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.

中文翻译：

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差异相关网络分析为原发性骨关节炎患者的全关节置换无反应者确定了新的代谢组学特征。

简介多达三分之一的关节置换患者（TJR）的手术结局较差。目的确定原发性骨关节炎（OA）患者对TJR无反应的代谢组学特征。方法将新开发的差分相关网络分析方法应用于我们先前发布的代谢组学数据集，以识别对TJR无反应者的代谢组学网络特征。结果确定了涉及疼痛无反应者和功能无反应者的分别涉及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，肌肉衰竭，伤口愈合和代谢综合征都可能在TJR反应中起作用，有待进一步研究。