Multi-tissue coexpression networks reveal unexpected subnetworks associated with disease

Radu Dobrin, Jun Zhu, Cliona Molony, Carmen Argman, Mark L. Parrish, Sonia Carlson, Mark F. Allan, Daniel Pomp, Eric E. Schadt

Research output: Contribution to journalArticlepeer-review

122 Scopus citations

Abstract

Background: Obesity is a particularly complex disease that at least partially involves genetic and environmental perturbations to gene-networks connecting the hypothalamus and several metabolic tissues, resulting in an energy imbalance at the systems level. Results: To provide an inter-tissue view of obesity with respect to molecular states that are associated with physiological states, we developed a framework for constructing tissue-to-tissue coexpression networks between genes in the hypothalamus, liver or adipose tissue. These networks have a scale-free architecture and are strikingly independent of gene-gene coexpression networks that are constructed from more standard analyses of single tissues. This is the first systematic effort to study inter-tissue relationships and highlights genes in the hypothalamus that act as information relays in the control of peripheral tissues in obese mice. The subnetworks identified as specific to tissue-to-tissue interactions are enriched in genes that have obesity-relevant biological functions such as circadian rhythm, energy balance, stress response, or immune response. Conclusions: Tissue-to-tissue networks enable the identification of disease-specific genes that respond to changes induced by different tissues and they also provide unique details regarding candidate genes for obesity that are identified in genome-wide association studies. Identifying such genes from single tissue analyses would be difficult or impossible.

Original languageEnglish
Article numberR55
JournalGenome Biology
Volume10
Issue number5
DOIs
StatePublished - 22 May 2009
Externally publishedYes

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