1. Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers.
- Author
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Wang, I-Ming, Zhang, Bin, Yang, Xia, Zhu, Jun, Stepaniants, Serguei, Zhang, Chunsheng, Meng, Qingying, Peters, Mette, He, Yudong, Ni, Chester, Slipetz, Deborah, Crackower, Michael A, Houshyar, Hani, Tan, Christopher M, Asante-Appiah, Ernest, O'Neill, Gary, Luo, Mingjuan Jane, Thieringer, Rolf, Yuan, Jeffrey, Chiu, Chi-Sung, Lum, Pek Yee, Lamb, John, Boie, Yves, Wilkinson, Hilary A, Schadt, Eric E, Dai, Hongyue, and Roberts, Christopher
- Subjects
Animals ,Mice ,Inbred BALB C ,Mice ,Inbred C57BL ,Mice ,Knockout ,Humans ,Mice ,Rats ,Rats ,Sprague-Dawley ,Disease Models ,Animal ,Caspases ,Intracellular Signaling Peptides and Proteins ,Chemokines ,Interleukins ,Analysis of Variance ,Bayes Theorem ,Cohort Studies ,Gene Expression Profiling ,Computational Biology ,Age Factors ,Sex Factors ,Female ,Male ,Gene Regulatory Networks ,Inflammasomes ,Bayesian network ,co-expression network ,inflammatome ,inflammatory diseases ,key regulators ,Inbred BALB C ,Inbred C57BL ,Knockout ,Sprague-Dawley ,Disease Models ,Animal ,Bioinformatics ,Biochemistry and Cell Biology ,Other Biological Sciences - Abstract
Common inflammatome gene signatures as well as disease-specific signatures were identified by analyzing 12 expression profiling data sets derived from 9 different tissues isolated from 11 rodent inflammatory disease models. The inflammatome signature significantly overlaps with known drug targets and co-expressed gene modules linked to metabolic disorders and cancer. A large proportion of genes in this signature are tightly connected in tissue-specific Bayesian networks (BNs) built from multiple independent mouse and human cohorts. Both the inflammatome signature and the corresponding consensus BNs are highly enriched for immune response-related genes supported as causal for adiposity, adipokine, diabetes, aortic lesion, bone, muscle, and cholesterol traits, suggesting the causal nature of the inflammatome for a variety of diseases. Integration of this inflammatome signature with the BNs uncovered 151 key drivers that appeared to be more biologically important than the non-drivers in terms of their impact on disease phenotypes. The identification of this inflammatome signature, its network architecture, and key drivers not only highlights the shared etiology but also pinpoints potential targets for intervention of various common diseases.
- Published
- 2012