Comprehensive analysis of DNA methylation and gene expression profiles in gestational diabetes mellitus

Background Although the WW-domain-containing oxidoreductase (WWOX)/Hypoxia-inducible factor 1 (HIF1) pathway is a well-known regulator of cellular glucose and energy metabolism in pathophysiological processes, its role in gestational diabetes mellitus (GDM), remains elusive. We undertook this study to determine the effect of WWOX/HIF1A signaling on the expression of glucose metabolism genes in GDM patients. Methods Leukocytes were obtained from 135 pregnant women with (n = 98) or without (n = 37) GDM and, in turn, 3 months (n = 8) and 1 year (n = 12) postpartum. Quantitative RT-PCR was performed to determine gene expression profiles of the WWOX/HIF1A-related genes, including those involved in glucose transport (SLC2A1, SLC2A4), glycolytic pathway (HK2, PKM2, PFK, LDHA), Wnt pathway (DVL2, CTNNB1), and inflammatory response (NFKB1). Results GDM patients displayed a significant downregulation of WWOX with simultaneous upregulation of HIF1A which resulted in approximately six times reduction in WWOX/HIF1A ratio. As a consequence, HIF1A induced genes (SLC2A1, HK2, PFK, PKM) were found to be overexpressed in GDM compared to normal pregnancy and negative correlate with WWOX/HIF1A ratio. The postpartum WWOX expression was higher than during GDM, but its level was comparable to that observed in normal pregnancy. Conclusions The obtained results suggest a significant contribution of the WWOX gene to glucose metabolism in patients with gestational diabetes. Decreased WWOX expression in GDM compared to normal pregnancy, and in particular reduction of WWOX/HIF1A ratio, indicate that WWOX modulates HIF1α activity in normal tissues as described in the tumor. The effect of HIF1α excessive activation is to increase the expression of genes encoding proteins directly involved in the glycolysis which may lead to pathological changes in glucose metabolism observed in gestational diabetes.

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Identification of diagnostic biomarkers in patients with gestational diabetes mellitus based on transcriptome gene expression and methylation correlation analysis

Reproductive Biology and Endocrinology ◽

10.1186/s12958-019-0556-x ◽

2019 ◽

Vol 17 (1) ◽

Cited By ~ 1

Author(s):

Enchun Li ◽

Tengfei Luo ◽

Yingjun Wang

Keyword(s):

Gene Expression ◽

Diabetes Mellitus ◽

Dna Methylation ◽

Gestational Diabetes ◽

Gestational Diabetes Mellitus ◽

Enrichment Analysis ◽

Data Sets ◽

Hub Genes ◽

Promoter Regions ◽

The Relationship

Abstract Background Gestational diabetes mellitus (GDM) has a high prevalence in the period of pregnancy. However, the lack of gold standards in current screening and diagnostic methods posed the biggest limitation. Regulation of gene expression caused by DNA methylation plays an important role in metabolic diseases. In this study, we aimed to screen GDM diagnostic markers, and establish a diagnostic model for predicting GDM. Methods First, we acquired data of DNA methylation and gene expression in GDM samples (N = 41) and normal samples (N = 41) from the Gene Expression Omnibus (GEO) database. After pre-processing the data, linear models were used to identify differentially expressed genes (DEGs). Then we performed pathway enrichment analysis to extract relationships among genes from pathways, construct pathway networks, and further analyzed the relationship between gene expression and methylation of promoter regions. We screened for genes which are significantly negatively correlated with methylation and established mRNA-mRNA-CpGs network. The network topology was further analyzed to screen hub genes which were recognized as robust GDM biomarkers. Finally, the samples were randomly divided into training set (N = 28) and internal verification set (N = 27), and the support vector machine (SVM) ten-fold cross-validation method was used to establish a diagnostic classifier, which verified on internal and external data sets. Results In this study, we identified 465 significant DEGs. Functional enrichment analysis revealed that these genes were associated with Type I diabetes mellitus and immunization. And we constructed an interactional network including 1091 genes by using the regulatory relationships of all 30 enriched pathways. 184 epigenetics regulated genes were screened by analyzing the relationship between gene expression and promoter regions’ methylation in the network. Moreover, the accuracy rate in the training data set was increased up to 96.3, and 82.1% in the internal validation set, and 97.3% in external validation data sets after establishing diagnostic classifiers which were performed by analyzing the gene expression profiles of obtained 10 hub genes from this network, combined with SVM. Conclusions This study provided new features for the diagnosis of GDM and may contribute to the diagnosis and personalized treatment of GDM.

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Age-related differences in monocyte DNA methylation and immune function in healthy Kenyan adults and children

Immunity & Ageing ◽

10.1186/s12979-021-00223-2 ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Katherine R. Dobbs ◽

Paula Embury ◽

Emmily Koech ◽

Sidney Ogolla ◽

Stephen Munga ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Young Adults ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Innate Immune ◽

Inflammatory Gene Expression ◽

Cpg Sites ◽

Age Related ◽

Adults And Children

Abstract Background Age-related changes in adaptive and innate immune cells have been associated with a decline in effective immunity and chronic, low-grade inflammation. Epigenetic, transcriptional, and functional changes in monocytes occur with aging, though most studies to date have focused on differences between young adults and the elderly in populations with European ancestry; few data exist regarding changes that occur in circulating monocytes during the first few decades of life or in African populations. We analyzed DNA methylation profiles, cytokine production, and inflammatory gene expression profiles in monocytes from young adults and children from western Kenya. Results We identified several hypo- and hyper-methylated CpG sites in monocytes from Kenyan young adults vs. children that replicated findings in the current literature of differential DNA methylation in monocytes from elderly persons vs. young adults across diverse populations. Differentially methylated CpG sites were also noted in gene regions important to inflammation and innate immune responses. Monocytes from Kenyan young adults vs. children displayed increased production of IL-8, IL-10, and IL-12p70 in response to TLR4 and TLR2/1 stimulation as well as distinct inflammatory gene expression profiles. Conclusions These findings complement previous reports of age-related methylation changes in isolated monocytes and provide novel insights into the role of age-associated changes in innate immune functions.

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A Comprehensive Analysis of Human Gene Expression Profiles Identifies Stromal Immunoglobulin κ C as a Compatible Prognostic Marker in Human Solid Tumors

Clinical Cancer Research ◽

10.1158/1078-0432.ccr-11-2210 ◽

2012 ◽

Vol 18 (9) ◽

pp. 2695-2703 ◽

Cited By ~ 127

Author(s):

Marcus Schmidt ◽

Birte Hellwig ◽

Seddik Hammad ◽

Amnah Othman ◽

Miriam Lohr ◽

...

Keyword(s):

Gene Expression ◽

Solid Tumors ◽

Prognostic Marker ◽

Human Gene ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Comprehensive Analysis ◽

Human Gene Expression ◽

Human Solid Tumors

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Comprehensive analysis of the gene expression profiles in human gastric cancer cell lines

Oncogene ◽

10.1038/sj.onc.1205829 ◽

2002 ◽

Vol 21 (42) ◽

pp. 6549-6556 ◽

Cited By ~ 39

Author(s):

Jiafu Ji ◽

Xin Chen ◽

Suet Yi Leung ◽

Jen-Tsan A Chi ◽

Kent Man Chu ◽

...

Keyword(s):

Gene Expression ◽

Gastric Cancer ◽

Cell Lines ◽

Cancer Cell ◽

Gastric Cancer Cell ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Comprehensive Analysis ◽

Human Gastric Cancer ◽

Gastric Cancer Cell Lines

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Epigenetic Changes in Neonates Born to Mothers With Gestational Diabetes Mellitus May Be Associated With Neonatal Hypoglycaemia

Frontiers in Endocrinology ◽

10.3389/fendo.2021.690648 ◽

2021 ◽

Vol 12 ◽

Author(s):

Yoshifumi Kasuga ◽

Tomoko Kawai ◽

Kei Miyakoshi ◽

Yoshifumi Saisho ◽

Masumi Tamagawa ◽

...

Keyword(s):

Diabetes Mellitus ◽

Dna Methylation ◽

Gestational Diabetes ◽

Gestational Diabetes Mellitus ◽

Start Site ◽

Epigenetic Changes ◽

Neonatal Hypoglycaemia ◽

Transcription Start ◽

Cpg Sites ◽

Alternative Transcription

The detection of epigenetic changes associated with neonatal hypoglycaemia may reveal the pathophysiology and predict the onset of future diseases in offspring. We hypothesized that neonatal hypoglycaemia reflects the in utero environment associated with maternal gestational diabetes mellitus. The aim of this study was to identify epigenetic changes associated with neonatal hypoglycaemia. The association between DNA methylation using Infinium HumanMethylation EPIC BeadChip and neonatal plasma glucose (PG) level at 1 h after birth in 128 offspring born at term to mothers with well-controlled gestational diabetes mellitus was investigated by robust linear regression analysis. Cord blood DNA methylation at 12 CpG sites was significantly associated with PG at 1 h after birth after adding infant sex, delivery method, gestational day, and blood cell compositions as covariates to the regression model. DNA methylation at two CpG sites near an alternative transcription start site of ZNF696 was significantly associated with the PG level at 1 h following birth (false discovery rate-adjusted P < 0.05). Methylation levels at these sites increased as neonatal PG levels at 1 h after birth decreased. In conclusion, gestational diabetes mellitus is associated with DNA methylation changes at the alternative transcription start site of ZNF696 in cord blood cells. This is the first report of DNA methylation changes associated with neonatal PG at 1 h after birth.

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A comprehensive analysis of gene expression profiles in distal parts of the mouse renal tubule

Pflügers Archiv - European Journal of Physiology ◽

10.1007/s00424-010-0863-8 ◽

2010 ◽

Vol 460 (6) ◽

pp. 925-952 ◽

Cited By ~ 24

Author(s):

Sylvain Pradervand ◽

Annie Zuber Mercier ◽

Gabriel Centeno ◽

Olivier Bonny ◽

Dmitri Firsov

Keyword(s):

Gene Expression ◽

Renal Tubule ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Comprehensive Analysis

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Exploring the Mechanism of Skeletal Muscle in a Tacrolimus-Induced Posttransplantation Diabetes Mellitus Model on Gene Expression Profiles

Journal of Diabetes Research ◽

10.1155/2020/6542346 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Chenlei Zheng ◽

Cheng Wang ◽

Tan Zhang ◽

Ding Li ◽

Xiao-feng Ni ◽

...

Keyword(s):

Gene Expression ◽

Diabetes Mellitus ◽

Skeletal Muscle ◽

Muscle Development ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Enrichment Analysis ◽

Quadriceps Muscle ◽

Control Group ◽

Bioinformatics Analyses

Objective. Posttransplantation diabetes mellitus (PTDM) is a known complication of transplantation that affects the prognosis. Tacrolimus (Tac or FK506) is a widely used immunosuppressant that has been reported to be a risk factor for PTDM and to further induce complications in heart and skeletal muscles, but the mechanism is still largely unknown. In our preliminary experiments, we found that after Tac treatment, blood glucose increased, and the weight of skeletal muscle declined. Here, we hypothesize that tacrolimus can induce PTDM and influence the atrophy of skeletal muscle. Methods. We designed preliminary experiments to establish a tacrolimus-induced PTDM model. Gene expression profiles in quadriceps muscle from this rat model were characterized by oligonucleotide microarrays. Then, differences in gene expression profiles in muscle from PTDM rats that received tacrolimus and control subjects were analyzed by using GeneSpring GX 11.0 software (Agilent). Functional annotation and enrichment analysis of differentially expressed genes (DEGs) helped us identify clues for the side effects of tacrolimus. Results. Our experiments found that the quadriceps in tacrolimus-induced PTDM group were smaller than those in the control group. The study identified 275 DEGs that may be responsible for insulin resistance and the progression of PTDM, including 86 upregulated genes and 199 downregulated genes. GO and KEGG functional analysis of the DEGs showed a significant correlation between PTDM and muscle development. PPI network analysis screened eight hub genes and found that they were related to troponin and tropomyosin. Conclusions. This study explored the molecular mechanism of muscle atrophy in a tacrolimus-induced PTDM model by bioinformatics analyses. We identified 275 DEGs and identified significant biomarkers for predicting the development and progression of tacrolimus-induced PTDM.

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