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MTNR1B gene on susceptibility to gestational diabetes mellitus: a two-stage hospital-based study in Southern China

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Abstract

Large-scale studies on genetic risk loci for melatonin receptor 1B (MTNR1B) gene and GDM risk have not been well generalized to the Chinese population. In this study, we performed two-stage case–control study: 1.429 pregnant women: 753 GDM/676 controls in the Southern Chinese population by genotyping 5 SNPs (rs10830963, rs1387153, rs2166706, rs1447352, and rs4753426) in MTNR1B. Genotypes were determined using the Sequenom MassARRAY platform and TaqMan allelic discrimination assay. Interactions between genetic variants and age/BMI as predictors of GDM risk were evaluated under the logistic regression model. In the first stage, the SNP rs10830963 was discovered to be potentially related to GDM risk (additive model: OR = 1.27, 95%CI = 1.05–1.55, P = 0.025), which was further confirmed in the second stage with a similar effect (additive model: OR = 1.53, 95%CI = 1.19–1.98, P = 0.005). In the combined stage, the G allele of rs10830963 was potentially associated with GDM risk (additive model: OR = 1.36, 95%CI = 1.17–1.59, P < 0.001; dominant model: OR = 1.45, 95%CI = 1.15–1.83, P = 0.005). The rs10830963 interacted with age and BMI to contribute to GDM risk in the combined participants. And, the similar interactive effects for the other four SNPs also exist. These findings offer the potential to improve our understanding of the etiology of GDM, and particularly of biological mechanisms.

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Data availability

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available because of privacy or ethical restrictions.

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Acknowledgements

This study was supported by the Shanghai Municipal Health Commission (201840297), and supported by Construction project of Shanghai Key Laboratory of Molecular Imaging(18DZ2260400), Shanghai Municipal Education Commission (Class II Plateau Disciplinary Construction Program of Medical Technology of SUMHS, 2018–2020), and supported by Nantong Science and Technology Plan-Frontiers and Key Technologies (MS12017013-3).

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Author notes

  1. Yulong Jia and Yi Shen contributed equally to the paper and Aiyong Zhu and Liying Jiang joined directly to the paper.

Authors and Affiliations

  1. Department of Epidemiology and Medical Statistics, School of Public Health, Nantong University, Nantong, Jiangsu, China

    Yulong Jia, Yi Shen & Xiuying Shi

  2. Shanghai Key Laboratory for Molecular Imaging, University of Medicine and Health Sciences, Shanghai, People’s Republic of China

    Xuefeng Gu & Liying Jiang

  3. School of Clinical Medicine, University of Medicine and Health Sciences, Shanghai, People’s Republic of China

    Peng Zhang

  4. Department of Obstetrics and Gynecology, Nantong University Affiliated Hospital, Nantong, Jiangsu, China

    Yuanlin Liu

  5. School of Nursing and Health Management, University of Medicine and Health Sciences, Shanghai, People’s Republic of China

    Aiyong Zhu

  6. Jiading District Central Hospital, Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China

    Liying Jiang

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  1. Yulong Jia
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Contributions

L.Y.J. contributed to the interpretation of results and made critical revisions. Y.L.J. drafted the protocol and wrote the final paper. X.Y.S., X.F.G., P.Z., Y.L.L, A.Y.Z., participated in the data collection. And, Y.S. reviewed the draft and made the critical revision. All authors have reviewed the final version of the manuscript and approved it for publication.

Corresponding author

Correspondence to Liying Jiang.

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Conflict of interest

Yulong Jia declares that he has no conflict of interest. Yi Shen declares that she has no conflict of interest. Xiuying Shi declares that she has no conflict of interest. Xuefeng Gu declares that he has no conflict of interest. Peng Zhang declares that he has no conflict of interest. Yuanlin Liu declares that he has no conflict of interest. Aiyong Zhu declares that he has no conflict of interest. Liying Jiang declares that she has no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Novelty statements

  • The rs10830963 in MTNR1B could modify individual susceptibility to gestational diabetes mellitus(GDM) in the study population.

  • The rs10830963 interacted with age and BMI to contribute to GDM risk. Similar interactive effects for the other 4 SNPs also exist.

Additional information

Communicated by Stefan Hohmann.

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Jia, Y., Shen, Y., Shi, X. et al. MTNR1B gene on susceptibility to gestational diabetes mellitus: a two-stage hospital-based study in Southern China. Mol Genet Genomics 295, 1369–1378 (2020). https://doi.org/10.1007/s00438-020-01706-5

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