title: Gene Expression Deconvolution for Uncovering Molecular Signatures in Response to Therapy in Juvenile Idiopathic Arthritis.
abstract: Gene expression-based signatures help identify pathways relevant to diseases and treatments, but are challenging to construct when there is a diversity of disease mechanisms and treatments in patients with complex diseases. To overcome this challenge, we present a new application of an in silico gene expression deconvolution method, ISOpure-S1, and apply it to identify a common gene expression signature corresponding to response to treatment in 33 juvenile idiopathic arthritis (JIA) patients. Using pre- and post-treatment gene expression profiles only, we found a gene expression signature that significantly correlated with a reduction in the number of joints with active arthritis, a measure of clinical outcome (Spearman rho = 0.44, p = 0.040, Bonferroni correction). This signature may be associated with a decrease in T-cells, monocytes, neutrophils and platelets. The products of most differentially expressed genes include known biomarkers for JIA such as major histocompatibility complexes and interleukins, as well as novel biomarkers including α-defensins. This method is readily applicable to expression datasets of other complex diseases to uncover shared mechanistic patterns in heterogeneous samples.
authors.affiliation: Division of Engineering Science, University of Toronto, Toronto, ON, Canada.
authors.forename: Ang
authors.initials: A
authors.lastname: Cui
authors.affiliation: Department of Computer Science, University of Toronto, Toronto, ON, Canada.
authors.forename: Gerald
authors.initials: G
authors.lastname: Quon
authors.affiliation: Department of Pediatrics, Division of Rheumatology, University of Saskatchewan, Saskatoon, SK, Canada.
authors.forename: Alan M
authors.initials: AM
authors.lastname: Rosenberg
authors.affiliation: Divisions of Rheumatology and Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada.|Departments of Paediatrics, Immunology and Medical Sciences, University of Toronto, Toronto, ON, Canada.
authors.forename: Rae S M
authors.initials: RS
authors.lastname: Yeung
authors.affiliation: Department of Computer Science, University of Toronto, Toronto, ON, Canada.|The Donnelly Centre, University of Toronto, Toronto, ON, Canada.|Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
authors.forename: Quaid
authors.initials: Q
authors.lastname: Morris
mesh_terms: D000293:Adolescent; D000465:Algorithms; D018501:Antirheumatic Agents / Q000627:therapeutic use*; D001171:Arthritis, Juvenile / Q000188:drug therapy* / Q000235:genetics*; D015415:Biomarkers; D001792:Blood Platelets / Q000166:cytology; D002648:Child; D015870:Gene Expression; D020869:Gene Expression Profiling; D006801:Humans; D018655:Lymphocyte Count; D008962:Models, Theoretical; D009000:Monocytes / Q000166:cytology; D009504:Neutrophils / Q000166:cytology; D010865:Pilot Projects; D013601:T-Lymphocytes / Q000166:cytology; D016896:Treatment Outcome; D023084:alpha-Defensins / Q000378:metabolism
chemical_list: D018501:Antirheumatic Agents; D015415:Biomarkers; D023084:alpha-Defensins