System for diagnosing primary biliary cholangitis by molecular marker expression amount

Abstract

The present disclosure finds that TGFBI in a plasma sample can serve as a diagnostic molecular marker for primary biliary cholangitis, provides a molecular marker and diagnostic model with high specificity and high sensitivity for individualized diagnosis and treatment of primary biliary cholangitis, and provides a new, efficient and non-invasive auxiliary tool for the clinician to formulate a diagnostic scheme for primary biliary cholangitis.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of biomedicine, in particular to a system for diagnosing primary biliary cholangitis by the expression level of a molecular marker, a system for determining the individual effectiveness of UDCA in treating patients with primary biliary cholangitis by the expression level of a molecular marker, use of a reagent for quantitatively detecting the expression level of a molecular marker in the preparation of a kit for diagnosing primary biliary cholangitis, use of a reagent for quantitatively detecting the expression level of a molecular marker in the preparation of a kit for determining the individual effectiveness of UDCA in treating patients with primary biliary cholangitis, a kit for diagnosing primary biliary cholangitis, and a kit for determining the individual effectiveness of UDCA in treating patients with primary biliary cholangitis. BACKGROUND

[0002] Primary biliary cholangitis (PBC) is a chronic autoimmune cholestatic liver disease, which is characterized by chronic cholestasis and interlobular bile duct destruction, and then induces liver fibrosis and cirrhosis, and severe cases can progress to cirrhosis, liver failure, and then threaten the life of the patient. PBC is more common in middle-aged women over 40 years old, and the male-to-female ratio of patients is about 1:10. Patients in the early stage of the disease may have non-specific symptoms such as skin itching, fatigue, and liver discomfort. Currently, there are three main standards for diagnosing PBC in clinical practice: (1) patients have detectable anti-mitochondrial antibodies (AMA) or anti-mitochondrial antibody M2 subtype (AMA-M2) in serum; (2) serum alkaline phosphatase (ALP) or glutamyl transpeptidase (GGT) is progressively elevated; (3) liver biopsy shows PBC pathological changes. Two of the above three diagnostic criteria can diagnose PBC. Some PBC patients in clinical practice only show AMA or AMA-M2 positive, while the levels of ALP or GGT are normal. These patients need to be further evaluated by liver biopsy to determine whether they have PBC. However, liver biopsy is an invasive procedure, which is often difficult for patients to accept, leading to delayed diagnosis of PBC patients and difficulty in early treatment. Ursodeoxycholic acid (UDCA) is a first-line drug for treating PBC. However, about 40% of patients in clinical practice have poor response to this drug, and need to choose second-line treatment drugs in time to improve the symptoms of patients and delay the occurrence of cirrhosis.

[0003] Therefore, there is an urgent need to provide a new marker that helps early diagnosis of PBC and reflects the efficacy of UDCA in treating PBC, thereby improving the prognosis of patients. SUMMARY

[0004] The present disclosure aims to provide a new marker and system that helps early diagnosis of primary biliary cholangitis and reflects the efficacy of UDCA treatment for primary biliary cholangitis.

[0005] To achieve the above-mentioned purpose, the present disclosure provides a system for diagnosing primary biliary cholangitis by molecular marker expression, which comprises a computing device, an input device for inputting the expression of molecular markers of a primary biliary cholangitis patient, and an output device for outputting the diagnosis result of primary biliary cholangitis; wherein the molecular markers comprise TGFBI;

[0006] The computing device comprises a memory and a processor, the memory stores a computer program, and the processor is configured to execute the computer program stored in the memory to realize a modeling algorithm and an algorithm of a discriminant function as shown in formula (1); the modeling algorithm is a support vector machine algorithm and / or a least squares algorithm;

[0007] F1(c1) = sgn[f1(c1) + b1] Formula (1)

[0008] In formula (1), F1(c1) represents the diagnosis result of primary biliary cholangitis, and the return value of F1(c1) is 1, indicating support, and the return value is -1, indicating rejection; c1 represents the absolute expression of TGFBI; f1(c1) is a kernel function trained according to the modeling algorithm, and b1 is a critical score value trained according to the modeling algorithm.

[0009] On the other hand, the present disclosure provides a system for determining the effectiveness of UDCA treatment for a primary biliary cholangitis patient by molecular marker expression, which comprises a computing device, an input device for inputting the expression of molecular markers of a primary biliary cholangitis patient, and an output device for outputting the effectiveness result of UDCA treatment for a primary biliary cholangitis patient; wherein the molecular markers comprise TGFBI;

[0010] The computing device comprises a memory and a processor, the memory stores a computer program, and the processor is configured to execute the computer program stored in the memory to realize a modeling algorithm and an algorithm of a discriminant function as shown in formula (2); the modeling algorithm is a support vector machine algorithm and / or a least squares algorithm;

[0011] F2(c2) = sgn[f2(c2) + b2] Formula (2)

[0012] In formula (2), F2(c2) represents the individual effectiveness of UDCA treatment for patients with primary biliary cholangitis, F2(c2) returns 1 to represent effectiveness, and returns -1 to represent ineffectiveness; c2 represents the absolute expression amount of TGFBI; f2(c2) is a kernel function trained according to the modeling algorithm; and b2 is a critical score value trained according to the modeling algorithm.

[0013] The molecular marker TGFBI (Transforming growth factor-beta-induced protein ig-h3) in the present disclosure is derived from a plasma sample of the patient with primary biliary cholangitis, is an extracellular matrix protein regulated by TGF-β, is composed of 683 amino acids and has a molecular weight of 68 kDa, and plays an important biological function in an extracellular environment, is widely expressed in major organs of the human body such as the kidney, heart, pancreas, liver and muscle tissue, and mainly participates in biological activities such as proliferation, adhesion, migration, differentiation and apoptosis between tissue cells through integrin α1β1, α3β1, α6β4, αmβ2, αvβ3 and αvβ5.

[0014] Optionally, the system further comprises a detection device for detecting the expression amount of the molecular marker; and the detection device comprises an enzyme-linked immunosorbent instrument.

[0015] Optionally, in formula (1), the unit of c1 is pg / mL, f1(c1) = 1 x c1, and b1 = -274889; and in formula (2), the unit of c2 is pg / mL, f2(c2) = 1 x c2, and b2 = -474869.

[0016] Optionally, the detection device further comprises an antibody reagent for quantitatively detecting the expression amount of the molecular marker, and the antibody reagent comprises a biotin-labeled rabbit anti-human transforming growth factor-beta-induced protein IG-H3 antibody.

[0017] In another aspect, the present disclosure provides use of a reagent for quantitatively detecting the expression amount of a molecular marker, which is TGFBI, in the preparation of a kit for diagnosing primary biliary cholangitis.

[0018] In another aspect, the present disclosure provides use of a reagent for quantitatively detecting the expression amount of a molecular marker, which is TGFBI, in the preparation of a kit for determining the individual effectiveness of UDCA treatment for patients with primary biliary cholangitis.

[0019] In another aspect, the present disclosure provides a kit for diagnosing primary biliary cholangitis, which comprises a reagent for quantitatively detecting the expression amount of a molecular marker, which is TGFBI.

[0020] In another aspect, the present disclosure provides a kit for determining the individual effectiveness of UDCA treatment for patients with primary biliary cholangitis, the kit comprising reagents for quantitatively detecting the expression level of a molecular marker, the molecular marker being TGFBI.

[0021] Optionally, the process of quantitatively detecting the expression level of the molecular marker comprises:

[0022] S1, obtaining a plasma sample of a patient with primary biliary cholangitis;

[0023] S2, determining the expression level of TGFBI in the plasma sample.

[0024] Through the above technical solution, the present disclosure finds that TGFBI in a plasma sample can be used as a diagnostic molecular marker for primary biliary cholangitis, and provides a molecular marker and a diagnostic model with high specificity and high sensitivity for individualized diagnosis and treatment of primary biliary cholangitis, and provides a new, efficient and non-invasive auxiliary tool for formulating a diagnostic scheme for primary biliary cholangitis in the clinic.

[0025] Other features and advantages of the present disclosure will be described in detail in the following specific embodiments section. BRIEF DESCRIPTION OF DRAWINGS

[0026] The accompanying drawings are included to provide a further understanding of the present disclosure and constitute a part of the specification, and are used together with the following specific embodiments to explain the present disclosure but do not constitute a limitation thereof. In the drawings:

[0027] Figure 1 is a determination graph of the expression level of TGFBI in the plasma of patients with PBC, SS, CHB and HC.

[0028] Figure 2 is a ROC curve analysis graph of TGFBI (PBC VS HC).

[0029] Figure 3 is a ROC curve analysis graph of TGFBI (PBC VS HC+SS+CHB).

[0030] Figure 4 is a comparison graph of the expression level of TGFBI in the plasma of patients with PBC and HC who have not been treated, have responded to UDCA treatment and have not responded to UDCA treatment.

[0031] Figure 5 is a ROC curve analysis graph of TGFBI (PBC patients who have responded to UDCA treatment and have not responded to UDCA treatment). DETAILED DESCRIPTION

[0032] The specific embodiments of the present disclosure are described in detail below. It should be understood that the specific embodiments described herein are merely intended for illustration and explanation of the present disclosure and are not intended to limit the present disclosure.

[0033] In one aspect, the present disclosure provides a system for diagnosing primary biliary cholangitis by molecular marker expression, comprising a computing device, an input device for inputting the molecular marker expression of a primary biliary cholangitis patient individual, and an output device for outputting the diagnosis result of primary biliary cholangitis; wherein the molecular marker comprises TGFBI;

[0034] The computing device comprises a memory and a processor, the memory stores a computer program, and the processor is configured to execute the computer program stored in the memory to realize a modeling algorithm and an algorithm of a discriminant function as shown in formula (1); the modeling algorithm is a support vector machine algorithm and / or a least squares algorithm;

[0035] F1(c1) = sgn[f1(c1) + b1] Formula (1)

[0036] In formula (1), F1(c1) represents the diagnosis result of primary biliary cholangitis, and F1(c1) returns 1 indicating support and -1 indicating rejection; c1 represents the absolute expression of TGFBI; f1(c1) is a kernel function trained according to the modeling algorithm, and b1 is a critical score value trained according to the modeling algorithm.

[0037] In another aspect, the present disclosure provides a system for determining the effectiveness of UDCA treatment for a primary biliary cholangitis patient individual by molecular marker expression, comprising a computing device, an input device for inputting the molecular marker expression of a primary biliary cholangitis patient individual, and an output device for outputting the effectiveness result of UDCA treatment for a primary biliary cholangitis patient individual; wherein the molecular marker comprises TGFBI;

[0038] The computing device comprises a memory and a processor, the memory stores a computer program, and the processor is configured to execute the computer program stored in the memory to realize a modeling algorithm and an algorithm of a discriminant function as shown in formula (2); the modeling algorithm is a support vector machine algorithm and / or a least squares algorithm;

[0039] F2(c2) = sgn[f2(c2) + b2] Formula (2)

[0040] In formula (2), F2(c2) represents the individual effectiveness of UDCA treatment for patients with primary biliary cholangitis, F2(c2) returns 1 to represent effectiveness, and returns -1 to represent ineffectiveness; c2 represents the absolute expression amount of TGFBI; f2(c2) is a kernel function trained according to the modeling algorithm; and b2 is a critical score value trained according to the modeling algorithm.

[0041] Optionally, the molecular marker TGFBI (Transforming growth factor-beta-induced protein ig-h3) is derived from a plasma sample of the patient with primary biliary cholangitis, is an extracellular matrix protein regulated by TGF-β, is composed of 683 amino acids and has a molecular weight of 68 kDa, and plays an important biological function in an extracellular environment, is widely expressed in major organs of the human body such as the kidney, heart, pancreas, liver and muscle tissue, and mainly participates in biological activities such as proliferation, adhesion, migration, differentiation and apoptosis between tissue cells through integrin α1β1, α3β1, α6β4, αmβ2, αvβ3 and αvβ5.

[0042] Optionally, the system further comprises a detection device for detecting the expression amount of the molecular marker; and the detection device comprises an enzyme-linked immunosorbent instrument.

[0043] Optionally, in formula (1), the unit of c1 is pg / mL, f1(c1) = 1 × c1, and b1 = -274889; and in formula (2), the unit of c2 is pg / mL, f2(c2) = 1 × c2, and b2 = -474869.

[0044] Optionally, the detection device further comprises an antibody reagent for quantitatively detecting the expression amount of the molecular marker, and the antibody reagent comprises a biotin-labeled rabbit anti-human transforming growth factor-beta-induced protein IG-H3 antibody.

[0045] In another aspect, the present disclosure provides use of a reagent for quantitatively detecting the expression amount of a molecular marker, which is TGFBI, in the preparation of a kit for diagnosing primary biliary cholangitis.

[0046] In another aspect, the present disclosure provides use of a reagent for quantitatively detecting the expression amount of a molecular marker, which is TGFBI, in the preparation of a kit for determining the individual effectiveness of UDCA treatment for patients with primary biliary cholangitis.

[0047] In another aspect, the present disclosure provides a kit for diagnosing primary biliary cholangitis, which comprises a reagent for quantitatively detecting the expression amount of a molecular marker, which is TGFBI.

[0048] In another aspect, the present disclosure provides a kit for determining the individual effectiveness of UDCA treatment for primary biliary cholangitis patients, the kit comprising reagents for quantitatively detecting the expression level of a molecular marker, the molecular marker being TGFBI.

[0049] Optionally, the process of quantitatively detecting the expression level of the molecular marker comprises:

[0050] S1, obtaining a plasma sample of a primary biliary cholangitis patient;

[0051] S2, determining the expression level of TGFBI in the plasma sample.

[0052] The present disclosure is further described in detail by the following examples. The raw materials used in the examples can be obtained by commercial channels.

[0053] The present disclosure detects the expression level of TGFBI protein (index number in NCBI database: NP_000349.1) in the plasma of 129 PBC patients, 16 Sjogren syndrome (SS) patients, 16 chronic hepatitis B (CHB) patients and 31 gender and age matched healthy controls (HC) by enzyme linked immunosorbent assay (ELISA), analyzes the absorbance of the standard and the detection sample by the enzyme marker, plots the standard curve of the obtained standard absorbance value and its standard concentration, and calculates the plasma TGFBI concentration of the sample to be tested. Kruskal-Wallis test is used to compare and analyze the differences in the expression level of TGFBI between PBC patients, SS patients, CHB patients and HC, and further evaluate the diagnostic value of TGFBI for PBC by receiver operating characteristic curve (ROC) analysis. In addition, the PBC patients are further divided into three groups according to the UDCA treatment and POISE treatment response standard, i.e. 19 cases of untreated group, 56 cases of UDCA treatment response group and 54 cases of UDCA treatment non-response group, for evaluating the performance of TGFBI in reflecting the UDCA treatment effect of PBC patients.

[0054] Example 1

[0055] Experimental process:

[0056] 1. Screening of subject samples: Inclusion criteria for PBC patients: (1) The subject's serum AMA or AMA-M2 is positive; (2) The subject's serum ALP and GGT levels are elevated; (3) The subject's liver biopsy examination is consistent with the pathological manifestations of PBC. A diagnosis of PBC can be made if two of the above three criteria are met;

[0057] Inclusion criteria for SS patients: The diagnosis of SS meets the consensus criteria of the United States-Europe on SS;

[0058] Inclusion criteria for CHB patients: The diagnosis meets the diagnostic criteria of the "Guidelines for the Prevention and Treatment of Chronic Hepatitis B (2019 Edition)" developed by the Chinese Medical Association Hepatology Branch and the Chinese Medical Association Infectious Disease Branch;

[0059] Inclusion criteria for HC: The samples of healthy people are collected at the same time, and the gender and age of the healthy people are matched with those of the PBC patients.

[0060] The research protocol of this example has been approved by the Ethics Committee of Beijing Union Medical College of the Chinese Academy of Medical Sciences.

[0061] 2. Sample collection:

[0062] 2 mL of venous blood was collected from all subjects before the experiment, and the specimen was centrifuged at 1000 x g for 15 minutes at 4°C after collection. The supernatant plasma was aliquoted and frozen at -80°C to avoid repeated freeze-thawing.

[0063] 3. Detection of plasma TGFBI protein levels by ELISA

[0064] 3.1, Pretreatment

[0065] (1) Take the kit and samples out of the refrigerator and equilibrate to room temperature (about 30 minutes);

[0066] (2) Add 1 part of concentrated washing solution to 24 parts of deionized water and mix well for use;

[0067] (3) Take one standard from the kit, centrifuge at 10000 rpm for 3 seconds, dissolve with 1 mL of sample diluent, and repeatedly suck and hit the bottom of the cryogenic tube with a gun head 5 times to help dissolve, mix thoroughly to get standard S7, and place for standby;

[0068] (4) Take 7 1.5 mL centrifuge tubes (S0-S6) in turn, add 250 μL of sample diluent to each, suck 250 μL of standard S7 into the first centrifuge tube (S6), mix gently, suck 250 μL from S6 into the second EP tube (S5), mix gently; dilute the standard in the same way, S0 is the sample diluent;

[0069] (5) Dilute the plasma sample with sample diluent by 1:100.

[0070] 3.2, Detection process:

[0071] (1) Set standard hole and sample hole respectively, add 100 μL of standard or sample to each hole, mix gently, cover with plate sticker, incubate at 37°C for 2 hours;

[0072] (2) Discard the liquid and spin dry, do not wash;

[0073] (3) Add 100 μL of biotin-labeled rabbit anti-human transforming growth factor-β-induced protein IG-H3 antibody working solution to each hole, cover with a new plate sticker, incubate at 37°C for 1 hour; the antibody is a TGFBI antibody derived from rabbit anti-human transforming growth factor-β-induced protein IG-H3 antibody.

[0074] (4) Discard the liquid in the hole, spin dry, wash the plate 3 times; each time soak for 2 minutes, 200 μL per hole, spin dry;

[0075] (5) Add 100 μL of horseradish peroxidase-labeled avidin working solution to each hole, cover with a new plate sticker, incubate at 37°C for 1 hour;

[0076] (6) Discard the liquid in the hole, spin dry, wash the plate 5 times, each time soak for 2 minutes, 200 μL per hole, spin dry;

[0077] (7) Add 90 μL of substrate solution to each hole in turn, develop color at 37°C for 15-30 minutes;

[0078] (8) Add 50 μL of termination solution to each hole in turn to terminate the reaction;

[0079] (9) Within 5 minutes after the reaction is terminated, measure the optical density (OD value) of each hole in turn with an enzyme marker at a wavelength of 450 nm.

[0080] 4, Data analysis:

[0081] Subtract the S0 hole value from the standard and sample values, then plot the curve with the concentration of the standard as the vertical coordinate (logarithmic coordinate) and the OD value as the horizontal coordinate (logarithmic coordinate), use computer software "Curve Expert" to fit and draw the standard curve, calculate the regression equation of the standard curve with the concentration and OD value of the standard, substitute the OD value of the sample into the equation, calculate the sample concentration, and multiply by the sample dilution factor 100 to obtain the actual concentration of the sample. Use GraphPad 9.0 to calculate the median of each group of data and calculate the P value, P<0.05 is considered to have statistical significance.

[0082] 5, Model construction:

[0083] Based on the concentration of the above-mentioned analysis markers, the least square method and the support vector machine algorithm were used to construct the diagnostic model of primary biliary cholangitis, as follows: the absolute concentration (pg / mL) of the molecular markers detected by ELISA was used as the data set.

[0084] The above data set was randomly divided into 4 data sets, of which 1 data set was used as the training set for diagnosing primary biliary cholangitis, 1 data set was used as the validation set for diagnosing primary biliary cholangitis; 1 data set was used as the training set for determining the effectiveness of UDCA treatment for primary biliary cholangitis patients, and 1 data set was used as the validation set for determining the effectiveness of UDCA treatment for primary biliary cholangitis patients; the calculation coefficients and threshold values of the components (absolute concentrations of molecular markers) in the above-mentioned two training sets were used to train the model, and the above-mentioned two validation sets were used for evaluation, and the discriminant function of the model is shown in equations (1) and (2):

[0085] F1(c1) = sgn [f1(c1) + b1] Equation (1)

[0086] F2(c2) = sgn [f2(c2) + b2] Equation (2).

[0087] In equation (1), c1 represents the absolute expression amount of TGFBI, and c2 represents the absolute expression amount of TGFBI after using UDCA to treat primary biliary cholangitis patients; F1(c1) and F2(c2) represent the diagnosis results of primary biliary cholangitis, and the return value of 1 indicates support, and the return value of -1 indicates rejection; f1(c1) and f2(c2) are kernel functions trained according to the modeling algorithm, and b1 and b2 are critical score values trained according to the modeling algorithm; the unit of c1 is pg / mL, f1(c1) takes 1×c1, b1 is -274889, the unit of c2 is pg / mL, f2(c2) takes 1×c2, b2 is -474869, that is, the discriminant function is as follows:

[0088] F1(c1) = sgn [1×c1-274889] Equation (1)

[0089] F2(c2) = sgn [1×c2-474869] Equation (2).

[0090] Example 2

[0091] The model established in Example 1 was further verified in this example:

[0092] The expression levels of plasma TGFBI in PBC, SS, CHB and HC were determined respectively: the expression level of plasma TGFBI in PBC (476918 (310729-816274) pg / mL) was significantly higher than that in SS (255422 (151046-441816) pg / mL), CHB (129356 (94498-306476) pg / mL) and HC (201203 (126899-293227) pg / mL) (PBC VS SS: P=0.003; PBC VS CHB: P<0.0001; PBC VS HC: P<0.0001), and the results are shown in Figure 1 .

[0093] The HC was included in the control group of ROC curve analysis, and the results are shown in Figure 2 , the plasma TGFBI concentration > 366882 pg / mL, when used for the diagnosis of PBC, the AUC was 0.839, the sensitivity was 65.12%, and the specificity was 90.32%.

[0094] The HC, SS and CHB were included in the control group of ROC curve analysis, and the results are shown in Figure 3 , the plasma TGFBI concentration > 274889 pg / mL, when used for the diagnosis of PBC, the AUC was 0.820, the sensitivity was 79.84%, and the specificity was 69.84%.

[0095] Comparison of the levels of plasma TGFBI in untreated, UDCA treatment responsive and UDCA treatment non-responsive PBC patients: the expression level of plasma TGFBI in UDCA treatment non-responsive PBC patients (686859 (475517-1038136) pg / mL) was significantly higher than that in UDCA treatment responsive PBC patients (324793 (224245-472443) pg / mL) and HC (201203 (126899-293227) pg / mL) (UDCA treatment non-responders VS UDCA treatment responders: P<0.0001; UDCA treatment non-responders VS HC: P<0.0001; UDCA treatment responders VS HC: P=0.0062), as shown in Figure 4 . The expression level of plasma TGFBI in untreated PBC patients (565570 (345547-1243905) pg / mL) was significantly higher than that in UDCA treatment responsive PBC patients and HC (untreated PBC VS HC: P<0.0001), but there was no significant change compared with UDCA treatment non-responsive PBC patients.

[0096] Analysis of the differential efficiency of plasma TGFBI for UDCA treatment response and UDCA treatment non-response PBC patients: UDCA treatment response PBC patients were included in the control group of ROC curve analysis, and the results are shown in Figure 5 Figure 6, when used to identify UDCA treatment non-response PBC patients, the AUC of plasma TGFBI concentration > 474869 pg / mL was 0.824, the sensitivity was 76.79%, and the specificity was 75.93%.

[0097] As can be seen from the above scheme, the TGFBI provided by the present disclosure can be used as a molecular marker for diagnosing primary biliary cholangitis, and can be used as a molecular marker for determining the individual effectiveness of UDCA treatment for primary biliary cholangitis patients; and the present disclosure provides a diagnosis and prediction model for primary biliary cholangitis with good clinical value.

[0098] The above describes the preferred embodiments of the present disclosure, but the present disclosure is not limited to the specific details in the above embodiments, and various simple modifications can be made to the technical solutions of the present disclosure within the technical concept of the present disclosure, and these simple modifications all belong to the protection scope of the present disclosure.

[0099] In addition, it should be noted that each specific technical feature described in the above specific embodiments can be combined in any appropriate manner without contradiction. In order to avoid unnecessary repetition, various possible combinations are not described again by the present disclosure.

[0100] Furthermore, any combination of various different embodiments of the present disclosure can also be made, as long as it does not deviate from the idea of the present disclosure, it should also be considered as disclosed by the present disclosure.

Claims

1. A system for diagnosing primary biliary cholangitis based on the expression levels of molecular markers, characterized in that, The system includes a computing device, an input device for inputting the expression levels of molecular markers in an individual patient with primary biliary cholangitis, and an output device for outputting the diagnostic results of primary biliary cholangitis; wherein the molecular markers include TGFBI; The computing device includes a memory and a processor, the memory storing a computer program, and the processor being configured to execute the computer program stored in the memory to implement a modeling algorithm and an algorithm for a discriminant function as shown in equation (1); the modeling algorithm is a support vector machine algorithm and / or a least partial squares algorithm. Equation (1) In equation (1), F1(c1) represents the diagnosis result of primary biliary cholangitis. A return value of 1 for F1(c1) indicates support, and a return value of -1 indicates rejection. c1 represents the absolute expression level of TGFBI. f1(c1) is the kernel function trained according to the modeling algorithm, and b1 is the critical score value trained according to the modeling algorithm.

2. A system for determining the individual effectiveness of UDCA treatment in patients with primary biliary cholangitis by measuring the expression levels of molecular markers, characterized in that, The system includes a computing device, an input device for inputting the expression levels of molecular markers in an individual patient with primary biliary cholangitis, and an output device for outputting the effectiveness results of UDCA treatment in an individual patient with primary biliary cholangitis; wherein the molecular markers include TGFBI; The computing device includes a memory and a processor. The memory stores a computer program, and the processor is configured to execute the computer program stored in the memory to implement a modeling algorithm and an algorithm for a discriminant function as shown in equation (2). The modeling algorithm is a support vector machine algorithm and / or a least partial squares algorithm. Equation (2) In equation (2), F2(c2) represents the individual effectiveness of UDCA treatment for patients with primary biliary cholangitis. A return value of 1 for F2(c2) indicates effectiveness, and a return value of -1 indicates ineffectiveness. c2 represents the absolute expression level of TGFBI. f2(c2) is the kernel function trained according to the modeling algorithm, and b2 is the critical score value trained according to the modeling algorithm.

3. The system according to claim 1 or 2, wherein, The molecular marker TGFBI was derived from plasma samples from patients with primary biliary cholangitis.

4. The system according to claim 1 or 2, wherein, The system also includes a detection device for detecting the expression level of molecular markers; the detection device includes an enzyme-linked immunosorbent assay (ELISA) instrument.

5. The system according to claim 1 or 2, wherein, In equation (1), the unit of c1 is pg / mL, f1(c1)=1×c1, b1=-274889; in equation (2), the unit of c2 is pg / mL, f2(c2)=1×c2pg / mL, b2 is -474869.

6. The use of reagents for quantitatively detecting the expression levels of molecular markers in the preparation of kits for diagnosing primary biliary cholangitis, characterized in that, The molecular marker is TGFBI.

7. The use of reagents for quantitatively detecting the expression levels of molecular markers in the preparation of kits for determining the individual efficacy of UDCA treatment in patients with primary biliary cholangitis, characterized in that, The molecular marker is TGFBI.

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