Volume 32, Issue 2 pp. 398-408
ORIGINAL ARTICLE

Observational and genetic associations of adiposity with cardiopulmonary multimorbidity: Linear and nonlinear Mendelian randomization analysis

Zimin Song

Zimin Song

Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China

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Wenxiu Wang

Wenxiu Wang

Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China

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Yimin Zhao

Yimin Zhao

Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China

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Wendi Xiao

Wendi Xiao

Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China

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Jie Du

Jie Du

Department of Biomedical Engineering, Peking University, Beijing, China

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Zhonghua Liu

Zhonghua Liu

Department of Biostatistics, Columbia University, New York, New York, USA

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Tao Huang

Corresponding Author

Tao Huang

Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China

Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China

Center for Intelligent Public Health, Academy for Artificial Intelligence, Peking University, Beijing, China

Correspondence

Tao Huang, Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, 38 Xueyuan Rd, Beijing 100191, China.

Email: [email protected]

Yida Tang, Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, 49 Huayuan N Rd, Beijing 100191, China.

Email: [email protected]

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Yida Tang

Corresponding Author

Yida Tang

Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, NHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Key Laboratory of Molecular Cardiovascular Science, Ministry of Education, Beijing Key Laboratory of Cardiovascular Receptors Research, Beijing, China

Correspondence

Tao Huang, Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, 38 Xueyuan Rd, Beijing 100191, China.

Email: [email protected]

Yida Tang, Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, 49 Huayuan N Rd, Beijing 100191, China.

Email: [email protected]

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First published: 05 November 2023

Abstract

Objective

Whether adiposity traits are causal risk factors for cardiopulmonary multimorbidity (CP-MM) remains largely unknown. The aim of this study was to examine the causal role of adiposity traits in the development of CP-MM.

Methods

This study involved 408,886 participants from the UK Biobank who had complete phenotypic and genetic data. Cox regression and Mendelian randomization (MR) analyses were conducted separately for observational and causal associations.

Results

During a median follow-up of 8.7 years, 1492 incident CP-MM were ascertained. In observational analysis, individuals with obesity had a hazard ratio (HR) of 1.51 (95% confidence intervals [CI]: 1.30–1.75) for developing CP-MM, compared with those with normal body mass index (BMI). Restricted cubic spline analyses showed a U-shaped relationship between continuous BMI and CP-MM (p < 0.001), whereas WHRadjBMI exhibited a linear relationship (p = 0.828). Joint analysis revealed that maintaining ideal waist–hip ratio (WHR) in adults with overweight is still effective in preventing CP-MM. In linear MR analysis, 1 kg/m2 increase in genetically predicted BMI and per 1% higher in genetically predicted WHRadjBMI was associated with 9% and 10% higher risk for incident CP-MM, respectively. Nonlinear MR analyses demonstrated linearity between genetically predicted BMI or WHRadjBMI and CP-MM.

Conclusions

Adiposity may play a causal role in CP-MM development and represent a promising approach for multimorbidity prevention.

CONFLICT OF INTEREST STATEMENT

The authors declared no conflict of interest.

DATA AVAILABILITY STATEMENT

Data are available in a public, open-access repository. The UK Biobank data are available on application to the UK Biobank (www.ukbiobank.ac.uk/). This research has been conducted using the UK Biobank resource under Application Number 44430.

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