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Gene coexpression network analysis identified potential biomarkers in gestational diabetes mellitus progression.

ABSTRACT: BACKGROUND:Gestational diabetes mellitus (GDM) is one of the most common problems during pregnancy. Lack of international consistent diagnostic procedures has limit improvement of current therapeutic effectiveness. Here, we aimed to screen potential gene biomarkers that might play vital roles in GDM progression for assistance of its diagnostic and treatment. METHODS:Gene expression profiles in four GDM placentae at first trimester, four GDM placentae at second trimester, and four normal placentae were obtained from the publicly available Gene Expression Omnibus (GEO). Weighted gene coexpression network analysis (WGCNA) indicated two gene modules, that is, black and brown module, that was significantly positively and negatively correlated with GDM progression time points, respectively. Additionally, a significant positive correlation between module membership (MM) and degree in protein-protein interaction network of brown module genes was observed. RESULTS:KIF2C, CENPE, CCNA2, AURKB, MAD2L1, CCNB2, CDC20, PLK1, CCNB1, and CDK1 all have degree larger than 50 and MM larger than 0.9, so they might be valuable biomarkers in GDM. Gene set enrichment analysis inferred tight relations between carbohydrate metabolism or steroid biosynthesis-related processes and GDM progression. CONCLUSIONS:All in all, our study should provide several novel references for GDM diagnosis and therapeutic.

SUBMITTER: Zhao X

PROVIDER: S-EPMC6382444 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Gene coexpression network analysis identified potential biomarkers in gestational diabetes mellitus progression.

Zhao Xiaomin X Li Wen W

Molecular genetics & genomic medicine 20181125 1

<h4>Background</h4>Gestational diabetes mellitus (GDM) is one of the most common problems during pregnancy. Lack of international consistent diagnostic procedures has limit improvement of current therapeutic effectiveness. Here, we aimed to screen potential gene biomarkers that might play vital roles in GDM progression for assistance of its diagnostic and treatment.<h4>Methods</h4>Gene expression profiles in four GDM placentae at first trimester, four GDM placentae at second trimester, and four ...[more]

PMID: 30474315

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Project description:BackgroundType 2 diabetes mellitus (T2DM) is characterized by chronic low-grade inflammation, showing an increasing trend. The infiltration of immune cells into adipose tissue has been shown to be an important pathogenic cause of T2DM. The purpose of this study is to use the relevant database to identify some abnormally expressed or dysfunctional genes related to diabetes from the perspective of immune infiltration.MethodsWeighted gene coexpression network analysis (WGCNA) was employed to systematically identify the coexpressed gene modules and hub genes associated with T2DM development based on a microarray dataset (GSE23561) from the Gene Expression Omnibus (GEO) database. The key genes in modules highly related to clinical features were calculated and screened by using R software, and their participation in T2DM was determined by gene enrichment analysis. The mRNA levels of CSF1R, H2AFV, LCK, and TLR9 in pre-T2DM mice and normal wild-type mice were detected by WGCNA screening and real-time quantitative reverse transcriptase polymerase chain reaction (qRT-PCR).ResultsWe constructed 14 coexpressed gene modules, and the brown module was shown to be significantly related to T2DM. Through verification of the protein-protein interaction (PPI) network, four upregulated hub genes, CSF1R, H2AFV, LCK, and TLR9, were screened from the brown module and successfully distinguishedT2DM patients from healthy people. These hub genes may be used as biomarkers and important indicators for patient diagnosis. Enrichment analysis showed that these hub genes were highly associated with IL-6-related inflammatory metabolism, immune regulation, and immune cell infiltration. Finally, we verified the hub genes CSF1R, LCK, and TLR9 in a T2DM animal model and found that their mRNA levels were significantly higher in animals with T2DM than in control group mice (NC).ConclusionsIn summary, our results suggest that these hub genes (CSF1R, LCK, and TLR9) can serve as biomarkers and immunotherapeutic targets for T2DM.

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Gene coexpression network analysis identified potential biomarkers in gestational diabetes mellitus progression.

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Gene coexpression network analysis identified potential biomarkers in gestational diabetes mellitus progression.

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