title: Selection of disease-specific biomarkers by integrating inflammatory mediators with clinical informatics in AECOPD patients: a preliminary study.
abstract: 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.
authors: Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
authors: Hong
authors: H
authors: Chen
authors: Zhenju
authors: Z
authors: Song
authors: Mengjia
authors: M
authors: Qian
authors: Chunxue
authors: C
authors: Bai
authors: Xiangdong
authors: X
authors: Wang
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000097:blood*; D018925:Chemokines / Q000097:blood; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D007249:Inflammation / Q000097:blood / Q000503:physiopathology; D018836:Inflammation Mediators / Q000494:pharmacology*; D008297:Male; D008490:Medical Informatics; D040901:Proteomics; D029424:Pulmonary Disease, Chronic Obstructive / Q000097:blood* / Q000503:physiopathology
chemical_list: D015415:Biomarkers; D018925:Chemokines; D018836:Inflammation Mediators