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Wu S, Zhong Q, Song Q, Wang M. The role of sex hormone binding globulin levels in the association of surgical and natural premature menopause with incident type 2 diabetes. Maturitas 2024; 187:108063. [PMID: 38991416 DOI: 10.1016/j.maturitas.2024.108063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Revised: 06/18/2024] [Accepted: 07/01/2024] [Indexed: 07/13/2024]
Abstract
OBJECTIVE To examine associations of surgical and natural menopause before the age of 40 years with the risk of type 2 diabetes (T2D) in women. METHODS A total of 273,331 women from the United Kingdom were recruited between 2006 and 2010 in the UK Biobank (UKB) study, and 146,343 women aged 40 to 69 years who were postmenopausal at baseline were included in the analysis. Surgical menopause and natural premature menopause were defined as bilateral oophorectomy before the age of 40 and menopause before the age of 40 without oophorectomy, respectively. Multivariable Cox regression models were used to estimate the hazard ratios (HRs) and 95 % confidence intervals (CIs) for the association between premature menopause and the incidence of T2D. RESULTS During a median follow-up of 10.4 years, 47 women with surgical premature menopause, 244 women with natural premature menopause, and 4724 women without premature menopause developed T2D. Compared with women without premature menopause, both surgical premature menopause (adjusted HR = 1.46, 95 % CI: 1.09-1.95; P = 0.01) and natural premature menopause (adjusted HR = 1.20, 95 % CI: 1.06-1.37; P < 0.01) were associated with higher risks of incident T2D in the multivariable-adjusted models. Additionally, we observed a significant interaction between levels of sex hormone binding globulin (SHBG) (Pinteraction < 0.01) and the effects of premature menopause on incident T2D. The association between premature menopause and T2D risk appeared to be stronger in women with higher SHBG levels. Furthermore, a joint association was detected between premature menopause and the genetic risk score (GRS) of T2D, with a higher score indicating a higher risk of developingT2D. The highest risk of T2D was observed with higher T2D GRS and surgical premature menopause (adjusted HR = 2.61, 95 % CI: 1.65-4.12; P < 0.01). CONCLUSIONS Surgical menopause and natural menopause before the age of 40 years were associated with an increased risk of T2D among postmenopausal women. The findings also suggest potential interactions of premature menopause with SHBG levels, with the association appearing to be stronger in higher SHBG levels, as well as a joint association between menopause status and genetic risk factors on T2D incidence.
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Affiliation(s)
- Shuang Wu
- Department of Gynecology and Obstetrics, Affiliated Hospital of Hangzhou Normal University, China
| | - Qiong Zhong
- Department of Ggynaecology and Obstetrics, Shuyang Mercy Hospital, China
| | - Qiying Song
- Department of Child Healthcare, Shenzhen Baoan Women's and Children's Hospital, China.
| | - Mengying Wang
- Department of Nutrition and Food Hygiene, School of Public Health, Peking University, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, China.
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Guo H, Wang M, Ye Y, Huang C, Wang S, Peng H, Wang X, Fan M, Hou T, Wu X, Huang X, Yan Y, Zheng K, Wu T, Li L. Short-Term Exposure to Nitrogen Dioxide Modifies Genetic Predisposition in Blood Lipid and Fasting Plasma Glucose: A Pedigree-Based Study. BIOLOGY 2023; 12:1470. [PMID: 38132296 PMCID: PMC10740487 DOI: 10.3390/biology12121470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 11/13/2023] [Accepted: 11/24/2023] [Indexed: 12/23/2023]
Abstract
(1) Background: Previous studies suggest that exposure to nitrogen dioxide (NO2) has a negative impact on health. But few studies have explored the association between NO2 and blood lipids or fasting plasma glucose (FPG), as well as gene-air pollution interactions. This study aims to fill this knowledge gap based on a pedigree cohort in southern China. (2) Methods: Employing a pedigree-based design, 1563 individuals from 452 families participated in this study. Serum levels of triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDLC), high-density lipoprotein cholesterol (HDLC), and FPG were measured. We investigated the associations between short-term NO2 exposure and lipid profiles or FPG using linear mixed regression models. The genotype-environment interaction (GenoXE) for each trait was estimated using variance component models. (3) Results: NO2 was inversely associated with HDLC but directly associated with TG and FPG. The results showed that each 1 μg/m3 increase in NO2 on day lag0 corresponded to a 1.926% (95%CI: 1.428-2.421%) decrease in HDLC and a 1.400% (95%CI: 0.341-2.470%) increase in FPG. Moreover, we observed a significant genotype-NO2 interaction with HDLC and FPG. (4) Conclusion: This study highlighted the association between NO2 exposure and blood lipid profiles or FPG. Additionally, our investigation suggested the presence of genotype-NO2 interactions in HDLC and FPG, indicating potential loci-specific interaction effects. These findings have the potential to inform and enhance the interpretation of studies that are focused on specific gene-environment interactions.
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Affiliation(s)
- Huangda Guo
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; (H.G.)
| | - Mengying Wang
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
- Department of Nutrition and Food Hygiene, School of Public Health, Peking University, Beijing 100191, China
| | - Ying Ye
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou 350012, China
| | - Chunlan Huang
- Department of Hygiene, Nanjing Country Center for Disease Control and Prevention, Nanjing 363600, China
| | - Siyue Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; (H.G.)
| | - Hexiang Peng
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; (H.G.)
| | - Xueheng Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; (H.G.)
| | - Meng Fan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; (H.G.)
| | - Tianjiao Hou
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; (H.G.)
| | - Xiaoling Wu
- Department of Hygiene, Nanjing Country Center for Disease Control and Prevention, Nanjing 363600, China
| | - Xiaoming Huang
- Department of Hygiene, Nanjing Country Center for Disease Control and Prevention, Nanjing 363600, China
| | - Yansheng Yan
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou 350012, China
| | - Kuicheng Zheng
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou 350012, China
| | - Tao Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; (H.G.)
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
- Key Laboratory of Reproductive Health, Ministry of Health, Beijing 100191, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China; (H.G.)
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
- Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing 100191, China
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