scholarly journals Genome-Wide DNA Methylation Changes Associated with Intermittent Explosive Disorder: A Gene-Based Functional Enrichment Analysis

2017 ◽  
Vol 21 (1) ◽  
pp. 12-20 ◽  
Author(s):  
Janitza L Montalvo-Ortiz ◽  
Huiping Zhang ◽  
Chao Chen ◽  
Chunyu Liu ◽  
Emil F Coccaro
Keyword(s):  
Dna Methylation ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Intermittent Explosive Disorder ◽  
Genome Wide

scholarly journals Monozygotic Twins Discordant for Immunoglobulin A Nephropathy Display Differences in DNA Methylation and Gene Expression

2020 ◽  
pp. 1-10
Author(s):  
Min Wei ◽  
Sijun Meng ◽  
Sufang Shi ◽  
Lijun Liu ◽  
Xujie Zhou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Expression Profiles ◽  
Immunoglobulin A ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Genome Wide ◽  
Mz Twins

<b><i>Introduction:</i></b> Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulonephritis. It involves both genetic and environmental factors, among which DNA methylation, the most studied epigenetic modification, was shown to play a role. Here, we assessed genome-wide DNA methylation and gene expression profiles in 2 pairs of IgAN-discordant monozygotic (MZ) twins, in order to characterize methylation changes and their potential influences on gene expression in IgAN. <b><i>Methods:</i></b> Genome-wide DNA methylation and gene expression profiles were evaluated in peripheral blood mononuclear cells obtained from 2 IgAN-discordant MZ twins. Differentially methylated regions (DMRs) and differentially expressed genes (DEGs) were detected, and an integrated analysis was performed. Finally, functional enrichment analysis was done for DMR-associated genes and DEGs. <b><i>Results:</i></b> Totally 521 DMRs were detected for 2 IgAN-discordant MZ twins. Among them, 9 DMRs were found to be mapped to genes that differentially expressed in 2 MZ twins, indicating the potential regulatory mechanisms of expression for these 9 genes (<i>MNDA</i>, <i>DYSF</i>, <i>IL1R2</i>, <i>TLR6</i>, <i>TREML2</i>, <i>TREM1</i>, <i>IL32</i>, <i>S1PR5</i>, and <i>ADGRE3</i>) in IgAN. Biological process analysis of them showed that they were mostly involved in the immune system process. Functional enrichment analysis of DEGs and DMR-associated genes both identified multiple pathways relevant to inflammatory and immune responses. And DMR-associated genes were significantly enriched in terms related to T-cell function. <b><i>Conclusions:</i></b> Our findings indicate that changes in DNA methylation patterns were involved in the pathogenesis of IgAN. Nine target genes detected in our study may provide new ideas for the exploration of molecular mechanisms of IgAN.

scholarly journals Integrated DNA Methylation and Gene Expression Analysis Identified S100A8 and S100A9 in the Pathogenesis of Obesity

2021 ◽  
Vol 8 ◽  
Author(s):  
Ningyuan Chen ◽  
Liu Miao ◽  
Wei Lin ◽  
Donghua Zou ◽  
Ling Huang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Mrna Expression ◽  
Regulatory Networks ◽  
Enrichment Analysis ◽  
Microarray Dataset ◽  
Functional Enrichment Analysis ◽  
Normal Subjects ◽  
Functional Enrichment ◽  
Differentially Methylated Genes

Background: To explore the association of DNA methylation and gene expression in the pathology of obesity.Methods: (1) Genomic DNA methylation and mRNA expression profile of visceral adipose tissue (VAT) were performed in a comprehensive database of gene expression in obese and normal subjects. (2) Functional enrichment analysis and construction of differential methylation gene regulatory networks were performed. (3) Validation of the two different methylation sites and corresponding gene expression was done in a separate microarray dataset. (4) Correlation analysis was performed on DNA methylation and mRNA expression data.Results: A total of 77 differentially expressed mRNAs matched with differentially methylated genes. Analysis revealed two different methylation sites corresponding to two unique genes—s100a8-cg09174555 and s100a9-cg03165378. Through the verification test of two interesting different expression positions [differentially methylated positions (DMPs)] and their corresponding gene expression, we found that methylation in these genes was negatively correlated to gene expression in the obesity group. Higher S100A8 and S100A9 expressions in obese subjects were validated in a separate microarray dataset.Conclusion: This study confirmed the relationship between DNA methylation and gene expression and emphasized the important role of S100A8 and S100A9 in the pathogenesis of obesity.

DNA methylation profile of liver of mice conceived by in vitro fertilization

2021 ◽  
pp. 1-9
Author(s):  
Saúl Lira-Albarrán ◽  
Xiaowei Liu ◽  
Seok Hee Lee ◽  
Paolo Rinaudo
Keyword(s):  
Dna Methylation ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Global Dna Methylation ◽  
Analysis Tool ◽  
Gene Promoters ◽  
Vitro Fertilization ◽  
Natural Mating

Abstract Offspring generated by in vitro fertilization (IVF) are believed to be healthy but display a possible predisposition to chronic diseases, like hypertension and glucose intolerance. Since epigenetic changes are believed to underlie such phenotype, this study aimed at describing global DNA methylation changes in the liver of adult mice generated by natural mating (FB group) or by IVF. Embryos were generated by IVF or natural mating. At 30 weeks of age, mice were sacrificed. The liver was removed, and global DNA methylation was assessed using whole-genome bisulfite sequencing (WGBS). Genomic Regions for Enrichment Analysis Tool (GREAT) and G:Profilerβ were used to identify differentially methylated regions (DMRs) and for functional enrichment analysis. Overrepresented gene ontology terms were summarized with REVIGO, while canonical pathways (CPs) were identified with Ingenuity® Pathway Analysis. Overall, 2692 DMRs (4.91%) were different between the groups. The majority of DMRs (84.92%) were hypomethylated in the IVF group. Surprisingly, only 0.16% of CpG islands were differentially methylated and only a few DMRs were located on known gene promoters (n = 283) or enhancers (n = 190). Notably, the long-interspersed element (LINE), short-interspersed element (SINE), and long terminal repeat (LTR1) transposable elements showed reduced methylation (P < 0.05) in IVF livers. Cellular metabolic process, hepatic fibrosis, and insulin receptor signaling were some of the principal biological processes and CPs modified by IVF. In summary, IVF modifies the DNA methylation signature in the adult liver, resulting in hypomethylation of genes involved in metabolism and gene transcription regulation. These findings may shed light on the mechanisms underlying the developmental origin of health and disease.

scholarly journals Integrated DNA Methylation and Gene Expression Analysis Identified S100A8 and S100A9 in the Pathogenesis of Obesity

2020 ◽  
Author(s):  
Ningyuan Chen ◽  
Liu Miao ◽  
Wei Lin ◽  
Dong-Hua Zhou ◽  
Ling Huang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Mrna Expression ◽  
Microarray Data ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Normal Subjects ◽  
Functional Enrichment ◽  
Data Set ◽  
Differentially Methylated Genes

Abstract Background: To explore the association of DNA methylation and gene expression in the pathology of obesity.Methods: (1) Genomic DNA methylation and mRNA expression profile of visceral adipose tissue (VAT) were performed in a comprehensive database of gene expression in obese and normal subjects; (2) functional enrichment analysis and construction of differential methylation gene regulatory network were performed; (3) Validation of the two different methylation sites and corresponding gene expression was done in a separate microarray data set; and (4) correlation analysis was performed on DNA methylation and mRNA expression data.Results: A total of 77 differentially expressed mRNA matched with differentially methylated genes. Analysis revealed two different methylation sites corresponding to two unique genes-s100a8-cg09174555 and s100a9-cg03165378. Through the verification test of two interested different expression positions (DMPS) and their corresponding gene expression, we found that the methylation in these genes was negatively correlated to gene expression in the obesity group. Higher S100A8 and S100A9 expression in obese subjects were validated in a separate microarray data set.Conclusion: This study confirmed the relationship between DNA methylation and gene expression and emphasized the important role of S100A8 and S100A9 in the pathogenesis of obesity.

scholarly journals Low expression or hypermethylation of PLK2 might predict favorable prognosis for patients with glioblastoma multiforme

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7974 ◽  
Author(s):  
Xiangping Xia ◽  
Fang Cao ◽  
Xiaolu Yuan ◽  
Qiang Zhang ◽  
Wei Chen ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Overall Survival ◽  
Regression Analysis ◽  
Glioblastoma Multiforme ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Favorable Prognosis ◽  
Low Expression

Background As the most aggressive brain tumor, patients with glioblastoma multiforme (GBM) have a poor prognosis. Our purpose was to explore prognostic value of Polo-like kinase 2 (PLK2) in GBM, a member of the PLKs family. Methods The expression profile of PLK2 in GBM was obtained from The Cancer Genome Atlas database. The PLK2 expression in GBM was tested. Kaplan–Meier curves were generated to assess the association between PLK2 expression and overall survival (OS) in patients with GBM. Furthermore, to assess its prognostic significance in patients with primary GBM, we constructed univariate and multivariate Cox regression models. The association between PLK2 expression and its methylation was then performed. Differentially expressed genes correlated with PLK2 were identified by Pearson test and functional enrichment analysis was performed. Results Overall survival results showed that low PLK2 expression had a favorable prognosis of patients with GBM (P-value = 0.0022). Furthermore, PLK2 (HR = 0.449, 95% CI [0.243–0.830], P-value = 0.011) was positively associated with OS by multivariate Cox regression analysis. In cluster 5, DNA methylated PLK2 had the lowest expression, which implied that PLK2 expression might be affected by its DNA methylation status in GBM. PLK2 in CpG island methylation phenotype (G-CIMP) had lower expression than non G-CIMP group (P = 0.0077). Regression analysis showed that PLK2 expression was negatively correlated with its DNA methylation (P = 0.0062, Pearson r = −0.3855). Among all differentially expressed genes of GBM, CYGB (r = 0.5551; P < 0.0001), ISLR2 (r = 0.5126; P < 0.0001), RPP25 (r = 0.5333; P < 0.0001) and SOX2 (r = −0.4838; P < 0.0001) were strongly correlated with PLK2. Functional enrichment analysis results showed that these genes were enriched several biological processes or pathways that were associated with GBM. Conclusion Polo-like kinase 2 expression is regulated by DNA methylation in GBM, and its low expression or hypermethylation could be considered to predict a favorable prognosis for patients with GBM.

Radiogenomics for the prognosis in advanced non-small cell lung cancer patients receiving bevacizumab.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e21669-e21669
Author(s):  
Butuo Li ◽  
Chao Jiang ◽  
Linlin Pang ◽  
Bingjie Fan ◽  
Mingjun Ding ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Advanced Nsclc ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Inflammatory Factors ◽  
Small Cell Lung ◽  
Nsclc Patients ◽  
Radiomics Signature ◽  
Methylation Profiling

e21669 Background: In the new era of immunotherapy, the regimen based on bevacizumab is still one of the standard options for treatment of advanced non-small cell lung cancer (NSCLC) patients without driver mutations. However, the prognostic factors for bevacizumab are still missing. We aimed to determine the integrative value of computed tomography (CT), epigenetic modifications, clinicopathological and systemic inflammatory factors for predicting the survival of advanced NSCLC patients with bevacizumab. Methods: Clinicopathological parameters, dynamic systemic inflammatory factors, radiomics features, and DNA methylation profiling in advanced non-squamous NSCLC patients receiving first- or second- line bevacizumab plus chemotherapy were included in this study. The prognostic radiomics signature were constructed by least absolute shrinkage and selection operator (LASSO) Cox analysis. A multi-omics prediction nomogram for progression-free survival (PFS) based on radiomics, clinicopathological and systemic inflammatory features was established and independently validated. Furthermore, radiomics signature-related DNA methylation were submitted to functional enrichment analysis. Results: Total of 272 patients were included in analysis, 224 in training cohort and 48 in validation cohort. Five radiomics features, including Information Measure Corr1, Inverse Variance, Local Std Max, Gauss Area, Spherical Disproportion, were finally selected to construct radiomics signature with the AUC of 0.71. Smoking history, anatomical feature, liver metastasis, LDH4, NLR2 and radiomics signature were found to be independent prognostic factors for PFS. A multi-omics nomogram was developed based on these features in training cohort with the C-index of 0.76, and external validated with the C-index of 0.75. The tissue slices of 20 patients receiving bevacizumab were used for DNA methylation profiling. Functional enrichment analysis indicated widespread and statistically significant associations between radiomics features and DNA methylation changes which involved in several pathways related to angiogenesis and immune system, such as Notch signaling pathway, small GTPase Rho signal transduction, TGFβ signal transduction. Conclusions: This multi-omics nomogram integrating radiomics, clinicopathological, systemics inflammatory features improved the prediction of PFS in advanced NSCLC patients receiving bevacizumab. And the radiomics signature were found to be related to angiogenesis and immune status.

scholarly journals A Novel Schizophrenia Diagnostic Model Based on Statistically Significant Changes in Gene Methylation in Specific Brain Regions

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Donghua Zou ◽  
Yufen Qiu ◽  
Rongjie Li ◽  
Youshi Meng ◽  
Yuan Wu
Keyword(s):  
Dna Methylation ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Brain Regions ◽  
Functional Enrichment ◽  
Diagnostic Model ◽  
Biological Processes ◽  
Gene Methylation ◽  
Model Based ◽  
Methylation Patterns

Objective. The present study identified methylation patterns of schizophrenia- (SCZ-) related genes in different brain regions and used them to construct a novel DNA methylation-based SCZ diagnostic model. Methods. Four DNA methylation datasets representing different brain regions were downloaded from the Gene Expression Omnibus. The common differentially methylated genes (CDMGs) in all datasets were identified to perform functional enrichment analysis. The differential methylation sites of 10 CDMGs involved in the largest numbers of neurological or psychiatric-related biological processes were used to construct a DNA methylation-based diagnostic model for SCZ in the respective datasets. Results. A total of 849 CDMGs were identified in the four datasets, but the methylation sites as well as degree of methylation differed across the brain regions. Functional enrichment analysis showed CDMGs were significantly involved in biological processes associated with neuronal axon development, intercellular adhesion, and cell morphology changes and, specifically, in PI3K-Akt, AMPK, and MAPK signaling pathways. Four DNA methylation-based classifiers for diagnosing SCZ were constructed in the four datasets, respectively. The sample recognition efficiency of the classifiers showed an area under the receiver operating characteristic curve of 1.00 in three datasets and >0.9 in one dataset. Conclusion. DNA methylation patterns in SCZ vary across different brain regions, which may be a useful epigenetic characteristic for diagnosing SCZ. Our novel model based on SCZ-gene methylation shows promising diagnostic power.

scholarly journals The regulatory pattern of target gene expression by aberrant enhancer methylation in glioblastoma

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Xiaoxiao Zhao ◽  
Jianghuai Ji ◽  
Shijia Wang ◽  
Rendong Wang ◽  
Qiuhong Yu ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Epigenetic Mechanism ◽  
Enhancer Region ◽  
Small Molecule Drugs ◽  
Tumorigenesis And Progression ◽  
Aberrant Dna Methylation

Abstract Background Glioblastoma multiforme (GBM) is the most common and aggressive primary malignant brain tumor with grim prognosis. Aberrant DNA methylation is an epigenetic mechanism that promotes GBM carcinogenesis, while the function of DNA methylation at enhancer regions in GBM remains poorly described. Results We integrated multi-omics data to identify differential methylation enhancer region (DMER)-genes and revealed global enhancer hypomethylation in GBM. In addition, a DMER-mediated target genes regulatory network and functional enrichment analysis of target genes that might be regulated by hypomethylation enhancer regions showed that aberrant enhancer regions could contribute to tumorigenesis and progression in GBM. Further, we identified 22 modules in which lncRNAs and mRNAs synergistically competed with each other. Finally, through the construction of drug-target association networks, our study identified potential small-molecule drugs for GBM treatment. Conclusions Our study provides novel insights for understanding the regulation of aberrant enhancer region methylation and developing methylation-based biomarkers for the diagnosis and treatment of GBM.

scholarly journals Integrated DNA methylation and gene expression analysis identified S100A8 and S100A9 in the pathogenesis of obesity

2020 ◽  
Author(s):  
Ningyuan Chen ◽  
Liu Miao ◽  
Wei Lin ◽  
Dong-Hua Zhou ◽  
Ling Huang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Mrna Expression ◽  
Microarray Data ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Normal Subjects ◽  
Functional Enrichment ◽  
Data Set ◽  
Differentially Methylated Genes

Abstract Background: To explore the association of DNA methylation and gene expression in the pathology of obesity.Methods: (1) Genomic DNA methylation and mRNA expression profile of visceral adipose tissue (VAT) were performed in a comprehensive database of gene expression in obese and normal subjects; (2) functional enrichment analysis and construction of differential methylation gene regulatory network were performed; (3) Validation of the two different methylation sites and corresponding gene expression was done in a separate microarray data set; and (4) correlation analysis was performed on DNA methylation and mRNA expression data.Results: A total of 77 differentially expressed mRNA matched with differentially methylated genes. Analysis revealed two different methylation sites corresponding to two unique genes-s100a8-cg09174555 and s100a9-cg03165378. Through the verification test of two interested different expression positions (DMPS) and their corresponding gene expression, we found that the methylation in these genes was negatively correlated to gene expression in the obesity group. Higher S100A8 and S100A9 expression in obese subjects were validated in a separate microarray data set.Conclusion: This study confirmed the relationship between DNA methylation and gene expression and emphasized the important role of S100A8 and S100A9 in the pathogenesis of obesity.

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