Integrative epigenomics, transcriptomics and proteomics of patient chondrocytes reveal genes and pathways involved in osteoarthritis
By
Julia Steinberg,
Graham R. S. Ritchie,
Theodoros I. Roumeliotis,
Raveen L. Jayasuriya,
Roger A. Brooks,
Abbie L. A. Binch,
Karan M. Shah,
Rachael Coyle,
Mercedes Pardo,
Christine L. Le Maitre,
Yolande F. M. Ramos,
Rob G. H. H. Nelissen,
Ingrid Meulenbelt,
Andrew W. McCaskie,
Jyoti S. Choudhary,
J Mark Wilkinson,
Eleftheria Zeggini
Posted 28 Jan 2016
bioRxiv DOI: 10.1101/038067
(published DOI: 10.1038/s41598-017-09335-6)
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.
Download data
- Downloaded 1,115 times
- Download rankings, all-time:
- Site-wide: 15,722
- In systems biology: 326
- Year to date:
- Site-wide: 53,623
- Since beginning of last month:
- Site-wide: 40,502
Altmetric data
Downloads over time
Distribution of downloads per paper, site-wide
PanLingua
News
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!