Back to Results

< Previous   Next >

Multi-tissue coexpression networks reveal unexpected subnetworks associated with disease

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

File Type: pdf | Filesize: 1.9 MB | Date Added: 2012-08-23 | Date Created: 2009-05-22

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.