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.

Gene profiling reveals specific molecular pathways in the pathogenesis of atherosclerosis and cardiovascular disease in antiphospholipid syndrome, systemic lupus erythematosus and antiphospholipid syndrome with lupus.

OBJECTIVE: To identify shared and differential molecular pathways involved in the pathogenesis of atherosclerosis (AT) and cardiovascular disease (CVD) in systemic lupus erythematosus (SLE), primary antiphospholipid syndrome (APS) and APS associated with SLE (APS plus SLE). METHODS: 129 patients (42 APS, 31 APS plus SLE and 56 SLE) and 61 healthy donors were included. Microarray expression profiling was performed in monocytes. RT-PCR of selected genes and western blot were used to validate microarray data. Clinical and inflammatory parameters were also analysed. RESULTS: Compared with controls, 555, 1224 and 518 genes were differentially expressed in monocytes from SLE, APS plus SLE and APS patients, respectively. Approximately 25-30% of differentially expressed genes were related to AT and CVD. Each disease displayed a specific AT/CVD/Inflammation-related gene signature. Compared with SLE, APS showed alterations in mitochondria biogenesis and function and oxidative stress. Besides the interferon signature, found in APS plus SLE and SLE patients, various genes mediating atherosclerotic/inflammatory signalling were also differentially expressed in APS plus SLE. IgG-anticardiolipin (aCL) titres independently predicted both atherosclerotic and thrombosis in APS plus SLE. Moreover, a significant correlation of IgG-aCL titres with mRNA levels of certain inflammatory molecules in monocytes was further noticed. In vitro treatment of monocytes with IgG-aCL promoted an increase in the expression of the genes most significantly changed in APS plus SLE versus healthy donors. CONCLUSIONS: Gene expression profiling allows the segregation of APS, APS plus SLE and SLE, with specific signatures explaining the pro-atherosclerotic and pro-thrombotic alterations in these highly related autoimmune diseases.

Potential use of statins in the treatment of antiphospholipid syndrome.

Antiphospholipid syndrome (APS) is a disorder characterized by the association of arterial or venous thrombosis and/or pregnancy morbidity with the presence of antiphospholipid antibodies (anticardiolipin antibodies, lupus anticoagulant antibodies, and/or anti-ß2-glycoprotein I antibodies). Several studies have contributed to uncovering the basis of antiphospholipid antibody pathogenicity, including the targeted cellular components, affected systems, involved receptors, intracellular pathways used, and the effector molecules that are altered in the process. Therapy for thrombosis traditionally has been based on long-term oral anticoagulation; however, bleeding complications and recurrence despite high-intensity anticoagulation can occur. Based on all the data obtained, new potential therapeutic agents have been proposed. Statins have a variety of direct effects on gene expression and the function of cells of both the innate and adaptive immune systems, many of which are related to blockade of GTPase isoprenylation. In APS, statins have multiple profound effects on monocyte, lymphocyte, and endothelial cell activities, all of which may contribute to thrombosis prevention in APS patients. Nevertheless, larger randomized trials are needed to validate the role of statins in the treatment of this autoimmune disease.