Cytokine and molecular networks in sepsis cases: a network biology approach

Sepsis is a life-threatening condition of organ dysfunction caused by a dysregulated host immune response to infection. We performed network analysis of cytokine molecules and compared network structures between a systematic inflammatory response syndrome (SIRS) or normal control (NC) group and a sepsis group. We recruited SIRS (n = 33) and sepsis (n = 89) patients from electronic medical records (EMR) according to whether data on PCT, CRP, interleukin (IL)-1β, IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-12p70, IL-13, IL-17, IL-22, TNF-α, and IFN-γ levels were available. From the public GEO dataset, GSE66099, GSE9960, GSE95233, GSE57065 were downloaded. Genes corresponding to 15 molecules were extracted from an expression array. A correlation matrix was formed for the 15 molecules and statistically significant molecular pairs were used as pairs for network analysis of coexpression. The number of molecular or gene expression pairs significantly correlated among the SIRS or control and sepsis groups are as follows for datasets: EMR, 15 and 15; GEO66099-1, 13 and 15; GEO9960, 13 and 11; GSE95233, 13 and 8; GSE66099-2, 15 and 14; GSE57065, 14 and 13, respectively. Network analysis revealed that network diameter, number of nodes and shortest path were equal to or lower in the sepsis group. The coexpression network in sepsis patients was relatively small sized and had lower shortest paths compared with the SIRS group or healthy control group. Cytokines with one degree (k = 1) are increased in sepsis group compared with SIRS or healthy control group. IL-9 and IL-2 were not included in network of sepsis group indicating that these cytokines showed no correlation with other cytokines. These data might imply that cytokines tend to be dysregulated in the sepsis group compared to that of SIRS or normal control groups

[1]  T. Rimmele,et al.  Modulation of LILRB2 protein and mRNA expressions in septic shock patients and after ex vivo lipopolysaccharide stimulation. , 2017, Human immunology.

[2]  D. Kelvin,et al.  Defining immunological dysfunction in sepsis: A requisite tool for precision medicine. , 2016, The Journal of infection.

[3]  T. Rea,et al.  Assessment of Clinical Criteria for Sepsis: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). , 2016, JAMA.

[4]  Adil Rafiq Rather,et al.  The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) , 2015 .

[5]  Purvesh Khatri,et al.  A comprehensive time-course–based multicohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene set , 2015, Science Translational Medicine.

[6]  Michael Bailey,et al.  Systemic inflammatory response syndrome criteria in defining severe sepsis. , 2015, The New England journal of medicine.

[7]  Yong-ming Yao,et al.  The growing spectrum of anti-inflammatory interleukins and their potential roles in the development of sepsis. , 2015, Journal of interferon & cytokine research : the official journal of the International Society for Interferon and Cytokine Research.

[8]  J. Y. Kim,et al.  Diagnosis and evaluation of severity of sepsis via the use of biomarkers and profiles of 13 cytokines: a multiplex analysis , 2015, Clinical chemistry and laboratory medicine.

[9]  G. Yoon,et al.  Characterization of age signatures of DNA methylation in normal and cancer tissues from multiple studies , 2014, BMC Genomics.

[10]  M. Paye,et al.  Early and dynamic changes in gene expression in septic shock patients: a genome-wide approach , 2014, Intensive Care Medicine Experimental.

[11]  T. van der Poll,et al.  Severe sepsis and septic shock. , 2013, The New England journal of medicine.

[12]  Yonggoo Kim,et al.  Procalcitonin as a diagnostic marker and IL-6 as a prognostic marker for sepsis. , 2013, Diagnostic microbiology and infectious disease.

[13]  Gary D Bader,et al.  A travel guide to Cytoscape plugins , 2012, Nature Methods.

[14]  R. Gazzinelli,et al.  Toll-like receptor 9 activation in neutrophils impairs chemotaxis and reduces sepsis outcome* , 2012, Critical care medicine.

[15]  Nadezhda T. Doncheva,et al.  Topological analysis and interactive visualization of biological networks and protein structures , 2012, Nature Protocols.

[16]  L. Arnaud,et al.  Cytokine Profiles in Sepsis Have Limited Relevance for Stratifying Patients in the Emergency Department: A Prospective Observational Study , 2011, PloS one.

[17]  R. Hotchkiss,et al.  Immunosuppression in patients who die of sepsis and multiple organ failure. , 2011, JAMA.

[18]  Raquel Almansa,et al.  Pro- and anti-inflammatory responses are regulated simultaneously from the first moments of septic shock. , 2011, European cytokine network.

[19]  Benjamin Tang,et al.  Development and validation of a novel molecular biomarker diagnostic test for the early detection of sepsis , 2011, Critical care.

[20]  Soojin V Yi,et al.  Path lengths in protein–protein interaction networks and biological complexity , 2011, Proteomics.

[21]  Reinhard Schneider,et al.  Using graph theory to analyze biological networks , 2011, BioData Mining.

[22]  Stephen J. Huang,et al.  Genome-wide transcription profiling of human sepsis: a systematic review , 2010, Critical care.

[23]  Jianzhi Zhang,et al.  A Big World Inside Small-World Networks , 2009, PloS one.

[24]  Ju Han Kim,et al.  Identifying set-wise differential co-expression in gene expression microarray data , 2009, BMC Bioinformatics.

[25]  Ian W. Dawes,et al.  Gene-expression profiling of peripheral blood mononuclear cells in sepsis* , 2009, Critical care medicine.

[26]  Sean R. Davis,et al.  GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor , 2007, Bioinform..

[27]  M. Gerstein,et al.  Getting connected: analysis and principles of biological networks. , 2007, Genes & development.

[28]  Fernando A Bozza,et al.  Cytokine profiles as markers of disease severity in sepsis: a multiplex analysis , 2007, Critical care.

[29]  Z. Oltvai,et al.  Network biology: understanding the cell's functional organization , 2004, Nature Reviews Genetics.

[30]  R. Hotchkiss,et al.  The pathophysiology and treatment of sepsis. , 2003, The New England journal of medicine.

[31]  Jonathan Cohen The immunopathogenesis of sepsis , 2002, Nature.

[32]  J. Cavaillon,et al.  Review: Immunodepression in sepsis and SIRS assessed by ex vivo cytokine production is not a generalized phenomenon: a review , 2001, Journal of endotoxin research.

[33]  W. Knaus,et al.  Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. American College of Chest Physicians/Society of Critical Care Medicine. , 1992, Chest.

[34]  N. Gulbahce,et al.  Network medicine: a network-based approach to human disease , 2010, Nature Reviews Genetics.