Analyzing networks of phenotypes in complex diseases: Methodology and applications in COPD

Jen hwa Chu, Craig P. Hersh, Peter J. Castaldi, Michael H. Cho, Benjamin A. Raby, Nan Laird, Russell Bowler, Stephen Rennard, Joseph Loscalzo, John Quackenbush, Edwin K. Silverman

Research output: Contribution to journalArticle

25 Scopus citations

Abstract

Background: The investigation of complex disease heterogeneity has been challenging. Here, we introduce a network-based approach, using partial correlations, that analyzes the relationships among multiple disease-related phenotypes.Results: We applied this method to two large, well-characterized studies of chronic obstructive pulmonary disease (COPD). We also examined the associations between these COPD phenotypic networks and other factors, including case-control status, disease severity, and genetic variants. Using these phenotypic networks, we have detected novel relationships between phenotypes that would not have been observed using traditional epidemiological approaches.Conclusion: Phenotypic network analysis of complex diseases could provide novel insights into disease susceptibility, disease severity, and genetic mechanisms.

Original languageEnglish (US)
Article number78
JournalBMC systems biology
Volume8
Issue number1
DOIs
StatePublished - Jun 25 2014

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Keywords

  • COPD
  • Genetic association analysis
  • Network medicine
  • Phenotypic networks

ASJC Scopus subject areas

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

Cite this

Chu, J. H., Hersh, C. P., Castaldi, P. J., Cho, M. H., Raby, B. A., Laird, N., Bowler, R., Rennard, S., Loscalzo, J., Quackenbush, J., & Silverman, E. K. (2014). Analyzing networks of phenotypes in complex diseases: Methodology and applications in COPD. BMC systems biology, 8(1), [78]. https://doi.org/10.1186/1752-0509-8-78