Online first
Research paper
Published online: 2023-03-10

open access

Page views 491
Article views/downloads 359
Get Citation

Connect on Social Media

Connect on Social Media

A preliminary integrated analysis of miRNA-mRNA expression profiles reveals a role of miR-146a-3p/TRAF6 in plasma from gestational diabetes mellitus patients

Min Chen1, Jianying Yan1


Objectives: To utilize an integrative strategy to construct functional miRNA-mRNA regulatory networks by combining the reverse expression relationships between miRNAs and targets and computational predictions for gestational diabetes mellitus (GDM).

Material and methods: A total of three microarray or RNA-seq datasets (GSE98043, GSE19649 and GSE92772) of plasma samples comparing GDM pregnant women and healthy control pregnant women were downloaded from the GEO database. The differentially expressed genes (DEmRNAs) and the differentially expressed miRNAs (DEmiRNAs) was performed. The target genes of DEmiRNAs were identified using two independent and complementary types of information: computational target predictions and expression relationships. An interaction network was constructed to identify hub genes of GDM. Another dataset (GSE92772) was used to externally verify the predictive ability of the hub genes.

Results: A total of 264 DEmiRNAs and 1217 DEmRNAs were identified with Hsa-miR-146a-3p ranked first of DEmiRNAs. Functions of GDM-related miRNAs were mainly enriched in the glypican pathway, proteoglycan syndecan-mediated signaling events, and syndecan-1-mediated signaling events. A total of 47 target genes, including TRAF6, were shared between the computational target predictions and DEmRNAs and were identified as target genes of hsa-miR-146a-3p. The interaction network analysis identified TRAF6, CASP8, PTPN6, and CHD3 as hub genes involved in the pathophysiological process of GDM. Next, independent external validation was performed using the GSE19649 dataset. The expression of TRAF6, CASP8 and CHD3 in eight pairs of GDM blood samples was confirmed to be higher than that in healthy pregnant women blood samples with a AUC of 0.813, 0.813, and 0.703, respectively.

Conclusions: Our preliminary analysis revealed that miR-146a-3p/TRAF6 might play a central role in the pathogenesis of GDM. Three hub genes, TRAF6, CASP8, and CHD3, were identified and independently externally validated as potential GDM noninvasive serum markers for future biomarkers research.

Article available in PDF format

View PDF Download PDF file


  1. Huang WQ, Lu Y, Xu M, et al. Excessive fruit consumption during the second trimester is associated with increased likelihood of gestational diabetes mellitus: a prospective study. Sci Rep. 2017; 7: 43620.
  2. Zhang Q, He M, Wang J, et al. Predicting of disease genes for gestational diabetes mellitus based on network and functional consistency. Eur J Obstet Gynecol Reprod Biol. 2015; 186: 91–96.
  3. Robitaille J, Grant AM. The genetics of gestational diabetes mellitus: evidence for relationship with type 2 diabetes mellitus. Genet Med. 2008; 10(4): 240–250.
  4. Loeken MR. Passive smoking as an independent risk factor for gestational diabetes that synergizes with prepregnancy obesity in urban Chinese women. Diabetes Metab Res Rev. 2017; 33(6).
  5. Sayed D, Abdellatif M. MicroRNAs in development and disease. Physiol Rev. 2011; 91(3): 827–887.
  6. Poirier C, Desgagné V, Guérin R, et al. MicroRNAs in Pregnancy and Gestational Diabetes Mellitus: Emerging Role in Maternal Metabolic Regulation. Curr Diab Rep. 2017; 17(5): 35.
  7. Kizilgul M, Kan S, Beysel S, et al. Is fibroblast growth factor 23 a new cardiovascular risk marker in gestational diabetes? Arch Endocrinol Metab. 2017; 61(6): 562–566.
  8. Zhao W, Pan J, Li H, et al. Relationship between High Serum Cystatin C Levels and the Risk of Gestational Diabetes Mellitus. PLoS One. 2016; 11(2): e0147277.
  9. Cao YL, Jia YJ, Xing BH, et al. Plasma microRNA-16-5p, -17-5p and -20a-5p: Novel diagnostic biomarkers for gestational diabetes mellitus. J Obstet Gynaecol Res. 2017; 43(6): 974–981.
  10. Wang F, Li Z, Zhao M, et al. Circulating miRNAs miR-574-5p and miR-3135b are potential metabolic regulators for serum lipids and blood glucose in gestational diabetes mellitus. Gynecol Endocrinol. 2021; 37(7): 665–671.
  11. Zhao YH, Wang DP, Zhang LL, et al. Genomic expression profiles of blood and placenta reveal significant immune-related pathways and categories in Chinese women with gestational diabetes mellitus. Diabet Med. 2011; 28(2): 237–246.
  12. Stirm L, Huypens P, Sass S, et al. Maternal whole blood cell miRNA-340 is elevated in gestational diabetes and inversely regulated by glucose and insulin. Sci Rep. 2018; 8(1): 1366.
  13. Davis S, Meltzer PS. GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor. Bioinformatics. 2007; 23(14): 1846–1847.
  14. Tokar T, Pastrello C, Rossos AEM, et al. mirDIP 4.1-integrative database of human microRNA target predictions. Nucleic Acids Res. 2018; 46(D1): D360–D370.
  15. Pathan M, Keerthikumar S, Ang CS, et al. FunRich: An open access standalone functional enrichment and interaction network analysis tool. Proteomics. 2015; 15(15): 2597–2601.
  16. Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004; 116(2): 281–297.
  17. Filmus J, Selleck S. Glypicans: proteoglycans with a surprise. Journal of Clinical Investigation. 2001; 108(4): 497–501.
  18. Murthi P, Sarkis R, Lim R, et al. Endocan expression is increased in the placenta from obese women with gestational diabetes mellitus. Placenta. 2016; 48: 38–48.
  19. Chen CP, Chang SC, Vivian Yang WC. High glucose alters proteoglycan expression and the glycosaminoglycan composition in placentas of women with gestational diabetes mellitus and in cultured trophoblasts. Placenta. 2007; 28(2-3): 97–106.
  20. Yang WCV, Su TH, Yang YC, et al. Altered perlecan expression in placental development and gestational diabetes mellitus. Placenta. 2005; 26(10): 780–788.
  21. Leelalertlauw C, Korwutthikulrangsri M, Mahachoklertwattana P, et al. Serum glypican 4 level in obese children and its relation to degree of obesity. Clin Endocrinol (Oxf). 2017; 87(6): 689–695.
  22. Ussar S, Bezy O, Blüher M, et al. Glypican-4 enhances insulin signaling via interaction with the insulin receptor and serves as a novel adipokine. Diabetes. 2012; 61(9): 2289–2298.
  23. Liu XS, Fan B, Szalad A, et al. MicroRNA-146a Mimics Reduce the Peripheral Neuropathy in Type 2 Diabetic Mice. Diabetes. 2017; 66(12): 3111–3121.
  24. Park H, Huang X, Lu C, et al. MicroRNA-146a and microRNA-146b regulate human dendritic cell apoptosis and cytokine production by targeting TRAF6 and IRAK1 proteins. J Biol Chem. 2015; 290(5): 2831–2841.
  25. Liu R, Shen H, Wang T, et al. TRAF6 mediates high glucose-induced endothelial dysfunction. Exp Cell Res. 2018; 370(2): 490–497.