scholarly journals Effects of hypoxia on anabolic and catabolic gene expression and DNA methylation in OA chondrocytes

2015 ◽  
Vol 23 ◽  
pp. A196-A197
Author(s):  
K. Alvarez ◽  
M.C. de Andres ◽  
A. Takahashi ◽  
R.O. Oreffo
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Catabolic Gene ◽  
Oa Chondrocytes

scholarly journals Effects of hypoxia on anabolic and catabolic gene expression and DNA methylation in OA chondrocytes

2014 ◽  
Vol 15 (1) ◽  
Author(s):  
Karl Alvarez ◽  
María C de Andrés ◽  
Atsushi Takahashi ◽  
Richard O C Oreffo
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Catabolic Gene ◽  
Oa Chondrocytes

scholarly journals Effects of 5-aza-2’-deoxycytidine on human osteoarthritic chondrocytes

2018 ◽  
Author(s):  
Shirin Kadler ◽  
Özlem Vural ◽  
Luzia Reiners-Schramm ◽  
Roland Lauster ◽  
Mark Rosowski
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Late Stage ◽  
Chondrogenic Differentiation ◽  
Disease Models ◽  
Mrna Levels ◽  
Differentiation Potential ◽  
Differentiation Capacity ◽  
Oa Chondrocytes

AbstractBackgroundGiven regenerative therapies, the utilization of primary human cells is desired and requested in the development of in vitro systems and disease models. After a few passages in vitro, all cells from the connective tissue end up in a similar fibroblastoid cell type marked by loss of the specific expression pattern. It is still under discussion whether different de-differentiated mesenchymal cells have similar or identical differentiation capacities in vitro.MethodsChondrocytes isolated from patients with late-stage osteoarthritis were cultured for several passages until de-differentiation was completed. The mRNA level of cartilage markers was investigated, and the adipogenic, osteogenic and chondrogenic differentiation capacity was examined. By adding 5-aza-2’-deoxycytidine (5-aza-dC) to the media, the influence of DNA methylation on the differentiation capacity was analyzed.ResultsThe chondrocytes used in this work were not affected by the loss of specific gene expression upon cell culture. The mRNA levels of SOX5, SOX6, SOX9, aggrecan, and proteoglycan-4 remained unchanged. The underlying mechanisms of cartilage marker maintenance in osteoarthritic (OA) chondrocytes were investigated with a focus on the epigenetic modification by DNA methylation. The treatment of de-differentiated chondrocytes with the DNA methyltransferase inhibitor 5-aza-2’-deoxycytidine (5-aza-dC) displayed no appreciable impact on the observed maintenance of marker gene expression, while the chondrogenic differentiation capacity was compromised. On the other hand, the pre-cultivation with 5-aza-dC improved the osteogenesis and adipogenesis of OA chondrocytes. Contradictory to these effects, the DNA methylation levels were not reduced after treatment with 1 μM 5-aza-dC for four weeks.ConclusionChondrocytes isolated from late-stage osteoarthritic patients represents a reliable cell source for in vitro studies as wells as disease models since the chondrogenic differentiation potential remains. 5-aza-2’-deoxycytidine could not further improve their chondrogenic potential.

DNA Demethylation Regulates Anabolic and Catabolic Gene Expression in Intervertebral Disc Cells

2014 ◽  
Vol 4 (1_suppl) ◽  
pp. s-0034-1376587-s-0034-1376587
Author(s):  
N. Chutkan ◽  
R. Sangani ◽  
H. Zhou ◽  
S. Fulzele
Keyword(s):  
Gene Expression ◽  
Intervertebral Disc ◽  
Dna Demethylation ◽  
Catabolic Gene ◽  
Disc Cells

DNA Methylation Inhibites ANXA1 Gene Expression in Nasopharyngeal Carcinoma Cell Lines*

2009 ◽  
Vol 36 (10) ◽  
pp. 1319-1326 ◽  
Author(s):  
Shuang-Xiang TAN ◽  
Rui-Cheng HU ◽  
Ai-Guo DAI ◽  
Cen-E TANG ◽  
Hong YI ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Nasopharyngeal Carcinoma ◽  
Cell Lines ◽  
Carcinoma Cell ◽  
Nasopharyngeal Carcinoma Cell ◽  
Carcinoma Cell Lines

scholarly journals Epigenetic Changes During Mechanically Induced Osteogenic Lineage Commitment

2015 ◽  
Vol 137 (2) ◽  
Author(s):  
Julia C. Chen ◽  
Mardonn Chua ◽  
Raymond B. Bellon ◽  
Christopher R. Jacobs
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Shear Stress ◽  
Fluid Shear Stress ◽  
Methylation Status ◽  
Lineage Commitment ◽  
Fluid Shear ◽  
Osteogenic Lineage ◽  
Osteogenic Markers ◽  
Heterochromatin Structure

Osteogenic lineage commitment is often evaluated by analyzing gene expression. However, many genes are transiently expressed during differentiation. The availability of genes for expression is influenced by epigenetic state, which affects the heterochromatin structure. DNA methylation, a form of epigenetic regulation, is stable and heritable. Therefore, analyzing methylation status may be less temporally dependent and more informative for evaluating lineage commitment. Here we analyzed the effect of mechanical stimulation on osteogenic differentiation by applying fluid shear stress for 24 hr to osteocytes and then applying the osteocyte-conditioned medium (CM) to progenitor cells. We analyzed gene expression and changes in DNA methylation after 24 hr of exposure to the CM using quantitative real-time polymerase chain reaction and bisulfite sequencing. With fluid shear stress stimulation, methylation decreased for both adipogenic and osteogenic markers, which typically increases availability of genes for expression. After only 24 hr of exposure to CM, we also observed increases in expression of later osteogenic markers that are typically observed to increase after seven days or more with biochemical induction. However, we observed a decrease or no change in early osteogenic markers and decreases in adipogenic gene expression. Treatment of a demethylating agent produced an increase in all genes. The results indicate that fluid shear stress stimulation rapidly promotes the availability of genes for expression, but also specifically increases gene expression of later osteogenic markers.

scholarly journals DNA methylation and gene expression integration in cardiovascular disease

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Guillermo Palou-Márquez ◽  
Isaac Subirana ◽  
Lara Nonell ◽  
Alba Fernández-Sanlés ◽  
Roberto Elosua
Keyword(s):  
Gene Expression ◽  
Cardiovascular Disease ◽  
Dna Methylation ◽  
Cardiovascular Diseases ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Risk Function ◽  
Predictive Biomarkers ◽  
Independent Study ◽  
Cell Type

Abstract Background The integration of different layers of omics information is an opportunity to tackle the complexity of cardiovascular diseases (CVD) and to identify new predictive biomarkers and potential therapeutic targets. Our aim was to integrate DNA methylation and gene expression data in an effort to identify biomarkers related to cardiovascular disease risk in a community-based population. We accessed data from the Framingham Offspring Study, a cohort study with data on DNA methylation (Infinium HumanMethylation450 BeadChip; Illumina) and gene expression (Human Exon 1.0 ST Array; Affymetrix). Using the MOFA2 R package, we integrated these data to identify biomarkers related to the risk of presenting a cardiovascular event. Results Four independent latent factors (9, 19, 21—only in women—and 27), driven by DNA methylation, were associated with cardiovascular disease independently of classical risk factors and cell-type counts. In a sensitivity analysis, we also identified factor 21 as associated with CVD in women. Factors 9, 21 and 27 were also associated with coronary heart disease risk. Moreover, in a replication effort in an independent study three of the genes included in factor 27 were also present in a factor identified to be associated with myocardial infarction (CDC42BPB, MAN2A2 and RPTOR). Factor 9 was related to age and cell-type proportions; factor 19 was related to age and B cells count; factor 21 pointed to human immunodeficiency virus infection-related pathways and inflammation; and factor 27 was related to lifestyle factors such as alcohol consumption, smoking and body mass index. Inclusion of factor 21 (only in women) improved the discriminative and reclassification capacity of the Framingham classical risk function and factor 27 improved its discrimination. Conclusions Unsupervised multi-omics data integration methods have the potential to provide insights into the pathogenesis of cardiovascular diseases. We identified four independent factors (one only in women) pointing to inflammation, endothelium homeostasis, visceral fat, cardiac remodeling and lifestyles as key players in the determination of cardiovascular risk. Moreover, two of these factors improved the predictive capacity of a classical risk function.

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