RESUMEN
Background: Computed tomography (CT) visual emphysema score is a better predictor of mortality than single quantitative CT emphysema measurements in COPD, but there are numerous CT measurements that reflect COPD-related disease features. The purpose of this study was to determine if linear combinations of quantitative CT measurements by principal component analysis (PCA) have a greater association with forced expiratory volume in 1â s (FEV1) lower limit of normal (LLN) annualised change (ΔFEV1) than visual emphysema score in COPD. Methods: In this retrospective, longitudinal study, demographic, spirometry and CT images were acquired. CT visual emphysema score and quantitative analysis were performed; low attenuation area <950â HU (LAA950) and 12 other quantitative CT measurements were investigated. PCA was used for CT feature extraction. Multiple linear regression models for baseline FEV1 LLN and 6-year ΔFEV1 were used to determine associations with visual emphysema score and CT measurements. A total of 725 participants were analysed (n=299 never-smokers, n=242 at-risk and n=184 COPD). Results: Quantitative CT measures (LAA950 and PCA components) were independently statistically significant (p<0.05) in predicting baseline FEV1 LLN, whereas visual emphysema score was not statistically significant in any baseline model. When predicting 6-year ΔFEV1, only visual emphysema score was significant (p<0.05) in models with LAA950 and PCA combination of emphysema measurements. In the model with PCA using all CT measurements predicting 6-year ΔFEV1, visual emphysema score (p=0.021) along with one PCA component (p=0.004) were statistically significant. Conclusions: PCA with a combination of CT measurements reflecting several different COPD-related disease features independently predicted baseline lung function and increased the relative importance of quantitative CT compared with visual emphysema score for predicting lung function decline.
RESUMEN
RATIONALE: Chronic obstructive lung disease (COPD) is a common and disabling lung disease for which there are few therapeutic options. OBJECTIVES: We reasoned that gene expression profiling of COPD lungs could reveal previously unidentified disease pathways. METHODS: Forty-eight human lung samples were obtained from tissue resected from five nonsmokers, 21 GOLD (Global Initiative for Chronic Obstructive Lung Disease) stage 0, 9 GOLD stage 1, 10 GOLD stage 2, and 3 GOLD stage 3 patients. mRNA from the specimens was profiled using Agilent's Functional ID v2.0 array (Agilent, Santa Clara, CA) containing 23,720 sequences. MEASUREMENTS AND MAIN RESULTS: The gene expression pattern was influenced by the percentage of the sample made up of parenchyma. Gene expression was related to forced expiratory flow between 25 and 75% of forced expiratory volume (FEF(25-75%) % predicted) revealing a signature gene set of 203 transcripts. Genes involved in extracellular matrix synthesis/degradation and apoptosis were among the up-regulated genes, whereas genes that participate in antiinflammatory responses were down-regulated. Immunohistochemistry confirmed expression of urokinase plasminogen activator (PLAU), urokinase plasminogen activator receptor (PLAUR), and thrombospondin (THBS1) by alveolar macrophages and airway epithelial cells. Genes in this pathway have been shown to be involved in the activation of transforming growth factor (TGF)-beta1 and matrix metalloproteinases and are subject to inhibition by SERPINE2. Interestingly, both TGF-beta1 and SERPINE2 have been identified as candidate genes in COPD genetic linkage and association studies. CONCLUSIONS: The results provide evidence that genes involved in tissue remodeling and repair are differentially regulated in the lungs of obstructed smokers and suggest that they are potential therapeutic targets. Data deposited in GEO at http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE8500.