Dataset Information

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 ?-defensins. This method is readily applicable to expression datasets of other complex diseases to uncover shared mechanistic patterns in heterogeneous samples.

SUBMITTER: Cui A

PROVIDER: S-EPMC4887077 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Gene Expression Deconvolution for Uncovering Molecular Signatures in Response to Therapy in Juvenile Idiopathic Arthritis.

Cui Ang A Quon Gerald G Rosenberg Alan M AM Yeung Rae S M RS Morris Quaid Q

PloS one 20160531 5

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. Us ...[more]

PMID: 27244050

Similar Datasets

Project description:ObjectiveAround one-third of patients with juvenile idiopathic arthritis (JIA) fail to respond to first-line methotrexate (MTX) or anti-tumor necrosis factor (TNF) therapy, with even fewer achieving ≥ American College of Rheumatology Pediatric 70% criteria for response (ACRpedi70), though individual responses cannot yet be accurately predicted. Because change in serum S100-protein myeloid-related protein complex 8/14 (MRP8/14) is associated with therapeutic response, we tested granulocyte-specific S100-protein S100A12 as a potential biomarker for treatment response.MethodsS100A12 serum concentration was determined by ELISA in patients treated with MTX (n = 75) and anti-TNF (n = 88) at baseline and followup. Treatment response (≥ ACRpedi50 score), achievement of inactive disease, and improvement in Juvenile Arthritis Disease Activity Score (JADAS)-10 score were recorded.ResultsBaseline S100A12 concentration was measured in patients treated with anti-TNF [etanercept n = 81, adalimumab n = 7; median 200, interquartile range (IQR) 133-440 ng/ml] and MTX (median 220, IQR 100-440 ng/ml). Of the patients in the anti-TNF therapy group, 74 (84%) were also receiving MTX. Responders to MTX (n = 57/75) and anti-TNF (n = 66/88) therapy had higher baseline S100A12 concentration compared to nonresponders: median 240 (IQR 125-615) ng/ml versus 150 (IQR 87-233) ng/ml, p = 0.021 for MTX, and median 308 (IQR 150-624) ng/ml versus 151 (IQR 83-201) ng/ml, p = 0.002, for anti-TNF therapy. Followup S100A12 could be measured in 44/75 MTX-treated patients (34/44 responders) and 39/88 anti-TNF-treated patients (26/39 responders). Responders had significantly reduced S100A12 concentration (MTX: p = 0.031, anti-TNF: p < 0.001) at followup versus baseline. Baseline serum S100A12 in both univariate and multivariate regression models for anti-TNF therapy and univariate analysis alone for MTX therapy was significantly associated with change in JADAS-10.ConclusionResponders to MTX or anti-TNF treatment can be identified by higher pretreatment S100A12 serum concentration levels.

Dataset Information

Gene Expression Deconvolution for Uncovering Molecular Signatures in Response to Therapy in Juvenile Idiopathic Arthritis.

Publications

Gene Expression Deconvolution for Uncovering Molecular Signatures in Response to Therapy in Juvenile Idiopathic Arthritis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets