Multi-tissue coexpression networks reveal unexpected subnetworks associated with disease
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. To provide an inter-tissue view of obesity with respec...
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| Published in: | Genome biology Vol. 10; no. 5; p. R55 |
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| Main Authors: | , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
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22-05-2009
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| Abstract | 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.
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.
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. |
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| AbstractList | 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. BACKGROUNDObesity 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. RESULTSTo 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. CONCLUSIONSTissue-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. 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. 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. 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. Tissue-to-tissue coexpression networks between genes in hypothalamus, liver or adipose tissue enable identification of obesity-specific genes. |
| ArticleNumber | R55 |
| Author | Argman, Carmen Dobrin, Radu Schadt, Eric E Pomp, Daniel Parrish, Mark L Carlson, Sonia Zhu, Jun Molony, Cliona Allan, Mark F |
| AuthorAffiliation | 2 Department of Animal Science, University of Nebraska, Lincoln, NE 68508, USA 5 Current address: Pacific Biosciences, 1505 Adams Dr, Menlo Park, CA 94025, USA 3 Department of Nutrition, Cell and Molecular Physiology, Carolina Center for Genome Science, University of North Carolina, Chapel Hill, NC 27599, USA 1 Rosetta Inpharmatics, LLC, Merck & Co., Inc., Terry Avenue North, Seattle, Washington 98109, USA 4 Current address: Pfizer Animal Health, Animal Genetics Business Unit, East 42nd Street, New York, NY 10017, USA |
| AuthorAffiliation_xml | – name: 2 Department of Animal Science, University of Nebraska, Lincoln, NE 68508, USA – name: 5 Current address: Pacific Biosciences, 1505 Adams Dr, Menlo Park, CA 94025, USA – name: 3 Department of Nutrition, Cell and Molecular Physiology, Carolina Center for Genome Science, University of North Carolina, Chapel Hill, NC 27599, USA – name: 4 Current address: Pfizer Animal Health, Animal Genetics Business Unit, East 42nd Street, New York, NY 10017, USA – name: 1 Rosetta Inpharmatics, LLC, Merck & Co., Inc., Terry Avenue North, Seattle, Washington 98109, USA |
| Author_xml | – sequence: 1 givenname: Radu surname: Dobrin fullname: Dobrin, Radu email: radu_dobrin@merck.com organization: Rosetta Inpharmatics, LLC, Merck & Co, Inc, Seattle, Washington 98109, USA. radu_dobrin@merck.com – sequence: 2 givenname: Jun surname: Zhu fullname: Zhu, Jun – sequence: 3 givenname: Cliona surname: Molony fullname: Molony, Cliona – sequence: 4 givenname: Carmen surname: Argman fullname: Argman, Carmen – sequence: 5 givenname: Mark L surname: Parrish fullname: Parrish, Mark L – sequence: 6 givenname: Sonia surname: Carlson fullname: Carlson, Sonia – sequence: 7 givenname: Mark F surname: Allan fullname: Allan, Mark F – sequence: 8 givenname: Daniel surname: Pomp fullname: Pomp, Daniel – sequence: 9 givenname: Eric E surname: Schadt fullname: Schadt, Eric E |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/19463160$$D View this record in MEDLINE/PubMed |
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| Snippet | Obesity is a particularly complex disease that at least partially involves genetic and environmental perturbations to gene-networks connecting the hypothalamus... Abstract Background Obesity is a particularly complex disease that at least partially involves genetic and environmental perturbations to gene-networks... BACKGROUNDObesity is a particularly complex disease that at least partially involves genetic and environmental perturbations to gene-networks connecting the... Tissue-to-tissue coexpression networks between genes in hypothalamus, liver or adipose tissue enable identification of obesity-specific genes. |
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| SubjectTerms | Adipose Tissue - metabolism Animals Gene Regulatory Networks Humans Liver - metabolism Mice Obesity - genetics Obesity - physiopathology |
| Title | Multi-tissue coexpression networks reveal unexpected subnetworks associated with disease |
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