Molecular Comparison of Adult and Pediatric Ulcerative Colitis Indicates Broad Similarity of Molecular Pathways in Disease Tissue

PANoptosis and Autophagy-Related Molecular Signature and Immune Landscape in Ulcerative Colitis: Integrated Analysis and Experimental Validation

Background

Ulcerative colitis (UC) is an autoimmune inflammatory disorder of the gastrointestinal tract. Programmed cell death (PCD), including PANoptosis and autophagy, plays roles in inflammation and immunity. This study aimed to investigate the molecular signature and immune landscape of the PANoptosis- and autophagy-related differentially expressed genes (DEGs) in UC.

Methods

Analyzing UC dataset GSE206285 yielded DEGs. Differentially expressed PANoptosis- and autophagy-related genes were identified using DEGs and relevant gene collections. Functional and pathway enrichment analyses were conducted. A protein-protein interaction (PPI) network was established to identify hub genes. TRRUST database predicted transcription factors (TFs), pivotal miRNAs, and drugs interacting with hub genes. Immune infiltration analysis, UC-associated single-cell sequencing data analysis, and construction of a competing endogenous RNA (ceRNA) network for hub genes were conducted. Machine learning identified key candidate genes, evaluated for diagnostic value via receiver operating characteristic (ROC) curves. A UC mice model verified expression of key candidate genes.

Results

Identifying ten PANoptosis-related hub DEGs and four autophagy-related hub DEGs associated them with cell chemotaxis, wound healing and positive MAPK cascade regulation. Immune infiltration analysis revealed increased immunocyte infiltration in UC patients, with hub genes closely linked to various immune cell infiltrations. Machine learning identified five key candidate genes, TIMP1, TIMP2, TIMP3, IL6, and CCL2, with strong diagnostic performance. At the single-cell level, these genes exhibited high expression in inflammatory fibroblasts (IAFs). They showed significant expression differences in the colon mucosa of both UC patients and UC mice model.

Conclusion

This study identified and validated novel molecular signatures associated with PANoptosis and autophagy in UC, potentially influencing immune dysregulation and wound healing, thus opening avenues for future research and therapeutic interventions.

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

Background

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.

Methods

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.

Results

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.

Conclusion

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.

Targeted delivery of the probiotic Saccharomyces boulardii to the extracellular matrix enhances gut residence time and recovery in murine colitis

Probiotic and engineered microbe-based therapeutics are an emerging class of pharmaceutical agents. They represent a promising strategy for treating various chronic and inflammatory conditions by interacting with the host immune system and/or delivering therapeutic molecules. Here, we engineered a targeted probiotic yeast platform wherein Saccharomyces boulardii is designed to bind to abundant extracellular matrix proteins found within inflammatory lesions of the gastrointestinal tract through tunable antibody surface display. This approach enabled an additional 24-48 h of probiotic gut residence time compared to controls and 100-fold increased probiotic concentrations within the colon in preclinical models of ulcerative colitis in female mice. As a result, pharmacodynamic parameters including colon length, colonic cytokine expression profiles, and histological inflammation scores were robustly improved and restored back to healthy levels. Overall, these studies highlight the potential for targeted microbial therapeutics as a potential oral dosage form for the treatment of inflammatory bowel diseases.

Biological characteristics of molecular subtypes of ulcerative colitis characterized by ferroptosis and neutrophil infiltration

Clinical ulcerative colitis (UC) is a heterogeneous condition. Moreover, medical interventions are nonspecific, and thus, treatment responses are inconsistent. The aim of this study was to explore the molecular subtypes and biological characteristics of UC based on ferroptosis and neutrophil gene sets. Multiple intestinal mucosa gene expression profiles of UC patients in the Gene Expression Omnibus (GEO) database were downloaded. Unsupervised clustering methods were used to identify potential molecular subtypes based on ferroptosis and neutrophil gene sets. Multiple immune infiltration algorithms were used to evaluate the biological characteristics of the molecular subtypes. Machine learning identifies hub genes for molecular subtypes and analyses their diagnostic efficacy for UC and predictive performance for drug therapy. The relevant conclusions were verified by clinical samples and animal experiments. Four molecular subtypes were identified according to the ferroptosis and neutrophil gene sets: neutrophil, ferroptosis, mixed and quiescent. The subtypes have different biological characteristics and immune infiltration levels. Multiple machine learning methods jointly identified four hub genes (FTH1, AQP9, STEAP3 and STEAP4). Receiver operating characteristic (ROC) curve analysis revealed that the four hub genes could be used as diagnostic markers for UC. The clinical response profile data of infliximab treatment patients showed that AQP9 and STEPA4 were reliable predictors of infliximab treatment response. In human samples the AQP9 and STEAP4 protein were shown to be increased in UC intestinal samples. In animal experiments, the ferroptosis and neutrophil phenotype were confirmed. Dual analysis of ferroptosis and neutrophil gene expression revealed four subgroups of UC patients. The molecular subtype-associated hub genes can be used as diagnostic markers for UC and predict infliximab treatment response.

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.

Construction of the underlying circRNA-miRNA-mRNA regulatory network and a new diagnostic model in ulcerative colitis by bioinformatics analysis

BACKGROUND

Circular RNAs (circRNAs) are involved in the pathogenesis of many diseases through competing endogenous RNA (ceRNA) regulatory mechanisms.

AIM

To investigate a circRNA-related ceRNA regulatory network and a new predictive model by circRNA to understand the diagnostic mechanism of circRNAs in ulcerative colitis (UC).

METHODS

We obtained gene expression profiles of circRNAs, miRNAs, and mRNAs in UC from the Gene Expression Omnibus dataset. The circRNA-miRNA-mRNA network was constructed based on circRNA-miRNA and miRNA-mRNA interactions. Functional enrichment analysis was performed to identify the biological mechanisms involved in circRNAs. We identified the most relevant differential circRNAs for diagnosing UC and constructed a new predictive nomogram, whose efficacy was tested with the C-index, receiver operating characteristic curve (ROC), and decision curve analysis (DCA).

RESULTS

A circRNA-miRNA-mRNA regulatory network was obtained, containing 12 circRNAs, three miRNAs, and 38 mRNAs. Two optimal prognostic-related differentially expressed circRNAs, hsa_circ_0085323 and hsa_circ_0036906, were included to construct a predictive nomogram. The model showed good discrimination, with a C-index of 1(> 0.9, high accuracy). ROC and DCA suggested that the nomogram had a beneficial diagnostic ability.

CONCLUSION

This novel predictive nomogram incorporating hsa_circ_0085323 and hsa_circ_0036906 can be conveniently used to predict the risk of UC. The circRNa-miRNA-mRNA network in UC could be more clinically significant.

Identification of potential crucial genes shared in psoriasis and ulcerative colitis by machine learning and integrated bioinformatics

BACKGROUND

Mounting evidence suggest that there are an association between psoriasis and ulcerative colitis (UC), although the common pathogeneses are not fully understood. Our study aimed to find potential crucial genes in psoriasis and UC through machine learning and integrated bioinformatics.

METHODS

The overlapping differentially expressed genes (DEGs) of the datasets GSE13355 and GSE87466 were identified. Then the functional enrichment analysis was performed. The overlapping genes in LASSO, SVM-RFE and key module in WGCNA were considered as potential crucial genes. The receiver operator characteristic (ROC) curve was used to estimate their diagnostic confidence. The CIBERSORT was conducted to evaluate immune cell infiltration. Finally, the datasets GSE30999 and GSE107499 were retrieved to validate.

RESULTS

112 overlapping DEGs were identified in psoriasis and UC and the functional enrichment analysis revealed they were closely related to the inflammatory and immune response. Eight genes, including S100A9, PI3, KYNU, WNT5A, SERPINB3, CHI3L2, ARNTL2, and SLAMF7, were ultimately identified as potential crucial genes. ROC curves showed they all had high confidence in the test and validation datasets. CIBERSORT analysis indicated there was a correlation between infiltrating immune cells and potential crucial genes.

CONCLUSION

In our study, we focused on the comprehensive understanding of pathogeneses in psoriasis and UC. The identification of eight potential crucial genes may contribute to not only understanding the common mechanism, but also identifying occult UC in psoriasis patients, even serving as therapeutic targets in the future.

Comprehensive Analysis of PANoptosis-Related Gene Signature of Ulcerative Colitis

Accumulating evidence shows that the abnormal increase in the mortality of intestinal epithelial cells (IECs) caused by apoptosis, pyroptosis, and necroptosis is closely related to the function of mucous membrane immunity and barrier function in patients with ulcerative colitis (UC). As a procedural death path that integrates the above-mentioned many deaths, the role of PANoptosis in UC has not been clarified. This study aims to explore the characterization of PANoptosis patterns and determine the potential biomarkers and therapeutic targets. We constructed a PANoptosis gene set and revealed significant activation of PANoptosis in UC patients based on multiple transcriptome profiles of intestinal mucosal biopsies from the GEO database. Comprehensive bioinformatics analysis revealed five key genes (ZBP1, AIM2, CASP1/8, IRF1) of PANoptosome with good diagnostic value and were highly correlated with an increase in pro-inflammatory immune cells and factors. In addition, we established a reliable ceRNA regulatory network of PANoptosis and predicted three potential small-molecule drugs sharing calcium channel blockers that were identified, among which flunarizine exhibited the highest correlation with a high binding affinity to the targets. Finally, we used the DSS-induced colitis model to validate our findings. This study identifies key genes of PANoptosis associated with UC development and hypothesizes that IRF1 as a TF promotes PANoptosome multicomponent expression, activates PANoptosis, and then induces IECs excessive death.

1,25(OH)2D3 alleviates oxidative stress and inflammation through up-regulating HMGCS2 in DSS-induced colitis

BACKGROUND

Previous study found that supplements with active vitamin D3 alleviated experimental colitis. The objective of this study was to investigate the possible role of 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2), a ketone synthase, on vitamin D3 protecting against experimental colitis.

METHODS

HMGCS2 and vitamin D receptor (VDR) were measured in UC patients. The effects of vitamin D deficiency (VDD) and exogenous 1,25(OH)2D3 supplementation on experimental colitis were investigated in dextran sulfate sodium (DSS)-treated mice. DSS-induced oxidative stress and inflammation were analyzed in HT-29 cells. HMGCS2 was detected in 1,25(OH)2D3-pretreated HT-29 cells and mouse intestines. HMGCS2 was silenced to investigate the role of HMGCS2 in 1,25(OH)2D3 protecting against experimental colitis.

RESULTS

Intestinal HMGCS2 downregulation was positively correlated with VDR reduction in UC patients. The in vivo experiments showed that VDD exacerbated DSS-induced colitis. By contrast, 1,25(OH)2D3 supplementation ameliorated DSS-induced colon damage, oxidative stress and inflammation. HMGCS2 was up-regulated after 1,25(OH)2D3 supplementation both in vivo and in vitro. Transfection with HMGCS2-siRNA inhibited antioxidant and anti-inflammatory effects of 1,25(OH)2D3 in DSS-treated HT-29 cells.

CONCLUSION

1,25(OH)2D3 supplementation up-regulates HMGCS2, which is responsible for 1,25(OH)2D3-mediated protection against oxidative stress and inflammation in DSS-induced colitis. These findings provide a potential therapeutic strategy for alleviating colitis-associated oxidative stress and inflammation.

Single-cell dissection, hdWGCNA and deep learning reveal the role of oxidatively stressed plasma cells in ulcerative colitis

Ulcerative colitis (UC) develops as a result of complex interactions between various cell types in the mucosal microenvironment. In this study, we aim to elucidate the pathogenesis of ulcerative colitis at the single-cell level and unveil its clinical significance. Using single-cell RNA sequencing and high-dimensional weighted gene co-expression network analysis, we identify a subpopulation of plasma cells (PCs) with significantly increased infiltration in UC colonic mucosa, characterized by pronounced oxidative stress. Combining 10 machine learning approaches, we find that the PC oxidative stress genes accurately distinguish diseased mucosa from normal mucosa (independent external testing AUC=0.991, sensitivity=0.986, specificity=0.909). Using MCPcounter and non-negative matrix factorization, we identify the association between PC oxidative stress genes and immune cell infiltration as well as patient heterogeneity. Spatial transcriptome data is used to verify the infiltration of oxidatively stressed PCs in colitis. Finally, we develop a gene-immune convolutional neural network deep learning model to diagnose UC mucosa in different cohorts (independent external testing AUC=0.984, sensitivity=95.9%, specificity=100%). Our work sheds light on the key pathogenic cell subpopulations in UC and is essential for the development of future clinical disease diagnostic tools.

Single-Cell RNA-Sequencing Analysis of Colonic Lamina Propria Immune Cells Reveals the Key Immune Cell-Related Genes of Ulcerative Colitis

Background

Ulcerative colitis (UC) is a severe threat to humans worldwide. Single-cell RNA sequencing (scRNA-seq) can be used to screen gene expression patterns of each cell in the intestine, provide new insights into the potential mechanism of UC, and analyze the development of immune cell changes. These findings can provide new ideas for the diagnosis and treatment of intestinal diseases. In this study, bioinformatics analysis combined with experiments applied in dextran sulfate sodium (DSS)-induced colitis mice was used to explore new diagnostic genes for UC and their potential relationship with immune cells.

Methods

We downloaded microarray datasets (GSE75214, GSE87473, GSE92415) from the Gene Expression Omnibus and used these datasets to screen differentially expressed genes (DEGs) and conduct Weighted Gene Co-expression Network Analysis (WGCNA) after quality control. The hub genes were screened, and ROC curves were drawn to verify the reliability of the results in both training set (GSE75214, GSE87473, GSE92415) and validation cohort (GSE87466). Also, we explored the relation of diagnostic genes and immune cells by CIBERSORT algorithm and single-cell analysis. Finally, the expression of hub genes and their relation with immune cells were verified in DSS-induced colitis mice.

Results

Diagnostic genes (ANXA5, MMP7, NR1H4, CYP3A4, ABCG2) were identified. In addition, we found these five genes firmly related to immune infiltration. The DSS-induced colitis mice confirm that the expression of ANXA5 mainly increased in the intestinal macrophages and had a strong negative correlation with M2 macrophages, which indicated its possible influence on the polarization of macrophages in UC patients.

Conclusion

We identified ANXA5, MMP7, NR1H4, CYP3A4, and ABCG2 as diagnostic genes of UC that are closely related to immune infiltration and ANXA5 maintains a negative correlation with M2 macrophages which indicated its possible influence on the polarization of macrophage in UC patients.

Identifying Macrophage-Related Genes in Ulcerative Colitis Using Weighted Coexpression Network Analysis and Machine Learning

Ulcerative colitis (UC) is an inflammatory bowel disease of unknown cause that typically affects the colon and rectum. Innate intestinal immunity, including macrophages, plays a significant role in the pathological development of UC. Using the CIBERSORT algorithm, we observed elevated levels of 22 types of immune cell infiltrates, as well as increased M1 and decreased M2 macrophages in UC compared to normal colonic mucosa. Weighted gene coexpression network analysis (WGCNA) was used to identify modules associated with macrophages and UC, resulting in the identification of 52 macrophage-related genes (MRGs) that were enriched in macrophages at single-cell resolution. Consensus clustering based on these 52 MRGs divided the integrated UC cohorts into three subtypes. Machine learning algorithms were used to identify ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1), sodium- and chloride-dependent neutral and basic amino acid transporter B(0+) (SLC6A14), and 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2) in the training set, and their diagnostic value was validated in independent validation sets. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) revealed the main biological effects, and that interleukin-17 was one of several signaling pathways enriched by the three genes. We also constructed a competitive endogenous RNA (CeRNA) network reflecting a potential posttranscriptional regulatory mechanism. Expression of diagnostic markers was validated in vivo and in biospecimens, and our immunohistochemistry (IHC) results confirmed that HMGCS2 gradually decreased during the transformation of UC to colorectal cancer. In conclusion, ENPP1, SLC6A14, and HMGCS2 are associated with macrophages and the progression of UC pathogenesis and have good diagnostic value for patients with UC.

Embelin targets PI3K/AKT and MAPK in age-related ulcerative colitis: an integrated approach of microarray analysis, network pharmacology, molecular docking, and molecular dynamics

Vaibhdang, an Ayurvedic treatment for Crohn's and UC, has been used for centuries. The main component of Vaibhdang is embelin derived from Embelia ribes. However, the pharmacological and molecular mechanisms of embelin in UC remain unclear. This study investigated the molecular targets and mechanisms of action of embelin in UC using microarray analysis, network pharmacology, molecular docking, and molecular dynamics simulations. Embelin targets were obtained by Swiss Target, TargetNet, STITCH, ChEMBL, and TCMSP. Ulcerative colitis targets were mapped using DisGenNET, Genecards, TCMSP, Therapeutic targets, and GEO databases (GSE87466). Co-targets between ulcerative colitis and embelin were identified, and a PPI network was constructed using the STRING database. To identify the core targets, we used Cytoscape to analyze the topology of the PPI network. There were 545 effective Embelin targets and 5171 effective ulcerative colitis targets, including 1470 DEG targets. ShinyGo and AutoDock were used to analyze GO and KEGG enrichment pathways and docking studies, respectively. Venn diagram analysis revealed 327 core targets of embelin in UC. An enrichment study showed that embelin is involved in PI3K-AKT, MAPK, RAS, and chemokine signalling. The top ten core targets docked with embelin and AKT1, MAPK1, and SRC complexes were utilized as representations and simulated using GROMACS for 100 ns. A comparison of native proteins and their complex interactions with embelin revealed that embelin might act on various PI3K/AKT and MAPK targets to treat ulcerative colitis. This study provides insights into the molecular targets and mechanisms of action of embelin against ulcerative colitis.Communicated by Ramaswamy H. Sarma.

Identifying Crucial Biomarkers in Osteoporosis and Ulcerative Colitis Through Bioinformatics Analysis of Co-expressed Genes

Osteoporosis (OP) and ulcerative colitis (UC), prevalent immune diseases, exert a substantial socioeconomic impact globally. This study identifies biomarkers for these diseases, paving the way for in-depth research. Initially, the Gene Expression Omnibus (GEO) database was employed to analyze datasets GSE35958 and GSE87466. This analysis aimed to pinpoint co-expression differential genes (DEGs) between OP and UC. Subsequently, the Metascape database facilitated the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of these DEGs' co-expression. For network construction and visualization, the STRING11.5 database along with Cytoscape 3.7.2 (Cytoscape Team, USA) were utilized to create a protein-protein interaction (PPI) network. Moreover, Cytoscape's cytoHubba plugin was instrumental in identifying the central genes, known as hub genes. In the datasets GSE35958 and GSE87466, 156 co-expressed DEGs were discovered. The PPI network, constructed using STRING11.5 and Cytoscape 3.7.2, comprises 96 nodes and 222 connections. Notably, seven hub genes were identified, namely COL6A1, COL6A2, BGN, NID1, PLAU, TGFB1, and PLAUR. These DEGs were predominantly enriched in pathways such as extracellular matrix organization and collagen-containing extracellular matrix, as per GO analysis. For diagnostic model construction and hub gene validation, datasets GSE56815 and GSE107499 from the GEO database were employed. The top five hub genes were validated. In conclusion, the hub genes identified in this study played a significant role in the early diagnosis, prevention, and treatment of OP and UC. Furthermore, they provide fresh insights into the underlying mechanisms of these diseases' development and progression.

The State of Clinical Trials in Pediatric Inflammatory Bowel Disease

The gap between available biologic and small molecule therapy for inflammatory bowel disease for children and adults remains large. At present only 2 anti-TNF agents are licensed for pediatric use compared with multiple other agents with different mechanisms of action being used in adults. The reasons are many but largely revolve around the inadequate acceptance of adult efficacy data to children, and the reluctance of industry to commit to early pediatric drug development for fear of inadequate return on investment. We suggest common sense steps that need to be taken to improve this situation.

Uncovering the shared molecule and mechanism between ulcerative colitis and atherosclerosis: an integrative genomic analysis

Background

Ulcerative colitis (UC) and atherosclerosis (AS) are closely related. However, the pathologic mechanisms underlying the co-occurrence of UC and AS are not well understood.

Objects

To reveal the hub molecule and mechanism involved in the co-occurrence of UC and AS.

Methods

Differentially expressed genes (DEGs) of UC and AS were obtained, and the shared DEGs of UC and AS were explored for biological function. Next, the hub genes were explored using the cytoHubba plugin. The predictive ability of the hub genes was measured by constructing the receiver operating characteristic curve. Analyses of immune infiltration and the single-gene gene set enrichment analysis (GSEA) for the hub genes were further carried out.

Results

Identification of 59 DEGs (55 were upregulated and four were downregulated) shared by both UC and AS was performed. Enriched pathways of the shared DEGs were mainly related to immunity and inflammation. Protein tyrosine phosphatase, receptor type, C (PTPRC) was identified as the hub crosstalk gene for the comorbidity of UC and AS. The upregulation of PTPRC was correlated with mast cells resting, T cells CD4 memory resting, macrophages M0, and macrophages M1. Pathways of immune and inflammatory processes, including NF-kappa B, viral protein interaction with cytokine and cytokine receptor, and cytokine-cytokine receptor interaction, were significantly correlated with high expression of PTPRC in UC and AS.

Conclusion

At the transcriptional level, our study reveals that imbalanced inflammatory and immune responses are the key pathological mechanisms underlying the comorbidity of UC and AS and that PTPRC is a key biomarker for the comorbidity of UC and AS.

Identification of genes critical for inducing ulcerative colitis and exploring their tumorigenic potential in human colorectal carcinoma

Ulcerative colitis (UC) is a chronic relapsing inflammatory bowel disease leading to continuous mucosal inflammation in the rectum extending proximally towards the colon. Chronic and/or recurrent UC is one of the critical predisposing mediators of the oncogenesis of human colorectal carcinoma (CRC). Perturbations of the differential expression of the UC-critical genes exert an intense impact on the neoplastic transformation of the affected tissue(s). Herein, a comprehensive exploration of the UC-critical genes from the transcriptomic profiles of UC patients was conducted to study the differential expression, functional enrichment, genomic alterations, signal transduction pathways, and immune infiltration level encountered by these genes concerning the oncogenesis of CRC. The study reveals that WFDC2, TTLL12, THRA, and EPHB3 play crucial roles as UC-CRC critical genes and are positively correlated with the molecular transformation of UC to CRC. Taken together, these genes can be used as potential biomarkers and therapeutic targets for combating UC-induced human CRC.

Analysis of cuproptosis-related genes in Ulcerative colitis and immunological characterization based on machine learning

Cuproptosis is a novel form of cell death, mediated by protein lipid acylation and highly associated with mitochondrial metabolism, which is regulated in the cell. Ulcerative colitis (UC) is a chronic inflammatory bowel disease that recurs frequently, and its incidence is increasing worldwide every year. Currently, a growing number of studies have shown that cuproptosis-related genes (CRGs) play a crucial role in the development and progression of a variety of tumors. However, the regulatory role of CRGs in UC has not been fully elucidated. Firstly, we identified differentially expressed genes in UC, Likewise, CRGs expression profiles and immunological profiles were evaluated. Using 75 UC samples, we typed UC based on the expression profiles of CRGs, followed by correlative immune cell infiltration analysis. Using the weighted gene co-expression network analysis (WGCNA) methodology, the cluster's differentially expressed genes (DEGs) were produced. Then, the performances of extreme gradient boosting models (XGB), support vector machine models (SVM), random forest models (RF), and generalized linear models (GLM) were constructed and predicted. Finally, the effectiveness of the best machine learning model was evaluated using five external datasets, receiver operating characteristic curve (ROC), the area under the curve of ROC (AUC), a calibration curve, a nomogram, and a decision curve analysis (DCA). A total of 13 CRGs were identified as significantly different in UC and control samples. Two subtypes were identified in UC based on CRGs expression profiles. Immune cell infiltration analysis of subtypes showed significant differences between immune cells of different subtypes. WGCNA results showed a total of 8 modules with significant differences between subtypes, with the turquoise module being the most specific. The machine learning results showed satisfactory performance of the XGB model (AUC = 0.981). Finally, the construction of the final 5-gene-based XGB model, validated by the calibration curve, nomogram, decision curve analysis, and five external datasets (GSE11223: AUC = 0.987; GSE38713: AUC = 0.815; GSE53306: AUC = 0.946; GSE94648: AUC = 0.809; GSE87466: AUC = 0.981), also proved to predict subtypes of UC with accuracy. Our research presents a trustworthy model that can predict the likelihood of developing UC and methodically outlines the complex relationship between CRGs and UC.

A precise molecular subtyping of ulcerative colitis reveals the immune heterogeneity and predicts clinical drug responses

BACKGROUND AND AIMS

We sought to identify novel molecular subtypes of ulcerative colitis (UC) based on large-scale cohorts and establish a clinically applicable subtyping system for the precision treatment of the disease.

METHODS

Eight microarray profiles containing colon samples from 357 patients were utilized. Expression heterogeneity was screened out and stable subtypes were identified among UC patients. Immune infiltration pattern and biological agent response were compared among subtypes to assess the value in guiding treatment. The relationship between PRLR and TNFSF13B genes with the highest predictive value was further validated by functional experiments.

RESULTS

Three stable molecular subtypes were successfully identified. Immune cell infiltration analysis defined three subtypes as innate immune activated UC (IIA), whole immune activated UC (WIA), and immune homeostasis like UC (IHL). Notably, the response rate towards biological agents (infliximab/vedolizumab) in WIA patients was the lowest (less than 10%), while the response rate in IHL patients was the highest, ranging from 42 to 60%. Among the featured genes of subtypes, the ratio of PRLR to TNFSF13B could effectively screen for IHL UC subtype suitable for biological agent therapies (Area under curve: 0.961-0.986). Furthermore, we demonstrated that PRLR expressed in epithelial cells could inhibit the expression of TNFSF13B in monocyte-derived macrophages through the CXCL1-NF-κB pathway.

CONCLUSIONS

We identified three stable UC subtypes with a heterogeneous immune pattern and different response rates towards biological agents for the first time. We also established a precise molecular subtyping system and classifier to predict clinical drug response and provide individualized treatment strategies for UC patients.

Polysaccharides from Paecilomyces hepiali Prevent Acute Colitis in Association with Modulating Gut Microbiota and Treg/Th17 Immune Balance in Mice

Cordyceps exopolysaccharide (CEP) has shown emerging potential in adjustment of gut microbiota and immune cell function. In this study, a water-soluble CEP with a molecular weight of 58.14 kDa was extracted from the fermentation broth of Paecilomyces hepiali, an endophytic fungus of Cordyceps sinensis. Our results indicated that Paecilomyces hepiali polysaccharide (PHP) showed significantly preventive potential on dextran sulfate sodium (DSS)-induced colitis in mice, which can prevent colon shortening, reduce intestinal epithelial cell (IEC) destruction, suppress inflammatory cell infiltration, and regulate the balance between regulatory T (Treg) cells and T helper type 17 (Th17) cells. Meanwhile, the disturbed gut microbiota was partially restored after PHP treatment. Further Pearson correlation coefficient analyses exhibited that the alteration of the gut microbiota was significantly related to adjustment of the IEC barrier and Treg/Th17 balance. In conclusion, all findings proposed that purified PHP has the potential to develop into a promising agent for colitis prevention and adjuvant therapy via maintaining intestinal homeostasis of gut microbiota and immune system.

Cross talk between bacterial and human gene networks enriched using ncRNAs in IBD disease

Inflammatory bowel disease (IBD) is a long-term inflammatory immune-mediated gut illness with several extra-intestinal complications. The aims of this study were to identify a novel network-based meta-analysis approach on the basis of the combinations of the differentially expressed genes (DEGs) from microarray data, to enrich the functional modules from human protein-protein interaction (PPI) and gene ontology (GO) data, and to profile the ncRNAs on the genes involved in IBD. The gene expression profiles of GSE126124, GSE87473, GSE75214, and GSE95095 are obtained from the Gene Expression Omnibus (GEO) database based on the study criteria between 2017 and 2022. The DEGs were screened by the R software. DEGs were then used to examine gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The ncRNAs including the miRNAs and ceRNAs were predicted on the PPIs visualized using Cytoscape. Enrichment analysis of genes with differential expression (n = 342) using KEGG and GO showed that the signaling pathways related with staphylococcus aureus and pertussis bacterial infections may stimulate the immune system and exacerbate IBD via the interaction with human proteins including Fibrinogen gamma chain (FGG), Keratin 10 (KRT10), and Toll like receptor 4 (TLR4). By building a ceRNA network, lncRNA XIST and NEAT1 were determined by affecting common miRNAs, hsa-miR-6875-5p, hsa-miR-1908-5p, hsa-miR-186-5p, hsa-miR-6763-5p, hsa-miR-4436a, and hsa-miR-520a-5p. Additionally, the chromosome regions including NM_001039703 and NM_006267, which produce the most potent circRNAs play a significant role in the ceRNA network of IBD. Also, we predicted the siRNAs that would be most effective against the bacterial genes in staphylococcus aureus and pertussis infections. These findings suggested that three genes (FGG, KRT10, and TLR4), six miRNAs (hsa-miR-6875-5p, hsa-miR-1908-5p, hsa-miR-186-5p, hsa-miR-4436a, hsa-miR-520a-5p, and hsa-miR-6763-5p), two lncRNAs (XIST and NEAT1), and chromosomal regions including NM_001039703 and NM_006267 with the production of the most effective circRNAs are involved in the ncRNA-associated ceRNA network of IBD. These ncRNA profiles are related to the described gene functions and may play therapeutic targets in controlling inflammatory bowel disease.

Protein stabilization of ITF2 by NF-κB prevents colitis-associated cancer development

Chronic colonic inflammation is a feature of cancer and is strongly associated with tumorigenesis, but its underlying molecular mechanisms remain poorly understood. Inflammatory conditions increased ITF2 and p65 expression both ex vivo and in vivo, and ITF2 and p65 showed positive correlations. p65 overexpression stabilized ITF2 protein levels by interfering with the binding of Parkin to ITF2. More specifically, the C-terminus of p65 binds to the N-terminus of ITF2 and inhibits ubiquitination, thereby promoting ITF2 stabilization. Parkin acts as a E3 ubiquitin ligase for ITF2 ubiquitination. Intestinal epithelial-specific deletion of ITF2 facilitated nuclear translocation of p65 and thus increased colitis-associated cancer tumorigenesis, which was mediated by Azoxymethane/Dextran sulfate sodium or dextran sulfate sodium. Upregulated ITF2 expression was lost in carcinoma tissues of colitis-associated cancer patients, whereas p65 expression much more increased in both dysplastic and carcinoma regions. Therefore, these findings indicate a critical role for ITF2 in the repression of colitis-associated cancer progression and ITF2 would be an attractive target against inflammatory diseases including colitis-associated cancer.

Identification of cuproptosis hub genes contributing to the immune microenvironment in ulcerative colitis using bioinformatic analysis and experimental verification

Instruction

Ulcerative colitis (UC) can cause a variety of immune-mediated intestinal dysfunctions and is a significant model of inflammatory bowel disease (IBD). Colorectal cancer (CRC) mostly occurs in patients with ulcerative colitis. Cuproptosis is a type of procedural death that is associated with different types of diseases to various degrees.

Methods

We used a combination of bioinformatic prediction and experimental verification to study the correlation between copper poisoning and UC. We used the Gene Expression Omnibus database to obtain disease gene expression data and then identified relevant genes involved in various expression levels in normal and UC samples. The Kyoto Encyclopedia of Genes and Genomes pathway analysis was performed to cluster the genes that are highly responsible and find the central interaction in gene crosstalk. Notably, DLD, DLAT, and PDHA1 were present in high-scoring PPI networks. In addition, hub gene expression information in UC tissues was integrated to estimate the relationship between UC copper poisoning and the immune environment.

Results

In our study, the expression of DLD, DLAT, and PDHA1 in UC tissues was lower than that in normal tissues. The key genes associated with cuproptosis have therapeutic effects on immune infiltration. We verified the expression of DLD, DLAT, and PDHA1 using real-time quantitative polymerase chain reaction in mouse models of UC induced by DSS.

Discussion

Notably, this study clearly indicates that bioinformatic analysis performed to verify the experimental methods provides evidence that cuproptosis is associated with UC. This finding suggests that immune cell infiltration in UC patients is associated with cuproptosis. The key genes associated with cuproptosis can be helpful for discovering the molecular mechanism of UC, thus facilitating the improvement of UC treatment and preventing the associated CRC.

Identification of cuproptosis-associated subtypes and signature genes for diagnosis and risk prediction of Ulcerative colitis based on machine learning

Background

Ulcerative colitis (UC) is a chronic and debilitating inflammatory bowel disease that impairs quality of life. Cuproptosis, a recently discovered form of cell death, has been linked to many inflammatory diseases, including UC. This study aimed to examine the biological and clinical significance of cuproptosis-related genes in UC.

Methods

Three gene expression profiles of UC were obtained from the Gene Expression Omnibus (GEO) database to form the combined dataset. Differential analysis was performed based on the combined dataset to identify differentially expressed genes, which were intersected with cuproptosis-related genes to obtain differentially expressed cuproptosis-related genes (DECRGs). Machine learning was conducted based on DECRGs to identify signature genes. The prediction model of UC was established using signature genes, and the molecular subtypes related to cuproptosis of UC were identified. Functional enrichment analysis and immune infiltration analysis were used to evaluate the biological characteristics and immune infiltration landscape of signature genes and molecular subtypes.

Results

Seven signature genes (ABCB1, AQP1, BACE1, CA3, COX5A, DAPK2, and LDHD) were identified through the machine learning algorithms, and the nomogram built from these genes had excellent predictive performance. The 298 UC samples were divided into two subtypes through consensus cluster analysis. The results of the functional enrichment analysis and immune infiltration analysis revealed significant differences in gene expression patterns, biological functions, and enrichment pathways between the cuproptosis-related molecular subtypes of UC. The immune infiltration analysis also showed that the immune cell infiltration in cluster A was significantly higher than that of cluster B, and six of the characteristic genes (excluding BACE1) had higher expression levels in subtype B than in subtype A.

Conclusions

This study identified several promising signature genes and developed a nomogram with strong predictive capabilities. The identification of distinct subtypes of UC enhances our current understanding of UC's underlying pathogenesis and provides a foundation for personalized diagnosis and treatment in the future.

Identification of gene signatures associated with ulcerative colitis and the association with immune infiltrates in colon cancer

Background

Inflammatory bowel diseases, including ulcerative colitis (UC) and Crohn's disease, are some of the most common inflammatory disorders of the gastrointestinal tract. The dysfunction of the immune system in the intestines is suggested to be the underlying cause of the pathogenesis of UC. However, the mechanisms regulating these dysfunctional immune cells and inflammatory phenotypes are still unclear.

Methods

The differential expression analysis on microarray datasets were performed including GSE24287, GSE87466, GSE102133, and GSE107499, including 376 samples. "Gene Ontology" and "Kyoto Encyclopedia of Genes and Genomes" pathway enrichment analyses were conducted to identify the common differentially expressed genes (DEGs) in these datasets and explore their underlying biological mechanisms. Further algorithms like "Cell-type Identification by Estimating Relative Subsets of RNA Transcripts" were used to determine the infiltration status of immune cells in patients with UC. "Cytoscape" and "Gene Set Enrichment Analysis" were used to screen for hub genes and to investigate their biological mechanisms. The Tumor Immune Estimation Resource database was used to study the correlation between hub genes and infiltrating immune cells in patients with UC. A total of three hub genes, CCL3, MMP3, and TIMP1, were identified using Cytoscape.

Results

A positive correlation was observed between these hub genes and patients with active UC. These genes served as a biomarker for active UC. Moreover, a decrease in CCL3, MMP3, and TIMP1 expression was observed in the mucosa of the intestine of patients with active UC who responded to Golimumab therapy. In addition, results show a significant positive correlation between CCL3, MMP3, and TIMP1 expression and different immune cell types including dendritic cells, macrophages, CD8+ T cells, and neutrophils in patients with colon cancer. Moreover, CCL3, MMP3, and TIMP1 expression were strongly correlated with different immune cell markers.

Conclusion

Study results show the involvement of hub genes like CCL3, MMP3, and TIMP1 in the pathogenesis of UC. These genes could serve as a novel pharmacological regulator of UC. These could be used as a therapeutic target for treating patients with UC and may serve as biomarkers for immune cell infiltration in colon cancer.

Increased stromal PFKFB3-mediated glycolysis in inflammatory bowel disease contributes to intestinal inflammation

Inflammatory bowel disease (IBD) is a chronic relapsing inflammation of the intestinal tract with currently not well-understood pathogenesis. In addition to the involvement of immune cells, increasing studies show an important role for fibroblasts in the pathogenesis of IBD. Previous work showed that glycolysis is the preferred energy source for fibroblasts in fibrotic diseases. 6-phosphofructo-2-kinase/fructose-2, 6-bisphosphatase 3 (PFKFB3) is a key kinase supporting glycolysis. Increased expression of PFKFB3 in several cancers and inflammatory diseases has been previously reported, but the metabolic status of fibroblasts and the role of PFKFB3 in patients with IBD are currently unknown. Therefore, in this study, we evaluated the role of glycolysis and PFKFB3 expression in IBD. Single-sample gene set enrichment analysis (ssGSEA) revealed that glycolysis was significantly higher in IBD intestinal samples, compared to healthy controls, which was confirmed in the validation cohorts of IBD patients. Single-cell sequencing data indicated that PFKFB3 expression was higher in IBD-derived stromal cells. In vitro, PFKFB3 expression in IBD-derived fibroblasts was increased after the stimulation with pro-inflammatory cytokines. Using seahorse real-time cell metabolic analysis, inflamed fibroblasts were shown to have a higher extracellular acidification rate and a lower oxygen consumption rate, which could be reversed by inhibition of JAK/STAT pathway. Furthermore, increased expression of pro-inflammatory cytokines and chemokines in fibroblasts could be reverted by PFK15, a specific inhibitor of PFKFB3. In vivo experiments showed that PFK15 reduced the severity of dextran sulfate sodium (DSS)- and Tcell transfer induced colitis, which was accompanied by a reduction in immune cell infiltration in the intestines. These findings suggest that increased stromal PFKFB3 expression contributes to inflammation and the pathological function of fibroblasts in IBD. Inhibition of PFKFB3 suppressed their inflammatory characteristics.

Identification and exploration of pharmacological pyroptosis-related biomarkers of ulcerative colitis

Ulcerative colitis (UC) is a chronic inflammatory bowel disease (IBD). Its etiology is unclear. Much evidence suggests that the death of abnormal intestinal epithelial cells (IECs) leads to intestinal barrier disruption, and the subsequent inflammatory response plays a vital role in UC. Pyroptosis is a form of programmed inflammatory cell death, and the role of pyroptosis in UC etiology remains to be explored. This study identified 10 hub genes in pyroptosis by gene expression profiles obtained from the GSE87466 dataset. Meanwhile, the biomarkers were screened based on gene significance (GS) and module membership (MM) through the Weighted Gene Co-Expression Network Analysis (WGCNA). The following analysis indicated that hub genes were closely associated with the UC progression and therapeutic drug response. The single-cell RNA (scRNA) sequencing data from UC patients within the GSE162335 dataset indicated that macrophages were most related to pyroptosis. Finally, the expression of hub genes and response to the therapeutic drug [5-aminosalicylic acid (5-ASA)] were verified in dextran sulfate sodium (DSS)-induced colitis mice. Our study identified IL1B as the critical pyroptosis-related biomarker in UC. The crosstalk between macrophage pyroptosis and IEC pyroptosis may play an essential role in UC, deserving further exploration.

Molecular Network Analyses Implicate Death-Associated Protein Kinase 3 (DAPK3) as a Key Factor in Colitis-Associated Dysplasia Progression

BACKGROUND

Ulcerative colitis (UC) is a progressive disorder that elevates the risk of colon cancer development through a colitis-dysplasia-carcinoma sequence. Gene expression profiling of colitis-associated lesions obtained from patients with varied extents of UC can be mined to define molecular panels associated with colon cancer development.

METHODS

Differential gene expression profiles of 3 UC clinical subtypes and healthy controls were developed for the GSE47908 microarray data set of healthy controls, left-sided colitis, pancolitis, and colitis-associated dysplasia (CAD) using limma R.

RESULTS

A gene ontology enrichment analysis of differentially expressed genes (DEGs) revealed a shift in the transcriptome landscape as UC progressed from left-sided colitis to pancolitis to CAD, from being immune-centric to being cytoskeleton-dependent. Hippo signaling (via Yes-associated protein [YAP]) and Ephrin receptor signaling were the top canonical pathways progressively altered in concert with the pathogenic progression of UC. A molecular interaction network analysis of DEGs in left-sided colitis, pancolitis, and CAD revealed 1 pairwise line, or edge, that was topologically important to the network structure. This edge was found to be highly enriched in actin-based processes, and death-associated protein kinase 3 (DAPK3) was a critical member and sole protein kinase member of this network. Death-associated protein kinase 3 is a regulator of actin-cytoskeleton reorganization that controls proliferation and apoptosis. Differential correlation analyses revealed a negative correlation for DAPK3-YAP in healthy controls that flipped to positive in left-sided colitis. With UC progression to CAD, the DAPK3-YAP correlation grew progressively more positive.

CONCLUSION

In summary, DAPK3 was identified as a candidate gene involved in UC progression to dysplasia.

Identification of Immune-Related Gene Signature and Prediction of CeRNA Network in Active Ulcerative Colitis

Background

Ulcerative colitis (UC) is an inflammatory disease of the intestinal mucosa, and its incidence is steadily increasing worldwide. Intestinal immune dysfunction has been identified as a central event in UC pathogenesis. However, the underlying mechanisms that regulate dysfunctional immune cells and inflammatory phenotype remain to be fully elucidated.

Methods

Transcriptome profiling of intestinal mucosa biopsies were downloaded from the GEO database. Robust Rank Aggregation (RRA) analysis was performed to identify statistically changed genes and differentially expressed genes (DEGs). Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to explore potential biological mechanisms. CIBERSORT was used to evaluate the proportion of 22 immune cells in biopsies. Weighted co-expression network analysis (WGCNA) was used to determine key module-related clinical traits. Protein-Protein Interaction (PPI) network and Cytoscape were performed to explore protein interaction network and screen hub genes. We used a validation cohort and colitis mouse model to validate hub genes. Several online websites were used to predict competing endogenous RNA (ceRNA) network.

Results

RRA integrated analysis revealed 1838 statistically changed genes from four training cohorts (adj. p-value < 0.05). GSEA showed that statistically changed genes were enriched in the innate immune system. CIBERSORT analysis uncovered an increase in activated dendritic cells (DCs) and M1 macrophages. The red module of WGCNA was considered the most critical module related to active UC. Based on the results of the PPI network and Cytoscape analyses, we identified six critical genes and transcription factor NF-κB. RT-PCR revealed that andrographolide (AGP) significantly inhibited the expression of hub genes. Finally, we identified XIST and three miRNAs (miR-9-5p, miR-129-5p, and miR-340-5p) as therapeutic targets.

Conclusions

Our integrated analysis identified four hub genes (CXCL1, IL1B, MMP1, and MMP10) regulated by NF-κB. We further revealed that AGP decreased the expression of hub genes by inhibiting NF-κB activation. Lastly, we predicted the involvement of ceRNA network in the regulation of NF-κB expression. Collectively, our results provide valuable information in understanding the molecular mechanisms of active UC. Furthermore, we predict the use of AGP and small RNA combination for the treatment of UC.

Molecular mechanisms of Huanglian jiedu decoction on ulcerative colitis based on network pharmacology and molecular docking

Huanglian jiedu decoction (HLJDD) is a heat-clearing and detoxifying agent composed of four kinds of Chinese herbal medicine. Previous studies have shown that HLJDD can improve the inflammatory response of ulcerative colitis (UC) and maintain intestinal barrier function. However, its molecular mechanism is not completely clear. In this study, we verified the bioactive components (BCI) and potential targets of HLJDD in the treatment of UC using network pharmacology and molecular docking, and constructed the pharmacological network and PPI network. Then the core genes were enriched by GO and KEGG. Finally, the bioactive components were docked with the key targets to verify the binding ability between them. A total of 54 active components related to UC were identified. Ten genes are very important to the PPI network. Functional analysis showed that these target genes were mainly involved in the regulation of cell response to different stimuli, IL-17 signal pathway and TNF signal pathway. The results of molecular docking showed that the active components of HLJDD had a good binding ability with the Hub gene. This study systematically elucidates the “multi-component, multi-target, multi-pathway” mechanism of anti-UC with HLJDD for the first time, suggesting that HLJDD or its active components may be candidate drugs for the treatment of ulcerative colitis.

Berberine inhibits IFN-γ signaling pathway in DSS-induced ulcerative colitis

Aims

The potential signaling pathways and core genes in ulcerative colitis (UC) were investigated in this study. Furthermore, potential mechanisms of BBR in treating UC were also explored.

Methods

Expression profiling by array of UC patients were obtained from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were determined with the differential analysis. The biological functions of DEGs were analyzed through the Database for Annotation, Visualization and Integrated Discovery (DAVID). The Gene Set Enrichment Analysis (GSEA) was applied to analyze the expression differences between two different phenotype sample sets. Dextran sulfate sodium (DSS) was applied to establish UC model of mice and lipopolysaccharide (LPS) was utilized to induce inflammatory damage of NCM460 cells. Therapeutic effects of berberine (BBR) on disease performance, pathologic changes and serum supernatant indices were analyzed in vivo. To further investigate the potential mechanisms of BBR in treating UC, the expression of genes and proteins in vivo and in vitro were examined by RT-qPCR, immunohistochemical staining and western blotting.

Results

Immune-inflammatory genes were identified and up-regulated significantly in UC patients. In addition, IFN-γ signaling pathway and its core genes were significantly up-regulated in the phenotype of UC. All disease performance and the pathologic changes of UC in mice were evidently ameliorated by BBR treatment. The pro-inflammatory cytokines of serum, including CXCL9, CXCL1, IL-17 and TNF-α, in UC mice were significantly reduced by treatment of BBR. In terms of mechanisms of BBR in treating UC, the pro-inflammatory and immune-related genes, encoding IFN-γ, IRF8, NF-κB and TNF-α decreased significantly in UC mice followed by BBR treatment. Meanwhile, the expression of IFN-γ and its initiated targets, including IRF8, Ifit1, Ifit3, IRF1, were suppressed significantly by BBR treatment in vivo. The blocking of IFN-γ in vitro led to the silence of IFN-γ signaling pathway after exposure to BBR. Furthermore, the blocking of IFN-γ in vitro led to the silence of IFN-γ signaling pathway after exposure to BBR.

Conclusion

BBR holds anti-inflammatory activity and can treat UC effectively. The anti-inflammatory property of BBR is tightly related to the suppression of IFN-γ signaling pathway, which is crucial in immune-inflammatory responses of the colon mucosa.

LCN2 as a Potential Diagnostic Biomarker for Ulcerative Colitis-Associated Carcinogenesis Related to Disease Duration

BACKGROUND

Patients with long-duration ulcerative colitis (UC) had a higher risk of developing ulcerative colitis-associated carcinogenesis (UCAC) when compared to those with short-duration UC. This study aimed to discover the biomarker for cancer surveillance related to disease duration.

METHODS

The microarrays were divided into short-duration (<10 years) UC, long-duration (≥10 years) UC, UCAC, and normal groups in the Gene Expression Omnibus (GEO) datasets. Differentially expressed genes (DEGs) of GEO and the hub genes of the selected weighted gene co-expression network analysis (WGCNA) were intersected to obtain the overlapping genes. Among these genes, the key gene was identified by using the protein-protein interaction (PPI) network, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, the cytoHubba of Cytoscape, and the expression levels. Also, immunofluorescence of human colonic mucosa and animal experiment were used to validate the expression trend of the key gene in the progress of UC developing into UCAC.

RESULTS

Lipocalin-2 (LCN2) was more relevant with disease duration of UC and significantly negatively correlated with the risk of UCAC. The expression level of LCN2 in short-duration UC was higher than that of long-duration UC (P < 0.01), long-duration UC was higher than that of UCAC (P = 0.001), and UC and UCAC were all higher than that of the normal (P < 0.001). We then discovered that the expression trend of LCN2 in blood and stool samples was consistent with that in colorectal mucosa.

CONCLUSION

The research indicates that LCN2 could be a novel biomarker to evaluate cancer surveillance related to disease duration of developing UC into UCAC. Compared with that of blood samples, stool detection of LCN2 may have more advantages for diagnosis value of early stage of UCAC as a complement to colonoscopy surveillance.

Integrated Analysis of Ulcerative Colitis Revealed an Association between PHLPP2 and Immune Infiltration

Ulcerative colitis (UC) is a progressive intestine inflammatory disease that is prone to recur. Herein, we utilize microarray technology and bioinformatics to reveal the underlying pathogenesis of UC and provide novel markers. Colonic biopsies were taken from eight UC patients and eight healthy controls. Three differentially expressed miRNAs (DEMIs) and 264 differentially expressed genes (DEGs) were screened using mRNA and miRNA microarray. Most DEGs were significantly associated with immune response and were markedly enriched in the IL-17 signaling pathway. Among the target genes of DEMIs, PHLPP2 overlapped with DEGs and the downregulation of PHLPP2 group was mainly involved in the epithelial-mesenchymal transition. PHLPP2 was downregulated in UC patients, which was validated in 5 GEO datasets and qRT-PCR. The ROC curve demonstrated that PHLPP2 has a perfect ability to distinguish UC patients from healthy controls. Moreover, PHLPP2 was low expression in patients with active UC. CIBERSORT algorithm indicated that the abundance of gamma delta T cells (P = 0.04), M0 macrophages (P = 0.01), and activated mast cells (P < 0.01) was significantly greater than that of the control group. The Spearman correlation analysis showed that PHLPP2 was positively correlated with the proportion of activated NK cells (rho = 0.62, P = 0.013) and Tregs (rho = 0.55, P = 0.03), but negatively correlated with those of activated mast cells (rho = -0.8, P < 0.01) and macrophages (rho = -0.73, P < 0.01). These results indicate that PHLPP2 is associated with immune cells in the pathogenesis of UC, as well as provide new prospects and future directions of investigation.

Identification of diagnostic signatures in ulcerative colitis patients via bioinformatic analysis integrated with machine learning

Ulcerative colitis (UC) is an immune-related disorder with enhanced prevalence globally. Early diagnosis is critical for the effective treatment of UC. However, it still lacks specific diagnostic signatures. The aim of our study was to explore efficient signatures and construct the diagnostic model for UC. Microarray data of GSE87473 and GSE48634, which were obtained from tissue biopsy samples, were downloaded from the Gene Expression Omnibus (GEO), and differently expressed genes (DEGs), GO, and KEGG analyses were performed. We constructed the PPI network via STRING database. The immune infiltration of the samples was evaluated using CIBERSORT methods combined with the LM22 feature matrix. The logistic regression model was constructed, with the expression of selected genes as the predictor variable, and the UC occurrence as the responsive variable. As a result, a total of 126 DEGs between the UC patients and normal counterparts were identified. The GO and KEGG analysis revealed that multiple biological processes, such as antimicrobial humoral immune response mediated by antimicrobial peptide and IL-17 signaling pathway, were enriched. The infiltration of eight immune cell types (B cells naive, Dendritic.cells.activated, Macrophages.M0, Macrophages.M2, Mast.cells.resting, Neutrophils, Plasma.cells, and T.cells.follicular.helper) was significantly different between patients with UC and normal counterparts. The top 50 most significant DEGs were selected for the construction of the PPI network. The average AUC of the logistic regression model in the fivefold cross-validation was 0.8497 in the training set, GSE87473. The AUC of another independent verification set of GSE48634 from the GEO database was 0.7208. In conclusion, we identified potential hub genes, including REG3A, REG1A, DEFA6, REG1B, and DEFA5, which might be significantly associated with UC progression. The logistic regression model based on the five genes could reliably diagnose UC patients.

Evidence for the butyrate metabolism as key pathway improving ulcerative colitis in both pediatric and adult patients

Accumulating evidence has shown many similarities and differences of gene profiles and pathways between pediatric and adult ulcerative colitis (UC) patients. In this study, we aimed to investigate the shared genes and pathways in intestinal tissues of pediatric and adult UC. Differentially expressed genes (DEGs) between pediatric and adult UC were identified via bioinformatic analysis of Gene Expression Omnibus datasets GSE87473 and GSE126124. Gene Ontology and pathway enrichment were used to analyze overlapped and distinguished DEGs. Gene Set Variation Analysis (GSVA) was utilized for contrast consistency. Mice colitis models were induced by dextran sulfate sodium (DSS) and Citrobacter rodentium. 2616 DEGs were screened out in intestinal tissues of adult UC compared with those of adult healthy controls, and 1195 DEGs in pediatrics. Same pathways between pediatric and adult UC were enriched using overlapped DEGs, mainly related to immune responses and metabolic processes, including butyrate metabolism, which was also identified by GSVA analysis. Of note, butyrate metabolism was the exclusive down-regulated pathway enriched by these two analyses, indicating that butyrate metabolism is one of the key pathways associated with both pediatric and adult UC. In addition, butyrate suppressed DSS-induced and Citrobacter rodentium-induced intestinal inflammation in mice. Therefore, the study revealed that butyrate metabolism was critical in both pediatric and adult UC. And butyrate suppressed colitis in mice, which provided a theoretical basis for the potential treatment of butyrate for UC patients.

Abbreviations: UC, Ulcerative colitis; IBD, Inflammatory bowel disease; DEGs, Differentially expressed genes; GEO, Gene Expression Omnibus; SVA, Spatial variant apodization; LIMMA, Linear models for the microarray data; FC, Fold change; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; GSVA, Gene Set Variation Analysis; MSigDB, Molecular Signatures Database; WT, Wild-type; DSS, Dextran sulfate sodium; HC, Healthy control; SD, Standard deviation; SNHG5, Small nucleolar RNA host gene 5; GLP-2, Glucagon-like peptide 2; GSE, Gene set enrichment; ECM, Extracellular matrix; TCA, Tricarboxylic acid cycle; NA, Not available.

The role of alcohol dehydrogenase 1C in regulating inflammatory responses in ulcerative colitis

Ulcerative colitis (UC) is a chronic relapsing inflammatory bowel disease caused by an interaction of genetics, immune responses, and environmental factors. However, the precise pathogenesis of UC remains poorly understood. The aim of the present study was to explore the potential target genes implicated in UC and to elucidate its underlying pathogenic mechanism. Firstly, three UC-associated microarray datasets (GSE75214, GSE87466, and GSE92517) were obtained to screen the differentially expressed genes (DEGs). As a result, alcohol dehydrogenase 1C (ADH1C) was the most significantly downregulated DEG in UC. We confirmed that ADH1C was downregulated in colonic tissue taken from patients with UC and colitis mice. Moreover, ADH1C expression was also decreased in colonic cell lines (NCM460 and HT29) treated with mixed proinflammatory cytokines (TNF-α, IFN-γ, IL-1β). Interestingly, we found that overexpression of ADH1C could distinctly decrease the production of IL-6 and IL-8. To elucidate the molecular mechanism of ADH1C in UC, gene set enrichment analysis (GSEA) was performed and demonstrated that immune-related pathways were mainly enriched in the low ADH1C group. Further studies displayed that STAT1/NF-κB pathway was activated in colitis mice and inflammatory cell model. Importantly, overexpression of ADH1C could suppress the phosphorylation of STAT1 and IκB. Therefore, ADH1C might regulate inflammatory responses through STAT1/NF-κB pathway. In conclusion, ADH1C was downregulated during inflammation, and its increased expression could inhibit the activation of STAT1/NF-κB pathway, thereby alleviating the secretion of IL-6 and IL-8. These findings indicate that ADH1C may be a potential therapeutic target for UC therapy.

Meta-analysis of gene expression disease signatures in colonic biopsy tissue from patients with ulcerative colitis

Publicly available ulcerative colitis (UC) gene expression datasets from observational studies and clinical trials include inherently heterogeneous disease characteristics and methodology. We used meta-analysis to identify a robust UC gene signature from inflamed biopsies. Eight gene expression datasets derived from biopsy tissue samples from noninflammatory bowel disease (IBD) controls and areas of active inflammation from patients with UC were publicly available. Expression- and meta-data were downloaded with GEOquery. Differentially expressed genes (DEG) in individual datasets were defined as those with fold change > 1.5 and a Benjamini–Hochberg adjusted P value < .05. Meta-analysis of all DEG used a random effects model. Reactome pathway enrichment analysis was conducted. Meta-analysis identified 946 up- and 543 down-regulated genes in patients with UC compared to non-IBD controls (1.2 and 1.7 times fewer up- and down-regulated genes than the median of the individual datasets). Top-ranked up- and down-regulated DEG were LCN2 and AQP8. Multiple immune-related pathways (e.g., ‘Chemokine receptors bind chemokine’ and ‘Interleukin-10 signaling’) were significantly up-regulated in UC, while ‘Biological oxidations’ and ‘Fatty acid metabolism’ were downregulated. A web-based data-mining tool with the meta-analysis results was made available (https://premedibd.com/genes.html). A UC inflamed biopsy disease gene signature was derived. This signature may be an unbiased reference for comparison and improve the efficiency of UC biomarker studies by increasing confidence for identification of disease-related genes and pathways.

Identifying Hub Genes, Key Pathways and Immune Cell Infiltration Characteristics in Pediatric and Adult Ulcerative Colitis by Integrated Bioinformatic Analysis

BACKGROUND AND AIMS

In the present study, we investigated the differentially expressed genes (DEGs), pathways and immune cell infiltration characteristics of pediatric and adult ulcerative colitis (UC).

METHODS

We conducted DEG analysis using the microarray dataset GSE87473 containing 19 pediatric and 87 adult UC samples downloaded from the Gene Expression Omnibus. Gene ontology and pathway enrichment analyses were conducted using Metascape. We constructed the protein-protein interaction (PPI) network and the drug-target interaction network of DEGs and identified hub modules and genes using Cytoscape and analyzed immune cell infiltration in pediatric and adult UC using CIBERSORT.

RESULTS

In total, 1700 DEGs were screened from the dataset. These genes were enriched mainly in inter-cellular items relating to cell junctions, cell adhesion, actin cytoskeleton and transmembrane receptor signaling pathways and intra-cellular items relating to the splicing, metabolism and localization of RNA. CDC42, POLR2A, RAC1, PIK3R1, MAPK1 and SRC were identified as hub DEGs. Immune cell infiltration analysis revealed higher proportions of naive B cells, resting memory T helper cells, regulatory T cells, monocytes, M0 macrophages and activated mast cells in pediatric UC, along with lower proportions of memory B cells, follicular helper T cells, γδ T cells, M2 macrophages, and activated dendritic cells.

CONCLUSIONS

Our study suggested that hub genes CDC42, POLR2A, RAC1, PIK3R1, MAPK1 and SRC and immune cells including B cells, T cells, monocytes, macrophages and mast cells play vital roles in the pathological differences between pediatric and adult UC and may serve as potential biomarkers in the diagnosis and treatment of UC.

Integrated Analysis of Multiple Microarray Studies to Identify Novel Gene Signatures in Ulcerative Colitis

Background: Ulcerative colitis (UC) is a chronic, complicated, inflammatory disease with an increasing incidence and prevalence worldwide. However, the intrinsic molecular mechanisms underlying the pathogenesis of UC have not yet been fully elucidated.

Methods: All UC datasets published in the GEO database were analyzed and summarized. Subsequently, the robust rank aggregation (RRA) method was used to identify differentially expressed genes (DEGs) between UC patients and controls. Gene functional annotation and PPI network analysis were performed to illustrate the potential functions of the DEGs. Some important functional modules from the protein-protein interaction (PPI) network were identified by molecular complex detection (MCODE), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG), and analyses were performed. The results of CytoHubba, a plug for integrated algorithm for biomolecular interaction networks combined with RRA analysis, were used to identify the hub genes. Finally, a mouse model of UC was established by dextran sulfate sodium salt (DSS) solution to verify the expression of hub genes.

Results: A total of 6 datasets met the inclusion criteria (GSE38713, GSE59071, GSE73661, GSE75214, GSE87466, GSE92415). The RRA integrated analysis revealed 208 significant DEGs (132 upregulated genes and 76 downregulated genes). After constructing the PPI network by MCODE plug, modules with the top three scores were listed. The CytoHubba app and RRA identified six hub genes: LCN2, CXCL1, MMP3, IDO1, MMP1, and S100A8. We found through enrichment analysis that these functional modules and hub genes were mainly related to cytokine secretion, immune response, and cancer progression. With the mouse model, we found that the expression of all six hub genes in the UC group was higher than that in the control group (P < 0.05).

Conclusion: The hub genes analyzed by the RRA method are highly reliable. These findings improve the understanding of the molecular mechanisms in UC pathogenesis.

The Construction and Comprehensive Analysis of Inflammation-Related ceRNA Networks and Tissue-Infiltrating Immune Cells in Ulcerative Progression

Ulcerative colitis (UC) is a common disease with great variability in severity, with a high recurrence rate and heavy disease burden. In recent years, the different biological functions of competing endogenous RNA (ceRNA) networks of long noncoding RNAs (lncRNAs) and microRNAs (miRs) have aroused wide concerns, the ceRNA network of ulcerative colitis (UC) may have potential research value, and these expressed noncoding RNAs may be involved in the molecular basis of inflammation recurrence and progression. This study analyzed 490 colon samples associated with UC from 4 gene expression microarrays from the GEO database and identified gene modules by weighted correlation network analysis (WGCNA). CIBERSORT detected tissue-infiltrating leukocyte profiling by deconvolution of microarray data. LncBase and multiMIR were used to identify lncRNA-miRNA-mRNA interaction. We constructed a ceRNA network which includes 4 lncRNAs (SH3BP5-AS1, MIR4435-2HG, ENTPD1-AS1, and AC007750.1), 5 miRNAs (miR-141-3p, miR-191-5p, miR-192-5p, miR-194-5p, and miR196-5p), and 52 mRNAs. Those genes are involved in interleukin family signals, neutrophil degranulation, adaptive immunity, and cell adhesion pathways. lncRNA MIR4435-2HG is a variable in the decision tree for moderate-to-severe UC diagnostic prediction. Our work identifies potential regulated inflammation-related lncRNA-miRNA-mRNA regulatory axes. The regulatory axes are dysregulated during the deterioration of UC, suggesting that it is a risk factor for UC progression.

Identification of key genes and biological processes contributing to colitis associated dysplasia in ulcerative colitis

Background

Ulcerative colitis-associated colorectal cancer (UC-CRC) is a life-threatening complication of ulcerative colitis (UC). The mechanisms underlying UC-CRC remain to be elucidated. The purpose of this study was to explore the key genes and biological processes contributing to colitis-associated dysplasia (CAD) or carcinogenesis in UC via database mining, thus offering opportunities for early prediction and intervention of UC-CRC.

Methods

Microarray datasets (GSE47908 and GSE87466) were downloaded from Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) between groups of GSE47908 were identified using the “limma” R package. Weighted gene co-expression network analysis (WGCNA) based on DEGs between the CAD and control groups was conducted subsequently. Functional enrichment analysis was performed, and hub genes of selected modules were identified using the “clusterProfiler” R package. Single-gene gene set enrichment analysis (GSEA) was conducted to predict significant biological processes and pathways associated with the specified gene.

Results

Six functional modules were identified based on 4929 DEGs. Green and blue modules were selected because of their consistent correlation with UC and CAD, and the highest correlation coefficient with the progress of UC-associated carcinogenesis. Functional enrichment analysis revealed that genes of these two modules were significantly enriched in biological processes, including mitochondrial dysfunction, cell-cell junction, and immune responses. However, GSEA based on differential expression analysis between sporadic colorectal cancer (CRC) and normal controls from The Cancer Genome Atlas (TCGA) indicated that mitochondrial dysfunction may not be the major carcinogenic mechanism underlying sporadic CRC. Thirteen hub genes (SLC25A3, ACO2, AIFM1, ATP5A1, DLD, TFE3, UQCRC1, ADIPOR2, SLC35D1, TOR1AIP1, PRR5L, ATOX1, and DTX3) were identified. Their expression trends were validated in UC patients of GSE87466, and their potential carcinogenic effects in UC were supported by their known functions and other relevant studies reported in the literature. Single-gene GSEA indicated that biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to angiogenesis and immune response were positively correlated with the upregulation of TFE3, whereas those related to mitochondrial function and energy metabolism were negatively correlated with the upregulation of TFE3.

Conclusions

Using WGCNA, this study found two gene modules that were significantly correlated with CAD, of which 13 hub genes were identified as the potential key genes. The critical biological processes in which the genes of these two modules were significantly enriched include mitochondrial dysfunction, cell-cell junction, and immune responses. TFE3, a transcription factor related to mitochondrial function and cancers, may play a central role in UC-associated carcinogenesis.

Long Noncoding RNA PMS2L2 Downregulates miR-24 through Methylation to Suppress Cell Apoptosis in Ulcerative Colitis

BACKGROUND

Ulcerative colitis (UC) is an inflammatory bowel disease characterized by chronic inflammation of the colon. It has been reported that PMS2L2 plays protective roles in inflammatory injury. This study aimed to investigate the role of the long noncoding RNA PMS2L2 in UC.

METHODS

Sixty-two patients with UC as well as 62 age- and gender-matched healthy controls were enrolled. Expressions of PMS2L2 and miR-24 in plasma from UC patients and healthy controls were determined by RT-qPCR. The interaction between PMS2L2 and miR-24 was predicted by bioinformatics and confirmed by RNA immunoprecipitation and RNA pull-down. The role of PMS2L2 in the regulation of miR-24 gene methylation was analyzed by methylation-specific PCR. The effects of PMS2L2 and miR-24 on the expressions of apoptosis-related proteins were detected by Western blots.

RESULTS

PMS2L2 was downregulated in the plasma of UC patients compared to that in age- and gender-matched healthy control. In human colonic epithelial cells (HCnEpCs), PMS2L2 overexpression inhibited miR-24 expression via promoting the methylation of miR-24 gene. In contrast, miR-24 overexpression failed to affect PMS2L2. In the detection of cell apoptosis, PMS2L2 overexpression could promote the expression of Bcl-2 and inhibit Bax, cleaved-caspase-3, and cleaved-caspase-9 expressions stimulated by LPS. Flow cytometer revealed that PMS2L2 elevation suppressed the apoptosis of HCnEpCs induced by LPS, but miR-24 aggravated the apoptosis. PMS2L2 overexpression rescued the detrimental effect of miR-24 on cell apoptosis.

CONCLUSION

PMS2L2 may downregulate miR-24 via methylation to suppress cell apoptosis in UC.

Carboxypeptidase A6 was identified and validated as a novel potential biomarker for predicting the occurrence of active ulcerative colitis

Ulcerative colitis (UC) is a chronic, highly heterogeneous intestinal inflammation with changes in epithelial function and tissue damage. However, the pathogenesis is still unclear between active UC and inactive UC. Herein, weighted gene co‐expression network analysis was applied to explore the gene modules related to active UC. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to further investigate the underlying mechanism of selected genes. We found that in the blue module (r = −.72), carboxypeptidase A6 (CPA6) was chosen to validate because of its high intra‐modular connectivity and module membership. In the test sets, the expression level of CPA6 was down‐regulated in active UC compared with inactive UC and normal colon. Furthermore, CPA6 expression was decreased primarily in the descending colon and only in mucosa affected by active UC. The receiver operating characteristic curve indicated that CPA6 expression had a performed well in diagnosing active UC from inactive UC (area under the curve = 0.99). Importantly, anti‐tumour necrosis factor (TNF) treatment (infliximab and golimumab) significantly increased the CPA6 expression. Finally, GSEA and GSVA found that extracellular matrix receptor, inflammatory response and epithelial‐mesenchymal transition were highly enriched in active UC with low CPA6 expression. In conclusion, CPA6 was identified and validated as a novel potential biomarker for predicting the occurrence of active UC, probably through regulating extracellular matrix or immune response.

Meta-Analysis of Expression Profiling Data Indicates Need for Combinatorial Biomarkers in Pediatric Ulcerative Colitis

BACKGROUND

Unbiased studies using different genome-wide methods have identified a great number of candidate biomarkers for diagnosis and treatment response in pediatric ulcerative colitis (UC). However, clinical translation has been proven difficult. Here, we hypothesized that one reason could be differences between inflammatory responses in an inflamed gut and in peripheral blood cells.

METHODS

We performed meta-analysis of gene expression microarray data from intestinal biopsies and whole blood cells (WBC) from pediatric patients with UC and healthy controls in order to identify overlapping pathways, predicted upstream regulators, and potential biomarkers.

RESULTS

Analyses of profiling datasets from colonic biopsies showed good agreement between different studies regarding pathways and predicted upstream regulators. The most activated predicted upstream regulators included TNF, which is known to have a key pathogenic and therapeutic role in pediatric UC. Despite this, the expression levels of TNF were increased in neither colonic biopsies nor WBC. A potential explanation was increased expression of TNFR2, one of the membrane-bound receptors of TNF in the inflamed colon. Further analyses showed a similar pattern of complex relations between the expression levels of the regulators and their receptors. We also found limited overlap between pathways and predicted upstream regulators in colonic biopsies and WBC. An extended search including all differentially expressed genes that overlapped between colonic biopsies and WBC only resulted in identification of three potential biomarkers involved in the regulation of intestinal inflammation. However, two had been previously proposed in adult inflammatory bowel diseases (IBD), namely, MMP9 and PROK2.

CONCLUSIONS

Our findings indicate that biomarker identification in pediatric UC is complicated by the involvement of multiple pathways, each of which includes many different types of genes in the blood or inflamed intestine. Therefore, further studies for identification of combinatorial biomarkers are warranted. Our study may provide candidate biomarkers for such studies.

Colonic Mucosal Transcriptomic Changes in Patients with Long-Duration Ulcerative Colitis Revealed Colitis-Associated Cancer Pathways

BACKGROUND AND AIMS

Patients with ulcerative colitis [UC] with long disease duration have a higher risk of developing colitis-associated cancer [CAC] compared with patients with short-duration UC. The aim of this study was to identify transcriptomic differences associated with the duration of UC disease.

METHODS

We conducted transcriptome profiling on 32 colonic biopsies [11 long-duration UC, ≥20 years; and 21 short-duration UC, ≤5 years] using Affymetrix Human Transcriptome Array 2.0. Differentially expressed genes [fold change > 1.5, p < 0.05] and alternative splicing events [splicing index > 1.5, p < 0.05] were determined using the Transcriptome Analysis Console. KOBAS 3.0 and DAVID 6.8 were used for KEGG and GO analysis. Selected genes from microarray analysis were validated using qPCR.

RESULTS

There were 640 differentially expressed genes between both groups. The top ten upregulated genes were HMGCS2, UGT2A3 isoforms, B4GALNT2, MEP1B, GUCA2B, ADH1C, OTOP2, SLC9A3, and LYPD8; the top ten downregulated genes were PI3, DUOX2, VNN1, SLC6A14, GREM1, MMP1, CXCL1, TNIP3, TFF1, and LCN2. Among the 123 altered KEGG pathways, the most significant were metabolic pathways; fatty acid degradation; valine, leucine, and isoleucine degradation; the peroxisome proliferator-activated receptor signalling pathway; and bile secretion, which were previously linked with CAC. Analysis showed that 3560 genes exhibited differential alternative splicing between long- and short-duration UC. Among them, 374 were differentially expressed, underscoring the intrinsic relationship between altered gene expression and alternative splicing.

CONCLUSIONS

Long-duration UC patients have altered gene expressions, pathways, and alternative splicing events as compared with short-duration UC patients, and these could be further validated to improve our understanding of the pathogenesis of CAC.