差异相关网络分析确定了原发性骨关节炎患者全关节置换无反应者的新代谢组学特征。
Differential correlation network analysis identified novel metabolomics signatures for non-responders to total joint replacement in primary osteoarthritis patients.
作者信息
Costello Christie A, Hu Ting, Liu Ming, Zhang Weidong, Furey Andrew, Fan Zhaozhi, Rahman Proton, Randell Edward W, Zhai Guangju
机构信息
Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St. John's, NL, A1B 3V6, Canada.
Department of Computer Science, Faculty of Science, Memorial University of Newfoundland, St. John's, NL, Canada.
出版信息
Metabolomics. 2020 Apr 25;16(5):61. doi: 10.1007/s11306-020-01683-1.
INTRODUCTION
Up to one third of total joint replacement patients (TJR) experience poor surgical outcome.
OBJECTIVES
To identify metabolomic signatures for non-responders to TJR in primary osteoarthritis (OA) patients.
METHODS
A newly developed differential correlation network analysis method was applied to our previously published metabolomic dataset to identify metabolomic network signatures for non-responders to TJR.
RESULTS
Differential correlation networks involving 12 metabolites and 23 metabolites were identified for pain non-responders and function non-responders, respectively.
CONCLUSION
The differential networks suggest that inflammation, muscle breakdown, wound healing, and metabolic syndrome may all play roles in TJR response, warranting further investigation.
引言
高达三分之一的全关节置换术（TJR）患者手术效果不佳。
目的
识别原发性骨关节炎（OA）患者中TJR无反应者的代谢组学特征。
方法
将一种新开发的差异相关网络分析方法应用于我们之前发表的代谢组学数据集，以识别TJR无反应者的代谢组学网络特征。
结果
分别为疼痛无反应者和功能无反应者识别出了涉及12种代谢物和23种代谢物的差异相关网络。
结论
差异网络表明，炎症、肌肉分解、伤口愈合和代谢综合征可能在TJR反应中均起作用，值得进一步研究。
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