Expression of Galectin-9 and correlation with disease activity and vascular endothelial growth factor in rheumatoid arthritis.

OBJECTIVES: Despite the important role of Galectin-9 (Gal-9) in inflammation and angiogenesis, only a few studies on Galectin-9 expression have been performed in rheumatoid arthritis (RA) patients. The present study aimed to identify the concentration of Galectin-9 in plasma, its expression in peripheral blood T cell subsets in RA patients, and the association between Galectin-9 and vascular endothelial growth factor (VEGF) in RA. METHODS: One hundred and five active RA patients and 52 age- and sex-matched healthy controls (HCs) were enrolled in the study. Gal-9, vascular endothelial growth factor (VEGF), and tumour necrosis factor (TNF)-α level in plasma were determined by ELISA. The intracellular positive expression rates and medium fluorescence intensity (MFI) of Gal-9 and VEGF in T cell subsets, were examined by flow cytometry. RESULTS: Plasma Gal-9, TNF-α, and VEGF levels were higher in the RA group than in the HCs group. The plasma Gal-9 level positively correlated with Gal-9 expression in the total lymphocyte and CD3+ T cell, CRP, SDAI, and CDAI of RA patients. The Gal-9 expressions in the cytoplasm of CD4+ T, CD8+ T, Treg, and DNT cells positively correlated with plasma TNF-α levels in RA patients. The Gal-9 expressions in CD4+ T and CD8+ T subsets also positively correlated with plasma VEGF levels. The plasma VEGF levels and VEGF expressions in CD4+ T, CD8+ T, and Treg subsets positively correlated with SDAI and CRP in RA patients. CONCLUSIONS: Gal-9 can be a potential biomarker for RA disease activity. Gal-9 is probably associated with angiogenesis processing in RA.

High Interleukin-37 (IL-37) Expression and Increased Mucin-Domain Containing-3 (TIM-3) on Peripheral T Cells in Patients with Rheumatoid Arthritis.

BACKGROUND Anti-inflammatory mediators such as mucin-domain containing-3 (TIM-3) and IL-37 play an important role in the regulation of Th1-mediated immunity. This study was designed to investigate the proportions of various T cell subsets and monocytes in the peripheral blood of rheumatoid arthritis (RA) patients, as well as the level of TIM-3 on these cells and serum cytokine levels. MATERIAL AND METHODS We enrolled 59 RA patients and 46 age- and sex-matched healthy controls in this study. The proportion of T cells and TIM-3 expression on these T cells were determined by flow cytometry. Cytokine levels in serum were determined by ELISA. RESULTS Compared with the healthy controls, the proportions of CD3+CD4+ T cells and CD3+CD4+CD25+CD127low T cells in the peripheral blood were significantly higher in RA patients. However, RA patients had significantly lower proportions of CD3+CD8+ T cells and CD3+CD4-CD8- T cells. TIM-3 was highly expressed on CD3+CD4+, CD3+CD8+, CD3+CD4+CD25+CD127low, and CD3+CD4-CD8- T cells, as well as CD14+ monocytes, in RA patients. Nevertheless, no correlation between TIM-3 level and an RA disease activity score of 28 was found. The elevated serum levels of IL-6 and IL-37 were positively correlated with tumor necrosis factor-α (TNF-α). CONCLUSIONS Both pro-inflammatory cytokines (TNF-α and IL-6) and anti-inflammatory mediators (TIM-3 and IL-37) simultaneously contribute to the pathogenesis of RA. TIM-3 and IL-37 may be used as potential biomarkers of active RA.

Establishment and verification of a nomogram and a preliminary study on predicting the clinical response of conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) in rheumatoid arthritis patients.

Background: Rheumatoid arthritis (RA) is an autoinflammatory disease, its core treatment principle is to achieve remission as soon as possible. There is no good prediction model that can accurately predict the remission rate of patients to choose a good treatment scheme. Here, we aimed to verify the prognostic value of some inflammatory indicators in RA and establish a prediction model to predict the remission rate after treatment. Methods: A total of 223 patients were enrolled at Qilu Hospital from June 2014 to June 2020. Baseline clinical data were collected and plasma was obtained to detect the inflammatory indicators. All patients were treated with conventional synthetic disease-modifying antirheumatic drugs (csDMARDs). All patients were followed up and were recorded the time to reach the disease activity score-28 with erythrocyte sedimentation rate (DAS28-ESR) of <2.6. A total of 156 patients were randomly assigned to the development cohort, and 67 patients were assigned to the validation cohort. Inflammatory indicators in plasma were detected by enzyme-linked immunosorbent assay (ELISA). The predictive factors were screeded by using least absolute shrinkage and selection operator (LASSO) and Cox regression. The model was created and verified by using the standard method. A total of 6 independent risk factors were analyzed to construct a nomogram to predict the remission rate in 3, 6 and 12 months. Results: The remission rates after treatment in 3, 6 and 12 months were 38.76%, 58.91%, and 81.40%, respectively. Patient age, C-reactive protein (CRP), interleukin (IL)-6, galectin-9 (Gal-9), health assessment questionnaire (HAQ), and DAS28-ESR were included in the prognostic model to predict the remission rate. The resulting model had good discrimination ability in both the development cohort (C-index, 0.729) and the validation cohort (C-index, 0.710). Time-dependent receiver operating characteristic (ROC) curve, calibration analysis, and decision curve analysis (DCA) showed that the model has significant discriminant power and clinical practicability in predicting the remission rate. Conclusions: We established a new predictive model and validated it. The model can predict the remission rate in 3, 6 and 12 months after receiving csDMARDs treatment. By using this model, we can facilitate the identification of high-risk patients early and intervene with them as soon as possible.

Nanomedicine-based combination of dexamethasone palmitate and MCL-1 siRNA for synergistic therapeutic efficacy against rheumatoid arthritis.

The main aim of this research was to design a MCL-1 siRNA and dexamethasone (DEX)-loaded folate modified poly(lactide-co-glycolide) (PLGA)-based polymeric micelles with an eventual goal to improve the therapeutic outcome in the rheumatoid arthritis (RA). Polymeric micelles encapsulating the MCL-1 siRNA and DEX was successfully developed and observed to be stable. Physicochemical characteristics such as particle size and particle morphology were ideal for the systemic administration. Folate-conjugated DEX/siRNA-loaded polymeric micelles (DS-FPM) significantly lowered the MCL-1 mRNA expression compared to either DEX/siRNA-loaded polymeric micelles (DS-PM) or free siRNA in Raw264.7 cells and macrophage cells suggesting the importance of targeted nanocarriers. Most importantly, DS-FPM exhibited a greatest decrease in the hind paw volume with lowest clinical score compared to any other treated group indicating a superior anti-inflammatory activity. DS-FPM showed significantly lower levels of the TNF-α and IL-1ß compared to AIA model and free groups. The folate receptor (FR)-targeting property of DS-FPM has been demonstrated to be a promising delivery platform for the effective delivery of combination therapeutics (siRNA and DEX) toward the treatment of rheumatoid arthritis.

Galectin-9 expression correlates with therapeutic effect in rheumatoid arthritis.

Galectin-9 (Gal-9) is a multifunctional immunomodulatory factor highly expressed in RA. This study aimed to investigate the expression of Gal-9 and its correlation with disease activity and therapeutic response in RA patients. Active RA patients were enrolled and treated with tacrolimus (TAC) alone or in combination therapy for 12 weeks in a prospective cohort study. Clinical and immunological parameters were recorded at baseline and week 12. We measured Gal-9 expression in different T cell subsets and in plasma. The disease activity of RA patients decreased after treatment. At baseline, the Gal-9 expression percentage was higher in the group with severe disease than in mild or moderate groups. After treatment, the Gal-9 expression in CD3+, CD4+, CD8+ and CD4-CD8- cell subsets decreased, as well as Gal-9 mean fluorescence intensity in CD3+, CD4+ and CD8+ T cells. Similarly, plasma Gal-9 levels were lower at week 12 than at baseline. Good responders showed significantly lower Gal-9 expression on CD3+ and CD4+ T cell subsets and lower plasma Gal-9 levels than poor responders. Gal-9 expression positively correlates with disease activity in RA patients. Gal-9 can be regarded as a new biomarker for evaluating RA activity and therapeutic effect, including TAC.