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by: Gaurav S. Rana, Timothy P. York, Jeffery S. Edmiston, Barbara K. Zedler, Joel G. Pounds, Joshua N. Adkins, Susan M. Varnum, Richard D. Smith, Zaigang Liu, Guoya Li, Bradley T. Webb, Edward L. Murrelle, Jason W. Flora

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Abstract

Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of morbidity and mortality in the United States and cigarette smoking is a primary determinant of the disease. COPD is characterized by chronic airflow limitation as measured by the forced expiratory volume in one second (FEV(1)). In this study, the plasma proteomes of 38 middle-aged or older adult smokers with mild to moderate COPD, with FEV(1) decline characterized as either rapid (RPD, n = 20) or slow or absent (SLW, n = 18), were interrogated using a comprehensive high-throughput proteomic approach, the accurate mass and time (AMT) tag technology. This technology is based upon a putative mass and time tag database (PMT), high-resolution LC separations and high mass accuracy measurements using FT-ICR MS with a 9.4-T magnetic field. The peptide and protein data were analyzed using three statistical approaches to address ambiguities related to the high proportion of missing data inherent to proteomic analysis. The RPD and SLW groups were differentiated by 55 peptides which mapped to 33 unique proteins. Twelve of the proteins have known roles in the complement or coagulation cascade and, despite an inability to adjust for some factors known to affect lung function decline, suggest potential mechanistic biomarkers associated with the rate of lung function decline in COPD. Whether these proteins are the cause or result of accelerated decline will require further research.

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  • biomarkers, chronic, clinical, copd, disease, lung, mass_spectrometry, obstructive, plasma, pnnl, proteomics, pulmonary, smoking, study

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