Differential gene expression of peripheral blood mononuclear cells from rheumatoid arthritis patients may discriminate immunogenetic, pathogenic and treatment features

PADI4 Epigenetically Suppresses p21 Transcription and Inhibits Cell Apoptosis in Fibroblast-like Synoviocytes from Rheumatoid Arthritis Patients

Rheumatoid arthritis (RA) is characterized by synovial lining hyperplasia, which involves abnormal growth of fibroblast-like synoviocytes (FLSs). This study aimed to investigate the function and molecular mechanism of peptidylarginine deiminase type 4 (PADI4) in FLSs isolated from RA patients (RA-FLSs). FLSs were isolated from RA patients and transfected with small interfering RNAs (siRNAs) or PADI4 overexpression plasmid. FLSs were treated by Adriamycin (ADR) to induce apoptosis, and apoptotic cells were detected by flow cytometry. The expression of PADI4, p53 and p21 was detected by qRT-PCR and Western blot analysis. The recruitment of PADI4 and histone H3 arginine modifications to p21 promoter was measured by chromatin immunoprecipitation. The results showed that knockdown of PADI4 promoted the apoptosis of RA-FLSs and the expression of p53 and p21. Ectopic expression of PADI4 inhibited ADR-induced apoptosis of RA-FLSs, and down-regulated the expression of p53 and p21. In RA-FLSs, global H3 citrullination (CitH3) and H3 arginine 17 methylation levels were dynamically changed by PADI4 and ADR treatment. PADI4 and H3 could bind p21 promoter region to regulate p21 expression. In conclusion, PADI4 contributes to the pathogenesis of RA by protecting FLSs from apoptosis. PADI4 suppresses p21 transcription through altering histone H3 arginine modifications on p21 promoter region. Our study provides new insight into the anti-apoptotic role of PADI4 in RA development.

Assessment of DNA damage and mRNA/miRNA transcriptional expression profiles in hyperglycemic versus non-hyperglycemic patients with type 2 diabetes mellitus

The development of type 2 diabetes mellitus (T2D) is associated with a number of genetic and environmental factors. Hyperglycemia, a T2D hallmark, is related to several metabolic complications, comorbidities and increased DNA damage. However, the molecular alterations of a proper glucose control are still unclarified. In this study, we aimed to evaluate DNA damage (comet assay), as well as to compare the transcriptional expression (mRNA and miRNA analyzed by the microarray technique) displayed by peripheral blood mononuclear cells (PBMCs) from three distinct groups: hyperglycemic T2D patients (T2D-H, n=14), non-hyperglycemic T2D patients (T2D-N, n=15), and healthy non-diabetic individuals (n=16). The comet assay revealed significantly (p<0.05) higher levels of DNA damage in T2D-H group compared to both T2D-N and control groups, while a significant difference was not observed between the control and T2D-N groups. After bioinformatics analysis, the differentially expressed mRNAs were subjected to functional enrichment analysis (DAVID) and inflammatory response was among the enriched terms found when comparing T2D-N with controls and T2D-H with T2D-N. Concerning the gene set enrichment and gene set analyses, among the differentially expressed gene sets, three were of interest: regulation of DNA repair (T2D-H versus T2D-N), superoxide response (T2D-H versus control group), and response to endoplasmic reticulum stress (T2D-H versus control group). We also identified miRNAs related with T2D and hyperglycemia not yet associated with these conditions in the literature. Some of the differentially expressed mRNAs were among the predicted targets of the differentially expressed miRNAs. Our results showed the association of hyperglycemia with increased DNA damage and aberrant expression of miRNAs and genes related to several biological processes, such as inflammation, DNA repair, ROS production and antioxidant defense, highlighting the importance of proper glycemic control. Moreover, the transcriptional expression of miRNAs provided novel information for understanding the regulatory mechanisms involved in the T2D progression.

Gene expression analysis in RA: towards personalized medicine

Gene expression has recently been at the forefront of advance in personalized medicine, notably in the field of cancer and transplantation, providing a rational for a similar approach in rheumatoid arthritis (RA). RA is a prototypic inflammatory autoimmune disease with a poorly understood etiopathogenesis. Inflammation is the main feature of RA; however, many biological processes are involved at different stages of the disease. Gene expression signatures offer management tools to meet the current needs for personalization of RA patients' care. This review analyses currently available information with respect to RA diagnostic, prognostic and prediction of response to therapy with a view to highlight the abundance of data, whose comparison is often inconclusive due to the mixed use of material source, experimental methodologies and analysis tools, reinforcing the need for harmonization if gene expression signatures are to become a useful clinical tool in personalized medicine for RA patients.

A new 12-gene diagnostic biomarker signature of melanoma revealed by integrated microarray analysis

Genome-wide microarray technology has facilitated the systematic discovery of diagnostic biomarkers of cancers and other pathologies. However, meta-analyses of published arrays often uncover significant inconsistencies that hinder advances in clinical practice. Here we present an integrated microarray analysis framework, based on a genome-wide relative significance (GWRS) and genome-wide global significance (GWGS) model. When applied to five microarray datasets on melanoma published between 2000 and 2011, this method revealed a new signature of 200 genes. When these were linked to so-called ‘melanoma driver’ genes involved in MAPK, Ca²⁺, and WNT signaling pathways we were able to produce a new 12-gene diagnostic biomarker signature for melanoma (i.e., EGFR, FGFR2, FGFR3, IL8, PTPRF, TNC, CXCL13, COL11A1, CHP2, SHC4, PPP2R2C, and WNT4). We have begun to experimentally validate a subset of these genes involved in MAPK signaling at the protein level, including CXCL13, COL11A1, PTPRF and SHC4 and found these to be over-expressed in metastatic and primary melanoma cells in vitro and in situ compared to melanocytes cultured from healthy skin epidermis and normal healthy human skin. While SHC4 has been reported previously to be associated to melanoma, this is the first time CXCL13, COL11A1, and PTPRF have been associated with melanoma on experimental validation. Our computational evaluation indicates that this 12-gene biomarker signature achieves excellent diagnostic power in distinguishing metastatic melanoma from normal skin and benign nevus. Further experimental validation of the role of these 12 genes in a new signaling network may provide new insights into the underlying biological mechanisms driving the progression of melanoma.

T cell post-transcriptional miRNA-mRNA interaction networks identify targets associated with susceptibility/resistance to collagen-induced arthritis

Background

Due to recent studies indicating that the deregulation of microRNAs (miRNAs) in T cells contributes to increased severity of rheumatoid arthritis, we hypothesized that deregulated miRNAs may interact with key mRNA targets controlling the function or differentiation of these cells in this disease.

Methodology/Principal Findings

To test our hypothesis, we used microarrays to survey, for the first time, the expression of all known mouse miRNAs in parallel with genome-wide mRNAs in thymocytes and naïve and activated peripheral CD3⁺ T cells from two mouse strains the DBA-1/J strain (MHC-H2q), which is susceptible to collagen induced arthritis (CIA), and the DBA-2/J strain (MHC-H2d), which is resistant. Hierarchical clustering of data showed the several T cell miRNAs and mRNAs differentially expressed between the mouse strains in different stages of immunization with collagen. Bayesian statistics using the GenMir⁺⁺ algorithm allowed reconstruction of post-transcriptional miRNA-mRNA interaction networks for target prediction. We revealed the participation of miR-500, miR-202-3p and miR-30b*, which established interactions with at least one of the following mRNAs: Rorc, Fas, Fasl, Il-10 and Foxo3. Among the interactions that were validated by calculating the minimal free-energy of base pairing between the miRNA and the 3′UTR of the mRNA target and luciferase assay, we highlight the interaction of miR-30b*-Rorc mRNA because the mRNA encodes a protein implicated in pro-inflammatory Th17 cell differentiation (Rorγt). FACS analysis revealed that Rorγt protein levels and Th17 cell counts were comparatively reduced in the DBA-2/J strain.

Conclusions/Significance

This result showed that the miRNAs and mRNAs identified in this study represent new candidates regulating T cell function and controlling susceptibility and resistance to CIA.

Gene expression patterns in peripheral blood cells associated with radiographic severity in African Americans with early rheumatoid arthritis

Gene expression profiling may be used to stratify patients by disease severity to test the hypothesis that variable disease outcome has a genetic component. In order to define unique expression signatures in African American rheumatoid arthritis (RA) patients with severe erosive disease, we undertook a gene expression study using samples of RNA from peripheral blood mononuclear cells (PBMCs). RNA from baseline PBMC samples of 96 African American RA patients with early RA (<2 years disease duration) was hybridized to cDNA probes of the Illumina Human HT-V3 expression array. Expression analyses were performed using the ca. 25,000 cDNA probes, and then expression levels were compared to the total number of erosions in radiographs of the hands and feet at baseline and 36 months. Using a false discovery rate cutoff of Q = 0.30, 1,138 genes at baseline and 680 genes at 36 months significantly correlated with total erosions. No evidence of a signal differentiating disease progression, or change in erosion scores between baseline and 36 months, was found. Further analyses demonstrated that the differential gene expression signature was localized to the patients with the most erosive disease (>10 erosions). Ingenuity Pathway Analysis demonstrated that genes with fold change greater than 1.5 implicated immune pathways such as CTLA signaling in cytotoxic T lymphocytes. These results demonstrate that CLEAR patients with early RA having the most severe erosive disease, as compared to more mild cases (<10 erosions), may be characterized by a set of differentially expressed genes that represent biological pathways with relevance to autoimmune disease.

Differential gene expression profiles may differentiate responder and nonresponder patients with rheumatoid arthritis for methotrexate (MTX) monotherapy and MTX plus tumor necrosis factor inhibitor combined therapy

OBJECTIVE

We aimed to evaluate whether the differential gene expression profiles of patients with rheumatoid arthritis (RA) could distinguish responders from nonresponders to methotrexate (MTX) and, in the case of MTX nonresponders, responsiveness to MTX plus anti-tumor necrosis factor-α (anti-TNF) combined therapy.

METHODS

We evaluated 25 patients with RA taking MTX 15-20 mg/week as a monotherapy (8 responders and 17 nonresponders). All MTX nonresponders received infliximab and were reassessed after 20 weeks to evaluate their anti-TNF responsiveness using the European League Against Rheumatism response criteria. A differential gene expression analysis from peripheral blood mononuclear cells was performed in terms of hierarchical gene clustering, and an evaluation of differentially expressed genes was performed using the significance analysis of microarrays program.

RESULTS

Hierarchical gene expression clustering discriminated MTX responders from nonresponders, and MTX plus anti-TNF responders from nonresponders. The evaluation of only highly modulated genes (fold change > 1.3 or < 0.7) yielded 5 induced (4 antiapoptotic and CCL4) and 4 repressed (4 proapoptotic) genes in MTX nonresponders compared to responders. In MTX plus anti-TNF non-responders, the CCL4, CD83, and BCL2A1 genes were induced in relation to responders.

CONCLUSION

Study of the gene expression profiles of RA peripheral blood cells permitted differentiation of responders from nonresponders to MTX and anti-TNF. Several candidate genes in MTX non-responders (CCL4, HTRA2, PRKCD, BCL2A1, CAV1, TNIP1, CASP8AP2, MXD1, and BTG2) and 3 genes in MTX plus anti-TNF nonresponders (CCL4, CD83, and BCL2A1) were identified for further study.

Exact and approximate area-proportional circular Venn and Euler diagrams

Scientists conducting microarray and other experiments use circular Venn and Euler diagrams to analyze and illustrate their results. As one solution to this problem, this paper introduces a statistical model for fitting area-proportional Venn and Euler diagrams to observed data. The statistical model outlined in this paper includes a statistical loss function and a minimization procedure that enables formal estimation of the Venn/Euler area-proportional model for the first time. A significance test of the null hypothesis is computed for the solution. Residuals from the model are available for inspection. As a result, this algorithm can be used for both exploration and inference on real data sets. A Java program implementing this algorithm is available under the Mozilla Public License. An R function venneuler() is available as a package in CRAN and a plugin is available in Cytoscape.

Gene expression profiles from discordant monozygotic twins suggest that molecular pathways are shared among multiple systemic autoimmune diseases

INTRODUCTION

The objective of this study is to determine if multiple systemic autoimmune diseases (SAID) share gene expression pathways that could provide insights into pathogenic mechanisms common to these disorders.

METHODS

RNA microarray analyses (Agilent Human 1A(V2) 20K oligo arrays) were used to quantify gene expression in peripheral blood cells from 20 monozygotic (MZ) twin pairs discordant for SAID. Six affected probands with systemic lupus erythematosus (SLE), six with rheumatoid arthritis (RA), eight with idiopathic inflammatory myopathies (IIM), and their same-gendered unaffected twins, were enrolled. Comparisons were made between discordant twin pairs and these were also each compared to 40 unrelated control subjects (matched 2:1 to each twin by age, gender and ethnicity) using statistical and molecular pathway analyses. Relative quantitative PCR was used to verify independently measures of differential gene expression assessed by microarray analysis.

RESULTS

Probands and unrelated, matched controls differed significantly in gene expression for 104 probes corresponding to 92 identifiable genes (multiple-comparison adjusted P values < 0.1). Differentially expressed genes involved several overlapping pathways including immune responses (16%), signaling pathways (24%), transcription/translation regulators (26%), and metabolic functions (15%). Interferon (IFN)-response genes (IFI27, OASF, PLSCR1, EIF2AK2, TNFAIP6, and TNFSF10) were up-regulated in probands compared to unrelated controls. Many of the abnormally expressed genes played regulatory roles in multiple cellular pathways. We did not detect any probes expressed differentially in comparisons among the three SAID phenotypes. Similarly, we found no significant differences in gene expression when comparing probands to unaffected twins or unaffected twins to unrelated controls. Gene expression levels for unaffected twins appeared intermediate between that of probands and unrelated controls for 6535 probes (32% of the total probes) as would be expected by chance. By contrast, in unaffected twins intermediate ordering was observed for 84 of the 104 probes (81%) whose expression differed significantly between probands and unrelated controls.

CONCLUSIONS

Alterations in expression of a limited number of genes may influence the dysregulation of numerous, integrated immune response, cell signaling and regulatory pathways that are common to a number of SAID. Gene expression profiles in peripheral blood suggest that for genes in these critical pathways, unaffected twins may be in a transitional or intermediate state of immune dysregulation between twins with SAID and unrelated controls, perhaps predisposing them to the development of SAID given the necessary and sufficient environmental exposures.

Gene expression profiles in peripheral blood for the diagnosis of autoimmune diseases

Gene expression profiling in clinical genomics has yet to deliver robust and reliable approaches for developing diagnostics and contributing to personalized medicine. Owing to technological developments and the recent accumulation of expression profiles, it is a timely and relevant question whether peripheral blood gene expression profiling can be used routinely in clinical decision making. Here, we review the available gene expression profiling data of peripheral blood in autoimmune and chronic inflammatory diseases and suggest that peripheral blood mononuclear cells are suitable for descriptive and comparative gene expression analyses. A gene-disease interaction network in chronic inflammatory diseases, a general protocol for future studies and a decision tree for researchers are presented to facilitate standardization and adoption of this approach.

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.

A comprehensive molecular interaction map for rheumatoid arthritis

Background

Computational biology contributes to a variety of areas related to life sciences and, due to the growing impact of translational medicine - the scientific approach to medicine in tight relation with basic science -, it is becoming an important player in clinical-related areas. In this study, we use computation methods in order to improve our understanding of the complex interactions that occur between molecules related to Rheumatoid Arthritis (RA).

Methodology

Due to the complexity of the disease and the numerous molecular players involved, we devised a method to construct a systemic network of interactions of the processes ongoing in patients affected by RA. The network is based on high-throughput data, refined semi-automatically with carefully curated literature-based information. This global network has then been topologically analysed, as a whole and tissue-specifically, in order to translate the experimental molecular connections into topological motifs meaningful in the identification of tissue-specific markers and targets in the diagnosis, and possibly in the therapy, of RA.

Significance

We find that some nodes in the network that prove to be topologically important, in particular AKT2, IL6, MAPK1 and TP53, are also known to be associated with drugs used for the treatment of RA. Importantly, based on topological consideration, we are also able to suggest CRKL as a novel potentially relevant molecule for the diagnosis or treatment of RA. This type of finding proves the potential of in silico analyses able to produce highly refined hypotheses, based on vast experimental data, to be tested further and more efficiently. As research on RA is ongoing, the present map is in fieri, despite being -at the moment- a reflection of the state of the art. For this reason we make the network freely available in the standardised and easily exportable .xml CellDesigner format at ‘www.picb.ac.cn/ClinicalGenomicNTW/temp.html’ and ‘www.celldesigner.org’.

Peripheral blood expression profiles of bone morphogenetic proteins, tumor necrosis factor-superfamily molecules, and transcription factor Runx2 could be used as markers of the form of arthritis, disease activity, and therapeutic responsiveness

OBJECTIVE

To assess whether different forms of arthritis and disease activity could be distinguished by peripheral blood expression profiles of bone-regulatory factors including tumor necrosis factor (TNF)-superfamily [TNF-related apoptosis-inducing ligand (TRAIL), the Fas ligand (FasL), and the ligand for herpesvirus entry mediator (LIGHT)] and bone morphogenetic protein (BMP)-family members (BMP-2, BMP-4, BMP-6) as well as osteoblast differentiation gene Runx2.

METHODS

Blood cells from healthy controls (n = 25) and patients at different disease stages with rheumatoid arthritis (RA; n = 49), osteoarthritis (OA; n = 17), or spondyloarthritis, including ankylosing spondylitis (AS; n = 27) or psoriatic arthritis (PsA; n = 23), were processed for quantitative polymerase chain reaction. Gene expression was assessed in comparison with control samples, correlated with clinical data of different forms of arthritis, and analyzed for discriminative efficacy between groups by receiver-operation characteristic (ROC) curves. Results were confirmed on diagnostic RA (n = 5) and AS (n = 8) samples.

RESULTS

BMP-4, BMP-6, and Runx2 expressions were significantly decreased in patients with RA and OA versus controls. Patients with RA also had decreased FasL and LIGHT expression, while patients with AS had increased Runx2 expression. Negative correlation with disease activity was found for BMP-4, FasL, and Runx2 in RA and for Runx2 in PsA, while positive correlation was found for BMP-4 in PsA. Gene expression was higher in the therapy-resistant form of AS (for BMP-4, LIGHT, and Runx2) and in methotrexate-treated patients in RA (for BMP-2 and LIGHT). ROC curve analysis confirmed discrimination between groups, particularly decreased LIGHT and Runx2 for RA and increased Runx2 for AS.

CONCLUSION

Our study identified BMP and Runx2 as possible biomarkers of bone metabolism in several forms of arthritis, while lower FasL and LIGHT were associated with RA. Correlation between gene expression and disease activity may be clinically useful in assessing therapeutic effectiveness and disease monitoring.

Overview of electrochemical DNA biosensors: new approaches to detect the expression of life

DNA microarrays are an important tool with a variety of applications in gene expression studies, genotyping, pharmacogenomics, pathogen classification, drug discovery, sequencing and molecular diagnostics. They are having a strong impact in medical diagnostics for cancer, toxicology and infectious disease applications. A series of papers have been published describing DNA biochips as alternative to conventional microarray platforms to facilitate and ameliorate the signal readout. In this review, we will consider the different methods proposed for biochip construction, focusing on electrochemical detection of DNA. We also introduce a novel single-stranded DNA platform performing high-throughput SNP detection and gene expression profiling.