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Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers
被引:108
作者:
Wang, I-Ming
[3
]
Zhang, Bin
[1
,2
,4
,5
]
Yang, Xia
[5
,6
]
Zhu, Jun
[1
,2
,4
,5
]
Stepaniants, Serguei
[7
]
Zhang, Chunsheng
[3
]
Meng, Qingying
[6
]
Peters, Mette
[5
]
He, Yudong
[8
]
Nl, Chester
[9
]
Slipetz, Deborah
[10
]
Crackower, Michael A.
[10
]
Houshyar, Hani
[11
]
Tan, Christopher M.
[12
]
Asante-Appiah, Ernest
[10
]
O'Neill, Gary
[10
]
Luo, Mingjuan Jane
[13
]
Thieringer, Rolf
[14
]
Yuan, Jeffrey
[15
]
Chiu, Chi-Sung
[11
]
Lum, Pek Yee
[16
]
Lamb, John
[17
]
Bole, Yves
[18
]
Wilkinson, Hilary A.
[19
]
Schadt, Eric E.
[1
,2
,4
,5
]
Dai, Hongyue
[20
]
Roberts, Christopher
[20
]
机构:
[1] Mt Sinai Sch Med, Dept Genet & Genom Sci, New York, NY 10029 USA
[2] Mt Sinai Sch Med, Inst Genom & Multiscale Biol, New York, NY USA
[3] Merck & Co Inc, Merck Res Labs, Informat & Anal, West Point, PA USA
[4] Mt Sinai Sch Med, Grad Sch Biol Sci, New York, NY USA
[5] Sage Bionetworks, Seattle, WA USA
[6] Univ Calif Los Angeles, Dept Integrat Biol & Physiol, Los Angeles, CA USA
[7] Covance Genom Lab, Seattle, WA USA
[8] Amgen Inc, Investigat Toxicol Dept, Seattle, WA USA
[9] Benaroya Res Inst, Syst Immunol, Seattle, WA USA
[10] Merck & Co Inc, Merck Res Labs, Dept Resp & Inflammat, Boston, MA USA
[11] Merck & Co Inc, In Vivo Pharmacol, Merck Res Labs, Boston, MA USA
[12] Merck & Co Inc, In Vivo Pharmacol, Merck Res Labs, Kenilworth, NJ USA
[13] Eli Lilly & Co, Lilly Corp Ctr, Lilly Res Labs, Indianapolis, IN 46285 USA
[14] Merck & Co Inc, Merck Res Labs, External Sci Affairs, Rahway, NJ USA
[15] Merck & Co Inc, Merck Res Labs, World Wide Regulatory Affairs, Rahway, NJ USA
[16] Ayasdi Inc, Product, Palo Alto, CA USA
[17] Pfizer, Oncol Res Unit, San Diego, CA USA
[18] Broad Inst, Cambridge, MA USA
[19] Merck & Co Inc, Merck Res Labs, Dept Resp & Inflammat, Rahway, NJ USA
[20] Merck & Co Inc, Merck Res Labs, Informat & Anal, Boston, MA USA
关键词:
Bayesian network;
co-expression network;
inflammatome;
inflammatory diseases;
key regulators;
INTEGRATIVE GENOMICS APPROACH;
SEGREGATING MOUSE-POPULATION;
NUCLEOTIDE POLYMORPHISM SNP;
NECROSIS-FACTOR-ALPHA;
GENE-EXPRESSION;
INSULIN-RESISTANCE;
TRANSCRIPTIONAL NETWORK;
ADIPOSE-TISSUE;
BREAST-CANCER;
MACROPHAGE INFILTRATION;
D O I:
10.1038/msb.2012.24
中图分类号:
Q5 [生物化学];
Q7 [分子生物学];
学科分类号:
071010 ;
081704 ;
摘要:
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. Molecular Systems Biology 8: 594; published online 17 July 2012; doi:10.1038/msb.2012.24 Subject Categories: metabolic and regulatory networks; molecular biology of disease
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