Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Remission in Polyarticular Juvenile Idiopathic Arthritis

ABSTRACT: Identify biomarkers to predict response to therapy in polyarticular juvenile idiopathic arthritis (JIA) using gene expression microarrays. 42 samples from 13 controls, 14 active patients, 9 patients in clinical remission with medication (CRM), and 6 patients in clinical remission without medication (CR). All patients had polyarticular JIA.

ORGANISM(S): Homo sapiens

SUBMITTER: Bart Frank

PROVIDER: E-GEOD-15645 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

The meaning of clinical remission in polyarticular juvenile idiopathic arthritis: gene expression profiling in peripheral blood mononuclear cells identifies distinct disease states.

Knowlton Nicholas N Jiang Kaiyu K Frank Mark Barton MB Aggarwal Amita A Wallace Carol C McKee Ryan R Chaser Brad B Tung Catherine C Smith Laura L Chen Yanmin Y Osban Jeanette J O'Neil Kathleen K Centola Michael M McGhee Julie L JL Jarvis James N JN

Arthritis and rheumatism 20090301 3

<h4>Objective</h4>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.<h4>Methods</h4>We performed gene transcriptional profiling on children who fulfill ...[more]

PMID: 19248118

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Project description:Objective. To identify gene expression differences in peripheral blood from patients with early and late onset juvenile idiopathic arthritis (JIA). Methods. Peripheral blood mononuclear cells (PBMC) were isolated from 56 healthy controls and 104 patients with recent onset JIA (39 persistent oligoarticular, 45 RF-polyarticular, and 20 systemic). Poly(A) RNA was amplified and labeled using NuGEN Ovation, and gene expression assessed with Affymetrix HG-U133 Plus 2.0 GeneChips®. Results. A total of 832 probe sets revealed gene expression differences (false-discovery rate 5%) in PBMC from children with oligoarticular JIA whose disease began before 6 years of age (age at onset [AaO] <6; early onset), compared to subjects whose disease began at 6 years of age or later (AaO ?6; late onset). In early onset patients there was greater expression of genes related to B-cells, and lesser expression of genes related to cells of the myeloid lineage. Support Vector Machine algorithms identified samples from early or late onset oligoarticular (97% accuracy) or polyarticular (89% accuracy) JIA patients, but not systemic JIA patients or healthy controls. Principal component analysis showed that the major classifier of samples was AaO regardless of whether they had oligoarticular or polyarticular JIA. Conclusion. PBMC gene expression analysis reveals biologic differences between early and late onset JIA patients independent of classification based on the number of joints involved. These data suggest AaO may be an important parameter to consider in JIA classification. Furthermore, different pathologic mechanisms may influence AaO, and understanding these processes may lead to improved treatment of JIA. Methods. Peripheral blood mononuclear cells (PBMC) were isolated from 56 healthy controls and 104 patients with recent onset JIA (39 persistent oligoarticular, 45 RF-polyarticular, and 20 systemic). Poly(A) RNA was amplified and labeled using NuGEN Ovation, and gene expression assessed with Affymetrix HG-U133 Plus 2.0 GeneChips®.

Project description:Objective. Microarray analysis was used to determine whether children with recent onset polyarticular juvenile idiopathic arthritis (JIA) exhibit biologically or clinically informative gene expression signatures in peripheral blood mononuclear cells (PBMC). Methods. Peripheral blood samples were obtained from 59 healthy children and 61 children with polyarticular JIA prior to treatment with second-line medications, such as methotrexate or biological agents. RNA was purified from Ficoll-isolated mononuclear cells, fluorescently labeled and then hybridized to Affymetrix U133 Plus 2.0 GeneChips. Data were analyzed using ANOVA at a 5% false discovery rate threshold after Robust Multi-Array Average pre-processing and Distance Weighted Discrimination normalization. Results. Initial analysis revealed 873 probe sets for genes that were differentially expressed between polyarticular JIA and controls. Hierarchical clustering of these probe sets distinguished three subgroups within polyarticular JIA. Prototypical subjects within each subgroup were identified and used to define subgroup-specific gene expression signatures. One of these signatures was associated with monocyte markers, another with transforming growth factor-beta-inducible genes, and a third with immediate-early genes. Correlation of these gene expression signatures with clinical and biological features of JIA subgroups suggests direct relevance to aspects of disease activity and supports the division of polyarticular JIA into distinct subsets. Conclusions. PBMC gene expression signatures in recent onset polyarticular JIA reflect discrete disease processes and offer a molecular classification of disease. Keywords: Patient vs. control, reassessment of phenotype PBMC samples were obtained from 59 healthy children and 61 children with polyarticular JIA prior to treatment with second-line medications, such as methotrexate or biological agents. RNA was purified from Ficoll-isolated mononuclear cells, fluorescently labeled and then hybridized to Affymetrix U133 Plus 2.0 GeneChips. Data were analyzed using ANOVA at a 5% false discovery rate threshold after Robust Multi-Array Average pre-processing and Distance Weighted Discrimination normalization.

Dataset Information

Remission in Polyarticular Juvenile Idiopathic Arthritis

Publications

The meaning of clinical remission in polyarticular juvenile idiopathic arthritis: gene expression profiling in peripheral blood mononuclear cells identifies distinct disease states.

Similar Datasets

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