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Disease trajectories and mortality among individuals diagnosed with depression: a community-based cohort study in UK Biobank

Molecular Psychiatry volume 26, pages 6736–6746 (2021)Cite this article

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Abstract

Patients with depression are at increased risk for a range of comorbid diseases, with, however, unclear explanations. In this large community-based cohort study of the UK Biobank, 24,130 patients diagnosed with depression were compared to 120,366 matched individuals without such a diagnosis. Follow-up was conducted from 6 months after the index date until death or the end of 2019, for the occurrence of 470 medical conditions and 16 specific causes of death. The median age at the time of the depression diagnosis was 62.0 years, and most of the patients were female (63.63%). During a median follow-up of 4.94 years, 129 medical conditions were found to be significantly associated with a prior diagnosis of depression, based on adjusted Cox regression models. Using disease trajectory network analysis to visualize the magnitude of disease–disease associations and the temporal order of the associated medical conditions, we identified three main affected disease clusters after depression (i.e., cardiometabolic diseases, chronic inflammatory diseases, and diseases related to tobacco abuse), which were further linked to a wider range of other conditions. In addition, we also identified three depression-mortality trajectories leading to death due to cardiovascular disease, respiratory system disease and malignant neoplasm. In conclusion, an inpatient diagnosis of depression in later life is associated with three distinct network-based clusters of medical conditions, indicating alterations in the cardiometabolic system, chronic status of inflammation, and tobacco abuse as key pathways to a wide range of other conditions downstream. If replicated, these pathways may constitute promising targets for the health promotion among depression patients.

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Fig. 1: Flow chart of study population selection and main analysis steps.
Fig. 2: Hazard ratios (HRs) of other medical conditions among depression individuals compared to matched individuals without depression.
Fig. 3: Trajectories of three main disease clusters among depression individuals.
Fig. 4: Disease trajectories leading to mortality with different death causes among depression individuals.

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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. Part of this research was conducted using the UK Biobank Resource under Application 54803.

Code availability

All statistical analyses were conducted by the following software tools: Python v. 3.8, and Cytoscape Desktop v. 3.8.0. All codes associated with the current submission is available, and can be requested by contacting the corresponding authors.

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Acknowledgements

We thank the team members and colleagues involved in West China Biomedical Big Data Center—UK Biobank project for their support.

Funding

This work is supported by the National Natural Science Foundation of China (No. 81971262 to HS), West China Hospital COVID-19 Epidemic Science and Technology Project (No. HX-2019-nCoV-014 to HS), Sichuan University Emergency Grant (No. 2020scunCoVyingji10002 to HS), EU Horizon2020 Research and Innovation Action Grant (847776 to UV and FF), Startup Fund for high-level talents of Fujian Medical University (XRCZX2020007 to HY), and Key Research and Development Program of Science and Technology Department of Sichuan Province (NO. 2019YFS0536 to LY).

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Author notes

  1. These authors contributed equally: Xin Han and Can Hou

Authors and Affiliations

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

    Xin Han, Can Hou, Huazhen Yang, Zhiye Ying, Yao Hu, Yajing Sun, Yuanyuan Qu, Wei Zhang & Huan Song

  2. Medical Big Data Center, Sichuan University, Chengdu, China

    Xin Han, Can Hou, Huazhen Yang, Zhiye Ying, Yao Hu, Yajing Sun, Yuanyuan Qu, Wei Zhang & Huan Song

  3. Division of Nephrology, Kidney Research Institute, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, China

    Wenwen Chen

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

    Lei Yang

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

    Unnur A. Valdimarsdóttir & Huan Song

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

    Unnur A. Valdimarsdóttir

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

    Unnur A. Valdimarsdóttir

  8. Mental Health Center, West China Hospital of Sichuan University, Chengdu, China

    Wei Zhang

  9. Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China

    Haomin Yang

  10. Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden

    Fang Fang

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Contributions

HS, HY, and FF were responsible for the study concept and design. ZY, HY, YS, LY, and YQ did the data and project management. XH, CH, HY, and WC did the data cleaning and analysis. XH, CH, HS, HY, and FF interpreted the data. XH, CH, FF, HY, and HS drafted the paper. All authors approved the final paper as submitted and agree to be accountable for all aspects of the work. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

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Correspondence to Haomin Yang or Huan Song.

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Ethics approval

The UK Biobank has full ethical approval from the NHS National Research Ethics Service (reference number: 16/NW/0274), and this study was also approved by the biomedical research ethics committee of West China Hospital (reference number: 2019–1171).

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The authors declare no competing interests.

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Han, X., Hou, C., Yang, H. et al. Disease trajectories and mortality among individuals diagnosed with depression: a community-based cohort study in UK Biobank. Mol Psychiatry 26, 6736–6746 (2021). https://doi.org/10.1038/s41380-021-01170-6

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