A diVIsive Shuffling Approach (VIStA) for gene expression analysis to identify subtypes in Chronic Obstructive Pulmonary Disease

Jörg Menche, Amitabh Sharma, Michael H. Cho, Ruth J. Mayer, Stephen I. Rennard, Bartolome Celli, Bruce E. Miller, Nick Locantore, Ruth Tal-Singer, Soumitra Ghosh, Chris Larminie, Glyn Bradley, John H. Riley, Alvar Agusti, Edwin K. Silverman, Albert László Barabási

Research output: Contribution to journalArticle

14 Scopus citations

Abstract

Background: An important step toward understanding the biological mechanisms underlying a complex disease is a refined understanding of its clinical heterogeneity. Relating clinical and molecular differences may allow us to define more specific subtypes of patients that respond differently to therapeutic interventions. Results: We developed a novel unbiased method called diVIsive Shuffling Approach (VIStA) that identifies subgroups of patients by maximizing the difference in their gene expression patterns. We tested our algorithm on 140 subjects with Chronic Obstructive Pulmonary Disease (COPD) and found four distinct, biologically and clinically meaningful combinations of clinical characteristics that are associated with large gene expression differences. The dominant characteristic in these combinations was the severity of airflow limitation. Other frequently identified measures included emphysema, fibrinogen levels, phlegm, BMI and age. A pathway analysis of the differentially expressed genes in the identified subtypes suggests that VIStA is capable of capturing specific molecular signatures within in each group. Conclusions: The introduced methodology allowed us to identify combinations of clinical characteristics that correspond to clear gene expression differences. The resulting subtypes for COPD contribute to a better understanding of its heterogeneity.

Original languageEnglish (US)
Article numberS8
JournalBMC systems biology
Volume8
Issue number2
DOIs
StatePublished - Mar 13 2014

Keywords

  • COPD
  • Chronic Bronchitis
  • Emphysema
  • Gene expression analysis
  • Subtyping

ASJC Scopus subject areas

  • Structural Biology
  • Modeling and Simulation
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics

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