Application of reagents for detecting PVRIG expression levels on T cells in the preparation of products for the diagnosis and prediction of type 1 diabetes mellitus

Abstract

The present invention provides a reagent for detecting the expression level of PVRIG on T cells in the preparation of products for diagnosing type 1 diabetes and predicting disease progression. Specifically, it relates to the expression of PVRIG on CD8 T cells in patients with type 1 diabetes in the honeymoon period and non-honeymoon period. + T cells, CCR7 ‑ CD8 + T cells and CCR7 + CD8 + There are differences in the expression of CD8 T cells and PVRIG in patients with type 1 diabetes who have rapid islet failure and those who have slow islet failure. + T cells, CCR7 ‑ CD8 + T cells and CCR7 + CD8 + There is differential expression on the surface of T cells, which indicates that PVRIG is closely related to type 1 diabetes and can serve as a new target for type 1 diabetes, providing a new approach for the diagnosis of type 1 diabetes and the prediction of disease progression.

Description

Technical Field

[0001] The present invention belongs to the field of biomedicine technology, and specifically relates to the use of a reagent for detecting the expression level of PVRIG in T cells in the preparation of products for diagnosing type 1 diabetes and predicting disease progression. Background Art

[0002] Type 1 diabetes (T1D) is a common metabolic disease with a complex pathogenesis involving genetic and environmental factors, as well as autoimmune systemic damage to pancreatic beta cells. Due to the complex pathological process involved in the development of T1D, clinical diagnosis and treatment are limited.

[0003] PVRIG is an inhibitory immune checkpoint receptor belonging to the poliovirus receptor (PVR) family. It was discovered in 2016. Expressed on the surface of T cells and NK cells, PVRIG binds to its ligand PVRL2, transmits immunosuppressive signals, and competitively antagonizes CD226, exerting its immunosuppressive function. Currently, PVRIG has been used in tumor immunotherapy, but its application in autoimmune diseases and metabolic diseases (such as T1D) has not yet been reported. Summary of the Invention

[0004] The purpose of this invention is to provide a new target PVRIG (CD8 + T cells), provides a new approach for the diagnosis of type 1 diabetes and prediction of disease progression.

[0005] In order to achieve the above object, the present invention provides a reagent for detecting the expression level of PVRIG in T cells in the preparation of a product for diagnosing type 1 diabetes and predicting disease progression, wherein the T cells are selected from CD8 + Phenotypic T cells, CCR7 - CD8 + Phenotypic T cells, CCR7 + CD8 + A type of T cell with a T phenotype.

[0006] In a specific embodiment, the type 1 diabetes diagnostic product is used to diagnose the disease progression stage of a diabetic patient, wherein the disease progression stage includes a honeymoon period or a non-honeymoon period.

[0007] In a specific embodiment, when the PVRIG expression level on the T cell surface of a type 1 diabetic patient is 80% to 120% of the standard expression level, the probability of diagnosing the diabetic patient as being in the honeymoon period is high, and the standard expression level is the PVRIG expression level on the T cells of a healthy control.

[0008] In a specific embodiment, when the PVRIG expression level on the surface of T cells of a type 1 diabetic patient is low relative to a standard expression level and is lower than 80% of the standard expression level, the probability of diagnosing that the diabetic patient is in the non-honeymoon period is high.

[0009] In a specific embodiment, the type 1 diabetes disease progression prediction product is used to predict diabetes progression based on the rate of pancreatic islet failure.

[0010] In a specific embodiment, the level of PVRIG expression on the surface of T cells in patients with type 1 diabetes is negatively correlated with the rate of pancreatic islet failure.

[0011] In a specific embodiment, the product is a reagent or a kit.

[0012] The beneficial effects of the present invention include at least:

[0013] 1. The present invention discovered CD8 for the first time + T cells, CCR7 - CD8 + T cells and CCR7 + CD8 + The expression level of PVRIG on T cell surface was different in the honeymoon period and non-honeymoon period of patients with type 1 diabetes. + T cells, CCR7 - CD8 + T cells and CCR7 + CD8 + The expression level of PVRIG on the surface of T cells can be used to diagnose the stage of disease progression in patients with type 1 diabetes and provide a basis for personalized treatment.

[0014] 2. This invention discovered CD8 for the first time + T cells, CCR7 - CD8 + T cells and CCR7 + CD8 + The PVRIG expression level on the surface of T cells is negatively correlated with the speed of pancreatic islet failure in patients with type 1 diabetes. The PVRIG expression level in the group with slower pancreatic islet failure was significantly higher than that in the group with faster pancreatic islet failure. + T cells, CCR7 - CD8 + T cells and CCR7 + CD8 + The relationship between the PVRIG expression level on the T cell surface and the rate of pancreatic islet failure can be used to predict the progression of diabetes and provide a basis for personalized treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 CD8 + T cells, CCR7 - CD8 + T cells and CCR7 + CD8 + The expression of PVRIG on the surface of T cells, Figure 1 A in the figure represents the CD8 + The expression of PVRIG on the surface of T cells, Figure 1 B is the CCR7 of the healthy control group (HC), the honeymoon period patient group (PR) and the non-honeymoon period patient group (NPR). - CD8 + The expression of PVRIG on the surface of T cells, Figure 1 C in the figure is CCR7 in the healthy control group (HC), the honeymoon period patient group (PR) and the non-honeymoon period patient group (NPR). + CD8 + Expression of PVRIG on the surface of T cells;

[0016] Figure 2 The CD8 + T cells, CCR7 - CD8 + T cells and CCR7 + CD8 + The expression of PVRIG on the surface of T cells, Figure 2 A in the figure represents the CD8 + The expression of PVRIG on the surface of T cells, Figure 2 B in the figure represents the CCR7-CD8 expression in the patient's honeymoon period (PR) and the period after the honeymoon period (PR-post). + The expression of PVRIG on the surface of T cells, Figure 2 C in the figure is the CCR7 level of the patient in the honeymoon period (PR) and the period after the honeymoon period (PR-post). + CD8 + Expression of PVRIG on the surface of T cells;

[0017] Figure 3 Graph showing the relationship between the concentration of CP-AUC and follow-up time for patients in the rapid decline group and the slow decline group in Example 2;

[0018] Figure 4 The baseline CD8 + T, CCR7 - CD8 + T, and CCR7 + CD8 + The expression of PVRIG on the surface of T cells, Figure 4 A is the baseline CD8 + The expression of PVRIG on the surface of T cells, Figure 4 B is the CCR7 at baseline in the rapid decline group and the slow decline group - CD8 + The expression of PVRIG on the surface of T cells, Figure 4 C is the CCR7 at baseline in the rapid decline group and the slow decline group + CD8 + Expression of PVRIG on the surface of T cells;

[0019] Figure 5 The forest plot is based on the Cox proportional hazards model to show the association between baseline immunological characteristics and the risk of severe islet function loss.

[0020] Figure 6 The statistical graph shows the average area under the receiver operating characteristic curve (AUC) and its 95% confidence interval for each machine learning model in 30 random samples;

[0021] Figure 7 Figure 2 is the receiver operating characteristic curve (ROC curve) of the Gaussian Naive Bayes (Gaussian NB) model in 30 random samples. DETAILED DESCRIPTION

[0022] The present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0023] Unless otherwise specified, all materials and reagents used in the following examples were commercially available. Specifically, the C-peptide detection kit (Advia Centaur System) was purchased from Siemens, Germany; lymphocyte separation medium (Histopaque-1077) was purchased from Sigma-Aldrich; Dulbecco's phosphate-buffered saline (DPBS) was purchased from Gibco; flow cytometry antibodies such as Anti-Human CD3 Antibody, Anti-Human CD197 (CCR7) Antibody, and Anti-Human CD8 Antibody were purchased from BD Biosciences; and the flow cytometry antibody Anti-Human CD112R (PVRIG) Antibody and cell viability dye (Zombie Aqua Fixable Viability Kit) were purchased from BioLegend.

[0024] In the present invention, density gradient centrifugation was used to separate peripheral blood mononuclear cells (PBMCs), full-spectrum flow cytometry was used to identify immune cell subsets, and full-spectrum flow cytometry was used to detect the expression of PVRIG surface molecules. The specific operating steps are as follows:

[0025] Density gradient centrifugation for PBMC isolation: Human peripheral blood samples were collected in sodium heparin or EDTA-anticoagulant tubes and processed within 2 hours. Whole blood was diluted 1:1 with Dulbecco's phosphate-buffered saline (DPBS, Gibco, USA) and carefully layered over an equal volume of lymphocyte separation medium (Histopaque-1077, Sigma-Aldrich, USA). Samples were centrifuged at 800 × g for 25 minutes at room temperature, with no brakes, at the lowest deceleration setting. The mononuclear cell (PBMC) layer at the plasma-separation medium interface was carefully aspirated and transferred to a new centrifuge tube. The pellet was then washed twice with DPBS (300 × g, 10 minutes). The final cell pellet was resuspended in an appropriate buffer for subsequent experiments. Cell count and viability were assessed using a hemocytometer or automated cell counter using trypan blue staining.

[0026] Identification of immune cell subsets by full-spectrum flow cytometry: To analyze different T cell subsets in peripheral blood, flow cytometry was used to analyze CD8 + Surface labeling and detection of T cells and their functional phenotypes. The specific operation is as follows: 1~2×10 6PBMCs were divided into flow cytometry tubes, washed with DPBS containing 2% fetal bovine serum (FBS), and then incubated with active dye (ZombieAqua, BioLegend) at room temperature in the dark for 15 minutes, followed by washing. A mixture of fluorescently labeled anti-human monoclonal antibodies was added and incubated at 4°C in the dark for 30 minutes. The antibodies used included Anti-Human CD3 Antibody, Anti-Human CD8 Antibody, Anti-Human CD197 (CCR7) Antibody from BD Biosciences, and Anti-Human PVRIG Antibody from BioLegend. After staining, the cells were washed again and resuspended in FACS buffer for detection on the machine. Data were collected using a BD LSRFortessa high-parameter flow cytometer, and data analysis was performed using FlowJo 10.8.1 software. Using the fluorescent labeling of flow cytometry antibodies, cell populations were identified through appropriate gating strategies, and CD8 + T cells, CCR7 + CD8 + T cells, CCR7 - CD8 + The proportion and distribution of T cell and other groups.

[0027] Full spectrum flow cytometry was used to detect the expression of PVRIG surface molecules: using the fluorescent labeling of flow cytometry antibodies, the appropriate gating strategy was used to detect the expression of PVRIG surface molecules in CD8 + T cells, CCR7 + CD8 + T cells, CCR7 - CD8 + PVRIG-labeled T cell population + subpopulation, and finally obtained CD8 + T cells, CCR7 - CD8 + T cells and CCR7 + CD8 + Expression of PVRIG on the surface of T cells.

[0028] Example 1

[0029] PVRIG in CD8 + Correlation between T cell surface expression levels and T1D stage in patients

[0030] 1.1 Sample Selection

[0031] Methods: 35 newly diagnosed T1D patients, 50 patients in the honeymoon phase, and 20 healthy controls were recruited and followed up regularly for 2 years, with patients reexamined every 3 months. Honeymoon phase (PR) was determined based on one of the following two criteria: (1) a C-peptide level ≥ 300 pmol / L stimulated by a mixed meal tolerance test (MMTT); (2) an insulin dose-adjusted glycated hemoglobin index (IDAA1c) ≤ 9, where IDAA1c = HbA1c (%) + 4 × daily insulin dose (units / kg body weight). When the C-peptide value was missing, the IDAA1c value was used to determine whether the patient was in the honeymoon phase.

[0032] 1.2 Identification of immune subpopulation cells in the above samples

[0033] All samples were collected from patients in the honeymoon period after fasting for at least 10 hours. Blood samples were collected again in the morning of the next day. PBMCs were separated from peripheral blood by density gradient centrifugation and immune subsets were detected by flow cytometry. Cell populations were identified by appropriate gating strategies, and CD8 + T cells, CCR7 - CD8 + T cells and CCR7 + CD8 + T cells, so as to subsequently detect the expression of PVRIG and obtain the proportion and distribution of each population.

[0034] 1.3 Detection of PVRIG expression levels

[0035] The expression of PVRIG surface molecules in each immune subpopulation cell identified in step 1.2 was detected by full-spectrum flow cytometry. The test results are detailed in Figure 1 and Figure 2 shown.

[0036] Figure 1 CD8 + T cells, CCR7 - CD8 + T cells and CCR7 + CD8 + The expression of PVRIG on the surface of T cells, Figure 1 A in the figure is the expression of PVRIG on the surface of CD8+T cells in the healthy control group (HC), the honeymoon period patient group (PR) and the non-honeymoon period patient group (NPR). Figure 1B is the CCR7 of the healthy control group (HC), the honeymoon period patient group (PR) and the non-honeymoon period patient group (NPR). - CD8 + The expression of PVRIG on the surface of T cells, Figure 1 C in the figure is CCR7 in the healthy control group (HC), the honeymoon period patient group (PR) and the non-honeymoon period patient group (NPR). + CD8 + The expression of PVRIG on the surface of T cells. Figure 1 It can be seen that PVRIG in patients in the honeymoon period is + T cells, CCR7 - CD8 + T cells and CCR7 + CD8 + The expression level on the T cell surface was significantly higher than that in non-honeymoon patients and was close to the expression level of PVRIG in the healthy control group.

[0037] Figure 2 The CD8 + T cells, CCR7 - CD8 + T cells and CCR7 + CD8 + The expression of PVRIG on the surface of T cells, Figure 2 A in the figure represents the CD8 + The expression of PVRIG on the surface of T cells, Figure 2 B in the figure is the expression of PVRIG on the surface of CCR7-CD8+T cells in the honeymoon period (PR) and the period after the end of the honeymoon period (PR-post). Figure 2 C in the figure is the CCR7 level of the patient in the honeymoon period (PR) and the period after the honeymoon period (PR-post). + CD8 + The expression of PVRIG on the surface of T cells Figure 2 It can be seen that PVRIG in patients in the honeymoon stage is + T cells, CCR7 - CD8 + T cells and CCR7 + CD8 + The expression level on the surface of T cells is significantly higher than that after the honeymoon period.

[0038] Combine Figure 1 and Figure 2It can be seen that the expression level of PVRIG is closely related to the disease stage of T1D patients and can be used as a biomarker for diagnosing the disease stage.

[0039] In the present invention, when the T cell PVRIG expression level in diabetic patients is 80% to 120% of the standard expression level, it indicates that the PVRIG expression levels of the two are close; when the T cell PVRIG expression level in diabetic patients is low expression relative to the standard expression level and is lower than 80% of the standard expression level, it indicates that the T cell PVRIG expression level is significantly lower than the standard expression level.

[0040] In the present invention, the standard expression level is the T cell PVRIG expression level of healthy controls.

[0041] Example 2

[0042] PVRIG in CD8 + T cell surface expression levels predict the rate of pancreatic islet failure in T1D patients

[0043] 2.1 Case selection

[0044] Newly diagnosed T1D patients (67 patients) were recruited and followed up regularly for a total of 2 years, with patients re-examined every 3 months. Patients were categorized based on the rate of islet function failure. Figure 3 , during the first 18 months of follow-up, 35 patients whose CP-AUC decreased to less than 50% of the baseline level were classified as the "rapid decline" group, while the remaining 32 patients whose CP-AUC did not decrease to less than 50% of the baseline were classified as the "slow decline" group.

[0045] Figure 3 The specific details of the 67 newly recruited T1D patients who were divided into "rapid decline" and "slow decline" groups according to the rate of islet function failure during the 2-year follow-up were provided. Figure 3 The changing trends of CP-AUC over time in the two groups of patients are shown. Specifically, Figure 3 The significance analysis in this study is for the comparison between groups in each follow-up month (i.e., the difference in data between different groups in the same follow-up month); Figure 3 The last “****” is the total difference in the follow-up change trend of the overall data between the “rapid decline” and “slow decline” groups.

[0046] 2.2 Identification of immune subsets in the above cases

[0047] Peripheral blood samples were collected from all subjects at baseline. PBMCs were isolated by density gradient centrifugation and immune subsets were detected by flow cytometry. Cell populations were identified by appropriate gating strategies, and CD8+ T cells, CCR7 - CD8 + T cells, CCR7 + CD8 + T cells, and obtain the proportion and distribution of each population.

[0048] 2.3 Detection of PVRIG expression level

[0049] The expression of PVRIG surface molecules in each immune subpopulation cell identified in step 2.2 was detected by full spectrum flow cytometry. The test results are detailed in Figure 4 shown.

[0050] Figure 4 The baseline CD8 + T, CCR7-CD8 + T, and CCR7 + CD8 + The expression of PVRIG on the surface of T cells, Figure 4 A is the baseline CD8 + The expression of PVRIG on the surface of T cells, Figure 4 B is the CCR7 at baseline in the rapid decline group and the slow decline group - CD8 + The expression of PVRIG on the surface of T cells, Figure 4 C is the CCR7 at baseline in the rapid decline group and the slow decline group + CD8 + The expression of PVRIG on the surface of T cells Figure 4 It can be seen that the CD8 + T cells, CCR7 - CD8 + T cells and CCR7 + CD8 + The expression level of PVRIG in T cells was significantly higher than that in the group with rapid islet failure. + CD8 + T cells, CCR7 - CD8 + T cells and CCR7 + CD8 + A high T cell surface ratio is a protective factor for islet function in T1D patients.

[0051] 2.4 Cox regression analysis

[0052] After collecting and collating the clinical follow-up data and baseline immunological characteristics of the patients within 2 years, the Cox proportional hazards regression model was used to analyze whether PVRIG-related immunological characteristics could predict the risk of severe islet function loss (C-peptide <100 pmol / L). The results are detailed in Tables 1 and Figure 5 .

[0053] Table 1

[0054]

[0055] Figure 5 The association between baseline immunologic features and the risk of severe islet function loss events in a Cox proportional hazards model is shown (where a hazard ratio <1 indicates that the corresponding feature is a protective factor, and a P value <0.05 indicates that the feature is significantly associated with the risk of the event).

[0056] From Table 1 and Figure 5 It can be seen that the patient's baseline CD8 + T, CCR7 - CD8 + T, and CCR7 + CD8 + The expression of PVRIG on the surface of T cells can independently serve as a protective factor and is significantly associated with the risk of severe islet function loss during follow-up.

[0057] 2.5 Evaluation of PVRIG in CD8 + Predictive performance of expression in each T cell subset as a predictive indicator

[0058] Using machine learning classification model algorithms, multiple prediction models for predicting the rate of pancreatic islet failure in T1D patients are constructed. The prediction models can be Cox proportional hazard regression models or K nearest neighbor (KNN), logistic regression (LogisticRegression), support vector machine (SVM), Gaussian naive Bayes (GaussianNB), decision tree (Decision Tree), random forest (Random Forest), integrated gradient boosting model (XGBoost, Light GBM, CatBoost) and other machine learning classification models.

[0059] See also Figure 6 , Figure 6The mean area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (CI) for each machine learning classification model across 30 random sampling runs are presented. The AUC reflects the ability of each model to discriminate between the faster and slower rates of pancreatic islet function decline based on baseline PVRIG-related immunological features. The Gaussian Naive Bayes (NB) model performed best, achieving a mean AUC of 0.74.

[0060] See also Figure 7 , Figure 7 The receiver operating characteristic curve (ROC curve) of the Gaussian naive Bayes (GaussianNB) model with the best performance in 30 random samples is shown. The average area under the receiver operating characteristic curve is 0.74, and the 95% confidence interval is 0.72~0.77.

[0061] from Figure 6 and Figure 7 It can be seen that baseline PVRIG in CD8 + The expression of PVRIG in various T cell subsets has good discriminatory power and can predict the speed of pancreatic islet failure in T1D patients in the early stages of the disease. This result suggests that PVRIG expression levels can be used to predict the speed of pancreatic islet failure in T1D patients and provide a basis for personalized treatment.

[0062] It’s important to note that the rate of pancreatic islet failure can reflect the progression of new-onset T1D. The faster the islet failure, the faster the islets are destroyed, indicating faster T1D progression.

[0063] Combining the experimental results of Example 1 and Example 2, it can be seen that PVRIG has a significant effect on the CD8 + T cells, CCR7 - CD8 + T cells and CCR7 + CD8 + There are differences in the expression of CD8 T cells and PVRIG in patients with type 1 diabetes who have rapid islet failure and those who have slow islet failure. + T cells, CCR7 - CD8 + T cells and CCR7 + CD8 +There are differential expressions on the surface of T cells. Specifically, PVRIG is significantly under-expressed in non-honeymoon patients. The expression of PVRIG is negatively correlated with the rate of pancreatic islet failure, indicating that PVRIG is closely related to type 1 diabetes and can serve as a new target for type 1 diabetes, providing a new approach for the diagnosis of type 1 diabetes and the prediction of disease progression.

[0064] The above content is a further detailed description of the present invention in conjunction with specific preferred embodiments, and the specific implementation of the present invention should not be considered to be limited to these descriptions. For those skilled in the art of the present invention, several simple deductions and substitutions can be made without departing from the concept of the present invention, and all of these should be considered to fall within the scope of protection of the present invention.

Claims

1. Use of a reagent for detecting the expression level of PVRIG in T cells in the preparation of a product for predicting disease progression in patients with type 1 diabetes, characterized in that: The T cells are selected from CD8 + Phenotypic T cells, CCR7 - CD8 + Phenotypic T cells, CCR7 + CD8 + A phenotypic T cell, type 1 diabetes disease progression prediction product is used to predict diabetes progression based on the rate of pancreatic islet failure.

2. The use according to claim 1, characterized in that The expression level of PVRIG on the T cell surface of patients with type 1 diabetes is negatively correlated with the rate of pancreatic islet failure.

3. The use according to claim 1 or 2, characterized in that The product is a reagent or a kit.

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