评估多种血管炎疾病活动的潜在血清生物标志物。
Evaluation of Potential Serum Biomarkers of Disease Activity in Diverse Forms of Vasculitis.
机构信息
From Boston University, Boston, Massachusetts; University of Arizona, Tucson, Arizona; University of Michigan, Ann Arbor, Michigan; University of South Florida, Tampa, Florida, USA; Mount Sinai Hospital, Toronto; McMaster University, Hamilton, Ontario, Canada; University of Utah, Salt Lake City, Utah; Cleveland Clinic, Cleveland, Ohio; University of Pennsylvania, Philadelphia; University of Pittsburgh, Pittsburgh, Pennsylvania; Johns Hopkins University, Baltimore, Maryland; Mayo Clinic, Rochester, Minnesota; VA Boston Healthcare System, Boston, Massachusetts, USA.
A. Rodriguez-Pla, MD, PhD, MPH, Boston University, and the University of Arizona; R.L. Warner, PhD, University of Michigan; D. Cuthbertson, MS, University of South Florida; S. Carette, MD, Mount Sinai Hospital; N.A. Khalidi, MD, McMaster University; C.L. Koening, MD, MS, University of Utah; C.A. Langford, MD, MHS, Cleveland Clinic; C.A. McAlear, MD, University of Pennsylvania; L.W. Moreland, MD, University of Pittsburgh; C. Pagnoux, MD, MPH, Mount Sinai Hospital; P. Seo, MD, MHS, Johns Hopkins University; U. Specks, MD, Mayo Clinic; A.G. Sreih, MD, University of Pennsylvania; S.R. Ytterberg, MD, Mayo Clinic; K.J. Johnson, MD, University of Arizona; P.A. Merkel, MD, MPH, University of Pennsylvania; P.A. Monach, MD, PhD, Boston University, and the VA Boston Healthcare System.
出版信息
J Rheumatol. 2020 Jul 1;47(7):1001-1010. doi: 10.3899/jrheum.190093. Epub 2019 Sep 1.
OBJECTIVE
We evaluated potential circulating biomarkers of disease activity in giant cell arteritis (GCA), Takayasu arteritis (TA), polyarteritis nodosa (PAN), and eosinophilic granulomatosis with polyangiitis (EGPA).
METHODS
A panel of 22 serum proteins was tested in patients enrolled in the Vasculitis Clinical Research Consortium Longitudinal Studies of GCA, TA, PAN, or EGPA. Mixed models were used for most analyses. A J48 classification tree method was used to find the most relevant markers to differentiate between active and inactive GCA.
RESULTS
Tests were done on 418 samples from 152 patients (60 GCA, 29 TA, 26 PAN, 37 EGPA), during both active vasculitis and remission. In GCA, these showed significant (p < 0.05) differences between disease states: B cell-attracting chemokine 1 (BCA)-1/CXC motif ligand 13 (CXCL13), erythrocyte sedimentation rate (ESR), interferon-γ-induced protein 10/CXC motif chemokine 10, soluble interleukin 2 receptor α (sIL-2Rα), and tissue inhibitor of metalloproteinase-1 (TIMP-1). In EGPA, these showed significant increases during active disease: granulocyte colony-stimulating factor (G-CSF), granulocyte-macrophage-CSF, interleukin (IL)-6, IL-15, and sIL-2Rα. BCA-1/CXCL13 also showed such increases, but only after adjustment for treatment. In PAN, ESR and matrix metalloprotease (MMP)-3 showed significant differences between disease states. Differences in biomarker levels between diseases were significant for 11 markers and were more striking (all p < 0.01) than differences related to disease activity. A combination of lower values of TIMP-1, IL-6, interferon-γ, and MMP-3 correctly classified 87% of samples with inactive GCA.
CONCLUSION
We identified novel biomarkers of disease activity in GCA and EGPA. Differences of biomarker levels between diseases, independent of disease activity, were more apparent than differences related to disease activity. Further studies are needed to determine whether these serum proteins have potential for clinical use in distinguishing active disease from remission or in predicting longer-term outcomes.
目的
我们评估了巨细胞动脉炎（GCA）、Takayasu 动脉炎（TA）、多发性大动脉炎（PAN）和嗜酸性肉芽肿伴多血管炎（EGPA）中潜在的疾病活动的循环生物标志物。
方法
在血管炎临床研究联盟 GCA、TA、PAN 或 EGPA 的纵向研究中，对纳入的患者进行了 22 种血清蛋白的检测。使用混合模型进行大多数分析。使用 J48 分类树方法找到区分活动和不活动 GCA 的最相关标记物。
结果
对来自 152 名患者（60 名 GCA、29 名 TA、26 名 PAN、37 名 EGPA）的 418 个样本进行了检测，这些样本在活动期和缓解期均有进行。在 GCA 中，这些标志物在疾病状态之间存在显著差异（p < 0.05）：B 细胞趋化因子 1（BCA）-1/CXC 基序趋化因子 13（CXCL13）、红细胞沉降率（ESR）、干扰素-γ 诱导蛋白 10/CXC 基序趋化因子 10、可溶性白细胞介素 2 受体 α（sIL-2Rα）和组织金属蛋白酶抑制剂-1（TIMP-1）。在 EGPA 中，这些标志物在疾病活动期显著增加：粒细胞集落刺激因子（G-CSF）、粒细胞-巨噬细胞集落刺激因子、白细胞介素（IL）-6、IL-15 和 sIL-2Rα。BCA-1/CXCL13 也表现出这种增加，但仅在调整治疗后。在 PAN 中，ESR 和基质金属蛋白酶（MMP）-3 之间存在疾病状态的显著差异。疾病之间的生物标志物水平差异对 11 种标志物有显著意义，且差异比与疾病活动相关的差异更明显（均 p < 0.01）。TIMP-1、IL-6、干扰素-γ 和 MMP-3 值较低的组合正确分类了 87%的无活动 GCA 样本。
结论
我们在 GCA 和 EGPA 中确定了疾病活动的新型生物标志物。疾病之间的生物标志物水平差异，独立于疾病活动，比与疾病活动相关的差异更为明显。需要进一步研究以确定这些血清蛋白是否有可能用于区分活动期疾病与缓解期或预测更长期的结果。
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