The clinical and molecular cardiometabolic fingerprint of an exploratory psoriatic arthritis cohort is associated with the disease activity and differentially modulated by methotrexate and apremilast

OBJECTIVES

(1) To evaluate clinical and molecular cardiovascular disease (CVD) signs and their relationship with psoriatic arthritis (PsA) features and (2) to identify a clinical patient profile susceptible to benefit from methotrexate (MTX) and/or apremilast regarding CVD risk.

METHODS

This cross-sectional study included 100 patients with PsA and 100 age-matched healthy donors. In addition, an exploratory cohort of 45 biologically naïve patients treated for 6 months with apremilast, MTX or combined therapy according to routine clinical practice was recruited. Extensive clinical and metabolic profiles were obtained. Ninety-nine surrogate CVD-related molecules were analysed in plasma and peripheral blood mononuclear cells (PBMCs). Hard cluster analysis was performed to identify the clinical and molecular phenotypes. Mechanistic studies were performed on adipocytes.

RESULTS

Cardiometabolic comorbidities were associated with disease activity and long-term inflammatory status. Thirty-five CVD-related proteins were altered in the plasma and PBMCs of PsA patients and were associated with the key clinical features of the disease. Plasma levels of some of the CVD-related molecules might distinguish insulin-resistant patients (MMP-3, CD163, FABP-4), high disease activity (GAL-3 and FABP-4) and poor therapy outcomes (CD-163, LTBR and CNTN-1). Hard cluster analysis identified two phenotypes of patients according to the rates of cardiometabolic comorbidities with distinctive clinical and molecular responses to each treatment.

CONCLUSIONS

(1) Novel CVD-related proteins associated with clinical features could be emerging therapeutic targets in the context of PsA and (2) the pleiotropic action of apremilast could make it an excellent choice for the management of PsA patients with high CVD risk, targeting metabolic alterations and CVD-related molecules.

Splicing machinery is impaired in rheumatoid arthritis, associated with disease activity and modulated by anti-TNF therapy

OBJECTIVES

To characterise splicing machinery (SM) alterations in leucocytes of patients with rheumatoid arthritis (RA), and to assess its influence on their clinical profile and therapeutic response.

METHODS

Leucocyte subtypes from 129 patients with RA and 29 healthy donors (HD) were purified, and 45 selected SM elements (SME) were evaluated by quantitative PCR-array based on microfluidic technology (Fluidigm). Modulation by anti-tumour necrosis factor (TNF) therapy and underlying regulatory mechanisms were assessed.

RESULTS

An altered expression of several SME was found in RA leucocytes. Eight elements (SNRNP70, SNRNP200, U2AF2, RNU4ATAC, RBM3, RBM17, KHDRBS1 and SRSF10) were equally altered in all leucocytes subtypes. Logistic regressions revealed that this signature might: discriminate RA and HD, and anti-citrullinated protein antibodies (ACPAs) positivity; classify high-disease activity (disease activity score-28 (DAS28) >5.1); recognise radiological involvement; and identify patients showing atheroma plaques. Furthermore, this signature was altered in RA synovial fluid and ankle joints of K/BxN-arthritic mice. An available RNA-seq data set enabled to validate data and identified distinctive splicing events and splicing variants among patients with RA expressing high and low SME levels. 3 and 6 months anti-TNF therapy reversed their expression in parallel to the reduction of the inflammatory profile. In vitro, ACPAs modulated SME, at least partially, by Fc Receptor (FcR)-dependent mechanisms. Key inflammatory cytokines further altered SME. Lastly, induced SNRNP70-overexpression and KHDRBS1-overexpression reversed inflammation in lymphocytes, NETosis in neutrophils and adhesion in RA monocytes and influenced activity of RA synovial fibroblasts.

CONCLUSIONS

Overall, we have characterised for the first time a signature comprising eight dysregulated SME in RA leucocytes from both peripheral blood and synovial fluid, linked to disease pathophysiology, modulated by ACPAs and reversed by anti-TNF therapy.

Integrative Clinical, Molecular, and Computational Analysis Identify Novel Biomarkers and Differential Profiles of Anti-TNF Response in Rheumatoid Arthritis

Background: This prospective multicenter study developed an integrative clinical and molecular longitudinal study in Rheumatoid Arthritis (RA) patients to explore changes in serologic parameters following anti-TNF therapy (TNF inhibitors, TNFi) and built on machine-learning algorithms aimed at the prediction of TNFi response, based on clinical and molecular profiles of RA patients.

Methods: A total of 104 RA patients from two independent cohorts undergoing TNFi and 29 healthy donors (HD) were enrolled for the discovery and validation of prediction biomarkers. Serum samples were obtained at baseline and 6 months after treatment, and therapeutic efficacy was evaluated. Serum inflammatory profile, oxidative stress markers and NETosis-derived bioproducts were quantified and miRNomes were recognized by next-generation sequencing. Then, clinical and molecular changes induced by TNFi were delineated. Clinical and molecular signatures predictors of clinical response were assessed with supervised machine learning methods, using regularized logistic regressions.

Results: Altered inflammatory, oxidative and NETosis-derived biomolecules were found in RA patients vs. HD, closely interconnected and associated with specific miRNA profiles. This altered molecular profile allowed the unsupervised division of three clusters of RA patients, showing distinctive clinical phenotypes, further linked to the TNFi effectiveness. Moreover, TNFi treatment reversed the molecular alterations in parallel to the clinical outcome. Machine-learning algorithms in the discovery cohort identified both, clinical and molecular signatures as potential predictors of response to TNFi treatment with high accuracy, which was further increased when both features were integrated in a mixed model (AUC: 0.91). These results were confirmed in the validation cohort.

Conclusions: Our overall data suggest that: 1. RA patients undergoing anti-TNF-therapy conform distinctive clusters based on altered molecular profiles, which are directly linked to their clinical status at baseline. 2. Clinical effectiveness of anti-TNF therapy was divergent among these molecular clusters and associated with a specific modulation of the inflammatory response, the reestablishment of the altered oxidative status, the reduction of NETosis, and the reversion of related altered miRNAs. 3. The integrative analysis of the clinical and molecular profiles using machine learning allows the identification of novel signatures as potential predictors of therapeutic response to TNFi therapy.

Neutrophils: Novel key players in Rheumatoid Arthritis. Current and future therapeutic targets

Rheumatoid Arthritis (RA) is a complex systemic autoimmune disease in which various cell types are involved. Among them, neutrophils have been recognized as important players in the onset and the progression of RA. The pathogenic role of neutrophils in RA lies in the alteration of several processes, including increased cell survival and migratory capacity, abnormal inflammatory activity, elevated oxidative stress and an exacerbated release of neutrophil extracellular traps. Through these mechanisms, neutrophils can activate other immune cells, thus perpetuating inflammation and leading to the destruction of the cartilage and bone of the affected joint. Given the considerable contribution of neutrophils to the pathophysiology of RA, several studies have attempted to clarify the effects of various therapeutic agents on this subtype of leukocyte. To date, recent studies have envisaged the role of new molecules on the pathogenic profile of neutrophils in RA, which could represent novel targets in future therapies. In this review, we aim to review the pathogenic role of neutrophils in RA, the effect of conventional treatments and biologic therapies, and the new, potential targets of neutrophil-derived molecules for the treatment of RA.

Tocilizumab improves the proatherothrombotic profile of rheumatoid arthritis patients modulating endothelial dysfunction, NETosis, and inflammation

Tocilizumab (TCZ) is an effective treatment for rheumatoid arthritis (RA). However, the changes that occurred after TCZ therapy on endothelial dysfunction, monocyte activity, NETosis, and oxidative stress, the principal effectors of atherosclerosis and cardiovascular disease, have not been analyzed yet. A total of 20 RA patients received 162 mg per week subcutaneous TCZ for 6 months. Endothelial function was measured through postocclusive hyperemia using Laser Doppler. Oxidative stress markers in monocytes and neutrophils were analyzed by flow cytometry. NETosis was measured through SYTOX staining of DNA fibers and the expression of myeloperoxidase and neutrophil elastase. Percentage of low-density granulocytes was analyzed through flow cytometry. Gene expression and phosphorylation of intracellular pathways was analyzed in monocytes. TCZ improved endothelial function and decreased oxidative stress in RA leukocytes. Percentage of low-density granulocytes and NETosis generation were reduced. The proinflammatory and prothrombotic status of RA monocytes was also reversed through a modulation of specific intracellular pathways. All these results were recapitulated after in vitro treatment with TCZ of monocytes and neutrophils purified from RA patients and cocultured with endothelial cells. TCZ might reduce the proatherothrombotic profile in RA patients through the restoration of the endothelial function, oxidative stress reduction, inhibition of monocytes' prothrombotic and inflammatory profile, and abridged NETosis generation.