tailieunhanh - Báo cáo y học: " Cluster analysis in severe emphysema subjects using phenotype and genotype data: an exploratory investigation"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học 'Respiratory Research cung cấp cho các bạn kiến thức về ngành y đề tài: Cluster analysis in severe emphysema subjects using phenotype and genotype data: an exploratory investigation. | Cho et al. Respiratory Research 2010 11 30 http content 11 1 30 RESPIRATORY RESEARCH RESEARCH Open Access Cluster analysis in severe emphysema subjects using phenotype and genotype data an exploratory investigation Michael H Cho1 2 George R Washko2 Thomas J Hoffmann3 Gerard J Criner4 Eric A Hoffman5 Fernando J Martinez6 Nan Laird3 John J Reilly7 Edwin K Silverman1 2 Abstract Background Numerous studies have demonstrated associations between genetic markers and COPD but results have been inconsistent. One reason may be heterogeneity in disease definition. Unsupervised learning approaches may assist in understanding disease heterogeneity. Methods We selected 31 phenotypic variables and 12 SNPs from five candidate genes in 308 subjects in the National Emphysema Treatment Trial NETT Genetics Ancillary Study cohort. We used factor analysis to select a subset of phenotypic variables and then used cluster analysis to identify subtypes of severe emphysema. We examined the phenotypic and genotypic characteristics of each cluster. Results We identified six factors accounting for 75 of the shared variability among our initial phenotypic variables. We selected four phenotypic variables from these factors for cluster analysis 1 post-bronchodilator FEV1 percent predicted 2 percent bronchodilator responsiveness and quantitative CT measurements of 3 apical emphysema and 4 airway wall thickness. K-means cluster analysis revealed four clusters though separation between clusters was modest 1 emphysema predominant 2 bronchodilator responsive with higher FEV1 3 discordant with a lower FEV1 despite less severe emphysema and lower airway wall thickness and 4 airway predominant. Of the genotypes examined membership in cluster 1 emphysema-predominant was associated with TGFB1 SNP rs1800470. Conclusions Cluster analysis may identify meaningful disease subtypes and or groups of related phenotypic variables even in a highly selected group of severe emphysema subjects