|Healthy control group
|Healthy control group
Specifically, a total of 901 undergraduates from the BBP were recruited via mobile telephone text message to complete the first online pandemic questionnaire survey from February 22 to 28, 2020. Among these participants, 604 had completed prepandemic brain scanning from September to December 2019, as well as a self-reported anxiety measurement immediately after the scanning (considered as the baseline or daily anxiety), in which eight participants were missing baseline anxiety scores and seven were excluded because of excessive head motion. We adopted a widely used criterion of head motion to exclude participants if the number of volumes with a framewise displacement >0.5 mm was more than 10% of the total number of volumes to ensure that head motion artifacts were not driving observed effects (17–19). Thus, for the first pandemic survey of the BBP, 589 undergraduates with brain imaging data, baseline anxiety scores, and pandemic-related anxiety scores were included in prediction analysis of whether the prepandemic functional connectome could predict pandemic-related anxiety. Some participants (N=486) had also completed the second online pandemic questionnaire survey from April 24 to May 1, 2020. In addition, a validation sample included 149 undergraduates who had completed an online pandemic survey from February 21 to 28, 2020, and brain scanning from June to October 2019, in which no one was excluded because of excessive head motion. The validation sample and anxiety scores from the second pandemic survey of the BBP were used to examine the reliability of the neural correlates of pandemic-related anxiety identified in the first pandemic survey.
Another validation sample was included from our former project (Southwest University Longitudinal Imaging Multimodal Project [SLIM]), comprising individuals whose self-reported anxiety scores were collected immediately after brain scanning (the data were collected before the COVID-19 pandemic) (20), which were used to validate the predictive performance of the functional connectome on daily anxiety. The present study included 474 undergraduates from SLIM after excluding 12 participants with excessive head motion. Details of the SLIM cohort are presented in the online supplement, as well as in our data description study (20). For the three undergraduate data sets, strict procedures were applied to ensure that all participants had no psychiatric illness or physical health problems and met the requirements for MRI scanning (for further details, see the online supplement). Data collection period and anxiety score information for the three undergraduate data sets are presented in Table 2.
|Data Collection Period
|Brain Imaging Data
|September– December 2019c
|September– December 2019
|First pandemic survey (N=589)
|February 22–28, 2020
|Same as baseline
|Second pandemic survey (N=486)
|April 24–May 1, 2020
|Same as baseline
|Validation sample (N=149)
|February 21–28, 2020
|November 2011– January 2013c
|November 2011– January 2013
We further explored the clinical relevance by linking the neuromarkers of pandemic-related anxiety to different mental disorders. Details on clinical diagnosis and symptom information are provided in the online supplement, as well as in previous studies (19, 21, 22). Briefly, the generalized anxiety disorder data set was collected from the Second Xiangya Hospital of Central South University, which included 25 participants with generalized anxiety disorder and 18 healthy control subjects (21). The major depression data set was collected from the First Affiliated Hospital of Chongqing Medical School and Southwest University, which included 282 participants with major depression and 254 healthy control subjects (19). The schizophrenia data set was obtained from the Center of Biomedical Research Excellence, which included 26 participants with schizophrenia and 46 healthy control subjects. A flow diagram with details of participants’ screening is provided in Figure S1 in the online supplement. All research projects were approved by the local institutional review boards, and written informed consent was obtained from each participant in accordance with the Declaration of Helsinki. The participants’ demographic characteristics are summarized in Table 1 (see also Tables S1 and S2 in the online supplement).
Participants’ anxiety scores from the three undergraduate data sets were assessed using the State-Trait Anxiety Inventory (STAI) (23), which consists of 20 items that assess an individual’s feelings over the past week (the state scale of STAI [STAI-S]) and 20 other items that assess an individual’s general feelings (the trait scale of STAI [STAI-T]) based on a 4-point Likert scale. Participants from the BBP and SLIM completed the STAI immediately after brain scanning, which was considered baseline or daily anxiety compared with pandemic-related anxiety. Notably, given that the BBP was originally designed to investigate the neural basis of Chinese personality and trait-like behaviors, participants of the BBP only completed the STAI-T at baseline. In addition, at the first pandemic survey, we used two open questions to assess individual concerns about the COVID-19 infection using a 5-point Likert scale: “How likely do you think you are to be infected with the COVID-19 coronavirus?” and “How likely do you think your family is to be infected with the COVID-19 coronavirus?”
Neuroimaging Data Preprocessing and Functional Network Construction
The three undergraduate data sets and the major depression data set were collected using the same scanner at the Brain Imaging Center of Southwest University. The generalized anxiety disorder and schizophrenia data sets were collected at two other sites. Resting-state functional MRI (fMRI) data from the different data sets were preprocessed independently (18). The preprocessed data were parcellated using the Brainnetome Atlas, which includes 210 cortical regions and 36 subcortical regions (
Functional Connectome Prediction of Anxiety Related to the COVID-19 Pandemic | American Journal of Psychiatry