Network-based analysis of affected biological processes in type 2 diabetes models

被引:134
作者
Liu, Manway [1 ]
Liberzon, Arthur
Kong, Sek Won
Lai, Weil R.
Park, Peter J.
Kohane, Isaac S.
Kasif, Simon
机构
[1] Boston Univ, Dept Biomed Engn, Boston, MA 02215 USA
[2] Childrens Hosp, Dept Cardiol, Boston, MA 02115 USA
[3] Childrens Hosp, Informat Program, Boston, MA USA
[4] MIT, Div Hlth Sci & Technol, Boston, MA USA
[5] Harvard Partners Ctr Genet & Genom, Boston, MA USA
[6] Harvard Med Sch, Ctr Biomed Informat, Boston, MA USA
[7] Boston Univ, Ctr Adv Genom Technol, Boston, MA 02215 USA
来源
PLOS GENETICS | 2007年 / 3卷 / 06期
关键词
D O I
10.1371/journal.pgen.0030096
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
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.
引用
收藏
页码:958 / 972
页数:15
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