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Background: Chronic obstructive pulmonary disease (COPD) is an inflammatory lung disease with associated systemic effects., Objective: To use gene expression microarrays in peripheral blood leukocytes of current and former cigarette smokers to identify differences associated with COPD., Materials and Methods: Random forest modelling and a split-sample case-control approach were used to identify candidate predictors., Results: We identified 1013 genes and one smoking exposure variable that differentiated current and former smokers with or without COPD. This predictor set was reduced to a nine-gene classifier (IL6R, CCR2, PPP2CB, RASSF2, WTAP, DNTTIP2, GDAP1, LIPE and RPL14)., Conclusion: These gene expression profiles represent potential biomarkers for COPD and may help increase mechanistic understanding of the disease.

Although cigarette smoking is recognized as the most important cause of chronic obstructive pulmonary disease (COPD), the pathophysiological mechanisms underlying the lung function decline are not well understood. Using off-line strong cation exchange fractionation with RP-LC-ESI-MS/MS and robust database searching, 1758 tryptic peptides were identified in plasma samples from cigarette smokers. Using two statistical approaches, 30 peptides were identified to be associated with the annualized rate of lung function decline over 5 years among smokers with COPD characterized as having rapid (n = 18) or slow (n = 18) decline and 18 smokers without COPD. The identified peptides belong to proteins that are involved in the complement or coagulation systems or have antiprotease or metabolic functions. This research demonstrates the utility of proteomic profiling to improve the understanding of molecular mechanisms involved in cigarette smoking-related COPD by identifying plasma proteins that correlate with decline in lung function.