title: A diVIsive Shuffling Approach (VIStA) for gene expression analysis to identify subtypes in Chronic Obstructive Pulmonary Disease.
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.
authors.forename: Jörg
authors.initials: J
authors.lastname: Menche
authors.forename: Amitabh
authors.initials: A
authors.lastname: Sharma
authors.forename: Michael H
authors.initials: MH
authors.lastname: Cho
authors.forename: Ruth J
authors.initials: RJ
authors.lastname: Mayer
authors.forename: Stephen I
authors.initials: SI
authors.lastname: Rennard
authors.forename: Bartolome
authors.initials: B
authors.lastname: Celli
authors.forename: Bruce E
authors.initials: BE
authors.lastname: Miller
authors.forename: Nick
authors.initials: N
authors.lastname: Locantore
authors.forename: Ruth
authors.initials: R
authors.lastname: Tal-Singer
authors.forename: Soumitra
authors.initials: S
authors.lastname: Ghosh
authors.forename: Chris
authors.initials: C
authors.lastname: Larminie
authors.forename: Glyn
authors.initials: G
authors.lastname: Bradley
authors.forename: John H
authors.initials: JH
authors.lastname: Riley
authors.forename: Alvar
authors.initials: A
authors.lastname: Agusti
authors.forename: Edwin K
authors.initials: EK
authors.lastname: Silverman
authors.forename: Albert-László
authors.initials: AL
authors.lastname: Barabási
mesh_terms: D000368:Aged; D019295:Computational Biology / Q000379:methods*; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D008297:Male; D058990:Molecular Targeted Therapy; D064887:Observational Studies as Topic; D029424:Pulmonary Disease, Chronic Obstructive / Q000175:diagnosis* / Q000188:drug therapy / Q000235:genetics* / Q000473:pathology; D013183:Sputum / Q000378:metabolism