Acta Diabetologica

, Volume 54, Issue 3, pp 309–316 | Cite as

Investigation of miRNA-binding site variants and risk of gestational diabetes mellitus in Chinese pregnant women

  • Xiaojing Wang
  • Wei Li
  • Liangkun Ma
  • Fan Ping
  • Juntao Liu
  • Xueyan Wu
  • Jiangfeng Mao
  • Xi Wang
  • Min Nie
Original Article

Abstract

Aims

Emerging evidence suggested genetic factor attributed as a major determinant for the complex pathogenic mechanism of gestational diabetes mellitus (GDM), but the related genetic study was limited. We aimed to investigate the impact of polymorphisms in miRNA-binding sites (miR-binding SNPs) on the risk of GDM in Chinese Han pregnant women.

Methods

We screened GDM susceptibility genes extensively and selected miR-binding SNPs using four bioinformatics software. TaqMan allelic discrimination assays were applied to miR-binding SNPs genotyping in 839 GDM patients and 900 controls.

Results

In total five potential miR-binding SNPs (SLC30A8 rs2466293, INSR rs1366600, INSR rs3745550, KCNJ11 rs5210 and KCNQ1 rs8234) were selected. Our results showed that SLC30A8 rs2466293 [OR 95% CI = 1.455 (1.077, 1.966); P = 0.014] and INSR rs1366600 [OR 95% CI = 2.191 (1.077, 4.455); P = 0.029] increased the risk of GDM after adjusting age in additive model. Furthermore, rs2466293 was found to significantly associate with higher levels of fasting plasma glucose (b dom = 0.054, P dom = 0.032), 2-h OGTT plasma glucose (b dom = 0.069, P dom = 0.007), lower fasting insulin concentrations (b rec = −0.082, P rec = 0.003) and decreased HOMA-B (b rec = −0.067, P rec = 0.015). Additionally, the correlation between rs1366600 and 2-h OGTT plasma glucose (b dom = 0.078, P dom = 0.001) was observed.

Conclusions

Two miR-binding SNPs SLC30A8 rs2466293 and INSR rs1366600 increased GDM susceptibility. Functional studies were required to confirm the underlying mechanism. Our study provided additional insights into the genetic pathogenesis of GDM.

Keywords

Gestational diabetes mellitus Variants miRNA Glucose metabolism 

Notes

Acknowledgements

We thank for all the participants in this study. The study was funded by research grants from the National Natural Science Foundation of China (Grant No. 81270879) and National Key Program of Clinical Science (WBYZ2011873).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical standard

All procedures performed in this study involving human participants were in accordance with the ethical standards of the Peking Union Medical College Hospital Ethics Committee.

Human and animal rights

The study was conducted in accordance with the principles of the Declaration of Helsinki of 1975, as revised in 2008.

Informed consent

Informed consent was obtained from all patients for being included in the study.

Supplementary material

592_2017_969_MOESM1_ESM.docx (283 kb)
Supplementary material 1 (DOCX 283 kb)

References

  1. 1.
    Agha-Jaffar R, Oliver N, Johnston D, Robinson S (2016) Gestational diabetes mellitus: does an effective prevention strategy exist? Nat Rev Endocrinol 12(9):533–546CrossRefPubMedGoogle Scholar
  2. 2.
    Ferrara A (2007) Increasing prevalence of gestational diabetes mellitus: a public health perspective. Diabetes Care 30(Suppl 2):S141–S146CrossRefPubMedGoogle Scholar
  3. 3.
    Zhu WW, Fan L, Yang HX et al (2013) Fasting plasma glucose at 24-28 weeks to screen for gestational diabetes mellitus: new evidence from China. Diabetes Care 36(7):2038–2040CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Group HSCR, Metzger BE, Lowe LP et al (2008) Hyperglycemia and adverse pregnancy outcomes. N Engl J Med 358(19):1991–2002CrossRefGoogle Scholar
  5. 5.
    Yang X, Hsu-Hage B, Zhang H et al (2002) Women with impaired glucose tolerance during pregnancy have significantly poor pregnancy outcomes. Diabetes Care 25(9):1619–1624CrossRefPubMedGoogle Scholar
  6. 6.
    Bellamy L, Casas JP, Hingorani AD, Williams D (2009) Type 2 diabetes mellitus after gestational diabetes: a systematic review and meta-analysis. Lancet 373(9677):1773–1779CrossRefPubMedGoogle Scholar
  7. 7.
    Hillier TA, Pedula KL, Schmidt MM et al (2007) Childhood obesity and metabolic imprinting: the ongoing effects of maternal hyperglycemia. Diabetes Care 30(9):2287–2292CrossRefPubMedGoogle Scholar
  8. 8.
    Al Mamun A, O’Callaghan MJ, Williams GM et al (2015) Breastfeeding is protective to diabetes risk in young adults: a longitudinal study. Acta Diabetol 52(5):837–844CrossRefPubMedGoogle Scholar
  9. 9.
    Sesmilo G, Meler E, Perea V et al (2017) Maternal fasting glycemia and adverse pregnancy outcomes in a Mediterranean population. Acta Diabetologica. doi: 10.1007/s00592-016-0952-z
  10. 10.
    de Seymour JV, Conlon CA, Sulek K et al (2014) Early pregnancy metabolite profiling discovers a potential biomarker for the subsequent development of gestational diabetes mellitus. Acta Diabetol 51(5):887–890CrossRefPubMedGoogle Scholar
  11. 11.
    Zhao C, Wang F, Wang P et al (2015) Early second-trimester plasma protein profiling using multiplexed isobaric tandem mass tag (TMT) labeling predicts gestational diabetes mellitus. Acta Diabetol 52(6):1103–1112CrossRefPubMedGoogle Scholar
  12. 12.
    Poulsen P, Levin K, Petersen I et al (2005) Heritability of insulin secretion, peripheral and hepatic insulin action, and intracellular glucose partitioning in young and old Danish twins. Diabetes 54(1):275–283CrossRefPubMedGoogle Scholar
  13. 13.
    Kwak SH, Kim SH, Cho YM et al (2012) A genome-wide association study of gestational diabetes mellitus in Korean women. Diabetes 61(2):531–541CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Zhang C, Bao W, Rong Y et al (2013) Genetic variants and the risk of gestational diabetes mellitus: a systematic review. Hum Reprod Updat 19(4):376–390CrossRefGoogle Scholar
  15. 15.
    Bartel DP (2009) MicroRNAs: target recognition and regulatory functions. Cell 136(2):215–233CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Ozcan S (2014) Minireview: microRNA function in pancreatic beta cells. Mol Endocrinol 28(12):1922–1933CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Ryan BM, Robles AI, Harris CC (2010) Genetic variation in microRNA networks: the implications for cancer research. Nat Rev Cancer 10(6):389–402CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Lei SF, Papasian CJ, Deng HW (2011) Polymorphisms in predicted miRNA binding sites and osteoporosis. J Bone Miner Res: Off J Am Soc Bone Min Res 26(1):72–78CrossRefGoogle Scholar
  19. 19.
    Goda N, Murase H, Kasezawa N, Goda T, Yamakawa-Kobayashi K (2015) Polymorphism in microRNA-binding site in HNF1B influences the susceptibility of type 2 diabetes mellitus: a population based case-control study. BMC Med Genet 16:75CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Wang X, Li W, Ma L et al (2015) Association study of the miRNA-binding site polymorphisms of CDKN2A/B genes with gestational diabetes mellitus susceptibility. Acta Diabetol 52(5):951–958CrossRefPubMedGoogle Scholar
  21. 21.
    American Diabetes A (2010) Diagnosis and classification of diabetes mellitus. Diabetes Care 33(Suppl 1):S62–S69CrossRefGoogle Scholar
  22. 22.
    Chimienti F, Devergnas S, Favier A, Seve M (2004) Identification and cloning of a beta-cell-specific zinc transporter, ZnT-8, localized into insulin secretory granules. Diabetes 53(9):2330–2337CrossRefPubMedGoogle Scholar
  23. 23.
    Chimienti F, Favier A, Seve M (2005) ZnT-8, a pancreatic beta-cell-specific zinc transporter. Biometals: Int J Role Metal Ions Biol, Biochem, Med 18(4):313–317CrossRefGoogle Scholar
  24. 24.
    Chabosseau P, Rutter GA (2016) Zinc and diabetes. Arch Biochem Biophys 611:79–85CrossRefPubMedGoogle Scholar
  25. 25.
    Sladek R, Rocheleau G, Rung J et al (2007) A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature 445(7130):881–885CrossRefPubMedGoogle Scholar
  26. 26.
    Fan M, Li W, Wang L et al (2016) Association of SLC30A8 gene polymorphism with type 2 diabetes, evidence from 46 studies: a meta-analysis. Endocrine 53(2):381–394CrossRefPubMedGoogle Scholar
  27. 27.
    Xu M, Bi Y, Xu Y et al (2010) Combined effects of 19 common variations on type 2 diabetes in Chinese: results from two community-based studies. PLoS One 5(11):e14022CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Xiang J, Li XY, Xu M et al (2008) Zinc transporter-8 gene (SLC30A8) is associated with type 2 diabetes in Chinese. The Journal of clinical endocrinology and metabolism 93(10):4107–4112CrossRefPubMedGoogle Scholar
  29. 29.
    Pound LD, Sarkar SA, Benninger RK et al (2009) Deletion of the mouse Slc30a8 gene encoding zinc transporter-8 results in impaired insulin secretion. Biochem J 421(3):371–376CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Wijesekara N, Dai FF, Hardy AB et al (2010) Beta cell-specific Znt8 deletion in mice causes marked defects in insulin processing, crystallisation and secretion. Diabetologia 53(8):1656–1668CrossRefPubMedGoogle Scholar
  31. 31.
    Rutter GA, Chimienti F (2015) SLC30A8 mutations in type 2 diabetes. Diabetologia 58(1):31–36CrossRefPubMedGoogle Scholar
  32. 32.
    Tamaki M, Fujitani Y, Hara A et al (2013) The diabetes-susceptible gene SLC30A8/ZnT8 regulates hepatic insulin clearance. J Clin Investig 123(10):4513–4524CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Ober C, Xiang KS, Thisted RA et al (1989) Increased risk for gestational diabetes mellitus associated with insulin receptor and insulin-like growth factor II restriction fragment length polymorphisms. Genet Epidemiol 6(5):559–569CrossRefPubMedGoogle Scholar
  34. 34.
    Zhao X, Ye Q, Xu K et al (2013) Single-nucleotide polymorphisms inside microRNA target sites influence the susceptibility to type 2 diabetes. J Hum Genet 58(3):135–141CrossRefPubMedGoogle Scholar
  35. 35.
    Lewis BP, Shih IH, Jones-Rhoades MW, Bartel DP, Burge CB (2003) Prediction of mammalian microRNA targets. Cell 115(7):787–798CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag Italia 2017

Authors and Affiliations

  • Xiaojing Wang
    • 1
  • Wei Li
    • 1
  • Liangkun Ma
    • 2
  • Fan Ping
    • 1
  • Juntao Liu
    • 2
  • Xueyan Wu
    • 1
  • Jiangfeng Mao
    • 1
  • Xi Wang
    • 1
  • Min Nie
    • 1
  1. 1.Key Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College HospitalChinese Academy of Medical SciencesBeijingChina
  2. 2.Department of Obstetrics and Gynecology, Peking Union Medical College HospitalChinese Academy of Medical SciencesBeijingChina

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