Cruz Criselda Jean G, Yang Chao-Chun
Department of Dermatology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
International Center for Wound Repair and Regeneration, National Cheng Kung University, Tainan, Taiwan.
Front Mol Biosci. 2023 Jul 21;10:1196323. doi: 10.3389/fmolb.2023.1196323. eCollection 2023.
Psoriasis, a chronic, multisystemic inflammatory disease affecting millions of people globally, manifests as erythematous, thick, scaly plaques on the skin. Clinical evaluation remains to be the benchmark for diagnosis and monitoring of this debilitating disease. With current advancements in targeted molecular therapy for psoriasis such as biologics, molecular detection methods may also help guide clinical decisions and therapeutic strategies through quantification of circulating biomarkers, which could reflect the underlying pathogenic events happening at a certain point of the disease course. In this review, we will discuss how biomarkers are detected in serum samples using enzyme-linked immunosorbent assay (ELISA). This review will feature candidate biomarkers supported by clinical data for psoriasis including, but not limited to, cytokines, chemokines, adipokines, and antimicrobial peptides. A better understanding of the common method used for biomarker detection would enable physicians to interpret and correlate laboratory results with the disease pathogenesis and clinical outcomes, e.g., severity assessment and/or therapeutic response. With better health outcomes as the main goal, the utility of such information to evaluate and even predict treatment response would be a major step closer towards patient-tailored management.
银屑病是一种慢性、多系统炎症性疾病,全球数百万人受其影响,表现为皮肤上出现红斑、增厚、鳞屑性斑块。临床评估仍然是诊断和监测这种使人衰弱疾病的基准。随着银屑病靶向分子疗法(如生物制剂)的当前进展,分子检测方法也可能通过量化循环生物标志物来帮助指导临床决策和治疗策略,这些生物标志物可以反映疾病进程中某个特定点发生的潜在致病事件。在本综述中,我们将讨论如何使用酶联免疫吸附测定(ELISA)在血清样本中检测生物标志物。本综述将介绍有临床数据支持的银屑病候选生物标志物,包括但不限于细胞因子、趋化因子、脂肪因子和抗菌肽。更好地理解用于生物标志物检测的常用方法将使医生能够解释实验室结果并将其与疾病发病机制和临床结果(如严重程度评估和/或治疗反应)相关联。以更好的健康结果为主要目标,此类信息用于评估甚至预测治疗反应的效用将朝着个性化患者管理迈出重要一步。