Genetic variants within the MAP kinase signalling network and anti-TNF treatment response in rheumatoid arthritis patients

Towards Personalized Medicine in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a chronic, incurable, multisystem, inflammatory disease characterized by synovitis and extra-articular features. Although several advanced therapies targeting inflammatory mechanisms underlying the disease are available, no advanced therapy is universally effective. Therefore, a ceiling of treatment response is currently accepted where no advanced therapy is superior to another. The current challenge for medical research is the discovery and integration of predictive markers of drug response that can be used to personalize medicine so that the patient is started on "the right drug at the right time". This review article summarizes our current understanding of predicting response to anti-rheumatic drugs in RA, obstacles impeding the development of personalized medicine approaches and future research priorities to overcome these barriers.

Study on the mechanism of action of Saposhnikovia divaricata and its key phytochemical on rheumatoid arthritis based on network pharmacology and bioinformatics

ETHNOPHARMACOLOGICAL RELEVANCE

Saposhnikovia divaricata (Turcz.) Schischk (SD; called "fangfeng" in China) has been widely used in the clinical treatment of rheumatoid arthritis (RA) and has shown well therapeutic effects, but the specific mechanisms of action of its bioactive phytochemicals remain unclear.

AIM OF THE STUDY

This study aimed to investigate the molecular biological mechanism of SD in treating RA through a pharmacology-based strategy. The SD-specific core ingredient Prangenidin was screened for further in-depth study.

MATERIALS AND METHODS

The bioactive phytochemicals of SD and potential targets for the treatment of RA were screened by network pharmacology, and phytochemicals-related parameters such as pharmacology, and toxicology were evaluated. The protein interaction network was established to screen the core targets, and the correlation between the core targets and RA was further validated by bioinformatics strategy. Finally, molecular docking of core components and corresponding targets was performed. The in vitro experiments were performed to elucidate the regulation of Prangenidin on MH7A cells and on the PI3K/AKT pathway, and the in vivo therapeutic effect of Prangenidin was validated in collagen-induced arthritis (CIA) mice.

RESULTS

A total of 18 bioactive phytochemicals and 66 potential target genes intersecting with the screened RA disease target genes were identified from SD. Finally, core ingredients such as wogonin, beta-sitosterol, 5-O-Methylvisamminol, and prangenidin and core targets such as PTGS2, RELA, and AKT1 were obtained. The underlying mechanism of SD in treating RA might be achieved by regulating pathways such as PI3K/AKT, IL-17 pathway, apoptosis, and multiple biological processes to exert anti-inflammatory and immunomodulatory effects. Molecular docking confirmed that all core ingredients and key targets had great docking activity. Prangenidin inhibited viability, migration, and invasion, and induced apoptosis in MH7A cells. Prangenidin also reduced the production of IL-1β, IL-6, IL-8, MMP-1, and MMP-3. Molecular analysis showed that Prangenidin exerts its regulatory effect on MH7A cells by inhibiting PI3K/AKT pathway. Treatment with Prangenidin ameliorated synovial inflammation in the joints of mice with CIA.

CONCLUSION

Our findings provide insights into the therapeutic effects of SD on RA, successfully predicting the effective ingredients and potential targets, which could suggest a novel theoretical basis for further exploration of its molecular mechanisms. It also revealed that Prangenidin inhibited viability, migration, invasion, cytokine, and MMPs expression, and induced apoptosis in RA FLSs via the PI3K/AKT pathway.

Association of caspase-1 gene polymorphisms with rheumatoid arthritis risk in a Chinese Han population

The goals of present research are to investigate if the genetic polymorphisms in the caspase-1 (CASP1) gene are associated with the risk of rheumatoid arthritis (RA) and the clinical characteristics of the illness in Han patients from China. Our team studied the CASP1 rs2409062 A/G polymorphisms in 1095 healthy controls and 805 RA patients, while the genotype was identified via a custom-by-design 48-Plex single nucleotide polymorphism (SNP) scan™ Kit. The mRNA expression levels of the CASP1 in 40 RA cases and 40 healthy controls were detected by qRT-PCR, while blood plasma levels of the CASP1 in 40 RA cases and 40 paired controls measured via ELISA. Our research showed that the CASP1 rs2409062 A/G polymorphisms were related to an elevated risk for RA. By stratified analysis, our team discovered a remarkably elevated RA risk in females sufferers, age ≥ 55, CRP-positive, or DAS28 < 3.20. In contrast to the control group, the mean level of CASP1 protein in the plasma of RA cases rised significantly. Moreover, RA cases displayed significantly greater levels of CASP1 mRNA versus the control group (P < 0.05). Those outcomes reveal that the CASP1 rs2409062 A/G gene polymorphisms are associated with an elevated risk for RA in a Chinese Han population.

Gene Ontology Analysis Highlights Biological Processes Influencing Non-Response to Anti-TNF Therapy in Rheumatoid Arthritis

Anti-TNF therapy has significantly improved disease control in rheumatoid arthritis, but a fraction of rheumatoid arthritis patients do not respond to anti-TNF therapy or lose response over time. Moreover, the mechanisms underlying non-response to anti-TNF therapy remain largely unknown. To date, many single biomarkers of response to anti-TNF therapy have been published but they have not yet been analyzed as a system of interacting nodes. The aim of our study is to systematically elucidate the biological processes underlying non-response to anti-TNF therapy in rheumatoid arthritis using the gene ontologies of previously published predictive biomarkers. Gene networks were constructed based on published biomarkers and then enriched gene ontology terms were elucidated in subgroups using gene ontology software tools. Our results highlight the novel role of proteasome-mediated protein catabolic processes (p = 2.91 × 10⁻¹⁵) and plasma lipoproteins (p = 4.55 × 10⁻¹¹) in anti-TNF therapy response. The results of our gene ontology analysis help elucidate the biological processes underlying non-response to anti-TNF therapy in rheumatoid arthritis and encourage further study of the highlighted processes.

Pharmacogenetics of Drug Therapies in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a chronic systemic inflammatory disorder that can lead to severe joint damage and is often associated with a high morbidity and disability. Disease-modifying anti-rheumatic drugs (DMARDs) are the mainstay of treatment in RA. DMARDs not only relieve the clinical signs and symptoms of RA but also inhibit the radiographic progression of disease and reduce the effects of chronic systemic inflammation. Since the introduction of biologic DMARDs in the late 1990s, the therapeutic range of options for the management of RA has significantly expanded. However, patients' response to these agents is not uniform with considerable variability in both efficacy and toxicity. There are no reliable means of predicting an individual patient's response to a given DMARD prior to initiation of therapy. In this chapter, the current published literature on the pharmacogenetics of traditional DMARDS and the newer biologic DMARDs in RA is highlighted. Pharmacogenetics may help individualize drug therapy in patients with RA by providing reliable biomarkers to predict medication toxicity and efficacy.

IFN-γ Drives Human Monocyte Differentiation into Highly Proinflammatory Macrophages That Resemble a Phenotype Relevant to Psoriasis

As key cells of the immune system, macrophages coordinate the activation and regulation of the immune response. Macrophages present a complex phenotype that can vary from homeostatic, proinflammatory, and profibrotic to anti-inflammatory phenotypes. The factors that drive the differentiation from monocyte to macrophage largely define the resultant phenotype, as has been shown by the differences found in M-CSF- and GM-CSF-derived macrophages. We explored alternative inflammatory mediators that could be used for in vitro differentiation of human monocytes into macrophages. IFN-γ is a potent inflammatory mediator produced by lymphocytes in disease and infections. We used IFN-γ to differentiate human monocytes into macrophages and characterized the cells at a functional and proteomic level. IFN-γ alone was sufficient to generate macrophages (IFN-γ Mϕ) that were phagocytic and responsive to polarization. We demonstrate that IFN-γ Mϕ are potent activators of T lymphocytes that produce IL-17 and IFN-γ. We identified potential markers (GBP-1, IP-10, IL-12p70, and IL-23) of IFN-γ Mϕ and demonstrate that these markers are enriched in the skin of patients with inflamed psoriasis. Collectively, we show that IFN-γ can drive human monocyte to macrophage differentiation, leading to bona fide macrophages with inflammatory characteristics.

Integrated strategy of LC-MS and network pharmacology for predicting active constituents and pharmacological mechanisms of Ranunculus japonicus Thunb. for treating rheumatoid arthritis

ETHNOPHARMACOLOGICAL RELEVANCE

Ranunculus japonicus Thunb. (short for R. japonicus) is a topically applied herb with the activities of removing jaundice, nebula and edema, preventing malaria, stopping asthma, promoting diuresis and relieving pain. It was firstly recorded in Zhouhou Beiji Fang and has been used for the treatment of malaria, ulcers, carbuncle, jaundice, migraine, stomachache, toothache and arthritis for over 1800 years.

AIM OF THE STUDY

This study aimed to uncover the potentially effective components of R. japonicus and the pharmacological mechanisms against rheumatoid arthritis (RA) by combing LC-MS and network pharmacology.

MATERIALS AND METHODS

Firstly, the chemical constituents of R. japonicus were qualitatively identified by UPLC-ESI-LTQ-Orbitrap MS. Then we performed target prediction by PharmMapper, protein-protein interaction (PPI) analysis via String, GO and KEGG pathway enrichment analysis by DAVID and constructed the compound-target-pathway network using Cytoscape. Thirdly, crucial compounds in the network were quantitatively analyzed to achieve quality control of R. japonicus. Finally, the pharmacological activities of R. japonicus and two potentially bioactive ingredients were validated in RA-FLSs (Rheumatoid Arthritis Fibroblast-like Synoviocytes) in vitro.

RESULTS

Overall fifty-four ingredients of R. japonicus were identified and forty-five components were firstly discovered in R. japonicus. Among them, twenty-seven validated compounds were predicted to act on twenty-five RA-related targets and they might exhibit therapeutic effects against RA via positive regulation of cell migration, etc. Nine potentially bioactive components of R. japonicus which played important roles in the compound-target-pathway network were simultaneously quantified by an optimized UPLC-ESI-Triple Quad method. In vitro, compared to control group, R. japonicus extract, berberine and yangonin significantly inhibited the migration capacity of RA-FLSs after 24 h treatment.

CONCLUSION

This study clarified that R. japonicus and the bioactive ingredients berberine and yangonin might exert therapeutic actions for RA via suppressing the aggressive phenotypes of RA-FLSs through combined LC-MS technology and network pharmacology tools for the first time. The present research provided deeper understanding into the chemical profiling, pharmacological activities and quality control of R. japonicus and offered reference for further scientific research and clinical use of R. japonicus in treating RA.

Development of IFN-Stimulated Gene Expression from Embryogenesis through Adulthood, with and without Constitutive MDA5 Pathway Activation

Pathogen-associated molecular patterns (e.g., dsRNA) activate expression of IFN-stimulated genes (ISGs), which protect hosts from infection. Although transient ISG upregulation is essential for effective innate immunity, constitutive activation typically causes harmful autoimmunity in mice and humans, often including severe developmental abnormalities. We have shown that transgenic mice expressing a picornavirus RNA-dependent RNA polymerase (RdRP) outside the viral context (RdRP mice) exhibit constitutive, MDA5-dependent, and quantitatively dramatic upregulation of many ISGs, which confers broad viral infection resistance. Remarkably, RdRP mice never develop autoinflammation, interferonopathy, or other discernible abnormalities. In this study, we used RNA sequencing and other methods to analyze ISG expression across five time points from fetal development to adulthood in wild-type and RdRP mice. In RdRP mice, the proportion of upregulated ISGs increased during development, with the most dramatic induction occurring 2 wk postnatally. The amplified ISG profile is then maintained lifelong. Molecular pathways and biological functions associated with innate immune and IFN signaling are only activated postnatally, suggesting constrained fetal responsiveness to innate immune stimuli. Biological functions supporting replication of viruses are only inhibited postnatally. We further determined that the RdRP is expressed at low levels and that blocking Ifnar1 reverses the amplified ISG transcriptome in adults. In conclusion, the upregulated ISG profile of RdRP mice is mostly triggered early postnatally, is maintained through adulthood, and requires ongoing type I IFN signaling to maintain it. The model provides opportunities to study the systems biology of innate immunity and to determine how sustained ISG upregulation can be compatible with robust health.

Meta-Analysis of Transcriptomic Data of Dorsolateral Prefrontal Cortex and of Peripheral Blood Mononuclear Cells Identifies Altered Pathways in Schizophrenia

Schizophrenia (SCZ) is a psychiatric disorder characterized by both positive and negative symptoms, including cognitive dysfunction, decline in motivation, delusion and hallucinations. Antipsychotic agents are currently the standard of care treatment for SCZ. However, only about one-third of SCZ patients respond to antipsychotic medications. In the current study, we have performed a meta-analysis of publicly available whole-genome expression datasets on Brodmann area 46 of the brain dorsolateral prefrontal cortex in order to prioritize potential pathways underlying SCZ pathology. Moreover, we have evaluated whether the differentially expressed genes in SCZ belong to specific subsets of cell types. Finally, a cross-tissue comparison at both the gene and functional level was performed by analyzing the transcriptomic pattern of peripheral blood mononuclear cells of SCZ patients. Our study identified a robust disease-specific set of dysfunctional biological pathways characterizing SCZ patients that could in the future be exploited as potential therapeutic targets.

<p>ADAM17 Genetic Variants and the Response of TNF-α Inhibitor in Rheumatoid Arthritis Patients</p>

Purpose

TNF-α is a transmembrane protein which requires cleavage by ADAM17 in order to act systemically. The activation of ADAM17 to generate soluble TNF‑α results in an increased inflammatory activity. We hypothesized that variants spanning the ADAM17 gene contribute towards the observed variation in patient response defined by the number of changes in TNF‑α inhibitors.

Patients and Methods

Seven single-nucleotide polymorphisms (SNPs) of ADAM17 in 63 patients with rheumatoid arthritis who received TNF-α inhibitors were analyzed: rs57467365, rs62117540, rs117645314, rs6432013, rs532704607, rs117179141, and rs12692386. Univariate and multivariate regression analysis were employed to investigate the independent predictable factors for changes in TNF-α inhibitors.

Results

ADAM17 rs117645314 and rs117179141 showed significant association with the number of changes in TNF-α inhibitors. Patients with GA in rs117645314 and AT in rs117179141 had significantly higher chance of two or more changes of TNF-α inhibitors than those with wild homozygous alleles. Multivariate analysis showed that rs117179141 explained 5.7% of the 23.8% variability in TNF-α inhibitor response.

Conclusion

This study showed that the number of changes in TNF-α inhibitor is associated with ADAM17 SNPs.

The Potential Role of Genomic Medicine in the Therapeutic Management of Rheumatoid Arthritis

During the last decade, important advances have occurred regarding understanding of the pathogenesis and treatment of rheumatoid arthritis (RA). Nevertheless, response to treatment is not universal, and choosing among different therapies is currently based on a trial and error approach. The specific patient’s genetic background influences the response to therapy for many drugs: In this sense, genomic studies on RA have produced promising insights that could help us find an effective therapy for each patient. On the other hand, despite the great knowledge generated regarding the genetics of RA, most of the investigations performed to date have focused on identifying common variants associated with RA, which cannot explain the complete heritability of the disease. In this regard, rare variants could also contribute to this missing heritability as well as act as biomarkers that help in choosing the right therapy. In the present article, different aspects of genetics in the pathogenesis and treatment of RA are reviewed, from large-scale genomic studies to specific rare variant analyses. We also discuss the shared genetic architecture existing among autoimmune diseases and its implications for RA therapy, such as drug repositioning.

Expression levels of selected genes can predict individual rheumatoid arthritis patient response to tumor necrosis factor alpha blocker treatment

OBJECTIVES

Rheumatoid arthritis (RA) patients have many therapeutic options; however, tools to predict individual patient response are limited. The Genefron personal diagnostic kit, developed by analyzing large datasets, utilizes selected interferon stimulated gene expressions to predict treatment response. This study evaluates the kit's prediction accuracy of individual RA patients' response to tumor necrosis alpha (TNFα) blockers.

METHODS

A retrospective analysis was performed on RA patients reported in published datasets. A prospective analysis assessed RA patients, before and 3 months after starting a TNFα blocker. Clinical response was evaluated according to EULAR response criteria. Blood samples were obtained before starting treatment and were analyzed utilizing the kit which measures expression levels of selected genes by quantitative real time polymerase chain reaction (PCR). ROC analysis was applied to the published datasets and the prospective data.

RESULTS

The Genefron kit analysis of retrospective data predicted the response to a TNFα blocker in 53 of 61 RA patients (86.8% accuracy). In the prospective analysis, the kit predicted the response in 16 of 18 patients (89% accuracy) achieving a EULAR moderate response, and in 15 of 18 patients achieving a EULAR good response (83.3% accuracy). ROC analysis applied to the two published datasets yielded an AUC of 0.89. ROC analysis applied to the prospective data yielded an AUC of 0.83 (sensitivity - 100%, specificity - 75%) The statistical power obtained in the prospective study was .9.

CONCLUSION

The diagnostic kit predicted the response to TNFα blockers in a high percentage of patients assessed retrospectively or prospectively. This personal kit may guide selection of a suitable biological drug for the individual RA patient.

Optimal search strategies for identifying moderators and predictors of treatment effects in PubMed

BACKGROUND

Treatment effects differ across patients. To guide selection of treatments for patients, it is essential to acknowledge these differences and identify moderators or predictors. Our aim was to generate optimal search strategies (commonly known as filters) for PubMed to retrieve papers identifying moderators and predictors of treatment effects.

METHODS

Six journals were hand-searched for articles on moderators or predictors. Selected articles were randomly allocated to a development and validation set. Search terms were extracted from the development set and tested for their performance. Search filters were created from combinations of these terms and tested in the validation set.

RESULTS

Of 4407 articles, 198 were considered to be relevant. The most sensitive filter in the development set '("Epidemiologic Methods" [MeSH] OR assign* OR control*[tiab] OR trial*[tiab]) AND therapy*[sh]' yielded in the validation set a sensitivity of 89% [88%-90%] and a specificity of 80% [79%-82%].

CONCLUSIONS

The search filters created in this study can help to efficiently retrieve evidence on moderators and predictors of treatment effect. Testing of the filters in multiple domains should reveal robustness across disciplines. These filters can facilitate the retrieval of evidence on moderators and predictors of treatment effects, helping the implementation of stratified or personalised health care.

Systems Pharmacology Dissection of Multiscale Mechanisms of Action for Herbal Medicines in Treating Rheumatoid Arthritis

As a chronic inflammatory and angiogenic disease with increased morbidity and mortality, rheumatoid arthritis (RA) is characterized by the proliferation of synovial tissue and the accumulation of excessive mononuclear infiltration, which always results in the joint deformity, disability, and eventually the destruction of the bone and cartilage. Traditional Chinese Medicine (TCM), with rich history of proper effectiveness in treating the inflammatory joint disease containing RA, has long combated such illness from, actually, an integrative and holistic point of view. However, its "multi-components" and "multi-targets" features make it very difficult to decipher the molecular mechanisms of RA from a systematic perspective if employing only routine methods. Presently, an innovative systems-pharmacology approach was introduced, which combined the ADME screening model, drug targeting, and network pharmacology, to explore the action mechanisms of botanic herbs for the treatment of RA. As a result, we uncovered 117 active compounds and 85 key molecular targets from seven RA-related herbs, which are mainly implicated in four signaling pathways, that is, vascular endothelial growth factor, PI3K-Akt, Toll-like receptor, and T-cell-receptor pathways. Additionally, the network relationships among the active components, target proteins, and pathways were further built to uncover the pharmacological characters of these herbs. Besides, molecular dynamics (MD) simulations and molecular mechanics-Poisson-Boltzmann surface area calculations were carried out to explore the binding interactions between the compounds and their receptors as well as to investigate the binding affinity of the ligand to their protein targets. In vitro experiments by ligand binding assays validate the reliability of the drug-target interactions as well as the MD results. The high binding affinities and good inhibitions of the active compounds indicate that the potential therapeutic effects of these herbal medicines for treating RA are exerted probably through the modulation of these relevant proteins, which further validates the rationality and reliability of the drug-target interactions as well as our the network-based analytical methods. This work may be of help for not only understanding the action mechanisms of TCM and for discovering new drugs from plants for the treatment of RA, but also providing a novel potential method for modern medicine in treating complex diseases.

Systematic review and meta-analysis: pharmacogenetics of anti-TNF treatment response in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic inflammatory disease that affects ~1% of the Caucasian population. Over the last decades, the availability of biological drugs targeting the proinflammatory cytokine tumour necrosis factor α, anti-TNF drugs, has improved the treatment of patients with RA. However, one-third of the patients do not respond to the treatment. We wanted to evaluate the status of pharmacogenomics of anti-TNF treatment. We performed a PubMed literature search and all studies reporting original data on associations between genetic variants and anti-TNF treatment response in RA patients were included and results evaluated by meta-analysis. In total, 25 single nucleotide polymorphisms were found to be associated with anti-TNF treatment response in RA (19 from genome-wide association studies and 6 from the meta-analyses), and these map to genes involved in T cell function, NFκB and TNF signalling pathways (including CTCN5, TEC, PTPRC, FCGR2A, NFKBIB, FCGR2A, IRAK3). Explorative prediction analyses found that biomarkers for clinical treatment selection are not yet available.

Application of omics in predicting anti-TNF efficacy in rheumatoid arthritis

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by progressive joint erosion. Tumor necrosis factor (TNF) antagonists are the most widely used biological disease-modifying anti-rheumatic drug in RA. However, there continue to be one third of RA patients who have poor or no response to TNF antagonists. Following consideration of the uncertainty of therapeutic effects and the high price of TNF antagonists, it is worthy to predict the treatment responses before anti-TNF therapy. According to the comparisons between the responders and non-responders to TNF antagonists by omic technologies, such as genomics, transcriptomics, proteomics, and metabolomics, rheumatologists are eager to find significant biomarkers to predict the effect of TNF antagonists in order to optimize the personalized treatment in RA.

Genome-wide association studies and gene expression profiles of rheumatoid arthritis: An analysis

OBJECTIVES

The molecular mechanism of rheumatoid arthritis (RA) remains elusive. We conducted a protein-protein interaction network-based integrative analysis of genome-wide association studies (GWAS) and gene expression profiles of RA.

METHODS

We first performed a dense search of RA-associated gene modules by integrating a large GWAS meta-analysis dataset (containing 5539 RA patients and 20 169 healthy controls), protein interaction network and gene expression profiles of RA synovium and peripheral blood mononuclear cells (PBMCs). Gene ontology (GO) enrichment analysis was conducted by DAVID. The protein association networks of gene modules were generated by STRING.

RESULTS

For RA synovium, the top-ranked gene module is HLA-A, containing TAP2, HLA-A, HLA-C, TAPBP and LILRB1 genes. For RA PBMCs, the top-ranked gene module is GRB7, consisting of HLA-DRB5, HLA-DRA, GRB7, CD63 and KIT genes. Functional enrichment analysis identified three significant GO terms for RA synovium, including antigen processing and presentation of peptide antigen via major histocompatibility complex class I (false discovery rate (FDR) = 4.86 × 10 - 4), antigen processing and presentation of peptide antigen (FDR = 2.33 × 10 - 3) and eukaryotic translation initiation factor 4F complex (FDR = 2.52 × 10 - 2).

CONCLUSION

This study reported several RA-associated gene modules and their functional association networks.Cite this article: X. Xiao, J. Hao, Y. Wen, W. Wang, X. Guo, F. Zhang. Genome-wide association studies and gene expression profiles of rheumatoid arthritis: an analysis. Bone Joint Res 2016;5:314-319. DOI: 10.1302/2046-3758.57.2000502.

A Personalized Approach to Biological Therapy Using Prediction of Clinical Response Based on MRP8/14 Serum Complex Levels in Rheumatoid Arthritis Patients

Objectives

Measurement of MRP8/14 serum levels has shown potential in predicting clinical response to different biological agents in rheumatoid arthritis (RA). We aimed to develop a treatment algorithm based on a prediction score using MRP8/14 measurements and clinical parameters predictive for response to different biological agents.

Methods

Baseline serum levels of MRP8/14 were measured in 170 patients starting treatment with infliximab, adalimumab or rituximab. We used logistic regression analysis to develop a predictive score for clinical response at 16 weeks. MRP8/14 levels along with clinical variables at baseline were investigated. We also investigated how the predictive effect of MRP8/14 was modified by drug type. A treatment algorithm was developed based on categorizing the expected response per drug type as high, intermediate or low for each patient and optimal treatment was defined. Finally, we present the utility of using this treatment algorithm in clinical practice.

Results

The probability of response increased with higher baseline MRP8/14 complex levels (OR = 1.39), differentially between the TNF-blockers and rituximab (OR of interaction term = 0.78), and also increased with higher DAS28 at baseline (OR = 1.28). Rheumatoid factor positivity, functional disability (a higher HAQ), and previous use of a TNF-inhibitor decreased the probability of response. Based on the treatment algorithm 80 patients would have been recommended for anti-TNF treatment, 8 for rituximab, 13 for another biological treatment (other than TNFi or rituximab) and for 69 no recommendation was made. The predicted response rates matched the observed response in the cohort well. On group level the predicted response based on the algorithm resulted in a modest 10% higher response rate in our cohort with much higher differences in response probability in individual patients treated contrary to treatment recommendation.

Conclusions

Prediction of response using MRP8/14 levels along with clinical predictors has potential in personalizing treatment for RA patients starting biological anti-rheumatic treatment, and might increase cost-effectiveness.

Genetic data: The new challenge of personalized medicine, insights for rheumatoid arthritis patients

Rapid advances in genotyping technology, analytical methods, and the establishment of large cohorts for population genetic studies have resulted in a large new body of information about the genetic basis of human rheumatoid arthritis (RA). Improved understanding of the root pathogenesis of the disease holds the promise of improved diagnostic and prognostic tools based upon this information. In this review, we summarize the nature of new genetic findings in human RA, including susceptibility loci and gene-gene and gene-environment interactions, as well as genetic loci associated with sub-groups of patients and those associated with response to therapy. Possible uses of these data are discussed, such as prediction of disease risk as well as personalized therapy and prediction of therapeutic response and risk of adverse events. While these applications are largely not refined to the point of clinical utility in RA, it seems likely that multi-parameter datasets including genetic, clinical, and biomarker data will be employed in the future care of RA patients.

A longitudinal genome-wide association study of anti-tumor necrosis factor response among Japanese patients with rheumatoid arthritis

Background

Studies of Caucasian patients with rheumatoid arthritis (RA) to identify genetic biomarkers of anti-tumor necrosis factor (TNF) response have used response at a single time point as the phenotype with which single nucleotide polymorphism (SNP) associations have been tested. The findings have been inconsistent across studies. Among Japanese patients, only a few SNPs have been investigated. We report here the first genome-wide association study (GWAS) to identify genetic biomarkers of anti-TNF response among Japanese RA patients, using response at 2 time-points for a more reliable clinical phenotype over time.

Methods

Disease Activity Scores based on 28 joint counts (DAS28) were assessed at baseline (before initial therapy), and after 3 and 6 months in 487 Japanese RA patients starting anti-TNF therapy for the first time or switching to a new anti-TNF agent. A genome-wide panel of SNPs was genotyped and additional SNPs were imputed. Using change in DAS28 scores from baseline at both 3 (ΔDAS-3) and 6 months (ΔDAS-6) as the response phenotype, a longitudinal genome-wide association analysis was conducted using generalized estimating equations (GEE) models, adjusting for baseline DAS28, treatment duration, type of anti-TNF agent and concomitant methotrexate. Cross-sectional analyses were performed using multivariate linear regression models, with response from a single time point (ΔDAS-3 or ΔDAS-6) as phenotype; all other variables were the same as in the GEE models.

Results

In the GEE models, borderline significant association was observed at 3 chromosomal regions (6q15: rs284515, p = 6.6x10⁻⁷; 6q27: rs75908454, p = 6.3x10⁻⁷ and 10q25.3: rs1679568, p = 8.1x10⁻⁷), extending to numerous SNPs in linkage disequilibrium (LD) across each region. Potential candidate genes in these regions include MAP3K7, BACH2 (6q15), GFRA1 (10q25.3), and WDR27 (6q27). The association at GFRA1 replicates a previous finding from a Caucasian dataset. In the cross-sectional analyses, ΔDAS-6 was significantly associated with the 6q15 locus (rs284511, p = 2.5x10⁻⁸). No other significant or borderline significant associations were identified.

Conclusion

Three genomic regions demonstrated significant or borderline significant associations with anti-TNF response in our dataset of Japanese RA patients, including a locus previously associated among Caucasians. Using repeated measures of response as phenotype enhanced the power to detect these associations.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-016-0920-6) contains supplementary material, which is available to authorized users.

Personalized biological treatment for rheumatoid arthritis: a systematic review with a focus on clinical applicability

OBJECTIVES

To review studies that address prediction of response to biologic treatment in RA and to explore the clinical utility of the studied (bio)markers.

METHODS

A search for relevant articles was performed in PubMed, Embase and Cochrane databases. Studies that presented predictive values or in which these could be calculated were selected. The added value was determined by the added value on prior probability for each (bio)marker. Only an increase/decrease in chance of response ⩾15% was considered clinically relevant, whereas in oncology values >25% are common.

RESULTS

Of the 57 eligible studies, 14 (bio)markers were studied in more than one cohort and an overview of the added predictive value of each marker is presented. Of the replicated predictors, none consistently showed an increase/decrease in probability of response ⩾15%. However, positivity of RF and ACPA in case of rituximab and the presence of the TNF-α promoter 308 GG genotype for TNF inhibitor therapy were consistently predictive, yet low in added predictive value. Besides these, 65 (bio)markers studied once showed remarkably high (but not validated) predictive values.

CONCLUSION

We were unable to address clinically useful baseline (bio)markers for use in individually tailored treatment. Some predictors are consistently predictive, yet low in added predictive value, while several others are promising but await replication. The challenge now is to design studies to validate all explored and promising findings individually and in combination to make these (bio)markers relevant to clinical practice.

Role of mitogen- and stress-activated kinases in inflammatory arthritis

Lysophosphatidic acid (LPA) is a pleiotropic lipid mediator that promotes motility, survival, and the synthesis of chemokines/cytokines in human fibroblast-like synoviocytes (FLS) from patients with rheumatoid arthritis. LPA activates several proteins within the mitogen activated protein (MAP) kinase signaling network, including extracellular signal-regulated kinases (ERK) 1/2 and p38 MAP kinase (MAPK). Upon docking to mitogen- and stress-activated kinases (MSKs), ERK1/2 and p38 MAPK phosphorylate serine and threonine residues within its C-terminal domain and cause autophosphorylation of MSKs. Activated MSKs can then directly phosphorylate cAMP response element-binding protein (CREB) at Ser133 in FLS. Phosphorylation of CREB by MSKs is essential for the production of pro-inflammatory and anti-inflammatory cytokines. However, other downstream effectors of MSK1/2 such as nuclear factor-kappa B, histone H3, and high mobility group nucleosome binding domain 1 may also regulate gene expression in immune cells involved in disease pathogenesis. MSKs are master regulators of cell function that integrate signals induced by growth factors, pro-inflammatory cytokines, and cellular stresses, as well as those induced by LPA.

Genetic Polymorphisms of IL-17F and TRAF3IP2 Could Be Predictive Factors of the Long-Term Effect of Infliximab against Crohn's Disease

Background. We aimed to identify certain genes related to response to infliximab (IFX) and biomarkers to predict the IFX effect for Japanese Crohn's disease (CD) patients by performing an association study of single nucleotide polymorphisms (SNPs) in candidate genes in the interleukin- (IL-) 17 signaling pathway with response to IFX after 1 year of treatment. Methods. A total of 103 patients were divided into two groups, responders and nonresponders. Twenty-eight tag SNPs in 5 genes were genotyped. The frequencies of alleles and genotypes of each SNP were compared between responders and nonresponders in three different inheritance models. A genetic test was performed using a combination of the associated SNPs as biomarkers. Results. Multivariate logistic regression analysis indicated that the four variable factors, concomitant use of immunomodulators, penetrating disease, a G/G genotype of rs766748 in IL-17F, and a C/C or C/A genotype of rs1883136 in TRAF3IP2, independently contributed to response to IFX after 1 year of treatment. Genetic test using the polymorphisms of these genes perfectly predicted the responder and nonresponder CD patients with both concomitant use of immunomodulators and penetrating disease. Conclusion. IL17F and TRAF3IP2 are one of IFX-related genes, useful as biomarkers of IFX response, and may be target molecules for new therapeutic drugs.

Replication of PTPRC as genetic biomarker of response to TNF inhibitors in patients with rheumatoid arthritis

Genetic biomarkers could be useful for orienting treatment of patients with rheumatoid arthritis (RA), but none has been convincingly validated yet. Putative biomarkers include 14 single nucleotide polymorphisms that have shown association with response to TNF inhibitors (TNFi) in candidate gene studies and that we assayed here in 755 RA patients. Three of them, in the PTPRC, IL10 and CHUK genes, were significantly associated with response to TNFi. The most significant result was obtained with rs10919563 in PTPRC, which is a confirmed RA susceptibility locus. Its RA risk allele was associated with improved response (B=0.33, P=0.006). This is the second independent replication of this biomarker (P=9.08 × 10(-8) in the combined 3003 RA patients). In this way, PTPRC has become the most replicated genetic biomarker of response to TNFi. In addition, the positive but weaker replication of IL10 and CHUK should stimulate further validation studies.

Haptoglobin-α1, -α2, vitamin D-binding protein and apolipoprotein C-III as predictors of etanercept drug response in rheumatoid arthritis

Introduction

The introduction of tumor necrosis factor-alpha (TNF-α) antagonists has substantially improved patient’s clinical outcome in rheumatoid arthritis (RA). However, nearly 20% to 40% of RA patients do not respond to anti-TNF-α treatment strategies. To identify valid predictors of TNF-α antagonist response in RA, serum proteome profiles from responders (R) and non-responders (NR) to etanercept, a soluble recombinant TNF-α receptor/IgG Fc fusion protein receptor, were compared in a prospective cohort study.

Methods

In this clinical study 50 RA patients with inadequate response to conventional DMARDs were included and treated with etanercept. The primary efficacy endpoint was response according to the European League against Rheumatism (EULAR) improvement criteria. Serum samples collected prior to initiation and after six months of etanercept therapy were cleared of the most abundant major proteins by immunoaffinity chromatography. After separation by two-dimensional differential gel electrophoresis (2D-DIGE) and identification by mass spectrometry (MS) data were validated by Western blot analysis.

Results

After six months of etanercept treatment 62% (n = 31) of RA patients achieved response. Haptoglobin-α1 (Hp-α1) and -α2 (Hp-α2) and vitamin D-binding protein (VDBP) were found to be significantly upregulated in responder sera (P ≤0.02) at study entry. In contrast, apolipoprotein C-III (ApoC-III) showed significantly higher levels in non-responders (P = 0.0162). At study end ApoA-II, Hp-α1, Hp-α2 and VDBP were identified to be expressed at significantly higher levels (P <0.05) in responder sera.

Conclusions

By application of clinical proteomics in immunodepleted sera we could identify and validate for the first time Hp-α1, -α2, VDBP and ApoC-III as potential biomarkers for prediction of etanercept drug response in RA.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-015-0553-1) contains supplementary material, which is available to authorized users.

Prognostic role of apoptosis-related gene functional variants in advanced non-small-cell lung cancer patients treated with first-line platinum-based chemotherapy

Background

Single-nucleotide polymorphisms in apoptosis-related genes have been shown to play a role in the efficacy of platinum-based chemotherapy and may influence clinical outcomes. Our study aimed to evaluate the correlations of four functional single-nucleotide polymorphisms − FAS −670 A>G, FAS ligand −844 T>C, survivin −31 G>C, and survivin 9386 C>T – with drug response and clinical outcomes in advanced non-small-cell lung cancer patients who received platinum-based chemotherapy.

Materials and methods

Polymorphisms were evaluated using the polymerase chain reaction-based restriction fragment-length polymorphism technique.

Results

Patients with the CC genotype of FAS −670 A>G had worse overall survival (OS) than those with the CT or TT genotype (P=0.044), with median OS values of 20.1 months, 22.8 months, and 26.0 months, respectively. Furthermore, progression-free survival was associated with the FAS −670 A>G polymorphism (P=0.032). In addition, patients with the TC and CC genotypes of survivin 9386 C>T experienced improved survival compared with patients with the TT genotype (median OS 31.4 months and 22.8 months, respectively).

Conclusion

The functional FAS −670 A>G and survivin 9386 C>T polymorphisms are potential independent prognostic factors in advanced non-small-cell lung cancer patients treated with platinum-based chemotherapy.

Current and future trends in biomarker discovery and development of companion diagnostics for arthritis

Musculoskeletal diseases such as rheumatoid arthritis are complex multifactorial disorders that are chronic in nature and debilitating for patients. A number of drug families are available to clinicians to manage these disorders but few tests exist to target these to the most responsive patients. As a consequence, drug failure and switching to drugs with alternate modes of action is common. In parallel, a limited number of laboratory tests are available which measure biological indicators or 'biomarkers' of disease activity, autoimmune status, or joint damage. There is a growing awareness that assimilating the fields of drug selection and diagnostic tests into 'companion diagnostics' could greatly advance disease management and improve outcomes for patients. This review aims to highlight: the current applications of biomarkers in rheumatology with particular focus on companion diagnostics; developments in the fields of proteomics, genomics, microbiomics, imaging and bioinformatics and how integration of these technologies into clinical practice could support therapeutic decisions.

TNF and TNF-receptors: From mediators of cell death and inflammation to therapeutic giants - past, present and future

Tumor Necrosis Factor (TNF), initially known for its tumor cytotoxicity, is a potent mediator of inflammation, as well as many normal physiological functions in homeostasis and health, and anti-microbial immunity. It also appears to have a central role in neurobiology, although this area of TNF biology is only recently emerging. Here, we review the basic biology of TNF and its normal effector functions, and discuss the advantages and disadvantages of therapeutic neutralization of TNF - now a commonplace practice in the treatment of a wide range of human inflammatory diseases. With over ten years of experience, and an emerging range of anti-TNF biologics now available, we also review their modes of action, which appear to be far more complex than had originally been anticipated. Finally, we highlight the current challenges for therapeutic intervention of TNF: (i) to discover and produce orally delivered small molecule TNF-inhibitors, (ii) to specifically target selected TNF producing cells or individual (diseased) tissue targets, and (iii) to pre-identify anti-TNF treatment responders. Although the future looks bright, the therapeutic modulation of TNF now moves into the era of personalized medicine with society's challenging expectations of durable treatment success and of achieving long-term disease remission.

Toward a personalized medicine approach to the management of inflammatory bowel disease

The medical management of inflammatory bowel disease (IBD) is evolving toward a personalized medicine-based model. Modern therapeutic algorithms that feature use of tumor necrosis factor (TNF) antagonists in combination with immunosuppressive are highly effective when initiated in high-risk patients early in the course of disease. Defined targets that guide intensification of therapy are critical interventions. In this model, therapy is optimized through appropriate pretreatment testing, therapeutic drug monitoring, and patient-based monitoring strategies. This review discusses the current application of personalized medicine to the management of IBD.

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.

Pharmacogenetics in rheumatoid arthritis

Rheumatoid arthritis (RA) is a systemic inflammatory arthritis leading to severe joint damage and associated with high morbidity and mortality. Disease-modifying antirheumatic drugs (DMARDs) are the mainstay of treatment in RA. DMARDs not only relieve the clinical signs and symptoms of RA but also inhibit the radiographic progression of disease. In the last decade, a new class of disease-modifying medications, the biologic agents, has been added to the existing spectrum of DMARDs in RA. However, patients' response to these agents is not uniform with considerable variability in both efficacy and toxicity. There are no reliable means of predicting an individual patient's response to a given DMARD prior to initiation of therapy. In this chapter, the current published literature on the pharmacogenetics of traditional DMARDS and the newer biologic DMARDs in RA is highlighted. Pharmacogenetics may help individualize drug therapy in patients with RA in the near future.

Activated protein C inhibits proliferation and tumor necrosis factor α-stimulated activation of p38, c-Jun NH2-terminal kinase (JNK) and Akt in rheumatoid synovial fibroblasts

Synovial fibroblast proliferation is a hallmark of the invasive pannus in the rheumatoid joint. Activated protein C (APC) is a natural anticoagulant that exerts antiinflammatory and cyto-protective effects in various diseases via endothelial protein C receptor (EPCR) and proteinase-activated receptor (PAR)-mediated pathways. In this study, we investigated the effect and the underlying cellular signaling mechanisms of APC on proliferation of human rheumatoid synovial fibroblasts (RSFs). We found that APC stimulated proliferation of mouse dermal fibroblasts (MDFs) and normal human dermal fibroblasts (HDFs) by up to 60%, but robustly downregulated proliferation of RSFs. APC induced the phosphorylation of extracellular signal-regulated protein kinase (ERK) and enhanced expression of p21 and p27 in a dose-dependent manner in RSFs. The latter effect was inhibited by pre-treatment with the ERK inhibitors PD98059 and U0126 but not by p38 inhibitor SB203580. In addition, APC significantly downregulated tumor necrosis factor (TNF)α-stimulated cell proliferation and activation of p38, c-Jun NH2-terminal kinase (JNK) and Akt in RSFs. These results provide the first evidence that APC selectively inhibits proliferation and the inflammatory signaling pathways of RSFs. Thus, APC may reduce synovial hyperplasia and pannus invasion in rheumatoid arthritis.

Personalized medicine: predicting responses to therapy in patients with RA

Personalized medicine where each patient receives the right drug and the right intensity of drug treatment for as long as needed or safe is the goal of medicine. The identification of predictors of response is the first step toward this. In rheumatoid arthritis (RA), several prediction matrices were designed to predict the risk of rapid radiological progression (RRP) in the first year of treatment, on either disease modifying anti-rheumatic drug (DMARD) monotherapy or combination therapy with prednisone or a biological agent. Both clinical markers and biomarkers of response to either anti-TNF or different mode of action biological agents, and of successful discontinuation of these agents once the treatment goal has been achieved, have been identified in different studies. Most of these markers need validation in other cohorts. Research into combining clinical markers and biomarkers of response could lead to identification of risk profiles resulting in a new step toward personalized medicine in RA.

Pharmacogenetics of disease-modifying antirheumatic drugs in rheumatoid arthritis: towards personalized medicine

Rheumatoid arthritis is a disease showing considerable heterogeneity in all its aspects, including response to therapy. The efficacy of disease-modifying antirheumatic drugs (DMARDs), with or without biological activity, has been unambiguously established. DMARDs improve the symptoms associated with the disease, and, even more importantly, are capable of stagnating the joint damage associated with the disease. Nonetheless, a considerable proportion of patients fail to achieve an adequate response and/or experience toxicity. This variability in treatment response between individuals has given rise to an extensive search for prognostic markers in order to personalize and optimize therapy in rheumatoid arthritis patients. Pharmacogenetics, the study of genetic variation underlying differential responses to drugs, is a rapidly progressing field in rheumatology that might enable personalized therapy in rheumatic diseases. This review will summarize the pharmacogenetics of commonly used synthetic and biological DMARDs.

Pharmacogenomics in pediatric rheumatology

PURPOSE OF REVIEW

Despite major advancements in therapeutics, variability in drug response remains a challenge in both adults and children diagnosed with rheumatic disease. The genetic contribution to interindividual variability has emerged as a promising avenue of exploration; however, challenges remain in making this knowledge relevant in the clinical realm.

RECENT FINDINGS

New genetic associations in patients with rheumatic disease have been reported for disease modifying antirheumatic drugs, antimetabolites and biologic drugs. However, many of these findings are in need of replication, and few have taken into account the concept of ontogeny, specific to pediatrics.

SUMMARY

In the current era in which we practice, genetic variation will undoubtedly contribute to variability in therapeutic response and may be a factor that will ultimately impact individualized care. However, preliminary studies have shown that there are many hurdles that need to be overcome as we explore pharmacogenomic associations specifically in the field of pediatric rheumatology.

NF-κB and Rheumatoid Arthritis: Will Understanding Genetic Risk Lead to a Therapeutic Reward?

NF-κB has long been known to play an important role in autoimmune diseases such as rheumatoid arthritis (RA). Indeed, as our understanding of how NF-κB is utilized has increased, we have been hard put to find a process not associated with this transcription factor family in some way. However, new data originating, in part, from genome-wide association studies have demonstrated that very specific alterations in components of the NF-κB pathway are sufficient to confer increased risk of developing disease. Here we review the data which have identified specific components of the NF-κB pathway, and consider what is known of their mechanisms of action and how these mechanisms might play into the disease process. In addition, the use of genetic information to predict RA is considered.

Investigation of single nucleotide polymorphisms and biological pathways associated with response to TNFα inhibitors in patients with rheumatoid arthritis

OBJECTIVE

Recently, two genome-wide association studies identified single nucleotide polymorphisms (SNPs) significantly associated with the treatment response to tumor necrosis factor α (TNFα) inhibitors in patients with rheumatoid arthritis (RA). We aimed to replicate these results and identify SNPs and the possible biological pathways associated with the treatment response to TNFα inhibitors.

METHODS

TNFα-naive patients with RA, who had available DNA and initiated TNFα inhibitor therapy between 1999 and 2008, were identified in the DANBIO registry and genotyped using the Illumina HumanHap550K Duo array. The associations between SNPs and changes in the absolute and the relative Disease Activity Score, and European League Against Rheumatism good versus no response after 14 weeks of treatment were tested. SNP data were combined with two independent cohorts in a meta-analysis. A gene-set enrichment analysis (GSEA) was carried out to identify the biological pathways associated with the treatment response.

RESULTS

After genotyping and quality control, 486 450 SNPs were analyzed in 196 Danish patients with moderate to severe RA treated with infliximab (n=142), etanercept (n=12), and adalimumab (n=42). None of the previously identified SNPs were confirmed in our dataset or in meta-analyses of available studies. Other potential SNPs were identified, but none achieved genome-wide significance. A GSEA identified the transforming growth factor β, TNF, mitogen-activated protein kinase, and mammalian target of rapamycin pathways to have a potential influence on the treatment response.

CONCLUSION

In a genome-wide association study of 196 genetically homogenous Danish patients with RA and in a meta-analysis, we found no SNPs associated with treatment response to TNFα inhibitors. A GSEA suggested that the transforming growth factor β, TNF, mitogen-activated protein kinase, and mammalian target of rapamycin pathways may be associated with treatment response.

Anti-citrullinated protein antibodies activated ERK1/2 and JNK mitogen-activated protein kinases via binding to surface-expressed citrullinated GRP78 on mononuclear cells

In a previous study, we found that anti-citrullinated protein antibodies (ACPAs) enhance nuclear factor (NF)-κB activity and tumor necrosis factor (TNF)-α production by normal human peripheral blood mononuclear cells (PBMCs) and U937 cells via binding to surface-expressed citrullinated glucose-regulated protein 78 (cit-GRP78). However, the downstream signaling pathways remain unclear after binding. In the present study, we firstly measured the effects of different kinase inhibitors on ACPA-mediated TNF-α production from normal PBMCs and monocytes. Then, the native and phosphorylated mitogen-activated protein kinases (MAPKs) were detected in ACPA-activated U937 cells by Western blotting. We also explored the role of the phosphoinositide 3-kinase (PI3K)-Akt pathway in activating IκB kinase alpha (IKK-α) in ACPA-stimulated U937 cells. Finally, we measured the amount of cit-GRP78 from PBMC membrane extracts in RA patients and controls. We found that MAPK and Akt inhibitors, but not PI3K inhibitor, remarkably suppressed ACPA-mediated TNF-α production. Interestingly, ACPAs selectively activated extracellular signal-regulated kinase 1/2 (ERK1/2) and c-jun N-terminal kinase (JNK), but not p38 MAPK, in U937 cells. This activation was suppressed by cit-GRP78, but not GRP78. The JNK activation further enhanced the phosphorylation of Akt and IKK-α. The expression of cit-GRP78 on cell membrane was higher in RA than normal PBMCs. Taken together; these results suggest that through binding to surface, over-expressed cit-GRP78 on RA PBMCs, ACPAs selectively activate ERK1/2 and JNK signaling pathways to enhance IKK-α phosphorylation, which leads to the activation of NF-κB and the production of TNF-α .

Replication of association of the PTPRC gene with response to anti-tumor necrosis factor therapy in a large UK cohort

Objective

Several rheumatoid arthritis (RA) susceptibility variants map close to genes involved in the tumor necrosis factor (TNF) signaling pathway, prompting the investigation of RA susceptibility variants in studies of predictors of response to TNF blockade. Based on a previously reported association of RA with the PTPRC genetic locus, the present study was undertaken to test established RA susceptibility variants, including PTPRC, in the prediction of response to TNF blockade in a large cohort of patients from the UK.

Methods

DNA was extracted from the blood of 1,115 UK patients with RA who were receiving anti-TNF biologic therapy. Samples were analyzed for 29 single-nucleotide polymorphisms (SNPs) previously established as RA susceptibility variants. In the primary analysis, the effect of each SNP on treatment response was assessed by linear regression, using an additive model, in which absolute change in the Disease Activity Score in 28 joints at 6 months of followup was the outcome measure. In a secondary analysis, logistic regression models were used to compare patients with a good treatment response (n = 274) to those with a poor response (n = 195), as defined using the European League Against Rheumatism response criteria. Results were combined with those from previous studies to confirm the findings by meta-analysis.

Results

The PTPRC rs10919563 SNP was associated with improved treatment response in both the primary analysis (regression coefficient 0.19, 95% confidence interval [95% CI] 0.09, 0.37; P = 0.04) and secondary analysis (odds ratio 0.62, 95% CI 0.40, 0.95; P = 0.03). A meta-analysis combining these data with the results from a previous study strengthened the evidence for association with the PTPRC SNP (P = 5.13 × 10⁻⁵). No convincing association of the treatment response with other candidate loci was detected.

Conclusion

Presence of the rs10919563 RA susceptibility variant at the PTPRC gene locus predicts improved response to anti-TNF biologic therapy. Fine-mapping studies are required to determine whether this SNP or another variant at the locus provides the greatest predictive accuracy for treatment response.

CD6 and syntaxin binding protein 6 variants and response to tumor necrosis factor alpha inhibitors in Danish patients with rheumatoid arthritis

BACKGROUND

TNFα inhibitor therapy has greatly improved the treatment of patients with rheumatoid arthritis, however at least 30% do not respond. We aimed to investigate insertions and deletions (INDELS) associated with response to TNFα inhibitors in patients with rheumatoid arthritis (RA).

METHODOLOGY AND PRINCIPAL FINDINGS

In the DANBIO Registry we identified 237 TNFα inhibitor naïve patients with RA (81% women; median age 56 years; disease duration 6 years) who initiated treatment with infliximab (n=160), adalimumab (n=56) or etanercept (n=21) between 1999 and 2008 according to national treatment guidelines. Clinical response was assessed at week 26 using EULAR response criteria. Based on literature, we selected 213 INDELS potentially related to RA and treatment response using the GeneVa® (Compugen) in silico database of 350,000 genetic variations in the human genome. Genomic segments were amplified by polymerase chain reaction (PCR), and genotyped by Sanger sequencing or fragment analysis. We tested the association between genotypes and EULAR good response versus no response, and EULAR good response versus moderate/no response using Fisher's exact test. At baseline the median DAS28 was 5.1. At week 26, 68 (29%) patients were EULAR good responders, while 81 (34%) and 88 (37%) patients were moderate and non-responders, respectively. A 19 base pair insertion within the CD6 gene was associated with EULAR good response vs. no response (OR=4.43, 95% CI: 1.99-10.09, p=7.211×10(-5)) and with EULAR good response vs. moderate/no response (OR=4.54, 95% CI: 2.29-8.99, p=3.336×10(-6)). A microsatellite within the syntaxin binding protein 6 (STXBP6) was associated with EULAR good response vs. no response (OR=4.01, 95% CI: 1.92-8.49, p=5.067×10(-5)).

CONCLUSION

Genetic variations within CD6 and STXBP6 may influence response to TNFα inhibitors in patients with RA.

Tumour necrosis factor receptor trafficking dysfunction opens the TRAPS door to pro-inflammatory cytokine secretion

Cytokines are secreted from macrophages and other cells of the immune system in response to pathogens. Additionally, in autoinflammatory diseases cytokine secretion occurs in the absence of pathogenic stimuli. In the case of TRAPS [TNFR (tumour necrosis factor receptor)-associated periodic syndrome], inflammatory episodes result from mutations in the TNFRSF1A gene that encodes TNFR1. This work remains controversial, however, with at least three distinct separate mechanisms of receptor dysfunction having been proposed. Central to these hypotheses are the NF-κB (nuclear factor κB) and MAPK (mitogen-activated protein kinase) families of transcriptional activators that are able to up-regulate expression of a number of genes, including pro-inflammatory cytokines. The present review examines each proposed mechanism of TNFR1 dysfunction, and addresses how these processes might ultimately impact upon cytokine secretion and disease pathophysiology.

Genetic and genomic predictors of anti-TNF response

The introduction of anti-TNF therapy has dramatically improved the outlook for patients suffering from a number of inflammatory conditions including rheumatoid arthritis and inflammatory bowel disease. Despite this, a substantial proportion of patients (approximately 30-40%) fail to respond to these potentially toxic and expensive therapies. Treatment response is likely to be multifactorial; however, variation in genes or their expression may identify those most likely to respond. By targeted testing of variants within candidate genes, potential predictors of anti-TNF response have been reported; however, very few markers have replicated consistently between studies. Emerging genome-wide association studies suggest that there may be a number of genes with modest effects on treatment response rather than a few genes of large effect. Other potential serum biomarkers of response have also been explored including cytokines and autoantibodies, with antibodies developing to the anti-TNF drugs themselves being correlated with treatment failure.

Genetics of rheumatoid arthritis: time for a change!

PURPOSE OF REVIEW

To review recent progress in the genetics of rheumatoid arthritis (RA) and discuss the implications for understanding the pathogenesis of the disease as well as clinical application.

RECENT FINDINGS

Protection against anticitrullinated protein antibody (ACPA) positive RA was shown to be associated wit DRB1*1301. Genome-wide association studies (GWASs) added about 10 new loci to the list of already more than 20 loci associated with RA, so the list is now over 30. Typing for the known risk loci is not helpful for prediction of the risk for RA. It is remarkable how few functional studies have been published.

SUMMARY

Known genetic factors explain 50-60% of the genetic variance for susceptibility to ACPA-positive and 30-50% for ACPA-negative RA. Searching for the remaining missing or hidden heritability is in all probability not going to yield much for prediction and/or targeted intervention. Therefore, I conclude that if you want to find more genes you should have a lot of patience, time and money, stop with convential GWAS and invest in large-scale sequencing of selected patients and controls. I have a better suggestion, however: use the information that is already available to perform functional studies in order to understand the mechanism of the known associations!

Pharmacogenetics: implications for therapy in rheumatic diseases

DMARDs not only improve the joint pain and swelling associated with rheumatoid arthritis (RA), but also slow down the joint damage associated with the disease. The efficacy of biologic therapies, introduced in the past decade for the treatment of RA, has been unequivocally established. Similarly, in addition to traditional drugs such as hydroxychloroquine, new biologic agents such as rituximab have been introduced for systemic lupus erythematosus in recent years. However, considerable variability occurs in the responses of patients to these therapies. Pharmacogenetics, the study of variations in genes encoding drug transporters, drug-metabolizing enzymes and drug targets, and their translation to differential responses to drugs, is a rapidly progressing field in rheumatology. Pharmacogenetic applications, particularly to the old vanguard DMARD, methotrexate, and the newer, more expensive biologic agents, might make personalized therapy in rheumatic diseases possible. The pharmacogenetics of commonly used DMARDs and of biologic therapies are described in this Review.

Treatment of rheumatoid arthritis with tumour necrosis factor inhibitors

Advances in our understanding of the key mediators of chronic inflammation and tissue damage characteristic of rheumatoid arthritis (RA) have resulted in the development of novel therapies primarily targeting pro-inflammatory cytokines. Inhibitors of tumour necrosis factor (TNF) are the most widely used of the biological therapies at present with five different agents currently available; four are based on monoclonal anti-TNF antibodies and a soluble TNF receptor-Fc fusion protein. Long-term use of these molecules has proven to be highly effective in the majority of patients; however, around one-third have a suboptimal response potentially leading to further cartilage and bone damage, furthermore these agents are expensive compared with conventional therapies such as methotrexate. Many recent studies have attempted to identify therapeutic response biomarkers of TNF inhibitors which could be used to improve therapeutic targeting. The presence of rheumatoid factor and anti-cyclic citullinated protein antibodies, present in around 65% of RA patients, are associated with a poorer response to anti-TNF agents. Poorer response is also associated with levels of C-reactive protein and cartilage degradation product at initiation of treatment. Intriguingly, genetic studies of variants of TNF and of genes encoding members of the Toll-like receptors, nuclear factor-kappa B and p38 mitogen-activated protein kinase signalling families have been associated with response to individual anti-TNF agents. Continued advances in technologies such as ultra high throughput sequencing and proteomics should facilitate the discovery of additional biomarkers of response to anti-TNF resulting in improved disease control and quality of life for RA patients and reduced costs for healthcare funders.