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Open Access Research article

Analysis of a gene co-expression network establishes robust association between Col5a2 and ischemic heart disease

Francisco Azuaje14*, Lu Zhang1, Céline Jeanty14, Sarah-Lena Puhl2, Sophie Rodius14 and Daniel R Wagner13

Author Affiliations

1 Department of Translational Cardiovascular Research, CRP-Santé, Luxembourg, Luxembourg

2 Department of Internal Medicine III, Saarland University Hospital, Homburg, Germany

3 Division of Cardiology, Centre Hospitalier, Luxembourg, Luxembourg

4 Current Address: Department of Oncology, NorLux Neuro-Oncology Laboratory, CRP-Santé, Luxembourg, Luxembourg

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BMC Medical Genomics 2013, 6:13  doi:10.1186/1755-8794-6-13

Published: 10 April 2013

Abstract

Background

This study aims to expand knowledge of the complex process of myocardial infarction (MI) through the application of a systems-based approach.

Methods

We generated a gene co-expression network from microarray data originating from a mouse model of MI. We characterized it on the basis of connectivity patterns and independent biological information. The potential clinical novelty and relevance of top predictions were assessed in the context of disease classification models. Models were validated using independent gene expression data from mouse and human samples.

Results

The gene co-expression network consisted of 178 genes and 7298 associations. The network was dissected into statistically and biologically meaningful communities of highly interconnected and co-expressed genes. Among the most significant communities, one was distinctly associated with molecular events underlying heart repair after MI (P < 0.05). Col5a2, a gene previously not specifically linked to MI response but responsible for the classic type of Ehlers-Danlos syndrome, was found to have many and strong co-expression associations within this community (11 connections with ρ > 0.85). To validate the potential clinical application of this discovery, we tested its disease discriminatory capacity on independently generated MI datasets from mice and humans. High classification accuracy and concordance was achieved across these evaluations with areas under the receiving operating characteristic curve above 0.8.

Conclusion

Network-based approaches can enable the discovery of clinically-interesting predictive insights that are accurate and robust. Col5a2 shows predictive potential in MI, and in principle may represent a novel candidate marker for the identification and treatment of ischemic cardiovascular disease.

Keywords:
Systems-based approaches; Co-expression networks; Myocardial infarction; Collagen proteins; Col5a2