BACKGROUND: Juvenile idiopathic arthritis (JIA) is the most common chronic inflammatory rheumatic disease in children, and adalimumab is one of the primary treatment options. Although it is widely used for inflammatory diseases, there is limited research on its safety and efficacy in patients with psychiatric disorders or in those with inflammatory diseases who also have comorbid psychiatric conditions.
METHODS: We report a 12-year-old adolescent boy who presented with emotional instability for 1 year, exacerbated leading to hospital admission in the past month. Upon detailed evaluation after admission, it was found that the patient\'s emotional fluctuations may be related to the use of Adalimumab. Follow-up after psychiatric inpatient treatment revealed that the patient did not experience emotional excitement again after discontinuing Adalimumab.
CONCLUSIONS: Although tumor necrosis factor-α inhibitors have positive effects on the emotional, cognitive, and physical functions of patients with inflammatory diseases, their use may induce mood swings in patients with comorbid mood disorders. This is particularly important for adolescents with rapid mood changes, where greater caution is required. Further research is necessary to clarify the correlation between the adverse effects of these drugs and their impact on patients with bipolar disorder.

UNASSIGNED: Neutrophil extracellular traps (NETs) are important factors in initiating and perpetuating inflammation. However, the role of NETs in different subtypes of juvenile idiopathic arthritis (JIA) has been rarely studied. Therefore, we aimed to explore the ability of JIA-derived neutrophils to release NETs and the effect of TNF-α (tumor necrosis factor-alpha) inhibitors on NET formation both in vitro and in vivo, and evaluate the associations of NET-derived products with clinical and immune-related parameters.
UNASSIGNED: The ability of neutrophils to release NETs and the effect of adalimumab on NET formation was assessed via in vitro stimulation and inhibition studies. Plasma NET-derived products were detected to assess the incidence of NET formation in vivo. Furthermore, flow cytometry and western blotting were used to detect NET-associated signaling components in neutrophils.
UNASSIGNED: Compared to those derived from HCs, neutrophils derived from patients with oligoarticular-JIA, polyarticular-JIA and enthesitis-related arthritis were more prone to generate NETs spontaneously and in response to TNF-α or PMA in vitro. Excessive NET formation existed in peripheral circulation of JIA patients, and elevated plasma levels of NET-derived products (cell-free DNA and MPO-DNA complexes) could accurately distinguish JIA patients from HCs and were positively correlated with disease activity. Multiple linear regression analysis showed that erythrocyte sedimentation rate and TNF-α levels were independent variables and were positively correlated with cell-free DNA concentration. Notably, TNF-α inhibitors could effectively prevent NET formation both in vitro and in vivo. Moreover, the phosphorylation levels of NET-associated kinases in JIA-derived neutrophils were markedly increased.
UNASSIGNED: Our data suggest that NETs might play pathogenic roles and may be involved in TNF-α-mediated inflammation in JIA. Circulating NET-derived products possess potential diagnostic and disease monitoring value. Furthermore, the preliminary results related to the molecular mechanisms of NET formation in JIA patients provide a theoretical basis for NET-targeted therapy.

UNASSIGNED: The gut microbiota significantly influences the onset and progression of juvenile idiopathic arthritis (JIA) and associated uveitis (JIAU); however, the causality remains unclear. This study aims to establish a causal link between gut microbiota and JIA or JIAU.
UNASSIGNED: Using publicly available genome-wide association studies (GAWS) summary data, we conducted a two-sample Mendelian randomisation (MR) analysis employing various methods, namely inverse variance weighted (IVW), simple mode, weighted mode, weighted median and MR-Egger regression methods, to assess the causal association between JIA or JIAU and gut microbiota. Sensitivity analyses, including Cochrane\'s Q test, MR-Egger intercept test, leave-one-out analysis and MR-PRESSO, were performed to evaluate the robustness of the MR results. Subsequently, reverse MR analysis was conducted to determine causality between gene-predicted gut microbiota abundance and JIA or JIAU.
UNASSIGNED: The MR analysis revealed a causal association between gut microbiota abundance variations and JIA or JIAU risk. Specifically, the increased abundance of genus Ruminococcaceae UCG013 (OR: 0.055, 95%CI: 0.006-0.103, p = 0.026) and genus Ruminococcaceae UCG003 (β: 0.06, 95%CI: 0.003-0.117, p = 0.041) correlated with an increased risk of JIA, while genus Lachnospiraceae UCG001 (OR: 0.833, 95%CI: 0.699~0.993, p = 0.042) was associated with a reduced risk of JIA, among others. Sensitivity analysis confirmed MR analysis robustness.
UNASSIGNED: This study provides substantial evidence supporting a causal association between genetically predicted gut microbiota and JIA or JIAU. It highlights the significant role of intestinal flora in JIA or JIAU development, suggesting their potential as novel biomarkers for diagnosis and prevention. These findings offer valuable insights to mitigate the impact of JIA or JIAU.

OBJECTIVE: Diagnosing juvenile idiopathic arthritis (JIA) is challenging. Our study aimed to investigate the clinical significance of anti-α-1,4-D-polygalacturonic acid (PGA) antibodies in JIA, focusing on their role in diagnosis and assessing disease activity.
METHODS: In this prospective case-control study, we examined variations in serum levels of PGA-IgA and PGA-IgG among children with different types of JIA and healthy controls. Serum PGA-IgA and PGA-IgG levels were assessed concurrently in children with active and inactive JIA.
RESULTS: This study included 126 patients diagnosed with JIA, 13 neonates, and 76 healthy children. Serum PGA-IgA and PGA-IgG levels were assessed, which revealed significant differences in PGA-IgA levels between various JIA subtypes and controls. An analysis of PGA-IgA levels in various JIA states revealed a statistically significant difference. Receiver operating characteristic (ROC) analysis demonstrated the robust predictive capability of PGA-IgA, with an AUC of 0.879 (p < 0.001), along with a specificity of 0.842 and sensitivity of 0.848.
CONCLUSIONS: Increased levels of anti-PGA antibodies, particularly PGA-IgA, were significantly associated with JIA. PGA-IgA may serve as a sensitive biomarker for disease activity in JIA and could potentially aid in the diagnosis of JIA. Key Points • This study found a significant correlation between blood levels of PGA-IgA and juvenile idiopathic arthritis (JIA), which may provide valuable diagnostic insights. • PGA-IgA shows potential as a sensitive biomarker for the assessment of disease activity in JIA patients, helping to determine disease activity.

UNASSIGNED: The causal relationship between juvenile idiopathic arthritis (JIA) and primary ovarian failure (POF) remains uncertain. To elucidate this relationship, we employed a two-sample Mendelian randomization analysis.
UNASSIGNED: The single nucleotide polymorphisms (SNPs) associated with JIA were obtained from a previously published genome-wide association study (GWAS), while the pooled data for POF originated from the FinnGen consortium. The study populations consisted exclusively of individuals of European descent. In our Mendelian randomization analysis, we performed inverse-variance weighted analysis, weighted-median analysis, weighted-mode analysis and Mendelian randomization-Egger regression analysis, supplemented by sensitivity analyses to validate the accuracy and robustness of the findings.
UNASSIGNED: The IVW (OR = 1.23, 95% CI 1.06-1.43; P = 0.007) and weighted median (OR = 1.25, 95% CI 1.06-1.47; P = 0.009), along with sensitivity analysis validation, provide compelling evidence of a significant causal association between JIA and POF.
UNASSIGNED: The study revealed a significant causal association between genetically predicted JIA and POF, indicating that JIA significantly elevates the risk of developing POF. Therefore, it is recommended to implement screening for premature ovarian failure in women diagnosed with JIA.

UNASSIGNED: The pathogenesis of juvenile idiopathic arthritis (JIA) is strongly influenced by an impaired immune system. However, the molecular mechanisms underlying its development and progression have not been elucidated. In this study, the computational methods TRUST4 were used to construct a T-cell receptor (TCR) and B-cell receptor (BCR) repertoire from the peripheral blood of JIA patients via bulk RNA-seq data, after which the clonality and diversity of the immune repertoire were analyzed.
UNASSIGNED: Our findings revealed significant differences in the frequency of clonotypes between the JIA and healthy control groups in terms of the TCR and BCR repertoires. This work identified specific V genes and J genes in TCRs and BCRs that could be used to expand our understanding of JIA. After single-cell RNA analysis, the relative percentages of CD14 monocytes were significantly greater in the JIA group. Cell-cell communication analysis revealed the significant role of the MIF signaling pathway in JIA.
UNASSIGNED: In conclusion, this work describes the immune features of both the TCR and BCR repertoires under JIA conditions and provides novel insight into immunotherapy for JIA.

BACKGROUND: Juvenile Idiopathic Arthritis (JIA) is a condition that occurs when individuals under the age of 16 develop arthritis that lasts for more than six weeks, and the cause is unknown. The development of JIA may be linked to serum metabolites. Nevertheless, the association between JIA pathogenesis and serum metabolites is unclear, and there are discrepancies in the findings across studies.
METHODS: In this research, the association between JIA in humans and 486 serum metabolites was assessed using genetic variation data and genome-wide association study. The identification of causal relationships was accomplished through the application of univariate Mendelian randomization (MR) analysis. Various statistical methods, including inverse variance weighted and MR-Egger, were applied to achieve this objective. To ensure that the findings from the MR analysis were trustworthy, a number of assessments were carried out. To ensure the accuracy of the obtained results, a range of techniques were utilised including the Cochran Q test, examination of the MR-Egger intercept, implementation of the leave-one-out strategy, and regression analysis of linkage disequilibrium scores. In order to identify the specific metabolic pathways associated with JIA, our primary objective was to perform pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes.
RESULTS: Two-sample summary data MR analyses and sensitivity analyses showed that five metabolites were significantly causally associated with JIA, including two risk factors-kynurenine (odds ratio [OR]: 16.39, 95% confidence interval [CI]: 2.07-129.63, p = 5.11 × 10- 6) and linolenate (OR: 16.48, 95% CI: 1.32-206.22, p = 0.030)-and three protective factors-3-dehydrocarnitine (OR: 0.32, 95% CI: 0.14-0.72, p = 0.007), levulinate (4-oxovalerate) (OR: 0.40, 95% CI: 0.20-0.80, p = 0.010), and X-14,208 (phenylalanylserine) (OR: 0.68, 95% CI: 0.51-0.92, p = 0.010). Furthermore, seven metabolic pathways, including α-linolenic acid metabolism and pantothenate and CoA biosynthesis, are potentially associated with the onset and progression of JIA.
CONCLUSIONS: Five serum metabolites, including kynurenine and 3-dehydrocarnitine, may be causally associated with JIA. These results provide a theoretical framework for developing effective JIA prevention and screening strategies.

BACKGROUND: Various non-steroidal anti-inflammatory drugs (NSAIDs) have been used for juvenile idiopathic arthritis (JIA). However, the optimal method for JIA has not yet been developed.
OBJECTIVE: To perform a systematic review and network meta-analysis to determine the optimal instructions.
METHODS: We searched for randomized controlled trials (RCTs) from PubMed, EMBASE, Google Scholar, CNKI, and Wanfang without restriction for publication date or language at August, 2023. Any RCTs that comparing the effectiveness of NSAIDs with each other or placebo for JIA were included in this network meta-analysis. The surface under the cumulative ranking curve (SUCRA) analysis was used to rank the treatments. P value less than 0.05 was identified as statistically significant.
RESULTS: We included 8 RCTs (1127 patients) comparing 8 different instructions including meloxicam (0.125 qd and 0.250 qd), Celecoxib (3 mg/kg bid and 6 mg/kg bid), piroxicam, Naproxen (5.0 mg/kg/d, 7.5 mg/kg/d and 12.5 mg/kg/d), inuprofen (30-40 mg/kg/d), Aspirin (60-80 mg/kg/d, 75 mg/kg/d, and 55 mg/kg/d), Tolmetin (15 mg/kg/d), Rofecoxib, and placebo. There were no significant differences between any two NSAIDs regarding ACR Pedi 30 response. The SUCRA shows that celecoxib (6 mg/kg bid) ranked first (SUCRA, 88.9%), rofecoxib ranked second (SUCRA, 68.1%), Celecoxib (3 mg/kg bid) ranked third (SUCRA, 51.0%). There were no significant differences between any two NSAIDs regarding adverse events. The SUCRA shows that placebo ranked first (SUCRA, 88.2%), piroxicam ranked second (SUCRA, 60.5%), rofecoxib (0.6 mg/kg qd) ranked third (SUCRA, 56.1%), meloxicam (0.125 mg/kg qd) ranked fourth (SUCRA, 56.1%), and rofecoxib (0.3 mg/kg qd) ranked fifth (SUCRA, 56.1%).
CONCLUSIONS: In summary, celecoxib (6 mg/kg bid) was found to be the most effective NSAID for treating JIA. Rofecoxib, piroxicam, and meloxicam may be safer options, but further research is needed to confirm these findings in larger trials with higher quality studies.

UNASSIGNED: The objective of this study is to investigate the causal relationship between gut microbiota and juvenile idiopathic arthritis, and to identify and quantify the potential role of plasma metabolites as mediators.
UNASSIGNED: Using summary-level data from genome-wide association studies, a two-sample Mendelian randomization was conducted involving 131 gut microbiota genus, 1,400 plasma metabolites, and juvenile idiopathic arthritis. Additionally, a two-step approach was employed to quantify the proportion of the effect of gut microbiota on juvenile idiopathic arthritis mediated by plasma metabolites. Effect estimation primarily utilized Inverse Variance Weighting, with further validation using Bayesian weighted Mendelian randomization.
UNASSIGNED: In our MR analysis, a positive correlation was observed between Rikenellaceae and the risk of juvenile idiopathic arthritis, while Dorea showed a negative correlation with juvenile idiopathic arthritis risk. Mediation analysis indicated that Furaneol sulfate levels acted as a mediator between Dorea and juvenile idiopathic arthritis, with an indirect effect proportion of 19.94, 95% CI [8.86-31.03%].
UNASSIGNED: Our study confirms a causal relationship between specific microbial genus and juvenile idiopathic arthritis, and computes the proportion of the effect mediated by plasma metabolites, offering novel insights for clinical interventions in juvenile idiopathic arthritis.

UNASSIGNED: Human gut microbiota has been shown to be significantly associated with various inflammatory diseases. Therefore, this study aimed to develop an excellent auxiliary tool for the diagnosis of juvenile idiopathic arthritis (JIA) based on fecal microbial biomarkers.
UNASSIGNED: The fecal metagenomic sequencing data associated with JIA were extracted from NCBI, and the sequencing data were transformed into the relative abundance of microorganisms by professional data cleaning (KneadData, Trimmomatic and Bowtie2) and comparison software (Kraken2 and Bracken). After that, the fecal microbes with high abundance were extracted for subsequent analysis. The extracted fecal microbes were further screened by least absolute shrinkage and selection operator (LASSO) regression, and the selected fecal microbe biomarkers were used for model training. In this study, we constructed six different machine learning (ML) models, and then selected the best model for constructing a JIA diagnostic tool by comparing the performance of the models based on a combined consideration of area under receiver operating characteristic curve (AUC), accuracy, specificity, F1 score, calibration curves and clinical decision curves. In addition, to further explain the model, Permutation Importance analysis and Shapley Additive Explanations (SHAP) were performed to understand the contribution of each biomarker in the prediction process.
UNASSIGNED: A total of 231 individuals were included in this study, including 203 JIA patients and Non-JIA individuals. In the analysis of diversity at the genus level, the alpha diversity represented by Shannon value was not significantly different between the two groups, while the belt diversity was slightly different. After selection by LASSO regression, 10 fecal microbe biomarkers were selected for model training. By comparing six different models, the XGB model showed the best performance, which average AUC, accuracy and F1 score were 0.976, 0.914 and 0.952, respectively, thus being used to construct the final JIA diagnosis model.
UNASSIGNED: A JIA diagnosis model based on XGB algorithm was constructed with excellent performance, which may assist physicians in early detection of JIA patients and improve the prognosis of JIA patients.