Analysis of Micro-RNAs Profile Identifies miR-3065-3p, miR-4650-3p, miR-29b-2-5p, and miR-3915 as Novel Biomarkers in Gestational Diabetes Mellitus

Research Article

J Endocr Disord. 2021; 7(1): 1044.

Analysis of Micro-RNAs Profile Identifies miR-3065-3p, miR-4650-3p, miR-29b-2-5p, and miR-3915 as Novel Biomarkers in Gestational Diabetes Mellitus

Bhushan R1, Gupta D2, Rani A3, Upadhyay S1, Tripathi A4 and Dubey PK1*

1Banaras Hindu University, Centre for Genetic Disorders, Institute of Science, India

2Department of Obstetrics and Gynecology, Ashirwad Hospital, India

3Department of Obstetrics and Gynecology, Banaras Hindu University, India

4Department of Zoology, MMV, Banaras Hindu University, India

*Corresponding author: Pawan K Dubey, Banaras Hindu University, Centre for Genetic Disorders, Institute of Science, Varanasi-221005, India

Received: February 15, 2021; Accepted: March 11, 2021; Published: March 18, 2021


Background: Gestational Diabetes Mellitus (GDM) is a metabolic disorder characterized by carbohydrate intolerance. Complete mechanisms involved in pathophysiology of GDM are still not well known and hence makes its early diagnosis and treatment a difficult task. Micro-RNAs are non-coding RNAs and have been found to be associated with many diseases including GDM. Methods: Here, we analyzed the transcriptomic datasets (GSE98043) to unravel the role of miRNAs in GDM. We processed and analyzed the microarray datasets to find differentially expressed miRNAs followed by miRNA-mRNA gene regulatory module to have a better understanding of its regulation.

Results: We identified a total of 128 Differentially Expressed (DE) miRNAs, of which the top 20 were selected for downstream processing. Four potential GDM miRNAs biomarkers namely miR-3065-3p, miR-4650-3p, miR-29b-2- 5p and miR-3915 were significantly altered in GDM. The micro-RNAs were linked to carbohydrate metabolism, insulin signaling, and cell proliferation and apoptosis. The pathways enrichment analysis shows that they are involved in insulin signaling and pathways related to cancer.

Conclusions: Our study lead to the identification of four potential GDM miRNAs biomarkers namely miR-3065-3p, miR-4650-3p, miR-29b-2-5p and miR-3915 were significantly altered in GDM and can be used as diagnostic as well as therapeutic purpose.

Keywords: Gestational diabetes mellitus; Micro-RNAs; Bio-markers; Genes; Gene ontology


Gestational Diabetes Mellitus (GDM) is defined as any degree of carbohydrate intolerance, with onset or first recognition during the second or third trimester of pregnancy [1]. GDM complicates around 7% of all pregnancies while it comprises 90-95 % of all cases of diabetes in pregnancy. It is a major cause of perinatal morbidity and mortality, as well as maternal long term morbidity. The pathophysiology of GDM is still not fully characterized. Gestational diabetes mellitus is a metabolic disorder characterized by insulin resistance accompanied by low/absent beta-cell compensatory adaptation to the increased insulin demands [2].

MicroRNAs (miRNAs) are endogenous ~19-24 nt small noncoding RNAs that modulate gene expression by inducing the translational arrest and degradation of messenger RNAs. Micro-RNA is highly versatile as a single miRNA can potentially modulate multiple genes, whereas a single gene can be regulated by several miRNAs [3]. Such complex nature of miRNAs justifies its role in virtually every cellular process, as well as in development or differentiation, regulation of cell cycle [4], and immune system homeostasis [5]. Recently, several studies have reported the role of miRNAs in multiple sides of beta-cell function and differentiation [6], both in normal and diabetic conditions, as well as in beta-cell compensatory processes during pregnancy. Therefore a deep understanding of microRNA functions and genes and pathways related to it could improve the knowledge on the etiology and pathophysiology of GDM and its complications. Furthermore, due to their high stability in body fluids and their accessibility from maternal blood throughout gestation, they could serve as biomarkers for the early diagnosis and treatment of GDM.

This study aims to find altered miRNAs in GDM and their potential validated target genes, the determination of the most important miRNAs, and their related genes and pathways in Gestational Diabetes Mellitus. Here we investigated and identified GDM related Differentially Expressed miRNAs (DEmiRNAs), validated GDM related target genes, miRNA-mRNA interactions, and signaling pathways. Our results showed 128 DEmiRNAs of which the top 20 was considered for further analysis. Target genes were predicted and a consensus-based approach leads to the identification of validated GDM related target genes. Of the 128miRNAs, miR-3065-3p, miR- 4650-3p, miR-29b-2-5p, and miR-3915 are the most novel promising biomarker. Besides, Functional and pathways enrichment showed that these miRNA and their target genes have important roles in GDM and insulin metabolism.


Microarray data

Micro-RNA expression profile (GSE ID: GSE98043) datasets of human GDM have been selected that are available in the public repository: NCBI Gene Expression Omnibus (GEO) (http://www. [7]. In this study, plasma from 4 pregnant women (2 from normal controls and 2 from GDM patients) were used. The Subjects were of Asian (Chinese) ethnicity and this microarray study was earlier approved by local Chinese ethics committee and participants; here we are just accessing the data from NCBI and analyzing them.

Data preprocessing and differentially expressed miRNA in GDM

The Series matrix file was downloaded and processed. The probe-level symbols were converted into gene-level symbols by using GEO2R [8]. Analyzing GDM has been done in two groups NGT (Normal Glucose Tolerant) control and GDM patients using the GEO2R tool, to detect the differentially expressed miRNAs. Top 20 differentially expressed miRNAs have been selected, of which 10 were highly up-regulated while 10 were highly down-regulated. The selection of miRNA was based on fold change value. All miRNA selected have P-values less than 0.05.

Identification of miRNA-target gene

Target genes of DE miRNAs, were identified from two databases namely Target scan [9] and miRDB [10]. Common target genes in both databases and having a target score >90 were selected and uploaded in STRING [11] for further analysis. Further CS>0.9 were taken as criteria for gene selection. Genes with TS>90 and CS>0.9 were selected.

Construction of miRNAs and mRNAs regulatory module (MMRM)

Target genes with a combined score >0.9 were then uploaded in Cytoscape 3.2.1 [12] and MicroRNA-mRNA Regulatory Module (MMRM) were constructed for up-miRNA and down-miRNA jointly. The network was analyzed and edge between ness was taken as criteria for network construction. Color and node size were attributed on the miRNA-target genes network to identify miRNA, mRNA, and GDM specific genes.

Enriched Gene Ontology and pathway analysis

Biological processes, molecular function, cellular component, and their related pathways in GDM related miRNA-target gene were identified using DAVID 7.6 [13]. Based on hypergeometric distribution, DAVID takes the genes with similar or related functions as a whole set. Significant functions were plotted against –log10 of the p-value for up and down miRNA-target genes separately. In this analysis p-value<0.05 was set as the criterion.


Micro-RNA expression profile

Micro-RNA data sets were normalized and preprocessed to get expression profiles (Figure 1). Based on, A total of 128 differentially expressed miRNAs, 63 Up-regulated, and 65 Down-regulated miRNAs (p-value<0.005; fold change value ≥1.5) were identified in GDM. Out of these 128, top 20 differentially expressed miRNAs: 10 Up-miRs and 10 Down-miRs were selected for further study (Figure 2).