Marker combination for predicting recurrence of ulcerative colitis and application

Abstract

The invention provides a marker combination for predicting recurrence of ulcerative colitis and application thereof, and particularly, the marker is at least one of SLC6A14, MUC-2 and Nanncy index. The marker can be used for diagnosis and recurrence prediction of ulcerative colitis, and especially has relatively strong detection capability for relieving and recurrence conditions of patients after clinical drug treatment.

Description

Technical Field

[0001] The present invention relates to the fields of biology and medicine, and particularly to markers for detecting and diagnosing ulcerative colitis and their applications. Background Art

[0002] Inflammatory Bowel Disease (IBD) is an intestinal inflammation and immune-related disease, which includes Ulcerative Colitis (UC) and Crohn's disease (CD). Among them, UC is the main form of IBD, with characteristics such as a long course, protracted illness, and progressive recurrence, seriously affecting the quality of life of patients.

[0003] Repeated attacks are a difficult point in the treatment of UC, and the damage of the mucosal barrier may be an important reason for the recurrence of UC. The true restoration of intestinal barrier function requires the epithelial cells to restore the state of tight junctions and restore the intestinal microecological balance. There is also an urgent need in the prior art to explore more accurate targets reflecting the pathological state of the disease to more accurately evaluate the condition, especially to predict the recurrence of the disease. Summary of the Invention

[0004] To achieve the above object, through immunohistochemical analysis of samples, the present application has discovered and identified markers related to the diagnosis and recurrence of ulcerative colitis, and further established a new detection system for UC in combination with the histological evaluation index of UC.

[0005] Specifically, the present application relates to the use of a marker in the preparation of a detection product for inflammatory bowel disease, wherein the marker is at least one of SLC6A14, MUC-2, and the Nancy index.

[0006] Further, the marker is any two of SLC6A14, MUC-2, and the Nancy index.

[0007] Further, the marker is SLC6A14, MUC-2, and the Nancy index.

[0008] Further, the detection product is used to detect the expression levels of SLC6A14 and / or MUC-2 in a sample, and / or to score the Nancy index of the sample.

[0009] Further, the sample includes tissues, cells, or secretions of a subject.

[0010] Further, the inflammatory bowel disease includes ulcerative colitis and Crohn's disease, preferably ulcerative colitis.

[0011] Furthermore, the detection product is used for the screening, diagnosis, recurrence prediction or treatment effect evaluation of inflammatory bowel disease, preferably for predicting the recurrence of inflammatory bowel disease.

[0012] This application also relates to a system for detecting inflammatory bowel disease in a subject, which includes:

[0013] An information acquisition module, which is used to obtain marker information data in a sample; and

[0014] An analysis and calculation module, which is used to form a prediction probability as an analysis index by establishing a logistic regression model for the marker information data obtained in the information acquisition module, and then establish an ROC curve to obtain the detection result of inflammatory bowel disease;

[0015] Wherein, the marker information includes at least one of the expression level of SLC6A14, the expression level of MUC-2, and the Nancy index score.

[0016] Furthermore, the marker information is any two of the expression level of SLC6A14, the expression level of MUC-2, and the Nancy index score.

[0017] Furthermore, the marker information is the expression level of SLC6A14, the expression level of MUC-2, and the Nancy index score.

[0018] Furthermore, the sample includes the tissue, cells or secretions of the subject.

[0019] Furthermore, the inflammatory bowel disease includes ulcerative colitis and Crohn's disease, preferably ulcerative colitis.

[0020] Furthermore, the system is used for the screening, diagnosis, recurrence prediction or treatment effect evaluation of inflammatory bowel disease, preferably for predicting the recurrence of inflammatory bowel disease.

[0021] This application also relates to a kit, which includes: a reagent for detecting the expression level of SLC6A14, a reagent for detecting the expression level of MUC-2, and a reagent for scoring the Nancy index. Description of the Drawings

[0022] Figure 1 For the differential comparison of MUC-2 expression, SCL6A14 expression, and Nancy histological score between the recurrence and non-recurrence groups.

[0023] Figure 2 For the immunohistochemical staining pictures of MUC-2 and SCL6A14.

[0024] Figure 3 For the ROC curve (ROC1) of MUC-2 expression in the discovery cohort.

[0025] Figure 4 ROC curve (ROC2) for SLC6A14 expression in the discovery cohort.

[0026] Figure 5 ROC curve (ROC3) for the pathological Nancy histological score in the discovery cohort.

[0027] Figure 6 ROC curve (ROC4) for the combined analysis of MUC-2 and SLC6A14 in the discovery cohort.

[0028] Figure 7 ROC curve (ROC5) for the combined analysis of MUC-2 and the Nancy histological score in the discovery cohort.

[0029] Figure 8 ROC curve (ROC6) for the combined analysis of SLC6A14 and the Nancy histological score in the discovery cohort.

[0030] Figure 9 ROC curve (ROC7) for the combined analysis of MUC-2, SLC6A14, and the Nancy histological score in the discovery cohort.

[0031] Figure 10 ROC curve (ROC8) for MUC-2 expression in the validation cohort.

[0032] Figure 11 ROC curve (ROC9) for SLC6A14 expression in the validation cohort.

[0033] Figure 12 ROC curve (ROC10) for the pathological Nancy histological score in the validation cohort.

[0034] Figure 13 ROC curve (ROC11) for the combined analysis of MUC-2 and SLC6A14 in the validation cohort.

[0035] Figure 14 ROC curve (ROC12) for the combined analysis of MUC-2 and the Nancy histological score in the validation cohort.

[0036] Figure 15 ROC curve (ROC13) for the combined analysis of SLC6A14 and the Nancy histological score in the validation cohort.

[0037] Figure 16 ROC curve (ROC14) for the combined analysis of MUC-2, SLC6A14, and the Nancy histological score in the validation cohort. Detailed implementation manners

[0038] The following will elaborate and illustrate the implementation manners of the present invention through specific embodiments, but the following content should not be construed as any limitation to the present invention.

[0039] This application mainly relates to a detection marker for inflammatory bowel disease (IBD), and the marker is at least one of SLC6A14, MUC-2, and the Nancy index.

[0040] SLC6A14 in this application is a member 14 of solute carrier family 6 (amino acid transporter), and MUC-2 is mucin-2.

[0041] The Nancy index in this application, namely the Nancy histopathology index, can be used as an evaluation tool for histological healing in UC patients. The Nancy histopathology index includes three histological evaluation indicators: ulcer, acute inflammatory cell infiltration, and chronic inflammatory cell infiltration. According to the infiltration degree of acute and chronic inflammatory cells and the presence or absence of ulcers, the disease activity degree is divided into 5 disease activity levels from 0 (no histological inflammation activity) to 4 (severe active disease), and the Nancy index ≤ 1 is defined as histological healing. The specific scoring criteria are shown in Table 1.

[0042] Table 1: Nancy histological score

[0043]

[0044] In some specific implementation manners, the marker is any two of SLC6A14, MUC-2, and the Nancy index. For example, SLC6A14 and MUC-2, SLC6A14 and the Nancy index, or MUC-2 and the Nancy index are used in combination for detecting inflammatory bowel disease.

[0045] In a specific implementation manner, the marker is SLC6A14, MUC-2, and the Nancy index, that is, the three markers are used in combination for detecting inflammatory bowel disease.

[0046] This application further provides the use of the marker described in this application in preparing a detection product for inflammatory bowel disease.

[0047] In specific implementation manners, the marker is any one or any two or three of SLC6A14, MUC-2, and the Nancy index.

[0048] In a preferred implementation manner, the marker is SLC6A14, MUC-2, and the Nancy index.

[0049] In the present application, the expression levels of the markers SLC6A14 and MUC-2 and the score of the Nancy index can be used for the detection of inflammatory bowel disease.

[0050] In a specific embodiment, the detection product can be used to detect the expression levels of SLC6A14 and / or MUC-2 in a sample.

[0051] In a specific embodiment, the detection product can be used to score the Nancy index of a sample.

[0052] In the present application, the sample includes tissues, cells or secretions of a subject.

[0053] In a specific embodiment, the tissue includes colorectal tissue, for example, intestinal mucosa.

[0054] In a specific embodiment, the cells include lymphocytes, neutrophils or plasma cells, etc.

[0055] In a specific embodiment, the secretion includes intestinal mucus.

[0056] The markers and the detection product provided by the present application can be used to achieve screening, diagnosis, recurrence prediction or treatment effect evaluation of inflammatory bowel disease.

[0057] In a specific embodiment, it can be used for screening, diagnosis or auxiliary diagnosis of inflammatory bowel disease, predicting the onset and recurrence risks of inflammatory bowel disease, evaluating the administration or treatment effect of inflammatory bowel disease, etc.

[0058] In the present application, recurrence includes the recurrence of a past medical condition (inflammatory bowel disease), and the signs and symptoms of the condition resume after remission. Recurrence includes the situation where the signs and symptoms of the disease reappear after the disease has achieved clinical cure, complete remission or partial remission. For example, the disease symptoms reappear within a certain period after effective remission by drug treatment. Treatment effects include, but are not limited to, effects in preventing the occurrence or recurrence of the disease, relieving disease symptoms, weakening any direct or indirect pathological consequences of the disease, slowing down the rate of disease progression, improving or alleviating the disease state, etc.

[0059] In the present application, the inflammatory bowel disease includes ulcerative colitis (UC) and Crohn's disease (CD). In a preferred embodiment, the inflammatory bowel disease is UC.

[0060] In a specific embodiment, the markers SLC6A14, MUC-2 and the Nancy index can be used for the diagnosis, prediction or evaluation of ulcerative colitis recurrence.

[0061] In a specific embodiment, the subject is selected from mammals, preferably humans.

[0062] In a specific embodiment, the detection product is selected from reagents, reagent kits, test strips or diagnostic chips.

[0063] The present application further provides a system for detecting inflammatory bowel disease in a subject, comprising:

[0064] An information acquisition module for acquiring marker information data in a sample; and

[0065] An analysis and calculation module for forming a prediction probability as an analysis index by establishing a logistic regression model for the marker information data obtained in the information acquisition module, and then establishing an ROC curve to obtain a detection result for inflammatory bowel disease;

[0066] Wherein, the marker information includes at least one of the expression level of SLC6A14, the expression level of MUC-2, and the Nancy index score.

[0067] In some specific embodiments, the marker information is any two of the expression level of SLC6A14, the expression level of MUC-2, and the Nancy index score.

[0068] In some specific embodiments, the marker information is the expression level of SLC6A14, the expression level of MUC-2, and the Nancy index score.

[0069] In a specific embodiment, the sample includes tissues, cells or secretions of the subject.

[0070] In a specific embodiment, the inflammatory bowel disease includes ulcerative colitis and Crohn's disease, preferably ulcerative colitis.

[0071] In a specific embodiment, the detection result of the inflammatory bowel disease includes a diagnosis result, a curative effect evaluation result, and a recurrence prediction result of the inflammatory bowel disease.

[0072] In a specific embodiment, the system is used for screening, diagnosing, predicting recurrence or evaluating treatment effect of inflammatory bowel disease, preferably for predicting recurrence of inflammatory bowel disease.

[0073] The present application also provides a method for detecting and diagnosing inflammatory bowel disease, including detecting markers, converting the detection data into an analysis index through a model, and obtaining a detection result. In a specific embodiment, it includes calculating the prediction probability of a diagnostic model by logistic regression analysis for multiple detection indexes, and then performing ROC curve analysis on the prediction probability.

[0074] In a specific embodiment, the detection includes detecting the expression levels of the marker SLC6A14 and / or MUC-2 in a sample.

[0075] In a specific embodiment, the detection further includes scoring the Nancy index of the sample.

[0076] In one embodiment of the present application, the marker or system can be used for screening inflammatory bowel disease, including detecting people who have not yet developed the disease to predict their risk of developing inflammatory bowel disease.

[0077] In one embodiment of the present application, the marker or system can be used for examining and diagnosing whether a specific population has inflammatory bowel disease.

[0078] In one embodiment of the present application, the marker or system can be used for predicting and diagnosing the remission or recurrence of the condition of patients who have previously had inflammatory bowel disease and have been in remission, or who are undergoing drug treatment for inflammatory bowel disease. In particular, in some specific embodiments, it can be used to predict the recurrence and remission of the disease after mesalazine drug treatment or vedolizumab treatment for ulcerative colitis clinically.

[0079] The present application also provides a kit, which includes: reagents for detecting the expression level of SLC6A14, reagents for detecting the expression level of MUC-2, and reagents for scoring the Nancy index.

[0080] Example

[0081] Unless otherwise specified, other materials, reagents, etc. used in the following examples of the present application can be obtained from commercial sources without special instructions.

[0082] Example 1: Screening of Markers

[0083] 1. Collection of Clinical Samples

[0084] (1) Source of samples:

[0085] Based on real-world clinical cases, the UC patients who visited Peking Union Medical College Hospital were included, with the baseline being the endoscopic mucosal remission stage, and the sample type being paraffin-embedded tissues.

[0086] (2) Diagnostic criteria:

[0087] Diagnostic criteria for UC patients: According to the Diagnostic Criteria for Inflammatory Bowel Disease (Beijing, 2018) and the Evidence-based Consensus on the Diagnosis and Treatment of Ulcerative Colitis (2017) by the European Crohn's and Colitis Organization (ECCO), patients in the clinically diagnosed remission phase (modified Mayo score ≤ 2 points and no single sub-item score > 1 point for clinical remission) and achieving mucosal healing.

[0088] Assessment of mucosal healing: The Mayo endoscopic score was used as the assessment tool for mucosal healing in UC patients. The Mayo endoscopic score is divided into 3 grades: 0 grade indicates normal or healed mucosa; 1 grade indicates mild inflammation, blurred vascular texture, and contact bleeding; 2 grade indicates moderate inflammation, disappearance of vascular texture, erosion, and contact bleeding; 3 grade indicates severe inflammation, visible ulcers, and spontaneous mucosal bleeding. Patients with a Mayo endoscopic score of 0 grade were defined as having mucosal healing.

[0089] Assessment of histological healing: The Nancy histopathological index was used as the assessment tool for histological healing in UC patients. The Nancy index ≤ 1 was defined as histological healing. The specific assessment criteria are shown in Table 1.

[0090] (3)Inclusion criteria:

[0091] ① Aged 18 - 70 years, both genders are included; ② UC patients achieving mucosal healing.

[0092] (4)Exclusion criteria:

[0093] ① Pregnant women, patients with other autoimmune diseases, patients with digestive tract malignancies; ② Patients with severe liver, kidney, endocrine, respiratory, neurological, or cardio-cerebro-pulmonary vascular diseases; ③ Patients with concurrent infections.

[0094] (5)Disease recurrence criteria: The modified Mayo score ≥ 3 points occurred within 1 year of follow-up.

[0095] 2. Immunohistochemistry and analysis

[0096] (1)Immunohistochemistry:

[0097] 1) After paraffin tissues are sectioned at 2.5 μm, they are spread in a spreading machine at 48°C and baked at 63°C for 1 hour; 2) The tissues are dewaxed and hydrated (soaked in dewaxing solution I for 15 minutes → soaked in dewaxing solution II for 15 minutes → soaked in absolute ethanol I for 5 minutes → soaked in absolute ethanol II for 5 minutes → soaked in 95% ethanol for 2 minutes → soaked in 80% ethanol for 1 minute → washed with distilled water 3 times); 3) Soaked in 0.01 M phosphate buffer (hereinafter referred to as PBS) for 5 minutes and repeated 3 times; 4) Heat antigen retrieval with a pressure cooker: Use citrate buffer (pH 6.0) or EDTA buffer (pH 9.0) for retrieval; preheat to boiling; put the sections into the corresponding pressure cooker, start timing for 3 min after the EDTA jets, and start timing for 2.5 min after the citrate jets; cool at room temperature for 20 minutes; soak in 0.01 M PBS for 5 minutes and repeat 3 times; soak in 3% H2O2 for 10 minutes; soak in 0.01 M PBS for 5 minutes again and repeat 3 times; after adding the primary antibody, put the sections into a humidified box and incubate overnight at 37°C; soak in 0.01 M PBS for 5 minutes and repeat 3 times; after adding the secondary antibody, put the sections into a humidified box and incubate at 37°C for 30 minutes; soak in 0.01 M PBS for 5 minutes and repeat 3 times; DAB color development (microscopic examination); counterstain with hematoxylin for 5 minutes and then wash 3 times with water in a glass tank; differentiate with differentiating solution and then wash 3 times with water in a glass tank; blue with bluing solution and then wash 3 times with water in a glass tank; microscopic examination to observe the nuclear staining condition; dehydrate and clear upward (soaked in 80% ethanol for 1 minute → soaked in 95% ethanol I for 2 minutes → soaked in 95% ethanol II for 2 minutes → soaked in absolute ethanol I for 5 minutes → soaked in absolute ethanol II for 5 minutes → soaked in clearing solution I for 1 minute → soaked in clearing solution II for 5 minutes → soaked in clearing solution III for 5 minutes); seal with neutral balsam and microscopic examination.

[0098] (2)HE staining

[0099] 1) Dewax the sections to water; 2) Stain with hematoxylin solution for 10 minutes; 3) Wash thoroughly with tap water; 4) Differentiate with differentiating solution for 5 seconds; 5) Wash thoroughly with tap water; 6) Blue with bluing solution for 5 seconds; 7) Wash thoroughly with tap water; 8) Stain with 0.1% eosin for 1 minute; 9) Immerse in 95% ethanol for 2 minutes; 10) Immerse in 95% ethanol for 2 minutes; 11) Immerse in 100% ethanol I for 3 minutes; 12) Immerse in 100% ethanol II for 3 minutes; 13) Immerse in xylene I for 7 minutes; 14) Immerse in xylene II for 7 minutes; 15) Seal with neutral balsam for fixation.

[0100] (3)Result analysis

[0101] All HE and immunohistochemistry slides were sequentially placed under an optical microscope to collect images. Two senior pathologists reviewed the slides, performed Nancy histological scoring on the HE staining, and then used Image Pro Plus 6.0 software to calculate the integrated optical density values of MUC-2 and SLC6A14, respectively. According to the results of Nancy histological scoring, MUC-2 and SLC6A14 integrated optical density values, ROC curves for predicting recurrence of single indicators were plotted. Further, ROC curves were plotted and the AUC was calculated by combining two or three indicators respectively, to analyze the predictive value of Nancy histological scoring, MUC-2 and SLC6A14 integrated optical density values as recurrence markers in patients with remission UC.

[0102] For the combined analysis, logistic regression analysis was used to calculate the predicted probability. The predicted probability was put into the test variable, and whether there was recurrence was put into the status variable. The value of the status variable was set to 1. The data and reference lines to be displayed were selected, and an ROC curve was formed. The area under the curve AUC was calculated. All analyses were performed using SPSS 27 software.

[0103] 3. Experimental Results

[0104] (1)Cohort Information:

[0105] Patients obtained after screening according to the above diagnosis, inclusion and exclusion criteria were numbered and included in the database. A total of 34 patients maintained remission within 52 weeks of follow-up and did not experience clinical recurrence. 16 patients had clinical recurrence within 52 weeks of follow-up. A total of 50 patients were enrolled. The 50 wax block tissues of the above patients were uniformly sectioned and stained by IHC for expression analysis. The specific information of the 50 patients is shown in Table 2, including disease type, gender, age, baseline date, Mayo endoscopic score (MES), Nancy score (NI) and recurrence status.

[0106] Table 2 Baseline clinical information of enrolled patients ; .

[0107] (2)Results of immunohistochemistry experiment and Nancy scoring

[0108] Through immunohistochemical pathological review, significant differences in the expression of MUC-2 and SLC6A14 were found in the tissues of recurrent and non-recurrent patients. Among them, MUC-2 was more highly expressed in the tissues of non-recurrent patients, while SLC6A14 was more highly expressed in the tissues of recurrent patients. The specific results are shown in Figure 1 A-C and Figure 2 as shown ( Figure 1 A-C are the statistical results of the discovery cohort, * P value < 0.05; **** P value < 0.0001;Figure 2 Representative immunohistochemical staining pictures of MUC-2 and SLC6A14 in recurrent and non-recurrent tissues). Through the above preliminary screening, it is considered that the expression levels of MUC-2 and SLC6A14 are related to the recurrence of UC disease and can be used as markers for judging disease recurrence. In addition, it can also be seen from the data in Table 2 that the Nancy histological score in the recurrence group is significantly higher than that in the non-recurrence group and can also be used as a prediction index.

[0109] Example 2: Verification of the prediction of UC recurrence by markers

[0110] 1. Verification cohort experiment

[0111] Fifty-nine patients treated with mesalazine were enrolled as the verification cohort. A total of 41 patients maintained remission within 52 weeks of follow-up and did not experience clinical recurrence, and 18 patients had clinical recurrence within 52 weeks of follow-up. A total of 59 cases were enrolled. According to the method in Example 1, through immunohistochemical techniques, after uniformly making sections and performing IHC staining on 59 wax block groups of cohort patients, the expressions of MUC-2 and SLC6A14 in the expression analysis samples were detected, and the histological healing was scored using HE staining. The specific information of the patients is shown in Table 3.

[0112] Table 3 Baseline clinical information of the enrolled patients in the verification cohort ; ; .

[0113] Figure 1 D-F are the statistical results of the verification cohort, showing that the expression level of SLC6A14 is higher in the tissues of recurrent patients, while the expression of MUC-2 is higher in the tissues of non-recurrent patients. The Nancy histological score in the recurrence group is also significantly higher than that in the non-recurrence group. These results are consistent with the statistical results of Example 1. This also indicates that the marker also has an evaluation and prediction effect on the effect after drug treatment and the recurrence risk.

[0114] 2. Verification of the detection sensitivity of the marker

[0115] Using the experimental results of the above-mentioned enrolled cohort and verification cohort, the sensitivity of the screened marker was further verified, and the specific results are as follows.

[0116] In the enrollment cohort: When predicting disease recurrence using each biomarker alone, the expression of MUC-2 [AUC 1(95%CI)=0.737 (0.562, 0.913)], the expression of SLC6A14 [AUC 2 (95%CI)=0.936 (0.848, 1)], or the Nancy histological score [AUC 3 (95%CI)=0.665 (0.513, 0.816)]; When performing predictive analysis by combining two biomarkers pairwise, the combination of MUC-2 expression and SLC6A14 expression [AUC 4 (95%CI)=0.939 (0.856, 1)], the combination of MUC-2 expression and the Nancy histological score [AUC 5 (95%CI)=0.779 (0.636, 0.923)], or the combination of SLC6A14 expression and the Nancy histological score [AUC 6 (95%CI)=0.954 (0.891, 1)]; When performing predictive analysis by combining the three biomarkers, [AUC 7 (95%CI)=0.960 (0.901, 1)], with the strongest predictive ability (the specific results are as shown in Figures 3 - 9 shown).

[0117] In the validation cohort: When predicting disease recurrence using each biomarker alone, the expression of MUC-2 [AUC 8(95%CI)= 0.8537 (0.7499, 0.9574)], the expression of SLC6A14 [AUC 9 (95%CI)= 0.874 (0.7732, 0.9748)], or the Nancy histological score [AUC 10 (95%CI)= 0.8218 (0.7062, 0.9375)]; When performing predictive analysis by combining two biomarkers pairwise, the combination of MUC-2 expression and SLC6A14 expression [AUC 11 (95%CI)= 0.958 (0.9095, 1)], the combination of MUC-2 expression and the Nancy histological score [AUC 12 (95%CI)= 0.9295 (0.8584, 1)], or the combination of SLC6A14 expression and the Nancy histological score [AUC 13 (95%CI)= 0.893 (0.783, 1)]; When performing predictive analysis by combining the three biomarkers, [AUC 14 (95%CI)= 0.9715 (0.9247, 1)], with the strongest predictive ability (the specific results are as shown in Figures 10 - 16 shown).

[0118] Only the principles of the present application are shown above. It should be understood that the scope of the present application is not intended to be limited to the exemplary aspects described herein, but should include all currently known and future-developed equivalents. Additionally, it should be noted that several improvements and modifications can be made without departing from the technical principles of the present application, and these improvements and modifications should also be considered within the scope of the present application.

Claims

1. Use of a marker in the preparation of a detection product for inflammatory bowel disease, wherein, The markers are SLC6A14, MUC-2 and Nancy index.

2. The use according to claim 1, wherein The detection product is used to detect the expression levels of SLC6A14 and MUC-2 in a sample, and to score the Nancy index of the sample.

3. The use according to claim 2, wherein, The sample includes tissues, cells or secretions of a subject.

4. The use according to claim 1, wherein, The inflammatory bowel disease includes ulcerative colitis and Crohn's disease, preferably ulcerative colitis.

5. The use according to claim 1, wherein, The detection product is used for screening, diagnosis, recurrence prediction or treatment effect evaluation of inflammatory bowel disease, preferably for predicting the recurrence of inflammatory bowel disease.

6. A system for detecting inflammatory bowel disease in a subject, comprising: An information collection module for obtaining marker information data in a sample; And An analysis and calculation module for forming a prediction probability as an analysis index by establishing a logistic regression model with the marker information data obtained in the information collection module, and then establishing an ROC curve to obtain the detection result of inflammatory bowel disease; Wherein, the marker information includes the expression level of SLC6A14, the expression level of MUC-2 and the Nancy index.

7. The system according to claim 6, wherein, The sample includes tissues, cells or secretions of a subject.

8. The system according to claim 6, wherein The inflammatory bowel disease includes ulcerative colitis and Crohn's disease, preferably ulcerative colitis.

9. The system according to claim 6, wherein, The system is used for screening, diagnosis, recurrence prediction or treatment effect evaluation of inflammatory bowel disease, preferably for predicting the recurrence of inflammatory bowel disease.

10. A kit, comprising: Reagents for detecting the expression level of SLC6A14, reagents for detecting the expression level of MUC-2 and reagents for scoring the Nancy index.

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