Ulcerative Colitis Controls Research Articles

Differential analysis of sorting nexin 10 and sterol regulatory element-binding protein 2 expression in inflammatory bowel disease.

Sorting nexin 10 (SNX10) expression induces intestinal barrier dysfunction and inflammatory responses; in contrast, its inhibition promotes intestinal mucosal healing through sterol regulatory element-binding protein 2 (SREBP2)-mediated cholesterol synthesis. However, its regulatory mechanism for the pathogenesis of inflammatory bowel disease (IBD) remains unclear. In this study, we examined SNX10 and SREBP2 expression in ulcerative colitis (UC) and Crohn's disease (CD). A total of 30 and 28 patients with UC and CD, respectively, were recruited. The expression of SNX10 and SREBP2 in the colonic mucosa was measured by immunohistochemistry (IHC). We discovered that patients with CD had significantly higher expression levels of SNX10 and SREBP2 than patients with UC and healthy controls. In addition, the expression of SREBP2 in patients with UC was significantly higher than that in healthy controls. In our study, we indicated that SNX10 and SREBP2 may serve as biomarkers for identifying patients with UC and CD, thereby providing a clinical therapeutic strategy for the treatment of IBD by inhibiting SNX10.

Unique sterol metabolite shifts in inflammatory bowel disease and primary sclerosing cholangitis

Inflammatory bowel disease (IBD) triggers chronic intestinal inflammation and is linked to primary sclerosing cholangitis (PSC). Cholesterol homeostasis, tightly regulated under normal conditions, becomes disrupted in both inflammation and chronic liver disease. We analyzed fecal and serum levels of cholesterol synthesis precursors, oxysterols, and phytosterols in 87 patients with IBD (81 for serum analysis) including patients with Crohn's disease (CD) and ulcerative colitis (UC), 11 patients with PSC, 21 patients with PSC-IBD (18 for serum analysis), and 16 healthy controls (17 for serum analysis). Cholesterol was analysed by flow injection analysis on a high-resolution hybrid quadrupole-Orbitrap mass spectrometer and further serum sterols and all fecal sterols were analysed by a gas chromatograph mass spectrometer. Serum levels of lanosterol, 7-dehydrocholesterol, 7-beta-hydroxycholesterol, 27-hydroxycholesterol, and the plant sterols campesterol, stigmasterol, and sitosterol were similar across control and patient groups. Notably, serum lathosterol was elevated in CD patients compared to those with UC, PSC, PSC-IBD, and healthy controls. All other serum and fecal sterols showed no differences between CD and UC. Cholesterol synthesis precursors in serum, serum cholesterol levels, and both serum and fecal plant sterol levels decreased with increasing IBD severity. Consequently, serum cholesterol, campesterol, sitosterol, and fecal 5-beta sitostanol and 5-alpha sitostanol were negatively correlated with C-reactive protein and fecal calprotectin. The conversion of cholesterol to coprostanol in feces was impaired in IBD, PSC, and PSC-IBD, independent of bowel inflammation severity or liver disease extent. Patients with PSC, and to a lesser extent PSC-IBD, had elevated serum plant sterol levels, positively correlating with liver disease markers. In conclusion, in patients with IBD, cholesterol biosynthetic precursors, serum cholesterol levels, and fecal plant sterols decrease with intestinal inflammation. An inverse association of serum plant sterols with intestinal inflammation was observed in patients with IBD and a direct association of serum phytosterols with liver injury in patients with PSC. The conversion of fecal cholesterol to coprostanol was impaired in all patient cohorts. IBD and PSC alter serum sterol levels differently, whereas changes in fecal sterols are not disease specific and are moderate.

UNVEILING THERAPEUTIC TARGETS THROUGH PATHWAY ANALYSIS AND IDENTIFICATION OF DIFFERENTIALLY EXPRESSED GENES IN ULCERATIVE COLITIS

Objective: This study utilizes integrated bioinformatics to investigate Differentially Expressed Genes (DEGs) and pathways related to ulcerative colitis (UC). Material and Method: Differentially Expressed Genes were identified from UC patients' colonic mucosal samples and controls using GSE13367 and GSE134025 datasets. Differentially Expressed Genes selection utilized GEO2R and Venn diagrams, followed by functional annotation, pathway analysis, PPI determination via the STRING database, and GO/KEGG enrichment analysis using Metascape. Result and Discussion: Analysis unveiled 197 DEGs, with 76 up-regulated and 121 down-regulated genes. Up-regulated genes were enriched in humoral immune response, peptidoglycan binding, and NADPH oxidase complex, while down-regulated genes were linked to inorganic anion transport, transmitter-gated ion channel activity, and integral plasma membrane components. In the PPI network, up-regulated DEGs formed a dense network (75 nodes, 190 edges), indicating significant interactions, whereas down-regulated DEGs formed a less dense network (114 nodes, 63 edges). Five hub genes (CXCR4, CXCL13, CXCL1, MMP3) were identified among the 197 DEGs. These findings provide new insights into UC's causes and offer promise for more effective therapeutic approaches.

Use of glucagon-like peptide-1 receptor agonists for type 2 diabetes mellitus and outcomes of inflammatory bowel disease.

Glucagon-like peptide-1 receptor agonists (GLP-1RA) show anti-inflammatory properties. To evaluate their clinical impact on inflammatory bowel disease (IBD) outcomes. Retrospective cohort study utilising the TriNetX database comparing IBD-specific outcomes in patients with ulcerative colitis (UC) or Crohn's disease (CD) and type 2 diabetes mellitus (T2DM) on GLP-1RA compared to oral hypoglycaemic agents. The primary outcome was hospitalisation requiring intravenous steroids and IBD-related surgery within 3 years. We performed 1:1 propensity score matching (PSM) for demographics, co-morbid conditions, BMI, laboratory values, HbA1c, and IBD medications including steroids. We identified 1130 patients in the UC GLP-1RA cohort (mean age: 58.9 ± 11.6 years, 56.3% female, 70.2% White, 57.2% with obesity) and 1140 patients in the CD GLP-1RA cohort (mean age: 56.7 ± 11.5, 61.9% female, 73.6% White, 56.2% with obesity). After PSM, there was no difference in the risk of intravenous steroid use (aHR: 1.21, 95% CI: 0.92-1.59) but a lower risk of colectomy (aHR: 0.37, 95% CI: 0.14-0.97) between the UC GLP-1RA and control cohort. There was no difference in the risk of intravenous steroid use (aHR: 1.04, 95% CI: 0.80-1.34) but a lower risk of surgery (aHR: 0.55, 95% CI: 0.36-0.84) between the CD GLP-1RA and CD control cohort. There was no difference in the risk of oral steroid use or advanced therapy initiation in the UC and CD GLP-1RA than control cohorts. We found an association between lower risk of IBD-related surgery and GLP-1RA use for T2DM in patients with UC or CD.

Integrated Analysis of Microbiome and Metabolome Reveals Disease-Specific Profiles in Inflammatory Bowel Diseases and Intestinal Behçet's Disease.

The gut microbial and metabolic characteristics of intestinal Behçet's disease (BD), a condition sharing many clinical similarities with ulcerative colitis (UC) and Crohn's disease (CD), are largely unexplored. This study investigated the gut microbial and metabolic characteristics of intestinal BD as well as potential biomarkers, comparing them with those in UC, CD, and healthy controls. Colon tissue and stool samples from 100 patients (35 UC, 30 CD, and 35 intestinal BD) and 41 healthy volunteers were analyzed using 16S ribosomal RNA sequencing to assess microbial diversity, taxonomic composition, and functional profiling. Plasma metabolomic analyses were performed using gas chromatography and ultra-performance liquid chromatography-mass spectrometry. Results indicated reduced microbial diversity in CD but not in intestinal BD, with intestinal BD showing fewer changes compared to controls yet distinct taxonomic features from UC, CD, and controls. Common alterations across all diseases included a reduction in beneficial bacteria producing short-chain fatty acids. Intestinal BD-specific changes featured a decreased abundance of Bacteroides fragilis. Metabolomic profiles in intestinal BD were similar to those in CD but distinct from those in UC, displaying significant changes in energy metabolism and genetic information processing. This integrative analysis revealed both shared and unique profiles in intestinal BD compared with UC, CD, and controls, advancing our understanding of the distinctive features of these diseases.

Possible role of intestinal fungal dysbiosis in dectin-1 and cytokines expression in patients with ulcerative colitis.

Dysregulation of cytokines and intestinal mycobiome has been surveyed in the progression of inflammatory bowel diseases (IBDs), including ulcerative colitis (UC) and Crohn's disease (CD). On the other hand, the intestinal fungal flora and its main receptor, Dectin-1, induce immune-derived cytokines. Total 64 individuals comprising 32 patients with UC (case group) and 32 healthy subjects (HS group) were assessed. The type and prevalence of fecal yeast species were determined by deoxyribonucleic acid (DNA) sequencing through polymerase chain reaction (PCR) amplification usingITS4 and ITS5 primers. Furthermore, the ribonucleic acid (RNAs) of IL-4, IL-10, IL-17, IL-22 and IFN-γ were extracted. The expression of Dectin-1 gene was then measured in the excised tissue samples. A higher global fungal load in UC-affectedpatients (75%) was found in comparison with the HS group (25%), especially Candida albicans. Saccharomyces cerevisiae was significantly reduced in the fecal samples of UC-affected patients compared to HS (15.04% vs. 1.93% UC). The expression level of Dectin-1 was significantly elevated in patients with active UC (7.37 ± 0.81) than in patients with non-active UC (5.01 ± 77.25) and healthy controls (0.97 ± 0.24) (p < 0.05). The expression levels of IL-4, IL-10, especially both IL-17 and IL-22, were higher in the active UC group compared to the HS group (p = 0.0101, p = 0.0155, p < 0.0001, p < 0.0001, respectively). Similar expression level of IL-4, IL-10, IL-17, IL-22 (p > 0.999) and lower expression of interferongamma (IFN-γ) (p = 0.0021) were found in the non-active UC group compared to the HS group. A significant weak to moderate correlation was detected between Dectin-1 and IL-17 (r = 0.339, p = 0.019), as well as Dectin-1 and IL-22 (r = 0.373, p = 0.015). Furthermore, the expression levels of Dectin-1, IL-17 and IL-22 displayed significant associations with disease activity (p < 0.001, p = 0.029 and p = 0.003, respectively), regardless of the participant group. The current study revealed a possible role for intestinal fungi to promote colonic inflammation and increase UC activity through Dectin-1 stimulation. A positive correlation was detected between intestinal fungal richness with UC susceptibility and activity. IL-4 and IL-10 were associated with disease activity. Besides, the expression levels of Dectin-1, IL-17 and IL-22 were independently associated with disease activity.

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.

Non-coding transcribed ultraconserved region uc.290 in colon mucosa promotes intestinal fibrosis in chronic active ulcerative colitis

Background and aimsTGF-β1 induces epithelial-mesenchymal transition (EMT) and leads to intestinal fibrosis in ulcerative colitis (UC). We aimed to investigate the expression of transcribed ultraconserved region uc.290 in chronic UC and its role in intestinal fibrosis. MethodsColon specimens were taken from thirty chronic active UC, chronic inactive UC and healthy controls respectively. Modified Mayo score, expressions of uc.290, TGF-β1, EMT biomarkers (Vimentin, α-SMA and E-cadherin) and intestinal fibrosis biomarker (collagen Ⅲ) in colon biopsy specimens were determined in human. Expressions of TGF-β1, EMT biomarkers and collagen Ⅲ were determined in uc.290 overexpressed or silenced epithelial colon cells (HT29). ResultsUc.290, TGF-β1 and collagen Ⅲ were overexpressed, and EMT was prominent in chronic active UC. Uc.290 level had a positive correlation with modified Mayo score in chronic active UC. TGF-β1 and collagen Ⅲ were overexpressed, and EMT was prominent in uc.290 overexpressed HT29 cells. ConclusionsUc.290 was overexpressed in chronic active UC and might promote intestinal fibrosis by TGF-β1/EMT/collagen Ⅲ pathway.

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.

Constituents of stable commensal microbiota imply diverse colonic epithelial cell reactivity in patients with ulcerative colitis

BackgroundDespite extensive research on microbiome alterations in ulcerative colitis (UC), the role of the constituent stable microbiota remains unclear.ResultsThis study, employing 16S rRNA-gene sequencing, uncovers a persistent microbial imbalance in both active and quiescent UC patients compared to healthy controls. Using co-occurrence and differential abundance analysis, the study highlights microbial constituents, featuring Phocaeicola, Collinsella, Roseburia, Holdemanella, and Bacteroides, that are not affected during the course of UC. Co-cultivation experiments, utilizing commensal Escherichia coli and Phocaeicola vulgatus, were conducted with intestinal epithelial organoids derived from active UC patients and controls. These experiments reveal a tendency for a differential response in tight junction formation and maintenance in colonic epithelial cells, without inducing pathogen recognition and stress responses, offering further insights into the roles of these microorganisms in UC pathogenesis. These experiments also uncover high variation in patients’ response to the same bacteria, which indicate the need for more comprehensive, stratified analyses with an expanded sample size.ConclusionThis study reveals that a substantial part of the gut microbiota remains stable throughout progression of UC. Functional experiments suggest that members of core microbiota – Escherichia coli and Phocaeicola vulgatus – potentially differentially regulate the expression of tight junction gene in the colonic epithelium of UC patients and healthy individuals.

Identified S100A9 as a target for diagnosis and treatment of ulcerative colitis by bioinformatics analysis

Ulcerative colitis (UC) is a chronic, recurrent inflammatory bowel disease. UC confronts with severe challenges including the unclear pathogenesis and lack of specific diagnostic markers, demanding for identifying predictive biomarkers for UC diagnosis and treatment. We perform immune infiltration and weighted gene co-expression network analysis on gene expression profiles of active UC, inactive UC, and normal controls to identify UC related immune cell and hub genes. Neutrophils, M1 macrophages, activated dendritic cells, and activated mast cells are significantly enriched in active UC. MMP-9, CHI3L1, CXCL9, CXCL10, CXCR2 and S100A9 are identified as hub genes in active UC. Specifically, S100A9 is significantly overexpressed in mice with colitis. The receiver operating characteristic curve demonstrates the excellent performance of S100A9 expression in diagnosing active UC. Inhibition of S100A9 expression reduces DSS-induced colonic inflammation. These identified biomarkers associated with activity in UC patients enlighten the new insights of UC diagnosis and treatment.

Mucosal Genes Encoding Clock, Inflammation and Their Mutual Regulators Are Disrupted in Pediatric Patients with Active Ulcerative Colitis.

Patients with active ulcerative colitis (UC) display a misalignment of the circadian clock, which plays a vital role in various immune functions. Our aim was to characterize the expression of clock and inflammation genes, and their mutual regulatory genes in treatment-naïve pediatric patients with UC. Using the Inflammatory Bowel Disease Transcriptome and Metatranscriptome Meta-Analysis (IBD TaMMA) platform and R algorithms, we analyzed rectal biopsy transcriptomic data from two cohorts (206 patients with UC vs. 20 healthy controls from the GSE-109142 study, and 43 patients with UC vs. 55 healthy controls from the GSE-117993 study). We compared gene expression levels and correlation of clock genes (BMAL1, CLOCK, PER1, PER2, CRY1, CRY2), inflammatory genes (IκB, IL10, NFκB1, NFκB2, IL6, TNFα) and their mutual regulatory genes (RORα, RORγ, REV-ERBα, PGC1α, PPARα, PPARγ, AMPK, SIRT1) in patients with active UC and healthy controls. The clock genes BMAL1, CLOCK, PER1 and CRY1 and the inflammatory genes IκB, IL10, NFκB1, NFκB2, IL6 and TNFα were significantly upregulated in patients with active UC. The genes encoding the mutual regulators RORα, RORγ, PGC1α, PPARα and PPARγ were significantly downregulated in patients with UC. A uniform pattern of gene expression was found in healthy controls compared to the highly variable expression pattern in patients with UC. Among the healthy controls, inflammatory genes were positively correlated with clock genes and they all showed reduced expression. The difference in gene expression levels was associated with disease severity and endoscopic score but not with histological score. In patients with active UC, clock gene disruption is associated with abnormal mucosal immune response. Disrupted expression of genes encoding clock, inflammation and their mutual regulators together may play a role in active UC.

N04 Impact of phase angle on nutritional assessment and disease activity in patients with Ulcerative Colitis

Abstract Background An increase in the prevalence of Ulcerative Colitis (UC) has been reported, especially in Latin America, malnutrition occurs in up to 70% of patients with active disease. The complete assessment of nutritional status is the best method to make an adequate diagnosis since it considers 4 parameters, anthropometry, biochemistry, clinical, and dietary, however, it is very extensive and there are other methods such as bioelectrical impedance (BIA), which is a non-invasive way to estimate the percentage and amount of fat, muscle, water and phase angle (PhA). Moreover, PhA has been proposed as a marker of cell integrity which may be a substitute for complete nutritional assessment. Therefore, the study aimed to evaluate the effectiveness of PhA in the nutritional diagnosis of patients with UC. Methods A cross-sectional study was carried out in patients with UC and healthy controls. Body composition was measured in both groups to obtain the PhA. U Mann-Whitney test was used to compare the data. Patients were classified according to their PhA, considering a normal value of &amp;gt;6.1° and a low value of &amp;gt;6.1°. Results The study included 60 UC and 120 controls, 65% were women, and 35% men, the PhA was lower in UC compared to the controls, in addition to the fact that patients with active disease had a lower PhA compared to patients with remission (5.6±0.9 vs 6.06±0.8, p&amp;lt;0.05). In our study, patients with a low PhA had a lower amount of weight (Active: 60.5±13.6 vs 70.3±.8, p=0.018, Remission: 57.1±11.4 vs 69.4±8.7, p=0.006), dry lean mass (Active: 13.8±3.6 vs 18.2±.6, p=0.009; Remission: 13.1±2 vs 19.7±5.3, p&amp;lt;0.001), total body water (Active: 27.4±6.2 vs 32.9±4.6, p=0.028; Remission: 25.3±3.8 vs 34.4±9.2, p=0.003), and intracellular water (Active: 51.9±3.2 vs 55.1±3.3, p=0.042; Remission: 49.3±10.7 vs 55.8±3.6, p=0.025 ) regardless of disease activity. In this population, we can observe that the inflammation markers (ESR, CRP) were increased in accordance with the activity of the disease associated with PhA, which is consistent with what has been reported in the literature. Conclusion The PhA is modified in patients with UC compared to healthy patients, even more so when they have active disease. Women with active UC are those at risk of malnutrition and cardiovascular risk measured by PhA and CCI. PhA is effective in diagnosing malnutrition in patients with UC regardless of conventional parameters for evaluating nutritional status (Figure 1).

Systematic review of metabolomic alterations in ulcerative colitis: unveiling key metabolic signatures and pathways.

Despite numerous metabolomic studies on ulcerative colitis (UC), the results have been highly variable, making it challenging to identify key metabolic abnormalities in UC. This study aims to uncover key metabolites and metabolic pathways in UC by analyzing existing metabolomics data. A systematic review. We conducted a comprehensive search in databases (PubMed, Cochrane Library, Embase, and Web of Science) and relevant study references for metabolomic research on UC up to 28 December 2022. Significant metabolite differences between UC patients and controls were identified, followed by an analysis of relevant metabolic pathways. This review incorporated 78 studies, identifying 2868 differentially expressed metabolites between UC patients and controls. The metabolites were predominantly from 'lipids and lipid-like molecules' and 'organic acids and derivatives' superclasses. We found 101 metabolites consistently altered in multiple datasets within the same sample type and 78 metabolites common across different sample types. Of these, 62 metabolites exhibited consistent regulatory trends across various datasets or sample types. Pathway analysis revealed 22 significantly altered metabolic pathways, with 6 pathways being recurrently enriched across different sample types. This study elucidates key metabolic characteristics in UC, offering insights into molecular mechanisms and biomarker discovery for the disease. Future research could focus on validating these findings and exploring their clinical applications.

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.

A Machine Learning-Based Diagnostic Model for Crohn's Disease and Ulcerative Colitis Utilizing Fecal Microbiome Analysis.

Recent research has demonstrated the potential of fecal microbiome analysis using machine learning (ML) in the diagnosis of inflammatory bowel disease (IBD), mainly Crohn's disease (CD) and ulcerative colitis (UC). This study employed the sparse partial least squares discriminant analysis (sPLS-DA) ML technique to develop a robust prediction model for distinguishing among CD, UC, and healthy controls (HCs) based on fecal microbiome data. Using data from multicenter cohorts, we conducted 16S rRNA gene sequencing of fecal samples from patients with CD (n = 671) and UC (n = 114) while forming an HC cohort of 1462 individuals from the Kangbuk Samsung Hospital Healthcare Screening Center. A streamlined pipeline based on HmmUFOTU was used. After a series of filtering steps, 1517 phylotypes and 1846 samples were retained for subsequent analysis. After 100 rounds of downsampling with age, sex, and sample size matching, and division into training and test sets, we constructed two binary prediction models to distinguish between IBD and HC and CD and UC using the training set. The binary prediction models exhibited high accuracy and area under the curve (for differentiating IBD from HC (mean accuracy, 0.950; AUC, 0.992) and CD from UC (mean accuracy, 0.945; AUC, 0.988)), respectively, in the test set. This study underscores the diagnostic potential of an ML model based on sPLS-DA, utilizing fecal microbiome analysis, highlighting its ability to differentiate between IBD and HC and distinguish CD from UC.

The impact of gut microbiome enterotypes on ulcerative colitis: identifying key bacterial species and revealing species co-occurrence networks using machine learning

ABSTRACT Ulcerative colitis (UC) is a chronic inflammatory intestinal disease affecting the colon and rectum, with its pathogenesis attributed to genetic background, environmental factors, and gut microbes. This study aimed to investigate the role of enterotypes in UC by conducting a hierarchical analysis, determining differential bacteria using machine learning, and performing Species Co-occurrence Network (SCN) analysis. Fecal bacterial data were collected from UC patients, and a 16S rRNA metagenomic analysis was performed using the QIIME2 bioinformatics pipeline. Enterotype clustering was conducted at the family level, and deep neural network (DNN) classification models were trained for UC and healthy controls (HC) in each enterotype. Results from eleven 16S rRNA gut microbiome datasets revealed three enterotypes: Bacteroidaceae (ET-B), Lachnospiraceae (ET-L), and Clostridiaceae (ET-C). Ruminococcus (R. gnavus) abundance was significantly higher in UC subjects with ET-B and ET-C than in those with ET-L. R. gnavus also showed a positive correlation with Clostridia in UC SCN for ET-B and ET-C subjects, with a higher correlation in ET-C subjects. Conversely, Odoribacter (O.) splanchnicus and Bacteroides (B.) uniformis exhibited a positive correlation with tryptophan metabolism and AMP-activated protein kinase (AMPK) signaling pathways, while R. gnavus showed a negative correlation. In vitro co-culture experiments with Clostridium (C.) difficile demonstrated that fecal microbiota from ET-B subjects had a higher abundance of C. difficile than ET-L subjects. In conclusion, the ET-B enterotype predisposes individuals to UC, with R. gnavus as a potential risk factor and O. splanchnicus and B. uniformis as protective bacteria, and those with UC may have ultimately become ET-C.

Gut microbiota-derived 12-ketolithocholic acid suppresses the IL-17A secretion from colonic group 3 innate lymphoid cells to prevent the acute exacerbation of ulcerative colitis

ABSTRACT Intestinal microbiota dysbiosis and metabolic disruption are well-known as the primary triggers of ulcerative colitis (UC). However, their role in regulating the group 3 innate lymphoid cells (ILC3s), which are essential for intestinal health, remains unexplored during the development of disease severity. Here, our results showed that the microbiota structure of patients with severe UC (SUCs) differed from those with mild UC (MiUCs), moderate UC (MoUCs), and healthy controls (HCs). Microbes producing secondary bile acids (SBAs) and SBAs decreased with the aggravation of UC, and a strong positive correlation existed between them. Next, fecal microbiota transfer was used to reproduce the human-derived microbiota in mice and decipher the microbiota-mediated inflammatory modulation during an increase in disease severity. Mice receiving SUC-derived microbiota exhibited enhancive inflammation, a lowered percentage of ILC3s, and the down-regulated expressions of bile acid receptors, including vitamin D receptor (VDR) and pregnane X receptor (PXR), in the colon. Similar to clinical results, SBA-producing microbes, deoxycholic acids (DCA), and 12-ketolithocholic acids (12-KLCA) were diminished in the intestine of these recipients. Finally, we compared the therapeutic potential of DCA and 12-KLCA in preventing colitis and the regulatory mechanisms mediated by ILC3s. 12-KLCA but not DCA represented a strong anti-inflammatory effect associated with the higher expression of VDR and the lower secretion of IL-17A from colonic ILC3s. Collectively, these findings provide new signatures for monitoring the acute deterioration of UC by targeting gut microbiota and bile acid metabolism and demonstrate the therapeutic and preventive potential of a novel microbiota-derived metabolite, 12-KLCA.

Gut microbial signatures in clinically stable ulcerative colitis according to the mucosal state and associated symptoms.

The gut microbiome of patients with clinically stable ulcerative colitis (UC) differs from that of healthy individuals depending on the state of the colonic mucosa, especially with or without advanced scarring; however, the underlying mechanism is unclear. Therefore, this study examined the gut microbiome compositional signatures in patients with significant mucosal scarring and UC-related symptoms. Stool samples for gut microbiome analysis were prospectively collected from 57 patients with clinically stable UC between January 1 and December 31, 2022. Data from 57 individuals without inflammatory bowel disease (non-IBD) paired by age and sex were selected from our previous study as the control group. The fecal samples were subjected to 16S rRNA gene sequencing. Associations between gut microbiome profiles and clinical or colonoscopic assessments were examined using diversity and differential abundance analyses. Gut microbiome compositions between the patients with clinically stable UC and non-IBD controls differed significantly. Furthermore, gut microbiome compositions varied between the preserved and altered mucosa groups identified based on mucosal changes in the UC group. Differential abundance test of patients with UC for symptomatic remission based on stool frequency from the two-item patient-reported outcome identified several overlapping taxa specified as gut microbiome signatures, including the Enterobacteriaceae unknown genera (Enterobacteriaceae_g), Klebsiella,and several Lachnospiraceae spp. both in mucosal and symptom change analyses. The gut microbiome can change with mucosal changes, even in clinically stable UC, and some gut microbial signatures may explain the symptom manifestations in patients with UC showing significant mucosal changes.

Fractal Parameters as Independent Biomarkers in the Early Diagnosis of Pediatric Onset Inflammatory Bowel Disease

Inflammatory bowel disease (IBD), which encompasses two different phenotypes—Crohn’s disease (CD) and ulcerative colitis (UC)—consists of chronic, relapsing disorders of the gastrointestinal tract. In 20–30% of cases, the disease begins in the pediatric age. There have been just a few studies that used fractals for IBD investigation, but none of them analyzed intestinal cell chromatin. The main aim of this study was to assess whether it is possible to differentiate between the two phenotypes in pediatric patients, or either of the phenotypes versus control, using the fractal dimension and lacunarity of intestinal cell chromatin. We analyzed nuclei from at least seven different intestinal segments from each group. In the majority of colon segments, both the fractal dimension (FD) and the lacunarity significantly differed between the UC group and CD group, and the UC group and control group. In addition, the ileocecal valve and rectum were the only segments in which CD could be differentiated from the controls based on the FD. The potential of the fractal analysis of intestinal cell nuclei to serve as an observer-independent histological tool for ulcerative colitis diagnosis was identified for the first time in this study. Our results pave the way for the development of computer-aided diagnosis systems that will assist the physicians in their clinical practice.