Biomarker for diagnosing primary biliary cholangitis and application thereof

Abstract

The invention provides a biomarker for diagnosing primary biliary cholangitis and application of the biomarker, and belongs to the technical field of biomarkers. The biomarker disclosed by the invention comprises serum protein and / or N-glycopeptide. According to the method, the improvement of PBC diagnosis is taken as a starting point, the serum protein and the N-glycopeptide are taken as screening templates, a more accurate non-invasive prediction means for differential diagnosis of PBC is provided, and a theoretical basis is provided for rapid and accurate diagnosis of PBC.

Description

Technical Field

[0001] This invention relates to the field of biomarker technology, and more particularly to a biomarker for the diagnosis of primary biliary cholangitis and its application. Background Technology

[0002] Autoimmune liver diseases (AILDs) include autoimmune hepatitis (AIH), primary biliary cholangitis (PBC), and primary sclerosing cholangitis (PSC). PBC and AIH primarily affect women. Although these diseases are known to involve genetic susceptibility and various environmental risk factors, their etiologies remain elusive. Their shared serological characteristics (such as elevated levels of liver function-related proteases) and similar clinical symptoms complicate differential diagnosis. Furthermore, the presence of patients exhibiting features of both diseases—a "coverage syndrome"—further challenges to clinical diagnosis. Liver biopsy is an effective diagnostic tool, but it carries a potential risk of infection. Therefore, the availability of biomarkers for accurate, non-invasive diagnosis of these diseases represents an important unmet medical need.

[0003] Currently, antimitochondrial antibody type 2 (AMA-M2) is a specific biomarker for diagnosing polycystic purpura (PBC), with approximately 90% of patients testing positive. However, some PBC patients have normal serum liver function tests or negative AMA-M2 tests, and their PBC diagnosis still relies on liver biopsy and histological examination.

[0004] More than 100,000 cases of PBC worldwide require accurate diagnosis each year. However, there is currently no clear diagnostic or testing method to differentiate PBC from AIH, as well as their overlap syndrome (PBC+AIH). Therefore, developing a non-invasive diagnostic method for PBC to distinguish it from other AILDs would significantly enhance the clinical management of these diseases.

[0005] Glycosylation is one of the most common types of protein modification, and N-linked glycoproteins (N-glycoproteins) are particularly abundant in eukaryotes, especially in immune-related proteins. Many glycoproteins are associated with the development and progression of chronic diseases, including liver diseases, and some have been used as biomarkers for cancer diagnosis. However, whether serum proteins and N-glycoproteins can serve as biomarkers for non-invasive diagnosis of PBC and other AILDs remains to be determined. Summary of the Invention

[0006] The purpose of this invention is to provide a biomarker for the diagnosis of primary biliary cholangitis and its application.

[0007] To achieve the above-mentioned objectives, the present invention provides the following technical solution: This invention provides a biomarker for the diagnosis of primary biliary cholangitis, the biomarker comprising serum protein and / or N-glycopeptide; The serum protein is selected from any one or more of the following: keratin 23, SURF6 protein, isopentenylcysteine ​​oxidase 1, complement factor B, histidine-rich glycoprotein, aminopeptidase N, Ras-related protein Rap-1b, mannose oligosaccharide glucosidase, calmodulin kinase-like vesicle-related protein, α2-macroglobulin, electron transfer flavin β-peptide, keratinocyte proline-rich protein, and Tsukushin protein. The N-glycopeptide is selected from the glycosylated forms of hyaluronic acid lectin, namely VTN_N169_HexNAc(3)Hex(5), immunoglobulin weight constant μIGHM_N46_HexNAc(4)Hex(5)Fuc(1)NeuAc(1), α2-macroglobulin A2M_N247_HexNAc(5)Hex(4)NeuAc(1), glycosylated forms of hyaluronic acid lectin, namely VTN_N169_HexNAc(3)Hex(4), phospholipid transfer protein FLTP_N245_HexNAc(4)Hex(5)Fuc(1)NeuAc(1), and heparin cofactor 2. SERPIND1_N49_HexNAc(4)Hex(5)NeuAc(2), sphingolipid-activated protein origin PSAP_N215_HexNAc(2)Hex(2)Fuc(1), zinc-binding α2-glycoprotein 1AZGP1_N128_HexNAc(4)Hex(5)NeuAc(2), α-albumin AFM_N402_HexNAc(4)Hex(5)NeuAc(2), immunoglobulin heavy chain γ2 constant region IGHG2_N176_HexNAc(4)Hex(3)Fuc(1), immunoglobulin heavy chain γ1 constant region IGHG1_N180_HexNAc(4)Hex(5)Fuc(1), immunoglobulin heavy chain constant μ IGHM_N440_HexNAc(2)Hex(8)

[0008] Preferably, the biomarker further includes clinical variables, which are selected from any five or more of the following: sex, age, albumin, globulin, direct bilirubin, alkaline phosphatase, gamma-glutamyl transferase, aspartate aminotransferase, alanine aminotransferase, and antimitochondrial antibody type 2.

[0009] Preferably, the differential diagnosis of primary biliary cholangitis involves distinguishing it from other autoimmune liver diseases.

[0010] Preferably, the other autoimmune liver diseases are autoimmune hepatitis, primary biliary cholangitis, and autoimmune hepatitis overlap syndrome.

[0011] This invention provides the application of a biomarker in the preparation of products for the diagnosis of primary biliary cholangitis, wherein the biomarker includes serum protein and / or N-glycopeptide; The serum protein is selected from any one or more of the following: keratin 23, SURF6 protein, isopentenylcysteine ​​oxidase 1, complement factor B, histidine-rich glycoprotein, aminopeptidase N, Ras-related protein Rap-1b, mannose oligosaccharide glucosidase, calmodulin kinase-like vesicle-related protein, α2-macroglobulin, electron transfer flavin β-peptide, keratinocyte proline-rich protein, and Tsukushin protein. The N-glycopeptide is selected from the glycosylated forms of hyaluronic acid lectin, namely VTN_N169_HexNAc(3)Hex(5), immunoglobulin weight constant μIGHM_N46_HexNAc(4)Hex(5)Fuc(1)NeuAc(1), α2-macroglobulin A2M_N247_HexNAc(5)Hex(4)NeuAc(1), glycosylated forms of hyaluronic acid lectin, namely VTN_N169_HexNAc(3)Hex(4), phospholipid transfer protein FLTP_N245_HexNAc(4)Hex(5)Fuc(1)NeuAc(1), and heparin cofactor 2. SERPIND1_N49_HexNAc(4)Hex(5)NeuAc(2), sphingolipid-activated protein origin PSAP_N215_HexNAc(2)Hex(2)Fuc(1), zinc-binding α2-glycoprotein 1AZGP1_N128_HexNAc(4)Hex(5)NeuAc(2), α-albumin AFM_N402_HexNAc(4)Hex(5)NeuAc(2), immunoglobulin heavy chain γ2 constant region IGHG2_N176_HexNAc(4)Hex(3)Fuc(1), immunoglobulin heavy chain γ1 constant region IGHG1_N180_HexNAc(4)Hex(5)Fuc(1), immunoglobulin heavy chain constant μ IGHM_N440_HexNAc(2)Hex(8) are any one or more of these.

[0012] Preferably, the differential diagnosis of primary biliary cholangitis involves distinguishing it from other autoimmune liver diseases.

[0013] Preferably, the other autoimmune liver diseases are autoimmune hepatitis, primary biliary cholangitis, and autoimmune hepatitis overlap syndrome.

[0014] This invention provides a product for diagnosing primary biliary cholangitis, the product containing reagents for detecting the biomarker.

[0015] Preferably, the product includes a reagent kit.

[0016] Compared with the prior art, the present invention has the following beneficial effects: This invention provides an application of non-invasive biomarkers in the differential diagnosis of polycystic cerebral bronchitis (PBC). These biomarkers include keratin 23 (KRT23) and the glycosylated forms of hyaluronic acid lectins, VTN_N169_HexNAc(3)Hex(5). This invention solves the problem of difficult PBC diagnosis and provides a foundation for the diagnosis and treatment of PBC.

[0017] This invention aims to improve the diagnosis of polycystic angina (PBC). Using serum proteins and N-glycopeptides as screening templates, it provides a more accurate and non-invasive predictive method for the differential diagnosis of PBC, offering a theoretical basis for the rapid and accurate diagnosis of PBC. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0019] Figure 1 The statistical results of the average AUC values ​​for the differential diagnosis of PBC, AIH, PBC+AIH and CTR under different combinations of protein, glycopeptide (IGP) and clinical variables in Example 1 are as follows: Figure 2 This is the AUC curve of the biomarker combination CPG-AILD in Example 1 for the differential diagnosis of PBC; Figure 3 The results of LC-MS / MS detection of KRT23 and VTN_N169_HexNAc(3)Hex(5) in the biomarker combination CPG-AILD in Example 1 in the serum of different types of patients; Figure 4 This is an AUC curve of the biomarker combination CPG-AILD in Example 2 for the differential diagnosis of PBC with different atypical clinical features; Figure 5 This is the AUC curve of the biomarker combination CPG-AILD in Example 3 for the differential diagnosis of PBC+AIH; Figure 6This is the AUC curve of the biomarker combination CPG-AILD in Example 3 for the differential diagnosis of AIH; Figure 7 The AUC curve is shown for the differential diagnosis of CTR using the biomarker combination CPG-AILD in Example 3. Detailed Implementation

[0020] The technical solutions provided by the present invention will be described in detail below with reference to the embodiments, but they should not be construed as limiting the scope of protection of the present invention.

[0021] Example 1

[0022] This embodiment aims to explore the role of different serum proteins and N-glycopeptides (IGP) in the diagnosis of PBC.

[0023] Based on the discovery cohort—healthy control group (CTR=138), primary biliary cholangitis (PBC=215), autoimmune hepatitis (AIH=100), and primary biliary cholangitis and autoimmune hepatitis overlap syndrome (PBC+AIH=119)—the top 10 upregulated and 10 downregulated proteins (N=85) and IGP (N=75) with the smallest P-values ​​were selected as candidate biomarkers from the comparison groups of PBC and CTR, AIH and CTR, PBC+AIH and CTR, PBC+AIH and AIH, PBC and AIH, and PBC and PBC+AIH.

[0024] Feature selection was evaluated using 2000 combinations with 1 / 2 / 3 / 5 / 7 / 10 features. The `train()` function from the `caret` package in R was used to construct a Random Forest model, and 10-fold cross-validation was used to optimize the hyperparameter `mtry` based on the Kappa coefficient. All other parameters were set to default. The optimal models were obtained by selecting 1 / 2 / 3 / 5 / 7 / 10 features respectively.

[0025] This analysis identified 19 candidate protein biomarkers and 17 candidate IGP biomarkers. Subsequently, using the same method described above, models with 1 / 2 / 3 / 5 / 7 / 10 features were constructed for these 19 proteins and / or 17 IGPs, and iterative feature selection was performed. Simultaneously, the features were further optimized using the Recursive Feature Elimination Random Forest (RFE-RF) method to obtain the final biomarker panel. The output shows the patient's probability of CTR, PBC, AIH, and PBC+AIH; the highest probability indicates the patient's disease type.

[0026] Furthermore, the final biomarkers were combined with clinical variables to optimize feature performance. The screened features were further validated using a validation cohort (CTR=32, PBC=61, AIH=31, PBC+AIH=41). Figure 1 As shown, with different combinations of protein, glycopeptide (IGP), and clinical variables, the diagnostic performance improves as the number of features increases.

[0027] The inventors studied the average AUC values ​​of different combinations of serum proteins and clinical indicators, combinations of N-glycopeptides and clinical indicators, and combinations of serum proteins, N-glycopeptides and clinical indicators for the differential diagnosis of PBC, AIH, PBC+AIH and CTR. The results are shown in Tables 1 to 3.

[0028] Table 1. Mean AUC values ​​of serum protein and clinical marker combinations for differential diagnosis of PBC, AIH, PBC+AIH, and CTR.

[0029] Table 2. Mean AUC values ​​of N-glycopeptide combinations with clinical indicators for the differential diagnosis of PBC, AIH, PBC+AIH, and CTR.

[0030] Table 3. Mean AUC values ​​of combinations of serum proteins, N-glycopeptides, and clinical indicators for the differential diagnosis of PBC, AIH, PBC+AIH, and CTR.

[0031] As can be seen from Tables 1 to 3, different combinations of serum proteins and clinical indicators, combinations of N-glycopeptides and clinical indicators, and combinations of serum proteins, N-glycopeptides and clinical indicators all have good application prospects for differential diagnosis of PBC, AIH, PBC+AIH, and CTR.

[0032] Subsequently, based on the principles of superior performance and ease of clinical application, we selected keratin 23 (KRT23) and the glycosylated form of hyaluronic acid lectin, VTN_N169_HexNAc(3)Hex(5), as a combination of biomarkers for the differential diagnosis of PBC. We then combined this biomarker combination with sex, age, albumin (ALB), globulin (GLO), direct bilirubin (DBIL), alkaline phosphatase (ALP), gamma-glutamyl transferase (GGT), aspartate aminotransferase (AST), alanine aminotransferase (ALT), and AMA-M2 to differentiate PBC (referred to as CPG-AILD).

[0033] CPG-AILD showed ROC-AUC values ​​of 0.957, 0.936, and 0.919 in the training, test, and validation sets, respectively. Figure 2 ), used to distinguish PBC from other AILDs and CTRs. Feature ablation analysis showed that removing the new screening features KRT23 and VTN_N169_HexNAc(3)Hex(5) alone or simultaneously in CPG-AILD significantly reduced model performance (Table 4). Compared with PBC and CTR, KRT23 significantly increased in AIH and PBC+AIH, but decreased in PBC compared to CTR. VTN_N169_HexNAc(3)Hex(5) significantly decreased in AIH and PBC+AIH, but there was no significant difference between PBC and CTR ( Figure 3 ).

[0034] Table 4 Ablation analysis results of novel biomarkers in CPG-AILD

[0035] Example 2: Diagnosis of atypical PBC using CPG-AILD

[0036] The accuracy and stability of CPG-AILD in diagnosing PBC were analyzed to assess its effectiveness in identifying PBC with atypical clinical features (the output shows the probability of the patient having different PBC characteristics, with the highest probability indicating the patient's type). Results are as follows... Figure 4 As shown.

[0037] PBC was divided into patients who tested positive for AMA-M2 (M... 2+ -PBC group) and AMA-M2 negative patients (M 2- When -PBC group), for M 2+ - In PBC patients, the ROC-AUC values ​​of CPG-AILD were 0.93 and 0.95 in the test and validation sets, respectively; for M 2- - In PBC patients, the ROC-AUC values ​​of CPG-AILD in the test and validation sets were 0.981 and 0.917, respectively. Figure 4 (Top left and top right).

[0038] When PBC was divided into the BP-PBC group (abnormally elevated ALP / GGT (alkaline phosphatase / gamma-glutamyl transferase) and AMA-M2 positive) and the BN-PBC group (normal ALP / GGT or AMA-M2 negative), the ROC-AUC values ​​of CPG-AILD in the test and validation sets were 0.956 and 0.965, respectively, in the BP-PBC group. In the BN-PBC group, the ROC-AUC values ​​of CPG-AILD in the test and validation sets were 0.906 and 0.864, respectively. Figure 4 (Lower left and lower right).

[0039] Example 3

[0040] The purpose of this embodiment is to verify the diagnostic performance of CPG-AILD in PBC+AIH and AIH. The results are as follows: Figures 5-7 As shown, CPG-AILD achieved diagnostic efficacy of 0.929, 0.86, and 0.912 in the training, experimental, and validation sets, respectively. Figure 5 The ROC-AUC values ​​for the diagnosis of AIH in the training, test, and validation sets were 0.965, 0.948, and 0.948, respectively. Figure 6 The ROC-AUC values ​​for the diagnosis of CTR on the training, test, and validation sets were 0.988, 0.997, and 0.995, respectively. Figure 7 ).

[0041] It can be seen that CPG-AILD can not only be used to diagnose PBC, but also to differentiate PBC from PBC+AIH, AIH and CTR, and has achieved better performance than traditional clinical trials.

[0042] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A biomarker for the diagnosis of primary biliary cholangitis, characterized in that, The biomarkers include serum proteins and / or N-glycopeptides; The serum protein is selected from any one or more of the following: keratin 23, SURF6 protein, isopentenylcysteine ​​oxidase 1, complement factor B, histidine-rich glycoprotein, aminopeptidase N, Ras-related protein Rap-1b, mannose oligosaccharide glucosidase, calmodulin kinase-like vesicle-related protein, α2-macroglobulin, electron transfer flavin β-peptide, keratinocyte proline-rich protein, and Tsukushin protein. The N-glycopeptide is selected from the glycosylated forms of hyaluronic acid lectin, namely VTN_N169_HexNAc(3)Hex(5), immunoglobulin weight constant μIGHM_N46_HexNAc(4)Hex(5)Fuc(1)NeuAc(1), α2-macroglobulin A2M_N247_HexNAc(5)Hex(4)NeuAc(1), glycosylated forms of hyaluronic acid lectin, namely VTN_N169_HexNAc(3)Hex(4), phospholipid transfer protein FLTP_N245_HexNAc(4)Hex(5)Fuc(1)NeuAc(1), and heparin cofactor 2. SERPIND1_N49_HexNAc(4)Hex(5)NeuAc(2), sphingolipid-activated protein origin PSAP_N215_HexNAc(2)Hex(2)Fuc(1), zinc-binding α2-glycoprotein 1AZGP1_N128_HexNAc(4)Hex(5)NeuAc(2), α-albumin AFM_N402_HexNAc(4)Hex(5)NeuAc(2), immunoglobulin heavy chain γ2 constant region IGHG2_N176_HexNAc(4)Hex(3)Fuc(1), immunoglobulin heavy chain γ1 constant region IGHG1_N180_HexNAc(4)Hex(5)Fuc(1), immunoglobulin heavy chain constant μ IGHM_N440_HexNAc(2)Hex(8) 2. The biomarker as described in claim 1, characterized in that, The biomarkers also include clinical variables, which are selected from any five or more of the following: sex, age, albumin, globulin, direct bilirubin, alkaline phosphatase, gamma-glutamyl transferase, aspartate aminotransferase, alanine aminotransferase, and antimitochondrial antibody type 2.

3. The biomarker as described in claim 2, characterized in that, The differential diagnosis of primary biliary cholangitis is to distinguish it from other autoimmune liver diseases.

4. The biomarker as described in claim 3, characterized in that, The other autoimmune liver diseases mentioned are autoimmune hepatitis, primary biliary cholangitis, and autoimmune hepatitis overlap syndrome.

5. The application of a biomarker in the preparation of products for the diagnosis of primary biliary cholangitis, characterized in that, The biomarkers include serum proteins and / or N-glycopeptides; The serum protein is selected from any one or more of the following: keratin 23, SURF6 protein, isopentenylcysteine ​​oxidase 1, complement factor B, histidine-rich glycoprotein, aminopeptidase N, Ras-related protein Rap-1b, mannose oligosaccharide glucosidase, calmodulin kinase-like vesicle-related protein, α2-macroglobulin, electron transfer flavin β-peptide, keratinocyte proline-rich protein, and Tsukushin protein. The N-glycopeptide is selected from the glycosylated forms of hyaluronic acid lectin, namely VTN_N169_HexNAc(3)Hex(5), immunoglobulin weight constant μIGHM_N46_HexNAc(4)Hex(5)Fuc(1)NeuAc(1), α2-macroglobulin A2M_N247_HexNAc(5)Hex(4)NeuAc(1), glycosylated forms of hyaluronic acid lectin, namely VTN_N169_HexNAc(3)Hex(4), phospholipid transfer protein FLTP_N245_HexNAc(4)Hex(5)Fuc(1)NeuAc(1), and heparin cofactor 2. SERPIND1_N49_HexNAc(4)Hex(5)NeuAc(2), sphingolipid-activated protein origin PSAP_N215_HexNAc(2)Hex(2)Fuc(1), zinc-binding α2-glycoprotein 1AZGP1_N128_HexNAc(4)Hex(5)NeuAc(2), α-albumin AFM_N402_HexNAc(4)Hex(5)NeuAc(2), immunoglobulin heavy chain γ2 constant region IGHG2_N176_HexNAc(4)Hex(3)Fuc(1), immunoglobulin heavy chain γ1 constant region IGHG1_N180_HexNAc(4)Hex(5)Fuc(1), immunoglobulin heavy chain constant μ IGHM_N440_HexNAc(2)Hex(8) 6. The application as described in claim 5, characterized in that, The differential diagnosis of primary biliary cholangitis is to distinguish it from other autoimmune liver diseases.

7. The application as described in claim 6, characterized in that, The other autoimmune liver diseases mentioned are autoimmune hepatitis, primary biliary cholangitis, and autoimmune hepatitis overlap syndrome.

8. A product for diagnosing primary biliary cholangitis, characterized in that, The product contains a reagent for detecting the biomarker described in claim 1 or 2.

9. The product as described in claim 8, characterized in that, The product includes a reagent kit.

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