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Chronic obstructive pulmonary disease (COPD), characterized by chronic airflow limitation, is a serious public health concern. In this study, we used proton nuclear magnetic resonance (1H NMR) spectroscopy to identify and quantify metabolites associated with lung function in COPD. Plasma and urine were collected from 197 adults with COPD and from 195 without COPD. Samples were assayed using a 600 MHz NMR spectrometer, and the resulting spectra were analyzed against quantitative spirometric measures of lung function. After correcting for false discoveries and adjusting for covariates (sex, age, smoking) several spectral regions in urine were found to be significantly associated with baseline lung function. These regions correspond to the metabolites trigonelline, hippurate and formate. Concentrations of each metabolite, standardized to urinary creatinine, were associated with baseline lung function (minimum p-value = 0.0002 for trigonelline). No significant associations were found with plasma metabolites. Urinary hippurate and formate are often related to gut microflora. This could suggest that the microbiome varies between individuals with different lung function. Alternatively, the associated metabolites may reflect lifestyle differences affecting overall health. Our results will require replication and validation, but demonstrate the utility of NMR metabolomics as a screening tool for identifying novel biomarkers of pulmonary outcomes.

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, LIPEand 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.