Department of Hematology, Clinical Immunology, and Infectious Diseases, Ehime University Graduate School of Medicine, Toon, Ehime, 791-0295, Japan.
Division of Proteomics Research, Proteo-Science Center, Ehime University, Toon, Ehime, 791-0295, Japan.
Arthritis Res Ther. 2017 Sep 29;19(1):218. doi: 10.1186/s13075-017-1429-3.
Targeted proteomics, which involves quantitative analysis of targeted proteins using selected reaction monitoring (SRM) mass spectrometry, has emerged as a new methodology for discovery of clinical biomarkers. In this study, we used targeted serum proteomics to identify circulating biomarkers for prediction of disease activity and organ involvement in antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV).
A large-scale SRM assay targeting 135 biomarker candidates was established using a triple-quadrupole mass spectrometer coupled with nanoflow liquid chromatography. Target proteins in serum samples from patients in the active and remission (6 months after treatment) stages were quantified using the established assays. Identified marker candidates were further validated by enzyme-linked immunosorbent assay using serum samples (n = 169) collected in a large-cohort Japanese study (the RemIT-JAV-RPGN study).
Our proteomic analysis identified the following proteins as biomarkers for discriminating patients with highly active AAV from those in remission or healthy control subjects: tenascin C (TNC), C-reactive protein (CRP), tissue inhibitor of metalloproteinase 1 (TIMP1), leucine-rich alpha-2-glycoprotein 1, S100A8/A9, CD93, matrix metalloproteinase 9, and transketolase (TKT). Of these, TIMP1 was the best-performing marker of disease activity, allowing distinction between mildly active AAV and remission. Moreover, in contrast to CRP, serum levels of TIMP1 in patients with active AAV were significantly higher than those in patients with infectious diseases. The serum levels of TKT and CD93 were higher in patients with renal involvement than in those without, and they predicted kidney outcome. The level of circulating TNC was elevated significantly in patients with lung infiltration. AAV severity was associated with markers reflecting organ involvement (TKT, CD93, and TNC) rather than inflammation. The eight markers and myeloperoxidase (MPO)-ANCA were clustered into three groups: MPO-ANCA, renal involvement (TKT and CD93), and inflammation (the other six markers).
We have identified promising biomarkers of disease activity, disease severity, and organ involvement in AAV with a targeted proteomics approach using serum samples obtained from a large-cohort Japanese study. Especially, our analysis demonstrated the effectiveness of TIMP1 as a marker of AAV activity. In addition, we identified TKT and CD93 as novel markers for evaluation of renal involvement and kidney outcome in AAV.
靶向蛋白质组学涉及使用选定反应监测 (SRM) 质谱对靶向蛋白进行定量分析,已成为发现临床生物标志物的新方法。在这项研究中,我们使用靶向血清蛋白质组学来鉴定循环生物标志物,以预测抗中性粒细胞胞质抗体 (ANCA) 相关性血管炎 (AAV) 的疾病活动和器官受累。
使用三重四极杆质谱仪与纳流液相色谱联用,建立了针对 135 个生物标志物候选物的大规模 SRM 测定法。使用建立的测定法定量分析处于活动期和缓解期(治疗后 6 个月)阶段的患者血清样本中的目标蛋白。使用在大型日本队列研究(RemIT-JAV-RPGN 研究)中收集的血清样本(n=169)通过酶联免疫吸附试验进一步验证鉴定的候选标记物。
我们的蛋白质组学分析确定了以下蛋白质作为区分高度活跃的 AAV 患者与缓解期或健康对照组患者的生物标志物:腱糖蛋白 C(TNC)、C 反应蛋白(CRP)、金属蛋白酶组织抑制剂 1(TIMP1)、富含亮氨酸的α-2-糖蛋白 1、S100A8/A9、CD93、基质金属蛋白酶 9 和转酮醇酶(TKT)。其中,TIMP1 是疾病活动的最佳表现标志物,可区分轻度活跃的 AAV 和缓解期。此外,与 CRP 不同,活动期 AAV 患者的血清 TIMP1 水平明显高于感染性疾病患者。与无肾脏受累的患者相比,有肾脏受累的患者的血清 TKT 和 CD93 水平更高,它们预测了肾脏结局。肺浸润患者的循环 TNC 水平显著升高。AAV 严重程度与反映器官受累的标志物(TKT、CD93 和 TNC)相关,而与炎症无关。这 8 个标志物和髓过氧化物酶 (MPO)-ANCA 聚类为三组:MPO-ANCA、肾脏受累(TKT 和 CD93)和炎症(其他 6 个标志物)。
我们使用来自大型日本队列研究的血清样本,通过靶向蛋白质组学方法鉴定了 AAV 疾病活动、疾病严重程度和器官受累的有前途的生物标志物。特别是,我们的分析表明 TIMP1 作为 AAV 活动的标志物的有效性。此外,我们还发现 TKT 和 CD93 是评估 AAV 肾脏受累和肾脏结局的新标志物。