Biomarkers In Ulcerative Colitis Research Articles

Integration of transcriptomics and metabolomics identify biomarkers of aberrant lipid metabolism in ulcerative colitis

BackgroundThe incidence of ulcerative colitis (UC) continues to rise globally, but effective therapeutic targets are still lacking. In recent years, numerous studies have indicated that lipid therapies could offer a novel perspective for UC treatment. Given the absence of prior research utilizing high-throughput data to identify target genes associated with lipid metabolism, we conducted this work. MethodsThe training set for this study was derived from four datasets within the Gene Expression Omnibus (GEO), encompassing a total of 357 UC patients. We employed four machine learning methods (LASSO, SVM, RF, and Boruta) to jointly identify core biomarkers in these patients, whose aberrant expression needed to be validated in independent datasets and in dextrose sulfate sodium salt (DSS)-induced UC mouse models. Regarding metabolomics, we detected abnormal oxidized lipids in the serum of UC mouse using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in conjunction with orthogonal partial least squares-discriminant analysis (OPLS-DA). ResultsPhospholipase A2 Group IIA (PLA2G2A) was first identified as a possible biomarker for UC, with AUC values of 0.810 and 1.000 in the two validation sets, while in animal models the gene showed similarly significant up-regulation in damaged intestinal mucosa. Further analysis of this gene showed that it was positively correlated with 17 immune cell types and histological severity. Additionally, we pioneered the development of a lipid metabolism score in UC research, which outperformed all individual genes in terms of disease diagnostic efficacy (AUC values of 0.980 and 1.000 for the two validation sets, respectively). Finally, the metabolomics study also identified 31 significantly abnormal oxidized lipids, including 12-HHT and DHA. ConclusionsPLA2G2A is a key therapeutic target for UC, and oxidized lipids such as 12-HHT can serve as potential serologic indicators for diagnosis.

Mitochondrial-related genes PDK2, CHDH, and ALDH5A1 served as a diagnostic signature and correlated with immune cell infiltration in ulcerative colitis.

We conducted an investigation to determine the potential of mitochondrial-related genes as diagnostic biomarkers in ulcerative colitis (UC), while also examining their association with immune cell infiltration. To achieve this, we acquired four datasets pertaining to UC, which included gene expression arrays and clinical data, from the GEO database. Subsequently, we selected three signature genes (PDK2, CHDH, and ALDH5A1) to construct a diagnostic model for UC. The nomogram and ROC curves exhibited exceptional diagnostic efficacy. Following this, quantitative real-time polymerase chain reaction and western blotting assays validated the decreased mRNA and protein expression of PDK2, CHDH, and ALDH5A1 in the model of UC cells and dextran sulfate sodium salt (DSS)-induced mice colitis tissues, aligning with the findings in the risk model. This investigation suggested a negative correlation between the expression of ALDH5A1, CHDH, and PDK2 and the infiltration of M1 macrophages. Then, immunofluorescence analysis confirmed the augmented expression of CD86 in the tissue of mice subjected to DSS, while a diminished expression of ALDH5A1, CHDH, and PDK2 was observed. Consequently, it can be inferred that targeting mitochondria-associated genes, namely PDK2, CHDH, and ALDH5A1, holds potential as a viable strategy for prognostic prediction and the implementation of immune therapy for UC.

Machine learning-based B cell-related diagnostic biomarker signature and molecular subtypes characteristic of ulcerative colitis.

As an inflammatory bowel disease, ulcerative colitis (UC) does not respond well to current treatments. It is of positive clinical significance to further study the pathogenesis of UC and find new therapeutic targets. B lymphocytes play an important role in the pathogenesis of UC. The effect of anti-CD20 therapy on UC also provides new evidence for the involvement of B cells in UC process additionally, suggesting the important role and potential therapeutic value of B cells in UC. In this study, we screened the most critical immune cell-related gene modules associated with UC and found that activated B cells were closely related to the gene modules. Subsequently, key activated B cell-associated gene (BRG) signatures were obtained based on WGCNA and differential expression analysis, and three overlapping BRG-associated genes were obtained by RF and LASSO algorithms as BRG-related diagnostic biomarkers for UC. Nomogram model was further performed to evaluate the diagnostic ability of BRG-related diagnostic biomarkers, subsequently followed by UC molecular subsets identification and immunoinfiltration analysis. We also further verified the expressions of the three screened BRGs in vitro by using an LPS-induced NCM460 cell line model. Our results provide new evidence and potential intervention targets for the role of B cells in UC from a new perspective.

Can Serum Histone H4 Level Be a Biomarker in Ulcerative Colitis?

Histones are a part of neutrophil extracellular trap molecules which were reported to have diagnostic values in some inflammatory diseases. We aimed to evaluate whether serum histone H4 can be a diagnostic and prognostic marker for ulcerative colitis. This case-control study included 58 ulcerative colitis patients (34 males and 24 females) and 45 healthy controls (25 males and 20 females). The Mayo clinical scoring system was used for the clinical and endoscopic features. Truelove-Witt's method was applied to the histology activity index. The human histone H4 kit was used for the enzyme-linked immunosorbent assay of serum histone H4. Serum histone H4 was significantly lower in the ulcerative colitis group compared to the control groups [268 (14-1639) vs. 598 (310-2134) ng/L, P < .001, respectively]. Among the ulcerative colitis patients, there was no correlation between serum histone H4 and disease extent, Mayo clinical scoring, Mayo endoscopic activity subscoring, histology activity index, inflammatory markers, d-dimer, and leukocyte and neutrophil counts (r < 0.20, P > .05). Histone H4 levels were not statistically significant between the patients with no medication and those taking 5-aminosalicylate and/or other agents (P > .05). The receiver operating characteristic curve analysis revealed that serum histone H4 concentrations had a 0.782 (95%CI: 0.690-0.857, P < .001) diagnostic accuracy for ulcerative colitis. The specificity and sensitivity for the cutoff level of ≤364 ng/L were 88.9% and 72.4%, respectively. Decreased serum histone H4 values may be used as an auxiliary marker in the progression and diagnosis of ulcerative colitis. Further studies are needed to delineate this relationship between clinical and laboratory traits of ulcerative colitis and serum histone H4.

LINC00641/miR-378a and Their Cross-Talk with TNF-α/IFN-γ as Potential Biomarkers in Ulcerative Colitis and Crohn's Diseases.

The most well-known forms of inflammatory bowel disease (IBD) that affect the entire gastrointestinal tract are ulcerative colitis (UC) and Crohn's disease (CD). The serum profile of inflammatory biomarkers and noncoding RNA and their role in the propagation of the inflammatory process remains controversial. Thus, this study was designed to examine the relationship between hematological profile, C-reactive protein (CRP), tumor necrosis factor-alpha (TNF-α), interferon-gamma (INF-γ), and the expression of LINC00641 and miR-378a in individuals with IBDs. In addition, we elucidated the correlation between the expression of LINC00641 and miR-378a and the biochemical variables analyzed. This retrospective study analyzed 94 unrelated participants. Group I included healthy controls, Group II consisted of participants diagnosed with UC, and Group III consisted of participants diagnosed with CD. Patients with IBDs experienced significant elevations in CRP, total leukocyte count, platelets, erythrocyte sedimentation rate, TNF-α, and INF-γ. However, participants with IBD had lower hemoglobin and albumin levels than healthy control participants. Moreover, the expression levels of LINC00641 and miR-378a were elevated in participants with IBD, with a significant difference between participants with IBD and healthy controls. The most striking observation was a clear association between serum LINC00641 and miR-378a levels and the biochemical variables assessed. This study demonstrated a positive correlation between the expression of LINC00641/miR-378a and TNF-α in patients with UC and CD patients. This study suggests that LINC00641 and miR-378a are prospective biomarkers and noninvasive screening tools for IBDs, which may help predict the progression of complications.

Exosomal-miR-129-2-3p derived from Fusobacterium nucleatum-infected intestinal epithelial cells promotes experimental colitis through regulating TIMELESS-mediated cellular senescence pathway

ABSTRACT Fusobacterium nucleatum (Fn) infection is known to exacerbate ulcerative colitis (UC). However, the link between Fn-infected intestinal epithelial cell (IEC)-derived exosomes (Fn-Exo) and UC progression has not been investigated. Differentially expressed miRNAs in Fn-Exo and non-infected IECs-derived exosomes (Con-Exo) were identified by miRNA sequencing. Then, the biological role and mechanism of Fn-Exo in UC development were determined in vitro and in vivo. We found that exosomes delivered miR-129-2-3p from Fn-infected IECs into non-infected IECs, exacerbating epithelial barrier dysfunction and experimental colitis. Mechanically, Fn-Exo induces DNA damage via the miR-129-2-3p/TIMELESS axis and subsequently activates the ATM/ATR/p53 pathway, ultimately promoting cellular senescence and colonic inflammation. In conclusion, Exo-miR-129-2-3p/TIMELESS/ATM/ATR/p53 pathway aggravates cellular senescence, barrier damage, and experimental colitis. The current study revealed a previously unknown regulatory pathway in the progression of Fn-infectious UC. Furthermore, Exosomal-miR-129-2-3p in serum and TIMELESS may function as novel potential diagnostic biomarkers for UC and Fn-high-UC.

Biomarkers of ulcerative colitis disease activity CXCL1, CYP2R1, LPCAT1, and NEU4 and their relationship to immune infiltrates

The diagnosis and assessment of ulcerative colitis (UC) poses significant challenges, which may result in inadequate treatment and a poor prognosis for patients. This study aims to identify potential activity biomarkers for UC and investigate the role of infiltrating immune cells in the disease. To perform gene set enrichment analysis, we utilized the cluster profiler and ggplot2 packages. Kyoto encyclopedia of genes and genomes was used to analyze degenerate enrichment genes. Significant gene set enrichment was determined using the cluster profiler and ggplot2 packages. Additionally, quantitative PCR (qRT-PCR) was employed to validate the expression of each marker in the ulcerative colitis model. We identified 651 differentially expressed genes (DEGs) and further investigated potential UC activity biomarkers. Our analysis revealed that CXCL1 (AUC = 0.710), CYP2R1 (AUC = 0.863), LPCAT1 (AUC = 0.783), and NEU4 (AUC = 0.833) were promising activity markers for the diagnosis of UC. Using rat DSS model, we validated these markers through qRT-PCR, which showed statistically significant differences between UC and normal colon mucosa. Infiltrating immune cell analysis indicated that M1 macrophages, M2 macrophages, activated dendritic cells (DCs), and neutrophils played crucial roles in the occurrence and progression of UC. Moreover, the activity markers exhibited varying degrees of correlation with activated memory CD4 T cells, M0 macrophages, T follicular helper cells, memory B cells, and activated DCs. The potential diagnostic genes for UC activity, such as CXCL1, CYP2R1, LPCAT1, and NEU4, as well as the infiltration of immune cells, may contribute to the pathogenesis and progression of UC.

Identification of diagnostic biomarks and immune cell infiltration in ulcerative colitis

We aimed to explore diagnostic biomarks and immune cell infiltration characteristics in ulcerative colitis (UC). We used the dataset GSE38713 as the training set and dataset GSE94648 as the test set. A total of 402 differentially expressed genes (DEGs) were obtained from GSE38713. Annotating, visualizing, and integrating discovery of these differential genes was performed using Gene Ontology (GO), Kyoto Gene and Genome Encyclopedia Pathway (KEGG), and Gene Set Enrichment Analysis (GSEA). Protein–protein interaction networks were constructed from the STRING database, and protein functional modules were identified using the CytoHubba plugin of Cytoscape. Random forest and LASSO regression were used to screen for UC-related diagnostic markers, and ROC curves were generated to validate their diagnostic value. The composition of 22 immune cells was analyzed, and the immune cell infiltration in UC was analyzed using CIBERSORT. Results: Seven diagnostic markers associated with UC were identified: TLCD3A, KLF9, EFNA1, NAAA,WDR4, CKAP4, and CHRNA1. Immune cell infiltration assessment revealed that macrophages M1, activated dendritic cells, and neutrophil cells infiltrated relatively more compared to normal control samples. Our results suggest a new functional feature of UC and suggest potential biomarkers for UC through comprehensive analysis of integrated gene expression data.

Novel biomarkers for neoplastic progression from ulcerative colitis to colorectal cancer: a systems biology approach

In recent studies, the void of evaluation and in-depth understanding of unknown clinically relevant potential molecular biomarkers involved in colorectal cancer (CRC) from the inflammatory stage of ulcerative colitis (UC) to CRC metastasis, which can be suitable therapeutic targets, is deeply felt. The regulation and interaction among different cancer-promoting molecules, including messenger RNAs (mRNAs) and micro RNAs (miRNAs) in CRC and its progression, were the aim we pursued in this study. Using microarray data, we investigated the differential expression for five datasets, including mRNA and microRNA samples related to UC, tumor/normal. Then, using robust data analysis, separate lists of differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) were identified, which were used for robust rank aggregation (RRA) and co-expression network analysis. Then, comprehensive computational systems biology analyses, including gene ontology and Kyoto encyclopedia of genes and genomic pathway enrichment analyses, mRNA-miRNA regulatory network, and survival analysis, were employed to achieve the aim of this study. Finally, we used clinical samples to validate this potential and new target. According to this systems biology approach, a total of 98 DEGs and 8 DEmiRNAs with common differential expression were identified. By combining the distinct results of RRA and network, several potential therapeutic targets, and predictive and prognostic biomarkers for UC and CRC were identified. These targets include six common hub genes, CXCL1, CXCL8, MMP7, SLCA16A9, PLAU, and TIMP1, which are upregulated. Among these, the important and new biomarker SLC16A9 is negatively regulated by hsa-mir-194-5p, and hsa-miR-378a-5p take. The findings of the present study provide new insight into the pathogenesis of CRC in UC. Our study suggests future evaluation of the functional role of SLC16A9 and hsa-mir-194-5p and hsa-miR-378a-5p in CRC development.

P250 The impact of Primary Sclerosing Cholangitis (PSC) on fecal calprotectin assessment in individuals with Inflammatory Bowel Disease (IBD)

Abstract Background Fecal calprotectin (FCP) is recommended as a non-invasive biomarker in ulcerative colitis (UC); however, the accuracy of FCP in individuals with concurrent primary sclerosing cholangitis (PSC) is less understood due to biliary fluid calprotectin excretion in PSC. We aimed to determine the relationship of endoscopic disease activity to FCP levels in individuals with PSC and colitis (PSC-IBD) compared to individuals with UC alone. Methods Individuals with PSC-IBD and UC controls who underwent colonoscopy at a large tertiary academic medical center. Controls with similar UC extent were selected in a 2:1 ratio. Mayo endoscopic scores (MES) were derived from the endoscopic database. If no prospective score was recorded, images were reviewed by two investigators with adjudicated discrepancies. Disease characteristics, baseline demographics, FCP (within 6 months of endoscopy), and C-reactive protein (CRP) were derived from the electronic medical record. Exclusion criteria included Crohn's disease or non-IBD colitis, infectious colitis, treatment change between endoscopy and FCP measurement, and colonic resection. Mean FCPs and standard deviations (SDs) were calculated, stratified by PSC status and MES. Multivariable linear regression was employed to assess the association of PSC on FCP adjusting for MES, age, alkaline phosphatase (ALP), and disease location. Results 264 colonoscopies for 197 patients (mean age 48, 61% males, 97% extensive disease) were identified with corresponding FCP from 2013 to 2022. Compared to UC controls, there were more males in the PSC-IBD cohort; MES did not differ significantly between the two groups (Table 1). There was no significant difference in mean FCP in PSC-IBD compared to UC controls (314.7 vs 284.5, p=0.56). Mean FCP increased with increasing MES (Table 2). There was no significant difference in mean FCP between those with PSC and those without when stratified by MES (Table 3). In multivariable linear regression, left-sided disease extent, MES, and ALP were independently associated with increasing FCP (Table 4). Conclusion In this cohort, a diagnosis of PSC was not associated with significant differences in FCP for IBD patients when stratified by MES. These data suggest that FCP remains a reliable marker of colitis activity in IBD patients with and without PSC. Further research is required to understand the role of PSC activity in modulating FCP concentrations.

Exploration of the shared pathways and common biomarker PAN3 in ankylosing spondylitis and ulcerative colitis using integrated bioinformatics analysis.

Ulcerative colitis (UC) is a chronic autoimmune-related disease that causes inflammation of the intestine. Ankylosing spondylitis (AS) is a common extraintestinal complication of UC involving the sacroiliac joint. However, the pathogenesis of AS secondary to UC has not been studied. This study aimed to investigate the shared pathways and potential common biomarkers of UC and AS. Microarray data downloaded from the Gene Expression Omnibus (GEO) database were used to screen differentially expressed genes (DEGs) in the UC and AS datasets. Weighted gene co-expression network analysis (WGCNA) was performed to identify co-expression modules related to UC and AS. Shared genes were then further analyzed for functional pathway enrichment. Next, the optimal common biomarker was selected using SVM-RFF and further validated using two independent GEO datasets. Finally, immune infiltration analysis was used to investigate the correlation of immune cell infiltration with common biomarkers in UC and AS. A total of 4428 and 2438 DEGs in UC and AS, respectively, were screened. Four modules were identified as significant for UC and AS using WGCNA. A total of 25 genes overlapped with the strongest positive and negative modules of UC and AS. KEGG analysis showed these genes may be involved in the mitogen-activated protein kinase (MAPK) signaling pathway. GO analysis indicated that these genes were significantly enriched for RNA localization. PAN3 was selected as the optimal common biomarker for UC and AS. Immune infiltration analysis showed that the expression of PAN3 was correlated with changes in immune cells. This study first explored the common pathways and genetic diagnostic markers involved in UC and AS using bioinformatic analysis. Results suggest that the MAPK signaling pathway may be associated with both pathogeneses and that PAN3 may be a potential diagnostic marker for patients with UC complicated by AS.

Novel Utility of Leucine-Rich Alpha-2-Glycoprotein as a Biomarker in Ulcerative Colitis: A Predictor of Endoscopic Remission Independent of Symptoms

Introduction: Leucine-rich alpha-2-glycoprotein (LRG) is a potential biomarker for disease activity and reflects mucosal healing in patients with ulcerative colitis (UC). However, only a few studies have described a detailed sensitivity analysis of LRG in predicting mucosal healing in patients. This study aimed to evaluate the association between LRG and the endoscopic activity of UC and its predictability for mucosal healing and explore the utility and clinical application of LRG. Methods: The diagnostic accuracy of biomarkers, including LRG, in predicting the endoscopic activity of UC was evaluated. All consecutive patients who underwent total colonoscopy between April 2021 and September 2022 were included. The Mayo endoscopic subscore (MES) was used for assessing endoscopic activity. Furthermore, endoscopic remission was defined as an MES of ≤1. Clinical activity was evaluated based on stool frequency and bloody stool. Receiver operating characteristic curve analysis and binary logistic regression were performed to assess the diagnostic accuracy of the biomarkers. We evaluated LRG trends and treatment response in patients with MES ≥2 who underwent induction therapy. Results: This study comprised 214 patients. The proportions of endoscopically and clinically active patients were 33.6% and 49.1%, respectively. LRG had an area under the curve (AUC) of 0.856, with a higher diagnostic accuracy than other biomarkers, such as C-reactive protein, leukocyte, neutrophil, platelet, and albumin. The cutoff value for LRG was 15.6 μg/mL (sensitivity, 72.2%; specificity, 86.6%). Using the MES, patients with higher scores had higher LRG levels than those with lower scores. The cutoff value, AUC, sensitivity, and specificity varied with a higher AUC for left-sided colitis and pancolitis than for proctitis. Logistic regression analysis showed that LRG was an independent predictor of endoscopic remission using multivariate analysis, even with the factor of clinical activity. The change ratio of LRG pre- and post-treatment was statistically significant in the higher LRG group. Conclusion: LRG reflected endoscopic activity independently, regardless of clinical symptoms. An LRG below the cutoff value could indicate a significantly low probability of endoscopic activity in asymptomatic patients, and follow-up endoscopy (not for cancer screening) may be unnecessary. Furthermore, a higher LRG level might be more useful as an indicator of treatment efficacy.

Identifying biomarkers associated with the diagnosis of ulcerative colitis via bioinformatics and machine learning.

Ulcerative colitis (UC) is an idiopathic inflammatory disease with an increasing incidence. This study aimed to identify potential UC biomarkers and associated immune infiltration characteristics. Two datasets (GSE87473 and GSE92415) were merged to obtain 193 UC samples and 42 normal samples. Using R, differentially expressed genes (DEGs) between UC and normal samples were filtered out, and their biological functions were investigated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Promising biomarkers were identified using least absolute shrinkage selector operator regression and support vector machine recursive feature elimination, and their diagnostic efficacy was evaluated through receiver operating characteristic (ROC) curves. Finally, CIBERSORT was used to investigate the immune infiltration characteristics in UC, and the relationship between the identified biomarkers and various immune cells was examined. We found 102 DEGs, of which 64 were significantly upregulated, and 38 were significantly downregulated. The DEGs were enriched in pathways associated with interleukin-17, cytokine-cytokine receptor interaction and viral protein interactions with cytokines and cytokine receptors, among others. Using machine learning methods and ROC tests, we confirmed DUOX2, DMBT1, CYP2B7P, PITX2 and DEFB1 to be essential diagnostic genes for UC. Immune cell infiltration analysis revealed that all five diagnostic genes were correlated with regulatory T cells, CD8 T cells, activated and resting memory CD4 T cells, activated natural killer cells, neutrophils, activated and resting mast cells, activated and resting dendritic cells and M0, M1 and M2 macrophages. DUOX2, DMBT1, CYP2B7P, PITX2 and DEFB1 were identified as prospective biomarkers for UC. A new perspective on understanding the progression of UC may be provided by these biomarkers and their relationship with immune cell infiltration.

Single-cell and microarray chip analysis revealed the underlying pathogenesis of ulcerative colitis and validated model genes in diagnosis and drug response

The morbidity rate of ulcerative colitis (UC) in the world is increasing year by year, recurrent episodes of diarrhea, mucopurulent and bloody stools, and abdominal pain are the main symptoms, reducing the quality of life of the patient and affecting the productivity of the society. In this study, we sought to develop robust diagnostic biomarkers for UC, to uncover potential targets for anti-TNF-ɑ drugs, and to investigate their associated pathway mechanisms. We collected single-cell expression profile data from 9 UC or healthy samples and performed cell annotation and cell communication analysis. Revealing the possible pathogenesis of ulcerative colitis by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) analysis. Based on the disease-related modules obtained from weighted correlation network analysis (WGCNA) analysis, we used Lasso regression analysis and random forest algorithm to identify the genes with the greatest impact on disease (EPB41L3, HSD17B3, NDRG1, PDIA5, TRPV3) and further validated the diagnostic value of the model genes by various means. To further explore the relationship and mechanism between model genes and drug sensitivity, we collected gene expression profiles of 185 UC patients before receiving anti-tumor necrosis factor drugs, and we performed functional analysis based on the results of differential analysis between NR tissues and R tissues, and used single-sample GSEA (ssGSEA) and CIBERSORT algorithms to explore the important role of immune microenvironment on drug sensitivity. The results suggest that our model is not only helpful in aiding diagnosis, but also has implications for predicting drug efficacy; in addition, model genes may influence drug sensitivity by affecting immune cells. We suggest that this study has developed a diagnostic model with higher specificity and sensitivity, and also provides suggestions for clinical administration and drug efficacy prediction.

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.

S780 Impact of Ozanimod on Fecal Calprotectin Levels and the Association With Efficacy in Patients With Moderately to Severely Active Ulcerative Colitis: Results From the Phase 3 True North Study

Introduction: Ozanimod (OZA) is approved in the USA and EU for the treatment of moderate/severe ulcerative colitis (UC). OZA demonstrated efficacy in the phase 3 True North (TN) trial in patients (pts) with moderate/severe UC (NCT02435992). Infiltration of neutrophils in intestinal mucosa contributes to inflammation in inflammatory bowel diseases. Calprotectin, which is released by neutrophils, is a neutrophilic activity marker that is useful in monitoring UC disease activity. Methods: We assessed the effect of OZA on fecal calprotectin (FCP) levels and association with OZA efficacy in TN. During the 10-week (W) induction period, pts were randomized to double-blind (DB) OZA 0.92 mg or placebo (PBO) once daily (Cohort 1) or received open-label (OL) OZA once daily (Cohort 2). Pts with clinical response (CRS) to OZA at W10 were rerandomized to DB OZA or PBO for maintenance through W52. Efficacy endpoints (clinical remission, CRS, endoscopic improvement, mucosal healing, and histologic remission) and FCP levels were assessed at W10 and W52. Results: Change in FCP from baseline (BL) to W10 was assessed in 517 pts who received DB OZA (n=347) or PBO (n=170) and 293 who received OL OZA. Pts on OZA demonstrated reductions from BL in FCP at W10; this was significant vs PBO (P< .001, both cohorts) (Table). FCP reductions were significantly greater in pts with vs without CRS at W10 in all treatment groups (P< .001, all groups). Change in FCP from BL to W52 was assessed in 149 pts remaining on OZA and 109 who switched to PBO. FCP levels remained low through W52; pts on continuous OZA had significantly greater FCP reductions at W52 vs pts who switched to PBO (P=.0002). FCP reductions were significantly greater in pts with vs without CRS at W52 in OZA-OZA and OZA-PBO groups (P< .01, for both). Significantly greater reductions from BL in FCP occurred with OZA vs PBO at W10 and W52 regardless of prior biologic or tumor necrosis factor inhibitor exposure (P< .05, all groups). BL FCP level was predictive for CRS and histologic remission at W10 (P< .05, both endpoints). Reduction from BL in FCP at W10 was predictive and prognostic for all endpoints except CRS at W52 (P< .05, all endpoints). Conclusion: OZA treatment led to FCP reductions, indicative of decreases in intestinal neutrophil levels. BL FCP was predictive for OZA response. FCP reductions were predictive for OZA response and prognostic for UC. These findings may support use of FCP as a predictive biomarker for OZA response and prognostic biomarker in UC. Table 1. - Change from baseline in FCP at Weeks 10 and 52 FCP adjusted mean percent change (95% CI) Induction (Week 10) Maintenance (Week 52) Cohort 1 Cohort 2 Placebo (n=170) Ozanimod (n=347) Ozanimod (n=293) Ozanimod-placebo (n=109) Ozanimod-ozanimod (n=149) All patients 18.8 (-11.6, 59.6) -59.3 (-67.1, -49.7) -71.6 (-77.2, -64.5) -70.7 (-79.6, -57.7) -87.7 (-91.0, -83.3) Responders a -48.7 (-68.7, -16.0) -83.9 (-87.8, -78.8) -86.2 (-89.5, -81.8) -81.5 (-87.8, -71.7) -91.0 (-93.7, -87.1) Nonresponders b 54.9 (12.4, 113.5) -12.1 (-32.4, 14.4) -33.3 (-50.9, -9.5) -10.5 (-53.6, 72.9) -75.4 (-85.9, -57.2) aResponders during induction are pts who achieved CRS at W10, and responders during maintenance are pts who achieved CRS at W52.bNonresponders during induction are pts who did not achieve CRS at W10 and nonresponders at W52 did not achieve CRS at W52.

Effect of disease duration on fecal biomarkers in ulcerative colitis: a prospective cohort study

BackgroundBiomarkers such as fecal calprotectin (FC) and fecal immunochemical occult blood tests (FIT) for ulcerative colitis (UC) are used in clinical practice. In this study, the effect of UC disease duration on FC was investigated and compared to that on FIT.MethodsOne hundred twenty-eight colonoscopic examinations and two fecal biomarkers measurements were performed. The cases of UC were divided into short- and long-term disease-duration groups or categorized into three groups with disease durations of 0–5, 6–13, and 14–38 years. We analyzed correlations between biomarker levels and endoscopic scores, including the Mayo endoscopic subscore (MES), ulcerative colitis endoscopic index of severity, and the sum of MES.ResultsIn the analysis of short- and long-term disease durations, the three endoscopic scores and biomarker levels showed significant correlations in both long-term and short-term groups. Most of the correlation coefficients for the individual long-term group were lower than the corresponding values for all cases, while most of the correlation coefficients for the individual short-term groups were higher than the corresponding values for all cases. In the three-group analysis (disease durations of 0–5, 6–13, and 14–38 years), the two biomarkers and three endoscopic scores showed significant correlations, and most of the correlation coefficients between biomarkers and endoscopic scores tended to be lower in the long-term follow-up group. In the receiver operating characteristic analysis for predicting mucosal healing in the three groups, the area under the curve for FC and FIT concentrations in the 0–5 year disease-duration group showed particularly higher values than those for the other two groups.ConclusionsSimilar to FIT, FC is affected by the duration of UC, indicating that FC may be a highly useful biomarker, especially in short-term disease.

Construction, bioinformatics analysis, and validation of competitive endogenous RNA networks in ulcerative colitis.

Background: Ulcerative colitis (UC) is a common chronic disease of the digestive system. Recently, competitive endogenous RNAs (ceRNAs) have been increasingly used to reveal key mechanisms for the pathogenesis and treatment of UC. However, the role of ceRNA in UC pathogenesis has not been fully clarified. This study aimed to explore the mechanism of the lncRNA-miRNA-mRNA ceRNA network in UC and identify potential biomarkers and therapeutic targets. Materials and Methods: An integrative analysis of mRNA, microRNA (miRNA), and long non-coding RNA (lncRNA) files downloaded from the Gene Expression Omnibus (GEO) was performed. Differentially expressed mRNA (DE-mRNAs), miRNA (DE-miRNAs), and lncRNA (DE-lncRNAs) were investigated between the normal and UC groups by the limma package. A weighted correlation network analysis (WGCNA) was used to identify the relative model for constructing the ceRNA network, and, concurrently, miRWalk and DIANA-LncBase databases were used for target prediction. Consecutively, the Gene Ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) pathway, and Reactome pathway enrichment analyses, protein-protein interaction (PPI) network, Cytohubba, and ClueGO were performed to identify hub genes. Additionally, we examined the immune infiltration characteristics of UC and the correlation between hub genes and immune cells using the immuCellAI database. Finally, the expression of potential biomarkers of ceRNA was validated via qRT-PCR in an experimental UC model induced by dextran sulfate sodium (DSS). Result: The ceRNA network was constructed by combining four mRNAs, two miRNAs, and two lncRNAs, and the receiver operating characteristic (ROC) analysis showed that two mRNAs (CTLA4 and STAT1) had high diagnostic accuracy (area under the curve [AUC] > 0.9). Furthermore, CTLA4 up-regulation was positively correlated with the infiltration of immune cells. Finally, as a result of this DSS-induced experimental UC model, CTLA4, MIAT, and several associate genes expression were consistent with the results of previous bioinformatics analysis, which proved our hypothesis. Conclusion: The investigation of the ceRNA network in this study could provide insight into UC pathogenesis. CTLA4, which has immune-related properties, can be a potential biomarker in UC, and MIAT/miR-422a/CTLA4 ceRNA networks may play important roles in UC.

A Selective and Sensitive LC-MS/MS Method for Quantitation of Indole in Mouse Serum and Tissues.

Indole is an endogenous substance currently being evaluated as a biomarker for ulcerative colitis, irritable bowel syndrome, Crohn’s disease and non-alcoholic fatty liver disease. A novel, selective, and sensitive method using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) was developed for quantitation of indole concentrations in mouse plasma and tissues. Samples were prepared by protein precipitation using ice-cold acetonitrile (ACN) followed by injecting the extracted analyte to LC-MS/MS system. Indole was separated using Synergi Fusion C18 (4 µm, 250 × 2.0 mm) column with mobile phase 0.1% aqueous formic acid (A) and methanol (B) using gradient flow with run time 12 min. The mass spectrometer was operated in atmospheric pressure chemical ionization (APCI) positive mode at unit resolution in multiple reaction monitoring (MRM) mode, using precursor ion > product ion combinations of 118.1 > 91.1 m/z for indole and 124.15 > 96.1 m/z for internal standard (IS) indole d7. The MS/MS response was linear over the range of indole concentrations (1–500 ng/mL). The validated method was applied for quantitation of indole concentrations range in mouse lungs (4.3–69.4 ng/g), serum (0.8–38.7 ng/mL) and cecum (1043.8–12,124.4 ng/g). This method would help investigate the role of indole as a biomarker and understand its implications in different disease states.

Identification of Potential Biomarkers and Immune Infiltration Characteristics in Ulcerative Colitis by Combining Results from Two Machine Learning Algorithms.

Objective This study was designed to identify potential biomarkers for ulcerative colitis (UC) and analyze the immune infiltration characteristics in UC. Methods Datasets containing human UC and normal control tissues (GSE87466, GSE107597, and GSE13367) were downloaded from the GEO database. Then, the GSE87466 and GSE107597 datasets were merged, and the differentially expressed genes (DEGs) between UC and normal control tissues were screened out by the “limma R” package. The LASSO regression model and support vector machine recursive feature elimination (SVM-RFE) were performed to screen out the best biomarkers. The GSE13367 dataset was used as a validation cohort, and the receiver operating characteristic curve (ROC) was used to evaluate the diagnostic performance. Finally, the immune infiltration characteristics in UC were explored by CIBERSORT, and we further analyzed the correlation between potential biomarkers and different immune cells. Results A total of 76 DEGs were screened out, among which 56 genes were upregulated and 20 genes were downregulated. Functional enrichment analysis revealed that these DEGs were mainly involved in immune response, chemokine signaling, IL−17 signaling, cytokine receptor interactions, inflammatory bowel disease, etc. ABCG2, HSPB3, SLC6A14, and VNN1 were identified as potential biomarkers for UC and validated in the GSE13367 dataset (AUC = 0.889, 95% CI: 0.797~0.961). Immune infiltration analysis by CIBERSORT revealed that there were significant differences in immune infiltration characteristics between UC and normal control tissues. A high level of memory B cells, γδ T cells, activated mast cells, M1 macrophages, neutrophils, etc. were found in the UC group, while a high level of M2 type macrophages, resting mast cells, eosinophils, CD8+ T cells, etc. were found in the normal control group. Conclusion ABCG2, HSPB3, SLC6A14, and VNN 1 were identified as potential biomarkers for UC. There was an obvious difference in immune infiltration between UC and normal control tissues, which may provide help to guide individualized treatment and develop new research directions.