Identification of hub‐methylated differentially expressed genes in patients with gestational diabetes mellitus by multi‐omic WGCNA basing epigenome‐wide and transcriptome‐wide profiling

2020 ◽  
Vol 121 (5-6) ◽  
pp. 3173-3184
Author(s):  
Min Chen ◽  
Jianying Yan ◽  
Qing Han ◽  
Jinying Luo ◽  
Qinjian Zhang
Keyword(s):  
Diabetes Mellitus ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Differentially Expressed Genes ◽  
Differentially Expressed

scholarly journals Identification of differentially expressed genes and signaling pathways in gestational diabetes mellitus by integrated bioinformatics analysis

2021 ◽  
Author(s):  
Basavaraj Mallikarjunayya Vastrad ◽  
Chanabasayya Mallikarjunayya Vastrad
Keyword(s):  
Diabetes Mellitus ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Gene Regulatory Network ◽  
Differentially Expressed Genes ◽  
Regulatory Network ◽  
Molecular Pathogenesis ◽  
Differentially Expressed ◽  
Hub Gene ◽  
Gene Regulatory

Gestational diabetes mellitus (GDM) is a metabolic disorder during pregnancy. Numerous biomarkers have been identified that are linked with the occurrence and development of GDM. The aim of this investigation was to identify differentially expressed genes (DEGs) in GDM using a bioinformatics approach to elucidate their molecular pathogenesis. GDM associated expression profiling by high throughput sequencing dataset (GSE154377) was obtained from Gene Expression Omnibus (GEO) database including 28 normal pregnancy samples and 33 GDM samples. DEGs were identified using DESeq2. The gene ontology (GO) and REACTOME pathway enrichments of DEGs were performed by g:Profiler. Protein-protein interaction (PPI) networks were assembled with Cytoscape software and separated into modules using the PEWCC1 algorithm. MiRNA-hub gene regulatory network and TF-hub gene regulatory network were performed with the miRNet database and NetworkAnalyst database. Receiver Operating Characteristic (ROC) analyses was conducted to validate the hub genes. A total of 953 DEGs were identified, of which 478 DEGs were up regulated and 475 DEGs were down regulated. Furthermore, GO and REACTOME pathway enrichment analysis demonstrated that these DEGs were mainly enriched in multicellular organismal process, cell activation, formation of the cornified envelope and hemostasis. TRIM54, ELAVL2, PTN, KIT, BMPR1B, APP, SRC, ITGA4, RPA1 and ACTB were identified as key genes in the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network. TRIM54, ELAVL2, PTN, KIT, BMPR1B, APP, SRC, ITGA4, RPA1 and ACTB in GDM were validated using ROC analysis. This investigation provides further insights into the molecular pathogenesis of GDM, which might facilitate the diagnosis and treatment of GDM.

scholarly journals Global mRNA and Long Non-Coding RNA Expression in the Placenta and White Adipose Tissue of Mice Fed a High-Fat Diet During Pregnancy

2018 ◽  
Vol 50 (6) ◽  
pp. 2260-2271 ◽  
Author(s):  
Chen Huang ◽  
Bin-bin Huang ◽  
Jian-min Niu ◽  
Yan Yu ◽  
Xiao-yun Qin ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Adipose Tissue ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
High Fat Diet ◽  
Differentially Expressed ◽  
High Fat ◽  
The Core ◽  
Non Coding Rna ◽  
Long Non Coding Rna

Background/Aims: Gestational diabetes mellitus (GDM) is a common complication of pregnancy, but the mechanisms underlying the disorders remain unclear. The study aimed to identify mRNA and long non-coding RNA (lncRNA) profiles in placenta and gonadal fat of pregnant mice fed a high-fat diet and to investigate the transcripts and pathways involved in the development of gestational diabetes mellitus. Methods: Deep and broad transcriptome profiling was performed to assess the expression of mRNAs and lncRNAs in placenta and gonadal fat from 3 mice fed an HFD and chow during pregnancy. Then, differentially expressed mRNAs and lncRNAs were validated by quantitative real-time PCR. The function of the differentially expressed mRNAs was determined by pathway and Gene Ontology (GO) analyses, and the physical or functional relationships between the lncRNAs and the corresponding mRNAs were determined. Results: Our study revealed that 82 mRNAs and 52 lncRNAs were differentially expressed in the placenta of mice fed an HFD during pregnancy, and 202 mRNAs and 120 lncRNAs were differentially expressed in gonadal fat. GO and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed differentially expressed mRNAs of placenta were closely related to extracellular matrix interactions, digestion, adhesion, and metabolism, whereas the differentially expressed mRNAs in adipose tissue were related to metabolic and insulin signalling pathways. The gene network demonstrated that Actg2, Cnfn, Muc16, Serpina3k, NONMMUT068202, and NONMMUT068203, were the core of the network in placental tissue, and the genes Tkt, Acss2, and Elovl6 served as the core of the network in gonadal fat tissue. Conclusion: These newly identified key genes and pathways in mice might provide valuable information regarding the pathogenesis of GDM and might be used to improve early diagnosis, prevention, drug design, and clinical treatment.

scholarly journals Early Second-Trimester Peptidomic Identification of Serum Peptides for Potential Prediction of Gestational Diabetes Mellitus

2018 ◽  
Vol 51 (3) ◽  
pp. 1264-1275 ◽  
Author(s):  
Lingfeng Yin ◽  
Yingying Huai ◽  
Chun Zhao ◽  
Hongjuan Ding ◽  
Tao Jiang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Challenge Test ◽  
Molecular Transport ◽  
Differentially Expressed ◽  
Oral Glucose ◽  
Care Hospital ◽  
Second Trimester ◽  
Serum Samples

Background/Aims: Early screening and diagnosis is important for minimizing gestational adverse outcomes. Routine screening of gestational diabetes mellitus (GDM) at 24–28 weeks with 75 g oral glucose challenge test (OGCT) leaves limited time for intervention and prevention. This study aims to analyze maternal serum peptides in the early second-trimester for prediction of gestational diabetes mellitus (GDM). Methods: Serum samples were collected from 16-18-week pregnant women that visited Nanjing Maternity and Child Health Care Hospital from April to August 2015. According to gestational outcome with or without GDM in late pregnancy, 200 of serum samples from GDM mothers and controls were randomly divided into two subgroups. Peptidomic identification of serum peptides was performed by combining ultrafiltration and liquid chromatography-tandem mass spectrometry (LC-MS/MS) to investigate the differentially-expressed peptides between two groups. Results: A total of 297 identified peptides, originating from 228 proteins, were significantly differentially expressed in the GDM group compared with control. These precursor proteins may play critical roles in cell death of cortical neurons, elongation of cellular protrusions, and stabilization of microtubules. Major networks identified included those involving lipid metabolism, molecular transport and small molecule biochemistry. Conclusion: We provide for the first time a validated peptidome profile of early second-trimester serum in normal and GDM mothers, and we investigated the potential serum biomarkers for GDM. We concluded that 297 peptides could serve as potential biomarkers for GDM.

scholarly journals Integrated Transcriptome Sequencing Analysis Reveals Role of miR-138-5p/ TBL1X in Placenta from Gestational Diabetes Mellitus

2018 ◽  
Vol 51 (2) ◽  
pp. 630-646 ◽  
Author(s):  
Rong Ding ◽  
Fei Guo ◽  
Yong Zhang ◽  
Xi-Mei Liu ◽  
Yu-Qian Xiang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Luciferase Assay ◽  
Control Group ◽  
Sequencing Analysis ◽  
Aberrant Expression

Background/Aims: The placenta has been suggested to play a crucial role in the pathology of gestational diabetes mellitus (GDM). Placenta-specific microRNAs (miRNAs) and the corresponding targeting genes involved in the pathology of GDM still remain to be elucidated. We aimed to identify the dysregulated miRNAs and the corresponding mRNA targets through an integrated miRNA and mRNA transcriptomic profiles analysis and investigate the role of differentially expressed miR-138-5p/TBL1X in GDM. Methods: RNA sequencing (RNA-seq) was performed in 16 placentas from GDM and control group. Differentially expressed mRNAs and miRNAs in GDM were validated by quantitative PCR (qPCR). The wound healing assay and transwell migration assay were used to analyze cell migration ability. The cell proliferation was determined by CCK8 assay. Luciferase assay was used to confirm the direct binding of the targeted TBL1X with miR-138-5p. Results: Totally, 281 mRNAs and 32 miRNAs were found to be differentially expressed in the GDM placentas. The biological relationships of the miRNA/mRNA pairs were related to cellular development and function and organ morphology. Among the aberrantly expressed molecules, we selected miR-138-5p from the bioinformatics analysis and found that miR-138-5p significantly inhibited the migration and proliferation of trophoblasts (HTR-8/SVneo) by targeting the 3’-UTR of TBL1X. Furthermore, the aberrant expression of miR-138-5p and TBL1X was significantly correlated with the weight of the placenta. Conclusion: We present the first integrative analysis of miRNA and mRNA expression profiles in GDM placenta and uncover a more detailed role for miR-138-5p, as well as its target TBL1X in the pathology of GDM.

scholarly journals 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

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Bhushan R ◽  
◽  
Gupta D ◽  
Rani A ◽  
Upadhyay S ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Insulin Signaling ◽  
Enrichment Analysis ◽  
Downstream Processing ◽  
Differentially Expressed ◽  
Regulatory Module ◽  
Micro Rnas ◽  
Mrna Gene

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.

scholarly journals Differentially Expressed Protein Analysis of Placenta from Women with Gestational Diabetes Mellitus using Tandem Mass Tag Quantitative Proteomics

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Sun X ◽  
◽  
Qu T ◽  
Yang X ◽  
He X ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Protein Interaction Network ◽  
Quantitative Proteomics ◽  
Interaction Network ◽  
Differentially Expressed ◽  
Tandem Mass ◽  
Differentially Expressed Proteins ◽  
Tandem Mass Tag

Gestational Diabetes Mellitus (GDM) is one of the diseases occurring in pregnancy. Although normal postpartum glycometabolism can be restored in most patients with GDM, they have a significantly increased risk of developing complications in the future. In recent years, many studies on the screening of differentially expressed proteins have been performed in patients with GDM by means of proteomics, but the pathogenesis of GDM in the placenta was still unclear. Thus, using the Tandem Mass Tag (TMT) quantitative technology, we aimed to identify candidate biomarkers that could predict GDM occurrence early and provide targets for future therapy. Placenta samples were obtained from pregnant women immediately after delivery. Quantitative proteomics was performed using TMT isobaric tags and liquid chromatography-tandem mass spectrometry. Bioinformatic analysis was performed to elucidate the biological processes that these differentially expressed proteins were involved in. Thirtyfive differentially expressed proteins were identified between patients with GDM and normal pregnant women. Therein, 7 and 28 proteins were upregulated and downregulated, respectively. Differentially expressed proteins were mainly enriched in African trypanosomiasis pathway, hematopoietic cell lineage, gap junction, glucagon signaling pathway, and retinol metabolism. Insulin resistance induced by the excessively activated glucagon signaling pathway in the placenta may be one of the reasons for GDM onset. Among the 35 differentially expressed proteins, excluding 12 unknown proteins or antibodies, 17 of the remaining 23 proteins converged to the same protein-protein interaction network, indicating that a highly linked protein interaction network in the placenta of patients with GDM affected the occurrence of disease.

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