MTNR1B variants increase gestational diabetes mellitus risk in young Chinese pregnant women
Abstract The aim of this study is to explore the relationship between the MTNR1B gene variants rs1387153 and rs10830963 and the risk of gestational diabetes mellitus (GDM). Additionally, the study sought to investigate gene-environment interactions, assess the cumulative genetic risk through the app...
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Nature Portfolio
2025-06-01
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| Online Access: | https://doi.org/10.1038/s41598-025-02248-9 |
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| author | Qiaoli Zeng Xin Liu Jia Liu Yanying Wu Yuxuan Zhang Zhaotao He Yue Wei Guofang Zeng Dehua Zou Runmin Guo |
| author_facet | Qiaoli Zeng Xin Liu Jia Liu Yanying Wu Yuxuan Zhang Zhaotao He Yue Wei Guofang Zeng Dehua Zou Runmin Guo |
| author_sort | Qiaoli Zeng |
| collection | DOAJ |
| description | Abstract The aim of this study is to explore the relationship between the MTNR1B gene variants rs1387153 and rs10830963 and the risk of gestational diabetes mellitus (GDM). Additionally, the study sought to investigate gene-environment interactions, assess the cumulative genetic risk through the application of Genetic Risk Scores (GRSs), and establish a predictive model for GDM. A case-control study was conducted with 500 GDM patients and 502 controls. MTNR1B gene variants were genotyped using SNPscan™. Associations between clinical data, genetic models, haplotype and GDM risk or blood glucose levels were analyzed using statistical tests. Gene-environment interactions were preliminarily analyzed with GMDR and logistic regression. SNP-age interactions were further explored through stratified analysis and GRS. A predictive model was developed using logistic regression, validated with bootstrap resampling, and its clinical utility was evaluated with decision curve analysis. The study has identified a significant association between the MTNR1B gene variants rs1387153 and rs10830963 and an increased risk of GDM, particularly in women under 30 years of age (all OR > 1, P < 0.05; rs1387153 TT vs. CC: OR = 2.969, P < 0.001, rs10830963 GG vs. CC: OR = 3.066, P < 0.001). The gene-age interaction was found to be statistically significant (P < 0.05). The analysis of the TC haplotype (OR > 1, P < 0.001) and the GRS, specifically in the top quartile of GRS (OR > 3, P < 0.001), further corroborates the cumulative impact of these variants on the risk of GDM among pregnant women under 30 years. The variants also significantly increase postprandial blood glucose levels in pregnant women under 30 years of age (P < 0.05). A predictive model that includes MTNR1B polymorphisms, maternal age, and pre-pregnancy BMI has shown good predictive accuracy for GDM risk (C-Statistics = 0.682, P < 0.001). The study highlights the key role of MTNR1B gene variants rs1387153 and rs10830963 in GDM risk among young pregnant women under the age of 30, with no correlation observed in pregnant women aged 30 and above. The gene-age interaction and GRS provide additional insights into GDM risk. These findings serve as a significant inspiration for future research on populations with MTNR1B gene variations, hopefully prompting more researchers to pay attention to adopting appropriate research, screening, prevention, and intervention strategies for pregnant women with diabetes at different age stages. |
| format | Article |
| id | doaj-art-e474b34c6ce747dd8257dc7bf9ee1025 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Nature Portfolio |
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| spelling | doaj-art-e474b34c6ce747dd8257dc7bf9ee10252025-08-20T03:26:42ZengNature PortfolioScientific Reports2045-23222025-06-0115111610.1038/s41598-025-02248-9MTNR1B variants increase gestational diabetes mellitus risk in young Chinese pregnant womenQiaoli Zeng0Xin Liu1Jia Liu2Yanying Wu3Yuxuan Zhang4Zhaotao He5Yue Wei6Guofang Zeng7Dehua Zou8Runmin Guo9Department of Internal Medicine, Shunde Women and Children’s Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical UniversityDepartment of Internal Medicine, Shunde Women and Children’s Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical UniversityDepartment of Internal Medicine, Shunde Women and Children’s Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical UniversityDepartment of Internal Medicine, Shunde Women and Children’s Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical UniversityDepartment of Internal Medicine, Shunde Women and Children’s Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical UniversityDepartment of Internal Medicine, Shunde Women and Children’s Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical UniversityDepartment of Ultrasound, Shunde Women and Children’s Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical UniversityDepartment of Biology & Pharmacy, Yulin Normal UniversityThe First Affiliated Hospital of Jinan University, and Guangdong Engineering Research Center of Chinese Medicine & Disease Susceptibility, Jinan UniversityDepartment of Internal Medicine, Shunde Women and Children’s Hospital (Maternity and Child Healthcare Hospital of Shunde Foshan), Guangdong Medical UniversityAbstract The aim of this study is to explore the relationship between the MTNR1B gene variants rs1387153 and rs10830963 and the risk of gestational diabetes mellitus (GDM). Additionally, the study sought to investigate gene-environment interactions, assess the cumulative genetic risk through the application of Genetic Risk Scores (GRSs), and establish a predictive model for GDM. A case-control study was conducted with 500 GDM patients and 502 controls. MTNR1B gene variants were genotyped using SNPscan™. Associations between clinical data, genetic models, haplotype and GDM risk or blood glucose levels were analyzed using statistical tests. Gene-environment interactions were preliminarily analyzed with GMDR and logistic regression. SNP-age interactions were further explored through stratified analysis and GRS. A predictive model was developed using logistic regression, validated with bootstrap resampling, and its clinical utility was evaluated with decision curve analysis. The study has identified a significant association between the MTNR1B gene variants rs1387153 and rs10830963 and an increased risk of GDM, particularly in women under 30 years of age (all OR > 1, P < 0.05; rs1387153 TT vs. CC: OR = 2.969, P < 0.001, rs10830963 GG vs. CC: OR = 3.066, P < 0.001). The gene-age interaction was found to be statistically significant (P < 0.05). The analysis of the TC haplotype (OR > 1, P < 0.001) and the GRS, specifically in the top quartile of GRS (OR > 3, P < 0.001), further corroborates the cumulative impact of these variants on the risk of GDM among pregnant women under 30 years. The variants also significantly increase postprandial blood glucose levels in pregnant women under 30 years of age (P < 0.05). A predictive model that includes MTNR1B polymorphisms, maternal age, and pre-pregnancy BMI has shown good predictive accuracy for GDM risk (C-Statistics = 0.682, P < 0.001). The study highlights the key role of MTNR1B gene variants rs1387153 and rs10830963 in GDM risk among young pregnant women under the age of 30, with no correlation observed in pregnant women aged 30 and above. The gene-age interaction and GRS provide additional insights into GDM risk. These findings serve as a significant inspiration for future research on populations with MTNR1B gene variations, hopefully prompting more researchers to pay attention to adopting appropriate research, screening, prevention, and intervention strategies for pregnant women with diabetes at different age stages.https://doi.org/10.1038/s41598-025-02248-9Gestational diabetes mellitusMTNR1B polymorphismsGene-environment interactionsGenetic risk scoresPredictive model |
| spellingShingle | Qiaoli Zeng Xin Liu Jia Liu Yanying Wu Yuxuan Zhang Zhaotao He Yue Wei Guofang Zeng Dehua Zou Runmin Guo MTNR1B variants increase gestational diabetes mellitus risk in young Chinese pregnant women Scientific Reports Gestational diabetes mellitus MTNR1B polymorphisms Gene-environment interactions Genetic risk scores Predictive model |
| title | MTNR1B variants increase gestational diabetes mellitus risk in young Chinese pregnant women |
| title_full | MTNR1B variants increase gestational diabetes mellitus risk in young Chinese pregnant women |
| title_fullStr | MTNR1B variants increase gestational diabetes mellitus risk in young Chinese pregnant women |
| title_full_unstemmed | MTNR1B variants increase gestational diabetes mellitus risk in young Chinese pregnant women |
| title_short | MTNR1B variants increase gestational diabetes mellitus risk in young Chinese pregnant women |
| title_sort | mtnr1b variants increase gestational diabetes mellitus risk in young chinese pregnant women |
| topic | Gestational diabetes mellitus MTNR1B polymorphisms Gene-environment interactions Genetic risk scores Predictive model |
| url | https://doi.org/10.1038/s41598-025-02248-9 |
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