Duke Molecular Physiology Institute, Durham, NC, USA.
Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA.
Sci Adv. 2023 Jan 25;9(4):eabq5095. doi: 10.1126/sciadv.abq5095.
We aimed to identify markers in blood (serum) to predict clinically relevant knee osteoarthritis (OA) progression defined as the combination of both joint structure and pain worsening over 48 months. A set of 15 serum proteomic markers corresponding to 13 total proteins reached an area under the receiver operating characteristic curve (AUC) of 73% for distinguishing progressors from nonprogressors in a cohort of 596 individuals with knee OA. Prediction based on these blood markers was far better than traditional prediction based on baseline structural OA and pain severity (59%) or the current "best-in-class" biomarker for predicting OA progression, urinary carboxyl-terminal cross-linked telopeptide of type II collagen (58%). The generalizability of the marker set was confirmed in a second cohort of 86 individuals that yielded an AUC of 70% for distinguishing joint structural progressors. Blood is a readily accessible biospecimen whose analysis for these biomarkers could facilitate identification of individuals for clinical trial enrollment and those most in need of treatment.
我们旨在鉴定血液（血清）中的标志物，以预测临床上有意义的膝关节骨关节炎（OA）进展，其定义为关节结构和疼痛在 48 个月内恶化的组合。在 596 例膝关节 OA 患者的队列中，一组 15 种血清蛋白质标志物对应 13 种总蛋白，其区分进展者和非进展者的受试者工作特征曲线（ROC）下面积（AUC）达到 73%。基于这些血液标志物的预测远远优于基于基线结构 OA 和疼痛严重程度的传统预测（59%），也优于目前预测 OA 进展的“最佳类别”生物标志物，即 II 型胶原羧基末端交联肽（58%）。在另一组 86 名个体中，该标志物集的通用性得到了确认，其区分关节结构进展者的 AUC 为 70%。血液是一种易于获得的生物样本，对这些生物标志物的分析可以帮助确定哪些个体需要参加临床试验，以及哪些个体最需要治疗。
