Abstract
BackgroundWhile standard reductionist approaches have provided some insights into specific gene polymorphisms and molecular pathways involved in disease pathogenesis, our understanding of complex traits such as atherosclerosis or type 2 diabetes remains incomplete. Gene expression profiling provides an unprecedented opportunity to understand complex human diseases by providing a global view of the multiple interactions across the genome that are likely to contribute to disease pathogenesis. Thus, the goal of gene expression profiling is not to generate lists of differentially expressed genes, but to identify the physiologic or pathogenic processes and structures represented in the expression profile.MethodsRNA was separately extracted from peripheral blood neutrophils and mononuclear leukocytes, labeled, and hybridized to genome level microarrays to generate expression profiles of children with polyarticular juvenile idiopathic arthritis, juvenile dermatomyositis relative to childhood controls. Statistically significantly differentially expressed genes were identified from samples of each disease relative to controls. Functional network analysis identified interactions between products of these differentially expressed genes.ResultsIn silico models of both diseases demonstrated similar features with properties of scale-free networks previously described in physiologic systems. These networks were observable in both cells of the innate immune system (neutrophils) and cells of the adaptive immune system (peripheral blood mononuclear cells).ConclusionGenome-level transcriptional profiling from childhood onset rheumatic diseases suggested complex interactions in two arms of the immune system in both diseases. The disease associated networks showed scale-free network patterns similar to those reported in normal physiology. We postulate that these features have important implications for therapy as such networks are relatively resistant to perturbation.
Highlights
While standard reductionist approaches have provided some insights into specific gene polymorphisms and molecular pathways involved in disease pathogenesis, our understanding of complex traits such as atherosclerosis or type 2 diabetes remains incomplete
Analysis of data from neutrophil samples from 14 patients with juvenile dermatomyositis (JDM) and 13 controls revealed fifteen differentially expressed genes (Additional File 2), five that were under-expressed in patients (1.8 – 2.3 fold) and ten that were over-expressed in patients (1.8 – 2.4 fold different)
RNA isolated from PBMC from 15 patients with Juvenile idiopathic arthritis (JIA), 13 patients with JDM, and 15 controls were used to obtain PBMC microarray datasets
Summary
While standard reductionist approaches have provided some insights into specific gene polymorphisms and molecular pathways involved in disease pathogenesis, our understanding of complex traits such as atherosclerosis or type 2 diabetes remains incomplete. Even single-gene traits have demonstrated previously unsuspected levels of complexity when scrutinized through the lens of whole-genome technologies [1,2,3] Chronic inflammatory diseases such as rheumatoid arthritis (RA) and juvenile dermatomyositis (JDM) are examples of human diseases whose etiologies and pathogenic mechanisms remain incompletely understood. Advances in miniaturization and robotics have made this approach feasible, providing the opportunity to address critical questions of pediatric rheumatic disease pathogenesis, diagnosis, prognosis, and identification of targets of therapy in this "global" way. This understanding, in turn, is critical to our understanding the disease and our translation of that understanding into clinical practice. Of the available genome-wide technologies, gene expression microarrays are in the most mature phase of development, allow the most rigorous level of independent corroboration, and show the greatest promise for rapid translation into the clinical sphere [8]
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