Apolipoprotein A-I and platelet factor 4 are biomarkers for infliximab response in rheumatoid arthritis

Biomarkers of Cardiovascular Risk in Patients With Rheumatoid Arthritis: Results From the TARGET Trial

Cardiovascular disease remains an important comorbidity in patients with rheumatoid arthritis (RA), but traditional models do not accurately predict cardiovascular risk in patients with RA. The addition of biomarkers could improve prediction.

METHODS AND RESULTS

The TARGET (Treatments Against RA and Effect on FDG PET/CT) trial assessed whether different treatment strategies in RA differentially impact cardiovascular risk as measured by the change in arterial inflammation on arterial target to background ratio on fluorodeoxyglucose positron emission tomography/computed tomography scans conducted 24 weeks apart. A group of 24 candidate biomarkers supported by prior literature was assessed at baseline and 24 weeks later. Longitudinal analyses examined the association between baseline biomarker values, measured in plasma EDTA, and the change in arterial inflammation target to background ratio. Model fit was assessed for the candidate biomarkers only, clinical variables only, and models combining both. One hundred nine patients with median (interquartile range) age 58 years (53-65 years), RA duration 1.4 years (0.5-6.6 years), and 82% women had biomarkers assessed at baseline and follow-up. Because the main trial analyses demonstrated significant target to background ratio decreases with both treatment strategies but no difference across treatment groups, we analyzed all patients together. Baseline values of serum amyloid A, C-reactive protein, soluble tumor necrosis factor receptor 1, adiponectin, YKL-40, and osteoprotegerin were associated with significant change in target to background ratio. When selected candidate biomarkers were added to the clinical variables, the adjusted R2 improved from 0.20 to 0.33 (likelihood ratio P=0.0005).

CONCLUSIONS

A candidate biomarker approach identified several promising biomarkers that associate with baseline and treatment-associated changes in arterial inflammation in patients with RA. These will now be tested in an external validation cohort.

The role of CXCR3 and its ligands in cancer

Chemokines are a class of small cytokines or signaling proteins that are secreted by cells. Owing to their ability to induce directional chemotaxis of nearby responding cells, they are called chemotactic cytokines. Chemokines and chemokine receptors have now been shown to influence many cellular functions, including survival, adhesion, invasion, and proliferation, and regulate chemokine levels. Most malignant tumors express one or more chemokine receptors. The CXC subgroup of chemokine receptors, CXCR3, is mainly expressed on the surface of activated T cells, B cells, and natural killer cells, and plays an essential role in infection, autoimmune diseases, and tumor immunity by binding to specific receptors on target cell membranes to induce targeted migration and immune responses. It is vital to treat infections, autoimmune diseases, and tumors. CXCR3 and its ligands, CXCL9, CXCL10, and CXCL11, are closely associated with the development and progression of many tumors. With the elucidation of its mechanism of action, CXCR3 is expected to become a new indicator for evaluating the prognosis of patients with tumors and a new target for clinical tumor immunotherapy. This article reviews the significance and mechanism of action of the chemokine receptor CXCR3 and its specific ligands in tumor development.

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.

Apolipoprotein A1 Modulates Teff/Treg Balance Through Scavenger Receptor Class B Type I-Dependent Mechanisms in Experimental Autoimmune Uveitis

Purpose

Experimental autoimmune uveitis (EAU) is a representative animal model of human uveitis. In this study, we investigated whether apolipoprotein A1 (APOA1) can alleviate EAU and explored its underlying mechanism.

Methods

Mice were immunized with interphotoreceptor retinoid-binding protein 1-20 and treated with APOA1 or vehicle. The retinas, draining lymph nodes (DLNs), and spleens were analyzed. Isolated T cells were used for proliferation, differentiation, and function assays in vitro. Selective inhibitors and pathway agonists were used to study signaling pathways. The effect of APOA1 on peripheral blood mononuclear cells (PBMCs) from uveitis patients was also examined.

Results

Administration of APOA1 ameliorated EAU. APOA1 suppressed pathogenic CD4+ T cell expansion in DLNs and spleen, and decreased the infiltration of effector T (Teff) cells into retina. APOA1 also inhibited T cell proliferation and T helper 1 cell differentiation in vitro and promoted regulatory T (Treg) cell differentiation. APOA1 restricted inflammatory cytokine production from lipopolysaccharide-stimulated PBMCs. Mechanistic studies revealed that the effect of APOA1 was mediated by scavenger receptor class B type I (SR-BI) and downstream signals including phosphatidylinositol 3-kinase/Protein kinase B (PKB, or Akt), p38 mitogen-activated protein kinase, and nuclear factor–κB.

Conclusions

APOA1 ameliorates EAU by regulating the Teff/Treg partially through SR-BI. Our results suggest that APOA1 can be a therapeutic alternative for autoimmune uveitis.

Validation in the ESPOIR cohort of vitamin K-dependent protein S (PROS) as a potential biomarker capable of predicting response to the methotrexate/etanercept combination

Background

To validate the ability of PROS (vitamin K-dependent protein S) and CO7 (complement component C7) to predict response to the methotrexate (MTX)/etanercept (ETA) combination in rheumatoid arthritis (RA) patients who received this therapeutic combination in a well-documented cohort.

Method

From the ESPOIR cohort, RA patients having received the MTX/ETA or MTX/adalimumab (ADA) combination as a first-line biologic treatment were included. Serum concentrations of PROS and CO7 were measured by ELISA prior to the initiation of ETA or ADA, at a time where the disease was active (DAS28 ESR > 3.2). The clinical efficacy (response/non-response) of both combinations has been evaluated after at least 6 months of treatment, according to the EULAR response criteria with some modifications.

Results

Thirty-two were treated by MTX/ETA; the numbers of responders and non-responders were 24 and 8, respectively. Thirty-three patients received the MTX/ADA combination; 27 and 5 patients were respectively responders and non-responders. While there were no differences for demographic, clinical, biological, and X-rays data, as well as for CO7, serum levels of PROS tended to be significantly higher in responders to the MTX/ETA combination (p = 0.08) while no difference was observed in the group receiving MTX/ADA. For PROS, the best concentration threshold to differentiate both groups was calculated at 40 μg/ml using ROC curve. The theranostic performances of PROS appeared better for the ETA/MTX combination. When considering the response to this combination, analysis of pooled data from ESPOIR and SATRAPE (initially used to validate PROS and CO7 as potential theranostic biomarkers) cohorts led to a higher theranostic value of PROS that became significant (p = 0.009).

Conclusion

PROS might be one candidate of a combination of biomarkers capable of predicting the response to MTX/ETA combination in RA patients refractory to MTX.

Trial registration

ClinicalTrials.gov identifiers: NCT03666091 and NCT00234234.

Establishing Classification Tree Models in Rheumatoid Arthritis Using Combination of Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry and Magnetic Beads

Background: There is no simple method for early diagnosis and evaluation of rheumatoid arthritis (RA). This study aimed to determine potential biomarkers and establish diagnostic patterns for RA using proteomic fingerprint technology combined with magnetic beads.

Methods: The serum protein profiles of 97 RA patients and 76 healthy controls (HCs) were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) with weak cationic exchange (WCX) magnetic beads. Samples were randomly divided into training (83 RA patients and 56 HCs) and test sets (14 RA patients and 20 HCs). Patients were classified according to their Disease Activity Score: in remission, n = 28; with low disease activity, n = 17; with moderate disease activity, n = 21; with high disease activity, n = 31. There are 44 RA patients alone, 22 RA patients with interstitial lung disease (RA-ILD), 18 RA patients with secondary Sjögren's syndrome (RA-sSS), 6 RA patients with osteonecrosis of the femoral head (RA-ONFH), and 7 RA patients with other complications. Eleven patients were treated with etanercept only for half a year, after which their serum protein profiles were detected. The proteomic pattern was identified by Biomarker Patterns Software, and the potential biomarkers for RA diagnosis were further identified and quantified by enzyme-linked immunosorbent assay.

Results: The diagnostic pattern with four potential protein biomarkers, mass-to-charge (m/z) 3,448.85, 4,716.71, 8,214.29, and 10,645.10, could accurately recognize RA patients from HCs (specificity, 91.57%; sensitivity, 92.86%). The test set were correctly classified by this model (sensitivity, 95%; specificity, 100%). The components containing the four biomarkers were preliminarily retrieved through the ExPasy database, including the C-C motif chemokine 24 (CCL24), putative metallothionein (MT1DP), sarcolipin (SLN), and C-X-C motif chemokine 11 (CCXL11). Only the CCL24 level was detected to have a significant decrease in the serum of RA patients as compared with HCs (p < 0.05). No significant difference was found in others, but a decreasing trend consistent with the down-regulation of the four biomarkers detected by MALDI-TOF-MS was observed. The diagnostic models could effectively discriminate between RA alone and RA with complications (RA-ILD: m/z 10,645.10 and 12,595.86; RA-sSS: m/z 6,635.62 and 33,897.72; RA-ONFH: m/z 2,071.689). The classification model, including m/z 1,130.776, 1,501.065, 2,091.198, and 11,381.87, could distinguish between RA patients with disease activity and those in remission. RA with low disease activity could be efficiently discriminated from other disease activity patients by specific protein biomarkers (m/z 2,032.31, 2,506.214, and Z9286.495). Two biomarkers (m/z 2,032.31 and 4,716.71) were applied to build the classification model for RA patients with moderate and high disease activities. Biological markers for etanercept (m/z 2,671.604064, 5,801.840579, 8,130.195641, and 9,286.49499) were observed between the responder (n = 7) and non-responder groups (n = 4) (p < 0.05).

Conclusion: We successfully established a series of diagnostic models involving RA and RA with complications as well as assessed disease activity. Furthermore, we found that CCL24 may be a valuable auxiliary diagnostic indicator for RA. These results provide reference values for clinical practice in the future.

Protein array-based companion diagnostics in precision medicine

INTRODUCTION

The development of companion diagnostics (CDx) will increase efficacy and cost-benefit markedly, compared to the currently prevailing trial-and-error approach for treatment. Recent improvements in high-throughput protein technology have resulted in large amounts of predictive biomarkers that are potentially useful components of future CDx assays. Current high multiplex protein arrays are suitable for discovery-based approaches, while low-density and more simple arrays are suitable for use in point-of-care facilities.

AREA COVERED

This review discusses the technical platforms available for protein array focused CDx, explains the technical details of the platforms and provide examples of clinical use, ranging from multiplex arrays to low-density clinically applicable arrays. We thereafter highlight recent predictive biomarkers within different disease areas, such as oncology and autoimmune diseases. Lastly, we discuss some of the challenges connected to the implementation of CDx assays as point-of-care tests.

EXPERT OPINION

Recent advances in the field of protein arrays have enabled high-density arrays permitting large biomarker discovery studies, which are beneficial for future CDx assays. The density of protein arrays range from a single protein to proteome-wide arrays, allowing the discovery of protein signatures that may correlate with drug response. Protein arrays will undoubtedly play a key role in future CDx assays.

Contribution of Multiplex Immunoassays to Rheumatoid Arthritis Management: From Biomarker Discovery to Personalized Medicine

Rheumatoid arthritis (RA) is a multifactorial, inflammatory and progressive autoimmune disease that affects approximately 1% of the population worldwide. RA primarily involves the joints and causes local inflammation and cartilage destruction. Immediate and effective therapies are crucial to control inflammation and prevent deterioration, functional disability and unfavourable progression in RA patients. Thus, early diagnosis is critical to prevent joint damage and physical disability, increasing the chance of achieving remission. A large number of biomarkers have been investigated in RA, although only a few have made it through the discovery and validation phases and reached the clinic. The single biomarker approach mostly used in clinical laboratories is not sufficiently accurate due to its low sensitivity and specificity. Multiplex immunoassays could provide a more complete picture of the disease and the pathways involved. In this review, we discuss the latest proposed protein biomarkers and the advantages of using protein panels for the clinical management of RA. Simultaneous analysis of multiple proteins could yield biomarker signatures of RA subtypes to enable patients to benefit from personalized medicine.

Efficacy, safety and cost-effectiveness of a web-based platform delivering the results of a biomarker-based predictive model of biotherapy response for rheumatoid arthritis patients: a protocol for a randomized multicenter single-blind active controlled clinical trial (PREDIRA)

BACKGROUND

Rheumatoid arthritis (RA) is one of the leading chronic inflammatory rheumatism. First-line therapy with synthetic disease-modifying antirheumatic drugs (sDMARD) is insufficiently effective in 40% of cases and these patients are treated with biotherapies. The increased use of these drugs each year is becoming a public health issue with considerable economic burden. This cost is 20 times higher than that of sDMARD. However, among patients treated with biotherapies, clinical practice shows that about one third will not respond to the selected drug. In nonresponse cases, practitioners currently have no choice but to perform an empirical switching between different treatments, because no tool capable of predicting the response or nonresponse to these molecules is currently available.

METHODS

The study is a prospective, phase III, controlled, multicenter, and randomized, single-blind (patient) clinical trial, including RA patients with a previous failure to anti-TNF therapies. The main objective is the analysis of the clinical and pharmacoeconomic impact after 6 months of treatment. Intervention arm: prescription of biotherapy (rituximab, adalimumab, abatacept) using SinnoTest® software, a prediction software based on proteomic biomarkers. Control arm: prescription of biotherapy based on current practice, without the SinnoTest® software (any biotherapy). In addition, a substudy will be carried out within this trial to generate a biobank and further analyze the proteomic profile of the patients and their modification throughout the study.

DISCUSSION

This clinical trial study will be the first validation study of a biotherapy response prediction software, bringing personalized medicine into the management of RA. We expect that the findings from this study will bring several benefits for the patient and the Health Care System.

TRIAL REGISTRATION

ClincalTrials.gov NCT04147026 . Registered on 31 October, 2019.

Multiple biomarker approach for the diagnosis and therapy of rheumatoid arthritis

The lack of specific clinical symptoms for patients in the early stage of rheumatoid arthritis (RA) has created strong interest in the laboratory diagnosis of RA. The main laboratory markers of RA, rheumatoid factor (RF) and anti-citrullinated protein antibodies (ACPAs), can be found in patients with other pathologies and in healthy donors. Even today, there is no single laboratory test that can diagnosis RA with high sensitivity and specificity. To improve the diagnosis and treatment of RA, alternative biomarkers, including 14-3-3η protein, connective tissue growth factor (CTGF), antibodies against PAD4, antibodies against BRAF, and anti-acetylated and anti-carbamylated protein antibodies have been studied extensively. The use of a multiple biomarker approach, the simultaneous measurement of a set of biomarkers, is an alternative strategy for the diagnosis of RA and for predicting the therapeutic effect of biological disease-modifying antirheumatic drugs (DMARDs). However, despite the large number of studies, only a few biomarker combinations have been validated and can be applied in clinical practice. In this article, results of studies focused on the multiple biomarker approach (both multiplex and combined single-analyte assays) to diagnose RA and to predict response to biological drug therapy are reviewed. Additionally, general factors limiting the use of multiplex analysis in RA diagnostics and therapy are discussed.

Proteomics in Chronic Arthritis-Will We Finally Have Useful Biomarkers?

PURPOSE OF REVIEW

Current technical advances enable the assessment of the complex changes in body fluid proteomes and thus allow for the discovery of biomarker signatures rather than just following differences of a single marker. In this review, we aim to summarize current approaches to discover and evaluate multi-biomarker panels for improved monitoring of chronic arthritis disease activity.

RECENT FINDINGS

Mass spectrometry and affinity proteomic methodologies have been used to identify biomarker panels in synovial fluid, serum, plasma, or urine of pediatric and adult chronic arthritis patients. Notably, despite the numerous efforts to develop new and better biomarker panels, very few have undergone extensive analytical and clinical validation and been adopted into routine use for patient benefit. There remains a significant gap between discovery of chronic arthritis biomarker signatures and their validation for clinical use.

High Level of APOA1 in Blood and Maternal Fetal Interface Is Associated With Early Miscarriage

Early miscarriage (EM) is one of the most devastating obstetrical complications globally affecting the quality of women's life. In the present study, we aimed to identify proteins that correlate with and could act as biomarkers for EM. We performed 2-dimensional gel electrophoresis in chorionic villi samples followed by mass spectrometry for identification of differential protein expression with EM. Proteomic studies detected a total 124 protein spots, out of which 83 spots were differentially expressed between EM and controls in chorionic villi samples. Matrix assisted laser desorbtion/ionization-time of flight (MALDI-TOF) mass spectrometry analysis revealed Apolipoprotein A1 (APOA1) to be the most upregulated protein in the EM group that was validated by Western blotting and Enzyme-linked immunosorbent assay (ELISA) . We found low but not statistically significant level of APOA1 on 21st day of menstruation in comparison to the 7th day. APOA1 level was observed to be the lowest in the first trimester. Hence, this study suggests that low APOA1 expression is critical in establishing pregnancy and elevated APOA1 expression in chorionic villi correlates with EM. Similar observation in serum samples suggests its potential as a marker for the risk of EM.

Prealbumin, platelet factor 4 and S100A12 combination at baseline predicts good response to TNF alpha inhibitors in rheumatoid arthritis

OBJECTIVES

Tumour necrosis factor-alpha inhibitors (TNFi) are effective treatments for Rheumatoid Arthritis (RA). Responses to treatment are barely predictable. As these treatments are costly and may induce a number of side effects, we aimed at identifying a panel of protein biomarkers that could be used to predict clinical response to TNFi for RA patients.

METHODS

Baseline blood levels of C-reactive protein, platelet factor 4, apolipoprotein A1, prealbumin, α1-antitrypsin, haptoglobin, S100A8/A9 and S100A12 proteins in bDMARD naive patients at the time of TNFi treatment initiation were assessed in a multicentric prospective French cohort. Patients fulfilling good EULAR response at 6 months were considered as responders. Logistic regression was used to determine best biomarker set that could predict good clinical response to TNFi.

RESULTS

A combination of biomarkers (prealbumin, platelet factor 4 and S100A12) was identified and could predict response to TNFi in RA with sensitivity of 78%, specificity of 77%, positive predictive values (PPV) of 72%, negative predictive values (NPV) of 82%, positive likelihood ratio (LR+) of 3.35 and negative likelihood ratio (LR-) of 0.28. Lower levels of prealbumin and S100A12 and higher level of platelet factor 4 than the determined cutoff at baseline in RA patients are good predictors for response to TNFi treatment globally as well as to Infliximab, Etanercept and Adalimumab individually.

CONCLUSION

A multivariate model combining 3 biomarkers (prealbumin, platelet factor 4 and S100A12) accurately predicted response of RA patients to TNFi and has potential in a daily practice personalized treatment.

Right drug, right patient, right time: aspiration or future promise for biologics in rheumatoid arthritis?

Individualising biologic disease-modifying anti-rheumatic drugs (bDMARDs) to maximise outcomes and deliver safe and cost-effective care is a key goal in the management of rheumatoid arthritis (RA). Investigation to identify predictive tools of bDMARD response is a highly active and prolific area of research. In addition to clinical phenotyping, cellular and molecular characterisation of synovial tissue and blood in patients with RA, using different technologies, can facilitate predictive testing. This narrative review will summarise the literature for the available bDMARD classes and focus on where progress has been made. We will also look ahead and consider the increasing use of ‘omics’ technologies, the potential they hold as well as the challenges, and what is needed in the future to fully realise our ambition of personalised bDMARD treatment.

Proteomics to predict the response to tumour necrosis factor-α inhibitors in rheumatoid arthritis using a supervised cluster-analysis based protein score

OBJECTIVE

In rheumatoid arthritis (RA), it is of major importance to identify non-responders to tumour necrosis factor-α inhibitors (TNFi) before starting treatment, to prevent a delay in effective treatment. We developed a protein score for the response to TNFi treatment in RA and investigated its predictive value.

METHOD

In RA patients eligible for biological treatment included in the BiOCURA registry, 53 inflammatory proteins were measured using xMAP® technology. A supervised cluster analysis method, partial least squares (PLS), was used to select the best combination of proteins. Using logistic regression, a predictive model containing readily available clinical parameters was developed and the potential of this model with and without the protein score to predict European League Against Rheumatism (EULAR) response was assessed using the area under the receiving operating characteristics curve (AUC-ROC) and the net reclassification index (NRI).

RESULTS

For the development step (n = 65 patient), PLS revealed 12 important proteins: CCL3 (macrophage inflammatory protein, MIP1a), CCL17 (thymus and activation-regulated chemokine), CCL19 (MIP3b), CCL22 (macrophage-derived chemokine), interleukin-4 (IL-4), IL-6, IL-7, IL-15, soluble cluster of differentiation 14 (sCD14), sCD74 (macrophage migration inhibitory factor), soluble IL-1 receptor I, and soluble tumour necrosis factor receptor II. The protein score scarcely improved the AUC-ROC (0.72 to 0.77) and the ability to improve classification and reclassification (NRI = 0.05). In validation (n = 185), the model including protein score did not improve the AUC-ROC (0.71 to 0.67) or the reclassification (NRI = -0.11).

CONCLUSION

No proteomic predictors were identified that were more suitable than clinical parameters in distinguishing TNFi non-responders from responders before the start of treatment. As the results of previous studies and this study are disparate, we currently have no proteomic predictors for the response to TNFi.

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.

Defining the proteomic landscape of rheumatoid arthritis: progress and prospective clinical applications

INTRODUCTION

The heterogeneity of Rheumatoid Arthritis (RA) and the absence of clinical tests accurate enough to identify the early stages of this disease have hampered its management. Therefore, proteomics research is increasingly focused on the discovery of novel biological markers, which would not only be able make an early diagnosis, but also to gain insight into the different pathological mechanisms underlying the heterogeneity of RA and also to stratify patients, which is critical to enabling effective treatments. Areas covered: The proteomic approaches that have been utilised to provide knowledge about RA pathogenesis, and to identify biomarkers for RA diagnosis, prognosis, disease monitoring and prediction of response to therapy, are summarized. Expert commentary: Although each proteomic study is unique in its design, all of them have contributed to the understanding of RA pathogenesis and the discovery of promising biomarkers for patient stratification, which would improve clinical care of RA patients. Still, efforts need to be made to validate these findings and translate them into clinical practice.

A Multi-Biomarker Disease Activity Score and the Choice of Second-Line Therapy in Early Rheumatoid Arthritis After Methotrexate Failure

Objective

To investigate whether the Multi‐Biomarker Disease Activity (MBDA) score predicts optimal add‐on treatment in patients with early rheumatoid arthritis (RA) who were inadequate responders to MTX (MTX‐IRs).

Methods

We analyzed data from 157 MTX‐IRs (with a Disease Activity Score using the erythrocyte sedimentation rate [DAS28‐ESR] >3.2) from the Swedish Pharmacotherapy (SWEFOT) trial who were randomized to receive triple therapy (MTX plus sulfasalazine plus hydroxychloroquine) versus MTX plus infliximab. The MBDA score as a predictor of the subsequent DAS28‐based response to each second‐line treatment was analyzed at randomization with the Breslow‐Day test for 2 × 2 groups, using both validated categories (low [<30], moderate [30–44], and high [>44]) and dichotomized categories (lower [≤38] versus higher [>38]).

Results

Among the 157 patients, 12% had a low MBDA score, 32% moderate, and 56% high. Of those with a low MBDA score, 88% responded to subsequent triple therapy, and 18% responded to MTX plus infliximab (P = 0.006); for those with a high MBDA score, the response rates were 35% and 58%, respectively (P = 0.040). When using 38 as a cutoff for the MBDA score (29% patients with lower scores versus 71% with higher scores), the differential associations with response to triple therapy versus MTX plus infliximab were 79% versus 44% and 36% versus 58%, respectively (P = 0.001). Clinical and inflammatory markers had poorer predictive capacity for response to triple therapy or MTX plus infliximab.

Conclusion

In patients with RA who had an inadequate response to MTX, the MBDA score categories were differentially associated with response to subsequent therapies. Thus, patients with post‐MTX biochemical improvements (lower MBDA scores) were more likely to respond to triple therapy than to MTX plus infliximab. If confirmed, these results may help to improve treatment in RA.

Psoriasis, psoriatic arthritis, and rheumatoid arthritis: Is all inflammation the same? Semin Arthritis Rheum. 2016;46:291-304. [PMID: 27388027 DOI: 10.1016/j.semarthrit.2016.05.012]

OBJECTIVES

To review the pathophysiology, co-morbidities, and therapeutic options for psoriasis, psoriatic arthritis and rheumatoid arthritis in order to further understand the similarities and differences in treatment paradigms in the management of each disease. New targets for individualized therapeutic decisions are also identified with the aim of improving therapeutic outcome and reducing toxicity.

SEARCH STRATEGY

Using the PubMed database, we searched literature published from 2000 to 2015 using combinations of the key words "psoriasis," "psoriatic arthritis," "rheumatoid arthritis," "pathogenesis," "immunomodulation," and "treatment."

INCLUSION AND EXCLUSION CRITERIA

This was a non-systematic review and there were no formal inclusion and exclusion criteria.

DATA EXTRACTION

Abstracts identified in the search were screened for relevance and articles considered appropriate evaluated further. References within these selected articles were also screened. Information was extracted from 198 articles for inclusion in this report.

DATA SYNTHESIS

There was no formal data synthesis. Articles were reviewed and summarized according to disease area (psoriasis, psoriatic arthritis, and rheumatoid arthritis).

HEADLINE RESULTS

The pathophysiology of psoriasis, psoriatic arthritis, and rheumatoid arthritis involves chronic inflammation mediated by pro-inflammatory cytokines. Dysfunction in integrated signaling pathways affecting different constituents of the immune system result in varying clinical features in the three diseases. Co-morbidities, including cardiovascular disease, malignancies, and non-alcoholic fatty liver disease are increased. Increased understanding of the immunopathogenesis allowed development of targeted treatments; however, despite a variety of potentially predictive genetic, protein and cellular biomarkers, there is still significant unmet need in these three inflammatory disorders.

A novel method predicting clinical response using only background clinical data in RA patients before treatment with infliximab

OBJECTIVES

The aim of the present study was to generate a novel method for predicting the clinical response to infliximab (IFX), using a machine-learning algorithm with only clinical data obtained before the treatment in rheumatoid arthritis (RA) patients.

METHODS

We obtained 32 variables out of the clinical data on the patients from two independent hospitals. Next, we selected both clinical parameters and machine-learning algorithms and decided the candidates of prediction method. These candidates were verified by clinical variables on different patients from two other hospitals. Finally, we decided the prediction method to achieve the highest score.

RESULTS

The combination of multilayer perceptron algorithm (neural network) and nine clinical parameters shows the best accuracy performance. This method could predict the good or moderate response to IFX with 92% accuracy. The sensitivity of this method was 96.7%, while the specificity was 75%.

CONCLUSIONS

We have developed a novel method for predicting the clinical response using only background clinical data in RA patients before treatment with IFX. Our method for predicting the response to IFX in RA patients may have advantages over the other previous methods in several points including easy usability, cost-effectiveness and accuracy.

Independent Candidate Serum Protein Biomarkers of Response to Adalimumab and to Infliximab in Rheumatoid Arthritis: An Exploratory Study

Response to treatment of rheumatoid arthritis shows large inter-individual variability. This heterogeneity is observed with all the anti-rheumatic drugs, including the commonly used TNF inhibitors. It seems that drug-specific and target-specific factors lead individual patients to respond or not to a given drug, although this point has been challenged. The search of biomarkers distinguishing responders from non-responders has included shotgun proteomics of serum, as a previous study of response to infliximab, an anti-TNF antibody. Here, we have used the same study design and technology to search biomarkers of response to a different anti-TNF antibody, adalimumab, and we have compared the results obtained for the two anti-TNF drugs. Search of biomarkers of response to adalimumab included depletion of the most abundant serum proteins, 8-plex isobaric tag for relative and absolute quantitation (iTRAQ) labeling, two-dimensional liquid chromatography fractionation and relative quantification with a hybrid Orbitrap mass spectrometer. With this approach, 264 proteins were identified in all the samples with at least 2 peptides and 95% confidence. Nine proteins showed differences between non-responders and responders (P < 0.05), representing putative biomarkers of response to adalimumab. These results were compared with the previous study of infliximab. Surprisingly, the non-responder/responder differences in the two studies were not correlated (rs = 0.07; P = 0.40). This overall independence with all the proteins showed two identifiable components. On one side, the putative biomarkers of response to either adalimumab or infliximab, which were not shared and showed an inverse correlation (rs = -0.69; P = 0.0023). On the other, eight proteins showing significant non-responder/responder differences in the analysis combining data of response to the two drugs. These results identify new putative biomarkers of response to treatment of rheumatoid arthritis and indicate that they are notably drug-specific.

Generation and Characterization of a New Monoclonal Antibody Against CXCL4

CXCL4 plays important roles in numerous disease processes, which makes the CXCL4 signaling pathway a potential therapeutic target. In this study, we aimed to develop a neutralizing antibody against both human and mouse CXCL4. Rats were immunized with recombinant human CXCL4 (rhCXCL4). Hybridoma clones were created by fusion of the immunized rat spleen cells with mouse myeloma SP2/0 cells and screened using recombinant mouse CXCL4 (rmCXCL4) and rhCXCL4. The CXCL4 monoclonal antibody (CXCL4 MAb) produced by the 16D6-3 hybridoma clone was sequenced and characterized by Western blot and Biacore assays. It recognized both human and mouse CXCL4 with high affinity and neutralized the effect of rhCXCL4 in vitro. Thus, the antibody may be used in the studies of CXCL4 in murine disease models and as a template in the antibody humanization for clinical developments.

Calprotectin (S100A8/A9) and S100A12 are associated with measures of disease activity in a longitudinal study of patients with rheumatoid arthritis treated with infliximab

OBJECTIVES

The pro-inflammatory proteins calprotectin (a heterocomplex of S100A8/A9) and S100A12 have been associated with disease activity in rheumatoid arthritis (RA). The aim of this study was to compare their potential as biomarkers in a prospective study of RA patients starting with infliximab as their first biological disease-modifying anti-rheumatic drug (DMARD).

METHOD

Thirty-nine RA patients were examined and serum samples collected when starting with infliximab and after 3, 6, and 12 months. Calprotectin and S100A12 were analysed by enzyme-linked immunosorbent assays (ELISAs) and, together with C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR), measured at all time points. A disease activity score of 28 joints (DAS28) was calculated. Radiographs of the hands, wrists, and feet were taken at baseline and after 3 years, and assessed according to the modified Sharp/van der Heijde (SvH) score. Responsiveness was evaluated according to the European League of Associations for Rheumatology (EULAR) response criteria based on 28 joints.

RESULTS

Both S100 proteins were significantly higher in seropositive than in seronegative patients (p = 0.01). Calprotectin correlated significantly with CRP (ρ = 0.51-0.75), ESR (ρ = 0.32-0.52), and DAS28 (ρ = 0.32-0.62). S100A12 correlated with calprotectin (ρ = 0.62-0.77) and CRP (ρ = 0.32-0.63). The S100 proteins, and especially calprotectin (ρ = 0.23-0.39), showed weak associations with radiographic progression, unlike CRP/ESR. None of the S100 proteins could predict responsiveness.

CONCLUSIONS

Calprotectin showed the strongest correlation with measures of disease activity and may be better than S100A12 when evaluating disease activity in RA patients. More extensive studies are needed to further compare the predictive value of the S100 proteins relative to radiographic progression.

Identification of cysteinylated transthyretin, a predictive biomarker of treatment response to partially hydrolyzed guar gum in type 2 diabetes rats, by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry

Recent evidence has indicated that total fiber intake is inversely related to type 2 diabetes risk. The present study aimed to investigate the effects of chronic administration of partially hydrolyzed guar gum (PHGG), a water-soluble dietary fiber, on the occurrence of diabetes and its complications, fatty liver and nephropathy. We also identified predictive serum biomarkers of treatment response to PHGG by mass spectroscopy-based proteomic analysis using Otsuka Long-Evans Tokushima Fatty (OLETF) rats, a good model of human non-insulin-dependent diabetes mellitus. In this study, at 5 weeks of age, OLETF rats and control strain Long-Evans Tokushima Otsuka (LETO) rats were fed a control diet or a high-fiber diet (5% PHGG) for 57 weeks. Body weight, food intake, oral glucose tolerance test, plasma insulin levels, and urine glucose and protein levels were regularly measured. Oral glucose tolerance tests (OGTT) and storage of serum in a deep freezer were conducted at the beginning of the experiment and every 4 weeks after overnight fasting during the experiments. PHGG treatment affected neither meal patterns nor the body weight of OLETF and LETO rats. Repeated measure analysis of variance revealed significant differences in fasting plasma glucose and plasma glucose at 2 h after OGTT between control OLETF (OLETF-C) rats and OLETF rats treated with PHGG (OLETF-F). The glucose response determined by the area under the curve of OGTT was significantly greater in OLETF-C rats than that in OLETF-F rats at 25 weeks of age. HOMA-IR, an index of insulin resistance, increased at 25 weeks of age in OLETF-C rats, while this increase was significantly inhibited in OLETF-F rats. At 62 weeks of age, PHGG treatment significantly improved hepatic steatosis as well as renal mesangial matrix accumulation in OLETF rats. To identify the risk marker for diabetes mellitus by SELDI-TOF MS, we collected sera from 21-week-old individuals. Among the 12 specific peaks that were risk marker candidates for diabetes mellitus, the m/z 13,720 peak was identified as that of cysteinylated transthyretin by sequencing of four tryptic peptides using tandem mass spectrometry and peak distribution around the m/z 13,720 peak in the SELDI-TOF spectra. In conclusion, we found that chronic treatment with PHGG improved insulin resistance, delayed the onset of diabetes, and inhibited the development of diabetic complications, as well as identified cysteinylated transthyretin as a predictive biomarker of treatment response to PHGG in OLETF rats.

Identification of 7 Proteins in Sera of RA Patients with Potential to Predict ETA/MTX Treatment Response

Objective: The recent growth of innovating biologics has opened fascinating avenues for the management of patients. In rheumatoid arthritis, many biologics are currently available, the choice of which being mostly determined empirically. Importantly, a given biologic may not be active in a fraction of patients and may even provoke side effects. Here, we conducted a comparative proteomics study in attempt to identify a predictive theranostic signature of non-response in patients with rheumatoid arthritis treated by etanercept/methotrexate combination.

Methods: A serum sample was collected prior to treatment exposure from a cohort of 22 patients with active RA. A proteomic “label free” approach was then designed to quantitate protein biomarkers using mass spectrometry. To verify these results, a relative quantification followed by an absolute quantification of interesting protein candidates were performed on a second cohort. The criterion of judgment was the response to etanercept/methotrexate combination according to the EULAR criteria assessed at 6 months of treatment.

Results: These investigations led to the identification of a set of 12 biomarkers with capacity to predict treatment response. A targeted quantitative analysis allowed to confirm the potential of 7 proteins from the latter combination on a new cohort of 16 patients. Two highly discriminating proteins, PROS and CO7, were further evaluated by ELISA on this second cohort. By combining the concentration threshold of each protein associated to a right classification (responders vs non-responders), the sensitivity and specificity reached 88.9 % and 100 %, respectively.

Conclusion: Prior to methotrexate/etanercept treatment, abundance of several sera proteins, notably PROS and CO7, were associated to response status of RA patients 6 month after treatment initiation.

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.

Pre-treatment whole blood gene expression is associated with 14-week response assessed by dynamic contrast enhanced magnetic resonance imaging in infliximab-treated rheumatoid arthritis patients

Approximately 30% of rheumatoid arthritis patients achieve inadequate response to anti-TNF biologics. Attempts to identify molecular biomarkers predicting response have met with mixed success. This may be attributable, in part, to the variable and subjective disease assessment endpoints with large placebo effects typically used to classify patient response. Sixty-one patients with active RA despite methotrexate treatment, and with MRI-documented synovitis, were randomized to receive infliximab or placebo. Blood was collected at baseline and genome-wide transcription in whole blood was measured using microarrays. The primary endpoint in this study was determined by measuring the transfer rate constant (K_trans) of a gadolinium-based contrast agent from plasma to synovium using MRI. Secondary endpoints included repeated clinical assessments with DAS28(CRP), and assessments of osteitis and synovitis by the RAMRIS method. Infliximab showed greater decrease from baseline in DCE-MRI K_trans of wrist and MCP at all visits compared with placebo (P<0.001). Statistical analysis was performed to identify genes associated with treatment-specific 14-week change in K_trans. The 256 genes identified were used to derive a gene signature score by averaging their log expression within each patient. The resulting score correlated with improvement of K_trans in infliximab-treated patients and with deterioration of K_trans in placebo-treated subjects. Poor responders showed high expression of activated B-cell genes whereas good responders exhibited a gene expression pattern consistent with mobilization of neutrophils and monocytes and high levels of reticulated platelets. This gene signature was significantly associated with clinical response in two previously published whole blood gene expression studies using anti-TNF therapies. These data provide support for the hypothesis that anti-TNF inadequate responders comprise a distinct molecular subtype of RA characterized by differences in pre-treatment blood mRNA expression. They also highlight the importance of placebo controls and robust, objective endpoints in biomarker discovery.

Trial Registration: ClinicalTrials.gov NCT01313520

Identification of autoantibodies against transthyretin for the screening and diagnosis of rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic, autoimmune, systemic and inflammatory rheumatic disease that leads to inflammation of the joints and surrounding tissues. Identification of novel protein(s) associated with severity of RA is a prerequisite for better understanding of pathogenesis of this disease that may also have potential to serve as novel biomarkers in the diagnosis of RA. Present study was undertaken to compare the amount of autoantigens and autoantibodies in the plasma of RA patients in comparison to healthy controls. Plasma samples were collected from the patients suffering from RA, Osteoarthritis (OA), Systemic lupus erythematosus (SLE) and healthy volunteers. The screening of plasma proteins were carried out using 2-dimensional gel electrophoresis followed by identification of differentially expressed protein by MALDI-TOF MS/MS. Among several differentially expressed proteins, transthyretin (TTR) has been identified as one of the protein that showed significantly up regulated expression in the plasma of RA patients. The results were further validated by Western blot analysis and ELISA. In comparison to OA synovium, an exclusive significantly high expression of TTR in RA has been validated through IHC, Western blotting and IEM studies. Most importantly, the increase in expression of TTR with the progression of severity of RA condition has been observed. The autoantibodies against TTR present in the RA plasma were identified using immunoprecipitation-Western methods. The significant production of autoantibodies was validated by ELISA and Western blot analysis using recombinant pure protein of TTR. Hence, these novel observations on increase in TTR expression with the increase in severity of RA conditions and significant production of autoantibodies against TTR clearly suggest that a systematic studies on the role TTR in the pathogenesis of RA is immediately required and TTR may be used as a serum diagnostic marker together with other biochemical parameters and clinical symptoms for RA screening and diagnosis.

The apoB/apoA1 ratio predicts future cardiovascular events in patients with rheumatoid arthritis

OBJECTIVES

Patients with rheumatoid arthritis (RA) have increased mortality and morbidity due to cardiovascular disease (CVD). A high apolipoprotein (apo)B/apoA1 ratio is known to predict cardiovascular events (CVEs) in the population. apoA1 has, besides anti-atherogenic effects, anti-inflammatory properties. The importance of apolipoproteins in the development of CVEs, in the context of lipids, haemostatic factors, and inflammation, was evaluated over 18 years in patients with RA.

METHOD

Seventy-four patients with inflammatory active RA (61 females/13 males, mean age 63.6 years, disease duration 22.1 years) had been previously investigated in a study of haemostatic factors [tissue plasminogen activator (tPA), plasminogen activator inhibitor (PAI)-1, von Willebrand factor (vWF)], lipids (cholesterol and triglycerides), apolipoproteins (apoA1 and apoB), lipoprotein(a) [Lp(a)], and markers of inflammation [erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and haptoglobin]. After 18 years, the first CVE during follow-up and the presence of traditional CV risk factors, extra-articular disease, and pharmacological treatment were registered. Cox proportional hazards regression was used to identify predictors of a new CVE.

RESULTS

A new CVE (n = 34) was predicted by the apoB/apoA1 ratio (p < 0.01), the triglyceride level (p < 0.01), PAI-1 (p < 0.01) and tPA (p < 0.01) activities, vWF (p < 0.001), ESR (< 0.001), CRP (< 0.05), and haptoglobin (p < 0.05). apoA1 (p = 0.056) and apoB (p < 0.05) correlated weakly and inversely with haptoglobin and CRP, respectively. In a multiple Cox regression model, adjusted for gender and previous CVD, the apoB/apoA1 ratio significantly predicted a new CVE, as did vWF, PAI-1, and ESR.

CONCLUSIONS

The apoB/apoA1 ratio was a good predictor of CVE during 18 years of follow-up in patients with active RA. Apolipoproteins correlated negatively with inflammation.

Serum protein profile of Crohn's disease treated with infliximab

The infliximab (IFX) has dramatically improved the treatment of Crohn's disease (CD). However, the need for predictive factors, indicative of patients' response to IFX, has yet to be met. In the current study, proteomics technologies were employed in order to monitor for differences in protein expression in a cohort of patients following IFX administration, aiming at identifying a panel of candidate protein biomarkers of CD, symptomatic of response to treatment. We enrolled 18 patients, who either had achieved clinical and serological remission (Rm, n=6), or response (Rs, n=6) and/or were PNRs (n=6), to IFX. Serum samples were subjected to two-dimensional Gel Electrophoresis. Following evaluation of densitometrical data, protein spots exhibiting differential expression among the groups, were further characterized by MALDI-TOF-MS. Identified proteins where evaluated by immunoblot analysis while functional network association was carried out to asses significance. Proteins apolipoprotein A-I (APOA1), apolipoprotein E (APOE), complement C4-B (CO4B), plasminogen (PLMN), serotransferrin (TRFE), beta-2-glycoprotein 1 (APOH), and clusterin (CLUS) were found to be up-regulated in the PNR and Rs groups whereas their levels displayed no changes in the Rm group when compared to baseline samples. Additionally, leucine-rich alpha-2-glycoprotein (A2GL), vitamin D-binding protein (VTDB), alpha-1B-glycoprotein (A1BG) and complement C1r subcomponent (C1R) were significantly increased in the serum of the Rm group. Through the incorporation of proteomics technologies, novel serum marker-molecules demonstrating high sensitivity and specificity are introduced, hence offering an innovative approach regarding the evaluation of CD patients' response to IFX therapy.

Biologic agents for rheumatoid arthritis: can we hypothesize new strategies of treatment?

Rheumatoid arthritis is a complex multifactorial disease, whose pathogenesis has not been fully elucidated. Biologic agents have revolutionized RA treatment, but a significant percentage of patients does not obtain an adequate response to the therapy. Most of the biologic agents do better if combined with conventional immunosuppressive DMARDs and they show a similar efficacy profile: most of the responders achieve the minimum desirable level of response (ACR20) and only few patients obtain a worthwhile clinical improvement (ACR70 or better). We need to identify new strategies of treatment, able to comply the non satisfied needs of RA patients. Taking inspiration from other medical fields, we could hypothesize a combined regimen in which biologic agents are administered simultaneously at a low or ultra-low dosage, targeting several pathogenetic mechanisms but avoiding important side effects. Alternatively it should be useful to identify rapid succession regimens in which biologic drugs are taken according to an established sequence. Research in this field is obviously not encouraged by pharmaceutical industries, but our efforts should be driven in this direction. According to these observations, adequate clinical trials should be designed to search for appropriate drugs associations and dosages.

Immobilized metal affinity chromatography and human serum proteomics

Metal-binding proteins have a pivotal role in normal and diseased states. We used metal affinity chromatography to enrich a fraction of human serum proteins on immobilized columns loaded with cadmium, nickel, zinc, copper, or lead in bis-Tris saline and these proteins were identified using LC-MS/MS. Tens of enriched proteins were identified and we here present the 20 most abundant for binding each metal. The binding of various proteins (complement C3, alpha-2-macroglobulin, serum albumin, apolipoprotein B-100, complement component 4B preproprotein, apolipoprotein A-I, serotransferrin, alpha-1-antitrypsin, ceruloplasmin, 47kDa protein, uncharacterized protein DKFZp686P15220, transthyretin, hemopexin, inter-alpha-trypsin inhibitor heavy chain H2, and histidine-rich glycoprotein) to different metals using immobilized metal affinity chromatography was compared to the literature. Although many metal-binding properties of these proteins have been confirmed, new metal-binding proteins have also been identified. The metal array use in the proteomic biomarker search technologies gives this data particular importance.

Platelets and autoimmunity

Vascular injury is the initial manifestation of inflammation resulting in the recruitment and activation of various cell types. The integrity of the vascular wall is monitored by platelets that become activated in the presence of exposed subendothelium. Besides their well-established role in haemostasis, ample data are now emerging on the many immunoregulatory functions of platelets. Platelets store and release a large plethora of cytokines, chemokines and growth factors. They also represent the largest circulating pool of many inflammatory mediators like P-selectin, CD40L and non-neuronal serotonin. Furthermore, complement activation occurs on the platelet surface and deposition of complement results in platelet activation. Overall, platelets have multiple functions in both innate and adaptive immunity. Further insight into the multifaceted role of platelets could therefore provide important clues into how we could implement current platelet therapy to reduce both platelet-induced thrombosis and inflammation. In this review, we discuss the current perceptions of platelet involvement in various autoimmune diseases like rheumatoid arthritis, systemic lupus erythematosus, systemic sclerosis and multiple sclerosis.

Metabonomics analysis of plasma reveals the lactate to cholesterol ratio as an independent prognostic factor of short-term mortality in acute heart failure

Objective

Mortality in heart failure (AHF) remains high, especially during the first days of hospitalization. New prognostic biomarkers may help to optimize treatment. The aim of the study was to determine metabolites that have a high prognostic value.

Methods

We conducted a prospective study on a training cohort of AHF patients (n = 126) admitted in the cardiac intensive care unit and assessed survival at 30 days. Venous plasmas collected at admission were used for ¹H NMR–based metabonomics analysis. Differences between plasma metabolite profiles allow determination of discriminating metabolites. A cohort of AHF patients was subsequently constituted (n = 74) to validate the findings.

Results

Lactate and cholesterol were the major discriminating metabolites predicting 30-day mortality. Mortality was increased in patients with high lactate and low total cholesterol concentrations at admission. Accuracies of lactate, cholesterol concentration and lactate to cholesterol (Lact/Chol) ratio to predict 30-day mortality were evaluated using ROC analysis. The Lact/Chol ratio provided the best accuracy with an AUC of 0.82 (P < 0.0001). The acute physiology and chronic health evaluation (APACHE) II scoring system provided an AUC of 0.76 for predicting 30-day mortality. APACHE II score, Cardiogenic shock (CS) state and Lact/Chol ratio ≥ 0.4 (cutoff value with 82% sensitivity and 64% specificity) were significant independent predictors of 30-day mortality with hazard ratios (HR) of 1.11, 4.77 and 3.59, respectively. In CS patients, the HR of 30-day mortality risk for plasma Lact/Chol ratio ≥ 0.4 was 3.26 compared to a Lact/Chol ratio of < 0.4 (P  =  0.018). The predictive power of the Lact/Chol ratio for 30-day mortality outcome was confirmed with the independent validation cohort.

Conclusion

This study identifies the plasma Lact/Chol ratio as a useful objective and simple parameter to evaluate short term prognostic and could be integrated into quantitative guidance for decision making in heart failure care.

Proteomic analysis reveals platelet factor 4 and beta-thromboglobulin as prognostic markers in severe acute respiratory syndrome

Previously, we reported that proteomic fingerprints were present in sera of patients with severe acute respiratory syndrome (SARS), and could separate patients into subgroups with different prognoses. In the present study, we examined the prognostic values of the SARS‐associated proteomic features by biostatistical analysis, and deciphered the identities of those with prognostic values. Data of 20 SARS‐associated serum proteomic features and ten serological variables from 38 SARS adult patients before treatment were subjected to multivariate logistic regression. Proteomic features of m/z 6634, m/z 7769, m/z 8635, and m/z 8865 were identified as independent prognostic markers. After purification by cation‐exchange chromatography and gel electrophoresis, proteomic features of m/z 7769 and m/z 8865 were found to be platelet factor 4 (PF4) and beta‐thromboglobulin (beta‐TG) by tandem mass spectrometry, respectively. The associations of decreased serum PF4 and increased serum beta‐TG levels with poor prognosis were confirmed by Western blot. Previous studies suggest that PF4 and beta‐TG are involved in the pathogenesis of acute respiratory distress syndrome (ARDS) in a negative and positive way, respectively. Our results suggest that PF4 and beta‐TG may also play similar roles in the development of ARDS in SARS patients.

Correlation of antinuclear antibody and anti-double-stranded DNA antibody with clinical response to infliximab in patients with rheumatoid arthritis: a retrospective clinical study

INTRODUCTION

The induction of antinuclear antibodies (ANAs) or anti-double-stranded (ds) -DNA antibodies (Abs) after infliximab (IFX) therapy in rheumatoid arthritis (RA) is a well-known phenomenon, but the correlation of such Abs with the clinical response to IFX has not yet been determined. The aims of this retrospective observational study were to examine the prevalence of positive ANA and anti-ds-DNA Abs before and after IFX therapy in patients with RA and to investigate whether an increased titer of such Abs is associated with the clinical efficacy of IFX.

METHODS

One hundred eleven RA patients who had received IFX were studied. ANA (indirect immunofluorescence with HEp-2 cells) and anti-ds-DNA Abs (Farr assay) results were examined before and after IFX therapy.

RESULTS

The overall clinical response assessed by EULAR response criteria was as follows: good response in 55%, including remission in 38%; moderate response in 18%; and no response (NOR) in 27%. The positivity of ANA (≥ 1:160) and anti-ds-DNA Abs significantly increased from 25% to 40% (P = 0.03) and from 3% to 26% (P < 0.001) after IFX, respectively. EULAR response differed significantly according to the ANA titer before IFX (P = 0.001), and the efficacy of IFX became worse as the ANA titer before starting IFX increased. Furthermore, the differences in the clinical response of the ANA titer before IFX ≤ 1:80 and ≥ 1:160 were significant (good, moderate, and no response were 66%, 9%, and 25% in ≤ 1:80 group versus 26%, 33%, 41% in ≥ 1:160 group, respectively; P < 0.001). In 13 patients whose ANA had increased after IFX, 10 showed NOR, only one showed a good response, and none reached remission. These clinical responses were significantly different from ANA no-change patients. In 21 patients with positive anti-ds-DNA Abs after IFX, 16 showed NOR, only two showed a good response, and none reached remission.

CONCLUSIONS

The present study suggests that the ANA titer before starting IFX predicts the clinical response to IFX. The increased titers of ANA or anti-ds-DNA Abs after IFX may be useful markers of NOR.

Platelet function in rheumatoid arthritis: arthritic and cardiovascular implications

Patients with rheumatoid arthritis (RA) are at high risk of cardiovascular events. Platelet biomarkers are involved in inflammation, atherosclerosis and thrombosis. Cardiovascular and RA-associated factors can alter the structure and function of platelets, starting from megakaryocytopoiesis. Reactive megakaryocytopoiesis increases circulating platelets count and triggers hyperactivity. Hyperactive platelets target synovial membranes with subsequent local rheumatoid inflammation. Hyperactive platelets interact with other cells, and target the vascular wall. Accumulating evidence suggests that disease modifying anti-rheumatic drugs (DMARD) decrease platelet activity.

Platelet function in rheumatoid arthritis: arthritic and cardiovascular implications

Patients with rheumatoid arthritis (RA) are at high risk of cardiovascular events. Platelet biomarkers are involved in inflammation, atherosclerosis and thrombosis. Cardiovascular and RA-associated factors can alter the structure and function of platelets, starting from megakaryocytopoiesis. Reactive megakaryocytopoiesis increases circulating platelets count and triggers hyperactivity. Hyperactive platelets target synovial membranes with subsequent local rheumatoid inflammation. Hyperactive platelets interact with other cells, and target the vascular wall. Accumulating evidence suggests that disease modifying anti-rheumatic drugs (DMARD) decrease platelet activity.

Proteome analysis of biological fluids from autoimmune-rheumatological disorders

Autoimmune-rheumatological diseases are worldwide distributed disorders and represent a complex array of illnesses characterized by autoreactivity (reactivity against self-antigens) of T-B lymphocytes and by the synthesis of autoantibodies crucial for diagnosis (biomarkers). Yet, the effects of the autoimmune chronic inflammation on the infiltrated tissues and organs generally lead to profound tissue and organ damage with loss of function (i.e., lung, kidney, joints, exocrine glands). Although progresses have been made on the knowledge of these disorders, much still remains to be investigated on their pathogenesis and identification of new biomarkers useful in clinical practice. The rationale of using proteomics in autoimmune-rheumatological diseases has been the unmet need to collect, from biological fluids that are easily obtainable, a summary of the final biochemical events that represent the effects of the interplay between immune cells, mesenchymal cells and endothelial cells. Proteomic analysis of these fluids shows encouraging results and in this review, we addressed four major autoimmune-rheumatological diseases investigated through proteomic techniques and provide evidence-based data on the highlights obtained in systemic sclerosis, primary and secondary Sjogren's syndrome, systemic lupus erythematosus and rheumatoid arthritis.

Proteomics in rheumatology: the dawn of a new era

Most rheumatic autoimmune diseases are complex in terms of their genetic origins and underlying pathogenic processes. Non-hypothesis-driven scanning platforms are adding novel insights to our understanding of these multifactorial diseases. This review summarizes the handful of recent proteomic studies that have been executed using samples from patients with rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis, osteoarthritis, or Sjogren's syndrome. The candidate biomarkers that have been uncovered in the reviewed studies have potential applications in diagnosis, prognosis, and theranostics. Though we are at the infancy of the proteomics era in rheumatology, the limited number of molecules uncovered thus far already hold promise. Ongoing research in proteomics holds tremendous potential for shaping how rheumatic diseases are diagnosed, prognosticated, and managed clinically over the coming years.