Ulcerative Colitis Samples Research Articles

Functional characterization of novel anti-DEFA5 monoclonal antibody clones 1A8 and 4F5 in inflammatory bowel disease colitis tissues

BackgroundThe aberrant expression of α defensin 5 (DEFA5) protein in colonic inflammatory bowel diseases (IBDs) underlies the distinct pathogenesis of Crohn’s colitis (CC). It can serve as a biomarker for differentiating CC from Ulcerative colitis (UC), particularly in Indeterminate colitis (IC) cases into UC and CC. We evaluated the specificity of commercially available anti-DEFA5 antibodies, emphasizing the need to further validate their appropriateness for a given application and highlighting the necessity for novel antibodies.MethodsWe established two mice monoclonal DEFA5 antibody clones, 1A8 and 4F5, by immunizing mice with purified recombinant protein. We validated the specificity, sensitivity, and cross-reactivity of these antibodies in recognizing both endogenous and recombinant DEFA5 protein, especially for use in Immunohistochemistry (IHC), Western blot (WB), Immunoprecipitation (IP), and enzyme-linked immunosorbent assay (ELISA).ResultsClones 1A8 and 4F5 effectively recognized the endogenous DEFA5 in active human colon tissue from patients with diverticulitis (DV), UC, CC, and IC disease samples, as well as in transiently transfected HEK293T cells expressing DEFA5 with minimal non-confounding cross reactivity.ConclusionsThe 1A8 and 4F5 clones are useful for a wide variety of immunoassays, including WB, IHC, IP/WB, and ELISA. Their specificity enhances their potential as valuable tools for research applications in IBD colitis.

P0086 The role of enteric glial cells in patients with ulcerative colitis.

Abstract Background Enteric glial cells (EGCs) have traditionally been regarded as supportive cells within the enteric nervous system. However, recent studies indicate that, beyond their involvement in neural circuit formation, EGCs possess antigen-presenting capabilities and actively contribute to mucosal defense. In the mouse myenteric plexus, inflammation-inducing stimuli have been shown to trigger the expression of MHC class II on glial cells, which subsequently influences the differentiation of helper T-cell and regulatory T-cell subtypes, thereby maintaining immune homeostasis under inflammatory conditions. Nevertheless, research on EGCs in humans remains limited. Thus, this study aimed to elucidate the function and involvement of EGCs in the pathogenesis of ulcerative colitis (UC). Methods Normal colonic mucosa was obtained from histologically and macroscopically intact areas of patients with colorectal cancer (n=6). Colonic mucosa from UC patients, diagnosed based on established clinical, bacteriological, radiologic, and endoscopic criteria, was also obtained from surgically resected specimens (n=7). Lamina propria mononuclear cells were isolated through enzymatic digestion, and mesenchymal stromal fractions (CD31-CD45-EPCAM-CD90+), containing glial cells, were further isolated using flow cytometry for single-cell RNA sequencing (scRNA-seq) analysis and T cell differentiation assay. Results We identified a specific EGC population (Cluster 3: PDPN+ HLA-DR high) with high antigen-presenting capacity, which was selectively elevated at inflamed sites in UC. scRNA-seq analysis, transcription factor activity analysis, and gene-enriched pathway analysis indicated that IFNγ-STAT1 signaling activation within Cluster 3 enhances MHC class II expression. To assess T-cell effects, naive CD4+ T-cells were co-cultured with PDPN+ HLA-DR high cells isolated from UC samples. This co-culture induced differentiation into IL-10+ IL-17A+ CD4+ T-cells, with a positive correlation observed between the proportions of IL-10+ IL-17A+ CD4+ T-cells and PDPN+ HLA-DR high cells. Bulk RNA sequencing and qPCR analysis further demonstrated that PDPN+ HLA-DR high cells highly express the IL-27 subunit EBI3 and the TGF-β activator integrin αvβ8. To evaluate clinical relevance, we also examined the correlation between PDPN+ HLA-DR high cell numbers and clinical factors in 45 UC patients. Immunofluorescence staining for the glial marker CDH2 and HLA-DR revealed a negative correlation between CDH2+ HLA-DR+ cell numbers and preoperative Mayo endoscopic scores. Conclusion PDPN+ HLA-DR high glial cells are increased in inflamed areas of UC patients, suggesting a role in anti-inflammatory processes and the maintenance of immune homeostasis.

P0216 PANoptosis-related genes can predict the progression of ulcerative colitis and colitis-associated colorectal cancer

Abstract Background Ulcerative colitis (UC) is a complex inflammatory bowel disease that significantly increases the risk of developing colitis-associated colorectal cancer (CAC). The etiology of UC remains unclear, and the mechanisms underlying its progression to CAC require further exploration. Recent studies have identified a novel form of cell death called pan-apoptosis, which is closely linked to inflammatory diseases. However, its specific role in UC and CAC progression is not yet fully understood. This study aims to develop a reliable predictive model based on pan-apoptosis using high-throughput RNA sequencing and validate it, along with an analysis of cellular characteristics in UC patients through single-cell sequencing data. This research offers new insights for the prognosis and treatment of UC patients. Methods This study collected single-cell and high-throughput sequencing data from UC patients and defined a pan-apoptosis gene set. The dataset was analyzed for immune infiltration, differential expression, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). Additionally, weighted gene co-expression network analysis (WGCNA) was used to identify key genes associated with UC, which were then utilized to construct a predictive model. Finally, single-cell data analysis was conducted on UC patients, followed by in vitro validation of the expression of key genes. Results By analyzing differentially expressed genes in UC samples and using the pan-apoptosis gene set, WGCNA identified key genes associated with UC, including CASP1, LCN2, STAT3, and ZBP1. These genes were used to construct a pan-apoptosis-related predictive model, establishing a pan-apoptosis-related score (PAR-Score). The results showed that PAR-Score has strong classification ability and is positively correlated with immune cell infiltration and the inflammatory microenvironment in UC patients. Notably, CAC patients had significantly higher PAR-Scores. Single-cell sequencing data confirmed that monocyte activity in UC patients is linked to pan-apoptosis, while intercellular communication among immune cells was notably reduced. The expression levels of key genes in the predictive model were validated in vivo. Drug predictions targeting these genes suggested that Leridistim, interferon-γ, and other compounds could serve as potential therapeutic agents for UC or CAC. Conclusion The predictive model established based on pan-apoptosis exhibits good predictive performance, providing new perspectives for assessing the condition and progression of UC patients, and opening up new avenues for the treatment of UC and CAC in the future. References Nature. 2007;448(7152):427-434. doi:10.1038/nature060052. Jess T, Rungoe C, Peyrin L. Risk of Colorectal Cancer in Patients With Ulcerative Colitis: A Meta-analysis of Population-Based Cohort Studies. 2012;10(6). 3. Shin J, Baek GH, Cha B, et al. Complementary Therapeutic Effect of Fecal Microbiota Transplantation in Ulcerative Colitis after the Response to Anti-Tumor Necrosis Factor Alpha Agent Was Lost: A Case Report. Published online 2024. doi:10.3390/biomedicines12040800 Front Cell Infect Microbiol. 2019;9:406. doi:10.3389/fcimb.2019.00406 J Immunol. 2022;209(9):1625-1633. doi:10.4049/jimmunol.2200508 World J Gastroenterol. 2014;20(44):16389. doi:10.3748/wjg.v20.i44.16389

Retinoblastoma-Binding Protein 9 Suppresses Intestinal Inflammation and Inflammation-Induced Tumorigenesis in Mice

BACKGROUND & AIMSRetinoblastoma-binding protein 9 (RBBP9) was initially reported as cell cycle regulator via RB/E2F. Accumulating evidence has revealed the importance of RBBP9 in physiological and pathological states including inflammatory disease. However, the functional role of RBBP9 in ulcerative colitis (UC) and colitis-associated cancer (CAC) remains elusive. METHODSHuman samples of UC and CAC were examined by immunohistochemical and bioinformatics analyses. We established dextran sodium sulfate (DSS)-induced colitis, azoxymethane (AOM)/DSS-induced CAC model, and ApcMin/+ sporadic tumor model using wild-type and Rbbp9-/- mice. RNA sequencing was analyzed to identify the phenotype alternation upon Rbbp9 deletion. In addition, genetic and pharmacological inhibition of the Janus kinase (JAK)/signal transducer and activator of transcription 1 (STAT1) pathway was performed. RESULTSThe expression of RBBP9 was reduced in human UC and CAC samples. The loss of RBBP9 enhanced the activation of interferon (IFN)/JAK/STAT1 signaling, resulting in susceptibility to DSS-induced colitis and AOM/DSS-induced CAC tumors by increasing epithelial cell apoptosis and immune activation. An in vitro kinase assay revealed that RBBP9 directly regulated JAK/STAT1 signaling by suppressing STAT1 phosphorylation. A positive feedback loop involving epithelial cell apoptosis, commensal microbiome invasion, and activation of submucosal immune activity was identified in Rbbp9-/- mouse intestines through enhanced JAK/STAT1 signaling in RBBP9-deficient epithelial cells and macrophages. The genetic inhibition of STAT1 or treatment with the JAK/STAT inhibitor reversed epithelial cell apoptosis and mitigated the enhanced susceptibility to DSS-induced colitis in Rbbp9-/- mice. CONCLUSIONSRBBP9 suppresses the intestinal inflammation by negatively regulating JAK/STAT1 signaling pathway.

Gut fungal profile in new onset treatment-naïve ulcerative colitis in Saudi children.

Although the role of fungi in gut inflammation in IBD has been suggested, data are still limited in ulcerative colitis (UC). Our aim was to describe the gut fungal profile in a pediatric UC in Saudi Arabia. Fecal samples from children with UC and control samples provided by healthy school children were collected. The fungal DNA was analyzed using Shotgun metagenomic procedures. Shannon alpha diversity, beta diversity, differential abundance, random forest classification algorithm, and area under the curve were analyzed. There were 20 children with UC and 20 healthy school children. The median age and range were 13 (0.5-21) and 13 (7-16) years for children with UC and controls, respectively. Male subjects were 40% and 35% for UC and controls, respectively. At diagnosis, the UC extent was E4 (38%); E3 (25%); E2 (37%) and 35% had a PUCAI ≥65. The reduction of alpha diversity and the significant dissimilarity in children with UC were similar to those of most published studies. However, a significant difference was found at all taxa levels with a remarkable enhancement of Candida genus and Saccharomyces cerevisiae in children with UC. Three species were identified as fungal signatures and an area under the curve of 98.4% (95.1-100% CI), indicating an association with UC that has not been reported thus far. We report significant fungal dysbiosis in children with UC consistent with published literature. However, the report of potential fungal signature and a strong association with UC deserves further studies with a bigger sample size from other populations.

Potential diagnostic markers and therapeutic targets for non-alcoholic fatty liver disease and ulcerative colitis based on bioinformatics analysis and machine learning.

Non-alcoholic fatty liver disease (NAFLD) and ulcerative colitis (UC) are two common health issues that have gained significant global attention. Previous studies have suggested a possible connection between NAFLD and UC, but the underlying pathophysiology remains unclear. This study investigates common genes, underlying pathogenesis mechanisms, identification of diagnostic markers applicable to both conditions, and exploration of potential therapeutic targets shared by NAFLD and UC. We obtained datasets for NAFLD and UC from the GEO database. The DEGs in the GSE89632 dataset of the NAFLD and GSE87466 of the UC dataset were analyzed. WGCNA, a powerful tool for identifying modules of highly correlated genes, was employed for both datasets. The DEGs of NAFLD and UC and the modular genes were then intersected to obtain shared genes. Functional enrichment analysis was conducted on these shared genes. Next, we utilize the STRING database to establish a PPI network. To enhance visualization, we employ Cytoscape software. Subsequently, the Cytohubba algorithm within Cytoscape was used to identify central genes. Diagnostic biomarkers were initially screened using LASSO regression and SVM methods. The diagnostic value of ROC curve analysis was assessed to detect diagnostic genes in both training and validation sets for NAFLD and UC. A nomogram was also developed to evaluate diagnostic efficacy. Additionally, we used the CIBERSORT algorithm to explore immune infiltration patterns in both NAFLD and UC samples. Finally, we investigated the correlation between hub gene expression, diagnostic gene expression, and immune infiltration levels. We identified 34 shared genes that were found to be associated with both NAFLD and UC. These genes were subjected to enrichment analysis, which revealed significant enrichment in several pathways, including the IL-17 signaling pathway, Rheumatoid arthritis, and Chagas disease. One optimal candidate gene was selected through LASSO regression and SVM: CCL2. The ROC curve confirmed the presence of CCL2 in both the NAFLD and UC training sets and other validation sets. This finding was further validated using a nomogram in the validation set. Additionally, the expression levels of CCL2 for NAFLD and UC showed a significant correlation with immune cell infiltration. This study identified a gene (CCL2) as a biomarker for NAFLD and UC, which may actively participate in the progression of NAFLD and UC. This discovery holds significant implications for understanding the progression of these diseases and potentially developing more effective diagnostic and treatment strategies.

Crohn's disease and ulcerative colitis share two molecular subtypes with different mechanisms and drug response.

Several therapies have been approved to treat crohn's disease (CD) and ulcerative colitis (UC), indicating that both diseases may share the same molecular subtypes. The aim of this study is to identify shared patient subtypes with common molecular drivers of disease. Five public datasets with 406 CD and 421 UC samples were integrated to identify molecular subtypes. Then, the patient labels from six independent datasets and eight treatment datasets were predicted for validating subtypes and identifying the relationship with response status of corticosteroids, infliximab, vedolizumab, and ustekimumab. Two molecular subtypes were identified from the training datasets, in which CD and UC patients were relatively evenly represented in each subtype. We found six S1-specific gene modules related to innate/adaptive immune responses and tissue remodeling and nine S1-specific cell types (cycling T, Tregs, cd8+ lamina propria, follicular B, cycling B plasma, inflammatory monocytes, inflammatory fibroblast, and post-capillary venules). Subtype S2 was associated with three modules related to metabolism functions and four cell types (immature enterocytes, transit amplifying, immature goblet and WNT5B+). The subtypes can be replicated in six independent datasets based on a 20-gene classifier. Furthermore, response rates to four treatments in subtype S2 were significantly higher than those in subtype S1. This study discovered and validated a robust transcriptome-based molecular classification shared by CD and UC and built a 20-gene classifier. Because two subtypes have different molecular mechanisms and drug response, our classification may aid interpretation of heterogeneous molecular and clinical information in IBD patients.

Anti-DEFA5 Monoclonal Antibody Clones 1A8 and 4F5 Immunoreactive Bioassay for Diagnosing Inflammatory Bowel Disease.

Robust evidence suggests that the aberrant expression of α defensin 5 protein (DEFA5) in colon inflammatory bowel diseases (IBDs) underlies the distinct pathogenesis of Crohn's colitis, can be exploited as a reliable diagnostic biomarker to differential diagnosis of Crohn's colitis (CC) from Ulcerative colitis (UC) in otherwise indeterminate colitis (IC). We evaluated the specificity of the commercially available anti-DEFA5 antibodies and showed further validation of their appropriateness for a given application is required. We established two mouse monoclonal DEFA5 antibody clones 1A8 and 4F5 by immunizing the mice with purified recombinant protein and validated the specificity, selectivity and cross reactivity in recognizing the endogenous and recombinant DEFA5 protein, especially for Immunohistochemistry, Western blot, Immunoprecipitation, or enzyme-linked immunosorbent assay. Clones 1A8 and 4F5 recognized effectively the endogenous DEFA5 in active human diverticulitis (DV), UC, CC or IC disease samples, including transiently transfected HEK293T cells expressing DEFA5 with high degree of specificity and minimal non-confounding cross reactivity. 1A8 and 4F5 clones are worth studying in larger IBD cohorts to fully address whether DEFA5 expression may be used as a diagnostic biomarker to discrimination of the diagnosis of UC from CC or IC into authentic CC or UC or a colitis with different pathological characteristics.

RNA methylation machinery and m6A target genes as circulating biomarkers of ulcerative colitis and Crohn’s disease: Correlation with disease activity, location, and inflammatory cytokines

Accurate diagnosis of ulcerative colitis (UC) and Crohn’s disease (CD), the main subtypes of inflammatory bowel disease (IBD), has been challenging due to the constraints of the current techniques. N6-methyl adenosine (m6A) regulators have evolved as key players in IBD pathogenesis; however, their relation to its clinical setting is largely unexplored. This study investigated the potential of selected RNA methylation machinery and m6A target genes as serum biomarkers of UC and CD, their predictive and discriminating capabilities, and their correlations with laboratory data, interleukin (IL)-6, interferon-γ, disease activity scores, and pathological features. Fifty UC and 45 CD patients, along with 30 healthy volunteers were enlisted. The mRNA expression levels of the m6A writers methyltransferase-like 3 (METTL3) and Wilms-tumor associated protein (WTAP), and the reader YTH domain family, member 1 (YTHDF1), along with the m6A candidate genes sex determining region Y-box 2 (SOX2), hexokinase 2 (HK2), and ubiquitin-conjugating enzyme E2 L3 (UBE2L3) were upregulated in UC patients, whereas only METTL3, HK2, and UBE2L3 were upregulated in CD patients versus controls. Serum WTAP (AUC = 0.94, 95 %CI = 0.874–1.006) and HK2 (AUC = 0.911, 95 %CI = 0.843–0.980) expression levels showed excellent diagnostic accuracy for UC, METTL3 showed excellent diagnostic accuracy for CD (AUC = 0.91, 95 %CI = 0.828–0.992), meanwhile, WTAP showed excellent discriminative power between the two diseases (AUC = 0.91, 95 %CI = 0.849–0.979). Multivariate logistic analysis unveiled the association of METTL3 and UBE2L3 expression with the risk of CD and UC diagnosis, respectively, controlled by age and sex as confounders. Remarkable correlations were recorded between the gene expression of studied m6A regulators and targets in both diseases. Among UC patients, serum METTL3 and WTAP were correlated with UC extent/type, while WTAP was correlated with IL-6. Among CD patients, serum METTL3 and HK2 were correlated with CD activity index (CDAI) and CD location. In conclusion, m6A regulators and target genes are distinctly expressed in UC and CD clinical samples, correlate with disease activity and extent/location, and could serve as a novel approach to empower the diagnosis and stratification of IBD subtypes.

Identification and experimental validation of immune-related gene PPARG is involved in ulcerative colitis

BackgroundThe pathophysiology of ulcerative colitis (UC) is believed to be heavily influenced by immunology, which presents challenges for both diagnosis and treatment. The main aims of this study are to deepen our understanding of the immunological characteristics associated with the disease and to identify valuable biomarkers for diagnosis and treatment. MethodsThe UC datasets were sourced from the GEO database and were analyzed using unsupervised clustering to identify different subtypes of UC. Twelve machine learning algorithms and Deep learning model DNN were developed to identify potential UC biomarkers, with the LIME and SHAP methods used to explain the models' findings. PPI network is used to verify the identified key biomarkers, and then a network connecting super enhancers, transcription factors and genes is constructed. Single-cell sequencing technology was utilized to investigate the role of Peroxisome Proliferator Activated Receptor Gamma (PPARG) in UC and its correlation with macrophage infiltration. Furthermore, alterations in PPARG expression were validated through Western blot (WB) and immunohistochemistry (IHC) in both in vitro and in vivo experiments. ResultBy utilizing bioinformatics techniques, we were able to pinpoint PPARG as a key biomarker for UC. The expression of PPARG was significantly reduced in cell models, UC animal models, and colitis models induced by dextran sodium sulfate (DSS). Interestingly, overexpression of PPARG was able to restore intestinal barrier function in H2O2-induced IEC-6 cells. Additionally, immune-related differentially expressed genes (DEGs) allowed for efficient classification of UC samples into neutrophil and mitochondrial metabolic subtypes. A diagnostic model incorporating the three disease-specific genes PPARG, PLA2G2A, and IDO1 demonstrated high accuracy in distinguishing between the UC group and the control group. Furthermore, single-cell analysis revealed that decreased PPARG expression in colon tissue may contribute to the polarization of M1 macrophages through activation of inflammatory pathways. ConclusionIn conclusion, PPARG, a gene related to immunity, has been established as a reliable potential biomarker for the diagnosis and treatment of UC. The immune response it controls plays a key role in the progression and development of UC by enabling interaction between characteristic biomarkers and immune infiltrating cells.

The development of artificial intelligence in the histological diagnosis of Inflammatory Bowel Disease (IBD-AI)

BackgroundInflammatory bowel disease (IBD) includes Crohn's Disease (CD) and Ulcerative Colitis (UC). Correct diagnosis requires the identification of precise morphological features such basal plasmacytosis. However, histopathological interpretation can be challenging, and it is subject to high variability. AimThe IBD-Artificial Intelligence (AI) project aims at the development of an AI-based evaluation system to support the diagnosis of IBD, semi-automatically quantifying basal plasmacytosis. MethodsA deep learning model was trained to detect and quantify plasma cells on a public dataset of 4981 annotated images. The model was then tested on an external validation cohort of 356 intestinal biopsies of CD, UC and healthy controls. AI diagnostic performance was calculated compared to human gold standard. ResultsThe system correctly found that CD and UC samples had a greater prevalence of basal plasma cells with mean number of PCs within ROIs of 38.22 (95 % CI: 31.73, 49.04) for CD, 55.16 (46.57, 65.93) for UC, and 17.25 (CI: 12.17, 27.05) for controls. Overall, OR=4.968 (CI: 1.835, 14.638) was found for IBD compared to normal mucosa (CD: +59 %; UC: +129 %). Additionally, as expected, UC samples were found to have more plasma cells in colon than CD cases. ConclusionOur model accurately replicated human assessment of basal plasmacytosis, underscoring the value of AI models as a potential aid IBD diagnosis.

HOXD10 regulates intestinal permeability and inhibits inflammation of dextran sulfate sodium-induced ulcerative colitis through the inactivation of the Rho/ROCK/MMPs axis

Abstract Ulcerative colitis (UC) has been identified as a severe inflammatory disease with significantly increased incidence across the world. The detailed role and mechanism of HOXD10 in UC remain unclear. In present study, we found that HOXD10 was lowly expressed in UC samples and was notably decreased by dextran sulfate sodium (DSS) administration. Overexpression of HOXD10 dramatically ameliorated DSS-induced UC symptoms, including the loss of weight, increased disease activity index values, and the shortened colon length. Additionally, terminal-deoxynucleoitidyl transferase mediated nick end labeling and immunohistochemistry staining assays showed that HOXD10 overexpression suppressed cell apoptosis and facilitated proliferation of colon tissues after DSS treatment. Moreover, HOXD10 overexpression obviously suppressed DSS-triggered inflammatory response by decreasing the expression level of TNF-α, IL-6, and IL-1β. Furthermore, overexpression of HOXD10 effectively restored the intestinal permeability, thereby alleviating DSS-induced intestinal barrier dysfunction. Mechanistic study demonstrated that HOXD10 significantly reduced the activities of Rho/ROCK/MMPs axis in colon tissues of mice with UC. In conclusion, this study revealed that HOXD10 might effectively improve DSS-induced UC symptoms by suppressing the activation of Rho/ROCK/MMPs pathway.

Exploring the Relevance of Disulfidptosis to the Pathophysiology of Ulcerative Colitis by Bioinformatics Analysis.

Ulcerative colitis (UC) is a nonspecific inflammatory disease confined to the intestinal mucosa and submucosa, and its prevalence significantly increases each year. Disulfidptosis is a recently discovered new form of cell death that has been suggested to be involved in multiple diseases. The aim of this study was to explore the relevance of disulfidptosis in UC. First, the UC datasets were downloaded from the Gene Expression Omnibus (GEO) database, and UC samples were typed based on upregulated disulfidptosis-related genes (DRGs). Then, weighted gene co-expression network analysis (WGCNA) was performed on the datasets and molecular subtypes of UC, respectively, to obtain candidate signature genes. After validation of the validation set and qRT-PCR, we constructed a nomogram model by signature genes to predict the risk of UC. Finally, single-cell sequencing analysis was used to study the heterogeneity of UC and to demonstrate the expression of DRGs and signature genes at the single-cell level. A total of 7 DRGs were significantly upregulated in the expression profiles of UC, and 180 UC samples were divided into two subtypes based on these DRGs. Five candidate signature genes were obtained by intersecting two key gene modules selected by WGCNA. After evaluation, four signature genes with diagnostic relevance (COL4A1, PRRX1, NNMT, and PECAM1) were eventually identified. The nomogram model showed excellent prediction ability. Finally, in the single-cell analysis, there were eight cell types (including B cells, T cells, monocyte, smooth muscle cells, epithelial cells, neutrophil, endothelial cells and NK cells) were identified. The signature genes were significantly expressed mainly in endothelial cells and smooth muscle cells. In this study, subtypes related to disulfidptosis were identified, and single-cell analysis was performed to understand the pathogenesis of UC from a new perspective. Four signature genes were screened and a prediction model with high accuracy was established. This provides novel insights for early diagnosis and therapeutic targets in UC.

Challenges in Defining a Reference Set of Differentially Expressed lncRNAs in Ulcerative Colitis by Meta-Analysis.

The study aimed to identify common differentially expressed lncRNAs from manually curated ulcerative colitis (UC) gene expression omnibus (GEO) datasets. Nine UC transcriptomic datasets of clearly annotated human colonic biopsies were included in the study. The datasets were manually curated to select active UC samples and controls. R packages geneknitR, gprofiler, clusterProfiler were used for gene symbol annotation. The R EdgeR package was used to analyze differential expression. This resulted in a total of nineteen lncRNAs that were differentially expressed in at least three datasets of the nine GEO datasets. Several of the differentially expressed lncRNAs found in UC were associated with promoting colorectal cancer (CRC) through regulating gene expression, epithelial to mesenchymal transition (EMT), cell cycle progression, and by promoting tumor proliferation, invasion, and migration. The expression of several lncRNAs varied between disease states and tissue locations within the same disease state. The identified differentially expressed lncRNAs may function as general markers for active UC independent of biopsy location, age, gender, or treatment, thereby representing a comparative resource for future comparisons using available GEO UC datasets.

Restoring Treg/Th17 cell balance in ulcerative colitis through HRas silencing and MAPK pathway inhibition

This study investigates HRas-dependent mechanisms in the disruption of regulatory T (Treg) cells and T helper 17 (Th17) cells balance in ulcerative colitis (UC). Comprehensive RNA sequencing and bioinformatics analyses revealed elevated HRas and MAPK pathway-related protein expression in UC samples. Using a murine UC model induced by dextran sulfate sodium (DSS), HRas silencing was found to promote Treg cell differentiation and suppress Th17 cell production, effectively restoring balance. Inactivation of the MAPK pathway played a pivotal role in this rebalancing effect. In vivo experiments further confirmed that HRas silencing mitigated colon tissue damage in DSS-induced mice, emphasizing its potential as a therapeutic strategy for UC.

Identification and immunoinfiltration analysis of key genes in ulcerative colitis using WGCNA.

Ulcerative colitis (UC) is a chronic non-specific inflammatory bowel disease characterized by an unclear pathogenesis. This study aims to screen out key genes related to UC pathogenesis. Bioinformatics analysis was conducted for screening key genes linked to UC pathogenesis, and the expression of the screened key genes was verified by establishing a UC mouse model. Through bioinformatics analysis, five key genes were obtained. Subsequent infiltration analysis revealed seven significantly different immune cell types between the UC and general samples. Additionally, animal experiment results illustrated markedly decreased body weight, visible colonic shortening and damage, along with a significant increase in the DAI score of the DSS-induced mice in the UC group in comparison with the NC group. In addition, H&E staining results demonstrated histological changes including marked inflammatory cell infiltration, loss of crypts, and epithelial destruction in the colon mucosa epithelium. qRT-PCR analysis indicated a down-regulation of ABCG2 and an up-regulation of IL1RN, REG4, SERPINB5 and TRIM29 in the UC mouse model. Notably, this observed trend showed a significant dependence on the concentration of DSS, with the mouse model of UC induced by 7% DSS demonstrating a more severe disease state compared to that induced by 5% DSS. ABCG2, IL1RN, REG4, SERPINB5 and TRIM29 were screened out as key genes related to UC by bioinformatics analysis. The expression of ABCG2 was down-regulated, and that of IL1RN, REG4, SERPINB5 and TRIM29 were up-regulated in UC mice as revealed by animal experiments.

P119 Single-cell RNA sequencing in Inflammatory Bowel Disease in patients with Primary Sclerosing Cholangitis: a distinct form of colitis

Abstract Background Primary sclerosing cholangitis (PSC) is an inflammatory disorder of the bile ducts, in which Inflammatory bowel disease (IBD) concomitantly occurs (PSC-IBD). Substantial differences in clinical presentation are observed between PSC-IBD and ulcerative colitis (UC). In this study we aim to find distinct pathomechanisms for PSC-IBD using single-cell RNA sequencing. Methods Forty-seven colonic samples of PSC-IBD (n=24), UC (n=18) and non-IBD subjects (n=5) were collected. Whole biopsies were dissociated into single cells using collagenase digestion. Library preparation was done with 10x Genomics and sequencing was performed on an MGI2000 sequencer. Then, differential abundance, differential expression, and cell-cell interaction analyses were performed. Stainings for DUOX2 and HLA-DR were performed on paraffin embedded colon mucosal slides. Results In total, 71,798 high quality cells identified 54 distinct cell types, including a new type of epithelial cells: DUOX2+ enterocytes. DUOX2+ enterocytes are almost exclusively present in diseased inflamed colon and can act as antigen presenting cells through the expression of MHC2 on its surface. A general shift in cell type composition upon inflammation was observed, comparable between PSC and UC samples. However, an increased abundance was seen for stem cells in non-inflamed (NI) PSC, and not in UC-NI, compared to healthy controls. Additionally, we found distinct gene expression patterns between PSC and UC inflammation: while activation of inflammatory monocytes was observed in PSC inflammation, several types of fibroblasts were activated upon UC inflammation. Conclusion We describe DUOX2+ enterocytes, which may play a role in both PSC and UC colitis through antigen presentation. Furthermore, we show that intestinal inflammation in PSC-IBD, as compared to UC, is characterized by distinct mucosal cell composition and cell-specific gene expression patterns. PSC colitis, and not UC colitis, is driven by activation of inflammatory monocytes, with antigen presentation through HLA-DRB1, and activation of CD4+ T cells. Additionally, an increased abundance of stem cells in PSC-NI could be related with the increased colorectal cancer risk in PSC-IBD.

Based on Weighted Gene Co-Expression Network Analysis Reveals the Hub Immune Infiltration-Related Genes Associated with Ulcerative Colitis.

Immune infiltration plays a pivotal role in the pathogenesis of mucosal damage in ulcerative colitis (UC). The objective of this study was to systematically analyze and identify genetic characteristics associated with immune infiltration in UC. Gene expression data from three independent datasets obtained from the Gene Expression Omnibus (GEO) were utilized. By employing the ssGSEA and CIBERSORT algorithms, we estimated the extent of immune cell infiltration in UC samples. Subsequently, Weighted Correlation Network Analysis (WGCNA) was performed to identify gene modules exhibiting significant associations with immune infiltration, and further identification of hub genes associated with immune infiltration was accomplished using least absolute shrinkage and selection operator (LASSO) regression analysis. The relationship between the identified hub genes and clinical information was subsequently investigated. Our findings revealed significant activation of both innate and adaptive immune cells in UC. Notably, the expression levels of CD44, IL1B, LYN, and ITGA5 displayed strong correlations with immune cell infiltration within the mucosa of UC patients. Immunohistochemical analysis confirmed the significant upregulation of CD44, LYN, and ITGA5 in UC samples, and their expression levels were found to be significantly associated with common inflammatory markers, including the systemic immune inflammation indices, C-reactive protein, and erythrocyte sedimentation rate. CD44, LYN, and ITGA5 are involved in the immune infiltration pathogenesis of UC and may be potential therapeutic targets for UC.

Unveiling and Validating the Role of Fatty Acid Metabolism in Ulcerative Colitis.

Ulcerative colitis (UC) is a debilitating intestinal disorder that imposes a significant burden on those affected. Fatty acid metabolism plays a pivotal role in regulating immune cell function and maintaining internal homeostasis. This study investigates the biological and clinical significance of fatty acid metabolism within the context of UC. Gene expression profiles from patients with UC and healthy controls were retrieved, enabling the identification of differentially expressed genes (DEGs) specific to UC. These DEGs were then intersected with genes related to fatty acid metabolism, resulting in the identification of differentially expressed fatty acid metabolism-related genes (FAM-DEGs). Machine learning was employed to pinpoint key feature genes from the FAM-DEGs, which were subsequently used to construct a predictive UC model and to uncover molecular subtypes associated with fatty acid metabolism in UC. An animal model of UC was established using 3% dextran sulfate sodium (DSS) administration. Western blot analysis confirmed the expression levels of genes in intestinal tissues. The machine learning analysis identified three pivotal genes-ACAT1, ACOX2, and HADHB-culminating in a highly predictive nomogram. Consensus cluster analysis further categorized 637 UC samples into two distinct subgroups. The molecular subtypes related to fatty acid metabolism in UC exhibited significant differences in gene expression, biological activities, and enrichment pathways. Immune infiltration analysis highlighted elevated expression of two genes (excluding HADHB) in subtype 1, which corresponded with a marked increase in immune cell infiltration within this subtype. Western blot analysis demonstrated that ACAT1, ACOX2, and HADHB expression levels in the DSS group were significantly reduced, paralleling those observed in the normal group. This study highlights the critical role of specific fatty acid metabolism-related genes in UC, emphasizing their potential as targets for therapeutic intervention and shedding light on the underlying mechanisms of UC progression.

Identification of cuproptosis-related molecular classification and characteristic genes in ulcerative colitis

Ulcerative colitis (UC) is a refractory inflammatory disease with imbalances in intestinal mucosal homeostasis. Cuproptosis serves as newly identified programmed cell death (PCD) form involved in UC. In the study, UC-related datasets were extracted from the Gene Expression Omnibus (GEO) database. A comparison of UC patients and healthy controls identified 11 differentially expressed cuproptosis-related genes (DE-CRGs), where FDX1, LIAS, and DLAT were differentially expressed in UC groups from the mouse models and clinical samples, with their expression correlating with disease severity. By comprehending weighted gene co-expression network analysis (WGCNA) and differential expression analysis, the key genes common to the module genes relevant to different cuproptosis-related clusters and differentially expressed genes (DEGs) both in different clusters and patients with and without UC were identified using several bioinformatic analysis. Furthermore, the mRNA levels of four characteristic genes with diagnostic potential demonstrated significant decrease in both mouse models and clinical UC samples. Our discoveries offer a theoretical foundation for cuproptosis effect in UC.