Cluster analysis in severe emphysema subjects using phenotype and genotype data: an exploratory investigation.

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 variabl

SUBMITTER: Cho MH 

PROVIDER: S-EPMC2850331 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature