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Integrative epigenomics, transcriptomics and proteomics of patient chondrocytes reveal genes and pathways involved in osteoarthritis
Graham R. S. Ritchie,
Theodoros I. Roumeliotis,
Raveen L. Jayasuriya,
Roger A. Brooks,
Abbie L. A. Binch,
Karan M. Shah,
Christine L. Le Maitre,
Yolande F. M. Ramos,
Rob G. H. H. Nelissen,
Andrew W. McCaskie,
Jyoti S. Choudhary,
J. Mark Wilkinson,
Posted 28 Jan 2016
bioRxiv DOI: 10.1101/038067 (published DOI: 10.1038/s41598-017-09335-6)
Posted 28 Jan 2016
Background: Osteoarthritis (OA) is a common disease characterized by cartilage degeneration and joint remodeling. The underlying molecular changes underpinning disease progression are incompletely understood, but can be characterized using recent advances in genomics technologies, as the relevant tissue is readily accessible at joint replacement surgery. Here we investigate genes and pathways that mark OA progression, combining genome-wide DNA methylation, RNA sequencing and quantitative proteomics in isolated primary chondrocytes from matched intact and degraded articular cartilage samples across twelve patients with OA undergoing knee replacement surgery. Results: We identify 49 genes differentially regulated between intact and degraded cartilage at multiple omics levels, 16 of which have not previously been implicated in OA progression. Using independent replication datasets, we replicate statistically significant signals and show that the direction of change is consistent for over 90% of differentially expressed genes and differentially methylated CpG probes. Three genes are differentially regulated across all 3 omics levels: AQP1, COL1A1 and CLEC3B, and all three have evidence implicating them in OA through animal or cellular model studies. Integrated pathway analysis implicates the involvement of extracellular matrix degradation, collagen catabolism and angiogenesis in disease progression. All data from these experiments are freely available as a resource for the scientific community. Conclusions: This work provides a first integrated view of the molecular landscape of human primary chondrocytes and identifies key molecular players in OA progression that replicate across independent datasets, with evidence for translational potential.
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