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Cross-species gene modules emerge from a systems biology approach to osteoarthritis.


ABSTRACT: Complexities in degenerative disorders, such as osteoarthritis, arise from multiscale biological, environmental, and temporal perturbations. Animal models serve to provide controlled representations of the natural history of degenerative disorders, but in themselves represent an additional layer of complexity. Comparing transcriptomic networks arising from gene co-expression data across species can facilitate an understanding of the preservation of functional gene modules and establish associations with disease phenotypes. This study demonstrates the preservation of osteoarthritis-associated gene modules, described by immune system and system development processes, across human and rat studies. Class prediction analysis establishes a minimal gene signature, including the expression of the Rho GDP dissociation inhibitor ARHGDIB, which consistently defined healthy human cartilage from osteoarthritic cartilage in an independent data set. The age of human clinical samples remains a strong confounder in defining the underlying gene regulatory mechanisms in osteoarthritis; however, defining preserved gene models across species may facilitate standardization of animal models of osteoarthritis to better represent human disease and control for ageing phenomena.

SUBMITTER: Mueller AJ 

PROVIDER: S-EPMC5460168 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Cross-species gene modules emerge from a systems biology approach to osteoarthritis.

Mueller Alan James AJ   Canty-Laird Elizabeth G EG   Clegg Peter D PD   Tew Simon R SR  

NPJ systems biology and applications 20170517


Complexities in degenerative disorders, such as osteoarthritis, arise from multiscale biological, environmental, and temporal perturbations. Animal models serve to provide controlled representations of the natural history of degenerative disorders, but in themselves represent an additional layer of complexity. Comparing transcriptomic networks arising from gene co-expression data across species can facilitate an understanding of the preservation of functional gene modules and establish associati  ...[more]

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