Laura Smith

Oklahoma City University, Oklahoma City, Oklahoma, United States

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Publications (1)7.48 Total impact

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    ABSTRACT: The development of biomarkers to predict response to therapy in polyarticular juvenile idiopathic arthritis (JIA) is an important issue in pediatric rheumatology. A critical step in this process is determining whether there is biologic meaning to clinically derived terms such as "active disease" and "remission." The aim of this study was to use a systems biology approach to address this question. We performed gene transcriptional profiling on children who fulfilled the criteria for specific disease states as defined by the consensus criteria developed by Wallace and colleagues. The study group comprised children with active disease (n = 14), children with clinical remission on medication (CRM; n = 9), children with clinical remission off medication (CR; n = 6), and healthy control children (n = 13). Transcriptional profiles in peripheral blood mononuclear cells (PBMCs) were obtained using Affymetrix U133 Plus 2.0 arrays. Hierarchical cluster analysis and predictive modeling demonstrated that the clinically derived criteria represent biologically distinct states. Minimal differences were seen between children with active disease and those with disease in CRM. Thus, underlying immune/inflammatory abnormalities persist despite a response to therapy. The PBMC transcriptional profiles of children whose disease was in remission did not return to normal but revealed networks of proinflammatory and antiinflammatory genes, suggesting that remission is a state of homeostasis, not a return to a normal state. Gene transcriptional profiling of PBMCs revealed that clinically derived criteria for JIA disease states reflect underlying biology. We also demonstrated that neither CRM nor CR status results in resolution of the underlying inflammatory process, but that these conditions are more likely to be states of balanced homeostasis between proinflammatory and antiinflammatory mechanisms.
    Arthritis & Rheumatology 03/2009; 60(3):892-900. · 7.48 Impact Factor