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Liu X, Liu X, Huang N, Yang Z, Zhang Z, Zhuang Z, Jin M, Li N, Huang T. Women's reproductive risk and genetic predisposition in type 2 diabetes: A prospective cohort study. Diabetes Res Clin Pract 2024; 208:111121. [PMID: 38295999 DOI: 10.1016/j.diabres.2024.111121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 01/25/2024] [Accepted: 01/28/2024] [Indexed: 02/03/2024]
Abstract
OBJECTIVE To assess synergistic effects of reproductive factors and gene-reproductive interaction on type 2 diabetes (T2D) risk, also the extent to which the genetic risk of T2D can be affected by reproductive risk. METHODS 84,254 women with genetic data and reproductive factors were enrolled between 2006 and 2010 in the UK Biobank. The reproductive risk score (RRS) was conducted based on 17 reproductive items, and genetic risk score (GRS) was based on 149 genetic variants. RESULTS There were 2300 (2.8 %) T2D cases during an average follow-up of 4.49 years. We found a significant increase in T2D risk across RRS categories (Ptrend < 0.001). Compared with low reproductive risk, high-mediate (adjusted hazard ratio [aHR] 1.38, 95 % CI 1.20-1.58) and high (aHR 1.84, 95 % CI 1.54-2.19) reproductive risk could increase the risk of T2D. We further observed a significant additive interaction between reproductive risk and genetic predisposition. In the situation of high genetic predisposition, women with low reproductive risk had lower risk of T2D than those with high reproductive risk (aHR 0.47, 95 % CI 0.30-0.76), with an absolute risk reduction of 2.98 %. CONCLUSIONS Our novo developed RRS identified high reproductive risk is associated with elevated risk of women's T2D, which can be magnified by gene-reproductive interaction.
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Affiliation(s)
- Xiaojing Liu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Institute of Reproductive and Child Health, Peking University/Key Laboratory of Reproductive Health, National Health Commission of the People's Republic of China, Beijing 100191, China
| | - Xiaowen Liu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Institute of Reproductive and Child Health, Peking University/Key Laboratory of Reproductive Health, National Health Commission of the People's Republic of China, Beijing 100191, China
| | - Ninghao Huang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China; Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University, China
| | - Zeping Yang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Institute of Reproductive and Child Health, Peking University/Key Laboratory of Reproductive Health, National Health Commission of the People's Republic of China, Beijing 100191, China
| | - Ziyi Zhang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Institute of Reproductive and Child Health, Peking University/Key Laboratory of Reproductive Health, National Health Commission of the People's Republic of China, Beijing 100191, China
| | - Zhenhuang Zhuang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China; Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University, China
| | - Ming Jin
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Institute of Reproductive and Child Health, Peking University/Key Laboratory of Reproductive Health, National Health Commission of the People's Republic of China, Beijing 100191, China
| | - Nan Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Institute of Reproductive and Child Health, Peking University/Key Laboratory of Reproductive Health, National Health Commission of the People's Republic of China, Beijing 100191, China.
| | - Tao Huang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China; Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing 100191, China; Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University, China
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Liu X, Huang N, Jin M, Zhuang Z, Wang W, Zhao Y, Liu X, Li N, Huang T. Associations of reproductive risk score and joint exposure to ambient air pollutants with chronic obstructive pulmonary disease: a cohort study in UK Biobank. Environ Health Prev Med 2023; 28:76. [PMID: 38057083 DOI: 10.1265/ehpm.23-00155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/08/2023] Open
Abstract
BACKGROUND Reproductive risk factors and air pollution for developing chronic obstructive pulmonary disease (COPD) have been documented separately. However, the combined effects of overall reproductive risk status on COPD and the extent to which this can be impacted by air pollution are unknown. The aim of this study was to construct a reproductive risk score (RRS) and an air pollution score (APS) and assess independent and joint associations between the two with incident COPD risk. METHODS 78,027 female participants aged 40-69 years without baseline COPD from UK Biobank recruited between 2006 to 2010 were included in this study. RRS was constructed by 17 women's reproductive health-related items, and APS incorporating PM2.5, PM2.5-10, PM10, NO2, and NOx was calculated to assess the joint exposure level. The outcome of the incident COPD was identified through the in-patient hospital register. The associations of RRS and APS with COPD were examined by Cox proportional hazards regression. RESULTS The risk of COPD reached its highest in the fourth quartile of the RRS (adjusted HR: 2.23, 95% CI: 1.76-2.82, P for trend < 0.001). A dose-response manner can also be observed between higher tertile APS with increased COPD risk and the highest risk was found in the third tertile of the APS (adjusted HR: 1.37, 95% CI: 1.19-1.58, P for trend < 0.001). The relative excess risk due to interaction (RERI) of 0.030 (95% CI: 0.012-0.048) showed additive interaction between RRS and APS on COPD was significant. In the joint analysis, the combinations of both higher RRS and APS signified higher incident COPD risk. CONCLUSION High RRS and high APS were jointly associated with increased COPD risks in a dose-response pattern. Using comprehensive indicators to identify women's reproductive risk factors, together with the control of air pollution, is effective for COPD prevention.
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Affiliation(s)
- Xiaowen Liu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
- Institute of Reproductive and Child Health, Peking University/ Key Laboratory of Reproductive Health, National Health Commission of the People's Republic of China
| | - Ninghao Huang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
| | - Ming Jin
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
- Institute of Reproductive and Child Health, Peking University/ Key Laboratory of Reproductive Health, National Health Commission of the People's Republic of China
| | - Zhenhuang Zhuang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
| | - Wenxiu Wang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
| | - Yimin Zhao
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
| | - Xiaojing Liu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
- Institute of Reproductive and Child Health, Peking University/ Key Laboratory of Reproductive Health, National Health Commission of the People's Republic of China
| | - Nan Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
- Institute of Reproductive and Child Health, Peking University/ Key Laboratory of Reproductive Health, National Health Commission of the People's Republic of China
| | - Tao Huang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University
- Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education
- Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University
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