Grupo de Investigación de Reumatología (GIR), Instituto de Investigación Biomédica de A Coruña (INIBIC), Complexo Hospitalario Universitario de A Coruña (CHUAC), Sergas, Universidade da Coruña (UDC), As Xubias de Arriba 84, 15006, A Coruña, Spain.
Universidade da Coruña (UDC), Grupo de Investigación de Reumatología y Salud (GIR-S), Departamento de Fisioterapia, Medicina y Ciencias Biomédicas, Facultad de Fisioterapia, Campus de Oza, 15008, A Coruña, Spain.
Osteoarthritis Cartilage. 2021 Aug;29(8):1147-1154. doi: 10.1016/j.joca.2021.04.011. Epub 2021 Apr 30.
We aimed to provide a model to predict the prospective development of radiographic KOA (rKOA).
Baseline sera from 333 non-radiographic KOA subjects belonging to OA Initiative (OAI) who developed or not, rKOA during a follow-up period of 96 months were used in this study. The exploratory cohort included 200 subjects, whereas the replication cohort included 133. The levels of inter-alpha trypsin inhibitor heavy chain 1 (ITIH1), complement C3 (C3) and calcyclin (S100A6), identified in previous large proteomic analysis, were analyzed by using sandwich immunoassays on suspension bead arrays. The association of protein levels and clinical covariates with rKOA incidence was assessed by combining logistic regression analysis, Receiver Operating Characteristic (ROC) analysis, Integrated Discrimination Improvement (IDI) analysis and Kaplan-Meier curves.
Levels of ITIH1, C3 and S100A6 were significantly associated with the prospective development of rKOA, showing an area under the curve (AUC) of 0.713 (0.624-0.802), 0.708 (0.618-0.799) and 0.654 (0.559-0.749), respectively to predict rKOA in the replication cohort. The inclusion of ITIH1 in the clinical model (age, gender, BMI, previous knee injury and WOMAC pain) improved the predictive capacity of the clinical covariates (AUC = 0.754 [0.670-0.838]) producing the model with the highest AUC (0.786 [0.705-0.867]) and the highest IDI index (9%). High levels of ITIH1 were also associated with an earlier onset of the disease.
A clinical model including protein biomarkers that predicts incident rKOA has been developed. Among the tested biomarkers, ITIH1 showed potential to improve the capacity to predict rKOA incidence in clinical practice.
本研究旨在建立一种预测影像学膝骨关节炎（rKOA）进展的模型。
本研究使用了来自 OA 倡议（OAI）的 333 名无 rKOA 受试者的基线血清，这些受试者在 96 个月的随访期间发生或未发生 rKOA。其中，探索性队列包括 200 名受试者，而复制性队列包括 133 名受试者。先前的大规模蛋白质组学分析中发现的几种蛋白质（如 inter-alpha trypsin inhibitor heavy chain 1 (ITIH1)、补体 C3 (C3) 和 calcyclin (S100A6)）的水平，通过使用悬浮珠阵列上的夹心免疫测定法进行分析。通过结合逻辑回归分析、接收者操作特征（ROC）分析、综合判别改善（IDI）分析和 Kaplan-Meier 曲线，评估蛋白质水平和临床协变量与 rKOA 发生率的关联。
ITIH1、C3 和 S100A6 的水平与 rKOA 的前瞻性发展显著相关，在复制队列中，ROC 曲线下面积（AUC）分别为 0.713（0.624-0.802）、0.708（0.618-0.799）和 0.654（0.559-0.749），可用于预测 rKOA。在临床模型（年龄、性别、BMI、既往膝关节损伤和 WOMAC 疼痛）中纳入 ITIH1 可提高临床协变量的预测能力（AUC=0.754 [0.670-0.838]），从而产生 AUC 最高（0.786 [0.705-0.867]）和 IDI 指数最高（9%）的模型。高水平的 ITIH1 也与疾病的早期发病有关。
已经建立了一种包含预测 rKOA 发生的蛋白生物标志物的临床模型。在测试的生物标志物中，ITIH1 具有提高临床实践中预测 rKOA 发生率的潜力。
