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Journal of Lipid Research, Vol. 48, 267-277, February 2007
Copyright © 2007 by American Society for Biochemistry and Molecular Biology

Thematic Review

Thematic review series: Systems Biology Approaches to Metabolic and Cardiovascular Disorders. Multi-organ whole-genome measurements and reverse engineering to uncover gene networks underlying complex traits

Jesper Tegnér^*,,, Josefin Skogsberg^*, and Johan Björkegren^1,*,

^* The Computational Medicine Group, the Atherosclerosis Research Unit, Center for Molecular Medicine, King Gustaf V Research Institute, Department of Medicine, Karolinska Institute, Karolinska University Hospital, Solna, SE-171 76 Stockholm, Sweden
Unit of Computational Medicine, Clinical Gene Networks, Fogdevreten 2b, SE-171 77, Stockholm, Sweden
Division of Computational Biology, Department of Physics, Linköpings Institute of Technology, Linköping University, SE-581 83 Linköping, Sweden

Published, JLR Papers in Press, December 1, 2006.

¹ To whom correspondence should be addressed. e-mail: johan.bjorkegren{at}ki.se

Together with computational analysis and modeling, the development of whole-genome measurement technologies holds the potential to fundamentally change research on complex disorders such as coronary artery disease. With these tools, the stage has been set to reveal the full repertoire of biological components (genes, proteins, and metabolites) in complex diseases and their interplay in modules and networks. Here we review how network identification based on reverse engineering, as applied to whole-genome datasets from simpler organisms, is now being adapted to more complex settings such as datasets from human cell lines and organs in relation to physiological and pathological states. Our focus is on the use of a systems biological approach to identify gene networks in coronary atherosclerosis. We also address how gene networks will probably play a key role in the development of early diagnostics and treatments for complex disorders in the coming era of individualized medicine.

Supplementary key words global gene expression • coronary atherosclerosis • multicellular disease • computational modeling • individualized medicine

Abbreviations: CAD, coronary artery disease; LCM, laser-capture microdissection; ODE, ordinary differential equation; siRNA, small interfering RNA

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