http://hdl.handle.net/2027.42/78400 Sun, 26 May 2013 04:32:50 GMT 2013-05-26T04:32:50Z http://deepblue.lib.umich.edu:80/bitstream/id/279993/216680.gif http://hdl.handle.net/2027.42/78400 http://hdl.handle.net/2027.42/83958 Magnetization Transfer Helps Detect Intestinal Fibrosis in an Animal Model of Crohn Disease Adler, Jeremy; Swanson, Scott; Schmiedlin-Ren, Phyllissa; Higgins, Peter; Golembeski, Christopher; Polydorides, Alexandros; McKenna, Barbara; Hussain, Hero; Verrot, Trevor; Zimmermann, Ellen Sat, 01 Jan 2011 00:00:00 GMT http://hdl.handle.net/2027.42/83958 2011-01-01T00:00:00Z http://hdl.handle.net/2027.42/83256 The Prognostic Power of the NOD2 Genotype for Complicated Crohn's Disease: A Meta-Analysis Adler, Jeremy; Rangwalla, Sujal; Dwamena, Ben; Peter, HIggins Thu, 24 Feb 2011 00:00:00 GMT http://hdl.handle.net/2027.42/83256 2011-02-24T00:00:00Z http://hdl.handle.net/2027.42/83254 CT enterography of pediatric Crohn disease Dillman, Jonathan; Adler, Jeremy; Zimmermann, Ellen Fri, 20 Nov 2009 00:00:00 GMT http://hdl.handle.net/2027.42/83254 2009-11-20T00:00:00Z http://hdl.handle.net/2027.42/78275 Identification of pediatric septic shock subclasses based on genome-wide expression profiling Wong, Hector R; Cvijanovich, Natalie; Lin, Richard; Allen, Geoffrey L; Thomas, Neal J; Willson, Douglas F; Freishtat, Robert J; Anas, Nick; Meyer, Keith; Checchia, Paul A; Monaco, Marie; Odoms, Kelli; Shanley, Thomas P Abstract Background Septic shock is a heterogeneous syndrome within which probably exist several biological subclasses. Discovery and identification of septic shock subclasses could provide the foundation for the design of more specifically targeted therapies. Herein we tested the hypothesis that pediatric septic shock subclasses can be discovered through genome-wide expression profiling. Methods Genome-wide expression profiling was conducted using whole blood-derived RNA from 98 children with septic shock, followed by a series of bioinformatic approaches targeted at subclass discovery and characterization. Results Three putative subclasses (subclasses A, B, and C) were initially identified based on an empiric, discovery-oriented expression filter and unsupervised hierarchical clustering. Statistical comparison of the three putative subclasses (analysis of variance, Bonferonni correction, P < 0.05) identified 6,934 differentially regulated genes. K-means clustering of these 6,934 genes generated 10 coordinately regulated gene clusters corresponding to multiple signaling and metabolic pathways, all of which were differentially regulated across the three subclasses. Leave one out cross-validation procedures indentified 100 genes having the strongest predictive values for subclass identification. Forty-four of these 100 genes corresponded to signaling pathways relevant to the adaptive immune system and glucocorticoid receptor signaling, the majority of which were repressed in subclass A patients. Subclass A patients were also characterized by repression of genes corresponding to zinc-related biology. Phenotypic analyses revealed that subclass A patients were younger, had a higher illness severity, and a higher mortality rate than patients in subclasses B and C. Conclusion Genome-wide expression profiling can identify pediatric septic shock subclasses having clinically relevant phenotypes. Wed, 22 Jul 2009 00:00:00 GMT http://hdl.handle.net/2027.42/78275 2009-07-22T00:00:00Z