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Association of pre-existing depression and anxiety with Omicron variant infection

Molecular Psychiatry (2024)Cite this article

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Abstract

Pre-existing psychiatric disorders were linked to an increased susceptibility to COVID-19 during the initial outbreak of the pandemic, while evidence during Omicron prevalence is lacking. Leveraging data from two prospective cohorts in China, we identified incident Omicron infections between January 2023 and April 2023. Participants with a self-reported history or self-rated symptoms of depression or anxiety before the Omicron pandemic were considered the exposed group, whereas the others were considered unexposed. We employed multivariate logistic regression models to examine the association of pre-existing depression or anxiety with the risk of any or severe Omicron infection indexed by medical interventions or severe symptoms. Further, we stratified the analyses by polygenic risk scores (PRSs) for COVID-19 and repeated the analyses using the UK Biobank data. We included 10,802 individuals from the Chinese cohorts (mean age = 51.1 years, 45.6% male), among whom 7841 (72.6%) were identified as cases of Omicron infection. No association was found between any pre-existing depression or anxiety and the overall risk of Omicron infection (odds ratio [OR] =1.04, 95% confidence interval [CI] 0.95–1.14). However, positive associations were noted for severe Omicron infection, either as infections requiring medical interventions (1.26, 1.02–1.54) or with severe symptoms (≥3: 1.73, 1.51–1.97). We obtained comparable estimates when stratified by COVID-19 PRS level. Additionally, using clustering method, we identified eight distinct symptom patterns and found associations between pre-existing depression or anxiety and the patterns characterized by multiple or complex severe symptoms including cough and taste and smell decline (ORs = 1.42–2.35). The results of the UK Biobank analyses corroborated findings of the Chinese cohorts. In conclusion, pre-existing depression and anxiety was not associated with the risk of Omicron infection overall but an elevated risk of severe Omicron infection, supporting the continued efforts on monitoring and possible early intervention in this high-risk population during Omicron prevalence.

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Fig. 1
Fig. 2: Associations between pre-existing depression and anxiety and identified severe Omicron symptom patterns in the China Severe Trauma Cohort and the China Surgery and Anesthesia Cohort.

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Data availability

Data from the UK Biobank (http://www.ukbiobank.ac.uk/) are available to all researchers upon making an application. The validation study was conducted using the UK Biobank Resource under Application 54803 (approved on October 29, 2019).

Code availability

All codes associated with the current submission are available and can be requested by contacting the corresponding authors.

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Acknowledgements

This work was supported by the 1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University (No. ZYYC21005 to HS) and Sichuan Science and Technology Program (No. 2023ZYD0168 to QL). We thank the team members involved in West China Biomedical Big Data Center for their support. The validation study was conducted using the UK Biobank Resource under Application 54803 (approved on October 29, 2019), including data provided by patients and collected by the NHS as part of their care and support, made available by National Safe Haven as part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics, and funded by UK Research and Innovation (grant ref: MC_PC_20029 and MC_PC_20058).

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  1. These authors contributed equally: Huazhen Yang, Lei Yang.

Authors and Affiliations

  1. Department of Anesthesiology and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China

    Huazhen Yang, Wenwen Chen, Yu Zeng, Yanan Zhang, Yuanyuan Qu, Yao Hu, Di Liu, Jie Song & Huan Song

  2. Med-X Center for Informatics, Sichuan University, Chengdu, China

    Huazhen Yang, Wenwen Chen, Yu Zeng, Yanan Zhang, Yuanyuan Qu, Yao Hu, Di Liu, Jie Song & Huan Song

  3. Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, China

    Lei Yang, Yuling Tang, Huolin Zeng, Di Yang & Qian Li

  4. Department of Anesthesiology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China

    Di Yang

  5. Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, China

    Di Yang

  6. Sichuan University - Pittsburgh Institute, Sichuan University, Chengdu, China

    Di Liu

  7. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

    Jie Song

  8. Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden

    Fang Fang, Unnur A. Valdimarsdóttir & Huan Song

  9. Center of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík, Iceland

    Unnur A. Valdimarsdóttir & Huan Song

  10. Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA

    Unnur A. Valdimarsdóttir

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Contributions

HS and HY was responsible for the study’s concept and design. YT, HZ, DY, LY, YQ, and YH did the acquisition of data. YZ and WC did the data and project management. HY, YZ, WC, and YZ did the data cleaning and analysis. HY, LY, JS, UAV, FF, and HS interpreted the data. HY, LY, DL, QL, UAV, FF, and HS drafted the manuscript. All the authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

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Correspondence to Qian Li or Huan Song.

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The authors declare no competing interests.

Ethics

The conduction of CSAC and CSTC were approved by the ethics committee of West China Hospital, Sichuan University (approval numbers: 2020.469 and 2020.243). The UK Biobank received full ethical approval from the NHS National Research Ethics Service (16/NW/0274). The additional collection of COVID-19 data in those Chinese cohorts and this specific study were approved by the ethics committee of West China Hospital, Sichuan University (2020.469, 2020.243, and 2020.66 [with submitted supplements]). All methods were performed in accordance with the relevant guidelines and regulations.

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Yang, H., Yang, L., Chen, W. et al. Association of pre-existing depression and anxiety with Omicron variant infection. Mol Psychiatry (2024). https://doi.org/10.1038/s41380-024-02594-6

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