The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.
Department of Rheumatology and Immunology, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China.
Front Immunol. 2024 Nov 14;15:1468810. doi: 10.3389/fimmu.2024.1468810. eCollection 2024.
To characterize the inflammatory proteome in both serum and synovial fluid (SF) of patients with gout, in comparison to healthy controls and individuals with osteoarthritis (OA), by utilizing a high-quality, high-throughput proteomic analysis technique.
Using the Olink Target 48 Inflammation panel, we measured serum concentrations of 45 inflammatory proteins in gout, OA, and healthy controls. We analyzed protein levels in SF samples from gout and OA, performed ROC curve analyses to identify diagnostic biomarkers, evaluate efficacy, and set cut-off values. Additionally, A protein-protein interaction (PPI) network was used to study protein relationships and significance.
We have delineated the proteomic landscape of gout and identified 20 highly differentially expressed proteins (DEPs) in the serum of gout patients in comparison to that of healthy controls, which included VEGF-A, MMP-1, TGF-α, and OSM with corresponding area under the curve (AUC) values of 0.95, 0.95, 0.92, and 0.91 respectively. For the analysis of synovial fluid, 6 proteins were found to be elevated in gout in contrast to osteoarthritis (OA), among which IP-10, VEGF-A, IL-8, and MIP-3β had corresponding AUC values of 0.78, 0.78, 0.76, and 0.75 respectively. The protein-protein interaction (PPI) network analysis identified significantly prominent pathways in gout.
This research marks a significant advancement in elucidating the inflammatory profile present in the serum and synovial fluid of individuals suffering from gout. Our discoveries have identified several novel proteins in both serum and synovial fluid that are potential biomarkers for diagnostic purposes and are believed to have critical roles as pathogenic factors in the pathophysiology of gout.
利用高质量、高通量的蛋白质组学分析技术，对痛风患者的血清和滑液（SF）中的炎症蛋白质组进行特征描述，并与健康对照和骨关节炎（OA）个体进行比较。
我们使用 Olink Target 48 炎症面板，测量了痛风、OA 和健康对照组血清中 45 种炎症蛋白的浓度。我们分析了痛风和 OA 的 SF 样本中的蛋白水平，进行了 ROC 曲线分析以识别诊断生物标志物、评估疗效并设定截止值。此外，还使用蛋白质-蛋白质相互作用（PPI）网络来研究蛋白质关系和意义。
我们描绘了痛风的蛋白质组学图谱，并鉴定出痛风患者血清中 20 种高度差异表达的蛋白（DEPs），与健康对照组相比，其中包括 VEGF-A、MMP-1、TGF-α和 OSM，相应的曲线下面积（AUC）值分别为 0.95、0.95、0.92 和 0.91。对于滑液分析，发现 6 种蛋白在痛风中与 OA 相比升高，其中 IP-10、VEGF-A、IL-8 和 MIP-3β 相应的 AUC 值分别为 0.78、0.78、0.76 和 0.75。蛋白质-蛋白质相互作用（PPI）网络分析确定了痛风中显著突出的途径。
这项研究标志着在阐明痛风患者血清和滑液中炎症特征方面取得了重大进展。我们的发现确定了血清和滑液中几种潜在的诊断生物标志物的新蛋白，它们被认为在痛风的病理生理学中作为致病因素具有关键作用。
