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Network-Based Analysis of Affected Biological Processes in Type 2 Diabetes Models

Type 2 diabetes mellitus is a complex disorder associated with multiple genetic, epigenetic, developmental, and environmental factors. Animal models of type 2 diabetes differ based on diet, drug treatment, and gene knockouts, and yet all display the clinical hallmarks of hyperglycemia and insulin re...

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Autores principales: Liu, Manway, Liberzon, Arthur, Kong, Sek Won, Lai, Weil R, Park, Peter J, Kohane, Isaac S, Kasif, Simon
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1904360/
https://www.ncbi.nlm.nih.gov/pubmed/17571924
http://dx.doi.org/10.1371/journal.pgen.0030096
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author Liu, Manway
Liberzon, Arthur
Kong, Sek Won
Lai, Weil R
Park, Peter J
Kohane, Isaac S
Kasif, Simon
author_facet Liu, Manway
Liberzon, Arthur
Kong, Sek Won
Lai, Weil R
Park, Peter J
Kohane, Isaac S
Kasif, Simon
author_sort Liu, Manway
collection PubMed
description Type 2 diabetes mellitus is a complex disorder associated with multiple genetic, epigenetic, developmental, and environmental factors. Animal models of type 2 diabetes differ based on diet, drug treatment, and gene knockouts, and yet all display the clinical hallmarks of hyperglycemia and insulin resistance in peripheral tissue. The recent advances in gene-expression microarray technologies present an unprecedented opportunity to study type 2 diabetes mellitus at a genome-wide scale and across different models. To date, a key challenge has been to identify the biological processes or signaling pathways that play significant roles in the disorder. Here, using a network-based analysis methodology, we identified two sets of genes, associated with insulin signaling and a network of nuclear receptors, which are recurrent in a statistically significant number of diabetes and insulin resistance models and transcriptionally altered across diverse tissue types. We additionally identified a network of protein–protein interactions between members from the two gene sets that may facilitate signaling between them. Taken together, the results illustrate the benefits of integrating high-throughput microarray studies, together with protein–protein interaction networks, in elucidating the underlying biological processes associated with a complex disorder.
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spelling pubmed-19043602007-06-30 Network-Based Analysis of Affected Biological Processes in Type 2 Diabetes Models Liu, Manway Liberzon, Arthur Kong, Sek Won Lai, Weil R Park, Peter J Kohane, Isaac S Kasif, Simon PLoS Genet Research Article Type 2 diabetes mellitus is a complex disorder associated with multiple genetic, epigenetic, developmental, and environmental factors. Animal models of type 2 diabetes differ based on diet, drug treatment, and gene knockouts, and yet all display the clinical hallmarks of hyperglycemia and insulin resistance in peripheral tissue. The recent advances in gene-expression microarray technologies present an unprecedented opportunity to study type 2 diabetes mellitus at a genome-wide scale and across different models. To date, a key challenge has been to identify the biological processes or signaling pathways that play significant roles in the disorder. Here, using a network-based analysis methodology, we identified two sets of genes, associated with insulin signaling and a network of nuclear receptors, which are recurrent in a statistically significant number of diabetes and insulin resistance models and transcriptionally altered across diverse tissue types. We additionally identified a network of protein–protein interactions between members from the two gene sets that may facilitate signaling between them. Taken together, the results illustrate the benefits of integrating high-throughput microarray studies, together with protein–protein interaction networks, in elucidating the underlying biological processes associated with a complex disorder. Public Library of Science 2007-06 2007-06-15 /pmc/articles/PMC1904360/ /pubmed/17571924 http://dx.doi.org/10.1371/journal.pgen.0030096 Text en © 2007 Liu et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Liu, Manway
Liberzon, Arthur
Kong, Sek Won
Lai, Weil R
Park, Peter J
Kohane, Isaac S
Kasif, Simon
Network-Based Analysis of Affected Biological Processes in Type 2 Diabetes Models
title Network-Based Analysis of Affected Biological Processes in Type 2 Diabetes Models
title_full Network-Based Analysis of Affected Biological Processes in Type 2 Diabetes Models
title_fullStr Network-Based Analysis of Affected Biological Processes in Type 2 Diabetes Models
title_full_unstemmed Network-Based Analysis of Affected Biological Processes in Type 2 Diabetes Models
title_short Network-Based Analysis of Affected Biological Processes in Type 2 Diabetes Models
title_sort network-based analysis of affected biological processes in type 2 diabetes models
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1904360/
https://www.ncbi.nlm.nih.gov/pubmed/17571924
http://dx.doi.org/10.1371/journal.pgen.0030096
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