Correlation of serum protein biomarkers with disease activity in psoriatic arthritis
Correlation of serum protein biomarkers with disease activity in psoriatic arthritis
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DOI：
10.1080/1744666x.2020.1729129
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发表时间：
2020-02-23
影响因子：
4.4
通讯作者：
Kavanaugh, A.
中科院分区：
文献类型：
--
作者：
Boyd, T. A.;Eastman, P. S.;Kavanaugh, A.
目的：评估血清蛋白生物标志物与银屑病关节炎（PsA）不同领域疾病活动度的相关性。材料和方法：从加州大学圣地亚哥分校 (UCSD) 关节炎诊所招募了 45 名符合银屑病关节炎分类 (CASPAR) 标准的成年 PsA 患者组成的横断面队列。收集临床数据和血清样本，并分析血清中假设与 PsA 疾病活动相关的蛋白质生物标志物。评估了跨疾病领域的临床疾病活动测量的相关性。结果：与综合指数和疾病领域相关性最高的生物标志物是 SAA、IL-6、YKL-40 和 ICAM-1。此外，一些生物标志物与个体综合指数和/或疾病领域具有中等相关性。观察到与某些生物标志物的相关性较低或没有相关性，例如MMP-3、MMP-1、EGF、VEGF 和 IL-6R。相比之下，所有生物标志物与某些疾病领域的相关性较低；具体来说，疼痛、牛皮癣体表面积百分比以及患者整体评估。针对类风湿性关节炎 (RA) 开发的多生物标志物疾病活动评分 (MBDA) 显示与 PsA 的大多数综合指数和某些疾病领域具有高度相关性。结论：这些数据表明生物标志物分析可以反映 PsA 跨疾病领域的疾病活动性。某些领域可能会受益于其他生物标志物的评估。
Objective: To assess the correlation of serum protein biomarkers with disease activity across different domains of psoriatic arthritis (PsA). Material and methods: A cross-sectional cohort of 45 adult patients with PsA fulfilling the classification for psoriatic arthritis (CASPAR) criteria was recruited from University of California San Diego (UCSD) Arthritis Clinics. Clinical data and serum samples were collected and serum was analyzed for protein biomarkers hypothesized to be relevant to disease activity in PsA. Correlations were evaluated for clinical disease activity measures across disease domains. Results: Biomarkers with the highest correlation to the composite indices and disease domains were SAA, IL-6, YKL-40, and ICAM-1. In addition, several biomarkers were moderately correlated with individual composite indices and/or disease domains. Low or no correlation was observed with some biomarkers, e.g. MMP-3, MMP-1, EGF, VEGF, and IL-6R. In contrast, the correlation of all biomarkers with certain disease domains was low; specifically, pain, percent body surface area of psoriasis, and patient global assessment. The multi-biomarker disease activity score (MBDA) developed for rheumatoid arthritis (RA) showed high correlations with most composite indices and some disease domains in PsA. Conclusions: These data suggest biomarker analysis can reflect disease activity across disease domains in PsA. Certain domains would likely benefit from the evaluation of additional biomarkers.