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Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers.

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.

SUBMITTER: Wang IM

PROVIDER: S-EPMC3421440 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers.

Wang I-Ming IM Zhang Bin B Yang Xia X Zhu Jun J Stepaniants Serguei S Zhang Chunsheng C Meng Qingying Q Peters Mette M He Yudong Y Ni Chester C Slipetz Deborah D Crackower Michael A MA Houshyar Hani H Tan Christopher M CM Asante-Appiah Ernest E O'Neill Gary G Luo Mingjuan Jane MJ Thieringer Rolf R Yuan Jeffrey J Chiu Chi-Sung CS Lum Pek Yee PY Lamb John J Boie Yves Y Wilkinson Hilary A HA Schadt Eric E EE Dai Hongyue H Roberts Christopher C

Molecular systems biology 20120717

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 ...[more]

PMID: 22806142

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Project description:Genome-wide association studies have identified multiple genetic variants affecting the risk of coronary artery disease (CAD). However, individually these explain only a small fraction of the heritability of CAD and for most, the causal biological mechanisms remain unclear. We sought to obtain further insights into potential causal processes of CAD by integrating large-scale GWA data with expertly curated databases of core human pathways and functional networks.Using pathways (gene sets) from Reactome, we carried out a 2-stage gene set enrichment analysis strategy. From a meta-analyzed discovery cohort of 7 CAD genome-wide association study data sets (9889 cases/11?089 controls), nominally significant gene sets were tested for replication in a meta-analysis of 9 additional studies (15?502 cases/55?730 controls) from the Coronary ARtery DIsease Genome wide Replication and Meta-analysis (CARDIoGRAM) Consortium. A total of 32 of 639 Reactome pathways tested showed convincing association with CAD (replication P<0.05). These pathways resided in 9 of 21 core biological processes represented in Reactome, and included pathways relevant to extracellular matrix (ECM) integrity, innate immunity, axon guidance, and signaling by PDRF (platelet-derived growth factor), NOTCH, and the transforming growth factor-?/SMAD receptor complex. Many of these pathways had strengths of association comparable to those observed in lipid transport pathways. Network analysis of unique genes within the replicated pathways further revealed several interconnected functional and topologically interacting modules representing novel associations (eg, semaphoring-regulated axonal guidance pathway) besides confirming known processes (lipid metabolism). The connectivity in the observed networks was statistically significant compared with random networks (P<0.001). Network centrality analysis (degree and betweenness) further identified genes (eg, NCAM1, FYN, FURIN, etc) likely to play critical roles in the maintenance and functioning of several of the replicated pathways.These findings provide novel insights into how genetic variation, interpreted in the context of biological processes and functional interactions among genes, may help define the genetic architecture of CAD.

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Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers.

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Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers.

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