Studies On A Panel Of Biomarkers In Acute Exacerbations Of Chronic Obstructive Pulmonary Disease

Part Ⅰ Proteomics-based biomarkers in chronic obstructive pulmonary diseaseObjective:The proteomic analysis highlights ways to identify novel biomarkers for diagnosis, therapy and prognosis in COPD. Human samples have been used for COPD proteomic research, each with its own merits and demerits. In first part of this thesis, we aimed at discussing the feasibility of clinical studies on COPD proteomics and the potential panels of candidate biomarkers detected in human samples that are sensitive to the progress of COPD, disease-specific to COPD and associated with the status of the patients.Methods:Human COPD studies based on proteomics were searched and reviewed. Study subjects, methods, potential biomarkers in all these reports were summarized and analyzed. Some biomarkers indicated in COPD were also compared to those in other chronic pulmonary diseases.Results:Altogether8studies were included. Among these studies, healthy controls, healthy smokers, and patients with al-antitrypsin deficiency, asthma, cystic fibrosis, IPF and bronchiectasis were also recruited for comparison purpose. Samples were collected from biopsy, BALF, induced sputum and blood. Several proteomics methods were employed, such as2-DE, RP-HPLC, tandom-MS/MS, MALDI, SELDI. Potential biomarkers played critical roles in oxidization, inflammation, and remodeling.Conclusions:Biomarker patterns were better to indicate status of disease than single protein. It is important to clarify the source of the samples, the efficiency and quality when dealing with large amount of candidates and the specificity of biomarkers according to the severity, therapeutic effects, progress and prognosis of the disease. There is also an urgent need to establish a method to combine clinical information with omics data. Part Ⅱ Alterations of plasma inflammatory biomarkers in the healthy and chronic obstructive pulmonary disease patients with or without acute exacerbationObjective:Systemic inflammation has been considered as one of major pathophysiologic alterations in AECOPD. This part aimed at developing disease-specific biomarker evaluation by integrating proteomic profiles of inflammatory mediators in AECOPD with clinical and biological informatics.Methods:Plasma samples from18subjects including healthy people or patients with stable COPD or AECOPD were collected to measure507inflammatory mediators using antibody microarray. Clinical informatics was achieved by a Digital Evaluation Score System (DESS) for assessing severity of patients.Results:20mediators were significantly different between3groups (p<0.05), of which, Cerberus1, Growth Hormone R, IL-1F6, IL-17B R, IL-17D, IL-19, Lymphotoxin-β, MMP-10, Thrombopoietin and TLR4were correlated with DESS scores (p<0.05). There was a down-regulation of systemic inflammatory responses in AECOPD.Conclusion:The integration of proteomic profile with clinical informatics as part of clinical bioinformatics is important to screen disease-specific and disease-staged biomarkers. Part Ⅲ Selection of disease-specific dynamic biomarkers by integrating inflammatory mediators with clinical informatics in patients with AECOPDObjective:The present part aimed at developing a new protocol of specific biomarker evaluation by integrating proteomic profiles of inflammatory mediators with clinical informatics in patients with AECOPD, in order to understand the biological function and signal networks.Methods:Plasma of healthy non-smokers or patients with stable COPD was collected, as well as AECOPD patients on days1and3of the admission and discharging day (day7-10). Chemokine concentration was measured using a chemokine multiplex antibody array. Clinical informatics was achieved by DESS for assessing severity of patients. Chemokine data was compared among different groups and its correlation with DESS variables was performed by SPSS software.Results:Of40inflammatory mediators,30showed statistically significant difference between COPD patients and healthy controls,16between AECOPD patients and controls.13chemokines, including BTC, IL-9, IL-18Bpa, CCL22, CCL23, CCL25, CCL28, CTACK, LIGHT, MSPa, MCP-3, MCP-4and OPN, showed statistically significance between AECOPD patients and both COPD and controls. Correlation was indicated among most DESS variables and most chemokines (p<0.05).Conclusion: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.