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Li C, Meng X, Zhang J, Wang H, Lu H, Cao M, Sun S, Wang Y. Associations of metabolic changes and polygenic risk scores with cardiovascular outcomes and all-cause mortality across BMI categories: a prospective cohort study. Cardiovasc Diabetol 2024; 23:231. [PMID: 38965592 PMCID: PMC11225301 DOI: 10.1186/s12933-024-02332-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Accepted: 06/22/2024] [Indexed: 07/06/2024] Open
Abstract
BACKGROUND Associations between metabolic status and metabolic changes with the risk of cardiovascular outcomes have been reported. However, the role of genetic susceptibility underlying these associations remains unexplored. We aimed to examine how metabolic status, metabolic transitions, and genetic susceptibility collectively impact cardiovascular outcomes and all-cause mortality across diverse body mass index (BMI) categories. METHODS In our analysis of the UK Biobank, we included a total of 481,576 participants (mean age: 56.55; male: 45.9%) at baseline. Metabolically healthy (MH) status was defined by the presence of < 3 abnormal components (waist circumstance, blood pressure, blood glucose, triglycerides, and high-density lipoprotein cholesterol). Normal weight, overweight, and obesity were defined as 18.5 ≤ BMI < 25 kg/m2, 25 ≤ BMI < 30 kg/m2, and BMI ≥ 30 kg/m2, respectively. Genetic predisposition was estimated using the polygenic risk score (PRS). Cox regressions were performed to evaluate the associations of metabolic status, metabolic transitions, and PRS with cardiovascular outcomes and all-cause mortality across BMI categories. RESULTS During a median follow-up of 14.38 years, 31,883 (7.3%) all-cause deaths, 8133 (1.8%) cardiovascular disease (CVD) deaths, and 67,260 (14.8%) CVD cases were documented. Among those with a high PRS, individuals classified as metabolically healthy overweight had the lowest risk of all-cause mortality (hazard ratios [HR] 0.70; 95% confidence interval [CI] 0.65, 0.76) and CVD mortality (HR 0.57; 95% CI 0.50, 0.64) compared to those who were metabolically unhealthy obesity, with the beneficial associations appearing to be greater in the moderate and low PRS groups. Individuals who were metabolically healthy normal weight had the lowest risk of CVD morbidity (HR 0.54; 95% CI 0.51, 0.57). Furthermore, the inverse associations of metabolic status and PRS with cardiovascular outcomes and all-cause mortality across BMI categories were more pronounced among individuals younger than 65 years (Pinteraction < 0.05). Additionally, the combined protective effects of metabolic transitions and PRS on these outcomes among BMI categories were observed. CONCLUSIONS MH status and a low PRS are associated with a lower risk of adverse cardiovascular outcomes and all-cause mortality across all BMI categories. This protective effect is particularly pronounced in individuals younger than 65 years. Further research is required to confirm these findings in diverse populations and to investigate the underlying mechanisms involved.
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Affiliation(s)
- Cancan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, 100069, Beijing, China
| | - Xiaoni Meng
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, 100069, Beijing, China
| | - Jie Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, 100069, Beijing, China
| | - Haotian Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, 100069, Beijing, China
| | - Huimin Lu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, 100069, Beijing, China
| | - Meiling Cao
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, 100069, Beijing, China
| | - Shengzhi Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China.
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, 100069, Beijing, China.
| | - Youxin Wang
- Beijing Municipal Key Laboratory of Clinical Epidemiology, School of Public Health, Capital Medical University, No.10 Xitoutiao, Youanmen Street, Fengtai District, 100069, Beijing, China.
- School of Public Health, North China University of Science and Technology, 21 Bohaidadao, Caofeidian, Tangshan, 063210, China.
- Centre for Precision Medicine, Edith Cowan University, Perth, 6027, Australia.
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Kim JS, Song J, Choi S, Park SM. Changes in body composition and subsequent cardiovascular disease risk among 5-year breast cancer survivors. Front Cardiovasc Med 2023; 10:1259292. [PMID: 38054098 PMCID: PMC10694451 DOI: 10.3389/fcvm.2023.1259292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 10/30/2023] [Indexed: 12/07/2023] Open
Abstract
Introduction Cardiovascular disease (CVD) remains a leading cause of death in breast cancer survivors, a growing population. The aim of this study was to determine whether changes in body composition, commonly observed in breast cancer survivors, is associated with subsequent CVD risk. Methods This cohort study used the Korean National Health Insurance Service database. The study population included 73,271 5-year breast cancer survivors aged 40 years or above. To assess changes in body composition and its effect on the risk of CVD, validated prediction equations and multivariate Cox proportional hazards regression were used. Changes in metabolic markers (blood pressure, total cholesterol, and fasting serum glucose) according to changes in body composition were calculated by multiple linear regression. Results Having persistently high predicted lean body and appendicular skeletal muscle mass percentages (LBMP and ASMP, respectively) among breast cancer survivors was associated with 32% and 40% lower CVD risks than a persistently low predicted LBMP or ASMP, respectively. Conversely, persistently high predicted body fat mass percentage (BFMP) was associated with a higher CVD risk than persistently low predicted BFMP. Additionally, those with a low to high change in predicted BFMP had a higher risk of CVD than those with persistently low predicted BFMP. Changes in body composition were accompanied by changes in metabolic markers. Discussion Maintaining high percentages of lean body and appendicular skeletal muscle mass and preventing an increase in fat mass may be beneficial in preventing CVD in breast cancer survivors.
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Affiliation(s)
- Ji Soo Kim
- International Healthcare Center, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jihun Song
- Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Republic of Korea
| | - Seulggie Choi
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Sang Min Park
- Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Republic of Korea
- Department of Family Medicine, Seoul National University Hospital, Seoul, Republic of Korea
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