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

BMC Systems Biology

Edwin K Silverman⁷  John Quackenbush³  Joseph Loscalzo⁶  Stephen Rennard²  Russell Bowler¹  Nan Laird⁴  Benjamin A Raby⁷  Michael H Cho⁷  Peter J Castaldi⁵  Craig P Hersh⁷  Jen-hwa Chu⁵ 

[1] Department of Medicine, National Jewish Health, Denver, CO, USA;University of Nebraska Medical Center, Omaha, NE, USA;Dana-Farber Cancer Institute, Boston, MA, USA;Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA;Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA;Division of Cardiovascular Medicine, Brigham and Women’s Hospital, Boston, MA, USA;Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, MA, USA

关键词: Genetic association analysis;    COPD;    Phenotypic networks;    Network medicine;   

Others  :  863174
DOI  :  10.1186/1752-0509-8-78

 received in 2014-04-04, accepted in 2014-06-19,  发布年份 2014

【 摘 要 】

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.

【 授权许可】

   
2014 Chu et al.; licensee BioMed Central Ltd.

【 图 表 】

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