Multi-tissue coexpression networks reveal unexpected subnetworks associated with disease.
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.
Dobrin
Radu
R
Rosetta Inpharmatics, LLC, Merck & Co, Inc, Seattle, Washington 98109, USA. radu_dobrin@merck.com
Zhu
Jun
J
Molony
Cliona
C
Argman
Carmen
C
Parrish
Mark L
ML
Carlson
Sonia
S
Allan
Mark F
MF
Pomp
Daniel
D
Schadt
Eric E
EE
D000273:Adipose Tissue / Q000378:metabolism*; D000818:Animals; D053263:Gene Regulatory Networks; D006801:Humans; D008099:Liver / Q000378:metabolism*; D051379:Mice; D009765:Obesity / Q000235:genetics* / Q000503:physiopathology