title: Disease-associated pathophysiologic structures in pediatric rheumatic diseases show characteristics of scale-free networks seen in physiologic systems: implications for pathogenesis and treatment.
abstract: BACKGROUND
  While standard reductionist approaches have provided some insights into specific gene polymorphisms and molecular pathways involved in disease pathogenesis, our understanding of complex traits such as atherosclerosis or type 2 diabetes remains incomplete. Gene expression profiling provides an unprecedented opportunity to understand complex human diseases by providing a global view of the multiple interactions across the genome that are likely to contribute to disease pathogenesis. Thus, the goal of gene expression profiling is not to generate lists of differentially expressed genes, but to identify the physiologic or pathogenic processes and structures represented in the expression profile.
  
  
  METHODS
  RNA was separately extracted from peripheral blood neutrophils and mononuclear leukocytes, labeled, and hybridized to genome level microarrays to generate expression profiles of children with polyarticular juvenile idiopathic arthritis, juvenile dermatomyositis relative to childhood controls. Statistically significantly differentially expressed genes were identified from samples of each disease relative to controls. Functional network analysis identified interactions between products of these differentially expressed genes.
  
  
  RESULTS
  In silico models of both diseases demonstrated similar features with properties of scale-free networks previously described in physiologic systems. These networks were observable in both cells of the innate immune system (neutrophils) and cells of the adaptive immune system (peripheral blood mononuclear cells).
  
  
  CONCLUSIONS
  Genome-level transcriptional profiling from childhood onset rheumatic diseases suggested complex interactions in two arms of the immune system in both diseases. The disease associated networks showed scale-free network patterns similar to those reported in normal physiology. We postulate that these features have important implications for therapy as such networks are relatively resistant to perturbation.
authors.affiliation: Microarray Research Facility, Arthritis and Immunology Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA. bart-frank@omrf.org
authors.forename: Mark Barton
authors.initials: MB
authors.lastname: Frank
authors.forename: Shirley
authors.initials: S
authors.lastname: Wang
authors.forename: Amita
authors.initials: A
authors.lastname: Aggarwal
authors.forename: Nicholas
authors.initials: N
authors.lastname: Knowlton
authors.forename: Kaiyu
authors.initials: K
authors.lastname: Jiang
authors.forename: Yanmin
authors.initials: Y
authors.lastname: Chen
authors.forename: Ryan
authors.initials: R
authors.lastname: McKee
authors.forename: Brad
authors.initials: B
authors.lastname: Chaser
authors.forename: Timothy
authors.initials: T
authors.lastname: McGhee
authors.forename: Jeanette
authors.initials: J
authors.lastname: Osban
authors.forename: James N
authors.initials: JN
authors.lastname: Jarvis