Gene expression in juvenile arthritis and spondyloarthropathy: pro-angiogenic ELR+ chemokine genes relate to course of arthritis

Regulation of immune responses in primary biliary cholangitis: a transcriptomic analysis of peripheral immune cells

BACKGROUND AIMS

In patients with primary biliary cholangitis (PBC), the serum liver biochemistry measured during treatment with ursodeoxycholic acid-the UDCA response-accurately predicts long-term outcome. Molecular characterization of patients stratified by UDCA response can improve biological understanding of the high-risk disease, thereby helping to identify alternative approaches to disease-modifying therapy. In this study, we sought to characterize the immunobiology of the UDCA response using transcriptional profiling of peripheral blood mononuclear cell subsets.

METHODS

We performed bulk RNA-sequencing of monocytes and TH1, TH17, TREG, and B cells isolated from the peripheral blood of 15 PBC patients with adequate UDCA response ("responders"), 16 PBC patients with inadequate UDCA response ("nonresponders"), and 15 matched controls. We used the Weighted Gene Co-expression Network Analysis to identify networks of co-expressed genes ("modules") associated with response status and the most highly connected genes ("hub genes") within them. Finally, we performed a Multi-Omics Factor Analysis of the Weighted Gene Co-expression Network Analysis modules to identify the principal axes of biological variation ("latent factors") across all peripheral blood mononuclear cell subsets.

RESULTS

Using the Weighted Gene Co-expression Network Analysis, we identified modules associated with response and/or disease status (q<0.05) in each peripheral blood mononuclear cell subset. Hub genes and functional annotations suggested that monocytes are proinflammatory in nonresponders, but antiinflammatory in responders; TH1 and TH17 cells are activated in all PBC cases but better regulated in responders; and TREG cells are activated-but also kept in check-in responders. Using the Multi-Omics Factor Analysis, we found that antiinflammatory activity in monocytes, regulation of TH1 cells, and activation of TREG cells are interrelated and more prominent in responders.

CONCLUSIONS

We provide evidence that adaptive immune responses are better regulated in patients with PBC with adequate UDCA response.

Profiling the peripheral immune response to ex vivo TNF stimulation in untreated juvenile idiopathic arthritis using single cell RNA sequencing

BACKGROUND

Juvenile Idiopathic Arthritis (JIA) is an autoimmune disease with a heterogenous clinical presentation and unpredictable response to available therapies. This personalized transcriptomics study sought proof-of-concept for single-cell RNA sequencing to characterize patient-specific immune profiles.

METHODS

Whole blood samples from six untreated children, newly diagnosed with JIA, and two healthy controls were cultured for 24 h with or without ex vivo TNF stimulation and subjected to scRNAseq to examine cellular populations and transcript expression in PBMCs. A novel analytical pipeline, scPool, was developed wherein cells are first pooled into pseudocells prior to expression analysis, facilitating variance partitioning of the effects of TNF stimulus, JIA disease status, and individual donor.

RESULTS

Seventeen robust immune cell-types were identified, the abundance of which was significantly affected by TNF stimulus, which resulted in notable elevation of memory CD8 + T-cells and NK56 cells, but down-regulation of naïve B-cell proportions. Memory CD8 + and CD4 + T-cells were also both reduced in the JIA cases relative to two controls. Significant differential expression responses to TNF stimulus were also characterized, with monocytes showing more transcriptional shifts than T-lymphocyte subsets, while the B-cell response was more limited. We also show that donor variability exceeds the small degree of possible intrinsic differentiation between JIA and control profiles. An incidental finding of interest was association of HLA-DQA2 and HLA-DRB5 expression with JIA status.

CONCLUSIONS

These results support the development of personalized immune-profiling combined with ex-vivo immune stimulation for evaluation of patient-specific modes of immune cell activity in autoimmune rheumatic disease.

A Cross-Tissue Transcriptome-Wide Association Study Identifies Novel Susceptibility Genes for Juvenile Idiopathic Arthritis in Asia and Europe

Background

Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease in children, and its pathogenesis is still unclear. Genome-wide association studies (GWASs) of JIA have identified hundreds of risk factors, but few of them implicated specific biological mechanisms.

Methods

A cross-tissue transcriptome-wide association study (TWAS) was performed with the functional summary-based imputation software (FUSION) tool based on GWAS summary datasets (898 JIA patients and 346,102 controls from BioBank Japan (BBJ)/FinnGen). The gene expression reference weights of skeletal muscle and the whole blood were obtained from the Genotype-Tissue Expression (GTExv8) project. JIA-related genes identified by TWAS findings genes were further compared with the differentially expressed genes (DEGs) identified by the mRNA expression profile of JIA from the Gene Expression Omnibus (GEO) database (accession number: GSE1402). Last, candidate genes were analyzed using functional enrichment and annotation analysis by Metascape to examine JIA-related gene sets.

Results

The TWAS identified 535 significant genes with P < 0.05 and contains 350 for Asian and 195 for European (including 10 genes both expressed in Asian and European), such as CDC16 (P = 1.72E-03) and PSMD5-AS1 (P = 3.65E-02). Eight overlapping genes were identified based on TWAS results and DEGs of JIA patients, such as SIRPB1 (P_TWAS = 4.21E-03, P_DEG = 1.50E-04) and FRAT2 (P_TWAS = 2.82E-02, P_DEG = 1.43E-02). Pathway enrichment analysis of TWAS identified 183 pathways such as cytokine signaling in the immune system and cell adhesion molecules. By integrating the results of DEGs pathway and process enrichment analyses, 19 terms were identified such as positive regulation of T-cell activation.

Conclusion

By conducting two populations TWAS, we identified a group of JIA-associated genes and pathways, which may provide novel clues to uncover the pathogenesis of JIA.

LAT1-specific inhibitor ameliorates severe autoimmune arthritis in SKG mouse

L-type amino acid transporter 1 (LAT1, slc7a5) supplies large neutral amino acids to highly proliferative cells. LAT1 is an attractive therapeutic target for treating overactive T cell-mediated immune disorders due to its high expression in activated T cells, but not in resting T cells. Here, we demonstrate that LAT1 plays a crucial role in T helper (Th) 17-mediated autoimmune arthritis in SKG mice, an animal model of human rheumatoid arthritis (RA). Administration of JPH203, a LAT1-specific inhibitor, suppressed mannan-induced joint swelling, synoviocyte proliferation and inflammatory cell infiltration in SKG mice. A diminished metabolic reprogramming, including a decrease in oxidative phosphorylation that regulates Hif-1α expression and subsequent control of glycolysis enzymes, was involved in the downregulation of Th17 differentiation by LAT1 inhibition. Moreover, publicly released database analysis revealed facilitated expression of LAT1 in T cells with cytotoxic features in patients with RA. Our results demonstrate the essential contribution of LAT1 to the development of RA, proposing a potential therapeutic approach targeting amino acid transporters for treating hypersensitive immune diseases.

Prevalence of Inflammatory Pathways Over Immuno-Tolerance in Peripheral Blood Mononuclear Cells of Recent-Onset Type 1 Diabetes

Background

Changes in innate and adaptive immunity occurring in/around pancreatic islets had been observed in peripheral blood mononuclear cells (PBMC) of Caucasian T1D patients by some, but not all researchers. The aim of our study was to investigate whether gene expression patterns of PBMC of the highly admixed Brazilian population could add knowledge about T1D pathogenic mechanisms.

Methods

We assessed global gene expression in PBMC from two groups matched for age, sex and BMI: 20 patients with recent-onset T1D (≤ 6 months from diagnosis, in a time when the autoimmune process is still highly active), testing positive for one or more islet autoantibodies and 20 islet autoantibody-negative healthy controls.

Results

We identified 474 differentially expressed genes between groups. The most expressed genes in T1D group favored host defense, inflammatory and anti-bacterial/antiviral effects (LFT, DEFA4, DEFA1, CTSG, KCNMA1) and cell cycle progression. Several of the downregulated genes in T1D target cellular repair, control of inflammation and immune tolerance. They were related to T helper 2 pathway, induction of FOXP3 expression (AREG) and immune tolerance (SMAD6). SMAD6 expression correlated negatively with islet ZnT8 antibody. The expression of PDE12, that offers resistance to viral pathogens was decreased and negatively related to ZnT8A and GADA levels. The increased expression of long non coding RNAs MALAT1 and NEAT1, related to inflammatory mediators, autoimmune diseases and innate immune response against viral infections reinforced these data.

Conclusions

Our analysis suggested the activation of cell development, anti-infectious and inflammatory pathways, indicating immune activation, whereas immune-regulatory pathways were downregulated in PBMC from recent-onset T1D patients with a differential genetic profile.

Immunopathophysiology of Juvenile Spondyloarthritis (jSpA): The "Out of the Box" View on Epigenetics, Neuroendocrine Pathways and Role of the Macrophage Migration Inhibitory Factor (MIF)

Juvenile spondyloarthritis (jSpA) is a an umbrella term for heterogeneous group of related seronegative inflammatory disorders sharing common symptoms. Although it mainly affects children and adolescents, it often remains active during adulthood. Genetic and environmental factors are involved in its occurrence, although the exact underlying immunopathophysiology remains incompletely elucidated. Accumulated evidence suggests that, in affected patients, subclinical gut inflammation caused by intestinal dysbiosis, is pivotal to the future development of synovial-entheseal complex inflammation. While the predominant role of IL17/23 axis, TNF-α, and IL-7 in the pathophysiology of SpA, including jSpA, is firmly established, the role of the cytokine macrophage migration inhibitory factor (MIF) is generally overlooked. The purpose of this review is to discuss and emphasize the role of epigenetics, neuroendocrine pathways and the hypothalamic-pituitary (HPA) axis, and to propose a novel hypothesis of the role of decreased NLRP3 gene expression and possibly MIF in the early phases of jSpA development. The decreased NLRP3 gene expression in the latter, due to hypomethylation of promotor site, is (one of) the cause for inflammasome malfunction leading to gut dysbiosis observed in patients with early jSpA. In addition, we highlight the role of MIF in the complex innate, adaptive cellular and main effector cytokine network, Finally, since treatment of advanced bone pathology in SpA remains an unmet clinical need, I suggest possible new drug targets with the aim to ultimately improve treatment efficacy and long-term outcome of jSpA patients.

Vitamin D3 receptor polymorphisms regulate T cells and T cell-dependent inflammatory diseases

It has proven difficult to identify the underlying genes in complex autoimmune diseases. Here, we use forward genetics to identify polymorphisms in the vitamin D receptor gene (Vdr) promoter, controlling Vdr expression and T cell activation. We isolated these polymorphisms in a congenic mouse line, allowing us to study the immunomodulatory properties of VDR in a physiological context. Congenic mice overexpressed VDR selectively in T cells, and thus did not suffer from calcemic effects. VDR overexpression resulted in an enhanced antigen-specific T cell response and more severe autoimmune phenotypes. In contrast, vitamin D3-deficiency inhibited T cell responses and protected mice from developing autoimmune arthritis. Our observations are likely translatable to humans, as Vdr is overexpressed in rheumatic joints. Genetic control of VDR availability codetermines the proinflammatory behavior of T cells, suggesting that increased presence of VDR at the site of inflammation might limit the antiinflammatory properties of its ligand.

Immunomics in Pediatric Rheumatic Diseases

The inherent complexity in the immune landscape of pediatric rheumatic disease necessitates a holistic system approach. Uncertainty in the mechanistic workings and etiological driving forces presents difficulty in personalized treatments. The development and progression of immunomics are well suited to deal with this complexity. Immunomics encompasses a spectrum of biological processes that entail genomics, transcriptomics, epigenomics, proteomics, and cytomics. In this review, we will discuss how various high dimensional technologies in immunomics have helped to grow a wealth of data that provide salient clues and biological insights into the pathogenesis of autoimmunity. Interfaced with critical unresolved clinical questions and unmet medical needs, these platforms have helped to identify candidate immune targets, refine patient stratification, and understand treatment response or resistance. Yet the unprecedented growth in data has presented both opportunities and challenges. Researchers are now facing huge heterogeneous data sets from different origins that need to be integrated and exploited for further data mining. We believe that the utilization and integration of these platforms will help unravel the complexities and expedite both discovery and validation of clinical targets.

An immunoregulatory and tissue-residency program modulated by c-MAF in human TH17 cells

Different types of effector and memory T lymphocytes are induced and maintained in protective or pathological immune responses. Here we characterized two human CD4⁺ T_H17 helper cell subsets that, in the recently activated state, could be distinguished on the basis of their expression of the anti-inflammatory cytokine IL-10. IL-10⁺ T_H17 cells upregulated a variety of genes encoding immunoregulatory molecules, as well as genes whose expression is characteristic of tissue-resident T cells. In contrast, IL-10^- T_H17 cells maintained a pro-inflammatory gene-expression profile and upregulated the expression of homing receptors that guide recirculation from tissues to blood. Expression of the transcription factor c-MAF was selectively upregulated in IL-10⁺ T_H17 cells, and it was bound to a large set of enhancer-like regions and modulated the immunoregulatory and tissue-residency program. Our results identify c-MAF as a relevant factor that drives two highly divergent post-activation fates of human T_H17 cells and provide a framework with which to investigate the role of these cells in physiology and immunopathology.

Comparative analysis of signaling pathways in peripheral blood from patients with Kashin-Beck disease and osteoarthritis

The aim of the present study was to investigate the early diagnostic biomarkers of Kashin-Beck disease (KBD), and to compare the common signaling pathways of peripheral mononuclear cells between patients with KBD and those with osteoarthritis (OA). A total of 20 and 12 peripheral blood samples were separately collected from KBD patients and normal control subjects, respectively, in an endemic area according to the diagnosis criteria. Total RNAs were extracted and gene expression levels were determined using an Agilent whole genome expression microarrays. The gene expression data of OA were obtained from GEO published database. Significant different pathways between KBD and OA were analyzed using Ingenuity Pathway Analysis software. A total of 82 differentially expressed genes, 51 significant different signaling pathways and five significant biological functions were identified in KBD patient samples, while 89, 50 and five significantly different genes, pathways and functions were identified in OA. Nine common significant pathways and five common differentially expressed genes were identified between the KBD and OA. Nine common significant pathways and five common differentially expressed genes were found between the two diseases. The present results suggest that there are similarities in vascular microcirculation, immunoreactions and cell apoptosis between KBD and OA, which may contribute to the early diagnosis and pathogenetic study of KBD.

Integrative analysis for identification of shared markers from various functional cells/tissues for rheumatoid arthritis

Rheumatoid arthritis (RA) is a systemic autoimmune disease. So far, it is unclear whether there exist common RA-related genes shared in different tissues/cells. In this study, we conducted an integrative analysis on multiple datasets to identify potential shared genes that are significant in multiple tissues/cells for RA. Seven microarray gene expression datasets representing various RA-related tissues/cells were downloaded from the Gene Expression Omnibus (GEO). Statistical analyses, testing both marginal and joint effects, were conducted to identify significant genes shared in various samples. Followed-up analyses were conducted on functional annotation clustering analysis, protein-protein interaction (PPI) analysis, gene-based association analysis, and ELISA validation analysis in in-house samples. We identified 18 shared significant genes, which were mainly involved in the immune response and chemokine signaling pathway. Among the 18 genes, eight genes (PPBP, PF4, HLA-F, S100A8, RNASEH2A, P2RY6, JAG2, and PCBP1) interact with known RA genes. Two genes (HLA-F and PCBP1) are significant in gene-based association analysis (P = 1.03E-31, P = 1.30E-2, respectively). Additionally, PCBP1 also showed differential protein expression levels in in-house case-control plasma samples (P = 2.60E-2). This study represented the first effort to identify shared RA markers from different functional cells or tissues. The results suggested that one of the shared genes, i.e., PCBP1, is a promising biomarker for RA.

Integrated Analyses of Gene Expression Profiles Digs out Common Markers for Rheumatic Diseases

OBJECTIVE

Rheumatic diseases have some common symptoms. Extensive gene expression studies, accumulated thus far, have successfully identified signature molecules for each rheumatic disease, individually. However, whether there exist shared factors across rheumatic diseases has yet to be tested.

METHODS

We collected and utilized 6 public microarray datasets covering 4 types of representative rheumatic diseases including rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis, and osteoarthritis. Then we detected overlaps of differentially expressed genes across datasets and performed a meta-analysis aiming at identifying common differentially expressed genes that discriminate between pathological cases and normal controls. To further gain insights into the functions of the identified common differentially expressed genes, we conducted gene ontology enrichment analysis and protein-protein interaction analysis.

RESULTS

We identified a total of eight differentially expressed genes (TNFSF10, CX3CR1, LY96, TLR5, TXN, TIA1, PRKCH, PRF1), each associated with at least 3 of the 4 studied rheumatic diseases. Meta-analysis warranted the significance of the eight genes and highlighted the general significance of four genes (CX3CR1, LY96, TLR5, and PRF1). Protein-protein interaction and gene ontology enrichment analyses indicated that the eight genes interact with each other to exert functions related to immune response and immune regulation.

CONCLUSION

The findings support that there exist common factors underlying rheumatic diseases. For rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis and osteoarthritis diseases, those common factors include TNFSF10, CX3CR1, LY96, TLR5, TXN, TIA1, PRKCH, and PRF1. In-depth studies on these common factors may provide keys to understanding the pathogenesis and developing intervention strategies for rheumatic diseases.

Gene expression signature in endemic osteoarthritis by microarray analysis

Kashin-Beck Disease (KBD) is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs) from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR) algorithm and support vector machine (SVM) algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD.

Genetics of juvenile idiopathic arthritis: new tools bring new approaches

PURPOSE OF REVIEW

In juvenile idiopathic arthritis (JIA), there are now more than 25 regions represented by single nucleotide polymorphisms that show strong genetic associations. The causal variants and corresponding functions have not yet been defined for the majority of these regions. Here, we review current JIA association findings and the recent progress in the annotation of noncoding portion of the human genome as well as the new technologies necessary to apply this knowledge to JIA association findings.

RECENT FINDINGS

An international collaboration was able to amass sufficient numbers of JIA and control samples to identify significantly robust genetic associations for JIA. The Encyclopedia of DNA Elements project and the National Institutes of Health (NIH) Roadmap Epigenetics Program have now annotated more than 80% of the noncoding genome, important in understanding the impact of risk loci, the majority of which fall outside of protein coding regions. Recent technological advances in high throughput sequencing, chromatin structure determination, transcription factor and enhancer binding site mapping and genome editing will likely provide a basis for understanding JIA genetic risk.

SUMMARY

Understanding the role of genetic variation in the cause of JIA will provide insight for disease mechanism and may explain disease heterogeneity between JIA subtypes and between autoimmune diseases in general.

The biologic basis of clinical heterogeneity in juvenile idiopathic arthritis

Objective

Childhood arthritis encompasses a heterogeneous family of diseases. Significant variation in clinical presentation remains despite consensus-driven diagnostic classifications. Developments in data analysis provide powerful tools for interrogating large heterogeneous data sets. We report a novel approach to integrating biologic and clinical data toward a new classification for childhood arthritis, using computational biology for data-driven pattern recognition.

Methods

Probabilistic principal components analysis was used to transform a large set of data into 4 interpretable indicators or composite variables on which patients were grouped by cluster analysis. Sensitivity analysis was conducted to determine key variables in determining indicators and cluster assignment. Results were validated against an independent validation cohort.

Results

Meaningful biologic and clinical characteristics, including levels of proinflammatory cytokines and measures of disease activity, defined axes/indicators that identified homogeneous patient subgroups by cluster analysis. The new patient classifications resolved major differences between patient subpopulations better than International League of Associations for Rheumatology subtypes. Fourteen variables were identified by sensitivity analysis to crucially determine indicators and clusters. This new schema was conserved in an independent validation cohort.

Conclusion

Data-driven unsupervised machine learning is a powerful approach for interrogating clinical and biologic data toward disease classification, providing insight into the biology underlying clinical heterogeneity in childhood arthritis. Our analytical framework enabled the recovery of unique patterns from small cohorts and addresses a major challenge, patient numbers, in studying rare diseases.

Aberrant expression of shared master-key genes contributes to the immunopathogenesis in patients with juvenile spondyloarthritis

Association of juvenile spondyloarthritis (jSpA) with the HLA-B27 genotype is well established, but there is little knowledge of other genetic factors with a role in the development of the disease. To date, only a few studies have tried to find those associated genes by obtaining expression profiles, but with inconsistent results due to various patient selection criteria and methodology. The aim of the present study was to identify and confirm gene signatures and novel biomarkers in highly homogeneous cohorts of untreated and treated patients diagnosed with jSpA and other forms of juvenile idiopathic arthritis (JIA) according to ILAR criteria. For the purposes of the research, total RNA was isolated from whole blood of 45 children with jSpA and known HLA genotype, 11 children with oligo- and polyarticular forms of JIA, as well as 12 age and sex matched control participants without diagnosis of inflammatory disease. DNA microarray gene expression was performed in 11 patients with jSpA and in four healthy controls, along with bioinformatical analysis of retrieved data. Carefully selected differentially expressed genes where analyzed by qRT-PCR in all participants of the study. Microarray results and bioinformatical analysis revealed 745 differentially expressed genes involved in various inflammatory processes, while qRT-PCR analysis of selected genes confirmed data universality and specificity of expression profiles in jSpA patients. The present study indicates that jSpA could be a polygenic disease with a possible malfunction in antigen recognition and activation of immunological response, migration of inflammatory cells and regulation of the immune system. Among genes involved in these processes TLR4, NLRP3, CXCR4 and PTPN12 showed almost consistent expression in study patients diagnosed with jSpA. Those genes and their products could therefore potentially be used as novel biomarkers, possibly predictive of disease prognosis and response to therapy, or even as a target for new therapeutic approaches.

Network analysis identifies protein clusters of functional importance in juvenile idiopathic arthritis

Introduction

Our objective was to utilise network analysis to identify protein clusters of greatest potential functional relevance in the pathogenesis of oligoarticular and rheumatoid factor negative (RF-ve) polyarticular juvenile idiopathic arthritis (JIA).

Methods

JIA genetic association data were used to build an interactome network model in BioGRID 3.2.99. The top 10% of this protein:protein JIA Interactome was used to generate a minimal essential network (MEN). Reactome FI Cytoscape 2.83 Plugin and the Disease Association Protein-Protein Link Evaluator (Dapple) algorithm were used to assess the functionality of the biological pathways within the MEN and to statistically rank the proteins. JIA gene expression data were integrated with the MEN and clusters of functionally important proteins derived using MCODE.

Results

A JIA interactome of 2,479 proteins was built from 348 JIA associated genes. The MEN, representing the most functionally related components of the network, comprised of seven clusters, with distinct functional characteristics. Four gene expression datasets from peripheral blood mononuclear cells (PBMC), neutrophils and synovial fluid monocytes, were mapped onto the MEN and a list of genes enriched for functional significance identified. This analysis revealed the genes of greatest potential functional importance to be PTPN2 and STAT1 for oligoarticular JIA and KSR1 for RF-ve polyarticular JIA. Clusters of 23 and 14 related proteins were derived for oligoarticular and RF-ve polyarticular JIA respectively.

Conclusions

This first report of the application of network biology to JIA, integrating genetic association findings and gene expression data, has prioritised protein clusters for functional validation and identified new pathways for targeted pharmacological intervention.

Integrative analyses for functional mechanisms underlying associations for rheumatoid arthritis

OBJECTIVE

Extensive association analyses including genome-wide association studies (GWAS) and powerful metaanalysis studies have identified a long list of loci associated with rheumatoid arthritis (RA) in very large populations, but most of them established statistical associations of genetic markers and RA only at the DNA level, without supporting evidence of functional relevance. Our study serves as a trial to detect the functional mechanisms underlying associations for RA by searching publicly available datasets and results.

METHODS

Based on publicly available datasets and results, we performed integrative analyses (gene relationships across implicated loci analysis, differential gene expression analysis, and functional annotation clustering analysis) and combined them with the expression quantitative trait locus (eQTL) results to dissect functional mechanisms underlying the associations for RA.

RESULTS

By searching 2 GWAS, Integrator and PheGenI, we selected 98 RA association results (p < 10(-5)). Among these associations, we found that 8 single-nucleotide polymorphisms (SNP; rs1600249, rs2736340, rs3093023, rs3093024, rs4810485, rs615672, rs660895, and rs9272219) serve as cis-effect regulators of the corresponding eQTL genes (BLK and CD4 in non-HLA region; CCR6, HLA-DQA1, and HLA-DQB1 in HLA region) that also were differentially expressed in RA-related cell groups. These 5 genes are closely related with immune response in function.

CONCLUSION

Our results showed the functional mechanisms underlying the associations of 8 SNP and the corresponding genes. This study is an example of mining publicly available datasets and results in validation of significant disease-association results. Using public data resources for integrative analyses may provide insights into the molecular genetic mechanisms underlying human diseases.

Common and specific signatures of gene expression and protein-protein interactions in autoimmune diseases

The aim of this study is to understand intracellular regulatory mechanisms in peripheral blood mononuclear cells (PBMCs), which are either common to many autoimmune diseases or specific to some of them. We incorporated large-scale data such as protein-protein interactions, gene expression and demographical information of hundreds of patients and healthy subjects, related to six autoimmune diseases with available large-scale gene expression measurements: multiple sclerosis (MS), systemic lupus erythematosus (SLE), juvenile rheumatoid arthritis (JRA), Crohn's disease (CD), ulcerative colitis (UC) and type 1 diabetes (T1D). These data were analyzed concurrently by statistical and systems biology approaches tailored for this purpose. We found that chemokines such as CXCL1-3, 5, 6 and the interleukin (IL) IL8 tend to be differentially expressed in PBMCs of patients with the analyzed autoimmune diseases. In addition, the anti-apoptotic gene BCL3, interferon-γ (IFNG), and the vitamin D receptor (VDR) gene physically interact with significantly many genes that tend to be differentially expressed in PBMCs of patients with the analyzed autoimmune diseases. In general, similar cellular processes tend to be differentially expressed in PBMC in the analyzed autoimmune diseases. Specifically, the cellular processes related to cell proliferation (for example, epidermal growth factor, platelet-derived growth factor, nuclear factor-κB, Wnt/β-catenin signaling, stress-activated protein kinase c-Jun NH2-terminal kinase), inflammatory response (for example, interleukins IL2 and IL6, the cytokine granulocyte-macrophage colony-stimulating factor and the B-cell receptor), general signaling cascades (for example, mitogen-activated protein kinase, extracellular signal-regulated kinase, p38 and TRK) and apoptosis are activated in most of the analyzed autoimmune diseases. However, our results suggest that in each of the analyzed diseases, apoptosis and chemotaxis are activated via different subsignaling pathways. Analyses of the expression levels of dozens of genes and the protein-protein interactions among them demonstrated that CD and UC have relatively similar gene expression signatures, whereas the gene expression signatures of T1D and JRA relatively differ from the signatures of the other autoimmune diseases. These diseases are the only ones activated via the Fcɛ pathway. The relevant genes and pathways reported in this study are discussed at length, and may be helpful in the diagnoses and understanding of autoimmunity and/or specific autoimmune diseases.

Correlation analyses of clinical and molecular findings identify candidate biological pathways in systemic juvenile idiopathic arthritis

BACKGROUND

Clinicians have long appreciated the distinct phenotype of systemic juvenile idiopathic arthritis (SJIA) compared to polyarticular juvenile idiopathic arthritis (POLY). We hypothesized that gene expression profiles of peripheral blood mononuclear cells (PBMC) from children with each disease would reveal distinct biological pathways when analyzed for significant associations with elevations in two markers of JIA activity, erythrocyte sedimentation rate (ESR) and number of affected joints (joint count, JC).

METHODS

PBMC RNA from SJIA and POLY patients was profiled by kinetic PCR to analyze expression of 181 genes, selected for relevance to immune response pathways. Pearson correlation and Student's t-test analyses were performed to identify transcripts significantly associated with clinical parameters (ESR and JC) in SJIA or POLY samples. These transcripts were used to find related biological pathways.

RESULTS

Combining Pearson and t-test analyses, we found 91 ESR-related and 92 JC-related genes in SJIA. For POLY, 20 ESR-related and 0 JC-related genes were found. Using Ingenuity Systems Pathways Analysis, we identified SJIA ESR-related and JC-related pathways. The two sets of pathways are strongly correlated. In contrast, there is a weaker correlation between SJIA and POLY ESR-related pathways. Notably, distinct biological processes were found to correlate with JC in samples from the earlier systemic plus arthritic phase (SAF) of SJIA compared to samples from the later arthritis-predominant phase (AF). Within the SJIA SAF group, IL-10 expression was related to JC, whereas lack of IL-4 appeared to characterize the chronic arthritis (AF) subgroup.

CONCLUSIONS

The strong correlation between pathways implicated in elevations of both ESR and JC in SJIA argues that the systemic and arthritic components of the disease are related mechanistically. Inflammatory pathways in SJIA are distinct from those in POLY course JIA, consistent with differences in clinically appreciated target organs. The limited number of ESR-related SJIA genes that also are associated with elevations of ESR in POLY implies that the SJIA associations are specific for SJIA, at least to some degree. The distinct pathways associated with arthritis in early and late SJIA raise the possibility that different immunobiology underlies arthritis over the course of SJIA.

Insights into the pathogenesis of axial spondyloarthropathy from network and pathway analysis

Background

Complex chronic diseases are usually not caused by changes in a single causal gene but by an unbalanced regulating network resulting from the dysfunctions of multiple genes or their products. Therefore, network based systems approach can be helpful for the identification of candidate genes related to complex diseases and their relationships. Axial spondyloarthropathy (SpA) is a group of chronic inflammatory joint diseases that mainly affect the spine and the sacroiliac joints. The pathogenesis of SpA remains largely unknown.

Results

In this paper, we conducted a network study of the pathogenesis of SpA. We integrated data related to SpA, from the OMIM database, proteomics and microarray experiments of SpA, to prioritize SpA candidate disease genes in the context of human protein interactome. Based on the top ranked SpA related genes, we constructed a SpA specific PPI network, identified potential pathways associated with SpA, and finally sketched an overview of biological processes involved in the development of SpA.

Conclusions

The protein-protein interaction (PPI) network and pathways reflect the link between the two pathological processes of SpA, i.e., immune mediated inflammation, as well as imbalanced bone modelling caused new boneformation and bone loss. We found that some known disease causative genes, such as TNFand ILs, play pivotal roles in this interaction.

Synovial fluid mononuclear cell gene expression profiling suggests dysregulation of innate immune genes in enthesitis-related arthritis patients

OBJECTIVE

Microarray studies have provided insight into the pathogenesis of systemic JIA and have opened new avenues for therapy. Data on the pathogenesis of the enthesitis-related arthritis (ERA) category of JIA are limited, thus we studied the expression profile of ERA patients' peripheral blood and SF mononuclear cells (PBMCs and SFMCs, respectively). PBMCs from healthy subjects were used as controls.

METHODS

RNA from PBMCs of ERA patients (n=17) and healthy controls (n=8) and seven ERA SFMCs were converted to labelled cRNA and hybridized to Illumina Human WG-6_v3_BeadChip chips. Expression profiles were analysed using GeneSpring software. Selected genes of interest were validated by real-time PCR.

RESULTS

There was no significant difference in PBMC gene expression of ERA and control groups. However, there was a significant difference between expression profiles of SFMCs and PBMCs of patients with ERA, with 131 genes being overexpressed and 216 being underexpressed in SFMCs. Among genes involved with immune function, cluster of differentiation (CD)1b, CD1d, MHC class II alpha and beta chain, and soluble CD163 were overexpressed, whereas genes related to NK cell function, namely, Granzyme H, killer cell lectin-like receptor subfamily F member 1, killer cell immunoglobulin-like receptor, three domains, long cytoplasmic tail (KIR3DL3), natural killer group 7 (NKG7) and other genes like CD244, CD248 and Fas apoptotic inhibitory molecule 3 (FAIM3) were underexpressed.

CONCLUSION

ERA SFMCs had a distinct gene expression profile from PBMCs and had higher expression of genes associated with antigen presentation, scavenger function, chemotaxis and proteases, whereas genes involved in NK cell function, cell adhesion and inhibitors of apoptosis were underexpressed.

Genome-wide gene expression analysis suggests an important role of suppressed immunity in pathogenesis of Kashin-Beck disease

Objective

To investigate the differences between the gene expression profiles in peripheral blood mononuclear cells (PBMC) from normal controls and patients with Kashin-Beck disease (KBD).

Methods

Twenty KBD patients and 12 normal subjects were selected from a KBD-endemic area and divided into four pairs of KBD vs. control (KBD, n = 5 per pair; control, n = 3 per pair). RNAs were respectively isolated from KBD PBMCs and normal PBMCs. Gene expression profiles were analyzed by oligonucleotide microarray. The gene expression profiles in PBMCs from KBD patients and normal controls were compared and the differentially expressed genes were identified. The obtained microarray data was further confirmed by using quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR).

Results

Approximately 501 genes, corresponding to 2.4% of the total probe transcripts, showed a 2-fold change in differential expression. 19.4% (97 out of 501)of the differentially expressed genes were commonly detected in all the four pairs. Among the 97 differentially expressed genes, 83 genes were up-regulated and 14 genes were down-regulated, compared with those in the normal controls. Some differentially expressed genes were found to be related to functions such as immunity, metabolism, apoptosis, cystoskeleton and cell movement, and extracellular matrix. The validity of our microarray data were supported by the results of qRT-PCR assay.

Conclusion

Differences in the PBMC gene expression profile between the KBD patients and the normal controls exhibited a similar pattern among all the four pairs of microarrays examined, indicating that the suppressed immunity may play an important role in the pathogenesis of KBD.

Gene expression profile of steroid-induced necrosis of femoral head of rats

The key to treating steroid-induced necrosis of femoral heads (SINFH) is early diagnosis. Dramatic improvements in diagnosis could be made if the pathogenesis of SINFH was more fully understood; however, the underlying mechanism of this disease is currently unknown. To explore the potential mechanism of SINFH, we performed gene array analysis on a rat model of the disease and compare the expression profile with that of normal rats. A quantitative RT-PCR and immunohistochemistry (IHC) assays were used to confirm the microarray results. Compared to the control group, 190 genes in the experimental group were differentially expressed, with 52 up-regulated and 138 down-regulated. Of these genes, 102 are known (deposited in GenBank), while 88 of them are unknown. The known genes can be divided into several families according to their biological functions, such as oxidative stress, apoptosis, signal transduction, angiogenesis, extracellular matrix, lipid metabolism, and transcription related genes. The results of quantitative RT-PCR and IHC were consistent with gene chip results. Our findings indicate that many genes involved in diverse signaling pathways were differentially expressed between SINFH rats and normal rats. Furthermore, our findings suggest that the development of SINFH is a complicated and dynamic process affected by multiple factors and signaling pathways and regulated by various genes.

Expression of CYP19 and CYP17 is associated with leg length, weight, and BMI

This study investigates associations between gene expressions of aromatase (CYP19), 17α hydroxylase (CYP17), and estrogen receptors α and β and anthropometric measurements in offspring of the Michigan fish eater cohort. Leg and trunk length, height, weight, and BMI and gene expression in peripheral blood cells were measured in offspring of the Michigan fish eater cohort. The parental generation was followed between 1973 and 1991, and maternal age, height, and weight data were collected. Female offspring were contacted in 2001/2002 and followed up in 2006/2007; offspring information included age, education, reproductive history, smoking, and exercise. Gene expression was standardized against 18S ribosomal ribonucleic acid (18SrRNA) and RNA polymerase II (RNA PolII) expressions. Mixed models assessed the statistical effect of gene expression on anthropometric outcomes, accounting for multiple offspring from one mother. Anthropometric measurements and gene expression were measured in 139 female offspring. The two length and the height measurements were correlated, as were BMI and weight. CYP19 expression was correlated with the other gene expressions and both estrogen receptor expressions were associated. For every 1 unit of ΔC(t) (18SrRNA - CYP19) or ΔC(t) (RNA PolII - CYP19), BMI was increased by 0.9 (P = 0.03) and 0.87 kg/m(2) (P = 0.04), respectively, and weight by 2.35 kg (P = 0.03) and 2.1 kg (P = 0.03), respectively. For every 1 unit of ΔC(t) (18SrRNA - CYP17), leg length was increased by 0.84 cm (P = 0.04). The results suggest that CYP17 gene expression may influence growth during childhood and adolescence while CYP19 may be associated with the concurrent measures of weight and BMI.

Validation of the use of peripheral blood mononuclear cells as surrogate model for skeletal muscle tissue in nutrigenomic studies

Peripheral blood mononuclear cells (PBMCs) offer a significant promise for gene expression analyses as a substitute for tissues that are not easily accessible. The objective of this study was to validate the use of PBMCs for gene expression analysis as a marker of nutritional intervention as an alternative to skeletal muscle tissue (SMT) biopsies. We performed a transcriptome comparison of PBMCs versus SMT after an 8-week supplementation with n-3 polyunsaturated fatty acid (PUFA) in 16 obese and insulin-resistant subjects. Expression levels of 48,803 transcripts were assessed by the Human-6 v3 Expression BeadChips (Illumina, San Diego, CA). In SMT, 36,738 (75%) transcripts were detected, whereas 34,182 (70%) transcripts were detected in PBMCs. Further, 88% (32,341) of these transcripts were coexpressed in both tissues. Importantly, a strong correlation (r = 0.84, p < 0.0001) was observed between transcript expression levels of PBMCs and SMT after n-3 PUFA supplementation. In conclusion, PBMCs express the majority of transcripts expressed in SMT subsequent to n-3 PUFA supplementation and their expression levels are comparable. In the interest of practicalities and cost, these results support the use of PBMCs as a surrogate model for SMT gene expression in nutrigenomic studies. Further research on PBMC and SMT gene expression in response to other nutritional exposures is warranted.

Biologic similarities based on age at onset in oligoarticular and polyarticular subtypes of juvenile idiopathic arthritis

OBJECTIVE

To explore biologic correlates to age at onset in patients with juvenile idiopathic arthritis (JIA) using peripheral blood mononuclear cell (PBMC) gene expression analysis.

METHODS

PBMCs were isolated from 56 healthy controls and 104 patients with recent-onset JIA (39 with persistent oligoarticular JIA, 45 with rheumatoid factor-negative polyarticular JIA, and 20 with systemic JIA). RNA was amplified and labeled using NuGEN Ovation, and gene expression was 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 PBMCs from children with oligoarticular JIA whose disease began before age 6 years (early-onset disease) compared with those whose disease began at or after age 6 years (late-onset disease). In patients with early-onset disease, there was greater expression of genes related to B cells and less expression of genes related to cells of the myeloid lineage. Support vector machine analyses identified samples from patients with early- or late-onset oligoarticular JIA (with 97% accuracy) or from patients with early- or late-onset polyarticular JIA (with 89% accuracy), but not from patients with systemic JIA or healthy controls. Principal components analysis showed that age at onset was the major classifier of samples from patients with oligoarticular JIA and patients with polyarticular JIA.

CONCLUSION

PBMC gene expression analysis reveals biologic differences between patients with early-and late-onset JIA, independent of classification based on the number of joints involved. These data suggest that age at onset may be an important parameter to consider in JIA classification. Furthermore, pathologic mechanisms may vary with age at onset, and understanding these processes may lead to improved treatment of JIA.

Peripheral blood gene expression patterns discriminate among chronic inflammatory diseases and healthy controls and identify novel targets

Background

Chronic inflammatory diseases including inflammatory bowel disease (IBD; Crohn's disease and ulcerative colitis), psoriasis and rheumatoid arthritis (RA) afflict millions of people worldwide, but their pathogenesis is still not well understood.

It is also not well known if distinct changes in gene expression characterize these diseases and if these patterns can discriminate between diseased and control patients and/or stratify the disease. The main focus of our work was the identification of novel markers that overlap among the 3 diseases or discriminate them from each other.

Methods

Diseased (n = 13, n = 15 and n = 12 in IBD, psoriasis and RA respectively) and healthy patients (n = 18) were recruited based on strict inclusion and exclusion criteria; peripheral blood samples were collected by clinicians (30 ml) in Venous Blood Vacuum Collection Tubes containing EDTA and peripheral blood mononuclear cells were separated by Ficoll gradient centrifugation. RNA was extracted using Trizol reagent. Gene expression data was obtained using TaqMan Low Density Array (TLDA) containing 96 genes that were selected by an algorithm and the statistical analyses were performed in Prism by using non-parametric Mann-Whitney U test (P-values < 0.05).

Results

Here we show that using a panel of 96 disease associated genes and measuring mRNA expression levels in peripheral blood derived mononuclear cells; we could identify disease-specific gene panels that separate each disease from healthy controls. In addition, a panel of five genes such as ADM, AQP9, CXCL2, IL10 and NAMPT discriminates between all samples from patients with chronic inflammation and healthy controls. We also found genes that stratify the diseases and separate different subtypes or different states of prognosis in each condition.

Conclusions

These findings and the identification of five universal markers of chronic inflammation suggest that these diseases have a common background in pathomechanism, but still can be separated by peripheral blood gene expression. Importantly, the identified genes can be associated with overlapping biological processes including changed inflammatory response. Gene panels based on such markers can play a major role in the development of personalized medicine, in monitoring disease progression and can lead to the identification of new potential drug targets in chronic inflammation.

Biologic predictors of extension of oligoarticular juvenile idiopathic arthritis as determined from synovial fluid cellular composition and gene expression

Objective

To identify biomarkers in the first synovial fluid (SF) aspirate obtained from children with oligoarticular juvenile idiopathic arthritis (JIA), which could be used to identify children whose disease is likely to extend to a more severe phenotype.

Methods

Patients with recent-onset oligoarticular JIA were identified and grouped according to those whose mild disease persisted (persistent disease) or those whose disease would extend from a mild to more severe phenotype (extended-to-be disease) at 1 year after diagnosis. Flow cytometry was used to delineate differences in the mononuclear cell populations between the first blood sample and first SF aspirate from the same patient and between outcome (persistent versus extended-to-be) groups. Proportions of lymphocytes in the joint were modeled on chemotaxis of lymphocytes to CCL5, using Transwell migration assays. Levels of CCL5 in the SF were quantified by enzyme-linked immunosorbent assay. RNA profiles of SF mononuclear cells were compared between groups using the Affymetrix GeneChip hybridization protocol and hierarchical clustering analyses.

Results

Compared with peripheral blood mononuclear cells, SF mononuclear cells displayed an expansion of CD8+ T cells, reduced proportion of B cells, and expansion of CD16− natural killer cells. The lower CD4:CD8 ratio in the SF was recapitulated in vitro by the observed migration of blood T cells in response to CCL5. Synovial CCL5 levels were higher in children whose disease extended to a more severe phenotype. The CD4:CD8 ratio in the SF was significantly lower in patients with extended-to-be oligoarticular JIA (0.57 compared with 0.90 in the persistent disease group, difference 0.33, 95% confidence interval 0.04–0.62; P = 0.009). Gene expression profiling revealed that 344 genes were >1.5-fold differentially expressed between outcome groups (P < 0.05), and these included genes associated with inflammation and macrophage differentiation, which showed increased levels in patients with extended disease at 1 year, and genes associated with immune regulation, which showed increased levels in patients with persistent disease at 1 year.

Conclusion

Analyses of the proportions of synovial lymphocytes, levels of CCL5, and differential gene expression yielded potential biomarkers with which to predict the likelihood of extension of oligoarticular JIA to a more severe disease phenotype.

Gene expression profiles of disc tissues and peripheral blood mononuclear cells from patients with degenerative discs

The objective of this study was to analyze gene expression profiles of intervertebral disc samples and peripheral blood mononuclear cells (PBMCs) from patients with degenerative discs using Agilent's Human 1A Oligo microarray. RNA samples from disc tissue and PBMCs were obtained from patients with degenerative discs and from subjects in a control group. RNA samples were reverse-transcribed into Cy5-labeled cRNA, combined with a Cy3-labeled reference and hybridized to oligonucleotide microarrays. Microarrays were scanned by Gene-Pix 4000B and data were analyzed using GenePixPro 3.0 software. The microarray data were validated in the same RNA samples by qRT-PCR analysis of selected genes. For the disc tissue, the mRNA expressions of 522 genes changed obviously in the degeneration group, accounting for approximately 2.64% of all analyzed transcripts. These included transcription-related, ion channel and transport protein, receptor, protein synthesis and modifying, growth factor, etc. For PBMCs, the expressions of 62 genes changed obviously in the patients in the degeneration group. These changes included ion channel, transport protein, transcription-related, DNA synthesis and repair, metalloprotease, immune globulin-related, growth factor-related, extracellular matrix-related, adhesion molecule, etc. Analyzed on the association of the differential expression of genes between disc tissue and PBMCs, some genes were not compatible. The course of intervertebral disc denegation is a complicated dynamic process, however, and may mainly be local pathogenesis. These findings furnish new data for the mechanistic investigation of degenerative discs.

Distribution of circulating cells in systemic juvenile idiopathic arthritis across disease activity states

Juvenile idiopathic arthritis (JIA) encompasses a group of chronic childhood arthritides of unknown etiology. One subtype, systemic JIA (SJIA), is characterized by a combination of arthritis and systemic inflammation. Its systemic nature suggests that clues to SJIA pathogenesis may be found in examination of peripheral blood cells. To determine the immunophenotypic profiles of circulating mononuclear cells in SJIA patients with different degrees of disease activity, we studied PBMC from 31 SJIA patients, 20 polyarticular JIA patients (similar to adult rheumatoid arthritis), and 31 age-matched controls. During SJIA disease flare, blood monocyte numbers were increased, whereas levels of myeloid dendritic cells (DC) and gammadelta T cells were reduced. At both flare and quiescence, increased levels of CD14 and CD16 were found on SJIA monocytes. Levels of CD16-DC were elevated at SJIA quiescence compared both to healthy controls and to SJIA subjects with active disease. Overall, our findings suggest dysregulation of innate immunity in SJIA and raise the possibility that quiescence represents a state of compensated inflammation.

Data recovery and integration from public databases uncovers transformation-specific transcriptional downregulation of cAMP-PKA pathway-encoding genes

BACKGROUND

The integration of data from multiple genome-wide assays is essential for understanding dynamic spatio-temporal interactions within cells. Such integration, which leads to a more complete view of cellular processes, offers the opportunity to rationalize better the high amount of "omics" data freely available in several public databases.In particular, integration of microarray-derived transcriptome data with other high-throughput analyses (genomic and mutational analysis, promoter analysis) may allow us to unravel transcriptional regulatory networks under a variety of physio-pathological situations, such as the alteration in the cross-talk between signal transduction pathways in transformed cells.

RESULTS

Here we sequentially apply web-based and statistical tools to a case study: the role of oncogenic activation of different signal transduction pathways in the transcriptional regulation of genes encoding proteins involved in the cAMP-PKA pathway. To this end, we first re-analyzed available genome-wide expression data for genes encoding proteins of the downstream branch of the PKA pathway in normal tissues and human tumor cell lines. Then, in order to identify mutation-dependent transcriptional signatures, we classified cancer cells as a function of their mutational state. The results of such procedure were used as a starting point to analyze the structure of PKA pathway-encoding genes promoters, leading to identification of specific combinations of transcription factor binding sites, which are neatly consistent with available experimental data and help to clarify the relation between gene expression, transcriptional factors and oncogenes in our case study.

CONCLUSIONS

Genome-wide, large-scale "omics" experimental technologies give different, complementary perspectives on the structure and regulatory properties of complex systems. Even the relatively simple, integrated workflow presented here offers opportunities not only for filtering data noise intrinsic in high throughput data, but also to progressively extract novel information that would have remained hidden otherwise. In fact we have been able to detect a strong transcriptional repression of genes encoding proteins of cAMP/PKA pathway in cancer cells of different genetic origins. The basic workflow presented herein may be easily extended by incorporating other tools and can be applied even by researchers with poor bioinformatics skills.

Phenotypic and functional characterization of switch memory B cells from patients with oligoarticular juvenile idiopathic arthritis

Introduction

In chronic inflammatory disorders, B cells can contribute to tissue damage by autoantibody production and antigen presentation to T cells. Here, we have characterized synovial fluid and tissue B-cell subsets in patients with oligoarticular juvenile idiopathic arthritis (JIA), an issue not addressed before in detail.

Methods

B cells from synovial fluid (SF) and peripheral blood (PB) of 25 JIA patients, as well as from PB of 20 controls of comparable age, were characterized by multicolor flow cytometry. Immunoglobulin-secreting cells were detected by ELISPOT. Immunohistochemical analyses of synovial tissue from three JIA patients were performed.

Results

JIA SF B cells were enriched in CD27⁺ and CD27^- switch memory B cells, but not in CD27⁺ IgM memory B cells, compared with patient and control PB. Plasma blasts were more abundant in SF and secreted higher amounts of IgG. Lymphoid aggregates not organized in follicle-like structures were detected in synovial tissue sections and were surrounded by CD138⁺ plasma cells. Finally, transitional B cells were significantly increased in JIA PB versus SF or control PB. CCR5, CCR8, CXCR2, and CXCR3 were upregulated, whereas CCR6, CCR7, and CXCR5 were downregulated on SF CD27⁺ and CD27^- switch memory B cells compared with their circulating counterparts. SF CD27⁺ and CD27^- switch memory B cells expressed at high levels the costimulatory molecule CD86 and the activation marker CD69.

Conclusions

This study demonstrates for the first time an expansion of activated switch memory B cells and of IgG-secreting plasma blasts in the SF from oligoarticular JIA patients. Memory B cells belonged to either the CD27⁺or the CD27^- subsets and expressed CD86, suggesting their involvement in antigen presentation to T cells. Patterns of chemokines-receptor expression on CD27⁺ and CD27^- switch memory B cells delineated potential mechanisms for their recruitment to the inflamed joints.

Gene expression signatures in polyarticular juvenile idiopathic arthritis demonstrate disease heterogeneity and offer a molecular classification of disease subsets

OBJECTIVE

To determine whether peripheral blood mononuclear cells (PBMCs) from children with recent-onset polyarticular juvenile idiopathic arthritis (JIA) exhibit biologically or clinically informative gene expression signatures.

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 biologic agents. RNA was extracted from isolated mononuclear cells, fluorescence labeled, and hybridized to commercial gene expression microarrays (Affymetrix HG-U133 Plus 2.0). Data were analyzed using analysis of variance at a 5% false discovery rate threshold after robust multichip analysis preprocessing and distance-weighted discrimination normalization.

RESULTS

Initial analysis revealed 873 probe sets for genes that were differentially expressed between polyarticular JIA patients and healthy controls. Hierarchical clustering of these probe sets distinguished 3 subgroups within the polyarticular JIA group. Prototypical patients 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 gene expression signatures with clinical and biologic features of JIA subgroups suggested relevance to aspects of disease activity and supported the division of polyarticular JIA into distinct subsets.

CONCLUSION

Gene expression signatures in PBMCs from patients with recent-onset polyarticular JIA reflect discrete disease processes and offer a molecular classification of disease.

Subtype-specific peripheral blood gene expression profiles in recent-onset juvenile idiopathic arthritis

OBJECTIVE

To identify differences in peripheral blood gene expression between patients with different subclasses of juvenile idiopathic arthritis (JIA) and healthy controls in a multicenter study of patients with recent-onset JIA prior to treatment with disease-modifying antirheumatic drugs (DMARDs) or biologic agents.

METHODS

Peripheral blood mononuclear cells (PBMCs) from 59 healthy children and 136 patients with JIA (28 with enthesitis-related arthritis [ERA], 42 with persistent oligoarthritis, 45 with rheumatoid factor [RF]-negative polyarthritis, and 21 with systemic disease) were isolated from whole blood. Poly(A) RNA was labeled using a commercial RNA amplification and labeling system (NuGEN Ovation), and gene expression profiles were obtained using commercial expression microarrays (Affymetrix HG-U133 Plus 2.0).

RESULTS

A total of 9,501 differentially expressed probe sets were identified among the JIA subtypes and controls (by analysis of variance; false discovery rate 5%). Specifically, 193, 1,036, 873, and 7,595 probe sets were different in PBMCs from the controls compared with those from the ERA, persistent oligoarthritis, RF-negative polyarthritis, and systemic JIA patients, respectively. In patients with persistent oligoarthritis, RF-negative polyarthritis, and systemic JIA subtypes, up-regulation of genes associated with interleukin-10 (IL-10) signaling was prominent. A hemoglobin cluster was identified that was underexpressed in ERA patients but overexpressed in systemic JIA patients. The influence of JAK/STAT, ERK/MAPK, IL-2, and B cell receptor signaling pathways was evident in patients with persistent oligoarthritis. In systemic JIA, up-regulation of innate immune pathways, including IL-6, Toll-like receptor/IL-1 receptor, and peroxisome proliferator-activated receptor signaling, were noted, along with down-regulation of gene networks related to natural killer cells and T cells. Complement and coagulation pathways were up-regulated in systemic JIA, with a subset of these genes being differentially expressed in other subtypes as well.

CONCLUSION

Expression analysis identified differentially expressed genes in PBMCs obtained early in the disease from patients with different subtypes of JIA and in healthy controls, providing evidence of immunobiologic differences between these forms of childhood arthritis.

Enhanced monocyte response and decreased central memory T cells in children with invasive Staphylococcus aureus infections

Staphylococcus aureus has emerged as a significant pathogen causing severe invasive disease in otherwise healthy people. Despite considerable advances in understanding the epidemiology, resistance mechanisms, and virulence factors produced by the bacteria, there is limited knowledge of the in vivo host immune response to acute, invasive S. aureus infections. Herein, we report that peripheral blood mononuclear cells from patients with severe S. aureus infections demonstrate a distinctive and robust gene expression profile which is validated in a distinct group of patients and on a different microarray platform. Application of a systems-wide modular analysis framework reveals significant over-expression of innate immunity genes and under-expression of genes related to adaptive immunity. Simultaneous flow cytometry analyses demonstrated marked alterations in immune cell numbers, with decreased central memory CD4 and CD8 T cells and increased numbers of monocytes. CD14+ monocyte numbers significantly correlated with the gene expression levels of genes related to the innate immune response. These results demonstrate the value of applying a systems biology approach that reveals the significant alterations in the components of circulating blood lymphocytes and monocytes in invasive S. aureus infections.

FitSNPs: highly differentially expressed genes are more likely to have variants associated with disease

Differential expressed genes are more likely to have variants associated with disease. A new tool, fitSNP, prioritizes candidate SNPs from association studies.

Background

Candidate single nucleotide polymorphisms (SNPs) from genome-wide association studies (GWASs) were often selected for validation based on their functional annotation, which was inadequate and biased. We propose to use the more than 200,000 microarray studies in the Gene Expression Omnibus to systematically prioritize candidate SNPs from GWASs.

Results

We analyzed all human microarray studies from the Gene Expression Omnibus, and calculated the observed frequency of differential expression, which we called differential expression ratio, for every human gene. Analysis conducted in a comprehensive list of curated disease genes revealed a positive association between differential expression ratio values and the likelihood of harboring disease-associated variants. By considering highly differentially expressed genes, we were able to rediscover disease genes with 79% specificity and 37% sensitivity. We successfully distinguished true disease genes from false positives in multiple GWASs for multiple diseases. We then derived a list of functionally interpolating SNPs (fitSNPs) to analyze the top seven loci of Wellcome Trust Case Control Consortium type 1 diabetes mellitus GWASs, rediscovered all type 1 diabetes mellitus genes, and predicted a novel gene (KIAA1109) for an unexplained locus 4q27. We suggest that fitSNPs would work equally well for both Mendelian and complex diseases (being more effective for cancer) and proposed candidate genes to sequence for their association with 597 syndromes with unknown molecular basis.

Conclusions

Our study demonstrates that highly differentially expressed genes are more likely to harbor disease-associated DNA variants. FitSNPs can serve as an effective tool to systematically prioritize candidate SNPs from GWASs.

Gene expression analysis of macrophages derived from ankylosing spondylitis patients reveals interferon-gamma dysregulation

OBJECTIVE

To determine whether macrophages, a type of cell implicated in the pathogenesis of ankylosing spondylitis (AS), exhibit a characteristic gene expression pattern.

METHODS

Macrophages were derived from the peripheral blood of 8 AS patients (median disease duration 13 years [range <1-43 years]) and 9 healthy control subjects over 7 days with the use of granulocyte-macrophage colony-stimulating factor. Cells were stimulated for 24 hours with interferon-gamma (IFN gamma; 100 units/ml), were left untreated for 24 hours, or were treated for 3 hours with lipopolysaccharide (LPS; 10 ng/ml). RNA was isolated and examined by microarray and real-time quantitative reverse transcription-polymerase chain reaction analysis.

RESULTS

Microarray analysis revealed 198 probe sets detecting the differential expression of 141 unique genes in untreated macrophages from AS patients compared with healthy controls. Clustering and principal components analysis clearly distinguished AS patients and controls. Of the differentially expressed genes, 78 (55%) were IFN-regulated, and their relative expression indicated a "reverse" IFN signature in AS patient macrophages, where IFN gamma-up-regulated genes were underexpressed and down-regulated genes were overexpressed. Treatment of macrophages with exogenous IFN gamma normalized the expression of these genes between patients and controls. In addition, the messenger RNA encoded by the IFN gamma gene was approximately 2-fold lower in AS patient macrophages at baseline (P = 0.004) and was poorly responsive to LPS (P = 0.018), as compared with healthy controls.

CONCLUSIONS

Our findings reveal consistent differences in gene expression in macrophages from AS patients, with evidence of a striking "reverse" IFN signature. Together with poor expression and responsiveness of the IFN gamma gene, these results suggest that there may be a relative defect in IFN gamma gene regulation, with autocrine consequences and implications for disease pathogenesis.

Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets

BACKGROUND

Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles from publicly available microarray datasets of cancer (breast, lymphoma and renal) samples linked to clinical information with an iterative machine learning algorithm. ROC curves were used to assess the prediction error of each profile for classification. We compared the prediction error of profiles correlated with molecular phenotype against profiles correlated with relapse-free status. Prediction error of profiles identified with supervised univariate feature selection algorithms were compared to profiles selected randomly from a) all genes on the microarray platform and b) a list of known disease-related genes (a priori selection). We also determined the relevance of expression profiles on test arrays from independent datasets, measured on either the same or different microarray platforms.

RESULTS

Highly discriminative expression profiles were produced on both simulated gene expression data and expression data from breast cancer and lymphoma datasets on the basis of ER and BCL-6 expression, respectively. Use of relapse-free status to identify profiles for prognosis prediction resulted in poorly discriminative decision rules. Supervised feature selection resulted in more accurate classifications than random or a priori selection, however, the difference in prediction error decreased as the number of features increased. These results held when decision rules were applied across-datasets to samples profiled on the same microarray platform.

CONCLUSION

Our results show that many gene sets predict molecular phenotypes accurately. Given this, expression profiles identified using different training datasets should be expected to show little agreement. In addition, we demonstrate the difficulty in predicting relapse directly from microarray data using supervised machine learning approaches. These findings are relevant to the use of molecular profiling for the identification of candidate biomarker panels.

Specific gene expression profiles in systemic juvenile idiopathic arthritis

OBJECTIVE

Patients with systemic juvenile idiopathic arthritis (JIA) have arthritis, quotidian fevers, and other extraarticular features. This disease often remains severe and debilitating. The purpose of this study was to compare gene expression profiles in peripheral blood mononuclear cells (PBMCs) from patients with active and inactive systemic JIA to define and better understand the cause of active disease.

METHODS

Gene expression profiles of PBMCs were determined in cells from 9 patients with active systemic JIA and 8 patients with inactive systemic JIA. Unsupervised clustering and significance analysis were performed. We compared the systemic JIA profile with data from patients with polyarticular JIA, chronic infantile neurologic, cutaneous, articular syndrome, Kawasaki disease, and systemic lupus erythematosus to identify disease-specific genes. Quantitative reverse transcription-polymerase chain reaction of selected genes was performed on negatively selected B cells, T cells, and monocytes.

RESULTS

Unsupervised clustering of expressed genes resulted in 2 groups that corresponded to the clinical status of the patients (active and inactive disease) and was independent of their medications. A total of 286 genes were identified as significantly up-regulated in patients with active disease and 86% of them were specific to systemic JIA. Interleukin-6 (IL-6) was expressed in monocytes and B cells, IL-10 in monocytes, and suppressor of cytokine signaling 3 in monocytes and T cells from patients with active disease.

CONCLUSION

Gene expression profiles in PBMCs identified disease-specific genes in patients with systemic JIA. Cell type analyses should allow further insight into the mechanisms of the disease.

Transcriptional profiling of lymphoblast lines from subjects with panic disorder

In attempts to isolate genetic vulnerability factors for panic disorder (PD), a number of investigators have used genome-wide linkage or association analyses. But these attempts have been only modestly successful which suggests that alternative approaches may be needed to define the biology of PD. Therefore, using recently developed genome-wide gene expression profiling, we explored whether transcriptional signatures associated with PD are present in lymphoblast cell line. The expression of 2,469 transcripts in lymphoblast cell lines from 16 subjects was arithmetically increased in every line and significantly increased overall and 354 transcripts was arithmetically decreased in every cell line and significantly decreased overall as compared to those lymphoblast lines from 17 subjects without a history of behavioral illness. Further sex specific analyses showed that in those 10 lines derived from female probands, the expression of a further 67 transcripts was arithmetically increased in every line and significantly increased overall and a further 332 transcripts was arithmetically decreased in every cell line and significantly decreased. Conversely, in cell lines from the six male probands, the expression of an additional 212 was arithmetically increased in every line and significantly increased overall and a further 332 transcripts was arithmetically decreased in every cell line. We conclude that lymphoblast cell lines derived from subjects with PD have significant, partially sex dependent changes in gene transcription. Further studies are necessary to correlate these changes in these hemopoetically derived cells with those changes postulated to occur in the CNS in association with PD.

Genomic progress in pediatric arthritis: recent work and future goals

PURPOSE OF REVIEW

Pediatric arthritis is a heterogeneous group of chronic arthropathies that are influenced by complex genetic and perhaps environmental factors. Interacting genetic traits may one day be identified that provide the basis for predicting disease risk and other characteristics such as course, age of onset, and disease severity. The purpose of this review is to describe the recent progress towards identifying the multiple genes related to pediatric arthritis and understand how they relate to each other and to disease pathology.

RECENT FINDINGS

Candidate gene studies are by far the most widely reported type of genetic studies to date for juvenile arthritis with only one genome-wide screen for juvenile rheumatoid/idiopathic arthritis published. Particular attention is paid to studies of candidate genes with potential immunological roles and those associated with other forms of autoimmunity.

SUMMARY

Genomic studies may perhaps one day provide information to allow future classification systems of childhood arthritis to include molecular biomarkers as a complement to clinical observations, as well as understand how these genes or proteins relate to each other and to disease pathogenesis.

The peripheral blood transcriptome dynamically reflects system wide biology: a potential diagnostic tool

In our genome-wide survey of gene expression in human peripheral blood cells using both an expressed sequence tag (EST) and a microarray hybridization approach, we identified the expression of a large proportion (approximately 80%) of the genes encoded in the human genome. Comparison of the peripheral blood transcriptome with genes expressed in nine different human tissue types revealed that expression of over 80% was shared with any given tissue. We also sought to determine whether those gene transcripts undetected by these methods were also expressed in peripheral blood cells. Using reverse-transcriptase-polymerase chain reaction, we detected additional tissue-specific gene transcripts including beta-myosin heavy chain (heart specific) and insulin (specific to pancreatic islet beta cells), in circulating blood cells. Arguably, the detection of low levels of tissue-specific transcripts could be considered products of "illegitimate" transcription; however, our study also demonstrates that environmental conditions affect the transcriptional regulation of insulin in the peripheral blood. We thus hypothesize that blood cells can act as sentinels of disease and that we could capitalize on this property of blood for the diagnosis/prognosis of disease (the "Sentinel Principle"). Peripheral blood is an ideal surrogate tissue as it is readily obtainable, provides a large biosensor pool in the form of gene transcripts, and response to changes in the macro- and micro-environments is detectable as alterations in the levels of these gene transcripts.

Distinct synovial immunopathologic characteristics of juvenile-onset spondylarthritis and other forms of juvenile idiopathic arthritis

OBJECTIVE

To characterize the synovial immunopathologic features of juvenile-onset spondylarthritis (SpA) in relation to adult SpA and other forms of juvenile idiopathic arthritis (JIA).

METHODS

Synovial biopsy samples were obtained from 10 patients with juvenile-onset SpA, 23 with adult SpA, 19 with rheumatoid arthritis (RA), 8 with juvenile polyarthritis, and 12 with juvenile oligoarthritis. Synovial immunopathologic features were studied by extensive histologic and immunohistochemical analyses.

RESULTS

Synovitis in juvenile SpA was characterized by marked lining layer hyperplasia, clear hypervascularity, and pronounced inflammatory cell infiltration with lymphocytes and macrophages, independent of disease duration or time of sampling. The immunopathologic features of juvenile SpA resembled those of adult SpA in terms of hypervascularity and absence of RA-specific intracellular citrullinated proteins and HLA-DR4/human cartilage glycoprotein 39(263-275) complexes, but differed markedly by a stronger lining layer hyperplasia and lower numbers of CD163+ macrophages. Accordingly, class prediction analysis failed to classify juvenile SpA synovitis in the SpA group. Comparison of juvenile SpA with other JIA subtypes showed a broad overlap, with the exception of slightly lower vascularity in juvenile polyarthritis and higher inflammatory cell infiltration in juvenile oligoarthritis. Unsupervised clustering analysis identified a subgroup of samples characterized by high plasma cell infiltration, which corresponded with active, longstanding JIA, mostly of the oligoarthritis subtype.

CONCLUSION

Despite some similarities with adult SpA, the findings with regard to lining layer hyperplasia and CD163+ macrophage infiltration are indicative of important differences in the synovial immunopathologic features of juvenile-onset SpA. The partial overlap with other JIA subtypes emphasizes the need for further biologic characterization of JIA in order to define pathophysiologic, rather than phenotypic, subgroups.

Blood-based biomarkers for detecting mild osteoarthritis in the human knee

OBJECTIVE

This study was designed to test the utility of a blood-based approach to identify mild osteoarthritis (OA) of the knee.

METHODS

Blood samples were drawn from 161 subjects, including 85 subjects with arthroscopically diagnosed mild OA of the knee and 76 controls. Following RNA isolation, an in-house custom cDNA microarray was used to screen for differentially expressed genes. A subset of selected genes was then tested using real-time RT-PCR. Logistic regression analysis was used to evaluate linear combinations of the biomarkers and receiver operating characteristic curve analysis was used to assess the discriminatory power of the combinations.

RESULTS

Genes differentially expressed (3543 genes) between mild knee OA and control samples were identified through microarray analysis. Subsequent real-time RT-PCR verification identified six genes significantly down-regulated in mild OA: heat shock 90kDa protein 1, alpha; inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase complex-associated protein; interleukin 13 receptor, alpha 1; laminin, gamma 1; platelet factor 4 (also known as chemokine (C-X-C motif) ligand 4) and tumor necrosis factor, alpha-induced protein 6. Logistic regression analysis identified linear combinations of nine genes--the above six genes, early growth response 1; alpha glucosidase II alpha subunit; and v-maf musculoaponeurotic fibrosarcoma oncogene homolog B (avian)--as discriminatory between subjects with mild OA and controls, with a sensitivity of 86% and specificity of 83% in a training set of 78 samples. The optimal biomarker combinations were then evaluated using a blind test set (67 subjects) which showed 72% sensitivity and 66% specificity.

CONCLUSIONS

Linear combinations of blood RNA biomarkers offer a substantial improvement over currently available diagnostic tools for mild OA. Blood-derived RNA biomarkers may be of significant clinical value for the diagnosis of early, asymptomatic OA of the knee.