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.

Impaired microRNA processing in neutrophils from rheumatoid arthritis patients confers their pathogenic profile. Modulation by biological therapies.

The aim of this study was to investigate the microRNA (miRNA) expression pattern in neutrophils from rheumatoid arthritis (RA) patients and its contribution to their pathogenic profile and to analyze the effect of specific autoantibodies or inflammatory components in the regulation of miRNA in RA neutrophils and its modulation by biological therapies. Neutrophils were isolated from paired peripheral blood (PB) and synovial fluid samples of 40 patients with RA and from PB of 40 healthy donors. A miRNA array was performed using nCounter technology. Neutrophils from healthy donors were treated in vitrowith antibodies to citrullinated protein antigens isolated from RA patients and tumor necrosis factor-a (TNF-a) or interleukin-6. A number of cytokines and chemokines were analyzed. In vitro treatments of RA-neutrophils with tocilizumab or infliximab were carried out. Transfections with pre-miRNA and DICER downregulation experiments were further performed. RA-neutrophils showed a global downregulation of miRNA and genes involved in their biogenesis, alongside with an upregulation of various potential mRNA targets related to migration and inflammation. Decreased levels of miRNA and DICER correlated with autoimmunity, inflammation and disease activity. Citrullinated protein antigens and TNF-a decreased the expression of numerous miRNA and their biogenesis-related genes, increasing their potential mRNA targets. Infliximab reversed those effects. Transfections with pre-miRNA-223, -126 and -148a specifically modulated genes regulating inflammation, survival and migration whereas DICER depletion influenced the inflammatory profile of neutrophils. Taken together RA-neutrophils exhibited a global low abundance of miRNA induced by autoantibodies and inflammatory markers, which potentially contributed to their pathogenic activation. miRNA biogenesis was significantly impaired in RAneutrophils and further associated with a greater downregulation of miRNA mainly related to migration and inflammation in synovial fluid neutrophils. Finally, anti-TNF-a and anti-interleukin-6 receptor treatments can modulate miRNA levels in the neutrophils, minimizing their inflammatory profile.

Complement component 3 as biomarker of disease activity and cardiometabolic risk factor in rheumatoid arthritis and spondyloarthritis.

OBJECTIVE: To analyze the relationship between complement component 3 (C3) and the prevalence of cardiometabolic risk factors and disease activity in the rheumatic diseases having the highest rates of cardiovascular morbidity and mortality: rheumatoid arthritis (RA), psoriatic arthritis (PsA) and axial spondyloarthritis (axSpA). METHODS: This is a cross-sectional study including 200 RA, 80 PsA, 150 axSpA patients and 100 healthy donors. The prevalence of cardiometabolic risk factors [obesity, insulin resistance, type 2 diabetes mellitus, hyperlipidemia, apolipoprotein B/apolipoprotein A (apoB/apoA) and atherogenic risks and hypertension] was analyzed. Serum complement C3 levels, inflammatory markers and disease activity were evaluated. Cluster analysis was performed to identify different phenotypes. Receiver operating characteristic (ROC) curve analysis to assess the accuracy of complement C3 as biomarker of insulin resistance and disease activity was carried out. RESULTS: Levels of complement C3, significantly elevated in RA, axSpA and PsA patients, were associated with the prevalence of cardiometabolic risk factors. Hard clustering analysis identified two distinctive phenotypes of patients depending on the complement C3 levels and insulin sensitivity state. Patients from cluster 1, characterized by high levels of complement C3 displayed increased prevalence of cardiometabolic risk factors and high disease activity. ROC curve analysis showed that non-obesity related complement C3 levels allowed to identify insulin resistant patients. CONCLUSIONS: Complement C3 is associated with the concomitant increased prevalence of cardiometabolic risk factors in rheumatoid arthritis and spondyloarthritis. Thus, complement C3 should be considered a useful marker of insulin resistance and disease activity in these rheumatic disorders.