Application of retin-1 in prediction of intestinal lesion range of ulcerative colitis

Abstract

The invention discloses application of retin-1 in prediction of an intestinal lesion range of ulcerative colitis, and relates to the technical field of inflammatory bowel disease markers. The serum Omentin-1 level can accurately predict the intestinal lesion range of the UC patient in the active period. Therefore, the invention provides a new means for managing the dynamic change of the disease of the UC patient clinically, and has a better clinical application prospect.

Description

Technical Field

[0001] This invention relates to the field of biomarkers for inflammatory bowel disease (IBD), and more specifically, to the application of omentin-1 in predicting the extent of intestinal lesions in ulcerative colitis. Background Technology

[0002] Ulcerative colitis (UC) is a clinical subtype of inflammatory bowel disease (IBD). It is a chronic, nonspecific inflammatory bowel disease characterized by alternating clinical remissions and relapses. Its main clinical symptoms include diarrhea, abdominal pain, and other intestinal manifestations. Extraintestinal manifestations are also frequently present, affecting joints, skin, eyes, and kidneys. UC is mostly confined to the colon, especially the terminal colon and rectum; a small percentage of patients may have involvement of the terminal ileum. The main manifestation is inflammation of the superficial mucosa of the colonic wall, which may present with ulcers and acute purulent leukocyte infiltration. This disease primarily affects young adults, is difficult to diagnose and treat, requires lifelong treatment, has limited current drug therapy options, is extremely expensive, and has a high incidence of cumulative complications.

[0003] Patients often fall into poverty, become disabled, develop cancer, or die due to illness, which reduces their quality of life and causes a heavy economic burden.

[0004] Ulcers (UC) are generally classified according to "disease activity" (i.e., the intensity of mucosal inflammation at a given point in time) and "disease extent" (i.e., the continuous segment of the colon macroscopically affected). The extent of UC is determined using the Montreal classification: proctitis, left-sided, and extensive, and can only be accurately determined by invasive colonoscopy. Studies have shown that the extent of UC is associated with disease severity, long-term prognosis, and the likelihood of treatment response. However, activity and extent are not necessarily synchronous. Increasing evidence shows that the extent of UC is an independent driver of hard endpoints such as hospitalization, colectomy, and colorectal cancer, but currently, there is a lack of biomarkers that specifically reflect the extent of UC. Therefore, clinicians still rely on repeated endoscopy to record lesion expansion or remission, a practice that is costly, uncomfortable for patients, and carries procedural risks.

[0005] In view of this, the present invention is proposed. Summary of the Invention

[0006] The purpose of this invention is to provide the application of omentin-1 in predicting the extent of intestinal lesions in ulcerative colitis, thereby providing a new means for clinical management of the dynamic changes in UC patients.

[0007] This invention is implemented as follows: In a first aspect, the present invention provides the application of a reagent for detecting biomarkers in the preparation of a predictive product for the extent of intestinal lesions in ulcerative colitis, wherein the biomarker includes reticulin-1; the predictive product generates a predictive result for the extent of intestinal lesions in ulcerative colitis in a subject based on characteristic data of the biomarkers contained in the subject's sample. The predicted product includes at least one of the following application methods: (1) Based on the characteristic data of biomarkers contained in the subject's sample, generate the prediction results of the extent of intestinal lesions during the clinical active phase of ulcerative colitis in the subject; (2) Based on the characteristic data of the biomarkers contained in the subject's sample, generate a prediction result of the extent of endoscopic active intestinal lesions; The predictive results for the extent of intestinal lesions are: the predictive results for distinguishing between extensive colitis and distal colitis.

[0008] In a second aspect, the present invention also provides a device for predicting the extent of intestinal lesions in ulcerative colitis, comprising: an input module, a control module, and an output module; The input module is configured to input characteristic data of biomarkers contained in the subject's sample. The control module includes: a result analysis module, which is configured to generate at least one of the following prediction results based on the characteristic data of biomarkers contained in the subject's test sample, based on the comparison of the concentration of biomarkers contained in the subject's test sample with a predetermined threshold, and based on the comparison results: (1) generating a prediction result of the extent of intestinal lesions in the clinical active phase of ulcerative colitis in the subject; (2) generating a prediction result of the extent of intestinal lesions in the active phase under endoscopy. The predictive results for the extent of intestinal lesions are: the predictive results for distinguishing between extensive colitis and distal colitis; the characteristic data of biomarkers refer to: the concentration of biomarkers contained in the subject's sample; The predetermined threshold is either the threshold obtained from the directly generated ROC curve, or the threshold obtained from the ROC curve generated based on the machine learning model; The output module is configured to output the predicted extent of intestinal lesions in the subject with ulcerative colitis.

[0009] Thirdly, the present invention also provides a computer-readable storage medium storing an executable program instruction set, wherein at least one instruction and the executable program instruction set are loaded and executed by a processor to realize a method for predicting the extent of intestinal lesions in ulcerative colitis. The method for predicting the extent of intestinal lesions in ulcerative colitis is based on the above-described application method.

[0010] The present invention has the following beneficial effects: This invention found that serum Omentin-1 levels in patients with extensive colitis were significantly lower than those in patients with distal colitis, suggesting that serum Omentin-1 levels can reflect the lesion site. Further evaluation of the predictive efficacy of this biomarker in the extent of intestinal lesions in patients with active UC showed extremely high predictive accuracy. Therefore, this invention provides a novel means for managing the dynamic changes in UC patients and has promising clinical application prospects. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 Figure showing the comparison of serum Omentin-1 concentrations between patients with distal colitis (distal group, Montreal classification E1 and E2) and extensive colitis (extensive group, Montreal classification E3); 84 patients with distal colitis; 42 patients with extensive colitis; ***p<0.001, statistical test used Mann-Whitney test; Data source: UC cohort 1; Figure 2 Figures showing serum Omentin-1 levels measured by ELISA in (A) clinical activity (p-Mayo ≥ 3, distal type n = 53, widespread type n = 30) and (B) clinical remission (p-Mayo ≤ 2, distal type n = 31, widespread type n = 12) groups, and serum Omentin-1 levels measured by ELISA in (C) endoscopic activity (MES = 2 / 3, distal type n = 47, widespread type n = 29) and (D) endoscopic remission (MES = 0 / 1, distal type n = 37, widespread type n = 13) groups; ***p<0.001, ns = no statistically significant difference, Mann-Whitney test used; Data source: UC cohort 1; Figure 3 Receiver operating characteristic curves to assess the ability of serum retinin-1 to differentiate between extensive colitis and distal colitis; Data source: UC cohort 1; (A) Total study population (n = 126); (B) Clinical activity subgroup (p-Mayo ≥ 3, n = 83); (C) Endoscopic activity subgroup (MES ≥ 2, n = 76); Figure 4Receiver operating characteristic curves to evaluate the ability of serum retinin-1 to differentiate between extensive colitis and distal colitis in clinically mild (A), clinically moderate (B), and clinically severe (C) phases; Data source: UC cohort 1; Figure 5 Receiver operating characteristic curves to assess the ability of serum retinin-1 to differentiate between extensive colitis and distal colitis; Data source: UC cohort 2; (A) Total study population (n = 80); (B) Clinical activity subgroup (p-Mayo ≥ 3); (C) Endoscopic activity subgroup (MES ≥ 2); Figure 6 Receiver operating characteristic curves were used to evaluate the ability of serum retinin-1 to distinguish between extensive colitis and distal colitis in clinically mild (A), clinically moderate (B), and clinically severe (C) phases, respectively; data source: UC cohort 2. Detailed Implementation

[0013] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Where specific conditions are not specified in the embodiments, conventional conditions or conditions recommended by the manufacturer shall apply. Reagents or instruments whose manufacturers are not specified are all conventional products that can be purchased commercially.

[0014] The extent of intestinal lesions in ulcerative colitis according to this invention is based on the Montreal classification, specifically as follows: .

[0015] This invention classifies ulcerative colitis into distal colitis and extensive colitis. Distal colitis corresponds to Montreal classification E1 and E2, while extensive colitis corresponds to Montreal classification E3.

[0016] The term "marker" broadly refers to any detectable compound or cell present in or derived from a sample, such as a protein, peptide, proteoglycan, glycoprotein, lipoprotein, cell, or any of the foregoing substances, that is differentiating molecule or differentiating fragment. For example, the detection of or binding to a specific antibody can indicate the presence of a specific antigen (e.g., a protein) in a sample. Here, a differentiating molecule or fragment is a molecule or fragment that, upon detection, indicates the presence or abundance of the aforementioned identified compound or cell. Markers can, for example, be isolated from the sample, measured directly in the sample, or detected or determined in the sample. Markers can, for example, be functional, partially functional, or non-functional. Markers may also be synonymous with "biomarker."

[0017] The term "sample" refers to a biological specimen obtained from or derived from an individual for a purpose. The source of the biological specimen can be a fresh, frozen, and / or preserved organ or tissue sample, or solid tissue derived from a biopsy or primers; blood or any blood component. The term "sample" includes biological samples that have been manipulated in any way after acquisition, such as by reagent treatment, stabilization, enrichment for certain components (e.g., proteins or polynucleotides), or embedding in a semi-solid or solid matrix for sectioning purposes. In this invention, the sample is particularly a peripheral blood sample or a serum sample.

[0018] As used herein, the term "subject" can be understood as anyone involved in the diagnosis or auxiliary diagnosis of inflammatory bowel disease (IBD). A subject can be a patient in a clinical setting undergoing one or more tasks related to the diagnosis of IBD, preparing the patient for one or more tests for IBD. IBD specifically refers to ulcerative colitis (UC).

[0019] The terms “area under the curve” or “AUC” refer to the area under the receiver operating characteristic (ROC) curve, both of which are well-known in the field. AUC measurements are useful for comparing the accuracy of classifiers across the entire data range. Classifiers with higher AUCs have a greater ability to correctly classify unknowns between two target groups (e.g., in samples of extensive and distal colitis groups). ROC curves are useful for depicting the performance of a specific feature (e.g., any biomarkers and / or any entries of additional biomedical information described in this invention) when distinguishing between two populations. Typically, feature data are selected across the entire population (e.g., cases and controls) in ascending order based on the value of a single feature. Then, for each value of that feature, the true positive and false positive rates of the data are calculated. The true positive rate is determined by counting the number of cases with values ​​higher than that feature and dividing by the total number of cases. The false positive rate is determined by counting the number of controls with values ​​higher than that feature and dividing by the total number of controls. Although this definition refers to cases where the characteristic is increased compared to the control, it also applies to cases where the characteristic is lower compared to the control (in which case samples with values ​​lower than the characteristic will be counted).

[0020] The term "predetermined threshold" refers to a parameter used to compare a marker or combination of markers in a subject's sample with a predetermined threshold when predicting the extent of intestinal lesions. The predicted extent of intestinal lesions is then output based on the comparison result.

[0021] Specifically, the predetermined thresholds include, but are not limited to, positive judgment values, predicted probability thresholds, dependent variable thresholds, and other critical values ​​that can be used to divide results and clarify judgment boundaries. The setting of these thresholds should be based on the performance requirements of the target detection scenario (such as sensitivity, specificity, accuracy, etc.) and determined through clinical data validation, statistical model analysis (such as ROC curve analysis combined with Youden index calculation, etc.) or industry standard calibration, so as to ensure their judgment effectiveness and reliability in the detection method or diagnostic model.

[0022] In a first aspect, the present invention provides the application of a reagent for detecting biomarkers in the preparation of a predictive product for the extent of intestinal lesions in ulcerative colitis, wherein the biomarker includes reticulin-1; the predictive product generates a predictive result for the extent of intestinal lesions in ulcerative colitis in a subject based on characteristic data of the biomarkers contained in the subject's sample. The predicted product includes at least one of the following application methods: (1) Based on the characteristic data of biomarkers contained in the subject's sample, generate the prediction results of the extent of intestinal lesions during the clinical active phase of ulcerative colitis in the subject; (2) Generate prediction results of the extent of intestinal lesions in the active phase under endoscopy; The predictive results for the extent of lesions are: the predictive results for distinguishing between extensive colitis and distal colitis.

[0023] Omentin-1 levels in the serum of patients with extensive colitis were significantly lower than those in patients with distal colitis, suggesting that serum Omentin-1 levels can reflect the location of the lesion.

[0024] In a preferred embodiment of the present invention, the biomarker is a biomarker in serum.

[0025] In a preferred embodiment of the present invention, the reagent for detecting the biomarker is a reagent for detecting the level of retinin-1 protein of the biomarker.

[0026] In a preferred embodiment of the present invention, the reagent for detecting the biomarker is one that detects the level of the biomarker protein in the sample using ELISA, Western blotting, and / or Elisopt methods. Any reagent capable of detecting the aforementioned remdesivir-1 level is within the scope of protection of this invention. In other embodiments, the reagent for detecting the biomarker can also be a PCR detection reagent, which predicts the extent of intestinal lesions in ulcerative colitis by detecting the level of the remdesivir-1 gene in the subject's sample.

[0027] In a preferred embodiment of the present invention, the predicted product is selected from at least one of reagents, test strips, kits, or chips.

[0028] In application method (1) above, the AUC value for distinguishing between extensive and distal colitis is greater than 0.8, and in application method (2), the AUC value for distinguishing between extensive and distal colitis is greater than 0.85. Therefore, serum omentin-1 can be used clinically to determine the extent of UC lesions in the active phase, and it is quite effective.

[0029] The predictive results for the extent of lesions are: the predictive results for distinguishing between extensive colitis and distal colitis.

[0030] In a preferred embodiment of the present invention, based on a comparison of the concentration of biomarkers contained in the subject's sample with a predetermined threshold, a predicted result of the extent of intestinal lesions in the subject's ulcerative colitis is generated according to the comparison result. The predetermined threshold is either the threshold obtained from the directly generated ROC curve, or the threshold obtained from the ROC curve generated based on the machine learning model.

[0031] In a preferred embodiment of the present invention, the machine learning model is selected from at least one of the following: logistic regression, random forest, K-nearest neighbors, Gaussian Bayes, Naive Bayes, support vector machine, AdaBoost, XGBoost, and DT decision tree.

[0032] Secondly, the present invention also provides an apparatus for predicting the extent of intestinal lesions in ulcerative colitis. The apparatus includes a processor and a memory, the memory storing a set of executable program instructions, which are loaded and executed by the processor to achieve a method for predicting the extent of intestinal lesions in ulcerative colitis.

[0033] Specifically, the electronic device may include a memory, a processor, a bus, and a communication interface, which are electrically connected directly or indirectly to each other to enable data transmission or interaction. For example, these components may be electrically connected to each other via one or more buses or signal lines. The processor may process information and / or data related to target identification to perform one or more functions described in this application.

[0034] The memory can be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc.

[0035] A processor can be an integrated circuit chip with signal processing capabilities. This processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0036] Thirdly, the present invention also provides a device for predicting the extent of intestinal lesions in ulcerative colitis, comprising: an input module, a control module, and an output module; The input module is configured to input characteristic data of biomarkers contained in the subject's sample. The control module includes: a result analysis module, which is configured to generate at least one of the following prediction results based on the characteristic data of biomarkers contained in the subject's test sample, based on the comparison of the concentration of biomarkers contained in the subject's test sample with a predetermined threshold, and based on the comparison results: (1) generating a prediction result of the extent of intestinal lesions in the clinical active phase of ulcerative colitis in the subject; (2) generating a prediction result of the extent of intestinal lesions in the active phase under endoscopy. The predictive results for the extent of intestinal lesions are: the predictive results for distinguishing between extensive colitis and distal colitis; the characteristic data of biomarkers refer to: the concentration of biomarkers contained in the subject's sample; The predetermined threshold is either the threshold obtained from the directly generated ROC curve, or the threshold obtained from the ROC curve generated based on the machine learning model; The output module is configured to output the predicted extent of intestinal lesions in the subject with ulcerative colitis.

[0037] Fourthly, the present invention also provides a computer-readable storage medium storing an executable program instruction set, wherein at least one instruction and the executable program instruction set are loaded and executed by a processor to realize a method for predicting the extent of intestinal lesions in ulcerative colitis. The method for predicting the extent of intestinal lesions in ulcerative colitis is based on the above-described application method.

[0038] The features and performance of the present invention will be further described in detail below with reference to embodiments.

[0039] Example 1 This embodiment screens and validates serum retinin-1 markers.

[0040] 1. Sample Inclusion This embodiment included two cohorts of patients diagnosed with UC: Cohort 1, totaling 126 patients, whose data were used for marker screening; and Cohort 2, totaling 80 patients, whose data were used for marker validation. The diagnosis of UC was based on a comprehensive analysis of medical history, clinical presentation, radiological, endoscopic and histological examinations, and laboratory tests. UC patients and controls were matched for sex and age. The Mayo Criterion System (total score of 9, without endoscopic scoring) was used to determine the clinical activity of the disease in UC patients. The Mayo endoscopic score was used to evaluate the endoscopic activity of the disease. The extent of the UC lesion was determined according to the Montreal Classification.

[0041] The Mayo Criterion System (total score of 9, no endoscopic scoring items) standards are as follows:

[0042] The Mayo Criterion (MCC) score is graded as follows: Total score ≤ 2 points, clinical remission; 3 ≤ Total score < 5 points, mild activity; 5 ≤ Total score < 7 points, moderate activity; Total score ≥ 7 points, severe activity.

[0043] Specific criteria for Mayo endoscopic scoring:

[0044] The Montreal classification criteria are as follows:

[0045] The exclusion criteria for inclusion in UC patients and the control group were as follows: smoking, alcoholism, hematopoietic system diseases, hepatobiliary diseases, coagulation abnormalities, use of drugs that may affect blood cell components or serum biochemical characteristics, hypertension, diabetes, infection, other systemic autoimmune diseases, other gastrointestinal diseases, and cancer.

[0046] 2. Detection of serum Omentin-1 concentration Enzyme-linked immunosorbent assay (ELISA) was used. The Omentin-1 detection kit was purchased from BioLegend (San Diego, CA, USA). Detailed operating procedures are as follows: (1) Antigen coating: Dilute the antigen to 10 μg / ml with carbonate coating solution, add 100 μl to each enzyme-labeled well, and incubate overnight at 4°C. Aspirate the antigen liquid and wash each well with 100 μl PBST for 5 min.

[0047] (2) Blocking: Add 100 μl of blocking solution (5% BSA) to each well, incubate at room temperature for 60 min, remove the blocking solution, and then wash with PBST for 5 min at a volume of 100 μl. One wash is sufficient.

[0048] (3) Primary antibody incubation: Remove the washing solution, add 100 μl of primary antibody diluted 500-1000 times with 5% BSA to each well, and incubate at room temperature for 1 h.

[0049] (4) Washing: Remove the liquid from the enzyme-labeled wells, wash each well three times with PBST, with a volume of 100 μl per well and a washing time of 5 min each time.

[0050] (5) Add enzyme-labeled antibody: Aspirate the washing solution and add 100 μl of secondary antibody diluted with 5% BSA at 1:2000 to each well. Incubate at room temperature for 1 h.

[0051] (6) Washing: Remove the liquid in the wells, wash three times with PBST for 5 min each time, with a volume of 100 μl per well, and then add 100 μl of PBS to each well for 5 min each time.

[0052] (7) Color development: Add 100 μl of TMB substrate solution to each well. Keep out of light during the addition process and react at room temperature for 40 min in the dark.

[0053] (8) Termination of reaction: Add 100 μl of 2M sulfuric acid to each enzyme-labeled well to terminate the reaction.

[0054] (9) Reading the plate: Place the ELISA plate in the ELISA reader and read the value.

[0055] 3. Results Analysis (1) In UC cohort 1, enrolled patients were divided into two groups according to the lesion site: distal colitis (Montreal classification E1 and E2, n = 84) and extensive colitis (E3, n = 42). Comparison of serum Omentin-1 levels between the two groups revealed that the extensive colitis group had significantly lower levels than the distal colitis group. Figure 1 This suggests that serum Omentin-1 levels can reflect the location of the lesion.

[0056] (2) To further exclude the influence of disease activity, serum Omentin-1 concentrations were compared between patients in the active or remission phases of the disease (in Cohort 1, 126 UC patients included 83 in the clinical active phase and 43 in the clinical remission phase; 76 in the endoscopic active phase and 50 in the endoscopic remission phase). The results showed that in patients in the clinical or endoscopic active phases, the Omentin-1 concentration in the extensive colitis group was significantly lower than that in the distal colitis group. Figure 2 This phenomenon was observed in patients in remission, but not in those in active UC. This further suggests that serum Omentin-1 concentration testing may be more suitable for UC patients in active phase.

[0057] (3) Evaluation of the diagnostic efficacy of serum omentin-1 in differentiating between extensive and distal colitis. ROC analysis yielded different AUC values ​​corresponding to different diagnostic accuracies: 0.6–0.7 was “acceptable”, 0.7–0.8 was “good”, 0.8–0.9 was “very good”, and ≥0.9 was “excellent”.

[0058] In the total UC population (n = 126, including patients in the mild, moderate, severe, and clinical remission phases), when differentiating between distal and extensive UC, the AUC was 0.7326, corresponding to a cutoff point of 56.2 ng / mL, with a sensitivity of 66.67%, specificity of 78.57%, a positive likelihood ratio of 3.1, and a negative likelihood ratio of 0.4. Figure 3 (A)

[0059] Further analysis revealed that in patients with clinically active disease (including mild, moderate, and severe active phases), serum omentin-1 showed an increased AUC of 0.8302 in differentiating between extensive and distal colitis, with a cutoff point of 50.65 ng / mL, sensitivity of 73.33%, specificity of 88.68%, positive likelihood ratio of 6.5, and negative likelihood ratio of 0.3. Figure 3 (Middle B). Further subdivision: In patients with mildly active UC, serum omentin-1 showed an AUC of 0.8718 in differentiating between extensive and distal colitis, with a cutoff point of 68 ng / mL, sensitivity of 66.67%, specificity of 84.62%, positive likelihood ratio of 4.3, and negative likelihood ratio of 0.4. Figure 4 In patients with moderately active UC, serum omentin-1 showed an AUC of 0.8 in differentiating between extensive and distal colitis, with a cutoff point of 52.75 ng / mL, sensitivity of 66.74%, specificity of 88.24%, positive likelihood ratio of 5.1, and negative likelihood ratio of 0.5. Figure 4In patients with clinically severe active UC, serum retinin-1 showed an AUC of 0.8129 in differentiating between extensive and distal colitis, with a cutoff point of 45.9 ng / mL, sensitivity of 87.35%, specificity of 62.47%, positive likelihood ratio of 2.2, and negative likelihood ratio of 0.2. Figure 4 (C)

[0060] In patients with active endoscopic procedures, the AUC further increased to 0.8870, with a cutoff point of 51.25 ng / mL, a sensitivity of 79.31%, a specificity of 89.36%, a positive likelihood ratio of 7.5, and a negative likelihood ratio of 0.2. Figure 3 (C)

[0061] The above results further confirm that serum retinin-1 can be used clinically to determine the extent of active UC lesions, and it is quite effective.

[0062] Example 2 This embodiment verifies the diagnostic efficacy described above in UC queue 2 of Embodiment 1.

[0063] In cohort 2: the total number of UC patients n = 80 (of which, distal type n = 54 and extensive type n = 26); Clinical active phase n = 57 (of which, distal type n = 35, widespread type n = 22), clinical remission phase n = 23 (of which, distal type n = 19, widespread type n = 4); Endoscopic active phase n = 50 (of which, distal type n = 28, extensive type n = 22), endoscopic remission phase n = 30 (of which, distal type n = 26, extensive type n = 4).

[0064] In the total UC population of cohort 2, when distinguishing between distal and extensive UC, the AUC was 0.7412, corresponding to a cutoff point of 54.55 ng / mL, with a sensitivity of 70.2%, specificity of 84.38%, a positive likelihood ratio of 6.3, and a negative likelihood ratio of 0.4. Figure 5 (A)

[0065] In patients with active clinical disease, serum omentin-1 showed an increased AUC of 0.8188 in differentiating between extensive and distal colitis, with a cutoff point of 51.45 ng / mL, sensitivity of 79.17%, specificity of 83.72%, positive likelihood ratio of 4.9, and negative likelihood ratio of 0.2. Figure 5 (Middle B). In patients with mild active UC, serum omentin-1 showed an AUC of 0.8704 in differentiating between extensive and distal colitis, with a cutoff point of 67.5 ng / mL, sensitivity of 67.57%, specificity of 88.89%, positive likelihood ratio of 6.0, and negative likelihood ratio of 0.4. Figure 6In patients with moderately active UC, serum retinin-1 showed an AUC of 0.9048 in differentiating between extensive and distal colitis, with a cutoff point of 55.25 ng / mL, sensitivity of 85.71%, specificity of 88.56%, positive likelihood ratio of 7.7, and negative likelihood ratio of 0.2. Figure 6 In patients with clinically severe active UC, serum retinin-1 showed an AUC of 0.7917 in differentiating between extensive and distal colitis, with a cutoff point of 37.95 ng / mL, sensitivity of 66.59%, specificity of 75%, positive likelihood ratio of 2.7, and negative likelihood ratio of 0.4. Figure 6 (C) In patients with active endoscopic procedures, the AUC further increased to 0.8882, with a cutoff point of 50.65 ng / mL, a sensitivity of 86.96%, a specificity of 88.57%, a positive likelihood ratio of 7.6, and a negative likelihood ratio of 0.1. Figure 5 (C)

[0066] The above results further confirm that serum retinin-1 can be used clinically to determine the extent of active UC lesions, and it is quite effective.

[0067] Example 3 This embodiment provides a device for predicting the extent of intestinal lesions in ulcerative colitis, which includes an input module, a control module, and an output module.

[0068] The input module is configured to input the feature data of Omentin-1 contained in the subject's test sample; The control module includes: a result analysis module, which is configured to: generate a prediction result of the extent of intestinal lesions in the subject's ulcerative colitis based on the feature data of Omentin-1 contained in the subject's sample; the prediction result of the extent of lesions is: a prediction result that distinguishes between extensive colitis and distal colitis.

[0069] The results analysis module compares the concentration of Omentin-1 in the subject's sample with a predetermined threshold. Based on the comparison results, it generates a predicted range of intestinal lesions in the subject with ulcerative colitis. The predetermined threshold is obtained directly from the generated ROC curve.

[0070] The output module is configured to output the predicted extent of intestinal lesions in the subject with ulcerative colitis.

[0071] In summary, this invention is the first to discover that a type of lipoprotein, Omentin-1, has good efficacy in predicting the extent of intestinal lesions in patients with active ulcerative colitis (UC). Serum Omentin-1 concentration measurements are objective, and peripheral serum samples are easy to obtain and minimally invasive, providing a new means for managing the dynamic changes in UC patients and showing promising clinical application prospects.

[0072] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. The application of a reagent for detecting biomarkers in the preparation of a predictive product for the extent of intestinal lesions in ulcerative colitis, characterized in that, The biomarker includes retinin-1; the predictive product is a predictive result of the extent of intestinal lesions in the subject's ulcerative colitis, generated based on the characteristic data of the biomarker contained in the subject's sample. The predicted product includes at least one of the following application methods: (1) Based on the characteristic data of the biomarkers contained in the subject's sample, generate a prediction result of the extent of intestinal lesions during the clinical active phase of ulcerative colitis in the subject; (2) Based on the characteristic data of the biomarkers contained in the subject's sample, generate a prediction result of the extent of endoscopic active intestinal lesions; The predicted extent of the intestinal lesions is the result of the prediction that distinguishes between extensive colitis and distal colitis.

2. The application according to claim 1, characterized in that, The biomarkers are those found in serum.

3. The application according to claim 1, characterized in that, The reagent used to detect the biomarker is a reagent for detecting the level of the retinin-1 protein of the biomarker.

4. The application according to claim 1, characterized in that, The predicted product is selected from at least one of reagents, test strips, kits, or chips.

5. The application according to claim 1, characterized in that, Based on the comparison between the concentration of the biomarker contained in the subject's sample and a predetermined threshold, a predicted result of the extent of intestinal lesions in the subject's ulcerative colitis is generated according to the comparison result. The predetermined threshold is either a threshold obtained from a directly generated ROC curve, or a threshold obtained from a ROC curve generated based on a machine learning model.

6. A device for predicting the extent of intestinal lesions in ulcerative colitis, characterized in that, It includes: Input module, control module, and output module; The input module is configured to input characteristic data of biomarkers contained in the subject's sample to be tested; The biomarker includes retinin-1; The control module includes: a result analysis module, which is configured to generate at least one of the following prediction results based on the characteristic data of the biomarkers contained in the subject's test sample, based on the comparison of the concentration of the biomarkers contained in the subject's test sample with a predetermined threshold: (1) generating a prediction result of the extent of intestinal lesions during the clinical active phase of ulcerative colitis in the subject; (2) generating a prediction result of the extent of intestinal lesions during the active phase under endoscopy. The predicted extent of the intestinal lesions is: the predicted outcome that distinguishes between extensive colitis and distal colitis; the characteristic data of the biomarkers refer to: the concentration of the biomarkers contained in the subject's sample. The predetermined threshold is either a threshold obtained by directly generating the ROC curve, or a threshold obtained by generating the ROC curve based on a machine learning model. The output module is configured to output the predicted extent of intestinal lesions in the subject's ulcerative colitis.

7. A computer-readable storage medium, characterized in that, The storage medium stores a set of executable program instructions. The at least one instruction and the set of executable program instructions are loaded and executed by a processor to implement a method for predicting the extent of intestinal lesions in ulcerative colitis. The method for predicting the extent of intestinal lesions in ulcerative colitis is based on the application method described in any one of claims 1-5.

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