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Impact of genetic variants on the age of systemic lupus erythematosus (SLE) onset was not fully understood. We investigated a cumulative effect of SLE-risk variants on the age of SLE onset and scanned genome-wide SNPs to search for new risk loci of childhood-onset SLE (cSLE). We analyzed 781 Korean single-center SLE subjects who previously genotyped by both Immunochip and genome-wide SNP arrays. Individual genetic risk scores (GRS) from well-validated SLE susceptibility loci were calculated and tested for their association with cSLE (<16 years at onset). Single-variant association tests were performed using a multivariable logistic regression adjusting for population stratification. GRS from SLE susceptibility loci was significantly higher in cSLE than aSLE (p = 1.23 × 10 −3 ). Two SNPs, rs7460469 in XKR6 (p = 1.26 × 10 −8 , OR = 5.58) and rs7300146 in GLT1D1 p = 1.49 × 10 −8 , OR = 2.85), showed the most significant associations with cSLE. The model consisting of GRS of SLE and two newly identified loci showed an area under curve (AUC) of 0.71 in a receiver operating characteristics (ROC) curve for prediction of cSLE. In conclusion, cSLE is associated with a high cumulative SLE-risk effect and two novel SNPs rs7460469 and rs7300146, providing the first predictive model for cSLE in Koreans.

In patients with systemic lupus erythematosus (SLE), there are concerns that infections may increase the risk of flares. We evaluated the association between influenza infection and SLE flares resulting in hospitalization. SLE flares resulting in hospitalization and influenza cases were ascertained from the Korean national healthcare insurance database (2014–2018). We used a self-controlled case series design. We defined the risk interval as the first 7 days after the influenza index date and the control interval was defined as all other times during the observation period of each year. We estimated the incidence rates of SLE flares resulting in hospitalization during the risk interval and control interval and compared them using a Poisson regression model. We identified 1624 influenza infections among the 1455 patients with SLE. Among those, there were 98 flares in 79 patients with SLE. The incidence ratio (IR) for flares during the risk interval as compared with the control interval was 25.75 (95% confidence interval 17.63–37.59). This significantly increased the IRs for flares during the risk interval in both women (IR 27.65) and men (IR 15.30), all age groups (IR 17.00–37.84), with and without immunosuppressive agent (IR 24.29 and 28.45, respectively), and with and without prior respiratory diseases (IR 21.86 and 26.82, respectively). We found significant association between influenza infection and SLE flares resulting in hospitalization. Influenza infection has to be considered as a risk factor for flares in all SLE patients regardless of age, sex, medications, and comorbidities.

A 58-year-old woman had a history of medical and acupuncture treatment for rheumatoid arthritis. Plain radiographs of the hands showed severe joint deformities, with short gold threads surrounding the joints.

The fluctuating nature of disease activity in systemic lupus erythematosus (SLE), alternating between flares and remissions, poses substantial challenges for its effective management. The use of current biomarkers for monitoring SLE is limited in clinical settings owing to insufficient comprehension of the complex immune involvement underlying the disease course. Here, therefore, we profiled peripheral blood mononuclear cells at both stable and exacerbation states (total of n  = 19) from six patients with SLE and 32 healthy donors using integrated single-cell RNA and T cell receptor (TCR) sequencing. To validate our findings, we analyzed two independent external datasets: bulk RNA sequencing and TCR data from 79 controls and 62 patients with SLE and single-cell RNA sequencing data from 99 healthy controls and 162 patients with SLE. Our analysis revealed cell type-specific activation of interferon-related genes in SLE grouped into four clusters, with elevated activity in disease-associated immune cells. Among these, atypical B cells associated with autoantibody production exhibited distinct differentiation patterns compared with conventional memory B cells, driven by heightened interferon signaling in SLE. Notably, clonal expansion of effector CD8 T cells emerged as a key driver of disease exacerbation, as indicated by reduced TCR diversity. Specific CD8 T cell clonotypes expanded during flare states, transitioning to effector phenotypes that exhibited heightened cytotoxicity and amplified interferon signaling, strongly correlating with tissue damage and flare severity. Our findings establish a critical link between interferon-driven mechanisms and cytotoxic T cell dysfunction in SLE flares, offering potential targets for therapeutic intervention and predictive biomarkers. Atypical B cells and CD8 T cells fuel lupus exacerbations Systemic lupus erythematosus (SLE) is a complex autoimmune disease that affects various organs and presents differently in each patient. This study addresses the challenge of understanding the variability of SLE by examining immune cells at a detailed level. The authors used single-cell RNA sequencing to analyze blood samples from six patients with SLE and healthy controls. The study focused on peripheral blood mononuclear cells, which are crucial for the immune response. By examining these cells individually, the researchers identified over 20 distinct cell types involved in SLE. They found that certain immune cells, such as CD8 T cells, were active during disease flare-ups, which are periods of increased symptoms. The results showed that specific gene patterns in these cells could predict disease activity and help classify patients into subtypes. This understanding could lead to more personalized treatments for SLE. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.

Osteoarthritis (OA) is an age-related joint disease that is characterized by degeneration of articular cartilage and chronic pain. Oxidative stress is considered one of the pathophysiological factors in the progression of OA. We investigated the effects of grape seed proanthocyanidin extract (GSPE), which is an antioxidant, on monosodium iodoacetate (MIA)-induced arthritis of the knee joint of rat, which is an animal model of human OA. GSPE (100 mg/kg or 300 mg/kg) or saline was given orally three times per week for 4 weeks after the MIA injection. Pain was measured using the paw withdrawal latency (PWL), the paw withdrawal threshold (PWT) and the hind limb weight bearing ability. Joint damage was assessed using histological and microscopic analysis and microcomputerized tomography. Matrix metalloproteinase-13 (MMP13) and nitrotyrosine were detected using immunohistochemistry. Administration of GSPE to the MIA-treated rats significantly increased the PWL and PWT and this resulted in recovery of hind paw weight distribution ( P < 0.05). GSPE reduced the loss of chondrocytes and proteoglycan, the production of MMP13, nitrotyrosine and IL-1β and the formation of osteophytes, and it reduced the number of subchondral bone fractures in the MIA-treated rats. These results indicate that GSPE is antinociceptive and it is protective against joint damage in the MIA-treated rat model of OA. GSPE could open up novel avenues for the treatment of OA.

Background We aimed to investigate the effects of ambient respiratory viral infections in the general population on rheumatoid arthritis (RA) development. Methods Data of weekly incident RA (2012–2013) were obtained from the Korean National Health Insurance claims database, and those of weekly observations on eight respiratory viral infections were obtained from the Korea Centers for Disease Control and Prevention database. We estimated the percentage change in incident RA associated with ambient mean respiratory viral infections using a generalized linear model, after adjusting for time trend, air pollution, and meteorological data. Results A total of 24,117 cases of incident RA (mean age 54.7 years, 18,688 [77.5%] women) were analyzed. Ambient respiratory viral infections in the population were associated with a higher number of incident RA over time, and its effect peaked 6 or 7 weeks after exposure. Among the 8 viruses, parainfluenza virus (4.8% for 1% respiratory viral infection increase, 95% CI 1.6 to 8.1, P  = .003), coronavirus (9.2%, 3.9 to 14.8, P  < .001), and metapneumovirus (44%, 2.0 to 103.4, P  = .038) were associated with increased number of incident RA. The impact of these respiratory viral infections remained significant in women (3.8%, 12.1%, and 67.4%, respectively, P  < .05) and in older patients (10.7%, 14.6%, and 118.2%, respectively, P  < .05). Conclusions Ambient respiratory viral infections in the population were associated with an increased number of incident RA, especially in women and older patients, suggesting that respiratory viral infections can be a novel environmental risk factor for the development of RA.

[This corrects the article DOI: 10.1371/journal.pone.0308010.].

The lung is recognized as a site for initiating the formation of self-antigen and autoimmune responses in rheumatoid arthritis (RA). We aimed to investigate the association of upper respiratory microbiota with RA, autoantibody production, and disease activity. Forty-six patients with RA and 17 controls were examined. Nasopharyngeal swab samples were sequenced for microbiome profiling using the V3–V4 region of the 16S rRNA gene. The microbial diversity and relative abundance were compared between RA patients and controls. Correlation analyses were conducted to evaluate the relationship between microbial abundance and clinical markers such as autoantibodies and disease activity. Microbial diversity analysis revealed no major differences between RA patients and healthy controls. However, beta diversity analysis indicated a subtle distinction in microbial composition (unweighted UniFrac distance) between the two groups ( P = 0.03), hinting at a minor subset of microbiota associated with disease status. Differential abundance analysis uncovered specific taxa at various taxonomic levels, including Saccharibacteria (TM7) [O-1] ( P FDR = 2.53 × 10 −2 ), TM7 [F-1] ( P FDR = 5.20 × 10 −3 ), Microbacterium ( P FDR = 3.37 × 10 −4 ), and Stenotrophomonas ( P FDR = 2.57 × 10 −3 ). The relative abundance of ten genera correlated significantly with anti-cyclic citrullinated peptide (anti-CCP) antibody levels ( P FDR < 0.05) and 11 genera were significantly associated with disease activity markers, including ESR, CRP, DAS28-ESR, and DAS-CRP ( P FDR < 0.05). In particular, Saccharibacteria TM7 [G-3] and Peptostreptococcaceae [XI] [G-1] were correlated with all disease activity biomarkers. Dysbiosis in the upper respiratory mucosa is associated with RA, anti-CCP antibody levels, and disease activity.

Limited knowledge exists regarding biomarkers that predict treatment response in Lupus nephritis (LN). We aimed to identify potential molecular biomarkers to predict treatment response in patients with LN. We enrolled 66 patients with active LN who underwent renal biopsy upon enrollment. Serum and urine samples were collected longitudinally, and we measured 12 biomarkers in each sample using a multiplex immunofluorescence assay. These biomarkers included monocyte chemoattractant protein-1 (MCP-1), interferon gamma-induced protein 10 (IP-10), interferon-γ (IFN-γ), interleukin 6 (IL-6), interleukin 16 (IL-16), interleukin 17 (IL-17), interleukin 23 (IL-23), tumor necrosis factor receptor II (TNF-RII), vascular cell adhesion molecule 1 (VCAM-1), retinol-binding protein 4 (RBP 4), vitamin D binding protein (VDBP), and neutrophil gelatinase-associated lipocalin (NGAL). Patients were categorized into two groups based on their 1-year treatment response to Mycophenolate mofetil (MMF)-based therapy: 50 responders and 16 non-responders. Only urine IL-17 (uIL-17) showed baseline level differences between the two groups, with higher in responders. In ROC curve analyses assessing the predictive performance of biomarkers, baseline uIL-17 and changes in uIL-6 and uIL-23 levels at 3 months could predict the 1-year treatment response, showing AUC values of 0.70 (95% CI 0.54–0.87), 0.70 (0.54–0.86), and 0.71 (0.57–0.85), respectively. Combining uIL-6 and uIL-23 into a model improved predictability, achieving an AUC of 0.75 (0.61–0.90). Baseline uIL-17 levels and early changes in uIL-6 and uIL-23 could serve as potential biomarkers to predict 1-year treatment response in lupus nephritis patients receiving MMF-based therapy.

Background Exercise has an anti-inflammatory effect and reduces fat mass. Leptin has been known to be proinflammatory adipokines mainly produced by adipocytes. However, few studies have investigated the association between exercise and changes in serum leptin levels of patients with RA. This study evaluated the effect of an individualized resistance exercise on inflammatory markers including leptin as well as muscle strength and exercise capacity in patients with rheumatoid arthritis (RA). Methods A total of 42 age- and sex-matched participants were assigned to a resistance exercise program (60 min, once a week for 12 weeks, and self-exercise twice a week) or to a control group. Muscle strength, exercise capacities, and inflammatory markers such as cytokines and adipokines were assessed at baseline and at 12 weeks follow-up. Longitudinal changes in muscle strength, exercise capacity, cytokines, and adipokines between groups were tested with repeated measures analysis of variance or using the generalized estimating equation, with adjustment for baseline disease activity score 28-C response protein as a covariate. Results A total of 37 of 42 female patients with RA completed this prospective intervention study. Grip strength improved significantly in the exercise group ( P < 0.05), while no between-group changes were found. Quadriceps contraction power ( P for group-time interaction = 0.035 for the right side and P for group-time interaction = 0.012 for the left side) and 6-minute walking distance ( P for group-time interaction = 0.021) were all improved significantly in the exercise group compared with the control group. In addition, serum leptin levels were significantly decreased in the exercise group compared with the control group ( P for group-time interaction = 5.22 × 10 −5 ), but not the other cytokines or adipokines. The change in serum leptin levels correlated with the changes in fat mass (Rho = 0.491, P = 0.015) and visceral fat area (Rho = 0.501, P = 0.013). Conclusion In addition to muscle strength and exercise capacity, the 12 weeks of individualized resistance exercise reduced serum leptin levels in keeping with body fat mass or visceral fat area, suggesting that serum leptin levels might be a surrogate marker of exercise in RA.