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

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.

[1]  E. Huskisson,et al.  Crystals, inflammation and osteoarthritis. , 1977, Acta rhumatologica Belgica.

[2]  B. Spiegelman,et al.  Adipose expression of tumor necrosis factor-alpha: direct role in obesity-linked insulin resistance. , 1993, Science.

[3]  B. Spiegelman,et al.  Increased adipose tissue expression of tumor necrosis factor-alpha in human obesity and insulin resistance. , 1995, The Journal of clinical investigation.

[4]  J. Rhodes,et al.  Unifying hypothesis for inflammatory bowel disease and associated colon cancer: sticking the pieces together with sugar , 1996, The Lancet.

[5]  B. Koller,et al.  Role of the 5-Lipoxygenase–activating Protein (FLAP) in Murine Acute Inflammatory Responses , 1997, The Journal of experimental medicine.

[6]  S. Snapper,et al.  The Wiskott-Aldrich syndrome protein (WASP): roles in signaling and cytoskeletal organization. , 1999, Annual review of immunology.

[7]  R. Darveau.  Infection, inflammation, and cancer , 1999, Nature Biotechnology.

[8]  M. Ala-Korpela,et al.  Modified LDL – trigger of atherosclerosis and inflammation in the arterial intima , 2000, Journal of internal medicine.

[9]  Michal Linial,et al.  Using Bayesian Networks to Analyze Expression Data , 2000, J. Comput. Biol..

[10]  Leena Peltonen,et al.  Loss-of-function mutations in TYROBP (DAP12) result in a presenile dementia with bone cysts , 2000, Nature Genetics.

[11]  M. C. Liu,et al.  Extensive surface phenotyping of alveolar macrophages in interstitial lung disease. , 2000, Clinical immunology.

[12]  Yudong D. He,et al.  Gene expression profiling predicts clinical outcome of breast cancer , 2002, Nature.

[13]  A. Barabasi,et al.  Hierarchical Organization of Modularity in Metabolic Networks , 2002, Science.

[14]  Van,et al.  A gene-expression signature as a predictor of survival in breast cancer. , 2002, The New England journal of medicine.

[15]  A. Aljada,et al.  Inflammation: the link between insulin resistance, obesity and diabetes. , 2004, Trends in immunology.

[16]  S. Friend,et al.  Signatures of environmental exposures using peripheral leukocyte gene expression: tobacco smoke. , 2004, Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology.

[17]  M. Shimizu,et al.  Variations in the C3, C3a receptor, and C5 genes affect susceptibility to bronchial asthma , 2004, Human Genetics.

[18]  J. Zhu,et al.  An integrative genomics approach to the reconstruction of gene networks in segregating populations , 2004, Cytogenetic and Genome Research.

[19]  S. Horvath,et al.  A General Framework for Weighted Gene Co-Expression Network Analysis , 2005, Statistical applications in genetics and molecular biology.

[20]  Richard A. Young,et al.  Insights into host responses against pathogens from transcriptional profiling , 2005, Nature Reviews Microbiology.

[21]  E E Schadt,et al.  Integrating genotypic and expression data in a segregating mouse population to identify 5-lipoxygenase as a susceptibility gene for obesity and bone traits , 2005, Nature Genetics.

[22]  J. Foekens,et al.  Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer , 2005, The Lancet.

[23]  J. Castle,et al.  An integrative genomics approach to infer causal associations between gene expression and disease , 2005, Nature Genetics.

[24]  Manjunatha Jagalur,et al.  Causal inference of regulator-target pairs by gene mapping of expression phenotypes , 2005, BMC Genomics.

[25]  A. Órfão,et al.  Aberrant expression of tetraspanin molecules in B-cell chronic lymphoproliferative disorders and its correlation with normal B-cell maturation , 2005, Leukemia.

[26]  D. Arvanitis,et al.  Genomic rearrangements on VCAM1, SELE, APEG1 and AIF1 loci in atherosclerosis , 2005, Journal of cellular and molecular medicine.

[27]  P. Hall,et al.  An expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects, and patient survival. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[28]  Y. Leea,et al.  Analysis of oncogenic signaling networks in glioblastoma identifies ASPM as a molecular target , 2006 .

[29]  Aiqing He,et al.  Identification of inflammatory gene modules based on variations of human endothelial cell responses to oxidized lipids , 2006, Proceedings of the National Academy of Sciences.

[30]  J. Lamb,et al.  Elucidating the murine brain transcriptional network in a segregating mouse population to identify core functional modules for obesity and diabetes , 2006, Journal of neurochemistry.

[31]  Peter Libby,et al.  The immune response in atherosclerosis: a double-edged sword , 2006, Nature Reviews Immunology.

[32]  N. Anthonisen,et al.  Association of Hck genetic polymorphisms with gene expression and COPD , 2006, Human Genetics.

[33]  楯谷 三四郎.  MCP-1 contributes to macrophage infiltration into adipose tissue, insulin resistance, and hepatic steatosis in obesity , 2006 .

[34]  N. Novak,et al.  Different expression of adhesion molecules and tetraspanins of monocytes of patients with atopic eczema , 2006, Allergy.

[35]  R. Kitazawa,et al.  MCP-1 contributes to macrophage infiltration into adipose tissue, insulin resistance, and hepatic steatosis in obesity. , 2006, The Journal of clinical investigation.

[36]  M. J. van de Vijver,et al.  Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. , 2006, Journal of the National Cancer Institute.

[37]  Piero Carninci,et al.  Transcriptional network dynamics in macrophage activation. , 2006, Genomics.

[38]  E. Schadt,et al.  Genetic and Genomic Analysis of a Fat Mass Trait with Complex Inheritance Reveals Marked Sex Specificity , 2006, PLoS genetics.

[39]  S. Horvath,et al.  Analysis of oncogenic signaling networks in glioblastoma identifies ASPM as a molecular target , 2006, Proceedings of the National Academy of Sciences.

[40]  L. O’Neill,et al.  Targeting signal transduction as a strategy to treat inflammatory diseases , 2006, Nature Reviews Drug Discovery.

[41]  M. Rudling,et al.  Inhibition of five lipoxygenase activating protein (FLAP) by MK‐886 decreases atherosclerosis in apoE/LDLR‐double knockout mice , 2006, European journal of clinical investigation.

[42]  Kathleen A. Kennedy,et al.  Systems biology approaches identify ATF3 as a negative regulator of Toll-like receptor 4 , 2006, Nature.

[43]  Anatoly L. Mayburd,et al.  Ingenuity Network-Assisted Transcription Profiling: Identification of a New Pharmacologic Mechanism for MK886 , 2006, Clinical Cancer Research.

[44]  耕一 長谷川.  Variations in the C3, C3a receptor, and C5 genes affect susceptibility to bronchial asthma , 2007 .

[45]  T. Wang,et al.  Inflammation, atrophy, and gastric cancer. , 2007, The Journal of clinical investigation.

[46]  J. Pedersen-Lane,et al.  Analysis of the thiol status of peripheral blood leukocytes in rheumatoid arthritis patients , 2007, Journal of leukocyte biology.

[47]  M. Mayes,et al.  An allograft inflammatory factor 1 (AIF1) single nucleotide polymorphism (SNP) is associated with anticentromere antibody positive systemic sclerosis. , 2007, Rheumatology.

[48]  Jun Zhu,et al.  Increasing the Power to Detect Causal Associations by Combining Genotypic and Expression Data in Segregating Populations , 2007, PLoS Comput. Biol..

[49]  V. Gurtsevitch.  Human oncogenic viruses: Hepatitis B and hepatitis C viruses and their role in hepatocarcinogenesis , 2008, Biochemistry (Moscow).

[50]  Jennifer J. Pointon,et al.  Comment on: An allograft inflammatory factor 1 (AIF1) single nucleotide polymorphism (SNP) is associated with anticentromere antibody positive systemic sclerosis. , 2007, Rheumatology.

[51]  L. Cardon,et al.  Fine mapping of the MHC Class III region demonstrates association of AIF1 and rheumatoid arthritis. , 2008, Rheumatology.

[52]  Bin Zhang,et al.  Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R , 2008, Bioinform..

[53]  Maria M. Mihaylova,et al.  AMPK and PPARδ Agonists Are Exercise Mimetics , 2008, Cell.

[54]  J. Pennings,et al.  Identification of a Common Gene Expression Response in Different Lung Inflammatory Diseases in Rodents and Macaques , 2008, PloS one.

[55]  Bin Zhang,et al.  A systems biology approach to drug discovery. , 2008, Advances in genetics.

[56]  C. Brenner,et al.  Faculty Opinions recommendation of AMPK and PPARdelta agonists are exercise mimetics. , 2008 .

[57]  R. Medzhitov.  Origin and physiological roles of inflammation , 2008, Nature.

[58]  Christopher B. Newgard,et al.  Molecular and metabolic mechanisms of insulin resistance and β-cell failure in type 2 diabetes , 2008, Nature Reviews Molecular Cell Biology.

[59]  Bruce E. Torbett,et al.  Developmental Regulation of TREM2 and DAP12 Expression in the Murine CNS: Implications for Nasu-Hakola Disease , 2008, Neurochemical Research.

[60]  P. Allavena,et al.  Cancer related inflammation: the macrophage connection. , 2008, Cancer letters.

[61]  Rachel B. Brem,et al.  Integrating large-scale functional genomic data to dissect the complexity of yeast regulatory networks , 2008, Nature Genetics.

[62]  G. Jensen.  Inflammation: roles in aging and sarcopenia. , 2008, JPEN. Journal of parenteral and enteral nutrition.

[63]  P. Allavena,et al.  Cancer-related inflammation , 2008, Nature.

[64]  John D. Storey,et al.  Mapping the Genetic Architecture of Gene Expression in Human Liver , 2008, PLoS biology.

[65]  F. Lee,et al.  Overcoming kinase resistance in chronic myeloid leukemia. , 2008, The international journal of biochemistry & cell biology.

[66]  H. Stefánsson,et al.  Genetics of gene expression and its effect on disease , 2008, Nature.

[67]  K. Nagata,et al.  The impact of inflammation on the pathogenesis and prognosis of ischemic stroke , 2008, Journal of the Neurological Sciences.

[68]  S. Horvath,et al.  Variations in DNA elucidate molecular networks that cause disease , 2008, Nature.

[69]  J. Lamb,et al.  The C3a Anaphylatoxin Receptor Is a Key Mediator of Insulin Resistance and Functions by Modulating Adipose Tissue Macrophage Infiltration and Activation , 2009, Diabetes.

[70]  N. Ruderman,et al.  AMPK and the biochemistry of exercise: implications for human health and disease. , 2009, The Biochemical journal.

[71]  Damien Chaussabel,et al.  Genomic transcriptional profiling identifies a candidate blood biomarker signature for the diagnosis of septicemic melioidosis , 2009, Genome Biology.

[72]  Martin S. Taylor,et al.  The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line , 2009, Nature Genetics.

[73]  E. Thorsby,et al.  Genetic variants of the HLA-A, HLA-B and AIF1 loci show independent associations with type 1 diabetes in Norwegian families , 2009, Genes and Immunity.

[74]  D. Baltimore,et al.  The stability of mRNA influences the temporal order of the induction of genes encoding inflammatory molecules , 2009, Nature Immunology.

[75]  M. Ichinose,et al.  The possible role of hematopoietic cell kinase in the pathophysiology of COPD. , 2009, Chest.

[76]  Angela M. Liu,et al.  microRNA-122 as a regulator of mitochondrial metabolic gene network in hepatocellular carcinoma , 2010, Molecular systems biology.

[77]  Long Yu,et al.  Oxidative Stress, Molecular Inflammation and Sarcopenia , 2010, International journal of molecular sciences.

[78]  Joshua L. Deignan,et al.  Identification and validation of genes affecting aortic lesions in mice. , 2010, The Journal of clinical investigation.

[79]  H. Bessler,et al.  Inflammation and Colorectal Cancer: Does Aspirin Affect the Interaction between Cancer and Immune Cells? , 2011, Inflammation.

[80]  Xia Yang,et al.  Systematic genetic and genomic analysis of cytochrome P450 enzyme activities in human liver. , 2010, Genome research.

[81]  Antihypertensive Drugs and Inflammation in Acute Ischemic Stroke as a Predictor Factor of Future Cardiovascular Mortality , 2012, Inflammation.

[82]  Takehiko Sasaki,et al.  Blockade of class IB phosphoinositide-3 kinase ameliorates obesity-induced inflammation and insulin resistance , 2011, Proceedings of the National Academy of Sciences.

[83]  G. Mastrangelo,et al.  Infection, inflammation and cancer , 2011, International journal of cancer.

[84]  Tao Xie,et al.  Inferring causal genomic alterations in breast cancer using gene expression data , 2011, BMC Systems Biology.

[85]  C. Carpenter,et al.  Addictive Genes and the Relationship to Obesity and Inflammation , 2011, Molecular Neurobiology.

[86]  J. Bromberg,et al.  Environment, inflammation, and cancer. , 2011, Current opinion in genetics & development.

[87]  C. Weinberg,et al.  Gene expression profiles from discordant monozygotic twins suggest that molecular pathways are shared among multiple systemic autoimmune diseases , 2011, Arthritis research & therapy.

[88]  M. Fornage,et al.  Association of coagulation‐related and inflammation‐related genes and factor VIIc levels with stroke: the Cardiovascular Health Study , 2011, Journal of thrombosis and haemostasis : JTH.

[89]  M. Jevtić,et al.  Cartilage oligomeric matrix protein - inflammation biomarker in knee osteoarthritis. , 2011, Bosnian journal of basic medical sciences.

[90]  K. Herholz,et al.  Brain inflammation is induced by co-morbidities and risk factors for stroke , 2011, Brain, Behavior, and Immunity.

[91]  R. Vandenbroucke,et al.  Treatment of TNF mediated diseases by selective inhibition of soluble TNF or TNFR1. , 2011, Cytokine & growth factor reviews.

[92]  A. Sica,et al.  Mechanisms linking pathogens-associated inflammation and cancer. , 2011, Cancer letters.

[93]  M. Aviram.  Atherosclerosis: cell biology and lipoproteins--inflammation and oxidative stress in atherogenesis: protective role for paraoxonases. , 2011, Current opinion in lipidology.

[94]  P. Grant,et al.  Inflammation and thrombosis in diabetes , 2011, Thrombosis and Haemostasis.

[95]  R. Jacob,et al.  Inflammation and the development of atherosclerosis. , 2011, Journal of atherosclerosis and thrombosis.

[96]  S. Mukhopadhyay,et al.  The evil axis of obesity, inflammation and type-2 diabetes. , 2011, Endocrine, metabolic & immune disorders drug targets.

[97]  Rachel B. Brem,et al.  Stitching together Multiple Data Dimensions Reveals Interacting Metabolomic and Transcriptomic Networks That Modulate Cell Regulation , 2012, PLoS biology.

[98]  D. Meyre,et al.  Common Variants in FTO, MC4R, TMEM18, PRL, AIF1, and PCSK1 Show Evidence of Association With Adult Obesity in the Greek Population , 2012, Obesity.

[99]  M. Blüher,et al.  Adipositas und Inflammation , 2013, Deutsche Medizinische Wochenschrift.