Arthritis Research & Therapy最新文献

Background: The purpose of this study was to stratify patients with rheumatoid arthritis (RA) according to the trend of disease activity by trajectory-based clustering and to identify contributing factors for treatment response to biologic and targeted synthetic disease-modifying anti-rheumatic drugs (DMARDs) according to trajectory groups.

Methods: We analyzed the data from a nationwide RA cohort from the Korean College of Rheumatology Biologics and Targeted Therapy registry. Patients treated with second-line biologic and targeted synthetic DMARDs were included. Trajectory modeling for clustering was used to group the disease activity trend. The contributing factors using the machine learning model of SHAP (SHapley Additive exPlanations) values for each trajectory were investigated.

Results: The trends in the disease activity of 688 RA patients were clustered into 4 groups: rapid decrease and stable disease activity (group 1, n = 319), rapid decrease followed by an increase (group 2, n = 36), slow and continued decrease (group 3, n = 290), and no decrease in disease activity (group 4, n = 43). SHAP plots indicated that the most important features of group 2 compared to group 1 were the baseline erythrocyte sedimentation rate (ESR), prednisolone dose, and disease activity score with 28-joint assessment (DAS28) (SHAP value 0.308, 0.157, and 0.103, respectively). The most important features of group 3 compared to group 1 were the baseline ESR, DAS28, and estimated glomerular filtration rate (eGFR) (SHAP value 0.175, 0.164, 0.042, respectively). The most important features of group 4 compared to group 1 were the baseline DAS28, ESR, and blood urea nitrogen (BUN) (SHAP value 0.387, 0.153, 0.144, respectively).

Conclusions: The trajectory-based approach was useful for clustering the treatment response of biologic and targeted synthetic DMARDs in patients with RA. In addition, baseline DAS28, ESR, prednisolone dose, eGFR, and BUN were important contributing factors for 4-year trajectories.

Objective: To evaluate the impact of cardiovascular risk (CVR) on the diagnostic accuracy of the ultrasonographic (US) Halo Score in patients with suspected giant cell arteritis (GCA).

Methods: Retrospective observational study of patients referred to our US fast track clinic with suspected GCA for a 2-year period. The intima-media thickness (IMT) of cranial and extra-cranial arteries and the Halo Score was determined to assess the extent of vascular inflammation. The European Society of Cardiology Guidelines on CV Disease Prevention were used to define different categories of CVR and patients were classified according to the Systemic Coronary Risk Evaluation (SCORE). The gold standard for GCA diagnosis was clinical confirmation after a 6-month follow-up.

Results: Of the 157 patients included, 47 (29.9%) had GCA after a 6-month follow-up. Extra-cranial artery IMT was significantly higher in patients with high/very high CVR than in those with low/moderate CVR, but only among patients without GCA. Non-GCA patients with high/very high CVR had also a significantly higher Halo Score in contrast with low/moderate CVR [9.38 (5.93) vs 6.16 (5.22); p = 0.007]. The area under the ROC curve of the Halo Score to identify GCA was 0.835 (95% CI 0.756-0.914), slightly greater in patients with low/moderate CVR (0.965 [95% CI 0.911-1]) versus patients with high/very high CVR (0.798 [95% CI 0.702-0.895]). A statistically weak positive correlation was found between the Halo Score and the SCORE (r 0.245; c = 0.002).

Conclusions: Elevated CVR may influence the diagnostic accuracy of the US Halo Score for GCA. Thus, CVR should be taken into consideration in the US screening for GCA.

Objective: Rheumatoid arthritis (RA) is characterized by the presence of disease-specific autoreactive B cell responses, in particular those generating anti-citrullinated protein antibodies (ACPA). For many years, Epstein-Barr virus (EBV) has been implicated in disease pathogenesis, possibly by facilitating the development and persistence of autoreactive B cells. To test this hypothesis, the presence of EBV episomes in ACPA-expressing B cells was analyzed.

Methods: ACPA-expressing B cells derived from peripheral blood (PB) of seven EBV-seropositive RA patients, and synovial fluid (SF) of one additional EBV-seropositive RA patient, were isolated by flow cytometry. PB cells were expanded for 11-12 days, after which supernatant was harvested and analyzed for cyclic citrullinated-peptide (CCP)2 reactivity. SF cells were isolated directly in a lysis buffer. DNA was isolated and qPCR reactions were performed to determine the EBV status of the cells. EBV-immortalized B cell lymphoblastoid-cell lines (EBV blasts) served as standardized controls.

Results: Two hundred ninety-six PB and 60 SF ACPA-expressing B cells were isolated and divided over 16 and 3 pools containing 10-20 cells, respectively. Supernatants of all 16 cultured PB pools contained CCP2-Ig. DNA of all pools was used for qPCR analysis. While EBV-blast analysis showed sensitivity to detect EBV DNA in single B cells, no EBV DNA was detected in any of the ACPA-expressing B cell pools.

Conclusion: ACPA-expressing B cells are not enriched for EBV-DNA-containing clones. These results do not support the hypothesis that EBV infection of autoreactive B cells causes or maintains autoreactive B cell populations in RA. Instead, other mechanisms might explain the association between positive EBV serology and RA.

Background: Gout is a highly hereditary disease, but not all those carrying well-known risk variants have developing gout attack even in hyperuricemia status. We performed a genome-wide association study (GWAS) and polygenic risk score (PRS) analysis to illustrate the new genetic architectures of gout and asymptomatic hyperuricemia (AH).

Methods: GWAS was performed to identify variants associated with gout/AH compared with normouricemia. The participants were males, enrolled from the Taiwan Biobank and China Medical University, and divided into discovery (n=39,594) and replication (n=891) cohorts for GWAS. For PRS analysis, the discovery cohort was grouped as base (n=21,814) and target (n=17,780) cohorts, and the score was estimated by grouping the polymorphisms into protective or not for the phenotypes in the base cohort.

Results: The genes ABCG2 and SLC2A9 were found as the major genetic factors governing gouty and AH, and even in those carrying the rs2231142 (ABCG2) wild-genotype. Surprisingly, variants on chromosome 1, such as rs7546668 (DNAJC16), rs10927807 (AGMAT), rs9286836 (NUDT17), rs4971100 (TRIM46), rs4072037 (MUC1), and rs2974935 (MTX1), showed significant associations with gout in both discovery and replication cohorts (all p-values < 1e-8). Concerning the PRS, the rates of gout and AH increased with increased quartile PRS in those SNPs having risk effects on the phenotypes; on the contrary, gout/AH rates decreased with increased quartile PRS in those protective SNPs.

Conclusions: We found new variants on chromosome 1 significantly relating to gout, and PRS predicts the risk of developing gout/AH more robustly based on the SNPs' effect types on the trait.

Background: Adipose-derived mesenchymal stem cells (ASCs) have gained attention as a new treatment for systemic sclerosis (SSc). Low-molecular-weight heparin (LMWH) enhances cell function and stimulates the production of hepatocyte growth factor (HGF) in a variety of cells. This study investigated the effects of LMWH on the functions of mouse ASCs (mASCs), and the therapeutic effects of mASCs activated with LMWH (hep-mASCs) in mouse models of SSc.

Methods: The cellular functions of mASCs cultured with different concentrations of LMWH were determined. Mice were divided into four groups: bleomycin (BLM)-induced SSc (BLM-alone), BLM-induced SSc administered with mASCs (BLM-mASC), and BLM-induced SSc administered with mASCs activated with 10 or 100 μg/mL LMWH (BLM-hep-mASC); there were 9 mice per group (n = 9). Skin inflammation and fibrosis were evaluated using histological and biochemical examinations and gene expression levels.

Results: In vitro assays showed that migration ability and HGF production were significantly higher in hep-mASCs than in mASCs alone. The mRNA expression levels of cell migration factors were significantly upregulated in hep-mASCs compared to those in mASCs alone. The hep-mASCs accumulated in the skin tissues more than mASCs alone. The thickness of skin and hydroxyproline content in BLM-hep-mASC groups were significantly decreased, and the skin mRNA expression levels of interleukin-2, α-smooth muscle actin, transforming growth factor β1, collagen type 1 alpha 1, and tissue inhibitor of metalloproteinase 2 were significantly downregulated compared to those in the BLM-alone group.

Conclusions: hep-mASCs showed higher anti-inflammatory and anti-fibrotic effects than mASCs alone and may be a promising candidate for SSc treatment.

Background: X-ray images are commonly used to assess the bone destruction of rheumatoid arthritis. The purpose of this study is to propose an automatic-bone-destruction-evaluation system fully utilizing deep neural networks (DNN). This system detects all target joints of the modified Sharp/van der Heijde score (SHS) from a hand X-ray image. It then classifies every target joint as intact (SHS = 0) or non-intact (SHS ≥ 1).

Methods: We used 226 hand X-ray images of 40 rheumatoid arthritis patients. As for detection, we used a DNN model called DeepLabCut. As for classification, we built four classification models that classify the detected joint as intact or non-intact. The first model classifies each joint independently, whereas the second model does it while comparing the same contralateral joint. The third model compares the same joint group (e.g., the proximal interphalangeal joints) of one hand and the fourth model compares the same joint group of both hands. We evaluated DeepLabCut's detection performance and classification models' performances. The classification models' performances were compared to three orthopedic surgeons.

Results: Detection rates for all the target joints were 98.0% and 97.3% for erosion and joint space narrowing (JSN). Among the four classification models, the model that compares the same contralateral joint showed the best F-measure (0.70, 0.81) and area under the curve of the precision-recall curve (PR-AUC) (0.73, 0.85) regarding erosion and JSN. As for erosion, the F-measure and PR-AUC of this model were better than the best of the orthopedic surgeons.

Conclusions: The proposed system was useful. All the target joints were detected with high accuracy. The classification model that compared the same contralateral joint showed better performance than the orthopedic surgeons regarding erosion.

Background: The IL-23/IL-17 axis is involved in inflammatory diseases including arthritis and psoriasis. However, the response to IL-23 or IL-17 inhibitors is different depending on the disease. The aim was to compare the effects of interactions between immune and stromal cells on the IL-23 axis to understand these differences.

Methods: Peripheral blood mononuclear cells were co-cultured with RA synoviocytes or Pso skin fibroblasts, with or without phytohemagglutinin, IL-23, or anti-IL-23 antibody. Production of IL-6, IL-1β, IL-23, IL-17, IL-12, and IFNγ was measured by ELISA. IL-23 and cytokine receptor gene expression (IL-17RA, IL-17RC, IL-12Rβ1, IL-12Rβ2, and IL-23R) was analyzed by RT-qPCR. IL-12Rβ1 and IL-23R subunits were analyzed by flow cytometry.

Results: The production of IL-6, IL-1β, IL-17, IL-12, and IFNγ with synoviocytes or skin fibroblasts was rather similar, and cell interactions with immune cells increased their production, specifically that of IL-17. A major difference was observed for IL-23. Interactions with synoviocytes but not with skin fibroblasts decreased IL-23 secretion while mRNA level was increased, mainly with synoviocytes, reflecting a major consumption difference. IL-23 addition had only one effect, the increase of IL-17 secretion. Cell activation induced similar effects on cytokine receptor gene expression in co-cultures with synoviocytes or skin fibroblasts. The key difference was the cell interaction effects depending on the stromal cell origin. Interactions with synoviocytes increased the expression of both IL-23 receptor subunits at mRNA levels and IL-23R at the surface expression level while interactions with skin fibroblasts decreased their expression at the mRNA level and had no effect at the surface expression level.

Conclusion: Interactions between immune and stromal cells are crucial in cytokine production and their receptor expression. The origin of stromal cells had a major influence on the production of IL-23 and its receptor expression. Such differences may explain part of the heterogeneity in treatment response.