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07-07-2016 | Juvenile idiopathic arthritis | Article

Whole blood expression profiling from the TREAT trial: insights for the pathogenesis of polyarticular juvenile idiopathic arthritis

Journal: Arthritis Research & Therapy

Authors: Kaiyu Jiang, Laiping Wong, Ashley D. Sawle, M. Barton Frank, Yanmin Chen, Carol A. Wallace, James N. Jarvis

Publisher: BioMed Central

Abstract

Background

The Trial of Early Aggressive Therapy in Juvenile Idiopathic Arthritis (TREAT trial) was accompanied by a once-in-a-generation sample collection for translational research. In this paper, we report the results of whole blood gene expression analyses and genomic data-mining designed to cast light on the immunopathogenesis of polyarticular juvenile idiopathic arthritis (JIA).

Methods

TREAT samples and samples from an independent cohort were analyzed on Affymetrix microarrays and compared to healthy controls. Data from the independent cohort were used to validate the TREAT data. Pathways analysis was used to characterize gene expression profiles. Furthermore, we correlated differential gene expression with new information about functional regulatory elements within the genome to develop models of aberrant gene expression in JIA.

Results

There was a strong concordance in gene expression between TREAT samples and the independent cohort. In addition, rheumatoid factor (RF)-positive and RF-negative patients showed only small differences on whole blood expression profiles. Analysis of the combined samples showed 158 genes represented by 176 probes that showed differential expression between TREAT subjects at baseline and healthy controls. None of the differentially expressed genes were encoded within linkage disequilibrium blocks containing single nucleotide polymorphisms known to be associated with risk for JIA. Functional analysis of these genes showed functional associations with multiple processes associated with innate and adaptive immunity, and appeared to reflect overall suppression of STAT1–3/interferon response factor-mediated pathways.

Conclusions

Despite their limitations, whole blood expression profiles clearly distinguish children with polyarticular JIA from healthy controls. Whole blood expression profiles identify several immunologic pathways of biologic relevance that will need to be pursued in homogeneous cell populations in order to clarify mechanisms of pathogenesis.

Trial registration

ClinicalTrials.gov registry #NCT00443430, originally registered 2 March 2007 and last updated 30 May 2013.
Literature
1.
Wallace CA, Giannini EH, Spalding SJ, et al. Trial of early aggressive therapy in polyarticular juvenile idiopathic arthritis. Arthritis Rheum. 2012;64:2012–21.CrossRefPubMed
2.
Jiang K, Sawle AD, Frank MB, et al. Whole blood gene expression profiling predicts therapeutic response at six months in patients with polyarticular juvenile idiopathic arthritis. Arthritis Rheumatol. 2014;66:1363–71.CrossRefPubMedPubMedCentral
3.
Liu J, Walter E, Stenger D, Thach D. Effects of globin mRNA reduction methods on gene expression profiles from whole blood. J Mol Diagn. 2006;8:551–8.CrossRefPubMedPubMedCentral
4.
Chai V, Vassilakos A, Lee Y, Wright JA, Young AH. Optimization of the PAXgene blood RNA extraction system for gene expression analysis of clinical samples. J Clin Lab Anal. 2005;19:182–8.CrossRefPubMed
5.
Du N, Jiang K, Sawle AD, et al. Dynamic tracking of functional gene modules in treated juvenile idiopathic arthritis. Genome Med. 2015;7:109.CrossRefPubMedPubMedCentral
6.
Petty RE, Southwood TR, Manners P, et al. International League of Associations for Rheumatology classification of juvenile idiopathic arthritis: second revision, Edmonton, 2001. J Rheumatol. 2004;31:390–2.PubMed
7.
Cobb JP, Mindrinos MN, Miller-Graziano C, et al. Application of genome-wide expression analysis to human health and disease. Proc Natl Acad Sci U S A. 2005;102:4801–6.CrossRefPubMedPubMedCentral
8.
Du P, Kibbe WA, Lin SM. lumi: a pipeline for processing Illumina microarray. Bioinformatics. 2008;24:1547–8.CrossRefPubMed
9.
Lin SM, Du P, Huber W, Kibbe WA. Model-based variance-stabilizing transformation for Illumina microarray data. Nucleic Acids Res. 2008;36:e11.CrossRefPubMedPubMedCentral
10.
Smyth GK. Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol. 2004;3:Article3.PubMed
11.
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc B. 1995;57:289–300.
12.
Calvano SE, Xiao W, Richards DR, et al. A network-based analysis of systemic inflammation in humans. Nature. 2005;437:1032–7.CrossRefPubMed
13.
Ficenec D, Osborne M, Pradines J, et al. Computational knowledge integration in biopharmaceutical research. Brief Bioinform. 2003;4:260–78.CrossRefPubMed
14.
Hinks A, Cobb J, Marion MC, et al. Dense genotyping of immune-related disease regions identifies 14 new susceptibility loci for juvenile idiopathic arthritis. Nat Genet. 2013;45:664–9.CrossRefPubMedPubMedCentral
15.
Hersh AO, Prahalad S. Immunogenetics of juvenile idiopathic arthritis: a comprehensive review. J Autoimmun. 2015;64:113–24.CrossRefPubMedPubMedCentral
16.
Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26:841–2.CrossRefPubMedPubMedCentral
17.
Bhardwaj RS, Eblenkamp M, Berndt T, Tietze L, Klosterhalfen B. Role of HSP70i in regulation of biomaterial-induced activation of human monocytes-derived macrophages in culture. J Mater Sci Mater Med. 2001;12:97–106.CrossRefPubMed
18.
Xu H, Lai W, Zhang Y, et al. Tumor-associated macrophage-derived IL-6 and IL-8 enhance invasive activity of LoVo cells induced by PRL-3 in a KCNN4 channel-dependent manner. BMC Cancer. 2014;14:330.CrossRefPubMedPubMedCentral
19.
Teofoli P, Lotti T. Cytokines, fibrinolysis and vasculitis. Int Angiol. 1995;14:125–9.PubMed
20.
Jarvis JN, Petty HR, Tang Y, et al. Evidence for chronic, peripheral activation of neutrophils in polyarticular juvenile rheumatoid arthritis. Arthritis Res Ther. 2006;8:R154.CrossRefPubMedPubMedCentral
21.
Grom AA, Hirsch R. T-cell and T-cell receptor abnormalities in the immunopathogenesis of juvenile rheumatoid arthritis. Curr Opin Rheumatol. 2000;12:420–4.CrossRefPubMed
22.
Jiang K, Sun X, Chen Y, Shen Y, Jarvis JN. RNA sequencing from human neutrophils reveals distinct transcriptional differences associated with chronic inflammatory states. BMC Med Genomics. 2015;8:55.CrossRefPubMedPubMedCentral
23.
Pohlers D, Beyer A, Koczan D, et al. Constitutive upregulation of the transforming growth factor-beta pathway in rheumatoid arthritis synovial fibroblasts. Arthritis Res Ther. 2007;9:R59.CrossRefPubMedPubMedCentral
24.
Knowlton N, Jiang K, Frank MB, et al. The meaning of clinical remission in polyarticular juvenile idiopathic arthritis: gene expression profiling in peripheral blood mononuclear cells identifies distinct disease states. Arthritis Rheum. 2009;60:892–900.CrossRefPubMedPubMedCentral
25.
Jarvis JN, Jiang K, Frank MB, et al. Gene expression profiling in neutrophils from children with polyarticular juvenile idiopathic arthritis. Arthritis Rheum. 2009;60:1488–95.CrossRefPubMedPubMedCentral
26.
Beauvillain C, Delneste Y, Scotet M, et al. Neutrophils efficiently cross-prime naive T cells in vivo. Blood. 2007;110:2965–73.CrossRefPubMed
27.
Puga I, Cols M, Barra CM, et al. B cell-helper neutrophils stimulate the diversification and production of immunoglobulin in the marginal zone of the spleen. Nat Immunol. 2012;13:170–80.CrossRef
28.
Sun J, Dodd H, Moser EK, Sharma R, Braciale TJ. CD4+ T cell help and innate-derived IL-27 induce Blimp-1-dependent IL-10 production by antiviral CTLs. Nat Immunol. 2011;12:327–34.CrossRefPubMedPubMedCentral
29.
Hock BD, Taylor KG, Cross NB, et al. Effect of activated human polymorphonuclear leucocytes on T lymphocyte proliferation and viability. Immunology. 2012;137:249–58.CrossRefPubMedPubMedCentral
30.
Harwood NE, Barral P, Batista FD. Neutrophils—the unexpected helpers of B-cell activation. EMBO Rep. 2012;13:93–4.CrossRefPubMedPubMedCentral
31.
Odobasic D, Kitching AR, Yang Y, et al. Neutrophil myeloperoxidase regulates T-cell-driven tissue inflammation in mice by inhibiting dendritic cell function. Blood. 2013;121:4195–204.CrossRefPubMed
32.
Jiang K, Frank M, Chen Y, Osban J, Jarvis JN. Genomic characterization of remission in juvenile idiopathic arthritis. Arthritis Res Ther. 2013;15:R100.CrossRefPubMedPubMedCentral
33.
Jiang K, Zhu L, Buck MJ, et al. Disease-associated single-nucleotide polymorphisms from noncoding regions in juvenile idiopathic arthritis are located within or adjacent to functional genomic elements of human neutrophils and CD4+ T cells. Arthritis Rheumatol. 2015;67:1966–77.CrossRefPubMedPubMedCentral
34.
Gibson G, Powell JE, Marigorta UM. Expression quantitative trait locus analysis for translational medicine. Genome Med. 2015;7:60.CrossRefPubMedPubMedCentral
35.
Yasuda K, Richez C, Uccellini MB, et al. Requirement for DNA CpG content in TLR9-dependent dendritic cell activation induced by DNA-containing immune complexes. J Immunol. 2009;183:3109–17.CrossRefPubMedPubMedCentral
36.
Kline JN. Eat dirt: CpG DNA and immunomodulation of asthma. Proc Am Thorac Soc. 2007;4:283–8.CrossRefPubMedPubMedCentral
37.
Klinman DM. Adjuvant activity of CpG oligodeoxynucleotides. Int Rev Immunol. 2006;25:135–54.CrossRefPubMed
38.
Rosa R, Melisi D, Damiano V, et al. Toll-like receptor 9 agonist IMO cooperates with cetuximab in K-ras mutant colorectal and pancreatic cancers. Clin Cancer Res. 2011;17:6531–41.CrossRefPubMed
39.
Berger R, Fiegl H, Goebel G, et al. Toll-like receptor 9 expression in breast and ovarian cancer is associated with poorly differentiated tumors. Cancer Sci. 2010;101:1059–66.CrossRefPubMedPubMedCentral
40.
Vaisanen MR, Vaisanen T, Jukkola-Vuorinen A, et al. Expression of toll-like receptor-9 is increased in poorly differentiated prostate tumors. Prostate. 2010;70:817–24.CrossRefPubMed
41.
Ronkainen H, Hirvikoski P, Kauppila S, et al. Absent Toll-like receptor-9 expression predicts poor prognosis in renal cell carcinoma. J Exp Clin Cancer Res. 2011;30:84.CrossRefPubMedPubMedCentral
42.
Takala H, Kauppila JH, Soini Y, et al. Toll-like receptor 9 is a novel biomarker for esophageal squamous cell dysplasia and squamous cell carcinoma progression. J Innate Immun. 2011;3:631–8.CrossRefPubMed
43.
Katz SJ, Russell AS. Re-evaluation of antimalarials in treating rheumatic diseases: re-appreciation and insights into new mechanisms of action. Curr Opin Rheumatol. 2011;23:278–81.CrossRefPubMed
44.
Brewer EJ, Giannini EH, Kuzmina N, Alekseev L. Penicillamine and hydroxychloroquine in the treatment of severe juvenile rheumatoid arthritis. Results of the USA-USSR double-blind placebo-controlled trial. N Engl J Med. 1986;314:1269–76.CrossRefPubMed
45.
Stroncek DF, Clay ME, Smith J, et al. Composition of peripheral blood progenitor cell components collected from healthy donors. Transfusion. 1997;37:411–7.CrossRefPubMed
46.
Field LA, Jordan RM, Hadix JA, et al. Functional identity of genes detectable in expression profiling assays following globin mRNA reduction of peripheral blood samples. Clin Biochem. 2007;40:499–502.CrossRefPubMed
47.
Weinstein JS, Lezon-Geyda K, Maksimova Y, et al. Global transcriptome analysis and enhancer landscape of human primary T follicular helper and T effector lymphocytes. Blood. 2014;124:3719–29.CrossRefPubMedPubMedCentral
48.
Lin H, Joehanes R, Pilling LC, et al. Whole blood gene expression and interleukin-6 levels. Genomics. 2014;104:490–5.CrossRefPubMedPubMedCentral
49.
Powell JE, Henders AK, McRae AF, et al. Genetic control of gene expression in whole blood and lymphoblastoid cell lines is largely independent. Genome Res. 2012;22:456–66.CrossRefPubMedPubMedCentral
50.
Xiao W, Mindrinos MN, Seok J, et al. A genomic storm in critically injured humans. J Exp Med. 2011;208:2581–90.CrossRefPubMedPubMedCentral