Biomarkers for rheumatoid arthritis: making it personal

Relationship Between Serum Interleukin-6 Levels, Systemic Immune-Inflammation Index, and Other Biomarkers Across Different Rheumatoid Arthritis Severity Levels

Background Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by joint inflammation, pain, and progressive disability. Identifying biomarkers that accurately reflect disease severity is crucial for effective management. Interleukin-6 (IL-6) is a pro-inflammatory cytokine involved in the pathogenesis of RA, and the systemic immune-inflammation index (SII) is emerging as a useful marker of systemic inflammation. This study aims to explore the relationship between serum IL-6 levels, SII, and various biomarkers to better predict disease severity in RA patients. Objective To determine the relationship between serum IL-6 levels and the SII, along with various biomarkers, across different severity levels for predicting the severity of RA in patients. Methods This cross-sectional, observational study was conducted at the Mardan Medical Complex from January 2024 to August 2024, involving 67 RA patients. Clinical assessments included demographic data, disease activity (DAS28), pain (VAS), joint damage (Larsen score), and functional status (HAQ-DI). Serum IL-6 levels, along with other biomarkers such as C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and the SII, were measured through fasting blood samples. Statistical analyses, including density plots, scatter plots, boxplots with ANOVA, and random forest models, were performed to explore associations between IL-6 and all other variables. Significance was set at p < 0.05. Results The study included 67 RA patients (mean age: 41.79 ± 10.51 years, 53.73% male). Elevated IL-6 levels (mean: 80.28 ± 35.27 pg/mL) were strongly associated with disease severity. Patients with DAS28 > 5.5 had IL-6 levels over 100 pg/mL, while those in remission had around 40 pg/mL. IL-6 levels correlated with joint damage (100 pg/mL in severe cases) and pain (over 120 pg/mL for severe pain). Patients with metabolic and cardiovascular comorbidities had the highest IL-6 levels, particularly with diabetes and hypertension (98.6 pg/mL) or cardiovascular disease (119.3 pg/mL). IL-6 correlated strongly with CRP (r = 0.65), ESR (r = 0.51), and SII (r = 0.62). Regression confirmed IL-6 as an independent predictor of severity (p < 0.001), with comorbidities being key predictors. Conclusion Elevated IL-6 and SII levels serve as critical markers for predicting the severity of RA. Addressing these markers may lead to more targeted and effective therapeutic strategies for managing disease progression.

Patient outcomes improve when a molecular signature test guides treatment decision-making in rheumatoid arthritis

BACKGROUND

The molecular signature response classifier (MSRC) predicts tumor necrosis factor-ɑ inhibitor (TNFi) non-response in rheumatoid arthritis. This study evaluates decision-making, validity, and utility of MSRC testing.

METHODS

This comparative cohort study compared an MSRC-tested arm (N = 627) from the Study to Accelerate Information of Molecular Signatures (AIMS) with an external control arm (N = 2721) from US electronic health records. Propensity score matching was applied to balance baseline characteristics. Patients initiated a biologic/targeted synthetic disease-modifying antirheumatic drug, or continued TNFi therapy. Odds ratios (ORs) for six-month response were calculated based on clinical disease activity index (CDAI) scores for low disease activity/remission (CDAI-LDA/REM), remission (CDAI-REM), and minimally important differences (CDAI-MID) .

RESULTS

In MSRC-tested patients, 59% had a non-response signature and 70% received MSRC-aligned therapy . In TNFi-treated patients, the MSRC had an 88% PPV and 54% sensitivity. MSRC-guided patients were significantly (p < 0.0001) more likely to respond to b/tsDMARDs than those treated according to standard care (CDAI-LDA/REM: 36.0% vs 21.9%, OR 2.01[1.55-2.60]; CDAI-REM: 10.4% vs 3.6%, OR 3.14 [1.94-5.08]; CDAI-MID: 49.5% vs 32.8%, OR 2.01[1.58-2.55]).

CONCLUSION

MSRC clinical validity supports high clinical utility: guided treatment selection resulted in significantly superior outcomes relative to standard care; nearly three times more patients reached CDAI remission.

Precision medicine in rheumatoid arthritis

Rheumatoid arthritis is an autoimmune disease that causes significant morbidity. Application of cellular profiling techniques such as single-cell transcriptomics and spatial transcriptomics has uncovered novel pathogenic cell types in RA joint tissues and revealed marked heterogeneity in the cellular composition among RA patients. Together, these insights provide exciting opportunities to translate discoveries into precision medicine in RA. The present review aims to highlight novel insights into RA pathology and discuss key steps needed to translate these discoveries into actionable changes in clinical practice. We review the efforts to identify surrogate biomarkers that could be used to predict RA synovial tissue phenotypes and the corresponding responses to therapy. Finally, we discuss the opportunity to develop novel patient-derived organoid systems as a platform for therapeutic target validation.

The Role of Natural Products in Rheumatoid Arthritis: Current Knowledge of Basic In Vitro and In Vivo Research

Rheumatoid arthritis (RA) is an autoimmune disorder affecting a vast variety of the population. The onset of RA as well as the development of systematic immunization is affected by both genetic and environmental risk factors. This review aims to point out the role of natural products in the management of RA, focusing on the reports of basic research (in vitro and animal studies) emphasizing the antioxidant and anti-inflammatory properties considered in the field of RA. A systematic screening of the relevant literature was carried out on PubMed, Google Scholar, and Scopus with the following criteria: publication date, 2015-2020; language, English; study design, in vitro or animal models; and the investigation of one or several natural products in the context of RA, including, when available, the molecular mechanisms implicated. A total of 211 papers were initially obtained and screened. In vitro and animal studies referring to 20 natural products and 15 pure compounds were ultimately included in this review. The outcomes of this work provide an overview of the methods employed in basic research over the past five years, with emphasis on the limitations presented, while demonstrating the potential benefits of utilizing natural products in the management of RA as supported by in vitro and animal studies.

Nutrition and Rheumatoid Arthritis in the 'Omics' Era

Modern high-throughput 'omics' science tools (including genomics, transcriptomics, proteomics, metabolomics and microbiomics) are currently being applied to nutritional sciences to unravel the fundamental processes of health effects ascribed to particular nutrients in humans and to contribute to more precise nutritional advice. Diet and food components are key environmental factors that interact with the genome, transcriptome, proteome, metabolome and the microbiota, and this life-long interplay defines health and diseases state of the individual. Rheumatoid arthritis (RA) is a chronic autoimmune disease featured by a systemic immune-inflammatory response, in genetically susceptible individuals exposed to environmental triggers, including diet. In recent years increasing evidences suggested that nutritional factors and gut microbiome have a central role in RA risk and progression. The aim of this review is to summarize the main and most recent applications of 'omics' technologies in human nutrition and in RA research, examining the possible influences of some nutrients and nutritional patterns on RA pathogenesis, following a nutrigenomics approach. The opportunities and challenges of novel 'omics technologies' in the exploration of new avenues in RA and nutritional research to prevent and manage RA will be also discussed.

The Progression of Hemophilic Arthropathy: The Role of Biomarkers

BACKGROUND

Hemophilia A and B are X-linked congenital bleeding disorders characterized by recurrent hemarthroses leading to specific changes in the synovium and cartilage, which finally result in the destruction of the joint: this process is called hemophilic arthropathy (HA). This review highlights the most prominent molecular biomarkers found in the literature to discuss their potential use in the clinical practice to monitor bleeding, to assess the progression of the HA and the effectiveness of treatments.

METHODS

A review of the literature was performed on PubMed and Embase, from 3 to 7 August 2020. Study selection and data extraction were achieved independently by two authors and the following inclusion criteria were determined a priori: English language, available full text and articles published in peer-reviewed journal. In addition, further articles were identified by checking the bibliography of relevant articles and searching for the studies cited in all the articles examined.

RESULTS

Eligible studies obtained at the end of the search and screen process were seventy-three (73).

CONCLUSIONS

Despite the surge of interest in the clinical use of biomarkers, current literature underlines the lack of their standardization and their potential use in the clinical practice preserving the role of physical examination and imaging in early diagnosis.

A budget impact analysis for making treatment decisions based on anti-cyclic citrullinated peptide (anti-CCP) testing in rheumatoid arthritis

Aim: Given that rheumatoid arthritis (RA) patients with high anti-citrullinated protein antibodies (ACPA) titer values respond well to abatacept, the aim of this study was to estimate the annual budget impact of anti-cyclic citrullinated peptide (anti-CCP) testing and treatment selection based on anti-CCP test results.Materials and methods: Budget impact analysis was conducted for patients with moderate-to-severe RA on biologic or Janus kinase inhibitor (JAKi) treatment from a hypothetical US commercial payer perspective. The following market scenarios were compared: (1) 90% of target patients receive anti-CCP testing and the results of anti-CCP testing do not impact the treatment selection; (2) 100% of target patients receive anti-CCP testing and the results of anti-CCP testing have an impact on treatment selection such that an increased proportion of patients with high titer of ACPA receive abatacept. A hypothetical assumption was made that the use of abatacept would be increased by 2% in Scenario 2 versus 1. Scenario analyses were conducted by varying the target population and rebate rates.Results: In a hypothetical health plan with one million insured adults, 2,181 patients would be on a biologic or JAKi treatment for moderate-to-severe RA. In Scenario 1, the anti-CCP test cost was $186,155 and annual treatment cost was $101,854,295, totaling to $102,040,450. In Scenario 2, the anti-CCP test cost increased by $20,684 and treatment cost increased by $160,467, totaling an overall budget increase of $181,151. This was equivalent to a per member per month (PMPM) increase of $0.015. The budget impact results were consistently negligible across the scenario analyses.Limitations: The analysis only considered testing and medication costs. Some parameters used in the analysis, such as the rebate rates, are not generalizable and health plan-specific.Conclusions: Testing RA patients to learn their ACPA status and increasing use of abatacept among high-titer ACPA patients result in a small increase in the total budget (<2 cents PMPM).

Composite contributions of cerebrospinal fluid GABAergic neurosteroids, neuropeptide Y and interleukin-6 to PTSD symptom severity in men with PTSD

Given that multiple neurobiological systems, as well as components within these systems are impacted by stress, and may interact in additive, compensatory and synergistic ways to promote or mitigate PTSD risk, severity, and recovery, we thought that it would be important to consider the collective, as well as separate effects of these neurobiological systems on PTSD risk. With this goal in mind, we conducted a proof-of-concept study utilizing cerebrospinal fluid (CSF) collected from unmedicated, tobacco- and illicit substance-free men with PTSD (n = 13) and trauma-exposed healthy controls (TC) (n = 17). Thirteen neurobiological factors thought to contribute to PTSD risk or severity based on previous studies were assayed. As the small but typical sample size of this lumbar puncture study limited the number of factors that could be considered in a hierarchical regression model, we included only those five factors with at least a moderate correlation (Spearman rho > 0.30) with total Clinician-Administered PTSD Scale (CAPS-IV) scores, and that did not violate multicollinearity criteria. Three of the five factors meeting these criteria—CSF allopregnanolone and pregnanolone (Allo + PA: equipotent GABAergic metabolites of progesterone), neuropeptide Y (NPY), and interleukin-6 (IL-6)—were found to account for over 75% of the variance in the CAPS-IV scores (R² = 0.766, F = 8.75, p = 0.007). CSF Allo + PA levels were negatively associated with PTSD severity (β = −0.523, p = 0.02) and accounted for 47% of the variance in CAPS-IV scores. CSF NPY was positively associated with PTSD severity (β = 0.410, p = 0.04) and accounted for 14.7% of the CAPS-IV variance. There was a trend for a positive association between PTSD severity and CSF IL-6 levels, which accounted for 15.3% of the variance in PTSD severity (β = 0.423, p = 0.05). Z-scores were then computed for each of the three predictive factors and used to depict the varying relative degrees to which each contributed to PTSD severity at the individual PTSD patient level. This first of its kind, proof-of-concept study bears replication in larger samples. However, it highlights the collective effects of dysregulated neurobiological systems on PTSD symptom severity and the heterogeneity of potential biological treatment targets across individual PTSD patients—thus supporting the need for precision medicine approaches to treatment development and prescribing in PTSD.

Levels of CXCL13 and sICAM-1 correlate with disease activity score in patients with rheumatoid arthritis treated with tocilizumab

Background

Tocilizumab (TCZ), a humanized monoclonal antibody against the interleukin-6 receptor, has been proven to be a safe and effective treatment for rheumatoid arthritis (RA). Because RA is a heterogenous disease and patient response to treatments can vary, identifying characteristics that predict which patients are more likely to respond to TCZ is important for optimal patient care. Serum levels of C-X-C motif chemokine ligand 13 (CXCL13) and soluble intercellular adhesion molecule-1 (sICAM-1) have been associated with response to TCZ in patients with RA.

Objectives

To evaluate the association of CXCL13 and sICAM-1 with disease activity and response to TCZ in patients with early RA and those with inadequate response to disease-modifying antirheumatic drugs (DMARD-IR).

Methods

Baseline and week 24 serum CXCL13 and sICAM-1 levels were measured using available patient samples from the FUNCTION (early RA) and LITHE (DMARD-IR) trials. Correlations between CXCL13 and sICAM-1 levels and Disease Activity Score in 28 joints calculated with erythrocyte sedimentation rate (DAS28-ESR) at baseline and between change in CXCL13 and sICAM-1 and change in DAS28-ESR at week 24 were estimated. CXCL13 and sICAM-1 changes from baseline to week 24 were compared between treatment arms. The effects of TCZ treatment and baseline DAS28-ESR, CXCL13 and sICAM-1 levels on DAS28-ESR remission and 50% improvement per the American College of Rheumatology (ACR50) response at week 24 were determined.

Results

Overall, 458 patients from FUNCTION and 287 patients from LITHE were included. Correlation of baseline serum CXCL13 and sICAM-1 levels with DAS28-ESR was weak to moderate. CXCL13 and sICAM-1 levels decreased significantly at week 24 in TCZ-treated patients in both the early-RA and DMARD-IR populations. CXCL13 and sICAM-1 changes correlated moderately to weakly with DAS28-ESR changes at week 24 in both populations. The treatment regimen, but not baseline CXCL13 and sICAM-1 levels, had a significant effect on the likelihood of DAS28-ESR remission and ACR50 response.

Conclusions

Although CXCL13 and sICAM-1 are modestly associated with RA disease activity, they do not predict response to TCZ in all RA populations.

Identification of pathological RA endotypes using blood-based biomarkers reflecting tissue metabolism. A retrospective and explorative analysis of two phase III RA studies

There is an increasing demand for accurate endotyping of patients according to their pathogenesis to allow more targeted treatment. We explore a combination of blood-based joint tissue metabolites (neoepitopes) to enable patient clustering through distinct disease profiles. We analysed data from two RA studies (LITHE (N = 574, follow-up 24 and 52 weeks), OSKIRA-1 (N = 131, follow-up 24 weeks)). Two osteoarthritis (OA) studies (SMC01 (N = 447), SMC02 (N = 81)) were included as non-RA comparators. Specific tissue-derived neoepitopes measured at baseline, included: C2M (cartilage degradation); CTX-I and PINP (bone turnover); C1M and C3M (interstitial matrix degradation); CRPM (CRP metabolite) and VICM (macrophage activity). Clustering was performed to identify putative endotypes. We identified five clusters (A-E). Clusters A and B were characterized by generally higher levels of biomarkers than other clusters, except VICM which was significantly higher in cluster B than in cluster A (p<0.001). Biomarker levels in Cluster C were all close to the median, whilst Cluster D was characterised by low levels of all biomarkers. Cluster E also had low levels of most biomarkers, but with significantly higher levels of CTX-I compared to cluster D. There was a significant difference in ΔSHP score observed at 52 weeks (p<0.05). We describe putative RA endotypes based on biomarkers reflecting joint tissue metabolism. These endotypes differ in their underlining pathogenesis, and may in the future have utility for patient treatment selection.

CTHRC1: A New Candidate Biomarker for Improved Rheumatoid Arthritis Diagnosis

Background: The purpose of this study was to determine whether plasma levels of the collagen triple helix repeat containing 1 (CTHRC1) protein can serve as a blood-based biomarker for improved diagnosis of rheumatoid arthritis (RA) patients and monitoring of RA disease activity.

Methods: We measured levels of CTHRC1 in the plasma of patients diagnosed with RA, osteoarthritis (OA), reactive arthritis (ReA), as well as in healthy individuals. We then assessed the correlation between CTHRC1 protein and a range of indices including the 28-joint disease activity score (DAS28), rheumatoid factor (RF), C-reactive protein (CRP), anti-citrullinated protein antibodies (ACPA), erythrocyte sedimentation rate (ESR), as well as a panel of cytokines, including interleukin 1 beta (IL-1β), interleukin 6 (IL-6), interleukin 8 (IL-8), and interferon gamma (IFNγ). Receiver operating characteristic (ROC) analysis was further performed to assess the diagnostic value of CTHRC1.

Results: CTHRC1 plasma levels were significantly elevated in RA patients compared to healthy individuals, OA and ReA patients. ROC curve and risk score analysis suggested that plasma CTHRC1 can accurately discriminate patients with RA from healthy controls and may have practical value for RA diagnosis. CTHRC1 levels were positively associated with RF, ACPA, CRP, and disease activity based on the combined index of DAS28 with CRP (DAS28-CRP), and also strongly correlated with IL-1β, IL-6, IL-8, and IFNγ.

Conclusion: Our studies show that CTHRC1 is a sensitive and easy-to-measure plasma marker that differentiates between RA and healthy status and also distinguishes between RA and other forms of arthritis, such as OA and ReA. At the current level of understanding, plasma CTHRC1 levels may improve the diagnosis of RA and these findings warrant confirmation in a larger, more comprehensive patient population.

The potential impact of monitoring disease activity biomarkers on rheumatoid arthritis outcomes and costs

Rheumatoid arthritis (RA) management requires monitoring of disease activity to determine course of treatment. Global assessments are used in clinical practice to determine RA disease activity. Monitoring disease activity via biomarkers may also help providers optimize biologic and nonbiologic drug use while decreasing overall drug spend by delaying use of expensive biologic therapies. By testing multiple biologic domains at the same time, a multibiomarker disease activity test may have utility in RA patient management, through improved intra- and inter-rater reliability. This report provides a comprehensive review of studies of objective measures, single biomarkers and multibiomarker disease activity tests as disease activity measures to decrease uncertainty in treatment decisions, and of biomarkers’ potential impact on economic and clinical outcomes of treatment choices.

A Clinician's Perspective on Biomarkers

Psychiatrists and mental health professionals regularly perform various clinical tasks (e.g., detection, differential diagnosis, prognostication, treatment selection and implementation). How well they perform each of these tasks has a direct impact on patient outcomes. Measurement-based care has brought greater precision to these tasks and has improved outcomes. This article provides an overview of the types of biomeasures and biomarkers, the clinical uses of biomarkers, and the challenges in their development and clinical use. Although still in their infancy, biomarkers hold the promise of bringing even greater precision and even better outcomes in mental health. Biomeasures that could become biomarkers include genetic, proteomic, metabolomic, and immunologic measures, as well as physiological, functional, and brain structural measures. Mechanistic markers reflect and are based on the specific pathobiological processes that are involved in the development of a clinically defined condition. Some clinically relevant biomarkers may rely on this mechanistic understanding while others may not. Clinical biomarkers serve three broadly defined goals. Diagnostic markers define what is wrong. Prognostic markers define what will happen in the natural course of the condition, although they may also predict the course of illness during treatment. Theranostic markers address issues pertinent to treatment by defining whether, when, whom, and how to treat. Other biomarkers may be used to monitor the overall effect of treatment regardless of the therapeutic effects or to monitor the specific therapeutic effects of the intervention on the disorder itself. Biomarkers can also be used to estimate susceptibility/risk of developing the condition or the biological consequences of having had the disorder.

Characterization of neutrophil-to-lymphocyte ratio as a measure of inflammation in rheumatoid arthritis

OBJECTIVES

The neutrophil to lymphocyte ratio (NLR) is one of the well-recognized sensitive measures of inflammation. This cross-sectional observational study was aimed at characterizing the relationship of NLR with the inflammatory markers erythrocyte sedimentation rate (ESR), C-reative protein (CRP), Disease Activity Score of 28 joints (DAS28)-CRP(3), joint counts and quality measures of rheumatoid arthritis (RA).

MATERIALS AND METHODS

Patients with RA were recruited in two phases. The following were assessed for all patients: joint count, pain by visual analogue scale (VAS), complete blood count, ESR, CRP and quality index assessment using the Short Form health survey (SF-36) questionnaire. A subgroup analysis was also performed to evaluate the association between NLR and cytokines.

RESULTS

Four hundred and eighty-nine subjects were recruited. Distribution of NLR values corresponded with DAS28-CRP(3) rather than CRP and ESR. A significant difference in VAS, swollen joint counts (SJC-28), inflammatory parameters and general health outcome measures was observed among the NLR groups. A weak correlation was observed between NLR and RA disease measures. It had least bias at lower ranges with DAS28-CRP(3) than CRP and ESR. The NLR cut-off value of 1.4 classified the patients in deep remission with 90% specificity, 24% sensitivity, likelihood ratio positive (LR+) 2.46 and likelihood ratio negative (LR-) 0.84. CRP was a significant baseline predictor of NLR. A significant influence of interleukin-6 on CRP was noted.

CONCLUSION

In contrast to the traditional markers, NLR may serve as a less expensive and effective measure of inflammation in RA. Its efficacy is comparable to that of CRP and it is not impacted by the cytokines influencing CRP and ESR.

A proteomic profile of synoviocyte lesions microdissected from formalin-fixed paraffin-embedded synovial tissues of rheumatoid arthritis

Background

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic inflammation of the synovial joints. Early intervention followed by early diagnosis can result in disease remission; however, both early stage diagnosis and provision of effective treatment have been impeded by the heterogeneity of RA, which details of pathological mechanism are unclear. Regardless of numerous investigations of RA by means of genomic and proteomic approaches, proteins interplaying in RA synovial tissues that contain various types of synoviocytes, are not yet sufficiently understood. Hence we have conducted an HPLC/mass spectrometry-based exploratory proteomic analysis focusing on synoviocyte lesions laser-microdissected (LMD) from formalin-fixed paraffin-embedded (FFPE) synovial tissues (RA, n = 15; OA, n = 5), where those of Osteoarthritis (OA) were used as the control.

Results

A total of 508 proteins were identified from the RA and OA groups. With the semi-quantitative comparisons, the spectral index (SpI), log2 protein ratio (R_SC) based on spectral counting, and statistical G-test, 98 proteins were found to be significant (pair-wise p < 0.05) to the RA synovial tissues. These include stromelysin-1 (MMP3), proteins S100-A8 and S100-A9, plastin-2, galectin-3, calreticulin, cathepsin Z, HLA-A, HLA-DRB1, ferritin, neutrophil defensin 1, CD14, MMP9 etc.

Conclusions

Our results confirmed the involvement of known RA biomarkers such as stromelysin-1 (MMP3) and proteins S100-A8 and S100-A9, and also that of leukocyte antigens such as HLA-DRB1. Network analyses of protein–protein interaction for those proteins significant to RA revealed a dominant participation of ribosome pathway (p = 5.91 × 10⁻⁴⁵), and, interestingly, the associations of the p53 signaling (p = 2.34 × 10⁻⁵). An involvement of proteins including CD14, S100-A8/S100-A9 seems to suggest an activation of the NF-kB/MAPK signaling pathway. Our strategy of laser-microdissected FFPE-tissue proteomic analysis in Rheumatoid Arthritis thus demonstrated its technical feasibility in profiling proteins expressed in synovial tissues, which may play important roles in the RA pathogenesis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-015-9091-8) contains supplementary material, which is available to authorized users.

Pretreatment Prediction of Individual Rheumatoid Arthritis Patients' Response to Anti-Cytokine Therapy Using Serum Cytokine/Chemokine/Soluble Receptor Biomarkers

The inability to match rheumatoid arthritis (RA) patients with the anti-cytokine agent most efficacious for them is a major hindrance to patients’ speedy recovery and to the clinical use of anti-cytokine therapy. Identifying predictive biomarkers that can assist in matching RA patients with more suitable anti-cytokine treatment was our aim in this report. The sample consisted of 138 RA patients (naïve and non-naïve) who were administered tocilizumab or etanercept for a minimum of 16 weeks as a prescribed RA treatment. Pretreatment serum samples were obtained from patients and clinical measures of their disease activity were evaluated at baseline and 16 weeks after treatment commenced. Using patients’ pretreatment serum, we measured 31 cytokines/chemokines/soluble receptors and used multiple linear regression analysis to identify biomarkers that correlated with patients’ symptom levels (DAS28-CRP score) at week 16 and multiple logistic analyses for biomarkers that correlated with patients’ final outcome. The results revealed that sgp130, logIL-6, logIL-8, logEotaxin, logIP-10, logVEGF, logsTNFR-I and logsTNFR-II pretreatment serum levels were predictive of the week 16 DAS28-CRP score in naïve tocilizumab patients while sgp130, logGM-CSF and logIP-10 were predictive in non-naïve patients. Additionally, we found logIL-9, logVEGF and logTNF-α to be less reliable at predicting the week 16 DAS28-CRP score in naïve etanercept patients. Multiple linear regression and multiple logistic regression analyses identified biomarkers that were predictive of remission/non-remission in tocilizumab and etanercept therapy. Although less reliable than those for tocilizumab, we identified a few possible biomarkers for etanercept therapy. The biomarkers for these two therapies differ suggesting that their efficacy will vary for individual patients. We discovered biomarkers in RA pretreatment serum that predicted their week 16 DAS28-CRP score and clinical outcome to tocilizumab therapy. Most of these biomarkers, especially sgp130, are involved in RA pathogenesis and IL-6 signal transduction, which further suggests that they are highly reliable.

Mass cytometry as a platform for the discovery of cellular biomarkers to guide effective rheumatic disease therapy

The development of biomarkers for autoimmune diseases has been hampered by a lack of understanding of disease etiopathogenesis and of the mechanisms underlying the induction and maintenance of inflammation, which involves complex activation dynamics of diverse cell types. The heterogeneous nature and suboptimal clinical response to treatment observed in many autoimmune syndromes highlight the need to develop improved strategies to predict patient outcome to therapy and personalize patient care. Mass cytometry, using CyTOF®, is an advanced technology that facilitates multiparametric, phenotypic analysis of immune cells at single-cell resolution. In this review, we outline the capabilities of mass cytometry and illustrate the potential of this technology to enhance the discovery of cellular biomarkers for rheumatoid arthritis, a prototypical autoimmune disease.

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.

Synovial phenotypes in rheumatoid arthritis correlate with response to biologic therapeutics

INTRODUCTION

Rheumatoid arthritis (RA) is a complex and clinically heterogeneous autoimmune disease. Currently, the relationship between pathogenic molecular drivers of disease in RA and therapeutic response is poorly understood.

METHODS

We analyzed synovial tissue samples from two RA cohorts of 49 and 20 patients using a combination of global gene expression, histologic and cellular analyses, and analysis of gene expression data from two further publicly available RA cohorts. To identify candidate serum biomarkers that correspond to differential synovial biology and clinical response to targeted therapies, we performed pre-treatment biomarker analysis compared with therapeutic outcome at week 24 in serum samples from 198 patients from the ADACTA (ADalimumab ACTemrA) phase 4 trial of tocilizumab (anti-IL-6R) monotherapy versus adalimumab (anti-TNFα) monotherapy.

RESULTS

We documented evidence for four major phenotypes of RA synovium - lymphoid, myeloid, low inflammatory, and fibroid - each with distinct underlying gene expression signatures. We observed that baseline synovial myeloid, but not lymphoid, gene signature expression was higher in patients with good compared with poor European league against rheumatism (EULAR) clinical response to anti-TNFα therapy at week 16 (P =0.011). We observed that high baseline serum soluble intercellular adhesion molecule 1 (sICAM1), associated with the myeloid phenotype, and high serum C-X-C motif chemokine 13 (CXCL13), associated with the lymphoid phenotype, had differential relationships with clinical response to anti-TNFα compared with anti-IL6R treatment. sICAM1-high/CXCL13-low patients showed the highest week 24 American College of Rheumatology (ACR) 50 response rate to anti-TNFα treatment as compared with sICAM1-low/CXCL13-high patients (42% versus 13%, respectively, P =0.05) while anti-IL-6R patients showed the opposite relationship with these biomarker subgroups (ACR50 20% versus 69%, P =0.004).

CONCLUSIONS

These data demonstrate that underlying molecular and cellular heterogeneity in RA impacts clinical outcome to therapies targeting different biological pathways, with patients with the myeloid phenotype exhibiting the most robust response to anti-TNFα. These data suggest a path to identify and validate serum biomarkers that predict response to targeted therapies in rheumatoid arthritis and possibly other autoimmune diseases.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01119859

Serum inflammatory mediators as markers of human Lyme disease activity

Chemokines and cytokines are key signaling molecules that orchestrate the trafficking of immune cells, direct them to sites of tissue injury and inflammation and modulate their states of activation and effector cell function. We have measured, using a multiplex-based approach, the levels of 58 immune mediators and 7 acute phase markers in sera derived from of a cohort of patients diagnosed with acute Lyme disease and matched controls. This analysis identified a cytokine signature associated with the early stages of infection and allowed us to identify two subsets (mediator-high and mediator-low) of acute Lyme patients with distinct cytokine signatures that also differed significantly (p<0.0005) in symptom presentation. In particular, the T cell chemokines CXCL9 (MIG), CXCL10 (IP-10) and CCL19 (MIP3B) were coordinately increased in the mediator-high group and levels of these chemokines could be associated with seroconversion status and elevated liver function tests (p = 0.027 and p = 0.021 respectively). There was also upregulation of acute phase proteins including CRP and serum amyloid A. Consistent with the role of CXCL9/CXCL10 in attracting immune cells to the site of infection, CXCR3+ CD4 T cells are reduced in the blood of early acute Lyme disease (p = 0.01) and the decrease correlates with chemokine levels (p = 0.0375). The levels of CXCL9/10 did not relate to the size or number of skin lesions but elevated levels of serum CXCL9/CXCL10 were associated with elevated liver enzymes levels. Collectively these results indicate that the levels of serum chemokines and the levels of expression of their respective chemokine receptors on T cell subsets may prove to be informative biomarkers for Lyme disease and related to specific disease manifestations.

Interleukin-1 receptor antagonist gene polymorphism and hepcidin in rheumatoid arthritis: Correlations with clinical and laboratory indices of disease activity

Rheumatoid arthritis (RA) is a systemic autoimmune disease, which is manifested as an inflammatory polyarthritis. Authors aimed to analyze the relationship between serum hepcidin, 25 amino acid protein, concentration and the anemia profiles of RA and to estimate whether it could reflect the disease activity of RA. Also, this study was conducted to explore the linkage between interleukin-1 (IL-1) receptor antagonist gene (IL-1RN) polymorphism, proinflammatory cytokine, and RA. One hundred and eighty five RA patients were enrolled in the study. For all, the following criteria were measured: RA disease activities, anemia profiles, serum concentration of hepcidin using enzyme-linked immunosorbent assay, and DNA samples were used to study genotypes of IL-1RN gene by polymerase chain reaction. Mean concentration of serum pro-hepcidin was (93.6 ± 31.5 ng/mL) in 185 RA patients. An increased frequency of the IL-1RN*1 and IL-1RN*2 alleles was relative to active RA (DAS28 > 5.1) than those with inactive to moderate RA (DAS28 ≤ 5.1). Both hepcidin and IL-1RN gene showed significant correlation with each other as well with RA disease activity parameters and anemia profile. IL-1RN gene was significantly correlated with laboratory anemia profile apart from transferritin. There was a significant difference among pro-hepcidin concentration and IL-1RN frequency regarding patients with anemia of chronic disease and those without. In conclusion, both serum concentration of pro-hepcidin and IL-1RN genotypes frequency reflect the disease activity, regardless of the anemia states in RA patients, thus they may be another potential markers for disease activity of RA.

Autoantibodies to posttranslationally modified type II collagen as potential biomarkers for rheumatoid arthritis

OBJECTIVE

Type II collagen (CII) posttranslationally modified by reactive oxygen species (ROS-CII) that are present in the inflamed joint is an autoantigen in rheumatoid arthritis (RA). The aim of this study was to investigate the potential use of anti-ROS-CII autoantibodies as a biomarker of RA.

METHODS

CII was exposed to oxidants that are present in the rheumatoid joint. Autoreactivity to ROS-CII was assessed by enzyme-linked immunosorbent assays in synovial fluid (SF) and serum samples obtained from patients during various phases of RA. This group included disease-modifying antirheumatic drug (DMARD)-naive patients with early RA (n = 85 serum samples) and patients with established RA (n = 80 serum and 50 SF samples), who were categorized as either DMARD responders or DMARD nonresponders. Control subjects included anti-citrullinated protein antibody (ACPA)-positive patients with arthralgia (n = 58 serum samples), patients with osteoarthritis (OA; n = 49 serum and 52 SF samples), and healthy individuals (n = 51 serum samples).

RESULTS

Reactivity to ROS-CII among DMARD-naive patients with early RA was significantly higher than that among patients with ACPA-positive arthralgia, patients with OA, and healthy control subjects (P < 0.0001), with 92.9% of serum samples from the patients with early RA binding to anti-ROS-II. There was no significant difference in anti-ROS-CII reactivity between ACPA-positive and ACPA-negative patients with RA, with 93.8% and 91.6% of serum samples, respectively, binding to ROS-CII. The sensitivity and specificity of binding to ROS-CII in patients with early RA were 92% and 98%, respectively. Among patients with established RA, serum reactivity in DMARD nonresponders was significantly higher than that in DMARD responders (P < 0.01); 58.3% of serum samples from nonresponders and 7.6% of serum samples from responders bound to HOCl-ROS, while the respective values for SF were 70% and 60%. In patients with longstanding RA, autoreactivity to ROS-CII changed longitudinally.

CONCLUSION

Autoantibodies to ROS-CII have the potential to become diagnostic biomarkers of RA.

Fibronectin molecular status determination useful to differentiate between rheumatoid arthritis and systemic lupus erythematosus patients

To find whether the plasma fibronectin (FN) molecular status can be useful to differentiate between rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). The expression of plasma FN domains was determined by ELISA using monoclonal domain-specific antibodies. FN molecular forms were revealed by immunoblotting and analyzed by densitometry. The following findings were found: (1) Mean values of ^{Fibrin–Heparin}FN concentration were lower in SLE and RA patients than in normal plasmas. The cut off points at 31 mg/l in SLE and at 45 mg/l in RA showed a sensitivity and specificity of 54, 55 and 75%, respectively. (2) Mean values of concentrations of ^CBDFN and ^CtFN were lower in SLE than those in normal and RA plasmas. Quantified data showed the cut off points of ^CBDFN and ^CtFN at 200 mg/l (58% of sensitivity, 56% of specificity) and 350 mg/l (58% of sensitivity, 58% of specificity) in SLE, as well as at 295 mg/l (52% of sensitivity, 51% of specificity) and 460 mg/l in RA (70% of sensitivity, 73% of specificity). (3) The plasma FN immunopatterns, characterized by the presence of high-molecular (260–310 kDa) and/or low-molecular (158–209 kDa) FN bands, were specific only for SLE samples. The analysis of plasma FN status revealed by its Fibrin-Heparin-, CBD- and Ct-domain reactivity with monoclonal antibody and immunoblotting can be helpful to differentiate the SLE in respect to RA and normal plasmas.

Detection of inflammatory arthritis by using hyperpolarized 13C-pyruvate with MR imaging and spectroscopy

PURPOSE

To examine the feasibility of using magnetic resonance (MR) spectroscopy with hyperpolarized carbon 13 ((13)C)-labeled pyruvate to detect inflammation.

MATERIALS AND METHODS

The animal care and use committee approved all work with animals. Arthritis was induced in the right hind paw of six rats; the left hind paw served as an internal control. The lactate dehydrogenase-catalyzed conversion of pyruvate to lactate was measured in inflamed and control paws by using (13)C MR spectroscopy. Clinical and histologic data were obtained to confirm the presence and severity of arthritis. Hyperpolarized (13)C-pyruvate was intravenously injected into the rats before simultaneous imaging of both paws with (13)C MR spectroscopy. The Wilcoxon signed rank test was used to test for differences in metabolites between the control and arthritic paws.

RESULTS

All animals showed findings of inflammation in the affected paws and no signs of arthritis in the control paws at both visible inspection (clinical index of 3 for arthritic paws and 0 for control paws) and histologic examination (histologic score of 3-5 for arthritic paws and 0 for control paws). Analysis of the spectroscopic profiles of (13)C-pyruvate and converted (13)C-lactate showed an increase in the amount of (13)C-lactate in inflamed paws (median lactate-to-pyruvate ratio, 0.50; mean lactate-to-pyruvate ratio ± standard deviation, 0.52 ± 0.16) versus control paws (median lactate-to-pyruvate ratio, 0.27; mean lactate-to-pyruvate ratio, 0.32 ± 0.11) (P < .03). The ratio of (13)C-lactate to total (13)C was also significantly increased in inflamed paws compared with control paws (P < .03).

CONCLUSION

These results suggest that alterations in the conversion of pyruvate to lactate as detected with (13)C-MR spectroscopy may be indicative of the presence of inflammatory arthritis.