The study is based on the significantly increased risk of lung cancer in patients with systemic lupus erythematosus (SLE), aiming to identify the differentially expressed genes shared by both through bioinformatics methods and evaluate their potential as early diagnostic markers for lung cancer. Electrochemical sensors have developed rapidly in the field of medical testing. With advantages such as high sensitivity, fast response, low cost and portability, they have become a key technology for achieving point-of-care testing (POCT) of trace biomarkers in peripheral blood. Especially for high-risk groups like SLE that require long-term follow-up, the development of non-invasive lung cancer screening tools based on electrochemical sensing platforms has significant clinical value. Electrochemical sensors can specifically recognize target proteins (such as cell surface receptors or soluble factors) through antibodies or aptamers, converting biological binding events into electrical signals. They are suitable for detecting membrane-related or secretory molecules such as KLRB1 and FCER1A. This study integrated the peripheral blood transcriptome data of SLE (GSE154851) and lung cancer (GSE42826, GSE42834) from the GEO database. Differentially expressed genes were screened using the limma package, and common genes were identified through Venn analysis. And GO/KEGG functional enrichment, ROC curve evaluation of diagnostic efficacy and correlation analysis of immune infiltration were conducted. The results identified 10 shared genes that were uniformly dysordered in SLE and lung cancer. Among them, KLRB1, FCER1A and KCNJ15 all demonstrated excellent diagnostic performance for lung cancer (AUC >= 0.9) in the independent validation cohort. These genes are mainly enriched in interferon signaling and inflammatory response pathways, and their expression levels are significantly correlated with the infiltration of T cells, dendritic cells and macrophages in the tumor microenvironment. The proteins encoded by these three high AUC genes have stable structures, clear epitopes or soluble forms, which highly meet the design requirements of electrochemical immunosensors, providing a solid molecular basis for their future transformation into portable lung cancer early screening devices suitable for SLE patients.

The sarcopenia index (SI) is an accessible biomarker of muscle mass, yet its specific association with osteoarthritis (OA) remains unclear. This study aimed to evaluate this relationship both cross-sectionally and longitudinally in a large, representative cohort. We analyzed data from the U.S. Health and Retirement Study, including 8720 participants for cross-sectional analysis (2016) and a longitudinal cohort of 3,745 participants free of OA at baseline followed through 2020. Baseline SI was the exposure, and self-reported prevalent and incident OA were the outcomes. Multivariable-adjusted logistic regression was used to assess the association with prevalent OA and Cox proportional hazards models were used for incident OA. The dose–response relationship was analyzed employing restricted cubic splines, and sensitivity analyses were conducted to confirm the stability of the findings. The cross-sectional analysis demonstrated an inverse association between SI and prevalent OA. After multivariable adjustment, each 1-standard deviation (SD) increase in SI was associated with a lower likelihood of OA (OR = 0.921; 95

Sarcopenia and osteoarthritis (OA) frequently coexist, yet the correlation of sarcopenia with mortality specifically within the OA population remains unclear. We intend to shed light on the correlation of sarcopenia and all-cause/cardiovascular disease (CVD) mortality in OA patients. We included 1301 OA individuals from National Health and Nutrition Examination Survey (NHANES) 1999–2018. Sarcopenia was determined utilizing appendicular skeletal muscle mass from dual-energy X-ray absorptiometry and body mass index. All-cause and CVD mortality were confirmed by connection with the national death index until December 31, 2019. Survival probabilities were evaluated via log-rank test, and the linkage of sarcopenia and mortality was evaluated by multivariable Cox regression. Among the 1301 participants, 240 (18.4

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent synovial inflammation and progressive joint destruction. The underlying molecular mechanisms remain incompletely defined. Transcriptomic data of RA and normal synovial samples (GSE89408) were analyzed to identify the differentially expressed genes (DEGs). WGCNA, GO/KEGG enrichment, and PPI analysis were performed on the DEGs to screen for hub genes involved in RA progression. The proliferation, apoptosis, migration, and invasion of the MH7A fibroblast-like synoviocytes were evaluated through routine functional assays. QRT-PCR and Western blotting were conducted for molecular validation. Bioinformatics analyses identified FOXC1 as a hub transcription factor in RA and confirmed its co-expression with ATP7A. FOXC1 was markedly upregulated in RA tissues and fibroblasts, where it enhanced ATP7A expression. Overexpression of FOXC1 or ATP7A promoted the proliferation, invasion, and migration of RA fibroblasts while inhibiting apoptosis. Knockdown of ATP7A abrogated the effects of FOXC1. Mechanistically, the FOXC1-ATP7A axis activated PI3K/AKT/mTOR signaling and reduced markers of cuproptosis in the MH7A cells, suggesting an essential role in maintaining fibroblast pathogenicity. FOXC1 is a novel upstream regulator of ATP7A in synovial fibroblasts, and the FOXC1/ATP7A/PI3K/AKT pathway mediates RA pathogenesis by activating the synovial fibroblasts and suppressing cuproptosis. Targeting this axis may provide new therapeutic opportunities for RA.

Systemic lupus erythematosus (SLE) is a chronic, systemic autoimmune disease characterized by immune dysregulation, autoantibody production, and chronic inflammation, which can potentially damage almost any organ. The estimated worldwide prevalence of SLE ranges from 5 to 7 million, and it is associated with significant morbidity, premature death, and significant global disparities in terms of sex, ethnicity/race, and geography. The key pathological basis of SLE is autoantibody production and the subsequent immune complex-mediated tissue damage, which is the culmina+ abnormal type I interferon signaling, formation of neutrophil extracellular traps, activation of plasmacytoid dendritic cells, imbalance in the homeostasis of T cells and B cells, hyperactivation of B cells, and dysregulated germinal center responses. This review offers a summary of the immunological mechanisms of SLE, encompassing genetic predisposition, epigenetic alterations, and innate and adaptive immune features. In addition, organ-specific manifestations of SLE, including lupus nephritis, neuropsychiatric SLE, cutaneous disease, cardiovascular involvement, hematological involvement, and musculoskeletal sequelae have also been discussed in the context of immune dysregulation. Furthermore, the recent progress in SLE biomarkers, multi-omics integration, and machine learning techniques that allow for molecular stratification and precision medicine have been highlighted. Finally, standard of care treatments, approved biologics, and novel immunotherapies (e.g., CAR-T cell strategies and restoration of immune tolerance), as well as the unmet needs, have been summarized. Altogether, this review integrates the immunological mechanisms with clinical translation to propose a framework for personalized and potentially curative treatment of SLE.

The ratio of red blood cell distribution width to albumin (RAR) is a systemic blood-based marker associated with adverse health outcomes. Although cross-sectional studies have suggested a link between RAR and depression, its longitudinal association with the incidence and long-term course of late-life depression has not yet been established. We aimed to address this knowledge gap using data from a large cohort of older adults. This longitudinal cohort study used data from the Health and Retirement Study (2016–2022). The analysis of incident depression included 6,151 U.S. adults aged ≥ 60 years who were free of depression at baseline. Multivariable Cox regression was used to assess the association, and restricted cubic splines were applied to examine the dose-response relationship. In a subcohort of 5,588 participants, group-based trajectory modeling was used to identify depressive symptom trajectories, and their association with baseline RAR was examined using multinomial logistic regression. During a median follow-up of 6 years, 1,287 participants developed incident depression. In the fully adjusted model, each 1-unit increase in baseline RAR was associated with a 19

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease affecting synovial joints. Jinwu Jiangu Capsules (JJC) has been shown to be effective in treating RA. However, the primary active components and the underlying molecular mechanisms of JJC in RA treatment remain unclear. This study investigates how the monomers of JJC regulate the DKK1/Wnt-OPG signaling axis and autophagy in RA, both in vivo and in vitro. Evaluate the antiarthritis effects of JJC using a Type II collagen-induced arthritis (CIA) rat model. Histopathological analysis is conducted using HE staining, while qPCR, Western blot, ELISA, and GFP-LC3 are used to assess the DKK1/Wnt-OPG signaling pathway and autophagy status. Key components of the capsule are identified through network pharmacology. The effects of these components on osteoblasts are evaluated using CCK-8, alizarin red staining, ALP activity assay, EdU staining, MDC detection, and TRAP staining. JJC effectively reduced the expression of DKK1, RANKL, β-catenin, and p-β-catenin, while increasing the levels of autophagy-related proteins such as Beclin-1, LC3, and Atg5, thus positively affecting the progression of RA. Network pharmacology analysis revealed that ethyl linoleate (EL), a key component of JJC, targeted DKK1. RA model rats showed a dose-dependent response to EL. It significantly reduced cell proliferation and inflammatory cell infiltration in knee joint synovium and improved tissue structure. EL lowered DKK1 and RANKL levels in knee joint synovium and bone tissue, and increased OPG and LC3 expression. Additionally, it enhanced ALP activity and survival of osteoblasts, promoted cell proliferation and autophagy, protected osteoblast function, and inhibited the differentiation of PBMCs into osteoclasts, demonstrating its potential therapeutic effects on RA pathology. EL, a key component of JJC, exhibits significant therapeutic potential and positive effects in the treatment of RA by influencing the DKK1/Wnt-OPG signaling axis and autophagic processes.

The interaction mechanism between Coronavirus Disease (COVID-19) and rheumatoid arthritis (RA) remains inadequately understood. Consequently, this study sought to elucidate the potential mechanisms underlying the comorbidity between RA and COVID-19, as well as to identify key genes, diagnostic markers, and associated immune cells. Differential analysis of the training set, derived from the GEO database, identified differentially expressed genes (DEGs) in the RA and COVID-19 gene chip and sequencing datasets. Weighted Gene Co-expression Network Analysis (WGCNA) identified key modular genes, while protein-protein interaction (PPI) network analysis revealed hub genes, which were validated by the validation set. Receiver Operating Characteristic (ROC) curves were used to assess clinical relevance. Cytoscape-based transcription factor (TF)-mRNA and microRNA (miRNA)-mRNA regulatory networks were used to identify potential therapeutic targets, and immune cell infiltration was evaluated using the CIBERSORT algorithm. Differential expression analysis identified 2,778 DEGs in RA and 12,733 in COVID-19, with WGCNA identifying 18 shared genes, suggesting possible common molecular mechanisms. Validation analysis confirmed LGMN and NRGN as key genes associated with RA and COVID-19 comorbidity, highlighting their diagnostic significance. Network analysis identified related miRNAs and TFs, and enrichment analysis revealed the critical signaling pathways. Immune cell infiltration in patients with RA and COVID-19 was assessed using the CIBERSORT algorithm. This study preliminarily explored the shared pathogenic mechanisms between RA and COVID-19, identifying LGMN and NRGN as potential biomarkers for both diseases. Notably, NRGN may play a significant role as a common biomarker involved in the immune response in both disease states. These findings may open new avenues for the diagnosis and treatment of RA and COVID-19.

Rheumatoid arthritis (RA) is a complex autoimmune and inflammatory disease that significantly impacts the quality of life for millions worldwide. In recent years, gut microbiota has garnered extensive attention as a potential health-modulating factor, with associations identified between it and various diseases, including RA. This study aims to investigate the causal relationship between gut microbiota and RA using Mendelian Randomization (MR) analysis, and further examines the mediating role of immune cells in this connection. A MR analytical method was employed by us, integrating genome-wide association study (GWAS) data from FinnGen, MiBioGen, and research led by Valeria Orrù and her team to systematically examine the relationships between gut microbiota, immune cells, and RA. Initially, we performed a bidirectional univariable MR analysis to examine the relationship between gut microbiota and RA, consciously avoiding any possible reverse causal influences. Following this, we applied multivariable MR adjustments on gut microbiota that showed positive associations and employed a two-step methodology to examine the overall genetic predictive role of immune cell-mediated gut microbiota in the risk of developing RA. Our results demonstrate notable causal connections between different gut microbiota and RA. In particular, Mollicutes, Ruminococcaceae UCG002, and Butyricimonas displayed positive associations with RA, while other microbiota, including Rikenellaceae, Lactobacillaceae, and Veillonella, showed negative associations. Additionally, we identified a reduction in the abundance of certain microbiota, including Lachnospiraceae and Ruminococcus1, which were excluded from our study and validated for analytical accuracy using methods such as "leave-one-out." Immune cells, including CD3 found on activated CD4 regulatory T cells that express CD39, serve a mediating function in the development of RA. To summarize, our research focused on the species Butyricimonas id. 945, recognizing immune cells as crucial contributors to the relationship between genetic predictions of gut microbiota and RA. This research clarifies the intricate causal links between gut microbiota and RA, emphasizing the crucial mediating function of immune cells in this mechanism. These findings not only enhance our understanding of the pathogenesis of RA but also provide new perspectives and potential intervention targets for future prevention and treatment strategies. Future research should further investigate the specific mechanisms underlying the interactions among gut microbiota, immune cells, and RA, while considering the validation of these findings across diverse populations.

Background:Osteoarthritis (OA), the most prevalent form of arthritis, is swiftly emerging as a chronic health condition, that poses the primary cause of disability and significant socioeconomic burden. Despite its prevalence, effective therapeutic options for OA remain elusive. This study seeks to explore the therapeutic potential of edaravone (EDA), a FDA-approved free radical scavenger, in the context of OA development and to elucidate its underlying mechanisms. Methods:In vitro, oxidative stress models were induced by stimulating chondrocytes with t-butylhydroperoxide (TBHP); then, we investigated the influence of EDA on chondrocyte dysfunction, apoptosis, inflammatory responses and mitochondrial function in TBHP-treated chondrocytes, along with the underlying mechanisms. In vivo, destabilization of the medial meniscus (DMM) model was used to investigate the impact of EDA on OA progression. Nrf2 -/- mice were applied to determine the potential role of NRF2 as a target for EDA. Results:EDA notably alleviates chondrocyte dysfunction triggered by oxidative stress, safeguards chondrocytes from apoptosis and inflammatory responses, and preserves mitochondrial function and redox balance within chondrocytes. At the molecular level, EDA appears to halt the progression of OA by engaging and activating the nuclear factor erythroid 2-related factor 2 (NRF2) pathway, which is crucial for maintaining mitochondrial function and redox equilibrium. Notably, the protective effects of EDA on OA are abolished in Nrf2 -/- mice, underscoring the significance of the NRF2 signaling pathway in mediating EDA's therapeutic effects. Conclusion:EDA has the potential to mitigate chondrocyte degeneration, thereby slowing the progression of OA. Thus, EDA may represent a novel therapeutic agent for the treatment of OA, potentially expanding its clinical utility. The translational potential of this article:As a clinically licensed drug used for the treatment of neurological disorders, edaravone has shown promising therapeutic effects on OA development. Mechanistically, edaravone stabilized mitochondrial function and maintained redox homeostasis by activating NRF2 signaling pathway. The protective effects of edaravone against OA were verified in vivo and in vitro. These findings presented robust evidence for repurposing edaravone for the treatment of OA in clinic.

Background The Body Roundness Index (BRI) has been identified as a potentially superior measure of body fat distribution such as body mass index (BMI) and waist circumference (WC). However, its relationship with rheumatoid arthritis (RA) has yet to be thoroughly investigated. This study examines the association between BRI and RA risk using data from the National Health and Nutrition Examination Survey (NHANES). Methods The analysis included 28,559 adults, excluding those with missing values for BRI or RA status. BRI was calculated using height and WC measurements, while RA was self-reported by participants. Multivariate logistic regression was utilized to assess the relationship between BRI and RA, while controlling for sociodemographic variables and pertinent comorbid conditions. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were employed to assess the predictive accuracy of BRI, BMI, and WC concerning RA. Results An elevated BRI demonstrated a notable correlation with a heightened risk of RA. With each unit increase in BRI, there was a corresponding 10% increase in the likelihood of RA after complete adjustment (OR: 1.10, 95% CI: 1.08–1.12, P < 0.001). A clear dose-response relationship was identified among the BRI quartiles, where individuals in the highest quartile exhibited a 76% increased risk (OR: 1.76, 95% CI: 1.50–2.07, P < 0.001). Subgroup analysis indicated a more pronounced association among participants exhibiting hyperlipidemia (P for interaction = 0.012). Threshold analysis revealed a BRI value of 4.61 as the critical inflection point, beyond which each unit increase correlated with a 12% elevated risk of RA (OR: 1.12, P < 0.001). ROC analysis revealed that BRI exhibited the highest AUC of 0.637 in predicting RA risk, surpassing WC at 0.622 and BMI at 0.594. Conclusions BRI serves as a strong indicator of RA risk, demonstrating enhanced predictive accuracy when contrasted with conventional metrics like BMI and WC. The results indicate that BRI may function as a valuable instrument for assessing the risk of RA, especially in those exhibiting hyperlipidemia.

Background: Rheumatoid arthritis (RA) is a chronic autoimmune disease treated with tocilizumab in patients unresponsive to methotrexate. This study aimed to identify gene expression profiles and predictive models for tocilizumab treatment response in RA patients.Methods: Using the GSE78068 dataset from 38 RA patients, we identified differentially expressed genes between remission and non-remission groups. Predictive models were created using CART, random forest, and SVM techniques, with model genes selected through LASSO regression. Gene set enrichment and immune cell landscape analyses were performed to understand biological pathways and immune cell composition.Results: Analysis revealed 40 differentially expressed genes, with LASSO regression identifying 8 model genes significantly associated with remission. The SVM-based model achieved the highest performance (AUC=1.0, Brier score=0.025).Conclusions: This study developed an effective 8-gene model for predicting tocilizumab treatment response, potentially supporting personalized therapy in RA patients.

Objective:Previous cross-sectional studies have demonstrated that the body roundness index (BRI) is associated with knee osteoarthritis (KOA). However, no longitudinal studies have confirmed this association. This study aims to explore the link between BRI and KOA risk in the Chinese population through longitudinal analysis and to evaluate its utility in early diagnosis and risk prediction. Methods:This study utilizes data from the China Health and Retirement Longitudinal Study (CHARLS). A total of 7,318 participants who were followed from 2015 to 2020 were included. BRI was calculated using physical examinations and questionnaire data, and participants were categorized by quartiles. The relationship between BRI and KOA risk was assessed using multivariate weighted regression models and trend tests, while subgroup and sensitivity analyses were conducted to ensure the robustness of the findings. Results:After 5 years of follow-up, 1,035 participants (14.14%) were diagnosed with KOA. Findings indicate a positive correlation between BRI and KOA risk (HR = 1.08, 95% CI: 1.02-1.13, p = 0.0039), with an increasing trend in KOA risk across BRI quartiles (p for trend = 0.0033). Subgroup analysis reveals that the association is particularly strong among individuals aged 50-59, males, those living in rural areas, and those without cardiovascular disease. Conclusion:This study establishes that an increase in BRI significantly elevates KOA risk. These findings suggest that BRI could be an effective tool for KOA risk assessment and could contribute to the development of personalized prevention strategies. Additionally, BRI is valuable in elucidating the potential mechanisms linking body fat distribution and inflammatory responses in KOA progression.

It has been shown that low testosterone levels are associated with the development of osteoarthritis (OA). In our study, we aimed to investigate a bidirectional causal relationship between bioavailable testosterone levels and OA using Mendelian randomization (MR) analysis. In our study, the datasets from publicly available genome-wide association study (GWAS) were adopted, including the OA-related dataset (ukb-b-14486) and the bioavailable testosterone levels-related dataset (ebi-a-GCST90012104). The UKB-B-14,486 dataset contains 462,933 samples in total, including 38,472 OA samples, 424,461 control samples, and 9,851,867 SNPs, all collected from the European population in 2018. Additionally, the EBI-A-GCST90012104 dataset includes 382,988 samples and 16,137,327 SNPs, which reflect data from the European population in 2020. In total, five methods were utilized, namely MR Egger, Weighted median, Inverse variance weighted (IVW), Simple mode, and Weighted mode. Among them, IVW was the main analytical method. Additionally, the sensitivity analysis was carried out through the heterogeneity test, the horizontal pleiotropy test, and the Leave-One-Out (LOO) method. The result of forward MR analysis demonstrated that bioavailable testosterone levels were considerably relevant to OA, and were a risk factor for OA (OR = 1.01, 95

We intended to investigate the correlation of the geriatric nutritional risk index (GNRI) and the risks of all-cause and cardiovascular mortality in elderly patients with osteoarthritis (OA). This study included 2,922 OA patients aged ≥ 60 years from National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018. GNRI was obtained using serum albumin and body weight, with participants stratified into high (≥ 98) and low (< 98) GNRI groups. Cox regressions, survival analysis, and restricted cubic spline (RCS) regression have been utilized to assess mortality risks. Nonlinear threshold effects were evaluated using piecewise regression. Moreover, subgroup analyses have also been completed based on demographic, lifestyle, and clinical features. Participants with low GNRI had significantly higher risks of all-cause mortality (adjusted HR = 1.494, 95

BACKGROUND/PURPOSE(S):The gut microbiota and its metabolites play crucial roles in pathogenesis of arthritis, highlighting gut microbiota as a promising avenue for modulating autoimmunity. However, the characterization of the gut virome in arthritis patients, including osteoarthritis (OA) and gouty arthritis (GA), requires further investigation. METHODS:We employed virus-like particle (VLP)-based metagenomic sequencing to analyze gut viral community in 20 OA patients, 26 GA patients, and 31 healthy controls, encompassing a total of 77 fecal samples. RESULTS:Our analysis generated 6819 vOTUs, with a considerable proportion of viral genomes differing from existing catalogs. The gut virome in OA and GA patients differed significantly from healthy controls, showing variations in diversity and viral family abundances. We identified 157 OA-associated and 94 GA-associated vOTUs, achieving high accuracy in patient-control discrimination with random forest models. OA-associated viruses were predicted to infect pro-inflammatory bacteria or bacteria associated with immunoglobulin A production, while GA-associated viruses were linked to Bacteroidaceae or Lachnospiraceae phages. Furthermore, several viral functional orthologs displayed significant differences in frequency between OA-enriched and GA-enriched vOTUs, suggesting potential functional roles of these viruses. Additionally, we trained classification models based on gut viral signatures to effectively discriminate OA or GA patients from healthy controls, yielding AUC values up to 0.97, indicating the clinical utility of the gut virome in diagnosing OA or GA. CONCLUSION:Our study highlights distinctive alterations in viral diversity and taxonomy within gut virome of OA and GA patients, offering insights into arthritis etiology and potential treatment and prevention strategies.

ObjectiveSystemic sclerosis(SSc) remains unclear, studies suggest that inflammation may be linked to its pathogenesis. Hence, we conducted a bidirectional Mendelian randomization (MR) analysis to evaluate the association between cytokine and growth factor cycling levels and the risk of SSc onset.MethodsIn our study, the instrumental variables(IVs) for circulating cytokines were sourced from the genome-wide association study (GWAS) dataset of 8293 Finnish individuals. The SSc data comprised 302 cases and 213145 controls, and was included in the GWAS dataset. We employed four methods for the MR analysis: MR Egger, Inverse variance weighted (IVW), Weighted medium, and Weighted Mode, with IVW being the primary analytical method. Sensitivity analyses were performed using heterogeneity testing, horizontal pleiotropy testing, and the Leave One Out (LOO) method. We also conducted a reverse MR analysis to determine any reverse causal relationship between SSc and circulating cytokines.ResultsAfter Bonferroni correction, MR analysis revealed that the Interleukin-5 (IL-5) cycle level was associated with a reduced risk of SSc [odds ratio (OR)=0.48,95% confidence interval (CI): 0.27-0.84, P=0.01]. It also indicated that the Stem cell growth factor beta (SCGF-β) cycling level might elevate the risk of SSc (OR = 1.36, 95% CI: 1.01-1.83, P = 0.04). However, the reverse MR analysis did not establish a causal relationship between SSc and circulating cytokine levels. Additionally, sensitivity analysis outcomes affirm the reliability of our results.ConclusionOur MR study suggests potential causal relationships between IL-5, SCGF-β, and the risk of SSc. Further research is essential to determine how IL-5 and SCGF-β influence the development of SSc.

Background: Although studies have found that plasma proteins play a key role in the pathogenesis of rheumatoid arthritis (RA), the specific plasma proteins that are causally associated with RA still need to be elucidated. Methods: We utilized MR analysis to study cis-pQTL of plasma proteins in the UK Biobank and Icelandic populations’ large-scale GWAS data to assess the impact of plasma proteins on RA. Concurrently, through protein-protein interaction (PPI) and functional enrichment analysis, statistics-based MR (SMR) analysis, and Phenome-wide MR (PheMR) analysis, we evaluated the quality of our findings. We also conducted in vitro cell experiments for validation. Findings: IL1RN was identified as having a hypothesized causal association with RA, with rs2232354 as a significant locus potentially linking IL1RN and RA. In vitro experiments confirmed that IL1RN could inhibit the IL-1 pathway and effectively reduce the inflammatory response, suggesting its significant role in RA management. Interpretation: This study demonstrates a causal relationship between plasma proteins and RA through MR analysis, particularly highlighting the potential protective effects of IL-1RN against RA. These results offer new insights into the mechanisms and therapeutic targets for RA. Funding: FT was supported by the National Natural Science Foundation of China(82160917). X.M Y was supported by the Guizhou University of Traditional Chinese Medicine National and Provincial Science and Technology Innovation Talent Team Cultivation Project (Guizhou University of Traditional Chinese Medicine TD NO.[2022]004). XC was supported by the Guizhou Provincial Administration of Traditional Chinese Medicine Traditional Chinese Medicine and Ethnic Medicine Science and Technology Research Project (QZYY-2024-040) and by the Science and Technology Plan Project of Guiyang Health Bureau ([2023] Zhuweijian Technology Contract No. 002). Declaration of Interest: The authors declare that they have no competing interests. Ethical Approval: This study was approved by the Medical Ethics Committee of the Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine (KYW2022020) and signing patient informed consent forms.

Abstract Background Sjogren's syndrome (SS) is a complex autoimmune disease influenced by genetics, yet its genetic underpinnings remain elusive. This study investigates the genetic correlation and potential causative link between cytokine cycling levels and SS. Methods Genome-wide association studies (GWAS) were conducted with 8,293 and 14,824 European participants to identify cytokines. The GWAS dataset for SS, comprising 368,028 individuals of European ancestry (2,495 cases and 365,533 controls), was sourced from the Finnish biological sample library. Single nucleotide polymorphisms (SNPs) associated with SS were identified using Linkage disequilibrium score (LDSC) regression for Mendelian randomization (MR) analysis. The inverse variance weighted (IVW) method was the primary analytical approach. Additional methods including MR Egger, Weighted median, and Weighted mode were employed for robustness assessment. Heterogeneity testing, horizontal pleiotropy testing, and Steiger testing were conducted for sensitivity analysis. Reverse MR analysis was performed to assess the potential for a reverse causal relationship between SS and cytokines. Results LDSC regression analysis identified 46 cytokines for bidirectional MR analysis with SS. The IVW method revealed significant associations of genetically predicted cytokines IL10RB (P = 0.019, OR = 1.138, 95% CI: 1.021–1.267) and CXCL11 (P = 0.015, OR = 1.269, 95% CI: 1.048–1.537) with increased SS risk. The absence of heterogeneity and horizontal pleiotropy in sensitivity analysis underscores the robustness of these findings. Conclusion The study suggests a potential causal relationship between genetically predicted cytokines and SS, particularly through IL10RB and CXCL11 cycles. Further research is warranted to elucidate the biological mechanisms by which cytokine cycling levels influence SS.