Arthritis Research & Therapy最新文献

Background: Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by increased levels of inflammation that primarily manifests in the joints. Macrophages act as key drivers for the progression of RA, contributing to the perpetuation of chronic inflammation and dysregulation of pro-inflammatory cytokines such as interleukin 1 (IL-1). The goal of this study was to develop a macrophage-based cell therapy for biologic drug delivery in an autoregulated manner.

Methods: For proof-of-concept, we developed "smart" macrophages to mitigate the effects of IL-1 by delivering its inhibitor, IL-1 receptor antagonist (IL-1Ra). Bone marrow-derived macrophages were lentivirally transduced with a synthetic gene circuit that uses an NF-κB inducible promoter upstream of either the Il1rn or firefly luciferase transgenes. Two types of joint like cells were utilized to examine therapeutic protection in vitro, miPSCs derived cartilage and isolated primary mouse synovial fibroblasts while the K/BxN mouse model of RA was utilized to examine in vivo therapeutic protection.

Results: These engineered macrophages were able to repeatably produce therapeutic levels of IL-1Ra that could successfully mitigate inflammatory activation in co-culture with both tissue-engineered cartilage constructs and synovial fibroblasts. Following injection in vivo, macrophages homed to sites of inflammation and mitigated disease severity in the K/BxN mouse model of RA.

Conclusion: These findings demonstrate the successful development of engineered macrophages that possess the ability for controlled, autoregulated production of IL-1 based on inflammatory signaling such as via the NF-κB pathway to mitigate the effects of this cytokine for applications in RA or other inflammatory diseases. This system provides proof of concept for applications in other immune cell types as self-regulating delivery systems for therapeutic applications in a range of diseases.

Objectives: Skeletal muscle dysfunction is the primary cause of functional limitations in osteoarthritis, associated biomarkers have the potential as targets for early disease identification, diagnosis, and prevention of osteoarthritis disability. This review aimed to identify associations between biomarkers and lower limb skeletal muscle function in individuals with osteoarthritis.

Methods: A systematic literature review and meta-analysis conducted in PubMed, MEDLINE, CINAHL, EMBASE, Scopus, SPORTDiscus and Web of Science databases from inception to 8^th August 2023. Two independent reviewers performed the title, abstract, full-text screening, data extraction and methodological quality assessment. A meta-analysis was undertaken based on the available data.

Results: Twenty-four studies with 4101 participants with osteoarthritis were included (females: 78%; age range; 49 to 71 years). One study reported muscle-specific biomarkers (n = 3), whilst six studies reported osteoarthritis-specific markers (n = 5). Overall, 93 biomarkers were reported, predominately characterised as inflammatory (n = 35), metabolic (n = 15), and hormones (n = 10). Muscle strength and vitamin D reported a significant association (Hedge's g: 0.58 (Standard Error (SE): 0.27; P = 0.03), k = 3 studies). Walking speed and high-sensitivity C-reactive protein reported no significant associations (Hedge's g: -0.02 (SE: 0.05; P = 0.73), k = 3 studies).

Conclusion: Associations between biomarkers and lower limb skeletal muscle function in individuals with osteoarthritis was limited, the few studies exploring lower limb muscle measures were mainly secondary outcomes. Furthermore, biomarkers were largely related to overall health, with a lack of muscle specific biomarkers. As such, the mechanistic pathways through which these associations occur are less evident, and difficult to draw clear conclusions on these relationships.

Trial registration: Registered on PROSPERO (CRD42022359405).

Objectives: Patients with rheumatoid arthritis (RA) commonly experience a high prevalence of multiple metabolic diseases (MD), leading to higher morbidity and premature mortality. Here, we aimed to investigate the pathogenesis of MD in RA patients (RA_MD) through an integrated multi-omics approach.

Methods: Fecal and blood samples were collected from a total of 181 subjects in this study for multi-omics analyses, including 16S rRNA and internally transcribed spacer (ITS) gene sequencing, metabolomics, transcriptomics, proteomics and phosphoproteomics. Spearman's correlation and protein-protein interaction networks were used to assess the multi-omics data correlations. The Least Absolute Shrinkage and Selection Operator (LASSO) machine learning algorithm were used to identify disease-specific biomarkers for RA_MD diagnosis.

Results: Our results found that RA_MD was associated with differential abundance of gut microbiota such as Turicibacter and Neocosmospora, metabolites including decreased unsaturated fatty acid, genes related to linoleic acid metabolism and arachidonic acid metabolism, as well as downregulation of proteins and phosphoproteins involved in cholesterol metabolism. Furthermore, a multi-omics classifier differentiated RA_MD from RA with high accuracy (AUC: 0.958). Compared to gouty arthritis and systemic lupus erythematosus, dysregulation of lipid metabolism showed disease-specificity in RA_MD.

Conclusions: The integration of multi-omics data demonstrates that lipid metabolic pathways play a crucial role in RA_MD, providing the basis and direction for the prevention and early diagnosis of MD, as well as new insights to complement clinical treatment options.

Objective: Rheumatoid arthritis (RA) is a clinically heterogeneous and complex autoimmune disease, making the prediction of therapeutic responses a significant challenge. This study aims to assess the role of clinical and synovial biomarkers in predicting poor response to adalimumab treatment in RA patients.

Methods: This single-center prospective study included 56 RA patients who had an inadequate response to methotrexate (MTX). At baseline, comprehensive assessments including complete blood count, liver and kidney function tests, blood glucose levels, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), rheumatoid factor (RF), anti-citrullinated protein antibody (ACPA), as well as counts of swollen and tender joints, Health Assessment Questionnaire (HAQ) score, pain visual analogue scale (VAS) scores, and DAS28-CRP scores were conducted. Synovial biopsies were performed, followed by an efficacy evaluation at 12 weeks of adalimumab treatment. Patients not meeting the ACR20 criteria were classified into the non-responder group, with the remainder categorized as the responder group.

Results: Out of the participants, 24 (42.9%) failed to achieve ACR20 with adalimumab treatment. Non-responders exhibited higher infiltration of plasma cells in the synovium. Multivariate logistic regression analysis identified the presence of plasma cells as an independent risk factor for inadequate response to adalimumab.

Conclusion: Inadequate responses to adalimumab in RA patients were associated with increased plasma cell infiltrations in the synovium. These findings suggest a promising target for tailored therapies in rheumatoid arthritis.