Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
J Cell Mol Med. 2012 Jun;16(6):1286-97. doi: 10.1111/j.1582-4934.2011.01416.x.
Systemic inflammation is a major factor influencing the outcome and quality of patient with chronic obstructive pulmonary disease (COPD) and acute exacerbations (AECOPD). Because of the inflammatory complexity, a great challenge is still confronted to optimize the identification and validation of disease-specific biomarkers. This study aimed at developing a new protocol of specific biomarker evaluation by integrating proteomic profiles of inflammatory mediators with clinical informatics in AECOPD patients, understand better their function and signal networks. Plasma samples were collected from healthy non-smokers or patients with stable COPD (sCOPD) or AECOPD on days 1 and 3 of the admission and discharging day (day 7-10). Forty chemokines were measured using a chemokine multiplex antibody array. Clinical informatics was achieved by a Digital Evaluation Score System (DESS) for assessing severity of patients. Chemokine data was compared among different groups and its correlation with DESS scores was performed by SPSS software. Of 40 chemokines, 30 showed significant difference between sCOPD patients and healthy controls, 16 between AECOPD patients and controls and 13 between AECOPD patients and both sCOPD and controls, including BTC, IL-9, IL-18Bpa, CCL22,CCL23, CCL25, CCL28, CTACK, LIGHT, MSPa, MCP-3, MCP-4 and OPN. Of them, some had significant correlation with DESS scores. There is a disease-specific profile of inflammatory mediators in COPD and AECOPD patients which may have a potential diagnostics together with clinical informatics of patients. Our preliminary study suggested that integration of proteomics with clinical informatics can be a new way to validate and optimize disease-special biomarkers.
全身炎症是影响慢性阻塞性肺疾病（COPD）和急性加重（AECOPD）患者结局和生活质量的主要因素。由于炎症的复杂性，仍然面临着一个巨大的挑战，即优化疾病特异性生物标志物的识别和验证。本研究旨在通过整合 AECOPD 患者炎症介质的蛋白质组谱和临床信息学，开发一种新的特定生物标志物评估方案，以更好地了解其功能和信号网络。在入院第 1 天和第 3 天以及出院日（第 7-10 天）采集健康非吸烟者或稳定期 COPD（sCOPD）患者或 AECOPD 患者的血浆样本。使用趋化因子多重抗体阵列测量了 40 种趋化因子。临床信息学通过数字评估评分系统（DESS）来评估患者的严重程度来实现。通过 SPSS 软件比较不同组之间的趋化因子数据，并与 DESS 评分进行相关性分析。在 40 种趋化因子中，30 种在 sCOPD 患者和健康对照组之间、16 种在 AECOPD 患者和对照组之间、13 种在 AECOPD 患者和 sCOPD 患者及对照组之间存在显著差异，包括 BTC、IL-9、IL-18Bpa、CCL22、CCL23、CCL25、CCL28、CTACK、LIGHT、MSPa、MCP-3、MCP-4 和 OPN。其中一些与 DESS 评分有显著相关性。COPD 和 AECOPD 患者存在特定的炎症介质疾病特征谱，可能具有与患者临床信息相结合的潜在诊断价值。我们的初步研究表明，蛋白质组学与临床信息学的结合可能是验证和优化疾病特异性生物标志物的一种新方法。
