Objectives: To collate the genes experimentally modulated in animal models of osteoarthritis (OA) and compare these data with OA transcriptomics data to identify potential therapeutic targets.
Methods: PubMed searches were conducted to identify publications describing gene modulations in animal models. Analysed gene expression data were retrieved from the SkeletalVis database of analysed skeletal microarray and RNA-Seq expression data. A network diffusion approach was used to predict new genes associated with OA joint damage.
Results: A total of 459 genes were identified as having been modulated in animal models of OA, with ageing and post-traumatic (surgical) models the most prominent. Ninety-eight of the 143 genes (69%) genetically modulated more than once had a consistent effect on OA joint damage severity. Several discrepancies between different studies were identified, providing lessons on interpretation of these data. We used the data collected along with OA gene expression data to expand existing annotations and prioritise the most promising therapeutic targets, which we validated using the latest reported associations. We constructed an online database OATargets to allow researchers to explore the collated data and integrate it with existing OA and skeletal gene expression data.
Conclusions: We present a comprehensive survey and online resource for understanding gene regulation of animal model OA pathogenesis.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7892386 | PMC |
| http://dx.doi.org/10.1136/annrheumdis-2020-218344 | DOI Listing |
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