Ankylosing spondylitis (AS) remains difficult to diagnose before irreversible damage to sacroiliac joint is noticeable. Circulating microRNAs have demonstrated to serve as diagnostic tools for several human diseases. Here, we analysed plasma microRNAs to identify potential AS biomarkers. Higher expression levels of microRNA (miR)-146a-5p, miR-125a-5p, miR-151a-3p and miR-22-3p, and lower expression of miR-150-5p, and miR-451a were found in AS versus healthy donors. Interestingly, higher miR-146a-5p, miR-125a-5p, miR-151a-3p, miR-22-3p and miR-451a expression was also observed in AS than psoriatic arthritis patients. The areas under the curve, generated to assess the accuracy of microRNAs as diagnostic biomarkers for AS, ranged from 0.614 to 0.781; the six-microRNA signature reached 0.957. Bioinformatics analysis revealed that microRNAs targeted inflammatory and bone remodeling genes, underlying their potential role in this pathology. Indeed, additional studies revealed an association between these six microRNAs and potential target proteins related to AS pathophysiology. Furthermore, miR-146a-5p, miR-125a-5p and miR-22-3p expression was increased in active versus non-active patients. Moreover, miR-125a-5p, miR-151a-3p, miR-150-5p and miR-451a expression was related to the presence of syndesmophytes in AS patients. Overall, this study identified a six-plasma microRNA signature that could be attractive candidates as non-invasive biomarkers for the AS diagnosis, and may help to elucidate the disease pathogenesis.
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.
Background: Radiographic axial spondyloarthritis (r-axSpA) is a chronic inflammatory form of arthritis in which tumor necrosis factor (TNF)-α, a potent inducer of inflammatory response and a key regulator of innate immunity and of Th1 immune responses, plays a central role. NETosis is a mechanism of innate immune defense that is involved in diverse rheumatology diseases. Nevertheless, spontaneous NETosis generation in r-axSpA, its association to disease pathogenesis, and the NETosis involvement on anti-TNF-α therapy's effects has never been explored.Methods: Thirty r-axSpA patients and 32 healthy donors (HDs) were evaluated. Neutrophil extracellular trap (NET) formation, mediators of signal-transduction cascade required for NETosis induction and cell-free NETosis-derived products were quantified. An additional cohort of 15 r-axSpA patients treated with infliximab (IFX) for six months were further analyzed. In vitro studies were designed to assess the effects of IFX in NETosis generation and the inflammatory profile triggered. (Continued on next page)Results: Compared to HDs, neutrophils from r-axSpA patients displayed augmented spontaneous NET formation, elevated expression of NET-associated signaling components, nuclear peptidylarginine deiminase 4 translocation and increased citrullinated histone H3. Furthermore, patients exhibited altered circulating levels of cell-free NETosisderived products (DNA, nucleosomes and elastase). Additional studies revealed that cell-free NETosis-derived products could be suitable biomarkers for distinguish r-axSpA patients from HDs. Correlation studies showed association between cell-free NETosis-derived products and clinical inflammatory parameters. Besides, nucleosomes displayed potential as a biomarker for discriminate patients according to disease activity. IFX therapy promoted a reduction in both NETosis generation and disease activity in r-axSpA patients. Mechanistic in vitro studies further unveiled the relevance of IFX in reducing NET release and normalizing the augmented inflammatory activities promoted by NETs in mononuclear cells.Conclusions: This study reveals that NETosis is enhanced in r-axSpA patients and identifies the NETosis-derived products as potential disease activity biomarkers. In addition, the data suggests the potential role of NET generation analysis for assessment of therapeutic effectiveness in r-axSpA.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.