Bertalan Mesko

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

BackgroundChronic inflammatory diseases including inflammatory bowel disease (IBD; Crohns 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.MethodsDiseased (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).ResultsHere 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.ConclusionsThese 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.

Transdab wiki: The interactive transglutaminase substrate database on web 2.0 surface

TRANSDAB wiki is a database of transglutaminase substrate proteins. This wiki is designed to provide quality content of all the details (including synonyms, structures, references) about transglutaminase substrate proteins and interaction partners. Currently TRANSDAB contains 243 articles about substrate proteins for 6 transglutaminase types in a user-friendly, editable format. Our aim was to collect structural information about substrate proteins and this information is provided in form of images, videos and links. The scientific community is invited to edit the database and besides providing up-to-date information, this wiki should serve as a platform for valuable discussions.

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.

Chronic Obstructive Pulmonary Disease-Specific Gene Expression Signatures of Alveolar Macrophages as well as Peripheral Blood Monocytes Overlap and Correlate with Lung Function

Background: Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disease characterized by progressive airflow limitation and significant extrapulmonary (systemic) effects that lead to co-morbid conditions, though the pathomechanism of COPD is largely undetermined. Alveolar macrophages (AM) derived from peripheral monocytes (MO) appear to play a key role in initiating and/or sustaining disease progression. Objectives: To identify disease- and cell type-specific gene expression profiles and potential overlaps in those in order to diagnose COPD, characterize its progression and determine the effect of drug treatment. Method: Global gene expression analysis was used for primary screening in order to obtain expression signatures of AMs and circulating MOs of COPD patients and healthy controls. The results of microarray analyses of AMs (20 controls and 26 COPD patients) and MOs (16 controls and 22 COPD patients) were confirmed and validated by real-time quantitative polymerase chain reaction. Results: We have identified gene sets specifically associated with COPD in AMs and MOs. There were overlapping genes between the two cell types. Our data also show that COPD-specific gene expression signatures in AMs and MOs correlate with percent of predicted FEV1. Conclusion: Disease-specific and overlapping gene expression signatures can be defined in lung-derived macrophages and also in circulating monocytes. Some of the validated expression changes in both cell types correlate with lung function and therefore could serve as biomarkers of disease progression.

Pharmacogenetics and pharmacogenomics in rheumatology

Pharmacogenetics and pharmacogenomics deal with possible associations of a single genetic polymorphism or those of multiple gene profiles with responses to drugs. In rheumatology, genes and gene signatures may be associated with altered efficacy and/or safety of anti-inflammatory drugs, disease-modifying antirheumatic drugs (DMARDs) and biologics. In brief, genes of cytochrome P450, other enzymes involved in drug metabolism, transporters and some cytokines have been associated with responses to and toxicity of non-steroidal anti-inflammatory drugs, corticosteroids and DMARDs. The efficacy of biologics may be related to alterations in cytokine, chemokine and FcγR genes. Numerous studies reported multiple genetic signatures in association with responses to biologics; however, data are inconclusive. More, focused studies carried out in larger patient cohorts, using pre-selected genes, may be needed in order to determine the future of pharmacogenetics and pharmacogenomics as tools for personalized medicine in rheumatology.

Peripheral blood derived gene panels predict response to infliximab in rheumatoid arthritis and Crohn's disease.

BackgroundBiological therapies have been introduced for the treatment of chronic inflammatory diseases including rheumatoid arthritis (RA) and Crohns disease (CD). The efficacy of biologics differs from patient to patient. Moreover these therapies are rather expensive, therefore treatment of primary non-responders should be avoided.MethodWe addressed this issue by combining gene expression profiling and biostatistical approaches. We performed peripheral blood global gene expression profiling in order to filter the genome for target genes in cohorts of 20 CD and 19 RA patients. Then RT-quantitative PCR validation was performed, followed by multivariate analyses of genes in independent cohorts of 20 CD and 15 RA patients, in order to identify sets ofinterrelated genes that can separate responders from non-responders to the humanized chimeric anti-TNFalpha antibody infliximab at baseline.ResultsGene panels separating responders from non-responders were identified using leave-one-out cross-validation test, and a pool of genes that should be tested on larger cohorts was created in both conditions.ConclusionsOur data show that peripheral blood gene expression profiles are suitable for determining gene panels with high discriminatory power to differentiate responders from non-responders in infliximab therapy at baseline in CD and RA, which could be cross-validated successfully. Biostatistical analysis of peripheral blood gene expression data leads to the identification of gene panels that can help predict responsiveness of therapy and support the clinical decision-making process.

Peripheral Blood Gene Expression and IgG Glycosylation Profiles as Markers of Tocilizumab Treatment in Rheumatoid Arthritis

Objective. Tocilizumab, a humanized anti-interleukin-6 receptor monoclonal antibody, has recently been approved as a biological therapy for rheumatoid arthritis (RA) and other diseases. It is not known if there are characteristic changes in gene expression and immunoglobulin G glycosylation during therapy or in response to treatment. Methods. Global gene expression profiles from peripheral blood mononuclear cells of 13 patients with RA and active disease at Week 0 (baseline) and Week 4 following treatment were obtained together with clinical measures, serum cytokine levels using ELISA, and the degree of galactosylation of the IgG N-glycan chains. Gene sets separating responders and nonresponders were tested using canonical variates analysis. This approach also revealed important gene groups and pathways that differentiate responders from nonresponders. Results. Fifty-nine genes showed significant differences between baseline and Week 4 and thus correlated with treatment. Significantly, 4 genes determined responders after correction for multiple testing. Ten of the 12 genes with the most significant changes were validated using real-time quantitative polymerase chain reaction. An increase in the terminal galactose content of N-linked glycans of IgG was observed in responders versus nonresponders, as well as in treated samples versus samples obtained at baseline. Conclusion. As a preliminary report, gene expression changes as a result of tocilizumab therapy in RA were examined, and gene sets discriminating between responders and nonresponders were found and validated. A significant increase in the degree of galactosylation of IgG N-glycans in patients with RA treated with tocilizumab was documented.

The triad of success in personalised medicine: Pharmacogenomics, biotechnology and regulatory issues from a Central European perspective

The population of the world has recently passed the 7 billion milestone and as the cost of human genome sequencing is rapidly declining, sequence data of billions of people should be accessible much sooner than anyone would have predicted 10 years ago. This will form the basis of personalised medicine. However it is still not clear, even in principle, whether these data, combined with data of the expression of ones genome in various cells and tissues relevant to different diseases, could be used effectively in clinical medicine and healthcare, or in predicting responses to different therapies. Therefore this is an important issue which needs to be addressed before more resources are wasted on less than informative studies and surveys simply because technologies exist. As a typical example, we have selected and summarise here key studies from the biomedical literature that focus on gene expression profiling of the response to biologic therapies in peripheral blood and biopsy samples in autoimmune diseases such as rheumatoid arthritis, spondylarthropathy, inflammatory bowel diseases and psoriasis. We also present the state of the biotechnology market from a European perspective, discuss how spin-offs leverage the power of genomic technologies and describe how they might contribute to personalised medicine. As ethical, legal and social issues are essential in the area of genomics, we analysed these aspects and present here the European situation with a special focus on Hungary. We propose that the synergy of these three issues: pharmacogenomics, biotechnology and regulatory issues should be considered a triad necessary to succeed in personalised medicine.

A7.20 Response to Infliximab Therapy can be Predicted using Distinct, Non-Overlapping Gene Panels of Peripheral Blood Gene Expression in Rheumatoid Arthritis and Crohn’s Disease

Background Biological therapies targeting tumour necrosis factor α (TNF-α) have been widely used to treat chronic inflammatory disorders including rheumatoid arthritis (RA) and Crohn’s disease (CD). As these treatment modalities are rather expensive, there is a need for biomarkers that may predict therapeutic responses. As RA and CD have similar pathogenic background, one may expect to detect overlapping gene panels in predicting the response to the same therapy by the same approach. There have been very few studies using simultaneous pharmacogenomic approach in two diseases. Methods In this study, we performed peripheral blood global gene expression profiling followed by Canonical Variates Analysis (CVA) in CD and RA to identify gene sets that can differentiate responders from non-responders for infliximab therapy; and validated the results in an independent cohort by RT-QPCR. Results In CD, global gene expression analysis of samples obtained at baseline resulted in a list of 48 probe sets differentiating responders from non-responders. Comparing baseline and week 2 samples resulted in a list of five genes including AQP9, IGKC, MGAM, MMP8 and TNFAIP6 that exert expression changes upon treatment. Similarly, in RA, analysis of baseline samples resulted in a list of 30 probe sets that differentiated responders from non-responders. Expression of 3 genes; AQP9, IGJ and TNFAIP6 showed significant difference between baseline and week 2 samples. Results were validated by RT-QPCR on independent patient cohorts in both diseases. CVA analysis yielded to 15 and 12 genes in RA and CD, respectively, showing the best discriminatory power between responders and non-responders in both diseases, however there was no overlap between these two gene lists. Conclusions We provided two pieces of proof of concept evidence showing that 1) peripheral blood gene expression profiles are suitable for determining gene panels with the highest discriminatory power in order to differentiate responders and non-responders in a patient cohort in CD and RA; and 2) distinct, non-overlapping gene panels are required for the prediction of the responder status in CD and RA despite the fact that these conditions have similar pathogenic background. Application of such gene panels could solve unmet needs in the clinical settings by determining specific responses to expensive biological therapies.

Combination of peripheral blood gene expression profiles and clinical parameters predicts response to tocilizumab treatment in rheumatoid arthritis

Background and objectives Tocilizumab, a humanised anti-interleukin 6 receptor monoclonal antibody, has recently been approved as a biologic therapy for rheumatoid arthritis and other diseases. It is not known if there are characteristic gene expression changes following therapy and if such alterations alone or in combination with clinical parameters can be used to predict responses. Materials and methods Global gene expression profiles from peripheral blood mononuclear cells of 13 rheumatoid arthritis patients with active disease at week 0 and 4 following treatment were obtained as well as clinical parameters and serum cytokine levels using ELISA. Gene sets separating responders and non-responders were created by using Canonical Variates Analysis. This approach also revealed important gene groups and pathways that differentiate responders from non-responders. Results Altogether 59 genes showed significant differences between week 0 and 4; and four genes (CCDC32, DHFR, EPHA4, TRAV8-3) separated responders from non-responders after multiple-testing correction. Genes correlating with disease activity and the responder status based on a novel scoring system were also found. 10 of the 12 genes with the most significant changes were validated using RT-QPCR. Conclusions This is the first instance that the gene expression changes as the result of tocilizumab therapy were examined and gene sets discriminating between responders and non-responders found and validated. This data also show that the use of the combination of a clinical score system along with Canonical Variates Analysis are likely to help predict responder status from peripheral blood in rheumatoid arthritis.