Screening method and application of ulcerative colitis biomarker

Abstract

The invention discloses a screening method and application of an ulcerative colitis biomarker, EPHX2 can be used as a biomarker for ulcerative colitis detection, provides a new technical means for ulcerative colitis detection, diagnosis, treatment and prognosis evaluation, provides a new direction for research of UC pathogenesis, and provides a new application prospect. And a new possibility is provided for clinical treatment.

Description

Technical Field

[0001] The present invention relates to the field of medical technology, and in particular to a method for screening a biomarker of ulcerative colitis and an application thereof. Background Art

[0002] Ulcerative colitis (UC) is a chronic inflammatory bowel disease with a prevalence of up to 5 million. It is characterized by alternating relapses and remissions, and the lesions usually involve the rectum and colon. Common clinical symptoms of ulcerative colitis are blood in the stool, abdominal pain, and weight loss, which can affect the patient's quality of life or induce intestinal cancer in the long run. However, the pathogenesis of ulcerative colitis is not clear. It is regulated by multiple factors such as environmental influences, genetic factors, damaged intestinal mucosal barrier, and immune disorders. Influenced by the genetic structure of UC itself, genetic factors play an important role in the pathogenesis of UC. As early as 2012, a study on IBD found that there are 163 susceptibility gene loci for IBD, of which 110 genes are shared susceptibility genes for UC and CD, and the other 53 loci are disease-specific. In a recent large-scale cross-ethnic IBD study, the number of IBD genetic loci increased to 240. These susceptibility genes not only affect the occurrence of the disease, but also affect the treatment effect. Further elucidation of the mechanism of UC disease genes is conducive to providing new directions for the treatment of UC.

[0003] Mucosal healing is the ultimate goal of clinical treatment of UC. The intestinal mucosal barrier is mainly regulated by intestinal epithelial cells (IECs), which maintain intestinal homeostasis by separating intestinal flora and immune cells. Intestinal epithelial cells are the fastest self-renewing tissue in adult mammals and are composed of intestinal cells of different lineages and functions. IECs are composed of absorptive intestinal epithelial cells, goblet cells, Paneth cells, and enteroendocrine cells, maintaining the "first line of defense." Studies have shown that the degree of inflammation in the lesion site of UC patients is proportional to the degree of damage to the tight junction structure of the mucosa; it is also related to changes in the thickness and composition of the mucus layer.

[0004] Studies have reported that EPHX2 affects the occurrence of familial hyperlipidemia and Alzheimer's disease as a disease gene. At the same time, based on early biological studies on EPHX2, it was found that EPHX2 is a member of the oxidase hydrolase family and is involved in lipid metabolism. CN118086507A discloses an application of EPHX2 as a colon cancer marker and a colon cancer detection kit. EPHX2 may be used as a biomarker for colon cancer detection, providing a new technical means for colon cancer detection, diagnosis, treatment and prognosis evaluation. Summary of the invention

[0005] The purpose of the present invention is to provide a method for screening a biomarker for ulcerative colitis and its application. EPHX2 can be used as a biomarker for the detection of ulcerative colitis, providing a new technical means for the detection, diagnosis, treatment and prognosis evaluation of ulcerative colitis, providing a new direction for studying the pathogenesis of UC, and providing new possibilities for clinical treatment.

[0006] The technical solution adopted by the present invention to solve its technical problem is: A method for screening biomarkers for ulcerative colitis comprises the following steps: (1) Using the GEO public database, we screened out the ulcerative colitis-related gene expression profile datasets: GSE73661 and GSE92415; and downloaded relevant expression data and clinical information from the GEO database; (2) The limma package was used to perform differential analysis on the gene expression levels of samples from GSE73661 and GSE92415 between the normal group and the UC group, and the intersection analysis of the up-regulated and down-regulated differentially expressed genes screened out from the two datasets was performed to screen out the common differentially expressed DEGs; (3) Download the UC-related GWAS dataset using the GEO public database, find the independent gene loci of UC through GWAS, and screen out independent pathogenic genes through eQTL analysis; cross-analyze the screened independent pathogenic genes and the common differentially expressed genes DEGs to screen out the main pathogenic genes. (4) Using the single-cell sequencing dataset GSE214695, we performed localization analysis on the main pathogenic genes and screened out EPHX2, EDN3, and SULT1A2, which were specifically differentially expressed in intestinal epithelial cells. Then, we mapped EDN3, EPHX2, and SULT1A2 to cell subpopulations. EPHX2 had the widest coverage, and was initially selected. (5) We constructed colitis mouse and cell inflammation models, verified that EPHX2 had significant expression differences in ulcerative colitis, and identified EPHX2 as a biomarker for ulcerative colitis.

[0007] In step (1), the data set contains at least 20 patients with ulcerative colitis who have not received any treatment and 20 healthy people.

[0008] In step (2), the limma package was used to perform differential analysis of gene expression between the normal group and the UC group for the samples of GSE73661 and GSE92415: the screening threshold was a logFC absolute value greater than 1 and a corrected p value less than 0.05.

[0009] Application of EPHX2 as a biomarker for ulcerative colitis. EPHX2 has the widest coverage in epithelial cells. Functional enrichment analysis showed that EPHX2 can affect the damage and repair function of the intestinal mucosal barrier. In vitro experiments showed that EPHX2 can indeed affect wound damage repair.

[0010] Application of EPHX2 in preparing animal model of ulcerative colitis.

[0011] A kit for detecting ulcerative colitis comprises a reagent for detecting the expression amount of EPHX2.

[0012] The beneficial effects of the present invention are: EPHX2 can be used as a biomarker for the detection of ulcerative colitis, providing a new technical means for the detection, diagnosis, treatment and prognosis evaluation of ulcerative colitis, providing a new direction for studying the pathogenesis of UC, and providing new possibilities for clinical treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a Venn diagram of the relationship between DEG and SMR. Differentially expressed genes Differentially expressed genes, Summary-data-based Mendelian Randomization (SMR) Mendelian randomization analysis.

[0014] Figure 2 It is a heat map of disease-related DEGs; in the disease state, the expression levels of these genes will change. Control (normal group); UC (ulcerative colitis group); Expression.

[0015] Figure 3 This is a graph showing the changes in the proportions of different cell subsets in healthy people and UC patients.

[0016] Figure 4This is the expression of EXPH2 in the colon tissue of mice with 3%DSS-induced colitis. AD: Differences in weight, stool blood score, and colon length between mice with 3%DSS-induced colitis and normal mice. Sacrificed; Day; DSS; water; stool blood score; weight; E: HE staining of colon sections of mice with 3%DSS-induced inflammation and normal mice (scale 250μm); F: Elisa detection of IL-6 and TNF-a expression levels in the plasma of mice with 3%DSS-induced inflammation and normal mice; G and H: Changes in the mRNA or protein expression levels of EXPH2 protein in the colon tissue of mice with 3%DSS-induced colitis were observed compared with normal mice (n=5). I: Using IHC, the expression of EPHX2 was observed in mice with 3%DSS-induced colitis and normal colon tissue (n=3).

[0017] Figure 5 is the expression of EPHX2 in NCM460 cells stimulated by inflammatory factors. Relative expression; no-flammation; inflammation. A and B: The expression of IL-6 and IL-8 in NCM460 cells stimulated by proinflammatory factors was detected by Elisa and RT-PCR. C: The mRNA expression of EPHX2 in NCM460 cells stimulated by proinflammatory factors. D: The protein expression of EPHX2 in NCM460 cells stimulated by proinflammatory cytokines. All data are mean ± SD (n=3), *P<0.05, **P<0.01, ***P<0.001protein expression.

[0018] Figure 6 is a functional enrichment diagram of EPHX2 that can affect mucosal injury repair through GSEA functional enrichment analysis; Ranked list (gene ranking); Enrichment score (enrichment score); Rank in Ordered DataSet (ranking value of the data set); NES (normalized enrichment score); Adjust Pvalue (adjusted p value).

[0019] Figure 7 is a diagram for the validation of the knockout efficiency of EPHX2 small interference. Data are expressed as mean ± SD (n=3), *P<0.05, **P<0.01, ***P<0.001.

[0020] Figure 8 is a comparison of the changes in wound healing ability after EPHX2 knockout compared with non-knockout. siEPHX2 (EPHX2 knockout); wound closure (wound healing index). DETAILED DESCRIPTION

[0021] The technical solution of the present invention is further described in detail below through specific embodiments.

[0022] In the present invention, unless otherwise specified, the raw materials and equipment used can be purchased from the market or are commonly used in the art. The methods in the following embodiments, unless otherwise specified, are all conventional methods in the art.

[0023] Embodiment 1: 1.1 Collection and processing of raw gene expression profiles According to the processing of previous research data sets related to UC, the data sets were screened and preprocessed to ensure that the screened data sets met the basic requirements. The basic requirements are as follows: 1. CD (Crohn's disease) patients and patients taking medication are excluded. 2. The data set must contain at least 20 UC patients who have not received any treatment and 20 healthy people. 3. The data set needs to contain relevant basic clinical information and gene expression matrix. Based on this, we selected two UC-related gene expression profile data sets, GSE73661 and GSE92415, in the GEO database (https: / / www.ncbi.nlm.nih.gov / GEO / ). The original CEL file was read and rma standardized using the affy package in the R-4.2.2 software, and the probe gene name conversion was performed using the hubene10sttranscriptcluster.db package.

[0024] 1.2 Genome-wide association analysis We selected the UC-related GWAS dataset from the openGWAS database: ieu-a-970 (https: / / gwas.mrcieu.ac.uk / datasets / ieu-a-970 / ). Using R4.2.2 software, we used VariantAnnotation combined with gwasglue to read the vcf file and convert the data format for TwoSampleMR analysis. We then used the clump_data function of TwoSampleMR to perform linkage disequilibrium analysis on the sites with p<0.0001 in the above results to find relatively independent sites. The threshold: the clustering window size was limited to 10,000 kb, and the LD value was 0.2.

[0025] 1.3 RNA-seq data analysis The Seurat package in R4.2.2 software was used to read the expression data and cell annotation data of GSE214695, extract the expression data corresponding to the cell annotation data, construct the Seurat object, and use harmony to correct the batch effect between samples. Finally, the UMAP and TSNE dimension coordinates corresponding to the PC obtained by PCA analysis were calculated, and the results were visualized.

[0026] 1.4 Animals Twelve specific pathogen-free (SPF) C57BL / 6 mice (wild type, female, 6 weeks old) were obtained from Hangzhou Qizhen Biotechnology Co., Ltd., ethics number: ZH20231029029. Before the start of the experiment, the animals were given free access to water and food for one week to adapt to the breeding environment. The animal experiment protocol was approved by the Animal Ethics Committee of Zhejiang Provincial People's Hospital.

[0027] 1.5 Construction of DSS-induced colitis model C57BL / 6 mice were randomly divided into a normal drinking water group (n=6) and a DSS group (n=6). To construct a colitis mouse model, the DSS mouse group was given drinking water containing 3% (W / V) dextran sulfate sodium (DSS, molecular weight, 36-50kDa; MP Biomedicals) for 7 days. The control group and the experimental group received regular diet and drinking water during the experiment. The daily body weight of the mice was recorded, and the DAI scoring standard (Table 2) was used for individual scoring, including the degree of weight loss, the degree of bloody stool (Yisheng, 60403ES60), and the consistency of stool. After 7 days, the mice were killed by cervical dislocation, orbital blood was collected, the colon was removed, and the length of the colon was measured.

[0028] 1.6 ELISA to detect inflammatory factors Blood was collected from the orbits of DSS mice and centrifuged at 2000 g for 5 min. The supernatant was collected for ELISA to analyze the expression of IL-6 (Lianke, 70-EK206 / 3-96) and TNF-α (70-EK282 / 3-96).

[0029] 1.7 Western blotting Protein was extracted from colon tissue, cell lysate was prepared with RIPA lysis buffer (Beijing Pulilai, C1053), and protein was quantified by BCA protein quantification method. Protein was separated by 10% SDS-PAGE and transferred to PVDF membrane (Millipore, Bedford), which was blocked with 5% skim milk at room temperature for 1 hour. The membrane was treated with Lgr5 (Affinity, DF2816), EPHX2 (Proteintech, 10833-1-AP), and β-actin (Proteintech, 20536-1-AP) at 4°C overnight. The next day, after washing three times with TBST (Servicebio), the membrane was incubated with HRP-linked secondary antibody (Beyotime, A0208; Beyotime, A0216) at room temperature for 1 hour. After washing three times with TBST again, the membrane was developed with enhanced chemiluminescence (ECL luminescent solution, for biological industry, Beit Haemek, Israel).

[0030] 1.8 Cell culture and treatment Human normal colon epithelial cell line NCM460 was purchased from INCELL Corporation (San Antonio, TX, USA). NCM460 cells were cultured in RPMI-1640 (Roswell Park Memorial Institute 1640) containing 10% fetal bovine serum (Fetal Bovine Serum) and 1% penicillin-streptomycin (Sangon Biotech). The culture environment was a 37°C constant temperature incubator with a sterile 5% CO2 concentration.

[0031] NCM460 cells were seeded into 6-well plates (1.5 × 10 5 / well), give complete culture medium, and transfer NC or EPHX2 siRNA (Heyuan Biotechnology) after the cells are completely attached. Replace the culture medium after 24 hours, and the cells can be used for subsequent experiments after 48 hours.

[0032] 1.9 In vitro wound healing assay The cells constructed with NC and EPHX2 siRNA were inoculated into 24-well culture plates (1×10 5 / well) and placed in a 37°C, 5% CO2 incubator for 24 hours. Use a 200ul pipette tip to scrape the surface of the inoculated cells and mark the position, wash with PBS, and take pictures at 0h and 24h. Use Image J software to calculate the distance of cell migration and perform statistical analysis.

[0033] 1.10 Statistical analysis All data are expressed as mean ± standard deviation (SD). GraphPad Prism software was used for statistical analysis, and unpaired two-tailed T test was performed between the two experimental groups. P value < 0.05 indicates a statistically significant difference, * indicates P < 0.05; ** indicates P < 0.01; *** indicates P < 0.001.

[0034] Embodiment 2: 2.1 UC-related DEGs Using the GEO public database, we screened out the ulcerative colitis-related gene expression profile datasets: GSE73661 and GSE92415. We also downloaded relevant expression data and clinical information from the GEO database. We used the limma package to analyze the differences between the normal group and the UC group for the gene expression levels of the samples of GSE73661 and GSE92415, respectively. The screening threshold was that the absolute value of logFC was greater than 1 and the corrected p value was less than 0.05. We performed an intersection analysis on the up-regulated and down-regulated differential genes of the two datasets, and obtained 348 up-regulated genes and 209 down-regulated genes.

[0035] 2.2 Identification of UC pathogenic genes using GWAS-eQTL method To explore the genetic factors of UC, we used smr Linux software to perform linkage disequilibrium analysis, map SNPs to genes, and identify genomic regions with independent linkage disequilibrium. The related mediating genes that affect the occurrence of the disease by site-mediated gene expression changes obtained by SMR analysis were intersected with the significantly up- and down-regulated genes to obtain the disease genes whose gene expression changes can affect the occurrence of UC and the intersection of DEGs ( Figure 1 Finally, we screened out 15 up-regulated pathogenic genes and 3 down-regulated pathogenic genes (Figure 2).

[0036] 2.3EPHX2 is significantly lower in UC and negatively correlated with IECs (intestinal epithelial cells) in UC The 18 pathogenic genes screened in 2.2 were projected into single-cell transcriptome sequencing (GSE214695) and localization analysis was performed. According to clinical guidelines: The ultimate treatment goal of UC is mucosal healing, and we will focus on epithelial cells. We downloaded single-cell data and clustered the cells using the TSNE algorithm based on the Seurat software package. All cells were divided into five categories: B cells and plasma cells, epithelial cells, bone marrow cells, stroma, and T cells. At the same time, the heat map shows the expression of different categories of cells. We found that intestinal epithelial cells were significantly downregulated in ulcerative colitis ( Figure 3). We found that only EPHX2, EDN3, and SULT1A2 were expressed in intestinal epithelial cells. EDN3, EPHX2, and SULT1A2 were then mapped to cell subsets. EPHX2 had the broadest coverage, and EPHX2 may have a more important role in UC.

[0037] 2.4 EPHX2 expression is downregulated in colitis mice For bioinformatics-based screening, we constructed a 3% DSS mouse inflammation model (n=6) to verify the expression of EPHX2 in colitis mice. Based on the weight, DAI score, colon length, and production of pro-inflammatory factors of mice, a colitis mouse model was successfully established ( Figure 4 AF). We found that EPHX2 was downregulated in colitis mice.

[0038] At the same time, we also used mixed inflammatory factors to treat NCM460 cells and constructed an in vitro cell model. We used mixed factors (TNF-α: IFN-γ: IL-1β = 50ng / ml: 50ng / ml: 25ng / ml) to stimulate NCM460 cells and detect the expression of IL-6 and IL-8 to determine the construction of the in vitro inflammatory model, and at the same time measured the mRNA and protein expression of EPHX2 in the in vitro model. The results showed that EPHX2 was significantly reduced at both mRNA and protein levels under the stimulation of mixed factors.

[0039] 2.5 EPHX2 expression is downregulated when stimulated by proinflammatory factors in vitro We established a cellular inflammation model to verify the expression of EPHX2, which is more conducive to functional studies. According to the model standards, we detected the expression of IL-8 and IL-6 to ensure the successful construction of the model ( Figure 5 A and 5B). Then, we extracted the mRNA and protein of the normal group and the inflammation group. This result is consistent with the differential expression of EPHX2 in colitis mice, and the abnormal expression of EPHX2 can be stimulated by proinflammatory factors (Figure 5C and 5D).

[0040] 2.6 EPHX2 expression affects healing ability and plays an important role in UC We can speculate that the expression of EPHX2 affects other cell subsets and induces a chain reaction in UC. To explore the function of EPHX2, GSEA was used to enrich the annotations of biological processes grouped by EPHX2 expression levels in GSE73661 and GSE92415. Then, GSEA was used to perform GO annotations on the enrichment of biological processes grouped by EPHX2 expression levels in GSE73661. We were surprised to find that EPHX2 affects mucosal healing (Figure 6), so we performed wound healing experiments to verify the function of EPHX2. We found that the loss of EPHXE2 expression affected the healing ability of the mucosa (Figures 7 and 8).

[0041] discuss: We used UC-related datasets (GSE73661 and GSE92415) in the GEO public database to screen DEGs. Functional enrichment analysis was performed on common DEGs in the two datasets to introduce the changes in biological functions caused by the occurrence of ulcerative colitis. According to the genetic structure of UC, we found independent gene loci of UC through GWAS, and analyzed which genes can affect the occurrence of colitis through gene expression through eQTL analysis. The independent pathogenic genes screened were cross-analyzed with DEGs, and 18 pathogenic genes were screened.

[0042] Aiming at the mucosal healing treatment target proposed in clinical guidelines, we performed cluster analysis using the single-cell sequencing dataset GSE214695. The results revealed EPHX2, EDN3, and SULT1A2. We found that EPHX2 is expressed in multiple epithelial cell subsets, which prompted us to study its role in UC.

[0043] Based on the treatment goal of clinical guidelines, mucosal healing, as the basis for analysis, we performed cluster analysis using the single-cell sequencing dataset GSE214695 and screened out EPHX2, EDN3, and SULT1A2. Further cell subset mapping showed that EPHX2 can be expressed in a variety of epithelial cell subsets, so we wanted to know whether EPHX2 plays an important role in UC. Therefore, we constructed colitis mice and cell inflammation models to verify the accuracy of bioinformatics in vivo and in vitro. We found that EPHX2 was downregulated in an inflammatory environment, which is consistent with our analysis results.

[0044] To further explore the potential disease responses mediated by EPHX2, we performed relevant functional analyses using bioinformatics and found that EPHX2 can affect mucosal healing. Therefore, we performed wound healing experiments in vitro. According to the experimental results, the loss of EPHX2 reduced the mucosal healing ability of IECs.

[0045] The above-described embodiment is only a preferred solution of the present invention and does not limit the present invention in any form. There are other variations and modifications without exceeding the technical solution described in the claims.

Claims

1. A method for screening biomarkers of ulcerative colitis, characterized in that: The following steps are involved: (1) Using the GEO public database, we screened out the ulcerative colitis-related gene expression profile datasets: GSE73661 and GSE92415; and downloaded relevant expression data and clinical information from the GEO database; (2) The limma package was used to perform differential analysis on the gene expression levels of samples from GSE73661 and GSE92415 between the normal group and the UC group, and the intersection analysis of the up-regulated and down-regulated differentially expressed genes screened out from the two datasets was performed to screen out the common differentially expressed DEGs; (3) Download the UC-related GWAS dataset using the GEO public database, find the independent gene loci of UC through GWAS, and screen out independent pathogenic genes through eQTL analysis; cross-analyze the screened independent pathogenic genes and the common differentially expressed genes DEGs to screen out the main pathogenic genes. (4) Using the single-cell sequencing dataset GSE214695, we performed localization analysis on the main pathogenic genes and screened out EPHX2, EDN3, and SULT1A2, which were specifically differentially expressed in intestinal epithelial cells. Then, we mapped EDN3, EPHX2, and SULT1A2 to cell subpopulations. EPHX2 had the widest coverage, and was initially selected. (5) We constructed colitis mouse and cell inflammation models, verified that EPHX2 had significant expression differences in ulcerative colitis, and identified EPHX2 as a biomarker for ulcerative colitis.

2. The method for screening biomarkers of ulcerative colitis according to claim 1, characterized in that: In step (1), the data set contains at least 20 patients with ulcerative colitis who have not received any treatment and 20 healthy people.

3. The method for screening biomarkers of ulcerative colitis according to claim 1, characterized in that: In step (2), the limma package was used to perform differential analysis of gene expression between the normal group and the UC group for the samples of GSE73661 and GSE92415: the screening threshold was a logFC absolute value greater than 1 and a corrected p value less than 0.

05.

4. Application of EPHX2 as a biomarker for ulcerative colitis.

5. Application of EPHX2 in preparing animal model of ulcerative colitis.

6. A kit for detecting ulcerative colitis, characterized in that: The invention comprises a reagent for detecting the expression amount of EPHX2.

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