Comprehensive Analysis of the Joint Impact of Polygenic Risk Scores and Lifestyle on Cardiovascular Disease Incidence: A Report from the China Kadoorie Biobank

Introduction

Cardiovascular disease (CVD) is one of the major global health threats. Despite the stable or declining incidence and prevalence of CVD among adults over 50 in recent decades, the incidence of CVD in the 15-49 age group has been on the rise. Early-onset CVD, in particular, is increasingly affecting younger people, highlighting the urgent need for effective prevention. Both genetic and environmental factors jointly influence the risk of early-onset CVD. Polygenic risk scores (PRS), typically derived from genome-wide association studies (GWAS), have become an important tool for quantifying individual genetic susceptibility. However, existing PRS perform poorly in East Asian populations, especially in predicting CVD subtypes such as stroke. Moreover, there is a lack of PRS studies on intracerebral hemorrhage (ICH) in the Chinese population. This study aims to develop three disease-specific polygenic risk scores (MetaPRS) for better stratification of genetic risk for different types of CVD by combining multiple CVD-related PRS and explore their association with CVD incidence across different age groups.

Study Background

This study was conducted by the China Kadoorie Biobank (CKB) collaboration group. CKB is a large-scale prospective cohort study designed to assess the joint impact of genetic risk and lifestyle. The CKB cohort includes 96,400 participants from 10 regions across China. The main goal of the study is to construct and validate MetaPRS suitable for the Chinese population by integrating GWAS data from different ancestries and analyze its association with CVD incidence at different ages.

Research Methods

Data Source

The data for this study were sourced from the China Kadoorie Biobank. Between 2004 and 2008, CKB recruited 512,723 participants aged 30-79. Baseline surveys included electronic questionnaires, physical exams, and blood sample collection. Participant information was obtained via national health insurance databases, local disease and death registries, and annual active follow-ups. The study received approval from the Chinese Centre for Disease Control and Prevention and the University of Oxford Tropical Research Ethics Committee.

Construction of Polygenic Risk Scores

We used GWAS data from East Asian and European populations to construct various PRS related to CVD traits via three algorithms (including the C+T method, Lassosum method, and PRS-CS method). These trait-specific PRS were integrated into MetaPRS using the elastic net logistic regression model. Ultimately, disease-specific MetaPRS for coronary artery disease (CAD), ischemic stroke (IS), and intracerebral hemorrhage (ICH) were constructed.

Lifestyle Assessment

Baseline questionnaires and physical examinations collected participants’ sociodemographic characteristics and lifestyle information. Five unhealthy lifestyle factors were selected, including smoking, unhealthy diet, lack of physical activity, unhealthy body mass index (BMI), and waist circumference. Lifestyle was categorized as favorable (0-1 unhealthy factors), intermediate (2-3 unhealthy factors), and unfavorable (4-5 unhealthy factors).

Data Analysis

Cox proportional hazards models were used to evaluate the association between genetic risk and lifestyle with the risk of three types of CVD. Models adjusted for covariates, such as sex, highest level of education, and marital status. Based on Schoenfeld residual tests, the timeline was divided into four age groups (<60 years, 60-69 years, 70-79 years, and ≥80 years), allowing the association coefficients to vary across age groups. Bootstrapping methods were used to calculate 95% confidence intervals.

Study Results

Characteristics of the Study Population

A total of 96,400 participants with a mean age of 53.3 years were included in the study, with 42.8% being male. The training set recorded 3,316 cases of CAD, 6,344 cases of IS, and 5,321 cases of ICH. The test set recorded 1,745 cases of CAD, 7,506 cases of IS, and 1,193 cases of ICH.

Joint Impact of Genetic Risk and Lifestyle

We found that the combination of high genetic risk and unfavorable lifestyle was significantly associated with an increased risk of early-onset CAD, IS, and ICH. Compared with participants with low genetic risk and favorable lifestyle, those with high genetic risk and unfavorable lifestyle had a 6.62-fold, 3.34-fold, and 6.53-fold increased risk of early-onset CAD, IS, and ICH, respectively. Additionally, lifestyle improvements had a more significant absolute risk reduction (ARR) effect in the high genetic risk group, with early-onset CAD ARR reaching 14.7-fold, early-onset IS and late-onset CAD having ARR of 2.5-fold and 2.6-fold, respectively.

Additive Interaction of Genetic Risk and Lifestyle

We observed significant positive additive interactions between high genetic risk and unfavorable lifestyle for early-onset CAD, IS, and late-onset CAD. The proportion of effects attributable to the interaction between genetic risk and lifestyle was 74.3%, 47.5%, and 43.8% for early-onset CAD, IS, and late-onset CAD, respectively.

Gender-Specific Analysis

No significant gender interaction effects were found for genetic risk or lifestyle on any outcome in the gender-specific analysis. Additionally, after excluding relevant participants, the results did not change significantly.

Conclusion

For the first time, this study constructed MetaPRS for CAD, IS, and ICH by integrating cross-ancestry PRS in the Chinese population and analyzed their associations with CVD incidence across different age groups. The results showed that the combination of high genetic risk and unfavorable lifestyle significantly increased the risk of early-onset CVD, and lifestyle improvements had a more significant ARR effect in the high genetic risk group. This indicates that the promotion of genetic testing and lifestyle improvements has important public health implications for young people with high genetic risk.

Research Significance

The results of this study have significant public health implications. First, the MetaPRS constructed by integrating multiple genetic risk factors can more effectively stratify genetic risk for different types of CVD. Second, the study reveals the additive interaction effect between genetic risk and lifestyle on early-onset CVD, emphasizing the importance of lifestyle improvements in high genetic risk populations. This provides a scientific basis for the development of precise prevention strategies, particularly for young people. Finally, the results support the application of genetic testing in public health, promoting the implementation of personalized preventive measures.

This study delved into the mechanisms of CVD onset through the combination of genetic and lifestyle factors, providing new insights and methods for the precise prevention of CVD. Future research should further validate these findings and explore more genetic and environmental factors influencing CVD incidence to advance CVD prevention and control.