BackgroundAn increasing number of autoimmune disorders (AD) have been associated with microbial dysbiosis[1, 2]. However, this dysbiosis is difficult to characterize for individual patients owing to the high heterogeneity of the gut microbiota. Thus, researchers must find an accurate method of characterizing the AD gut microbiota that is meaningful to clinical diagnosis.ObjectivesThe aim of this study was to investigate the enterotype characters of intestinal flora in AD and their associations with peripheral lymphocyte subpopulations and cytokines.MethodsA total of 339 AD patients and 339 age- and sex- matched healthy controls (HCs) were enrolled in this study. Mathematical modeling using Dirichlet multinomial mixtures (DMM) was applied to describe the variability in the microbiome data and cluster samples into enterotypes. The peripheral lymphocyte subsets were detected by flow cytometry and the cytokines were assessed by ELISA. Differential abundance analysis was carried out the STAMP software. R (version 4.1.0) was used for comparative statistics, and spearman’s correlation analysis was used to assess the correlations between the relative abundances of bacterial genera and clinical variables.ResultsLaplace approximation of DMM suggested gut microbiota of AD patients and HCs both can be divided into two distinct enterotypes (Figure 1 A-B), and AD E1 and HC E1 were primarily dominated by Prevotella while AD E2 and HC E2 by Bacteroides. Interestingly, the Prevotella-enriched enterotype (AD E1 and HC E1) had a higher alpha diversity than The Bacteroides-enriched enterotype (AD E2 and HC E2). Patients with AD always had a lower richness and diversity compared with those of HCs in each enterotype (p< 0.001), suggesting gut microbiome was markedly less diverse in composition in AD. Bray curtis distance-based beta-diversity were also different (P<0.001, ANOSIM.R =0.23, Figure 1 C-H). Significant differences in gut microbiota composition at the genus level between AD patients and HCs were found using the STAMP software in each enterotype. Compared with HCs, 37 species in AD E1 patients and 40 species in AD E2 patients of flora were discovered to be distinctly different. In the co-upregulated flora of both enterotypes, Lactobacillus was inversely associated with a variety of lymphocytes such as T, CD4+T, NK, Th2, Th17, Treg cells(P<0.05), and positive correlation with IL-10 and IFN-γ(P<0.05,Figure 1 I). However, in the co-downregulated floras Coprococcus had a positive correlation with B, NK and Treg cells, and anaerostipes had a negativate corrleation with IL-2 and IL-4(P<0.05,Figure 1 J).ConclusionThere were both two enterotypes in patients and HCs with autoimmune disease, E2 exhibited a loss of Prevotella but a growth of Bacteroides, while E1 presented the opposite results, which were closely correlated with peripheral lymphocyte subsets and cytokines.References[1]Levy M, Thaiss CA, Zeevi D, Dohnalová L, Zilberman-Schapira G, Mahdi JA, David E, Savidor A, Korem T, Herzig Y et al: Microbiota-Modulated Metabolites Shape the Intestinal Microenvironment by Regulating NLRP6 Inflammasome Signaling. Cell 2015, 163(6):1428-1443.[2]Belkaid Y, Hand TW: Role of the microbiota in immunity and inflammation. Cell 2014, 157(1):121-141.AcknowledgementsThis work was supported by the National Natural Science Foundation of China (No. 82001740).Disclosure of InterestsNone declared

BackgroundInflammatory bowel disease (IBD) is a chronic and recurring intestinal inflammatory disease, that includes Crohn’s disease (CD) and ulcerative colitis (UC). There is no known cure for IBD and its subtypes. It is essential to identify modifiable risk factors and seek potential treatments to slow down the progression or even prevent the onset of these diseases. As one of these factors, physical activity and sedentary time have recently aroused much research interest in the coming years. However, previous observational studies designed to examine the relationship between physical activity, sedentary time and inflammatory bowel diseases have mostly yielded inconsistent results. Furthermore, whether observed associations are causal remains elusive due to reverse causation and residual confounding noted in observational studies.ObjectivesMendelian randomization (MR) assesses causality by using genotypes to simulate randomized trial groups. Herein, we assessed whether lifelong physical activity (i.e., moderate to vigorous intense physical activity [MVPA]) or sedentary time (sedentary behavior at work, sedentary commuting, and leisure screen time [LST]) has the potential causal relationship with the risk for IBD and its subtypes, using a genetically informed method.MethodsInstrumental variables (IVs) for the main exposures in our study were extracted from the latest published meta-analysis of up to 703,901 European individuals in 51 studies on a genome-wide-association study (GWAS) for self-reported MVPA, LST, sedentary commuting, and sedentary behavior at work (minimum n = 159,606; maximum n = 608,595)[1]. Summary statistics for IBD, CD, and UC were retrieved from the up-to-date studies in European ancestry (cases/controls for IBD: 25042/34915; CD: 12194/28072; UC: 12366/33609)[2]. The inverse variance weighted (IVW) method was utilized as the primary MR analysis. Weighted median and MR-Egger were then implemented as complements to the IVW.ResultsMendelian randomization evidence suggested a protective relationship between MVPA and IBD (Figure 1a) (IBD: odds ratio [OR]: 0.67, 95% confidence interval [CI]: 0.47 to 0.95, P = 0.03) and CD (Figure 1b) (OR: 0.53, 95% CI: 0.30 to 0.94, P = 0.03). Greater genetically-predicted LST was associated with higher risks of IBD (Figure 1c) (IBD: OR: 1.21, 95% CI: 1.06 to 1.38, P = 0.004) and CD (Figure 1d) (OR: 1.25, 95% CI: 1.07 to 1.45, P = 0.004). In contrast, there was no statistically significant relationship between MVPA and UC (OR: 0.76, 95% CI: 0.49 to 1.18, P = 0.23). A similar insignificant association was found between LST and UC (OR: 1.12, 95% CI: 0.95 to 1.32, P = 0.18). Furthermore, there was no significant relationship between sedentary behavior at work and IBD (including CD and UC) or between sedentary commuting and IBD (including CD and UC) with a P-value > 0.05.ConclusionOur study provides strong evidence that greater MVPA and lower LST are likely to reduce the risks for IBD and CD. Particular attention should be given to reducing LST and encouraging proper physical activities during the management and treatment of IBD and CD.References[1]Wang Z, Emmerich A, Pillon NJ, et al. Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention. Nat Genet 2022;54(9):1332-44.[2]de Lange KM, Moutsianas L, Lee JC, et al. Genome-wide association study implicates immune activation of multiple integrin genes in inflammatory bowel disease. Nat Genet 2017;49(2):256-61.Acknowledgements:NIL.Disclosure of InterestsNone Declared.

BackgroundSecondary Sjogren’s syndrome(SS) is a common extra-articular manifestation of rheumatoid arthritis (RA)[1]. RA patients combined with SS have different outcomes from those without SS[2]. However, the studies investigated the characteristics of gut microbiota in patients with RA and SS is limited.ObjectivesTo investigate the characteristics of gut microbiome and the associations between flora and peripheral lymphocyte subpopulations in RA patients with or without Sjogren’s syndrome.MethodsA total of 326 samples from 145 RA patients without SS, 23 RA combined with SS patients(RA-SS) and 168 healthy controls (HCs) were recruit in this study from The Second Hospital of Shanxi Medical University (Taiyuan, Shanxi, China). The gut microbiota were investigated via 16s rRNA sequencing and the peripheral T lymphocyte subsets of these participants were assessed by flow cytometry. The Wilcoxon rank-sum test was used to compare alpha diversity indicesbetween groups. Differential abundance analysis was carried out the STAMP software. Spearman’s correlation analysis was used to assess the correlations between the relative abundances of bacterial genera and clinical meatures.ResultsPatients with RA and RA-SS exhibited a significant reduction in the richness and diversity of gut microbiota compared with those of HCs (Figure 1 A-B, p < 0.05), whereas there was no significant difference between RA and RA-SS patients. Principal co-ordinates analyses based on bray curtis distance suggested that these there microbiota states explained a definable proportion of observed variance in microbiota composition (ANOSIM R2 = 0.074, p < 0.001; Figure 1 C). Compared with HCs, 58 species of flora were discovered to be distinctly different in RA patients without SS at the genus level of which 6 species of flora unique to RA-SS patients were presented much fewer ([Eubacterium]_hallii_group, Anaerostipes, CAG-56, Fusobacterium, Turicibacter and Enterococcus). Among these RA-SS patients‘ unique species of flora, it seems that Turicibacter is the key species of flora, owing to whose has a positive correlation with most of lymphocytes such as T, B, CD4+T, CD8+T and NK cells suggesting a close association with intestinal immunity.(Figure 1 F-G,P<0.05)ConclusionRA patients with deficiency of Turicibacter in flora had higer occurrence of Sjögren’s syndrome sjogren’s syndrome complication, which was correlated with peripherial lymphocyte subpopulations and cytokines.References[1]Chen Y, Ma C, Liu L, He J, Zhu C, Zheng F, Dai W, Hong X, Liu D, Tang D et al: Analysis of gut microbiota and metabolites in patients with rheumatoid arthritis and identification of potential biomarkers. Aging 2021, 13(20):23689-23701.[2]Brown LE, Frits ML, Iannaccone CK, Weinblatt ME, Shadick NA, Liao KP: Clinical characteristics of RA patients with secondary SS and association with joint damage. Rheumatology (Oxf) 2015, 54(5):816-820.AcknowledgementsThis work was supported by the National Natural Science Foundation of China (No. 82001740).Disclosure of InterestsNone declared

BackgroundUlcerative colitis (UC) is an inflammatory bowel disease characterized by idiopathic and recurrent mucosal inflammation [1]. The pathogenesis is multifactorial, involving genetic susceptibility, epithelial barrier defects, dysregulation of the immune response, and environmental factors. UC is a highly heterogeneous disease [2]. Despite efforts to characterize disease subgroups and predict differential outcomes in UC patients, disease heterogeneity is not adequately translated into current clinical subclassifications.ObjectivesThis study seeks to unravel this complexity by using an integrated systems approach that classifies UC patients into different phenotypes based on the immune microenvironment, capable of providing new insights into the development of stratified therapies.MethodsRNA sequencing datasets of 602 colon tissue samples from 455 patients with UC and 147 healthy controls (HC) was imported from GEO database. The microarray datasets were transformed into immune cell components by CIBERSORT, and patients were stratified by a consensus clustering algorithm. Then, the cellular characteristics of the subtypes and the overall role of specific pathways were determined by immune cell infiltration and pathway enrichment. The clinical characteristics of the different subtypes were also analyzed to clarify the characteristics of these classifications.ResultsPatients can be classified into two distinct immune phenotypes (Subtype A, B) based on their specific RIME, which have different cellular and pathway characteristics. (Figure A, B) The results show that Subtype A is mainly enriched in immune cells such as B cells, CD8+ T cells, CD4+ memory T cells, DC cells, macrophages, mast cells and plasma cells. Acidic granulocytes and neutrophils were more active in Subtype B. It was also significantly enriched in the peroxisome proliferator-activated receptor (PPAR) signaling pathway in Subtype B. In contrast, Subtype A showed a strong enrichment for most inflammatory pathways B cell and T cell receptor signaling, IL-17 signaling pathway, TNF, and interleukin 4 and interleukin 13 signaling pathway. (Figure 1 D, E) In addition, there was a significant difference between molecular subclassification and disease status, with Subtype A being more active in patients (69.3% of Subtype A vs.30.6% of Subtype B subtypes in 137 cases), while inactive patients, Subtype B were more prevalent (44.8% of Subtype A vs. 55.2% of Subtype B in 105 cases). (Figure 1C)ConclusionAnalysis of the immune microenvironment of colonic mucosal tissue provides good insight into the pathophysiological characteristics of UC. These results can be used as a model for future studies. the response and clinical outcomes of patients with different classification need to be further investigated.References[1]Ghosh S, Shand A, Ferguson A. Ulcerative colitis. BMJ (Clinical research ed). 2000;320(7242):1119-23.[2]Ordás I, Eckmann L, Talamini M, Baumgart DC, Sandborn WJ. Ulcerative colitis. Lancet (London, England). 2012;380(9853):1606-19.Acknowledgements:NIL.Disclosure of InterestsNone Declared.

BackgroundUlcerative colitis (UC) is an inflammatory bowel disease characterized by idiopathic and recurrent mucosal inflammation, whereas disease heterogeneity has not sufficiently translated into current clinical subclassifications[1].ObjectivesThis study aims to Identify and characterize subgroups of patients with similar target status and molecular biomarkers to reliably predict treatment response which is of great interest for the treatment of UC patients.Methods16 microarray datasets including 602 colon tissue samples (455 patients with UC and 147 healthy controls) were both obtained from GEO database. Depend on up-regulated differentially expressed genes (DEGs),unsupervised clustering[2]was applied to group the samples and pathways and biomarkers associated with UC was unearthed by gene-set enrichment analysis. Xgboost classifier was used for evaluating the efficacy of different biologics in patients with UC.ResultsAccording to the 267 upregulated DEGs of UC, colon tissue samples were classified into three subtypes(A-C) with distinct molecular and cellular characteristics. Subtype A is designated as epithelial hyperplastic subtype with epithelial features while subtype C was characterized by the immune activation subtype with prominent immune cells and proinflammatory signatures. The subtype B is named mixed, which is in between the above two and is moderately activated in all signaling pathways. It is worth noting that, compared with subtype C as refractory UC patients, subtype A shows stronger correlation with the excellent reactions of biological agents such as golimumab(80%in A vs 37.5%in C), infliximab(100%in A vs 16.7%in C), vedolizumab(33.3%in A vs 0% in C) and ustekinumab(22.4%in A vs 3%in C).ConclusionThese results, based on the most comprehensive microarray provide an in-depth understanding of the pathophysiological characteristics of UC, and build an accurate typing model for ulcerative colitis, which can benefit clinical treatment.References[1]Ghosh S, Shand A, Ferguson A. Ulcerative colitis.BMJ (Clinical research ed) 2000;320(7242):1119-23. doi: 10.1136/bmj.320.7242.1119 [published Online First: 2000/04/25][2]Pierce BL, Burgess S. Efficient design for Mendelian randomization studies: subsample and 2-sample instrumental variable estimators.American journal of epidemiology2013;178(7):1177-84. doi: 10.1093/aje/kwt084 [published Online First: 2013/07/19]Acknowledgements:NIL.Disclosure of InterestsNone Declared.