Gout is characterized by episodes of intense joint inflammation in response to intra-articular monosodium urate monohydrate (MSU) crystals. miR-155 is crucial for the proinflammatory activation of human myeloid cells and antigen-driven inflammatory arthritis. The functional role of miR-155 in acute gouty arthritis has not been defined. Therefore, the aim of this study was to examine the role of miR-155 in pathogenesis of acute gouty arthritis.

Health-related quality of life (HRQOL) in patients with fibromyalgia (FM) is lower than in patients with other chronic diseases and the general population. Although various factors affect HRQOL, no study has examined a structural equation model of HRQOL as an outcome variable in FM patients. The present study assessed relationships among physical function, social factors, psychological factors, and HRQOL, and the effects of these variables on HRQOL in a hypothesized model using structural equation modeling (SEM). HRQOL was measured using SF-36, and the Fibromyalgia Impact Questionnaire (FIQ) was used to assess physical dysfunction. Social and psychological statuses were assessed using the Beck Depression Inventory (BDI), the State-Trait Anxiety Inventory (STAI), the Arthritis Self-Efficacy Scale (ASES), and the Social Support Scale. SEM analysis was used to test the structural relationships of the model using the AMOS software. Of the 336 patients, 301 (89.6%) were women with an average age of 47.9±10.9 years. The SEM results supported the hypothesized structural model (χ² = 2.336, df = 3, p = 0.506). The final model showed that Physical Component Summary (PCS) was directly related to self-efficacy and inversely related to FIQ, and that Mental Component Summary (MCS) was inversely related to FIQ, BDI, and STAI. In our model of FM patients, HRQOL was affected by physical, social, and psychological variables. In these patients, higher levels of physical function and self-efficacy can improve the PCS of HRQOL, while physical function, depression, and anxiety negatively affect the MCS of HRQOL.

Introduction: The purpose of this study was to analyze the cellular expressions of pro-resorptive cytokines in gouty tophus tissues, to determine the capacity of monosodium urate monohydrate (MSU) crystals to induce these cytokines, and to understand the mechanisms of bone destruction in chronic gout. Methods: Fourteen fixed, paraffin-embedded, uninfected tophus samples were analyzed immunohistochemically. Peripheral blood mononuclear cells (PBMCs) were cultured in vitro with MSU crystals, and gene expression was assessed by reverse transcription-polymerase chain reaction. In vitro osteoclastogenesis was performed using PBMCs and synovial fluid mononuclear cells (SFMCs). Results: CD4+ T cells, CD8+ T cells, CD20+ B cells and mast cells infiltrated tophus tissues. Tartrate-resistant acid phosphatase (TRAP)+ osteoclasts were present around tophi and in osteolytic lesions. Interleukin (IL)-1, IL-6 and tumor necrosis factor (TNF)-alpha were produced from infiltrated mononuclear cells, whereas receptor activator of nuclear factor κB ligand (RANKL) was strongly expressed in T cells. However, osteoprotegerin (OPG) was not or was weakly expressed in tophus tissues. MSU crystals induced the expressions of IL-1, IL-6, TNF-alpha and RANKL in PBMCs, but inhibited OPG expression. In addition, the pro-resorptive cytokines were highly expressed in SFMCs of gouty arthritis patients. Furthermore, in vitro osteoclastogenesis was enhanced in SFMC cultures, but inhibited in T cell-depleted SFMC cultures. Conclusions: Our study demonstrates that RANKL-expressing T cells and TRAP+ osteoclasts are present within gouty tophus tissues, and that infiltrating cells express pro-resorptive cytokines. Furthermore, our data show that MSU crystals have the potential to induce pro-resorptive cytokines, and T cells are involved in osteoclastogenesis in chronic gout.

Human leukocyte antigen (HLA) is a key genetic factor conferring risk of systemic lupus erythematosus (SLE), but precise independent localization of HLA effects is extremely challenging. As a result, the contribution of specific HLA alleles and amino-acid residues to the overall risk of SLE and to risk of specific autoantibodies are far from completely understood. Here, we dissected (a) overall SLE association signals across HLA, (b) HLA-peptide interaction, and (c) residue-autoantibody association. Classical alleles, SNPs, and amino-acid residues of eight HLA genes were imputed across 4,915 SLE cases and 13,513 controls from Eastern Asia. We performed association followed by conditional analysis across HLA, assessing both overall SLE risk and risk of autoantibody production. DR15 alleles HLA-DRB1*15:01 (P = 1.4x10^-27, odds ratio (OR) = 1.57) and HLA-DQB1*06:02 (P = 7.4x10^-23, OR = 1.55) formed the most significant haplotype (OR = 2.33). Conditioned protein-residue signals were stronger than allele signals and mapped predominantly to HLA-DRB1 residue 13 (P = 2.2x10^-75) and its proxy position 11 (P = 1.1x10^-67), followed by HLA-DRB1-37 (P = 4.5x10^-24). After conditioning on HLA-DRB1, novel associations at HLA-A-70 (P = 1.4x10^-8), HLA-DPB1-35 (P = 9.0x10^-16), HLA-DQB1-37 (P = 2.7x10^-14), and HLA-B-9 (P = 6.5x10^-15) emerged. Together, these seven residues increased the proportion of explained heritability due to HLA to 2.6%. Risk residues for both overall disease and hallmark autoantibodies (i.e., nRNP: DRB1-11, P = 2.0x10^-14; DRB1-13, P = 2.9x10^-13; DRB1-30, P = 3.9x10^-14) localized to the peptide-binding groove of HLA-DRB1. Enrichment for specific amino-acid characteristics in the peptide-binding groove correlated with overall SLE risk and with autoantibody presence. Risk residues were in primarily negatively charged side-chains, in contrast with rheumatoid arthritis. We identified novel SLE signals in HLA Class I loci (HLA-A, HLA-B), and localized primary Class II signals to five residues in HLA-DRB1, HLA-DPB1, and HLA-DQB1. These findings provide insights about the mechanisms by which the risk residues interact with each other to produce autoantibodies and are involved in SLE pathophysiology. The Human leukocyte antigen (HLA) region is a key genetic factor conferring risk of systemic lupus erythematosus (SLE). In spite of multiple SLE association signals identified in the HLA region, only amino-acid residues within HLA-DRB1 have been specifically described previously. In this study, we performed an imputation-based analysis on individuals with East Asian ancestry, and characterized SLE risk within the HLA region for all involved independent genes (HLA-DRB1, HLA-DPB1, HLA-DQB1, HLA-A, and HLA-B). Furthermore, we identified a characteristic SLE risk residue signature as well as a pattern of specific nRNP and Ro/La autoantibody residues located in the peptide-binding grooves, suggesting their key involvement in autoantibody production.

Objective: Allopurinol‐induced severe cutaneous adverse reactions (SCARs) are relatively rare but cause high rates of morbidity and mortality. Studies have shown that the HLA–B5801 allele and renal impairment are strongly associated with SCARs. Recent American College of Rheumatology guidelines recommend that, prior to treatment with allopurinol, the HLA–B5801 genotype of gout patients at high risk for SCARs, including Korean patients with chronic renal insufficiency, should be determined. However, whether such genotyping is cost‐effective is unknown. This study evaluated the cost‐effectiveness of HLA–B5801 genotyping for the treatment of gout in patients with chronic renal insufficiency in Korea.Methods: A decision analytical model over a time period of 12 months was employed to compare the cost and outcomes of treatment informed by HLA–B5801 genotyping with that of a conventional treatment strategy using a hypothetical cohort of gout patients with chronic renal insufficiency. Direct medical costs were obtained from real patients with SCARs from 2 tertiary hospitals. Outcomes were measured as a total expected cost and an incremental cost‐effectiveness ratio.Results: In the base model, the total expected cost and probability of continuation of gout treatment without SCARs for the conventional and HLA–B5801 screening strategies were $1,193 and 97.8% and $1,055 and 100%, respectively. The results were robust according to sensitivity analyses.Conclusion: Our model suggests that gout treatment informed by HLA–B5801 genotyping is less costly and more effective than treatment without genotyping, and HLA–B5801 genotyping could considerably reduce the occurrence of allopurinol‐induced SCARs and related deaths.

Objectives: We investigated whether systemic lupus erythematosus (SLE) patients could be distinguished based on the time of disease onset and, if so, whether the groups differed in their clinical and laboratory features in ethnically homogeneous Korean patients. Methods: We enrolled 201 SLE patients with available clinical data at the time of onset of SLE from the lupus cohort at Chonnam National University Hospital. Sociodemographic, clinical, and laboratory data, including autoantibodies, and concomitant diseases were found at the time of diagnosis of SLE by reviewing patient charts. We divided SLE patients according to age at SLE diagnosis into three groups: juvenile-onset SLE (JSLE, diagnosed at ≤ 18 years), adult-onset SLE (ASLE, diagnosed at 19–50 years), and late-onset SLE (LSLE, diagnosed at >50 years), and compared baseline demographic, clinical, and relevant laboratory findings. Results: Of the 201 patients, 27 (14.4%), 149 (74.1%), and 25 (12.4%) were JSLE, ASLE, and LSLE patients, respectively. Fever, oral ulcers, nephritis, anemia, and thrombocytopenia were more common in JSLE patients than ASLE or LSLE patients ( p < 0.05, < 0.05, 0.001, < 0.05, and < 0.05, respectively). However, Sjögren’s syndrome was more frequent in LSLE patients than JSLE or ASLE patients ( p < 0.05). Disease activity was significantly higher in JSLE patients than in ASLE or LSLE patients ( p < 0.001). Anti-dsDNA and anti-nucleosome antibodies were found more frequently in JSLE patients and less frequently in LSLE patients ( p < 0.05 and 0.005, respectively) and decreased complement levels were more common in JSLE patients and less common in LSLE patients ( p < 0.001, 0.001, and < 0.05, respectively). Conclusions: Our results indicate that SLE patients present with different clinical and serological manifestations according to age at disease onset. JSLE patients have more severe disease activity and more frequent renal involvement and LSLE patients have milder disease activity, more commonly accompanied by Sjögren’s syndrome, at disease onset.