Multi-tissue coexpression networks reveal unexpected subnetworks associated with disease

Open Access et al. Dobrin 2009 Volume 10, Issue 5, Article R55 Research 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†‡ and Eric E Schadt*¶ Addresses: *Rosetta Inpharmatics, LLC, Merck & Co., Inc., Terry Avenue North, Seattle, Washington 98109, USA. †Department of Animal Science, University of Nebraska, Lincoln, NE 68508, USA. ‡Department of Nutrition, Cell and Molecular Physiology, Carolina Center for Genome Science, University of North Carolina, Chapel Hill, NC 27599, USA. §Current address: Pfizer Animal Health, Animal Genetics Business Unit, East 42nd Street, New York, NY 10017, USA. ¶Current address: Pacific Biosciences, 1505 Adams Dr, Menlo Park, CA 94025, USA. Correspondence: Eric E Schadt. Email: Published: 22 May 2009 Genome Biology 2009, 10:R55 (doi:10.1186/gb-2009-10-5-r55) Received: 26 November 2008 Revised: 12 February 2009 Accepted: 22 May 2009 The electronic version of this article is the complete one and can be found online at http://genomebiology.com/2009/10/5/R55 © 2009 Dobrin et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. genes.</p> Obesity networks coexpression networks between genes in hypothalamus, liver or adipose tissue enable identification of obesity-specific <p>Tissue-to-tissue 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. Background Significant successes identifying susceptibility genes for common human diseases have been obtained from a plethora of genome-wide association studies in a diversity of disease areas, including asthma [1,2], type 1 and 2 diabetes [3,4], obesity [5-8], and cardiovascular disease [9-11]. To inform how variations in DNA can affect disease risk and progression, studies that integrate clinical measures with molecular profiling data like gene expression and single nucleotide polymorphism genotypes have been carried out to elucidate the Genome Biology 2009, 10:R55 http://genomebiology.com/2009/10/5/R55 Genome Biology 2009, network of intermediate, molecular phenotypes that define disease states [12,13]. However, in almost all cases the focus has been on single tissue analyses that largely ignore the fact that complex phenotypes manifested in mammalian systems are the result of a complex array of networks operating within and between tissues. Nowhere is this complexity more apparent than in studies of obesity. nucleus neurons that co-express the agouti-related protein (Agrp) and neuropeptide Y (Npy) by activating the phosphatidylinositol 3-kinase pathway, is achieved in a manner that is independent of the STAT3 pathway [22]. Alternatively, leptin activates the JAK/STAT3 pathway in pro-pomelacortin neurons [23]. Obesity is a particularly complex disease involving genetic and environmental perturbations to networks connecting peripheral tissues such as adipose, muscle, stomach, intestine, liver, and pancreas with the hypothalamus, resulting in an energy imbalance that affects the system as a whole. With more than 30% of adults in the US overweight or obese (body mass index >30) [14], a dramatic increase in the progression of obesity rates in children aged 2 to 19 years [15], and the fact that obesity is a principal cause of type 2 diabetes [16] and results in an increased risk of asthma, certain forms of cancer, cardiovascular disease and stroke, obesity is truly a disease of significant public health concern. Because of this, significant effort has been undertaken to understand the underlying mechanisms critical to the development of obesity. While many of these efforts have shown great promise, they are also revealing a more complex picture of obesity than was previously thought, consisting of highly integrative, interactive and multi-tissue physiological control. Energy storage is a complex event in any organism. In higher organisms like mammals, multiple tissues interact to ensure adequate energy storage. A key to understanding obesity is deciphering the paths along which molecules move as well as the signals that control these processes. While white adipose tissue is the primary organ for longer-term storage of energy in the form of triglycerides, it is also a very dynamic compartment within the body. In fact, white adipose tissue can be considered among the most active endocrine organs, secreting hormones like leptin, adiponectin, tumor necrosis factor-α, interleukin-6, estradiol, resistin, angiotensin, and plasminogen activator inhibitor-1. The active state of this organ is evidence enough that it does not act in isolation. In fact, it is already well established that the brain receives signals through small molecules like leptin and insulin circulating in the blood, and through sympathetic and parasympathetic systems. The central nervous system has proven to be a primary player in maintaining energy homeostasis, where it is believed that the brain acts as an 'energy-on-request' system, with a hierarchical organization in which the hypothalamus plays a central role [17,18]. Using the neuronal tracer cholera toxin B and the retrograde neuronal tracer pseudorabies virus, Kreier et al. [19] showed that the autonomic nervous system exhibited a distinct organizatio (...truncated)