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Novel approaches to gene expression analysis of active polyarticular juvenile rheumatoid arthritis.

ABSTRACT: Juvenile rheumatoid arthritis (JRA) has a complex, poorly characterized pathophysiology. Modeling of transcriptosome behavior in pathologic specimens using microarrays allows molecular dissection of complex autoimmune diseases. However, conventional analyses rely on identifying statistically significant differences in gene expression distributions between patients and controls. Since the principal aspects of disease pathophysiology vary significantly among patients, these analyses are biased. Genes with highly variable expression, those most likely to regulate and affect pathologic processes, are excluded from selection, as their distribution among healthy and affected individuals may overlap significantly. Here we describe a novel method for analyzing microarray data that assesses statistically significant changes in gene behavior at the population level. This method was applied to expression profiles of peripheral blood leukocytes from a group of children with polyarticular JRA and healthy control subjects. Results from this method are compared with those from a conventional analysis of differential gene expression and shown to identify discrete subsets of functionally related genes relevant to disease pathophysiology. These results reveal the complex action of the innate and adaptive immune responses in patients and specifically underscore the role of IFN-gamma in disease pathophysiology. Discriminant function analysis of data from a cohort of patients treated with conventional therapy identified additional subsets of functionally related genes; the results may predict treatment outcomes. While data from only 9 patients and 12 healthy controls was used, this preliminary investigation of the inflammatory genomics of JRA illustrates the significant potential of utilizing complementary sets of bioinformatics tools to maximize the clinical relevance of microarray data from patients with autoimmune disease, even in small cohorts.

SUBMITTER: Jarvis JN

PROVIDER: S-EPMC400410 | biostudies-literature | 2004

REPOSITORIES: biostudies-literature

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Novel approaches to gene expression analysis of active polyarticular juvenile rheumatoid arthritis.

Jarvis James N JN Dozmorov Igor I Jiang Kaiyu K Frank Mark Barton MB Szodoray Peter P Alex Philip P Centola Michael M

Arthritis research & therapy 20031106 1

Juvenile rheumatoid arthritis (JRA) has a complex, poorly characterized pathophysiology. Modeling of transcriptosome behavior in pathologic specimens using microarrays allows molecular dissection of complex autoimmune diseases. However, conventional analyses rely on identifying statistically significant differences in gene expression distributions between patients and controls. Since the principal aspects of disease pathophysiology vary significantly among patients, these analyses are biased. Ge ...[more]

PMID: 14979934

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Project description:Although strong epidemiologic evidence suggests an important role for adaptive immunity in the pathogenesis of polyarticular juvenile rheumatoid arthritis (JRA), there remain many aspects of the disease that suggest equally important contributions of the innate immune system. We used gene expression arrays and computer modeling to examine the function in neutrophils of 25 children with polyarticular JRA. Computer analysis identified 712 genes that were differentially expressed between patients and healthy controls. Computer-assisted analysis of the differentially expressed genes demonstrated functional connections linked to both interleukin (IL)-8- and interferon-gamma (IFN-gamma)-regulated processes. Of special note is that the gene expression fingerprint of children with active JRA remained essentially unchanged even after they had responded to therapy. This result differed markedly from our previously reported work, in which gene expression profiles in buffy coats of children with polyarticular JRA reverted to normal after disease control was achieved pharmacologically. These findings suggest that JRA neutrophils remain in an activated state even during disease quiescence. Computer modeling of array data further demonstrated disruption of gene regulatory networks in clusters of genes modulated by IFN-gamma and IL-8. These cytokines have previously been shown to independently regulate the frequency (IFN-gamma) and amplitude (IL-8) of the oscillations of key metabolites in neutrophils, including nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and superoxide ion. Using real-time, high-speed, single-cell photoimaging, we observed that 6/6 JRA patients displayed a characteristic defect in 12% to 23% of the neutrophils tested. Reagents known to induce only frequency fluctuations of NAD(P)H and superoxide ion induced both frequency and amplitude fluctuations in JRA neutrophils. This is a novel finding that was observed in children with both active (n = 4) and inactive (n = 2) JRA. A subpopulation of polyarticular JRA neutrophils are in a chronic, activated state, a state that persists when the disease is well controlled pharmacologically. Furthermore, polyarticular JRA neutrophils exhibit an intrinsic defect in the regulation of metabolic oscillations and superoxide ion production. Our data are consistent with the hypothesis that neutrophils play an essential role in the pathogenesis of polyarticular JRA.

Project description:ObjectiveTo explore the shared gene signatures and potential molecular mechanisms of polyarticular juvenile idiopathic arthritis (pJIA) and autoimmune uveitis (AU).MethodThe microarray data of pJIA and AU from the Gene Expression Omnibus (GEO) database were downloaded and analyzed. The GEO2R tool was used to identify the shared differentially expressed genes (DEGs) and genes of extracellular proteins were identified among them. Then, weighted gene co-expression network analysis (WGCNA) was used to identify the shared immune-related genes (IRGs) related to pJIA and AU. Moreover, the shared transcription factors (TFs) and microRNAs (miRNAs) in pJIA and AU were acquired by comparing data from HumanTFDB, hTFtarget, GTRD, HMDD, and miRTarBase. Finally, Metascape and g: Profiler were used to carry out function enrichment analyses of previously identified gene sets.ResultsWe found 40 up-regulated and 15 down-regulated shared DEGs via GEO2R. Then 24 shared IRGs in positivity-related modules, and 18 shared IRGs in negatively-related modules were found after WGCNA. After that, 3 shared TFs (ARID1A, SMARCC2, SON) were screened. And the constructed TFs-shared DEGs network indicates a central role of ARID1A. Furthermore, hsa-miR-146 was found important in both diseases. The gene sets enrichment analyses suggested up-regulated shared DEGs, TFs targeted shared DEGs, and IRGs positivity-correlated with both diseases mainly enriched in neutrophil degranulation process, IL-4, IL-13, and cytokine signaling pathways. The IRGs negatively correlated with pJIA and AU mainly influence functions of the natural killer cell, cytotoxicity, and glomerular mesangial cell proliferation. The down-regulated shared DEGs and TFs targeted shared DEGs did not show particular functional enrichment.ConclusionOur study fully demonstrated the flexibility and complexity of the immune system disorders involved in pJIA and AU. Neutrophil degranulation may be considered the shared pathogenic mechanism, and the roles of ARID1A and MiR-146a are worthy of further in-depth study. Other than that, the importance of periodic inspection of kidney function is also noteworthy.

Dataset Information

Novel approaches to gene expression analysis of active polyarticular juvenile rheumatoid arthritis.

Publications

Novel approaches to gene expression analysis of active polyarticular juvenile rheumatoid arthritis.

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