A marker combination for predicting recurrence of ulcerative colitis and application thereof

Abstract

The application provides a marker combination and application for predicting recurrence of ulcerative colitis. Specifically, the marker is at least one of SLC6A14, MUC-2 and Nancy index. The marker can be used for diagnosis and recurrence prediction of ulcerative colitis, and has strong detection capability for remission and recurrence of patients after clinical drug treatment.

Description

TECHNICAL FIELD

[0001] The present application relates to the fields of biology and medicine, and particularly relates to a marker for detecting and diagnosing ulcerative colitis and application thereof. BACKGROUND

[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, which has the characteristics of long course, delayed healing and progressive recurrence, and seriously affects the quality of life of patients.

[0003] Repeated attacks are the difficulty in treating UC, and the damage of the mucosal barrier may be an important reason for the recurrence of UC. The real recovery of intestinal barrier function requires the recovery of tight junction state of epithelial cells and the recovery of intestinal microecological balance. There is an urgent need in the prior art to explore more accurate target markers reflecting the pathological state of the disease to more accurately assess the disease, especially to predict the recurrence of the disease. SUMMARY

[0004] To achieve the above-mentioned purpose, the present application finds and identifies a marker related to the diagnosis and recurrence of ulcerative colitis by immunohistochemical analysis of samples, and further establishes 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 Nancy index.

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

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

[0008] Further, the detection product is used for detecting the expression amount of SLC6A14 and / or MUC-2 in the sample, and / or for scoring 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] Further, the detection product is used for screening, diagnosis, relapse prediction or treatment effect evaluation of inflammatory bowel disease, preferably for predicting the relapse of inflammatory bowel disease.

[0012] The present application also relates to a system for detecting inflammatory bowel disease in a subject, comprising:

[0013] an information acquisition module for acquiring marker information data in a sample; and

[0014] an analysis calculation module for forming a prediction probability as an analysis index by establishing a logistic regression model for the marker information data acquired in the information acquisition module, and obtaining a detection result of inflammatory bowel disease by establishing a ROC curve.

[0015] The marker information comprises at least one of SLC6A14 expression, MUC-2 expression and Nancy index score.

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

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

[0018] Further, the sample comprises tissue, cells or secretion of the subject.

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

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

[0021] The present application also relates to a kit comprising: a reagent for detecting SLC6A14 expression, a reagent for detecting MUC-2 expression and a reagent for scoring Nancy index. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 Differences of MUC-2 expression, SCL6A14 expression and Nancy histological score between relapse and non-relapse groups.

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

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

[0025] Figure 4 ROC curve for MUC-2 expression for the discovery cohort (ROC 8).

[0026] Figure 5 ROC curve for pathological Nancy histological score for the discovery cohort (ROC 10).

[0027] Figure 6 ROC curve for MUC-2, SLC6A14 combined analysis for the discovery cohort (ROC 11).

[0028] Figure 7 ROC curve for MUC-2, Nancy histological score combined analysis for the discovery cohort (ROC 12).

[0029] Figure 8 ROC curve for SLC6A14, Nancy histological score combined analysis for the discovery cohort (ROC 13).

[0030] Figure 9 ROC curve for MUC-2, SLC6A14, Nancy histological score combined analysis for the discovery cohort (ROC 14).

[0031] Figure 10 ROC curve for MUC-2 expression for the validation cohort (ROC 8).

[0032] Figure 11 ROC curve for SLC6A14 expression for the validation cohort (ROC 9).

[0033] Figure 12 ROC curve for pathological Nancy histological score for the validation cohort (ROC 10).

[0034] Figure 13 ROC curve for MUC-2, SLC6A14 combined analysis for the validation cohort (ROC 11).

[0035] Figure 14 ROC curve for MUC-2, Nancy histological score combined analysis for the validation cohort (ROC 12).

[0036] Figure 15 ROC curve for SLC6A14, Nancy histological score combined analysis for the validation cohort (ROC 13).

[0037] Figure 16 ROC curve for MUC-2, SLC6A14, Nancy histological score combined analysis for the validation cohort (ROC 14). DETAILED DESCRIPTION

[0038] The embodiments of the present application will be described in detail below with specific examples, but the following should not be understood as any limitation to the present application.

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

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

[0041] The Nancy index in the present application is Nancy histopathology index, which can be used as an evaluation tool for histological healing of UC patients. The Nancy histopathology index includes three histological evaluation indexes of ulcer, acute inflammatory cell infiltration and chronic inflammatory cell infiltration, and the degree of disease activity is divided into five disease activity levels from 0 (no histological inflammatory activity) to 4 (severe active disease) according to the infiltration degree of acute and chronic inflammatory cells and whether there is ulcer, 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 embodiments, the marker is any two of SLC6A14, MUC-2 and Nancy index. For example, SLC6A14 and MUC-2, SLC6A14 and Nancy index or MUC-2 and Nancy index are used in combination for the detection of inflammatory bowel disease.

[0045] In one specific embodiment, the marker is SLC6A14, MUC-2 and Nancy index, i.e. the three markers are used in combination for the detection of inflammatory bowel disease.

[0046] The present application further provides the use of the marker described in the present application in the preparation of a detection product for inflammatory bowel disease.

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

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

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

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

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

[0052] In the present application, the sample includes tissue, cells or secretion of the 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 marker and the detection product provided in the present application can be used for the screening, diagnosis, relapse prediction or treatment effect evaluation of inflammatory bowel disease.

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

[0058] In the present application, relapse includes the recurrence of past medical conditions (inflammatory bowel disease), and the signs and symptoms of the condition recover after remission. Relapse includes the case where the disease signs and symptoms reoccur after the disease reaches clinical cure, complete remission or partial remission. For example, the disease symptoms reappear within a certain period of time after effective drug treatment, etc. The treatment effect includes but is not limited to the effect in preventing the occurrence or relapse of the disease, relieving the symptoms of the disease, 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 marker SLC6A14, MUC-2 and Nancy index can be used for the diagnosis, prediction or evaluation of the relapse of ulcerative colitis.

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

[0062] In specific embodiments, the detection product is selected from a reagent, a kit, a test paper or a diagnostic chip.

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

[0064] an information collection module for obtaining marker information data in a sample; and

[0065] an analysis calculation module for obtaining a prediction probability as an analysis index by establishing a logistic regression model from the marker information data obtained in the information collection module, and obtaining a detection result of the inflammatory bowel disease by establishing a ROC curve.

[0066] In specific embodiments, the marker information comprises at least one of SLC6A14 expression level, MUC-2 expression level and Nancy index score.

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

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

[0069] In specific embodiments, the sample comprises a tissue, a cell or a secretion of the subject.

[0070] In specific embodiments, the inflammatory bowel disease comprises ulcerative colitis and Crohn's disease, preferably ulcerative colitis.

[0071] In specific embodiments, the detection result of the inflammatory bowel disease comprises a diagnosis result, an efficacy evaluation result and a recurrence prediction result of the inflammatory bowel disease.

[0072] In specific embodiments, the system is used for screening, diagnosis, recurrence prediction or treatment effect evaluation of the inflammatory bowel disease, preferably for predicting recurrence of the inflammatory bowel disease.

[0073] The present application further provides a method for detecting and diagnosing inflammatory bowel disease, comprising detecting a marker, converting the detection data into an analysis index by a model, and obtaining a detection result. In specific embodiments, the method comprises calculating a prediction probability of a diagnosis model by Logistic regression analysis of multiple detection indexes, and performing ROC curve analysis on the prediction probability.

[0074] In specific embodiments, the detecting comprises detecting the expression level of the marker SLC6A14 and / or MUC-2 in the sample.

[0075] In specific embodiments, the detecting further comprises scoring the Nancy Index of the sample.

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

[0077] In one embodiment of the present application, the marker or system can be used for checking and diagnosing whether a specific person 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 a disease in patients who have had inflammatory bowel disease and have been in remission, or have been treated for inflammatory bowel disease. In particular, in some specific embodiments, it can be used to predict the remission or recurrence of the disease after clinical treatment of ulcerative colitis with mesalazine or vedolizumab.

[0079] The present application also provides a kit comprising: 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.

[0080] Examples

[0081] Unless otherwise specified, the following examples of the present application use. Other materials, reagents, etc., unless otherwise specified, can be obtained commercially.

[0082] Example 1: Screening of markers

[0083] 1. Clinical sample collection

[0084] (1) Sample source:

[0085] Based on real-world clinical cases from UC patients treated at Peking Union Medical College Hospital, the baseline was included in the endoscopic mucosal remission period, and the sample type was paraffin-embedded tissue.

[0086] (2) Diagnostic criteria:

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

[0088] Evaluation of mucosal healing: The Mayo endoscopic score was used as an evaluation tool for mucosal healing in UC patients. The Mayo endoscopic score was divided into 3 points: 0 points for normal or healed mucosa; 1 point for mild inflammation, blurred vascular texture, contact bleeding; 2 points for moderate inflammation, disappearance of vascular texture, erosion, contact bleeding; 3 points for severe inflammation, visible ulcer, mucosa with spontaneous bleeding. Mayo endoscopic score of 0 points was defined as mucosal healing.

[0089] Evaluation of histological healing: The Nancy histopathology index was used as an evaluation tool for histological healing in UC patients. Nancy index ≤1 was defined as histological healing. The specific evaluation criteria are shown in Table 1.

[0090] (3) Inclusion criteria:

[0091] ① Age 18-70 years old, male and female; ② UC patients who reached mucosal healing.

[0092] (4) Exclusion criteria:

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

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

[0095] 2. Immunohistochemistry and analysis

[0096] (1) Immunohistochemistry:

[0097] 1) Paraffin tissue was sectioned at 2.5 microns, then spread in a 48°C film spreading machine, dried at 63°C, and baked for 1 hour; 2) The tissue was deparaffinized and hydrated (deparaffinizing solution I for 15 minutes → deparaffinizing solution II for 15 minutes → anhydrous ethanol I for 5 minutes → anhydrous ethanol II for 5 minutes → 95% ethanol for 2 minutes → 80% ethanol for 1 minute → distilled water for 3 times); 3) 0.01 M phosphate buffer (hereinafter referred to as PBS) for 5 minutes for 3 times; 4) High-pressure pot heat antigen repair: using citric acid buffer (pH 6.0) or EDTA buffer (pH 9.0) for repair; preheated to boiling; put the section into the corresponding high-pressure pot, and count 3 min after EDTA spraying, and count 2.5 min after citric acid spraying; cool at room temperature for 20 minutes; soak in 0.01 M PBS for 5 minutes, repeat 3 times; soak in 3% H2O2 for 10 minutes; soak in 0.01 M PBS for 5 minutes again, repeat 3 times; put the section into a humidifying box after adding the first antibody, and incubate in a 37°C constant temperature box overnight; soak in 0.01 M PBS for 5 minutes, repeat 3 times; put the section into a humidifying box after adding the second antibody, and incubate at 37°C for 30 minutes; soak in 0.01 M PBS for 5 minutes, repeat 3 times; DAB color development (microscopy); put into a glass jar and wash with water for 3 times after hematoxylin re-staining for 5 minutes; put into a glass jar and wash with water for 3 times after color separation with color separation solution; put into a glass jar and wash with water for 3 times after counterbluing with counterbluing solution; microscopy, observe the nuclear staining; ascending dehydration and transparency (80% ethanol for 1 minute → 95% ethanol I for 2 minutes → 95% ethanol II for 2 minutes → anhydrous ethanol I for 5 minutes → anhydrous ethanol II for 5 minutes → transparency solution I for 1 minute → transparency solution II for 5 minutes → transparency solution III for 5 minutes); neutral gum mounting, microscopy.

[0098] (2) HE staining

[0099] 1) Section deparaffinization to water; 2) hematoxylin staining solution for 10 minutes; 3) tap water for full washing; 4) differentiation solution for 5 seconds; 5) tap water for full washing; 6) counterbluing solution for 5 seconds; 7) tap water for full washing; 8) 0.1% eosin for 1 minute; 9) 95% ethanol for 2 minutes; 10) 95% ethanol for 2 minutes; 11) 100% ethanol I for 3 minutes; 12) 100% ethanol II for 3 minutes; 13) xylene I for 7 minutes; 14) xylene II for 7 minutes; 15) neutral gum mounting and fixing.

[0100] (3) Result analysis

[0101] All HE and immunohistochemistry slides were placed under an optical microscope in turn, images were collected, and slides were reviewed by two experienced pathologists. The Nancy histological score was performed for HE staining, and the integrated optical density values of MUC-2 and SLC6A14 were calculated using Image Pro Plus 6.0 software, respectively. The ROC curve for predicting the recurrence of a single index was drawn according to the results of the Nancy histological score, MUC-2 and SLC6A14 integrated optical density values. Further, the ROC curve was drawn and the AUC was calculated by combining two or three indexes, respectively, to analyze the predictive value of the Nancy histological score, MUC-2 and SLC6A14 integrated optical density values as a marker for predicting the recurrence of patients with UC in remission.

[0102] The combined analysis used Logistic regression analysis to calculate the prediction probability, and the prediction probability was put into the test variable and whether the recurrence was put into the state variable. The state variable value was set to 1, the data to be displayed was checked, and the reference line was formed to form the ROC curve. The area under the curve AUC was calculated, and all analyses were performed using SPSS 27 software.

[0103] 3. Experimental results

[0104] (1) Cohort information:

[0105] After screening according to the above diagnosis and inclusion and exclusion criteria, the patients were numbered and included in the database. A total of 34 patients maintained remission within 52 weeks of follow-up and did not appear clinically. Sixteen patients had clinical recurrence within 52 weeks of follow-up, and a total of 50 patients were enrolled. After IHC staining of the 50 wax block tissues, expression analysis was performed. The specific information of the 50 patients is shown in Table 2, which includes disease type, gender, age, baseline date, Mayo endoscopic score (MES), Nancy score (NI), and recurrence.

[0106] Table 2 Baseline clinical information of enrolled patients

[0107] ;

[0108] .

[0109] (2) Immunohistochemical experiment and Nancy score results

[0110] Through immunohistochemical pathological review, it was found that MUC-2 and SLC6A14 had significant differences in the tissues of patients with recurrence and non-recurrence. Among them, MUC-2 was more highly expressed in the tissues of patients with non-recurrence, while SLC6A14 was more highly expressed in the tissues of patients with recurrence. The specific results are shown in Figure 1 A-C and Figure 2 . Figure 1A-C are the statistical results of the discovery cohort, *P value <0.05; ****P value <0.0001; Figure 2 The expression of MUC-2 and SLC6A14 in the tissues of relapse and non-relapse is shown in the representative pictures of immunohistochemical staining. It is considered that the expression of MUC-2 and SLC6A14 is related to the relapse of UC disease through the above-mentioned preliminary screening, and can be used as a marker for judging the relapse of disease. In addition, it can also be seen from the data in Table 2 that the Nancy histological score in the relapse group is significantly higher than that in the non-relapse group, and can also be used as a predictive index.

[0111] Example Two: Verification of the Marker for Predicting the Relapse of UC

[0112] 1. Verification cohort experiment

[0113] 59 patients treated with mesalazine were enrolled as a verification cohort, and 41 patients maintained remission and did not appear clinically relapse within 52 weeks of follow-up, and 18 patients appeared clinically relapse within 52 weeks of follow-up, a total of 59 cases were enrolled. According to the method in Example One, the expression of MUC-2 and SLC6A14 in the sample was analyzed after IHC staining of the 59 wax blocks of the cohort patients, and the histological healing was scored by HE staining. The specific information of the patients is shown in Table 3.

[0114] Table 3 Baseline clinical information of patients enrolled in the verification cohort

[0115] ;

[0116] ;

[0117] .

[0118] Figure 1 D-F are the statistical results of the verification cohort, showing that the expression of SLC6A14 in the tissues of relapse patients is higher, while the expression of MUC-2 in the tissues of non-relapse patients is higher. The Nancy histological score of the relapse group is also significantly higher than that of the non-relapse group. These results are consistent with the statistical results of Example One. This also indicates that the marker also has the effect of evaluating and predicting the effect and relapse risk after drug treatment.

[0119] 2. Verification of the sensitivity of the marker detection

[0120] The results of the above-mentioned enrollment cohort and verification cohort experiments were further used to verify the sensitivity of the screened marker, and the specific results are as follows.

[0121] In the enrollment cohort: when each marker was used alone to predict disease recurrence, MUC-2 expression

AUC 1 (95% CI) = 0.737 (0.562, 0.913)

AUC 2 (95% CI) = 0.936 (0.848, 1)

AUC 3 (95% CI) = 0.665 (0.513, 0.816)

AUC 4 (95% CI) = 0.939 (0.856, 1)

AUC 5 (95% CI) = 0.779 (0.636, 0.923)

AUC 6 (95% CI) = 0.954 (0.891, 1)

AUC 7 (95% CI) = 0.960 (0.901, 1)

[0122] In the validation cohort: when each marker was used alone to predict disease recurrence, MUC-2 expression

AUC 8 (95% CI) = 0.8537 (0.7499, 0.9574)

AUC 9 (95% CI) = 0.874 (0.7732, 0.9748)

AUC 10 (95% CI) = 0.8218 (0.7062, 0.9375)

AUC 11 (95% CI) = 0.958 (0.9095, 1)

AUC 12 (95% CI) = 0.9295 (0.8584, 1)

AUC 13 (95% CI) = 0.893 (0.783, 1)

AUC 14 (95% CI) = 0.9715 (0.9247, 1)

[0123] The foregoing merely illustrates the principles of the application and it will thus be appreciated that those skilled in the art will be able to devise numerous alternative arrangements which, although not explicitly described herein, embody the principles of the application and are thus within its spirit and scope. Further, all examples and conditional language recited herein are intended to mean that at least one of the enumerated examples is present and that the other enumerated examples are not excluded.​​

Claims

1. The use of reagents for detecting combinations of biomarkers in the preparation of diagnostic products for inflammatory bowel disease, wherein, The biomarkers are SLC6A14, MUC-2, and the Nancy index, and the reagents are reagents for detecting the expression level of SLC6A14, reagents for detecting the expression level of MUC-2, and reagents for scoring the 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 the sample, and to score the Nancy index of the sample.

3. The use according to claim 2, wherein, The samples include the subject's tissues, cells, or secretions.

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

5. The use according to claim 1, wherein, The testing products are used for screening, diagnosis, recurrence prediction, or treatment efficacy evaluation of inflammatory bowel disease.

6. A system for detecting inflammatory bowel disease in a subject, comprising: The information acquisition module is used to acquire information data about biomarkers in the sample. as well as The analysis and calculation module is used to take the biomarker information data obtained from the information acquisition module, establish a logistic regression model, form a predicted probability as an analysis indicator, and then establish an ROC curve to obtain the detection results of inflammatory bowel disease. The biomarker information includes SLC6A14 expression level, MUC-2 expression level, and Nancy index.

7. The system according to any one of claims 6, wherein, The samples include the subject's tissues, cells, or secretions.

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

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

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

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