scholarly journals Integrating genome-wide DNA methylation and mRNA expression profiles identified different molecular features between Kashin-Beck disease and primary osteoarthritis

2018 ◽  
Vol 20 (1) ◽  
Author(s):  
Yan Wen ◽  
Ping Li ◽  
Jingcan Hao ◽  
Chen Duan ◽  
Jing Han ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Mrna Expression ◽  
Expression Profiles ◽  
Molecular Features ◽  
Primary Osteoarthritis ◽  
Genome Wide ◽  
Beck Disease

scholarly journals Use of integrative epigenetic and mRNA expression analyses to identify significantly changed genes and functional pathways in osteoarthritic cartilage

2018 ◽  
Vol 7 (5) ◽  
pp. 343-350 ◽  
Author(s):  
A. He ◽  
Y. Ning ◽  
Y. Wen ◽  
Y. Cai ◽  
K. Xu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Mrna Expression ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Signalling Pathway ◽  
Pathway Enrichment Analysis ◽  
Osteoarthritic Cartilage ◽  
Pathway Enrichment ◽  
Genome Wide

Aim Osteoarthritis (OA) is caused by complex interactions between genetic and environmental factors. Epigenetic mechanisms control the expression of genes and are likely to regulate the OA transcriptome. We performed integrative genomic analyses to define methylation-gene expression relationships in osteoarthritic cartilage. Patients and Methods Genome-wide DNA methylation profiling of articular cartilage from five patients with OA of the knee and five healthy controls was conducted using the Illumina Infinium HumanMethylation450 BeadChip (Illumina, San Diego, California). Other independent genome-wide mRNA expression profiles of articular cartilage from three patients with OA and three healthy controls were obtained from the Gene Expression Omnibus (GEO) database. Integrative pathway enrichment analysis of DNA methylation and mRNA expression profiles was performed using integrated analysis of cross-platform microarray and pathway software. Gene ontology (GO) analysis was conducted using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Results We identified 1265 differentially methylated genes, of which 145 are associated with significant changes in gene expression, such as DLX5, NCOR2 and AXIN2 (all p-values of both DNA methylation and mRNA expression < 0.05). Pathway enrichment analysis identified 26 OA-associated pathways, such as mitogen-activated protein kinase (MAPK) signalling pathway (p = 6.25 × 10-4), phosphatidylinositol (PI) signalling system (p = 4.38 × 10-3), hypoxia-inducible factor 1 (HIF-1) signalling pathway (p = 8.63 × 10-3 pantothenate and coenzyme A (CoA) biosynthesis (p = 0.017), ErbB signalling pathway (p = 0.024), inositol phosphate (IP) metabolism (p = 0.025), and calcium signalling pathway (p = 0.032). Conclusion We identified a group of genes and biological pathwayswhich were significantly different in both DNA methylation and mRNA expression profiles between patients with OA and controls. These results may provide new clues for clarifying the mechanisms involved in the development of OA. Cite this article: A. He, Y. Ning, Y. Wen, Y. Cai, K. Xu, Y. Cai, J. Han, L. Liu, Y. Du, X. Liang, P. Li, Q. Fan, J. Hao, X. Wang, X. Guo, T. Ma, F. Zhang. Use of integrative epigenetic and mRNA expression analyses to identify significantly changed genes and functional pathways in osteoarthritic cartilage. Bone Joint Res 2018;7:343–350. DOI: 10.1302/2046-3758.75.BJR-2017-0284.R1.

scholarly journals Variability of genome-wide DNA methylation and mRNA expression profiles in reproductive and endocrine disease related tissues

Epigenetics ◽  
2017 ◽  
Vol 12 (10) ◽  
pp. 897-908 ◽  
Author(s):  
Nilufer Rahmioglu ◽  
Alexander W Drong ◽  
Helen Lockstone ◽  
Thomas Tapmeier ◽  
Karin Hellner ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Mrna Expression ◽  
Expression Profiles ◽  
Endocrine Disease ◽  
Genome Wide

DDR1 methylation is associated with bipolar disorder and the isoform expression and methylation of myelin genes

Epigenomics ◽  
2021 ◽  
Author(s):  
Beatriz Garcia-Ruiz ◽  
Manuel Castro de Moura ◽  
Gerard Muntané ◽  
Lourdes Martorell ◽  
Elena Bosch ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Bipolar Disorder ◽  
Mrna Expression ◽  
Gene Expression Analysis ◽  
Mrna Levels ◽  
Healthy Controls ◽  
Genome Wide ◽  
Isoform Expression

Aim: To investigate DDR1 methylation in the brains of bipolar disorder (BD) patients and its association with DDR1 mRNA levels and comethylation with myelin genes. Materials & methods: Genome-wide profiling of DNA methylation (Infinium MethylationEPIC BeadChip) corrected for glial composition and DDR1 gene expression analysis in the occipital cortices of individuals with BD (n = 15) and healthy controls (n = 15) were conducted. Results: DDR1 5-methylcytosine levels were increased and directly associated with DDR1b mRNA expression in the brains of BD patients. We also observed that DDR1 was comethylated with a group of myelin genes. Conclusion: DDR1 is hypermethylated in BD brain tissue and is associated with isoform expression. Additionally, DDR1 comethylation with myelin genes supports the role of this receptor in myelination.

scholarly journals Development and Validation of a Prognostic Nomogram Based on DNA Methylation-Driven Genes for Patients With Ovarian Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Min Zhou ◽  
Shasha Hong ◽  
Bingshu Li ◽  
Cheng Liu ◽  
Ming Hu ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Dna Methylation ◽  
Mrna Expression ◽  
Risk Score ◽  
Cox Regression ◽  
Expression Profiles ◽  
Figo Stage ◽  
Prognostic Indicator ◽  
Tissue Expression ◽  
The Cancer Genome Atlas

Background: DNA methylation affects the development, progression, and prognosis of various cancers. This study aimed to identify DNA methylated-differentially expressed genes (DEGs) and develop a methylation-driven gene model to evaluate the prognosis of ovarian cancer (OC).Methods: DNA methylation and mRNA expression profiles of OC patients were downloaded from The Cancer Genome Atlas, Genotype-Tissue Expression, and Gene Expression Omnibus databases. We used the R package MethylMix to identify DNA methylation-regulated DEGs and built a prognostic signature using LASSO Cox regression. A quantitative nomogram was then drawn based on the risk score and clinicopathological features.Results: We identified 56 methylation-related DEGs and constructed a prognostic risk signature with four genes according to the LASSO Cox regression algorithm. A higher risk score not only predicted poor prognosis, but also was an independent poor prognostic indicator, which was validated by receiver operating characteristic (ROC) curves and the validation cohort. A nomogram consisting of the risk score, age, FIGO stage, and tumor status was generated to predict 3- and 5-year overall survival (OS) in the training cohort. The joint survival analysis of DNA methylation and mRNA expression demonstrated that the two genes may serve as independent prognostic biomarkers for OS in OC.Conclusion: The established qualitative risk score model was found to be robust for evaluating individualized prognosis of OC and in guiding therapy.

scholarly journals Genome-Wide DNA Methylation Profiles of Phlegm-Dampness Constitution

2018 ◽  
Vol 45 (5) ◽  
pp. 1999-2008 ◽  
Author(s):  
Haiqiang Yao ◽  
Shanlan Mo ◽  
Ji Wang ◽  
Yingshuai Li ◽  
Chong-Zhi Wang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Metabolic Disorders ◽  
Mononuclear Cells ◽  
Metabolic Diseases ◽  
Body Type ◽  
Peripheral Blood Mononuclear ◽  
Molecular Features ◽  
Genome Wide ◽  
A Genome ◽  
Differentially Methylated Genes

Background/Aims: Metabolic diseases are leading health concerns in today’s global society. In traditional Chinese medicine (TCM), one body type studied is the phlegm-dampness constitution (PC), which predisposes individuals to complex metabolic disorders. Genomic studies have revealed the potential metabolic disorders and the molecular features of PC. The role of epigenetics in the regulation of PC, however, is unknown. Methods: We analyzed a genome-wide DNA methylation in 12 volunteers using Illumina Infinium Human Methylation450 BeadChip on peripheral blood mononuclear cells (PBMCs). Eight volunteers had PC and 4 had balanced constitutions. Results: Methylation data indicated a genome-scale hyper-methylation pattern in PC. We located 288 differentially methylated probes (DMPs). A total of 256 genes were mapped, and some of these were metabolic-related. SQSTM1, DLGAP2 and DAB1 indicated diabetes mellitus; HOXC4 and SMPD3, obesity; and GRWD1 and ATP10A, insulin resistance. According to Ingenuity Pathway Analysis (IPA), differentially methylated genes were abundant in multiple metabolic pathways. Conclusion: Our results suggest the potential risk for metabolic disorders in individuals with PC. We also explain the clinical characteristics of PC with DNA methylation features.

scholarly journals Bacterial Lipopolysaccharide Induced Alterations of Genome-Wide DNA Methylation and Promoter Methylation of Lactation-Related Genes in Bovine Mammary Epithelial Cells

Toxins ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 298 ◽  
Author(s):  
Jingbo Chen ◽  
Yongjiang Wu ◽  
Yawang Sun ◽  
Xianwen Dong ◽  
Zili Wang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Immune Response ◽  
Mrna Expression ◽  
Promoter Methylation ◽  
Mammary Epithelial Cells ◽  
Mammary Epithelial ◽  
Bovine Mammary Epithelial Cells ◽  
Genome Wide ◽  
Immune Response Pathway ◽  
Gene Mrna

Bacterial lipopolysaccharide (LPS) could result in poor lactation performance in dairy cows. High methylation of DNA is associated with gene repression. However, it is unclear whether LPS could suppress the expression of lactation-related genes by inducing DNA methylation. Therefore, the objective of this study was to investigate the impact of LPS on genome-wide DNA methylation, using methylated DNA immunoprecipitation with high-throughput sequencing (MeDIP-seq) and on the promoter methylation of lactation-related genes using MassArray analysis in bovine mammary epithelial cells. The bovine mammary epithelial cell line MAC-T cells were treated for 48 h with LPS at different doses of 0, 1, 10, 100, and 1000 endotoxin units (EU)/mL (1 EU = 0.1 ng). The results showed that the genomic methylation levels and the number of methylated genes in the genome as well as the promoter methylation levels of milk genes increased when the LPS dose was raised from 0 to 10 EU/mL, but decreased after further increasing the LPS dose. The milk gene mRNA expression levels of the 10 EU/mL LPS treatment were significantly lower than these of untreated cells. The results also showed that the number of hypermethylated genes was greater than that of hypomethylated genes in lipid and amino acid metabolic pathways following 1 and 10 EU/mL LPS treatments as compared with control. By contrast, in the immune response pathway the number of hypomethylated genes increased with increasing LPS doses. The results indicate LPS at lower doses induced hypermethylation of the genome and promoters of lactation-related genes, affecting milk gene mRNA expression. However, LPS at higher doses induced hypomethylation of genes involved in the immune response pathway probably in favor of immune responses.

scholarly journals A Prognostic Nomogram Model Based on mRNA Expression of DNA Methylation-Driven Genes for Gastric Cancer

2020 ◽  
Vol 10 ◽  
Author(s):  
Zuhua Chen ◽  
Bo Liu ◽  
Minxiao Yi ◽  
Hong Qiu ◽  
Xianglin Yuan
Keyword(s):  
Gastric Cancer ◽  
Dna Methylation ◽  
Mrna Expression ◽  
Risk Model ◽  
Cox Regression ◽  
Risk Group ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Clinicopathological Parameters ◽  
Dna Hypomethylation

PurposeThe exploration and interpretation of DNA methylation-driven genes might contribute to molecular classification, prognostic prediction and therapeutic choice. In this study, we built a prognostic risk model via integrating analysis of the transcriptome and methylation profile for patients with gastric cancer (GC).MethodsThe mRNA expression profiles, DNA methylation profiles and corresponding clinicopathological information of 415 GC patients were downloaded from The Cancer Genome Atlas (TCGA). Differential expression and correlation analysis were performed to identify DNA methylation-driven genes. The candidate genes were selected by univariate Cox regression analyses followed by the least absolute shrinkage and selection operator (LASSO) regression. A prognostic risk nomogram model was then built together with clinicopathological parameters.Results5 DNA methylation-driven genes (CXCL3, F5, GNAI1, GAMT and GHR) were identified by integrated analyses and selected to construct the prognostic risk model with clinicopathological parameters. High expression and low DNA hypermethylation of F5, GNAI1, GAMT and GHR, as well as low expression and high DNA hypomethylation of CXCL3 were significantly associated with poor prognosis rates, respectively. The high-risk group showed a significantly shorter prognosis than the low-risk group in the TCGA dataset (HR = 0.212, 95% CI = 0.139–0.322, P = 2e-15). The final nomogram model showed high predictive efficiency and consistency in the training and validation group.ConclusionWe construct and validate a prognostic nomogram model for GC based on five DNA methylation-driven genes with high performance and stability. This nomogram model might be a powerful tool for prognosis evaluation in the clinic and also provided novel insights into the epigenetics in GC.

Sign in / Sign up

Export Citation Format

Share Document