Dataset Information

DNA Methylation in Osteoarthritis.

ABSTRACT: Osteoarthritis (OA) is a prevalent disease of articular joints and primarily characterized by degradation and calcification of articular cartilage. Presently, no effective treatment other than pain relief exists and patients ultimately need to undergo replacement surgery of the affected joint. During disease progression articular chondrocytes, the single cell type present in articular cartilage, show altered transcriptional profiles and undergo phenotypic changes that resemble the terminal differentiation route apparent in growth plate chondrocytes. Hence, given its prominent function in both regulating gene expression and maintaining cellular phenotypes, DNA methylation of CpG dinucleotides is intensively studied in the context of OA. An increasing number of studies have been published that employed a targeted approach on genes known to play a role in OA pathophysiology. As of such, it has become clear that OA responsive DNA methylation changes seem to mediate disease associated aberrant gene expression. Furthermore, established OA susceptibility alleles such as GDF5 and DIO2 appear to confer OA risk via DNA methylation and respective pathophysiological expression changes. In more recent years, genome wide profiling of DNA methylation in OA affected articular cartilage has emerged as a powerful tool to address the epigenetic changes in their entirety, which has resulted in the identification of putative patient subgroups as well as generic OA associated pathways.

SUBMITTER: den Hollander W

PROVIDER: S-EPMC4765529 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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DNA Methylation in Osteoarthritis.

den Hollander Wouter W Meulenbelt Ingrid I

Current genomics 20151201 6

Osteoarthritis (OA) is a prevalent disease of articular joints and primarily characterized by degradation and calcification of articular cartilage. Presently, no effective treatment other than pain relief exists and patients ultimately need to undergo replacement surgery of the affected joint. During disease progression articular chondrocytes, the single cell type present in articular cartilage, show altered transcriptional profiles and undergo phenotypic changes that resemble the terminal diffe ...[more]

PMID: 27019616

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Project description:Osteoarthritis (OA) is chronic arthritis characterized by articular cartilage degradation. However, a comprehensive regulatory network for OA-related microRNAs and DNA methylation modifications has yet to be established. Thus, we aimed to identify epigenetic changes in microRNAs and DNA methylation and establish the regulatory network between miRNAs and DNA methylation. The mRNA, miRNA, and DNA methylation expression profiles of healthy or osteoarthritis articular cartilage samples were downloaded from Gene Expression Omnibus (GEO) database, including GSE169077, GSE175961, and GSE162484. The differentially expressed genes (DEGs), differentially expressed miRNAs (DEMs), and differentially methylated genes (DMGs) were analyzed by the online tool GEO2R. DAVID and STRING databases were applied for functional enrichment analysis and protein-protein interaction (PPI) network. Potential therapeutic compounds for the treatment of OA were identified by Connectivity map (CMap) analysis. A total of 1424 up-regulated DEGs, 1558 down-regulated DEGs, 5 DEMs with high expression, 6 DEMs with low expression, 1436 hypermethylated genes, and 455 hypomethylated genes were selected. A total of 136 up-regulated and 65 downregulated genes were identified by overlapping DEGs and DEMs predicted target genes which were enriched in apoptosis and circadian rhythm. A total of 39 hypomethylated and 117 hypermethylated genes were obtained by overlapping DEGs and DMGs, which were associated with ECM receptor interactions and cellular metabolic processes, cell connectivity, and transcription. Moreover, The PPI network showed COL5A1, COL6A1, LAMA4, T3GAL6A, and TP53 were the most connective proteins. After overlapping of DEGs, DMGs and DEMs predicted targeted genes, 4 up-regulated genes and 11 down-regulated genes were enriched in the Axon guidance pathway. The top ten genes ranked by PPI network connectivity degree in the up-regulated and downregulated overlapping genes of DEGs and DMGs were further analyzed by the CMap database, and nine chemicals were predicted as potential drugs for the treatment of OA. In conclusion, TP53, COL5A1, COL6A1, LAMA4, and ST3GAL6 may play important roles in OA genesis and development.

Project description:Osteoarthritis (OA) is a common type of arthritis, which may cause pain and disability. Alterations in gene expression and DNA methylation have been proven to be associated with the development of OA. The aim of the present study was to identify potential therapeutic targets and associated processes for OA via the combined analysis of gene expression and DNA methylation datasets. The gene expression and DNA methylation profiles were obtained from the Gene Expression Omnibus, and differentially expressed genes (DEGs) and differentially methylated sites (DMSs) were identified in the present study, using R programming software. The enriched functions of DEGs and DMSs were obtained via the Database for Annotation, Visualization and Integrated Discovery. Finally, cross analysis of DEGs and DMSs was performed to identify genes that exhibited differential expression and methylation simultaneously. The protein?protein interaction (PPI) network of overlaps between DEGs and DMSs was obtained using the Human Protein Reference Database; the topological properties of PPI network overlaps were additionally obtained. Hub genes in the PPI network were further confirmed via reverse transcription?quantitative polymerase chain reaction (RT?qPCR). The results of the present study revealed that the majority of DEGs and DMSs were upregulated and hypomethylated in patients with OA, respectively. DEGs and DMSs were primarily involved in inflammatory, immune and gene expression regulation?associated processes and pathways. Cross analysis revealed 30 genes that exhibited differential expression and methylation in OA simultaneously. Topological analysis of the PPI network revealed that numerous genes, including G protein subunit ?1 (GNAI1), runt related transcription factor 2 (RUNX2) and integrin subunit ?2 (ITGB2), may be involved in the development of OA. Additionally, RT?qPCR analysis of GNAI1, RUNX2 and ITGB2 provided further confirmation. Numerous known and novel therapeutic targets were obtained via network analysis. The results of the present study may be beneficial for the diagnosis and treatment of OA.

Project description:BACKGROUND:Osteoarthritis is a chronic musculoskeletal disease characterized by age-related gradual thinning and a high risk in females. Recent studies have shown that DNA methylation plays important roles in osteoarthritis. However, the genome-wide pattern of methylation in enhancers in osteoarthritis remains unclear. METHODS:To explore the function of enhancers in osteoarthritis, we quantified CpG methylation in human enhancers based on a public dataset that included methylation profiles of 470,870 CpG probes in 108 samples from patients with hip and knee osteoarthritis and hip tissues from healthy individuals. Combining various bioinformatics analysis tools, we systematically analyzed aberrant DNA methylation of the enhancers throughout the genome in knee osteoarthritis and hip osteoarthritis. RESULTS:We identified 16,816 differentially methylated CpGs, and nearly half (8111) of them were from enhancers, suggesting major DNA methylation changes in both types of osteoarthritis in the enhancer regions. A detailed analysis of hip osteoarthritis identified 2426 differentially methylated CpGs in enhancers between male and female patients, and 84.5% of them were hypomethylated in female patients and enriched in phenotypes related to hip osteoarthritis in females. Next, we explored the enhancer methylation dynamics among patients with knee osteoarthritis and identified 280 differentially methylated enhancer CpGs that were enriched in the human phenotypes and disease ontologies related to osteoarthritis. Finally, a comparison of enhancer methylation between knee osteoarthritis and hip osteoarthritis revealed organ source-dependent differences in enhancer methylation. CONCLUSION:Our findings indicate that aberrant methylation of enhancers is related to osteoarthritis phenotypes, and a comprehensive atlas of enhancer methylation is useful for further analysis of the epigenetic regulation of osteoarthritis and the development of clinical drugs for treatment of osteoarthritis.

Project description:Genetics and epigenetics are important subjects in the field of osteoarthritis (OA) research. DNA methylation may affect gene transcription, but the specific mechanisms have remained to be fully elucidated. In the present study, the ChAMP methylation analysis package was used to identify differentially methylated genes (DMGs) from the dataset GSE63695 from the Gene Expression Omnibus (GEO) database. The distribution of differentially methylated sites (DMS) and the total array sites across the genome were analyzed by enrichment analysis. Subsequently, two mRNA expression profiling datasets, GSE114007 and GSE113825, were obtained from the GEO database and common differentially expressed genes (DEGs) were identified using the Limma package. Key genes were screened by analyzing the distribution of DMS across the genome consisting of DEGs and DMGs. A total of 1,662 and 1,986 DEGs were identified between OA and normal human cartilage from the GSE113825 and GSE114007 dataset, respectively. A further screening revealed 292 genes with common differences between the two datasets. A total of 574 DMS containing 394 DMGs were observed between OA and normal cartilage. Integrative analysis revealed a corresponding subset of 15 genes. Of these, 6 genes were verified by reverse transcription-quantitative PCR, confirming that the mRNA expression of 5 genes (MAP1B, FNDC1, ANLN, SCNN1A and STC2) in OA cartilage was consistent with the mRNA expression from the analysis of the datasets. Upon treatment with the DNA methylation inhibitor 5-aza-2'-deoxycytidine, the mRNA levels of FNDC1 and SCNN1A were decreased, and no significant alteration in the mRNA levels of MAP1B, ANLN, KCNN4 and STC2 was observed. The incidence of differential methylation varied in subregions of the genome and the effects on transcription were associated with the distribution of DEGs across the genome. The regulation of this appears more complex than initially postulated. Combining the data on epigenetic differences of OA with the genome or transcriptome data for analysis may improve the understanding of the pathophysiological processes of OA. FNDC1 and SCNN1A may potentially be valuable biomarkers for OA.

Project description:Our study aimed to identify differentially methylated regions (i.e., genomic region where multiple adjacent CpG sites show differential methylation) and their enriched genomic pathways associated with knee osteoarthritis pain (KOA). We recruited cognitively healthy middle to older aged (age 45-85) adults with (n = 182) and without (n = 31) self-reported KOA pain. We also extracted DNA from peripheral blood that was analyzed using MethylationEPIC arrays. The R package minfi (Aryee et al., 2014) was used to perform methylation data preprocessing and quality control. To investigate biological pathways impacted by differential methylation, we performed pathway enrichment analysis using Ingenuity Pathway Analysis (IPA) to identify canonical pathways and upstream regulators. Annotated genes within ± 5 kb of the putative differentially methylated regions (DMRs, p < 0.05) were subjected to the IPA analysis. There was no significant difference in age, sex, study site between no pain and pain group (p > 0.05). Non-Hispanic black individuals were overrepresented in the pain group (p = 0.003). At raw p < 0.05 cutoff, we identified a total of 19,710 CpG probes, including 13,951 hypermethylated CpG probes, for which DNA methylation level was higher in the groups with highest pain grades. We also identified 5,759 hypomethylated CpG probes for which DNA methylation level was lower in the pain groups with higher pain grades. IPA revealed that pain-related DMRs were enriched across multiple pathways and upstream regulators. The top 10 canonical pathways were linked to cellular signaling processes related to immune responses (i.e., antigen presentation, PD-1, PD-L1 cancer immunotherapy, B cell development, IL-4 signaling, Th1 and Th2 activation pathway, and phagosome maturation). Moreover, in terms of upstream regulators, NDUFAF3 was the most significant (p = 8.6E-04) upstream regulator. Our findings support previous preliminary work suggesting the importance of epigenetic regulation of the immune system in knee pain and the need for future work to understand the epigenetic contributions to chronic pain.

Dataset Information

DNA Methylation in Osteoarthritis.

Publications

DNA Methylation in Osteoarthritis.

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