Biomarker as well as screening method and application thereof

Abstract

The invention relates to a biomarker as well as a screening method and application thereof, and relates to the technical field of liver injury biomarkers. The biomarker is one or more of CD5L, GSTO1 (Glutathione S-Transferase Oxidase 1) and DNPEP (Deoxyribose Nucleic Acid The application of the biomarker comprises an application in preparation of products for identifying liver injury and an application in preparation of products for identifying drug-induced liver injury and autoimmune hepatitis. By adopting the biomarker provided by the invention, the accuracy of liver injury identification and identification between DILI and AIH can be improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of liver injury biomarkers, and in particular, to a biomarker and a screening method thereof, as well as applications in identifying liver injury, DILI and AIH. Background Art

[0002] Drug-induced liver injury (DILI) and autoimmune hepatitis (AIH) are currently the main causes of non-viral unexplained liver disease.

[0003] Liver tissue puncture pathological biopsy is an important auxiliary means for the diagnosis of unexplained liver injury, and it has important value in the diagnosis of DILI and AIH. Previous studies have shown that eosinophil infiltration and hepatocellular cholestasis are more common in DILI. Compared with DILI, significant fibrosis is more common in AIH. There are also literatures that have found that acute onset AIH includes acute manifestations and acute exacerbations of chronic diseases, and central lobular necrosis may be the main pathological feature. The new expert consensus launched by the International AIH Pathology Group in 2022 also emphasizes the acute manifestations of AIH, and regards both portal inflammation and lobular inflammation as pathological features of AIH. Recent evidence shows that the simplified diagnostic criteria for AIH in 2008, that is, histological features such as hepatocyte rosettes and lymphocyte penetration are considered necessary for "typical AIH", can also be found in other inflammatory liver diseases such as viral hepatitis. In the case of severe hepatocyte damage, hepatocyte rosette manifestations are an indication of hepatocyte regeneration, rather than pointing to a specific cause, and they lack diagnostic specificity for AIH. Centrilobular lesions with marked hepatocellular necrosis are considered part of the histological spectrum of AIH, and this histological feature is mainly associated with DILI but is also regularly found in severe acute manifestations of AIH. Therefore, liver histopathology can be used as an auxiliary diagnostic tool but cannot completely distinguish DILI from AIH.

[0004] At present, AIH and DILI are diagnosed clinically using the AIH 2008 simplified score and RUCAM, respectively. However, both require the exclusion of other diagnoses and lack accurate diagnostic biomarkers. The AIH simplified diagnostic scoring system is useful in excluding other diseases and diagnosing AIH patients with typical immune features, but it is difficult to identify atypical AIH cases. RUCAM mainly relies on establishing the temporal relationship between drug exposure and liver injury, as well as clinical outcomes and liver function during follow-up, and excluding other causes. The final diagnosis is divided into possible, probable, and extremely likely, and none of them can directly determine the diagnosis of DILI. The accurate diagnosis of DILI and AIH is very important for patients: if recurrent DILI is misdiagnosed as AIH recurrence, patients may use unnecessary immunosuppressive therapy for a long time, which will bring adverse drug reactions and psychological burden; if atypical AIH is misdiagnosed as DILI, immunosuppressive therapy will be delayed, and patients may have persistent hepatitis and progressive fibrosis, or even progress to cirrhosis. In short, the accurate differentiation of DILI and AIH is still a challenging problem, and biomarkers are urgently needed to distinguish DILI from AIH. Therefore, finding biomarkers for early identification of DILI and AIH is an important issue that needs to be addressed in this field.

[0005] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0006] The purpose of the present disclosure is to overcome the deficiencies of the above-mentioned prior art and to provide a biomarker and a screening method and application thereof. By detecting the biomarkers CD5L, GSTO1, and DNPEP, it can be used to identify liver damage, and can also be used to identify drug-induced liver damage and autoimmune hepatitis, thereby improving the efficiency and accuracy of identifying liver damage.

[0007] According to a first aspect of the present disclosure, a biomarker is provided, wherein the biomarker is one or more of CD5L, GSTO1, and DNPEP.

[0008] According to a second aspect of the present disclosure, there is provided a use of the above-mentioned biomarker in the preparation of a product for identifying liver damage.

[0009] In an exemplary embodiment of the present disclosure, the product for identifying liver damage identifies liver damage by detecting the expression levels of CD5L, GSTO1, and DNPEP in a liver tissue sample to be tested;

[0010] Compared with normal liver tissue samples, when CD5L is highly expressed and / or DNPEP is highly expressed and / or GSTO1 is lowly expressed, the liver tissue sample to be tested is determined to be liver damaged.

[0011] In an exemplary embodiment of the present disclosure, the product for identifying liver damage detects the expression levels of GSTO1 and DNPEP in serum samples to identify liver damage;

[0012] Compared with normal serum samples, when DNPEP is highly expressed and / or GSTO1 is highly expressed, the serum sample to be tested is determined to be liver damaged.

[0013] In an exemplary embodiment of the present disclosure, the product for identifying liver damage detects the expression level of DNPEP and / or GSTO1 in the serum sample to be tested, and identifies liver damage together with clinical detection parameters related to the blood sample.

[0014] According to a third aspect of the present disclosure, there is provided a use of the above-mentioned biomarker in the preparation of a product for identifying drug-induced liver injury and autoimmune hepatitis.

[0015] In an exemplary embodiment of the present disclosure, the product for distinguishing drug-induced liver injury and autoimmune hepatitis distinguishes drug-induced liver injury and autoimmune hepatitis by detecting the expression levels of CD5L, GSTO1, and DNPEP in the liver tissue sample to be tested;

[0016] Compared with the positive control of drug-induced liver injury, when CD5L is highly expressed and / or DNPEP is highly expressed and / or GSTO1 is lowly expressed, the liver tissue sample to be tested is determined to be autoimmune hepatitis;

[0017] Compared with the positive control of autoimmune hepatitis, when CD5L is lowly expressed and / or DNPEP is lowly expressed and / or GSTO1 is highly expressed, the liver tissue sample to be tested is determined to be drug-induced liver injury.

[0018] In an exemplary embodiment of the present disclosure, the product for distinguishing drug-induced liver injury and autoimmune hepatitis distinguishes drug-induced liver injury and autoimmune hepatitis by detecting the expression levels of CD5L and GSTO1 in the serum sample to be tested;

[0019] Compared with the positive control of drug-induced liver injury, when CD5L is highly expressed and / or GSTO1 is lowly expressed, the serum sample to be tested is determined to be autoimmune hepatitis;

[0020] Compared with the positive control of autoimmune hepatitis, when CD5L is lowly expressed and / or GSTO1 is highly expressed, the serum sample to be tested is determined to be drug-induced liver injury.

[0021] In an exemplary embodiment of the present disclosure, the product for identifying drug-induced liver injury and autoimmune hepatitis detects the expression level of GSTO1 and / or CD5L in the serum sample to be tested, and identifies drug-induced liver injury and autoimmune hepatitis together with clinical detection parameters related to the blood sample.

[0022] The present invention performs proteomic analysis on liver tissue samples and serum samples respectively, and then jointly analyzes the liver tissue proteomic results with the serum proteomic results to obtain protein biomarkers CD5L, DNPEP and GSTO1 that have significant differential expression in both DILI and VIH.

[0023] According to a third aspect of the present disclosure, a method for screening the above biomarkers is provided, comprising the following steps:

[0024] S10, obtaining experimental samples; the experimental samples include liver tissue samples and serum samples;

[0025] The liver tissue samples were divided into a first normal control group, a first drug-induced liver injury group, and a first autoimmune hepatitis group;

[0026] The serum samples were divided into a second normal control group, a second drug-induced liver injury group, and a second autoimmune hepatitis group;

[0027] S20, analyzing the liver tissue samples by microproteomics to obtain the protein analysis results of the liver tissue samples in each group; analyzing the serum samples by serum proteomics to obtain the protein analysis results of the serum samples in each group;

[0028] S30, a first subset consisting of differential proteins between the first drug-induced liver injury group and the first autoimmune hepatitis group; a second subset consisting of differential proteins between the second drug-induced liver injury group and the second autoimmune hepatitis group; a third subset consisting of proteins that exist in both liver tissue samples and serum samples and have inter-group differences;

[0029] The first subset, the second subset, and the third subset are intersected to obtain biomarkers.

[0030] On the one hand, the biomarker can be used to prepare products for identifying whether liver damage exists, and on the other hand, it can also be used to prepare products for identifying DILI and VIH, thereby improving the accuracy of clinical identification of liver damage and identification of DILI and VIH, and avoiding disease delays or inappropriate treatment methods caused by misdiagnosis.

[0031] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0033] Figure 1 Schematic diagram of the log2 distribution of protein abundance in each FFPE sample in the AIH group, DILI group, and HC group.

[0034] Figure 2 Schematic diagram of the proteomic PLS-DA analysis results of each FFPE sample in the AIH group, DILI group and HC group.

[0035] Figure 3 Schematic diagram of the cross-analysis results of the number of differentially expressed proteins in liver tissue proteomics in pairwise comparisons among AIH group, DILI group and HC group.

[0036] Figure 4 Schematic diagram of GO enrichment analysis results of differentially expressed proteins in liver tissue proteomics between AIH group and HC group.

[0037] Figure 5 Schematic diagram of the KEGG enrichment analysis results of tissue proteomics differential proteins between the AIH group and the HC group.

[0038] Figure 6 Schematic diagram of GO enrichment analysis results of tissue proteomics differential proteins between DILI group and HC group.

[0039] Figure 7 Schematic diagram of the KEGG enrichment analysis results of tissue proteomics differential proteins between the DILI group and the HC group.

[0040] Figure 8 Schematic diagram of the differential proteins in liver tissue proteomics between the AIH group and the DILI group.

[0041] Fig. 9 Schematic diagram of the distribution of log2 values ​​of protein abundance in serum samples in the AIH group, DILI group and HC group.

[0042] Fig.10 Schematic diagram of Pearson correlation analysis of protein expression levels of each serum sample in the AIH group, DILI group and HC group.

[0043] Fig.11 Schematic diagram of the cross-analysis results of the number of differentially expressed proteins in serum proteomics in pairwise comparisons of the AIH group, DILI group, and HC group.

[0044] Fig.12 Schematic diagram of serum proteomic differential proteins with significant differences between any two groups of AIH, DILI and HC.

[0045] Fig.13 Schematic diagram of GO enrichment analysis results of serum proteomic differential proteins between AIH group and HC group.

[0046] Fig.14 Schematic diagram of the KEGG enrichment analysis results of serum proteomic differential proteins between the AIH group and the HC group.

[0047] Fig.15 Schematic diagram of GO enrichment analysis results of tissue proteomics differential proteins between DILI group and HC group.

[0048] Fig.16 Schematic diagram of the KEGG enrichment analysis results of tissue proteomics differential proteins between the DILI group and the HC group.

[0049] Fig.17 Schematic diagram of GO enrichment analysis results of serum proteomic differential proteins between AIH group and DILI group.

[0050] Fig.18 Schematic diagram of the KEGG enrichment analysis results of serum proteomic differential proteins between the AIH group and the DILI group.

[0051] Fig.19 Schematic diagram of the combined analysis of differentially expressed proteins between liver tissue proteomics and serum proteomics; (A) is a schematic diagram of the intersection analysis results of proteins measured by liver tissue proteomics and proteins measured by serum proteomics; (B) is a schematic diagram of the quantitative analysis results of proteins with significant differential expression in both liver tissue and serum; (C) is a schematic diagram of the analysis results of proteins with significant differential expression between the DILI group and the AIH group and expressed in both liver tissue and serum.

[0052] Fig. 20 Schematic diagram of the immunohistochemical results of CD5L in liver tissue samples of the AIH group, DILI group and HC group; wherein, (A) is a schematic diagram of the immunohistochemical staining results of CD5L in liver tissue samples of the AIH group, DILI group and HC group; (B) is a schematic diagram of the immunohistochemical quantification results of CD5L in liver tissue samples of the AIH group, DILI group and HC group.

[0053] Fig.21Schematic diagram of the immunohistochemical results of DNPEP in liver tissue samples of the AIH group, DILI group and HC group; wherein, (A) is a schematic diagram of the immunohistochemical staining results of DNPEP in liver tissue samples of the AIH group, DILI group and HC group; (B) is a schematic diagram of the immunohistochemical quantification results of DNPEP in liver tissue samples of the AIH group, DILI group and HC group.

[0054] Fig. 22 Schematic diagram of the immunohistochemical results of GSTO1 in liver tissue samples of the AIH group, DILI group and HC group; wherein, (A) is a schematic diagram of the immunohistochemical staining results of GSTO1 in liver tissue samples of the AIH group, DILI group and HC group; (B) is a schematic diagram of the immunohistochemical quantitative results of GSTO1 in liver tissue samples of the AIH group, DILI group and HC group.

[0055] Fig.23 The figure is a schematic diagram of the ELISA experimental results of serum samples of AIH group, DILI group and HC group; wherein, (A) is a schematic diagram of the expression level results of CD5L in serum samples of three groups; (B) is a schematic diagram of the expression level results of DNPEP in serum samples of three groups; (C) is a schematic diagram of the expression level results of GSTO1 in serum samples of three groups.

[0056] Fig.24 Schematic diagram of the efficacy evaluation results of CD5L and / or DNPEP and / or GSTO1 in serum samples in distinguishing AIH, DILI and HC; wherein, (A) is a schematic diagram of the efficacy evaluation results of CD5L, DNPEP and GSTO1 in distinguishing AIH from DILI, respectively; (B) is a schematic diagram of the efficacy evaluation results of CD5L and GSTO1 in combination, and CD5L, GSTO1 and IgG in distinguishing AIH from DILI; (C) is a schematic diagram of the efficacy evaluation results of CD5L, DNPEP and GSTO1 in distinguishing AIH from HC, respectively; (D) is a schematic diagram of the efficacy evaluation results of CD5L, DNPEP and GSTO1 in distinguishing DILI from HC, respectively. DETAILED DESCRIPTION

[0057] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be comprehensive and complete and will fully convey the concept of the example embodiments to those skilled in the art.

[0058] In the present disclosure, CD5L is a CD5 antigen-like protein, also known as Apoptosis Inhibitor of Macrophage (AIM), which is mainly expressed or secreted in immune cells such as macrophages, monocytes and dendritic cells, and participates in immune regulation and inflammatory response, and has the effects of anti-apoptosis, regulating inflammation and clearing apoptotic cells. GSTO1 is a glutathione S transferase Ω1 protein, which belongs to the glutathione transferase (GST) enzyme family and is an enzyme that metabolizes xenobiotics through cytochrome P450. DNPEP is an asparagine aminopeptidase protein, whose main function is to participate in the process of protein degradation in cells.

[0059] Unless otherwise defined, all terms and phrases used herein include the meanings that the terms and phrases have in the art unless clearly indicated to the contrary or clearly apparent from the context in which the terms and phrases are used.

[0060] The present disclosure embodiment provides a biomarker, which is one or more of CD5L, GSTO1, and DNPEP. For example, the biomarker may be CD5L, or the biomarker may be GSTO1, or the biomarker may be DNPEP, or the biomarker may be CD5L and GSTO1, or the biomarker may be CD5L and DNPEP, or the biomarker may be GSTO1 and DNPEP, or the biomarker may be CD5L, GSTO1, and DNPEP. Further, the CD5L, GSTO1, and DNPEP are all proteins.

[0061] The disclosed embodiments also provide the use of the biomarker in preparing a product for identifying liver damage.

[0062] In one embodiment of the present disclosure, the product for identifying liver damage detects the expression levels of CD5L, GSTO1, and DNPEP in the liver tissue sample to be tested to identify liver damage. The liver tissue sample to be tested is compared with the normal liver tissue sample. When CD5L is highly expressed and / or DNPEP is highly expressed and / or GSTO1 is lowly expressed, the liver tissue sample to be tested is determined to be liver damaged.

[0063] That is to say, when CD5L is highly expressed, it can be determined that the liver tissue sample to be tested is liver damage. When DNPEP is highly expressed, it can be determined that the liver tissue sample to be tested is liver damage. When GSTO1 is lowly expressed, it can be determined that the liver tissue sample to be tested is liver damage. When CD5L and DNPEP are highly expressed, it can be determined that the liver tissue sample to be tested is liver damage. When CD5L is highly expressed and GSTO1 is lowly expressed, it can be determined that the liver tissue sample to be tested is liver damage. When DNPEP is highly expressed and GSTO1 is lowly expressed, it can be determined that the liver tissue sample to be tested is liver damage. When CD5L is highly expressed and DNPEP is highly expressed and GSTO1 is lowly expressed, it can be determined that the liver tissue sample to be tested is liver damage.

[0064] In one embodiment of the present disclosure, the product for identifying liver damage detects the expression levels of GSTO1 and DNPEP in the serum sample to be tested to identify liver damage. The serum sample to be tested is compared with the normal serum sample. When DNPEP is highly expressed and / or GSTO1 is highly expressed, the serum sample to be tested is determined to be liver damage. That is to say, when DNPEP is highly expressed, the serum sample to be tested can be determined to be liver damage. When GSTO1 is highly expressed, the serum sample to be tested can be determined to be liver damage. When DNPEP is highly expressed and GSTO1 is highly expressed, the serum sample to be tested can be determined to be liver damage.

[0065] In one embodiment of the present disclosure, the product for identifying liver damage detects the expression level of GSTO1 and / or DNPEP in the serum sample to be tested, and identifies liver damage together with the clinical test parameters related to the blood sample. Exemplary, the relevant clinical test parameters can be blood biochemical test indicators, for example, can include total bilirubin (TBIL), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), glutamine transpeptidase (GGT), total bile acid (TBA), total cholesterol (CHOL), triglycerides (TG), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), apolipoprotein E (ApoE), immunoglobulin G (IgG), immunoglobulin A (IgA), immunoglobulin M (IgM) One or more.

[0066] The disclosed embodiments also provide the use of the biomarker in the preparation of products for identifying drug-induced liver injury and autoimmune hepatitis.

[0067] In one embodiment of the present disclosure, the product for identifying drug-induced liver injury and autoimmune hepatitis detects the expression levels of CD5L, GSTO1, and DNPEP in the liver tissue sample to be tested to identify drug-induced liver injury and autoimmune hepatitis. The product for identifying drug-induced liver injury and autoimmune hepatitis is mainly used to identify people suspected of drug-induced liver injury or autoimmune hepatitis.

[0068] The liver tissue sample to be tested is compared with the positive control sample of drug-induced liver injury. When CD5L is highly expressed and / or DNPEP is highly expressed and / or GSTO1 is lowly expressed, it is determined to be autoimmune hepatitis. That is, when CD5L is highly expressed, the liver tissue sample to be tested can be determined to be autoimmune hepatitis. When DNPEP is highly expressed, the liver tissue sample to be tested can be determined to be autoimmune hepatitis. When GSTO1 is lowly expressed, the liver tissue sample to be tested can be determined to be autoimmune hepatitis. When both CD5L and DNPEP are highly expressed, the liver tissue sample to be tested can be determined to be autoimmune hepatitis. When CD5L is highly expressed and GSTO1 is lowly expressed, the liver tissue sample to be tested can be determined to be autoimmune hepatitis. When DNPEP is highly expressed and GSTO1 is lowly expressed, the liver tissue sample to be tested can be determined to be autoimmune hepatitis. When CD5L is highly expressed and DNPEP is highly expressed and GSTO1 is lowly expressed, the liver tissue sample to be tested can be determined to be autoimmune hepatitis. When CD5L is highly expressed and DNPEP is highly expressed and GSTO1 is lowly expressed, the liver tissue sample to be tested can be determined to be autoimmune hepatitis.

[0069] The liver tissue sample to be tested is compared with the positive control of autoimmune hepatitis. When CD5L is lowly expressed and / or DNPEP is lowly expressed and / or GSTO1 is highly expressed, it is determined to be drug-induced liver injury. That is to say, when CD5L is lowly expressed, the liver tissue sample to be tested can be determined to be drug-induced liver injury. When DNPEP is lowly expressed, the liver tissue sample to be tested can be determined to be drug-induced liver injury. When GSTO1 is highly expressed, the liver tissue sample to be tested can be determined to be drug-induced liver injury. When both CD5L and DNPEP are lowly expressed, the liver tissue sample to be tested can be determined to be drug-induced liver injury. When CD5L is lowly expressed and GSTO1 is highly expressed, the liver tissue sample to be tested can be determined to be drug-induced liver injury. When DNPEP is lowly expressed and GSTO1 is highly expressed, the liver tissue sample to be tested can be determined to be drug-induced liver injury. When CD5L is lowly expressed and DNPEP is lowly expressed and GSTO1 is highly expressed, the liver tissue sample to be tested can be determined to be drug-induced liver injury. When CD5L is lowly expressed and DNPEP is lowly expressed and GSTO1 is highly expressed, the liver tissue sample to be tested can be determined to be drug-induced liver injury.

[0070] In one embodiment of the present disclosure, the biomarkers in the liver tissue sample to be tested can be detected by immunohistochemistry, but are not limited to it. Fig. 20, the biomarkers include CD5L. Compared with the positive control sample of drug-induced liver injury, when CD5L is highly expressed, and in the immunohistochemical staining result image, CD5L-positive expressing cells are concentrated in the portal area (PV area), then the liver tissue sample to be tested is AIH. Compared with the positive control of autoimmune hepatitis, when CD5L is lowly expressed, and in the immunohistochemical staining result image, CD5L-positive expressing cells are concentrated in the central vein area (CV area), then the liver tissue sample to be tested is DILI. In this way, by combining the expression level of CD5L in liver tissue with the results of immunohistochemical staining, the accuracy of differential diagnosis of AIH and DILI can be better improved.

[0071] In one embodiment of the present disclosure, the product for distinguishing drug-induced liver injury and autoimmune hepatitis distinguishes drug-induced liver injury and autoimmune hepatitis by detecting the expression levels of CD5L and GSTO1 in serum samples. The product for distinguishing drug-induced liver injury and autoimmune hepatitis is mainly used to distinguish people suspected of drug-induced liver injury or autoimmune hepatitis.

[0072] The serum sample to be tested is compared with the positive control of drug-induced liver injury. When CD5L is highly expressed and / or GSTO1 is lowly expressed, the serum sample to be tested is determined to be autoimmune hepatitis. In other words, when CD5L is highly expressed, the serum sample to be tested can be determined to be autoimmune hepatitis. When GSTO1 is lowly expressed, the serum sample to be tested can be determined to be autoimmune hepatitis. When CD5L is highly expressed and GSTO1 is lowly expressed, the serum sample to be tested can be determined to be autoimmune hepatitis.

[0073] The serum sample to be tested is compared with the positive control of autoimmune hepatitis. When CD5L is lowly expressed and / or GSTO1 is highly expressed, the serum sample to be tested is determined to be drug-induced liver injury. In other words, when CD5L is lowly expressed, the serum sample to be tested can be determined to be drug-induced liver injury. When GSTO1 is highly expressed, the serum sample to be tested can be determined to be drug-induced liver injury. When CD5L is lowly expressed and GSTO1 is highly expressed, the serum sample to be tested can be determined to be drug-induced liver injury.

[0074] In one embodiment of the present disclosure, the product for identifying drug-induced liver injury and autoimmune hepatitis detects the expression level of GSTO1 and / or CD5L in serum samples, and identifies drug-induced liver injury and autoimmune hepatitis together with clinical test parameters related to blood samples. Exemplary, the relevant clinical parameters can be blood biochemical test indicators, for example, total bilirubin (TBIL), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), glutamine transpeptidase (GGT), total bile acid (TBA), total cholesterol (CHOL), triglycerides (TG), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), apolipoprotein E (ApoE), immunoglobulin G (IgG), immunoglobulin A (IgA), immunoglobulin M (IgM) One or more.

[0075] The solution of the present disclosure is further described below in conjunction with specific embodiments.

[0076] Embodiment 1

[0077] In this embodiment, on the one hand, formalin-fixed paraffin-embedded (FFPE) samples of liver tissue were used to screen liver tissue protein markers based on microproteomics. On the other hand, serum samples were used to screen serum protein markers based on proteomics. Liver tissue proteomics and serum proteomics were then jointly analyzed to screen out biomarkers for identifying liver damage.

[0078] (I) Obtaining samples

[0079] 1. FFPE sample screening and grouping

[0080] The FFPE samples were from inpatients who visited Hangzhou Xixi Hospital from January 1, 2018 to July 30, 2022 and were diagnosed with DILI and AIH by liver biopsy pathology. Among them, the FFPE samples of healthy controls were normal liver tissue pathological sections of patients with hepatic hemangioma after surgery.

[0081] FFPE sample screening criteria:

[0082] DILI group (drug-induced liver injury group): patients with a clear history of taking liver-damaging drugs, RUCAM ≥ 8 points and no history of drinking, and autoimmune diseases were excluded.

[0083] AIH group (autoimmune hepatitis group): AIH simplified diagnostic score ≥ 6 points, no glucocorticoid treatment before admission, no history of drinking or taking liver-damaging drugs, viral hepatitis (hepatitis A, hepatitis B, hepatitis C, hepatitis D, hepatitis E, CMV (cytomegalovirus) hepatitis, EBV (EV virus) hepatitis, HSV (herpes simplex virus) hepatitis, etc.), fatty liver, biliary obstruction, alcoholic liver disease, overlap syndrome, PBC (primary biliary cirrhosis), PSC (primary sclerosing cholangitis), pregnancy, combined with severe septic shock, heart, kidney and brain diseases, etc., history of acute liver ischemia, etc.

[0084] HC group (healthy control group): no liver disease, kidney disease, cardiovascular and cerebrovascular disease, personal history of malignant tumors and other related diseases.

[0085] 2. Screening and grouping of serum samples

[0086] Serum samples were collected from first-time inpatients who visited Hangzhou Xixi Hospital between June 1, 2022 and May 30, 2023. They were suspected of being diagnosed with DILI and / or AIH, and blood samples were collected from the laboratory. A 6-month follow-up was then conducted, and appropriate serum samples were selected for experiments based on the follow-up results. The follow-up results need to be analyzed: patients with typical AIH and DILI who meet the liver tissue pathology diagnosis; patients with DILI who meet the clinical diagnosis; patients with AIH who respond to hormone therapy; patients with clear progression of AIH cirrhosis or DILI cirrhosis.

[0087] Thus, DILI group: serum samples confirmed as DILI; AIH group: serum samples confirmed as AIH; HC group: serum samples with normal liver function and no underlying diseases.

[0088] (II) Screening of liver tissue protein markers based on microproteomics

[0089] FFPE samples were obtained from 14 cases in the DILI group, 10 cases in the AIH group, and 7 cases in the HC group. The basic information of the three groups of samples is shown in Table 1.

[0090] Table 1. Basic information of FFPE samples

[0091]

[0092]

[0093] Among them, WBC: white blood cell, RBC: red blood cell, HB: hemoglobin, PLT: platelet, TBIL: total bilirubin, ALB: albumin, ALT: alanine aminotransferase, AST: aspartate aminotransferase, GGT: glutamate transpeptidase, ALP: alkaline phosphatase, TBA: bile acid, IgG: immunoglobulin G, PT: prothrombin time, TE-LSM: liver stiffness measurement value measured by transient elastography of liver fibrosis, TE-CAP: controlled attenuation index measured by transient elastography of liver fibrosis, ANA: antinuclear antibody.

[0094] 1. Obtain proteomics results from FFPE samples

[0095] One biopsy section was taken from each of the 31 FFPE samples in the AIH group, DILI group, and HC group. After dewaxing, rehydration, and precipitation, each sample was subjected to rapid protein lysis, peptide extraction, and desalting in a 1.5 ml centrifuge tube and then directly subjected to DIA mass spectrometry analysis. The results were retrieved from the database and analyzed using R language software.

[0096] The database search results of 31 FFPE samples were as follows: 118,834 peptides, 10,825 proteomes were identified, and 8,871 proteins were quantified. Figure 1 As shown, the log2 values ​​of protein abundance are evenly distributed among samples, and the overall data quality is high.

[0097] The proteomic results of 31 FFPE samples from the AIH, DILI, and HC groups were analyzed using partial least squares faction analysis (PLS-DA). Figure 2 The PLS-DA model for comparing the three groups of samples shown is Figure 2 It can be seen that there is no overlap between the three groups, and the dispersion between groups is good. The results suggest that t1 and t2 can explain 19.8% and 5.6% of the differences between samples, respectively. The three groups can be effectively clustered according to the phenotype. The samples are consistent and there are differences in gene expression patterns between different sample groups, which can serve as an effective basis for subsequent differential gene analysis.

[0098] 2. Analysis of differentially expressed proteins among AIH, DILI and HC groups

[0099] Pairwise differential protein analysis was performed between the AIH group, DILI group, and HC group. Figure 3 As shown, when the cutoff value was set to |log2 FC|>0.5 and P<0.05, a total of 1951 differentially expressed proteins were screened by differential analysis of the three groups of protein spectrum data.

[0100] Differential analysis was performed on the FFPE microproteomics data of AIH group samples and HC group samples. When the cutoff value was set to |log2 FC|>0.5 and P<0.05, there were 1180 differentially expressed proteins between AIH group and HC group, of which 652 differentially expressed proteins were up-regulated and 528 differentially expressed proteins were down-regulated. GO enrichment analysis was performed on the above 1180 differentially expressed proteins between AIH group and HC group, as shown in Figure 2. Figure 4 As shown in the figure, 803 pathways were significantly enriched, including 430 biological process BP pathways, 169 cell component CC pathways, and 204 molecular function MF pathways. The most significantly different GO pathways were mainly concentrated in BP and CC pathways. The BP pathway mainly involved RNA splicing, peroxisomal organization, organic acid decomposition metabolic process, carboxylic acid decomposition metabolic process, small molecule decomposition metabolic process, etc.; the CC pathway mainly involved peroxisomes, microbodies, and organelles, microbodies, mitochondrial outer molds, etc. KEGG pathway enrichment analysis was performed on the above 1180 differential proteins between the AIH group and the HC control group, as shown in the figure. Figure 5 As shown in the figure, there are 32 differential signaling pathways enriched with qvalue<0.05 and pvalue<0.05, mainly including amino acid and nucleotide sugar metabolism, NOD-like receptor signaling pathway, nucleotide sugar biosynthesis, peroxisome, as well as fatty acid synthesis and metabolism, glutathione metabolism and ferroptosis signaling pathways.

[0101] Differential analysis was performed on the FFPE microproteomics data of the DILI group and the HC group. The cutoff value was set at |log2 FC|>0.5 and P<0.05. There were 1266 differentially expressed proteins between DILI and HC, of ​​which 691 were up-regulated and 575 were down-regulated. GO enrichment analysis was performed on the above 1266 differentially expressed proteins between the DILI group and the HC group, as shown in Figure 2. Figure 6 As shown in the figure, 1323 pathways were significantly enriched, including 856 biological process BP pathways, 234 cell component CC pathways, and 233 molecular function MF pathways. The most significantly different GO pathways were mainly concentrated in the CC and MF pathways. The CC pathway mainly involved peroxisomes, microbodies, and cytoplasmic ribosomal protein particles. The MF pathway mainly involved isomerase activity, ribosomal protein complex binding oxidoreductase activity, and disulfide oxidoreductase activity. KEGG pathway enrichment analysis was performed on the above 1266 differential proteins between the DILI group and the HC group, as shown in the figure. Figure 7As shown in the figure, there were 27 differential signaling pathways enriched with qvalue<0.05 and pvalue<0.05, mainly including nucleotide sugar biosynthesis, amino acid and nucleotide sugar metabolism, peroxisome, PPAR signaling pathway, ferroptosis, fructose and mannose metabolism, cholesterol metabolism, fatty acid degradation and NOD-like receptor signaling pathway.

[0102] The FFPE microproteomics data of AIH and DILI samples were analyzed for differences. The cutoff values ​​of |log2 FC|>0.5 and P<0.05 were used for screening, and 30 differentially expressed proteins were obtained between the AIH and DILI groups, indicating that the differences between the two groups were relatively small. Figure 8 The figure shows the detailed display of 30 differentially expressed proteins in the AIH group and the DILI group. Among them, 11 differentially expressed proteins were upregulated in the AIH group, namely ATP7A, CD5L, CLIC2, CSKI1, GHITM, ROA3, RPA49, SET1A, SNX8, TT21A and ZN462; there were 19 differentially expressed proteins upregulated in the DILI group, namely BAG5, CATL2, CENL1, CENL3, CFA46, DNPEP, GET3, GSDMD, IMB1, KPCZ, MYSM1, PAP1L, PHP14, PIDD1, RT18A, SAE1, STX5 and TOM70.

[0103] (III) Screening of protein markers based on serum proteomics

[0104] Serum samples were obtained from 108 cases in the DILI group, 84 cases in the AIH group, and 61 cases in the HC group. The sample information of each group is shown in Table 2.

[0105] Table 2. Basic information of serum samples in each group

[0106] Grouping AIH DILI HC Gender (F,%) 92.9(78 / 84) 69.4(75 / 108) 52.5(32 / 61) age 55.8±10.3 58.2±10.4 48.7±13.1 BMI 22.3±3.1 22.3±2.9 / Short-term hormone use rate 39.2(31 / 79) / / TCM Ratio / 58.3(63 / 108) / Inclusion recurrence rate 77.1(64 / 83) 24.5(26 / 106) / Follow-up recurrence rate 58.1(36 / 62) 27.1(13 / 48) / LSM 12.4±5.8 10.3±4.7 / CAP 218.2±33.0 224.9±32.6 /

[0107] Among them, the TCM ratio is the proportion of DILI caused by TCM (Traditional Chinese medicine).

[0108] 1. Obtain serum proteomics data

[0109] The 253 serum samples were sequentially subjected to resin adsorption filtration to remove high-abundance serum proteins, protein cleavage, peptide extraction, etc., and then the serum proteomics data were obtained through mass spectrometry detection and database comparison, and the serum proteomics data were subsequently analyzed using R language. The 253 serum protein spectrum data were searched and compared to the database, and a total of 2407 proteins were quantified, with an average of 1522±212 proteins per sample. Fig. 9The log2 distribution of protein abundance among samples is balanced, and the overall data quality is high. Fig.10 ,Through Pearson correlation coefficient analysis, the correlation between protein expression levels of all samples was also good.

[0110] 2. Analysis of intergroup differences in serum proteomics data

[0111] The serum proteomic data of AIH group, DILI group and HC group were subjected to pairwise differential protein analysis. The cutoff value was set at |log2 FC|>0.5 and P<0.05. A total of 650 differential proteins were screened for differential analysis of the serum protein spectrum data of the three groups.

[0112] There were 504 differential proteins in the differential analysis and screening between AIH group and HC group, of which 251 differential proteins were up-regulated and 253 differential proteins were down-regulated; there were 509 differential proteins in the differential analysis and screening between DILI group and HC group, of which 242 differential proteins were up-regulated and 267 differential proteins were down-regulated; there were 111 differential proteins in the differential analysis and screening between DILI group and AIH group, of which 55 differential proteins were up-regulated and 56 differential proteins were down-regulated; the Venn diagram of the number of differential proteins between any two of the three groups is shown in the figure below: Fig.11 As shown in Figure 2, there were only 38 proteins with significant differences between any two of the three groups. Fig.12 Shown is a heat map of 38 differentially expressed proteins among DILI, AIH and HC groups.

[0113] like Fig.13 As shown in the figure, GO pathway analysis was performed on the above 504 serum differential proteins in the AIH group and the HC group, and 2774 pathways were significantly enriched, including 2704 biological process BP pathways, 215 cell component CC pathways, and 255 molecular function MF pathways. The most significantly different GO pathways mainly include: BP pathway mainly involves hemostasis, coagulation, coagulation, wound healing, and fluid level regulation; CC pathway mainly involves secretory granule lumen, cytoplasmic vesicle lumen, vesicle lumen and collagen-containing extracellular matrix; MF pathway mainly involves glycosaminoglycan binding, integrin binding and cytoskeleton structural components. Fig.14 As shown in the figure, KEGG pathway enrichment analysis was performed on the above 504 serum differential proteins between the AIH group and the HC group. According to qvalue<0.05 and pvalue<0.05, a total of 66 differential signaling pathways were enriched, mainly including complement and coagulation cascades, peroxisomes, ECM receptor interactions, and arginine biosynthesis signaling pathways.

[0114] GO pathway analysis was performed on the above 509 serum differential proteins between the DILI group and the HC group, such as Fig.15 As shown in the figure, 1992 pathways were significantly enriched. Among them, there were 1600 biological process BP pathways, 163 cellular component CC pathways, and 229 molecular function MF pathways. The most significantly different GO pathways included: BP pathways mainly involved hemostasis, coagulation, coagulation, immunoglobulin and immune response mediating molecules; CC pathways mainly involved immunoglobulin complexes, secretory granule lumen, cytoplasmic vesicles and vesicle lumen; MF pathways mainly involved antigen binding, integrin binding and glycosaminoglycan binding. KEGG pathway enrichment analysis was performed on the above 509 serum differential proteins between the DILI group and the HC group, as shown in the figure. Fig.16 As shown in the figure, there are 61 differentially enriched signal pathways according to qvalue<0.05 and pvalue<0.05, mainly including peroxisome, carbon metabolism, amino acid biosynthesis, ECM receptor interaction and arginine biosynthesis signal pathways.

[0115] GO pathway analysis was performed on the above 111 serum differential proteins between the DILI group and the AIH group, such as Fig.17 As shown in the figure, 663 pathways were significantly enriched. Among them, there were 510 biological process BP pathways, 32 cell component CC pathways, and 121 molecular function MF pathways. The most significantly different GO pathways mainly include: BP pathways mainly involve the production of immunoglobulins and immune response mediating molecules, fructose metabolism, small molecule catabolism, and amino acid metabolism; CC pathways mainly involve immunoglobulin complexes, proteasome core complexes, and proteasome complexes. KEGG pathway enrichment analysis was performed on the above 111 serum differential proteins between the DILI group and the AIH group, as shown in the figure. Fig.18 As shown in the figure, there are 66 differentially enriched signal pathways according to qvalue<0.05 and pvalue<0.05, mainly including peroxisome, carbon metabolism and arginine biosynthesis signal pathways.

[0116] (IV) Combined analysis of liver tissue proteomics and serum proteomics

[0117] Combined analysis of liver tissue FFPE microproteomics and serum proteomics data, such as Fig.19 As shown in (A), after data normalization, liver tissue proteomics detected 7685 proteins in the corresponding samples, and serum proteomics detected 1680 proteins in the corresponding samples; the intersection of liver tissue proteins and serum proteins had 492 overlapping proteins, that is, 492 proteins existed in liver tissue and secreted into serum at the same time. Fig.19As shown in (B), the intersection of the 492 proteins with the 650 serum differential proteins and the 1951 liver tissue differential proteins was taken, and a total of 51 differential proteins were expressed in both liver tissue and serum, and had differences between the groups. Fig.19 The Venn diagram shown in (C) is obtained by intersecting the common differential proteins in the 51 liver tissues and serum, the 30 liver tissue differential proteins differentially analyzed between the DILI group and the AIH group, and the 111 serum differential proteins differentially analyzed between the DILI group and the AIH group. Among the 51 differential proteins, the candidate biomarkers in the intersection are Glutathione S Transferase Omega1 (GSTO1), Apoptosis Inhibitor of Macrophage (AIM / CD5L), and Aspartylaminopeptidase (DNPEP). These three proteins have significant differences in liver tissue and serum between the DILI group and the AIH group.

[0118] Example 2: Validation of candidate biomarkers

[0119] 1. Immunohistochemical validation of candidate biomarkers

[0120] Using the screening criteria in "Example 1", 10 FFPE samples of patients diagnosed with AIH and DILI were rescreened, respectively, as the AIH group and the DILI group; FFPE sections of 3 normal liver tissue samples were used as the HC group. Immunohistochemical staining was performed for the three candidate target proteins CD5L, DNPEP and GSTO1, and the results were scanned. CaseViewer software was used to select 3 different visual fields for each sample under a 40x microscope to save the image, and the immunohistochemical image of each sample was saved by ImageJ. The results were as follows: 30 immunohistochemical images (n=30) were obtained in the AIH group, 30 immunohistochemical images (n=30) were obtained in the DILI group, and 9 immunohistochemical images (n=9) were obtained in the HC group. The immunohistochemical images obtained in the above groups were quantitatively analyzed. The specific quantitative analysis method is as follows: ImageJ was used for immunohistochemistry analysis, the IHC Profiler plug-in was used to automatically score the staining of the samples, and the Trainable Weka Segmentation plug-in was used to count the immunohistochemistry-positive and negative cells in the pathological section scan images respectively; GraphPad Prism software was used to plot the data and analyze the differences between the groups.

[0121] like Fig. 20As shown in (A), the immunohistochemical staining results of CD5L showed that the expression level of CD5L was the highest in the AIH group, and the expression levels in the DILI group and HC group decreased in turn. There were almost no positive cells expressing CD5L in the HC group. Fig. 20 As shown in (B), there was a statistically significant difference between any two groups among the AIH group, DILI group and HC group (P<0.0001). Moreover, CD5L is an apoptosis inhibitor expressed and secreted by macrophages. From the morphological structure of the liver lobule in the immunohistochemical results, it can be seen that the CD5L-positive cells in the AIH group were concentrated in the portal duct area (PV area), while the CD5L-positive cells in the DILI group were mostly concentrated in the central vein area (CV area). The distribution of CD5L-positive cells was related to the different liver injury mechanisms of AIH and DILI.

[0122] like Fig.21 As shown in (A), the immunohistochemical staining results of DNPEP showed that the protein was mainly expressed in the cytoplasm and the nuclei of some cells, and the specific expression level was the highest in the AIH group samples, followed by the DILI group and the HC group samples. Fig.21 The quantitative analysis results shown in (B) showed that there were significant differences between any two groups among the AIH group, DILI group and HC group.

[0123] GSTO1 protein is an enzyme that is mainly expressed in the cytoplasm and cytoplasm, exhibiting glutathione-dependent sulfhydryl transferase and dehydroascorbate reductase activities, which are characteristic of glutathione reducing proteins. Fig. 22 As shown in (A), the immunohistochemical staining results of GSTO1 showed that the expression level of GSTO1 was the highest in the HC group, followed by the DILI group, and the expression level of GSTO1 was the lowest in the AIH group. Fig. 22 As shown in (B), quantitative analysis showed that the expression level of GSTO1 in the HC group was significantly higher than that in the DILI group (P=0.0052), and that in the DILI group was significantly higher than that in the AIH group (P<0.0001).

[0124] 2. ELISA validation of candidate biomarkers

[0125] According to the screening method of serum samples in "Example 1", serum samples of patients with confirmed diagnosis of AIH and DILI were rescreened, including 32 cases in the AIH group, 37 cases in the DILI group, and 16 cases in the healthy population HC group. The basic information of the 69 patient samples in the AIH group and the DILI group is shown in Table 3, among which the AIH group and the DILI group samples had significant differences in gender, TBIL, ALT, AST, ALP and GGT.

[0126] The three protein markers CD5L, DNPEP and GSTO1 in the above 85 serum samples were detected by enzyme-linked immunosorbent assay (ELISA), and the expression levels of these three protein markers in the serum of AIH group, DILI group and HC group were analyzed. Among them, the ELISA kit with the catalog number EH94RB of Thermo (Thermo Fisher Scientific) was used to detect the level of CD5L in serum, the ELISA kit with the catalog number abx386959 of Abbexa (UK) was used to detect the level of DNPEP in serum, and the ELISA kit with the catalog number EK14393-2 of SAB (USA) was used to detect the level of GSTO1 in serum.

[0127] like Fig.23 As shown in (A), the expression level of CD5L in serum samples of AIH group and DILI group was significantly different (P=0.0243), but there was no significant difference in serum expression level between AIH group and HC group, and between DILI group and HC group (P=0.8245, P=0.3056). Fig.23 As shown in (B), the serum expression levels of DNPEP between the AIH group and the HC group, and between the DILI group and the HC group were significantly different (P = 0.0010, P = 0.0003), but there was no statistical difference in the serum expression levels between the AIH group and the DILI group (P = 0.9119). Fig.23 As shown in (C), in the measurement results of serum expression level of GSTO1 protein, the expression level of serum in AIH group was significantly lower than that in DILI group (P=0.0362), while the expression level of GSTO1 in serum samples of AIH group, DILI group and HC group was significantly increased, and the differences were statistically significant (P<0.0001).

[0128] Table 3. Basic information of serum samples in AIH and DILI groups

[0129] Grouping AIH (n=32) DILI (n=37) P Gender (F, n%) 30(93.8) 28(75.7) 0.0408 Age (y) 53.3±9.7 58.6±12.9 0.0615 body mass index 22.9±3.7 22.3±2.7 0.4214 TBIL (μmol / L) 15.7(10.2-27.8) 25.0(15.3-80.9) 0.0157 ALT(U / L) 101.5(29.8-216.3) 300.0(173.5-665.5) <0.0001 AST(U / L) 73.5(37.3-127.5) 202.0(87.0-344.0) 0.0006 ALP(U / L) 110.0(71.8-138.8) 154.0(109.0-202.5) 0.0008 GGT(U / L) 121.5±122.7 204.5±131.4 0.0088 TBA (μmol / L) 17.1(5.2-49.8) 22.7(10.3-57.6) 0.3975 CHOL(mmol / L) 4.8±1.0 4.3±1.0 0.0568 TG (mmol / L) 1.4±0.7 1.6±0.7 0.3353 ApoA1(g / L) 1.3±0.5 1.1±0.3 0.0729 ApoB(g / L) 0.9±0.3 0.9±0.3 0.5168 ApoE(g / L) 62.8±30.3 69.7±29.7 0.3905 IgG(g / L) 14.6±4.6 12.8±3.5 0.0726 IgA (g / L) 2.6±1.0 2.7±2.0 0.8240 IgM(g / L) 1.3(1.0-1.8) 1.1(0.8-1.4) 0.0550 LSM 11.0±5.0 9.3±3.1 0.1860 CAP 224.4±30.3 221.6±25.3 0.7417

[0130] Among them, CHOL: total serum cholesterol, TG: thyroglobulin, ApoA1: apolipoprotein AI, ApoB: apolipoprotein B, ApoE: apolipoprotein E, IgA: immunoglobulin A, IgM: immunoglobulin M.

[0131] 3. Evaluation of the efficacy of biomarkers in differentiating AIH and DILI

[0132] like Fig.24 As shown in (A), when used to differentiate AIH from DILI, the areas under the ROC curve (AUC) of CD5L, DNPEP, and GSTO1 were 0.6356, 0.6199, and 0.5080, respectively.

[0133] like Fig.24 As shown in (B), when used to differentiate AIH and DILI, the area under the ROC curve of CD5L and GSTO1 combined is 0.6791; the area under the ROC curve of CD5L, GSTO1 and IgG combined is 0.7785. In other words, when the cutoff value of the binary logistic regression of CD5L, GSTO1 and IgG is 0.5717, the sensitivity and specificity of differential diagnosis of AIH and DILI are 74.2% and 76.7%. Therefore, the accuracy of distinguishing AIH and DILI can be improved by detecting serum CD5L and GSTO1 and combining the results of IgG. Among them, IgG is the total IgG in serum.

[0134] like Fig.24 (C) and Fig.24 As shown in (D), when GSTO1 is used alone to distinguish AIH from HC, the area under the ROC curve AUC is 0.9102; when it is used to distinguish DILI from HC, the area under the ROC curve AUC of GSTO1 alone is 0.9848. Therefore, GSTO1 can effectively distinguish AIH from HC, DILI from HC as a marker. In other words, when the cutoff value of GSTO1 is 12.35 ng / ml, the sensitivity of differential diagnosis of AIH and HC is 93.8%, and the specificity is 81.3%; when the cutoff value is 12.99 ng / ml, the sensitivity of differential diagnosis of DILI and HC is 100%, and the specificity is 81.9%. When used to distinguish AIH from HC, the area under the ROC curve AUC of DNPEP alone is 0.7852; when used to distinguish DILI from HC, the area under the ROC curve AUC of DNPEP alone is 0.8007. Therefore, DNPEP can also effectively distinguish AIH from HC, DILI from HC as a marker.

[0135] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the appended claims.

Claims

1. A biomarker, characterized in that The biomarkers are one or more of CD5L, GSTO1, and DNPEP.

2. Use of the biomarker according to claim 1 in the preparation of a product for identifying liver damage.

3. The use according to claim 2, characterized in that: The product for identifying liver damage detects the expression levels of CD5L, GSTO1, and DNPEP in the liver tissue sample to be tested to identify liver damage; Compared with normal liver tissue samples, when CD5L is highly expressed and / or DNPEP is highly expressed and / or GSTO1 is lowly expressed, the liver tissue sample to be tested is determined to be liver damaged.

4. The use according to claim 2, characterized in that: The product for identifying liver damage detects the expression levels of DNPEP and GSTO1 in the serum sample to be tested to identify liver damage; Compared with normal serum samples, when DNPEP is highly expressed and / or GSTO1 is highly expressed, the serum sample to be tested is determined to be liver damaged.

5. The use according to claim 2, characterized in that: The product for identifying liver damage detects the expression level of DNPEP and / or GSTO1 in the serum sample to be tested, and identifies liver damage together with clinical detection parameters related to the blood sample.

6. Use of the biomarker according to claim 1 in the preparation of a product for identifying drug-induced liver injury and autoimmune hepatitis.

7. The use according to claim 6, characterized in that: The product for distinguishing drug-induced liver injury and autoimmune hepatitis distinguishes drug-induced liver injury and autoimmune hepatitis by detecting the expression levels of CD5L, GSTO1, and DNPEP in the liver tissue sample to be tested; Compared with the positive control of drug-induced liver injury, when CD5L is highly expressed and / or DNPEP is highly expressed and / or GSTO1 is lowly expressed, the liver tissue sample to be tested is determined to be autoimmune hepatitis; Compared with the positive control of autoimmune hepatitis, when CD5L is lowly expressed and / or DNPEP is lowly expressed and / or GSTO1 is highly expressed, the liver tissue sample to be tested is determined to be drug-induced liver injury.

8. The use according to claim 7, characterized in that: The product for distinguishing drug-induced liver injury and autoimmune hepatitis distinguishes drug-induced liver injury and autoimmune hepatitis by detecting the expression levels of CD5L and GSTO1 in the serum sample to be tested; Compared with the positive control of drug-induced liver injury, when CD5L is highly expressed and / or GSTO1 is lowly expressed, the serum sample to be tested is determined to be autoimmune hepatitis; Compared with the positive control of autoimmune hepatitis, when CD5L is lowly expressed and / or GSTO1 is highly expressed, the serum sample to be tested is determined to be drug-induced liver injury.

9. The use according to claim 7, characterized in that: The product for identifying drug-induced liver injury and autoimmune hepatitis detects the expression level of GSTO1 and / or CD5L in the serum sample to be tested, and identifies drug-induced liver injury and autoimmune hepatitis together with clinical test parameters related to the blood sample.

10. A method for screening biomarkers according to claim 1, characterized in that: The following steps are involved: S10, obtaining experimental samples; the experimental samples include liver tissue samples and serum samples; The liver tissue samples were divided into a first normal control group, a first drug-induced liver injury group, and a first autoimmune hepatitis group; The serum samples were divided into a second normal control group, a second drug-induced liver injury group, and a second autoimmune hepatitis group; S20, analyzing the liver tissue samples by microproteomics to obtain the protein analysis results of the liver tissue samples in each group; Serum samples were analyzed using serum proteomics to obtain protein analysis results of serum samples in each group; S30, the first subset composed of differentially expressed proteins between the first drug-induced liver injury group and the first autoimmune hepatitis group; The second subset consisted of proteins that were differentially expressed between the second drug-induced liver injury group and the second autoimmune hepatitis group; the third subset consisted of proteins that existed in both liver tissue samples and serum samples and had differences between the groups; The first subset, the second subset, and the third subset are intersected to obtain biomarkers.

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