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Risk of Cardiovascular Disease after Common Psychiatric Disorders: Analyses of Disease Susceptibility and Progression Trajectory in the UK Biobank

37 Pages Posted: 26 Aug 2022

See all articles by Xin Han

Xin Han

Sichuan University - West China Biomedical Big Data Center

Yu Zeng

Sichuan University - West China Biomedical Big Data Center

Yanan Shang

Sichuan University - West China Biomedical Big Data Center

Yao Hu

Sichuan University - West China Biomedical Big Data Center

Can Hou

Sichuan University - West China Biomedical Big Data Center

Huazhen Yang

Sichuan University - West China Biomedical Big Data Center

Wenwen Chen

Sichuan University - State Key Laboratory of Biotherapy and Cancer Center

Zhiye Ying

Sichuan University - West China Biomedical Big Data Center

Yajing Sun

Sichuan University - West China Biomedical Big Data Center

Yuanyuan Qu

Sichuan University - West China Biomedical Big Data Center

Junren Wang

Sichuan University - West China Biomedical Big Data Center

Wei Zhang

Sichuan University - Mental Health Center

Fang Fang

Karolinska Institutet - Institute of Environmental Medicine

Unnur Anna Valdimarsdóttir

University of Iceland - School of Health Sciences

Huan Song

Sichuan University - West China Biomedical Big Data Center

More...

Abstract

Background: Whether associations between psychiatric disorders and cardiovascular diseases (CVDs) can be modified by disease susceptibility and the temporal pattern of these associated CVDs remain unknown.

Methods: We conducted a matched cohort study of UK Biobank including 44,505 patients with common psychiatric disorders (anxiety, depression, and stress-related disorders) between 1997 and 2019, together with 222,525 sex- and birth year- individually matched unexposed individuals.

Results: During a mean follow-up of 12.29 years, we observed an elevated risk of CVD among patients with psychiatric disorders, compared with matched unexposed individuals (hazard ratios [HRs] =1.19, 95% confidence interval [CI]: 1.17-1.22), especially during the first six months of follow-up (1.82 [1.63-2.02]). The stratification analyses by family history of CVD and by polygenic risk score of CVD obtained similar estimates between subgroups with different susceptibilities to CVD. We conducted trajectory analysis to visualize the temporal pattern of CVDs after common psychiatric disorders, identifying primary hypertension, acute myocardial infarction, and stroke as three main intermediate steps leading to further increased risk of other CVDs.

Conclusions: The association between common psychiatric disorders and subsequent CVD is not modified by predisposition to CVD. Hypertension, acute myocardial infarction, and stroke are three initial CVDs linking psychiatric disorders to other CVD sequelae, highlighting a need of timely intervention on these targets to prevent further CVD sequelae among all individuals with common psychiatric disorders.

Funding Information: This work is supported by the National Natural Science Foundation of China (No. 81971262 to HS), 1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University (No. ZYYC21005 to HS), EU Horizon2020 Research and Innovation Action Grant (847776 to UV and FF).

Declaration of Interests: We declare no competing interests.

Ethics Approval Statement: Written informed consent was obtained from all participants by the UK Biobank. The UK Biobank has full ethical approval from the 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).

Keywords: Psychiatric disorders, Cardiovascular disease, Disease susceptibility, Disease trajectory

Suggested Citation

Han, Xin and Zeng, Yu and Shang, Yanan and Hu, Yao and Hou, Can and Yang, Huazhen and Chen, Wenwen and Ying, Zhiye and Sun, Yajing and Qu, Yuanyuan and Wang, Junren and Zhang, Wei and Fang, Fang and Valdimarsdóttir, Unnur Anna and Song, Huan, Risk of Cardiovascular Disease after Common Psychiatric Disorders: Analyses of Disease Susceptibility and Progression Trajectory in the UK Biobank. Available at SSRN: https://ssrn.com/abstract=4201399 or http://dx.doi.org/10.2139/ssrn.4201399

Xin Han

Sichuan University - West China Biomedical Big Data Center ( email )

Yu Zeng

Sichuan University - West China Biomedical Big Data Center ( email )

Yanan Shang

Sichuan University - West China Biomedical Big Data Center ( email )

Yao Hu

Sichuan University - West China Biomedical Big Data Center ( email )

Can Hou

Sichuan University - West China Biomedical Big Data Center ( email )

Huazhen Yang

Sichuan University - West China Biomedical Big Data Center ( email )

Wenwen Chen

Sichuan University - State Key Laboratory of Biotherapy and Cancer Center ( email )

Zhiye Ying

Sichuan University - West China Biomedical Big Data Center ( email )

Yajing Sun

Sichuan University - West China Biomedical Big Data Center ( email )

Yuanyuan Qu

Sichuan University - West China Biomedical Big Data Center ( email )

Junren Wang

Sichuan University - West China Biomedical Big Data Center

Wei Zhang

Sichuan University - Mental Health Center ( email )

Fang Fang

Karolinska Institutet - Institute of Environmental Medicine ( email )

Unnur Anna Valdimarsdóttir

University of Iceland - School of Health Sciences

Huan Song (Contact Author)

Sichuan University - West China Biomedical Big Data Center ( email )

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