Advanced immunophenotyping: A powerful tool for immune profiling, drug screening, and a personalized treatment approach.

Various autoimmune diseases are characterized by distinct cell subset distributions and activation profiles of peripheral blood mononuclear cells (PBMCs). PBMCs can therefore serve as an ideal biomarker material, which is easily accessible and allows for screening of multiple cell types. A detailed understanding of the immune landscape is critical for the diagnosis of patients with autoimmune diseases, as well as for a personalized treatment approach. In our study, we investigate the potential of multi-parameter spectral flow cytometry for the identification of patients suffering from autoimmune diseases and its power as an evaluation tool for in vitro drug screening approaches (advanced immunophenotyping). We designed a combination of two 22-color immunophenotyping panels for profiling cell subset distribution and cell activation. Downstream bioinformatics analyses included percentages of individual cell populations and median fluorescent intensity of defined markers which were then visualized as heatmaps and in dimensionality reduction approaches. In vitro testing of epigenetic immunomodulatory drugs revealed an altered activation status upon treatment, which supports the use of spectral flow cytometry as a high-throughput drug screening tool. Advanced immunophenotyping might support the exploration of novel therapeutic drugs and contribute to future personalized treatment approaches in autoimmune diseases and beyond.

Big data analyses and individual health profiling in the arena of rheumatic and musculoskeletal diseases (RMDs).

Health care processes are under constant development and will need to embrace advances in technology and health science aiming to provide optimal care. Considering the perspective of increasing treatment options for people with rheumatic and musculoskeletal diseases, but in many cases not reaching all treatment targets that matter to patients, care systems bare potential to improve on a holistic level. This review provides an overview of systems and technologies under evaluation over the past years that show potential to impact diagnosis and treatment of rheumatic diseases in about 10 years from now. We summarize initiatives and studies from the field of electronic health records, biobanking, remote monitoring, and artificial intelligence. The combination and implementation of these opportunities in daily clinical care will be key for a new era in care of our patients. This aims to inform rheumatologists and healthcare providers concerned with chronic inflammatory musculoskeletal conditions about current important and promising developments in science that might substantially impact the management processes of rheumatic diseases in the 2030s.

EULAR points to consider for the management of difficult-to-treat rheumatoid arthritis.

OBJECTIVE: To develop evidence-based European Alliance of Associations for Rheumatology (EULAR) points to consider (PtCs) for the management of difficult-to-treat rheumatoid arthritis (D2T RA). METHODS: An EULAR Task Force was established comprising 34 individuals: 26 rheumatologists, patient partners and rheumatology experienced health professionals. Two systematic literature reviews addressed clinical questions around diagnostic challenges, and pharmacological and non-pharmacological therapeutic strategies in D2T RA. PtCs were formulated based on the identified evidence and expert opinion. Strength of recommendations (SoR, scale A-D: A typically consistent level 1 studies and D level 5 evidence or inconsistent studies) and level of agreement (LoA, scale 0-10: 0 completely disagree and 10 completely agree) of the PtCs were determined by the Task Force members. RESULTS: Two overarching principles and 11 PtCs were defined concerning diagnostic confirmation of RA, evaluation of inflammatory disease activity, pharmacological and non-pharmacological interventions, treatment adherence, functional disability, pain, fatigue, goal setting and self-efficacy and the impact of comorbidities. The SoR varied from level C to level D. The mean LoA with the overarching principles and PtCs was generally high (8.4-9.6). CONCLUSIONS: These PtCs for D2T RA can serve as a clinical roadmap to support healthcare professionals and patients to deliver holistic management and more personalised pharmacological and non-pharmacological therapeutic strategies. High-quality evidence was scarce. A research agenda was created to guide future research.

The pathogenesis of rheumatoid arthritis: new insights from old clinical data?

Despite their different targets, biologic agents used for blockade of TNF and IL-6, inhibition of T-cell co-stimulation and B-cell depletion all have similar beneficial effects on the outcome of rheumatoid arthritis (RA). This observation raises questions as to whether the targets of these therapies might all be involved in a common pathogenetic pathway. However, blockade of TNF and IL-6 has a similar inhibitory effect on joint damage progression in patients with either early or late disease. In comparison, B-cell depletion and inhibition of T-cell co-stimulation seem to have a somewhat delayed effect on joint damage (compared with cytokine inhibition), which suggests that these approaches affect upstream pathogenetic events. This article discusses these disparities and presents hypotheses as to whether clinical trial data can be used to determine at which point a biologic agent might interfere with the pathogenetic cascade in RA.

Diagnostic and prognostic value of antibodies and soluble biomarkers in undifferentiated peripheral inflammatory arthritis: a systematic review.

OBJECTIVE: When patients present with undifferentiated peripheral inflammatory arthritis (UPIA), early diagnosis and evaluation of prognostic factors are decisive steps for therapeutic success. We reviewed published evidence on the diagnostic and prognostic performance of autoantibodies and soluble biomarkers in UPIA. METHODS: We conducted a systematic literature search covering studies published until January 2009. Additionally, we screened conference abstracts presented at European League Against Rheumatism and American College of Rheumatology meetings in 2007 and 2008. RESULTS: We included 52 full-text articles and 12 abstracts. The association of anti-cyclic citrullinated peptide antibody (anti-CCP) and rheumatoid factor (RF) with diagnosis of rheumatoid arthritis at followup is compelling, supported by positive likelihood ratios (LR+) ranging between 1.2 and 20.5 for anti-CCP and 1.1 to 13.5 for RF. The same applies to radiographic outcome. For antikeratin antibodies (AKA) and antiperinuclear factor, existing evidence suggests diagnostic usefulness; AKA also showed prognostic value. Diagnostic and prognostic evidence for other autoantibodies and for bone and cartilage biomarkers was scarce, negative, or controversial. CONCLUSION: Among serological tests, unanimous evidence of substantial diagnostic value exists only for anti-CCP and RF, but is scarce for other markers.

Disease activity early in the course of treatment predicts response to therapy after one year in rheumatoid arthritis patients.

OBJECTIVE: To assess whether disease activity levels at treatment initiation or during the first 3 months of therapy predict disease activity at 1 year after treatment initiation. METHODS: Pooled patient data from early rheumatoid arthritis (RA) clinical trials (n = 1,342) of methotrexate (MTX), tumor necrosis factor (TNF) inhibitor monotherapy (adalimumab and etanercept), and the combination of the two (adalimumab or infliximab plus MTX) were used for the primary analyses. Pooled data from clinical trials of MTX and of TNF inhibitor plus MTX in late RA (n = 712) were used for validation of the results. Disease activity was primarily assessed using the Simplified Disease Activity Index (SDAI); in addition, we calculated the Disease Activity Score 28-joint assessment (DAS28) and the Clinical Disease Activity Index (CDAI). Associations of disease activity measures at baseline and at 1, 2, 3, and 6 months with disease activity values or disease activity states at 1 year were performed using Spearman's rank correlation, analysis of variance, and diagnostic testing procedures, including receiver operating characteristic (ROC) curve analyses, and probit analysis. RESULTS: Correlations with SDAI values at end point were significant (P < 0.0001) at baseline, and increased to r = approximately 0.6 at 3 months. The area under the ROC curve indicated a high diagnostic test yield with respect to the 1-year outcome (area under the ROC curve approximately 0.8). At all time points, including baseline, the group of patients who achieved remission at 1 year had lower average SDAI values than did those whose disease activity was high at 1 year. The groups achieving low or moderate disease activities at 1 year had SDAI values lying between. Baseline disease activity was less associated with disease activity at the end point for treatment with TNF inhibitor plus MTX, indicating its effectiveness over a broader range of baseline disease activity, but the association with end point disease activity was similar to that in the MTX treatment group at 1 month after treatment initiation. The data were similar when scores on the DAS28 and CDAI were used and were fully validated in the independent cohort of patients with late RA. CONCLUSION: The level of disease activity at baseline and especially during the first 3 months of treatment is significantly related to the level of disease activity at 1 year. Patients who reach a moderate or low disease activity status after 3-6 months of therapy may require switching to alternative therapies. Our findings indicate that intensive and dynamic treatment strategies that include a closer look at disease activity at 3 months in patients with early and late RA is warranted.