Chu, Jen-HwaHersh, CraigCastaldi, PeterCho, MichaelRaby, BenjaminLaird, NanBowler, RussellRennard, StephenLoscalzo, JosephQuackenbush, JohnSilverman, Edwin2014-09-082014Chu, J., C. P. Hersh, P. J. Castaldi, M. H. Cho, B. A. Raby, N. Laird, R. Bowler, et al. 2014. “Analyzing networks of phenotypes in complex diseases: methodology and applications in COPD.” BMC Systems Biology 8 (1): 78. doi:10.1186/1752-0509-8-78. http://dx.doi.org/10.1186/1752-0509-8-78.1752-0509http://nrs.harvard.edu/urn-3:HUL.InstRepos:12785842Background: 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.en-USNetwork medicinePhenotypic networksCOPDGenetic association analysisJournal Article2014-09-0810.1186/1752-0509-8-78