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跨物种基因模块源自骨关节炎的系统生物学研究方法。

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

作者信息

Mueller Alan James, Canty-Laird Elizabeth G, Clegg Peter D, Tew Simon R

机构信息

Department of Musculoskeletal Biology, Institute of Ageing and Chronic Disease, Faculty of Health and Life Sciences, University of Liverpool, William Henry Duncan Building, 6 West Derby Street, Liverpool, L7 8TX UK.

The MRC-Arthritis Research UK, Centre for Integrated Research into Musculoskeletal Ageing (CIMA), Liverpool, UK.

出版信息

NPJ Syst Biol Appl. 2017 May 17;3:13. doi: 10.1038/s41540-017-0014-3. eCollection 2017.

DOI:10.1038/s41540-017-0014-3
PMID:28649440
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5460168/
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 , 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.

摘要

退行性疾病(如骨关节炎)的复杂性源于多尺度的生物、环境和时间扰动。动物模型有助于提供退行性疾病自然史的可控表征,但模型本身又增加了一层复杂性。比较跨物种基因共表达数据产生的转录组网络,有助于理解功能基因模块的保守性,并建立与疾病表型的关联。本研究证明,在人类和大鼠研究中,由免疫系统和系统发育过程描述的骨关节炎相关基因模块具有保守性。分类预测分析确定了一个最小基因特征,包括Rho GDP解离抑制剂的表达,该特征在一个独立数据集中始终能区分健康人类软骨和骨关节炎软骨。人类临床样本的年龄在定义骨关节炎潜在基因调控机制方面仍然是一个很强的混杂因素;然而,确定跨物种保守的基因模型可能有助于骨关节炎动物模型的标准化,以更好地代表人类疾病并控制衰老现象。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d20d/5460168/6fc265cfbb4a/41540_2017_14_Fig6_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d20d/5460168/ceae6de032db/41540_2017_14_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d20d/5460168/6fc265cfbb4a/41540_2017_14_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d20d/5460168/a1a352bdebca/41540_2017_14_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d20d/5460168/bb59cb422b08/41540_2017_14_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d20d/5460168/706abcfed656/41540_2017_14_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d20d/5460168/e822e9aec9f5/41540_2017_14_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d20d/5460168/ceae6de032db/41540_2017_14_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d20d/5460168/6fc265cfbb4a/41540_2017_14_Fig6_HTML.jpg

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