Open AccessSystems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers
Author(s) -
Wang IMing,
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,
AsanteAppiah Ernest,
O'Neill Gary,
Jane Luo Mingjuan,
Thieringer Rolf,
Yuan Jeffrey,
Chiu ChiSung,
Yee Lum Pek,
Lamb John,
Boie Yves,
Wilkinson Hilary A,
Schadt Eric E,
Dai Hongyue,
Roberts Christopher
Publication year - 2012
Publication title -
molecular systems biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 8.523
H-Index - 148
ISSN - 1744-4292
DOI - 10.1038/msb.2012.24
Subject(s) - biology , key (lock) , rodent , signature (topology) , rodent model , computational biology , ecology , geometry , mathematics , endocrinology
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.