Marker combination, antibody chip and kit for detecting diabetic kidney diseases

Abstract

The invention discloses a marker combination, an antibody chip and a kit for detecting diabetic kidney diseases. The antibody chip comprises a solid phase carrier and a capture antibody coated on the surface of the solid phase carrier, the capture antibody can be specifically combined with a diabetic kidney disease marker combination, and the marker combination comprises CTACK, HGF and MIP-1 alpha. The antibody chip and the kit for detecting the marker combination of the diabetic kidney disease show high sensitivity and high specificity in detection of the diabetic kidney disease by detecting the screened marker combination. The detection method is small in sample demand, simple and convenient to operate and low in cost, overcomes the defects that a traditional technology is tedious in operation, single in index and prone to being interfered, and provides a powerful tool for early screening, risk assessment and medication curative effect monitoring of the diabetic kidney diseases.

Description

Technical Field

[0001] This application relates to the field of biotechnology, specifically to biomarker combinations, antibody chips, and reagent kits for detecting diabetic kidney disease. Background Technology

[0002] Diabetic kidney disease (DKD) is a major microvascular complication of diabetes. Data shows that approximately 20-40% of diabetic patients have DKD, and 30-50% of end-stage renal disease (ESRD) is caused by DKD. Early screening and detection of kidney disease in diabetic patients are of great importance.

[0003] According to the Chinese Consensus on Clinical Management of Diabetes Mellitus Complicated with Chronic Kidney Disease (2024), early screening and detection of chronic kidney disease (CKD) can significantly reduce the risk of end-stage renal disease (ESRD) and cardiovascular disease in patients with diabetes mellitus and CKD. The urine albumin / creatinine ratio (UACR) is recommended as the primary screening method for urinary albumin excretion. Secondly, 24-hour urinary albumin quantification or urinary albumin excretion rate (UAER) has comparable diagnostic value to UACR. Clinically, it is also recommended to calculate eGFR using a validated formula based on serum creatinine levels. However, UACR, as a screening method for urinary albumin excretion, is affected by various physiological or pathological factors; therefore, it should be repeated three times within 3–6 months, with at least two abnormal results to be considered an increase in urinary albumin excretion. Secondly, although UAER has comparable diagnostic value to UACR, sample collection is more cumbersome. Thirdly, the clinically recommended validated formula for calculating eGFR is also susceptible to bias due to the influence of various physiological or pathological factors on serum creatinine levels. Summary of the Invention

[0004] Therefore, it is necessary to provide biomarker combinations, antibody chips, and kits for detecting diabetic kidney disease.

[0005] A first aspect of this application provides an antibody chip for detecting a combination of biomarkers for diabetic kidney disease, comprising a solid-phase carrier and a capture antibody coated on the surface of the solid-phase carrier, the capture antibody being capable of specifically binding to the combination of biomarkers for diabetic kidney disease, the combination of biomarkers including CTACK, HGF, and MIP-1α.

[0006] In some implementations, the combination of markers also includes Prolatin, TIM-1, and IL3.

[0007] In some embodiments, the capture antibodies for each marker in the marker combination are separately disposed in different reaction tanks.

[0008] In some embodiments, the solid support comprises a glass slide.

[0009] In some embodiments, the solid support further includes one or more of a soft silicone pad, a rigid frame, and a U-shaped frame clamp, wherein the soft silicone pad and the rigid frame are combined with the glass slide to form multiple independent reaction tanks.

[0010] A second aspect of this application provides an antibody chip kit for detecting a combination of biomarkers for diabetic kidney disease, comprising the antibody chip described in the first aspect of this application.

[0011] In some embodiments, the solution may also include one or more of the following: washing solution or its concentrate, diluent or its concentrate, horseradish peroxidase-streptavidin solution, fluorescein-streptavidin solution or its concentrate, detection antibody, sample processing solution, and standards.

[0012] In some embodiments, the washing solution comprises 0.1-0.2% Tween-20 and 0.1-0.2 mol / L phosphate buffer;

[0013] Optionally, the pH of the phosphate buffer solution is 7.1 to 7.3.

[0014] In some embodiments, the diluent includes diluent B and diluent D;

[0015] Optionally, the diluent B comprises 14 mM to 16 mM PBS buffer, 0.4% (w / v) to 0.6% (w / v) casein, 2% (w / v) to 4% (w / v) sucrose, and 140 mM to 160 mM sodium chloride, wherein the pH of the PBS buffer is 7.3 to 7.5;

[0016] Optionally, the diluent D comprises 14 mM to 16 mM PBS buffer, 2% (w / v) to 4% (w / v) sucrose and 140 mM to 160 mM sodium chloride, wherein the pH of the PBS buffer is 6.4 to 6.6.

[0017] In some embodiments, the sample processing solution is a cell lysis buffer or its concentrate;

[0018] Optionally, the cell lysis buffer includes HEPES buffer and a protease inhibitor.

[0019] In some implementations, one or more of the following conditions are also satisfied:

[0020] The detection antibody is a biotinylated specific antibody against a combination of biomarkers for diabetic kidney disease, the combination of biomarkers including CTACK, HGF and MIP-1α, and optionally, the combination of biomarkers also including Prolatin, TIM-1 and IL3;

[0021] The standard is a mixture of biomarkers for diabetic kidney disease.

[0022] A third aspect of this application provides the use of the antibody chip described in the first aspect of this application, or the antibody chip kit described in the second aspect of this application, in detecting a combination of biomarkers for diabetic nephropathy or in assisting in the assessment of renal prognosis in diabetic patients or in assisting in the detection of diabetic nephropathy, wherein the biomarker combination includes CTACK, HGF, and MIP-1α.

[0023] In the auxiliary assessment of renal prognosis in diabetic patients, the diabetic patients were given Yishen Huashi Granules.

[0024] The application is not for disease detection purposes;

[0025] Optionally, the combination of markers may also include Prolatin, TIM-1, and IL3.

[0026] A fourth aspect of this application provides a biomarker combination for detecting diabetic kidney disease, the biomarker combination including CTACK, HGF and MIP-1α, and optionally, the biomarker combination further including Prolatin, TIM-1 and IL3.

[0027] The aforementioned antibody chip and kit for detecting biomarker combinations in diabetic nephropathy demonstrate high sensitivity and specificity in the detection of diabetic nephropathy by detecting the selected biomarker combinations. This detection method requires minimal sample volume, is simple to operate, and is inexpensive, overcoming the shortcomings of traditional techniques such as cumbersome operation, single indicator, and susceptibility to interference. It provides a powerful tool for early screening, risk assessment, and monitoring of medication efficacy in diabetic nephropathy. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments and examples of this application, and to more completely understand this application and its beneficial effects, the accompanying drawings used in the description of the embodiments or examples will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of this application. Those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0029] Figure 1 This is a scanning result image of the GSR-CYT3 and GSR-CYT4 antibody chip in one embodiment of this application;

[0030] Figure 2 This is a PCA analysis diagram of differentially expressed proteins between intervention group 1 and the normal group in one embodiment of this application;

[0031] Figure 3 This is a PCA analysis diagram of differentially expressed proteins between the normal group and the DKD model group in one embodiment of this application;

[0032] Figure 4 This is a PCA analysis diagram of differentially expressed proteins between intervention group 2 and the normal group in one embodiment of this application;

[0033] Figure 5 This is a PCA analysis diagram of differentially expressed proteins between intervention group 3 and the normal group in one embodiment of this application;

[0034] Figure 6 This is a graph showing the GO enrichment analysis of differentially expressed proteins between the normal group and the DKD model group in one embodiment of this application (Biological Engineering).

[0035] Figure 7 This is a graph showing the GO enrichment analysis (molecular function) of differentially expressed proteins between the normal group and the DKD model group in one embodiment of this application.

[0036] Figure 8 This is a KEGG enrichment analysis diagram of the normal group and the DKD model group in one embodiment of this application;

[0037] Figure 9 This is a differential protein volcano plot between intervention group 3 and the DKD model group in one embodiment of this application;

[0038] Figure 10 This is a heatmap of differential protein clustering between intervention group 3 and the DKD model group in one embodiment of this application;

[0039] Figure 11 This is a scatter plot showing the differential protein expression between intervention group 3 and the DKD model group in one embodiment of this application.

[0040] Figure 12 This is a KEGG enrichment analysis diagram of differentially expressed proteins between intervention group 3 and the DKD model group in one embodiment of this application;

[0041] Figure 13 This is a heatmap of differential protein clustering between intervention group 3 and intervention group 1 in one embodiment of this application;

[0042] Figure 14 This is a differential protein volcano plot between intervention group 3 and intervention group 1 in one embodiment of this application;

[0043] Figure 15 This is a scatter plot showing the differential protein expression between intervention group 3 and intervention group 1 in one embodiment of this application;

[0044] Figure 16 This is a KEGG enrichment analysis diagram of differentially expressed proteins between intervention group 3 and intervention group 1 in one embodiment of this application;

[0045] Figure 17 This is a PCA analysis diagram of differentially expressed proteins in all grouped samples according to one embodiment of this application;

[0046] Figure 18 This is a heatmap of differential protein clustering for all grouped samples in one embodiment of this application;

[0047] Figure 19 This is a graph showing the expression trend of differentially expressed proteins in each group according to one embodiment of this application;

[0048] Figure 20 This is a schematic diagram of the serial dilution of standards in the CTACK ELISA kit according to one embodiment of this application;

[0049] Figure 21 This is a heatmap showing the expression clustering of different proteins in plasma samples from different populations according to one embodiment of this application;

[0050] Figure 22 This is a graph showing the ELISA detection results of different proteins in the serum of different populations according to one embodiment of this application;

[0051] Figure 23 This is a graph showing the ELISA detection results of different proteins in the plasma of different populations according to one embodiment of this application;

[0052] Figure 24 This is a comparison chart of chip results using kidney tissue detection and ELISA results using blood sample verification in one embodiment of this application. Detailed Implementation

[0053] To facilitate understanding of this application, a more complete description will be provided below with reference to the accompanying drawings. Preferred embodiments of this application are shown in the drawings. However, this application can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a thorough and complete understanding of the disclosure of this application.

[0054] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0055] In this application, "optionally," "optionally," and "optional" mean that something is optional, that is, it means that it is selected from either "with" or "without." If there are multiple "optional" entries in a technical solution, unless otherwise specified, and there are no contradictions or mutual constraints, each "optional" entry shall be independent.

[0056] In this application, terms such as "preferred," "better," "more suitable," and "ideal" are merely used to describe implementation methods or embodiments that achieve better results, and should be understood not to limit the scope of protection of this application.

[0057] The terms “having,” “containing,” “comprising,” and “including” as used in this application are synonyms and are inclusive or open-ended, not excluding additional, uncited members or features. Members or features include, for example, materials or components, structures, elements, instruments, etc.; non-limiting examples of members or features include actions, conditions under which actions occur, timing, states, etc.

[0058] In this application, the technical features or solutions described in open-ended language include both closed-ended technical features or solutions consisting of the listed contents and open-ended technical features or solutions that include the listed contents.

[0059] In this application, if the unit of a data range is only followed by the right endpoint, it means that the units of the left and right endpoints are the same.

[0060] In this application, where the method flow involves multiple steps, unless otherwise explicitly stated herein, there is no strict order restriction on the execution of these steps; they can be executed in any order other than those described. Moreover, any step may include multiple sub-steps or multiple stages, which are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or simultaneously with other steps or parts of the sub-steps or stages of other steps.

[0061] In this application, the exemplary descriptions such as "in some implementations (or embodiments)" and "in one implementation (or embodiment)" may cover, but are not limited to, the following meanings: these solutions can be combined with other solutions in a suitable manner to form new technical solutions.

[0062] In this application, the terms "first aspect," "second aspect," "third aspect," "fourth aspect," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or quantity, nor should they be construed as implicitly indicating the importance or quantity of the indicated technical features. Moreover, "first," "second," "third," "fourth," etc., serve only as a non-exhaustive enumeration and should be understood not to constitute a closed limitation on quantity.

[0063] In this application, when numerical intervals (i.e., numerical ranges) are mentioned, unless otherwise specified, the distribution of selectable numerical values ​​within the numerical interval is considered continuous, and includes the two endpoints of the numerical interval (i.e., the minimum and maximum values), as well as every numerical value between these two endpoints. Unless otherwise specified, when a numerical interval refers only to integers within that numerical interval, it includes the two endpoint integers of the numerical range, as well as every integer between the two endpoints, which is equivalent to directly listing every integer. When multiple numerical ranges are provided to describe features or characteristics, these numerical ranges can be merged. In other words, unless otherwise specified, the numerical ranges disclosed herein should be understood to include any and all subranges included therein. The "numerical value" in the numerical interval can be any quantitative value, such as a number, percentage, ratio, etc. The term "numerical interval" can be broadly included to include numerical interval types such as percentage intervals, ratio intervals, and proportion intervals.

[0064] In this application, the terms "room temperature" or "normal temperature" generally refer to 4°C to 35°C, for example, 20°C ± 5°C. In some embodiments of this application, "room temperature" or "normal temperature" refers to 10°C to 30°C. In some embodiments of this application, "room temperature" or "normal temperature" refers to 20°C to 30°C.

[0065] In this application, w / v represents mass-volume percentage. In some embodiments of this application, w is expressed in grams and v in mL.

[0066] Currently, UACR, as a screening method for urinary albumin excretion, is affected by various physiological or pathological factors. Therefore, it should be repeated 3 times within 3-6 months, with at least 2 abnormal results to be considered as increased urinary albumin excretion. Secondly, although UAER has comparable detection value to UACR, sample collection is more cumbersome. Thirdly, the clinically recommended and validated formula for calculating eGFR is also subject to bias due to the susceptibility of serum creatinine to various physiological or pathological factors.

[0067] Based on this, the embodiments of this application at least provide a combination of biomarkers, an antibody chip, and a kit for detecting diabetic kidney disease.

[0068] Cytokines play crucial roles in innate immunity, apoptosis, angiogenesis, cell growth, and differentiation. They are involved in interactions between different cell types, cellular responses to environmental conditions, and the maintenance of homeostasis. Furthermore, cytokines are involved in most disease processes, including cancer and heart disease. This application utilizes RayBio® G series antibody chips, allowing researchers to rapidly and accurately analyze the expression profiles of hundreds of cytokines, chemokines, growth factors, proteases, soluble receptors, and other proteins from any biological fluid. Similar to traditional sandwich ELISAs, this chip uses specific cytokine antibody pairs for detection. After sample incubation, the target cytokine is captured by antibodies imprinted on a solid surface. A second biotin-labeled detection antibody is then added, recognizing different epitopes of the target cytokine. The cytokine-antibody-biotin complex can be visualized by adding streptavidin-conjugated Cy3 equivalent dye. Similar to Quantibody® chips, the G series employs a highly sensitive and stable fluorescence readout method, detectable by most laser fluorescence scanning systems. After capturing the spot density using a laser scanner, researchers can easily calculate the normalization of the raw data, or complete the task by quickly copying and pasting it into Excel-based analysis software.

[0069] In some embodiments, this application provides a high-throughput, high-sensitivity, high-specificity, and low-cost DKD detection kit, specifically employing antibody chip technology, which can simultaneously detect multiple DKD biomarkers. This overcomes the shortcomings of existing technologies, such as cumbersome operation, single detection index, and low sensitivity. It has the advantages of being inexpensive, convenient, sensitive, accurate, high-throughput, requiring less sample volume, and being able to be promoted and scaled up in ordinary laboratories.

[0070] In a first aspect of this application, an antibody chip is provided for detecting a combination of biomarkers for diabetic nephropathy, comprising a solid-phase carrier and a capture antibody coated on the surface of the solid-phase carrier, wherein the capture antibody is capable of specifically binding to the combination of biomarkers for diabetic nephropathy, the combination of biomarkers including CTACK, HGF and MIP-1α.

[0071] In some implementations, the marker combination also includes Prolatin, TIM-1, and IL3.

[0072] Those skilled in the art can obtain the above-mentioned capture antibodies through commercial purchase or prepare them using conventional techniques in the art. It should be noted that the above-mentioned capture antibodies are not limited to their full-length form, but also include variants modified by genetic engineering or protein engineering, such as mutants containing functional fragments (e.g., Fab, F(ab')2, scFv), mutants with point mutations, deletions or insertions, and fusion proteins formed with tag proteins.

[0073] In some implementations, the capture antibodies coated on the surface of the solid-phase carrier are used with different coating concentrations to ensure that each marker is within its optimal linear detection range during detection, thus avoiding insufficient sensitivity due to inappropriate concentration.

[0074] In some implementations, the solid support includes a glass slide.

[0075] In some embodiments, the solid support also includes one or more of a soft silicone pad, a rigid frame, and a U-shaped frame clamp, wherein the soft silicone pad and the rigid frame are combined with the glass slide to form multiple independent reaction tanks.

[0076] In a second aspect of this application, an antibody chip kit for detecting a combination of biomarkers for diabetic kidney disease is provided, comprising the antibody chip described above.

[0077] In some embodiments, the solution may also include one or more of the following: washing solution or its concentrate, diluent or its concentrate, horseradish peroxidase-streptavidin solution, fluorescein-streptavidin solution or its concentrate, detection antibody, sample processing solution, and standards.

[0078] In some embodiments, the washing solution comprises 0.1% (w / v) to 0.2% (w / v) of Tween-20 and 0.1 to 0.2 mol / L of phosphate buffer, wherein the pH of the phosphate buffer is 7.1 to 7.3. Non-limitingly, the concentration of Tween-20 may be, but is not limited to, 0.1% (w / v), 0.15% (w / v), 0.2% (w / v), or any value or range between two of the above; the concentration of the phosphate buffer may be, but is not limited to, 0.1 mol / L, 0.15 mol / L, 0.2 mol / L, or any value or range between two of the above.

[0079] In some embodiments, the concentration factor of the detergent concentrate is 1 to 20 times.

[0080] In some embodiments, the diluent includes diluent B and diluent D.

[0081] In some embodiments, diluent B comprises 14 mM to 16 mM PBS buffer, 0.4% (w / v) to 0.6% (w / v) casein, 2% (w / v) to 4% (w / v) sucrose, and 140 mM to 160 mM sodium chloride, wherein the pH of the PBS buffer is 7.3 to 7.5. Non-limitingly, the concentration of the PBS buffer may be, but is not limited to, 14 mM, 15 mM, 16 mM, or any two of the above values ​​or a range thereof; the concentration of the casein may be, but is not limited to, 0.4% (w / v), 0.5% (w / v), 0.6% (w / v), or any two of the above values ​​or a range thereof; the concentration of the sucrose may be, but is not limited to, 2% (w / v), 3% (w / v), 4% (w / v), or any two of the above values ​​or a range thereof; and the concentration of the sodium chloride may be, but is not limited to, 140 mM, 150 mM, 160 mM, or any two of the above values ​​or a range thereof.

[0082] In some embodiments, the diluent D comprises 14 mM to 16 mM PBS buffer, 2% (w / v) to 4% (w / v) sucrose, and 140 mM to 160 mM sodium chloride, wherein the pH of the PBS buffer is 6.4 to 6.6. Non-limitingly, the concentration of the PBS buffer may be, but is not limited to, 14 mM, 15 mM, 16 mM, or any value or range between two of the above; the concentration of the sucrose may be, but is not limited to, 2% (w / v), 3% (w / v), 4% (w / v), or any value or range between two of the above; and the concentration of the sodium chloride may be, but is not limited to, 140 mM, 150 mM, 160 mM, or any value or range between two of the above.

[0083] In some embodiments, the concentration factor of the concentrate of diluent B is 1 to 5 times.

[0084] In some embodiments, the concentration factor of the concentrate of diluent D is 1 to 5 times.

[0085] In some embodiments, the sample processing solution is a cell lysis buffer or its concentrate, the cell lysis buffer comprising HEPES buffer and protease inhibitors.

[0086] In some embodiments, the concentration factor of the cell lysate concentrate is 1 to 5 times.

[0087] In some embodiments, the detection antibody is a biotinylated specific antibody against a combination of biomarkers for diabetic nephropathy, including CTACK, HGF, and MIP-1α. Further, the biomarker combination also includes Prolatin, TIM-1, and IL3.

[0088] In some implementations, the standard is an antigen mixture of the above-mentioned markers.

[0089] In a third aspect of this application, the above-described antibody chip or antibody chip kit is provided for use in detecting a combination of biomarkers for diabetic nephropathy or in assisting in the assessment of renal prognosis in diabetic patients or in assisting in the detection of diabetic nephropathy. The biomarker combination includes CTACK, HGF, and MIP-1α; further, the biomarker combination also includes Prolatin, TIM-1, and IL3.

[0090] In assisting the assessment of renal prognosis in diabetic patients, the diabetic patients were given Yishen Huashi Granules.

[0091] In some implementations, the application is for non-disease detection purposes. It can be used to study the pathogenesis of diabetic nephropathy, analyze biomarker expression profiles, validate animal models of the disease, or evaluate the interventional effects of drugs on the expression levels of said biomarkers.

[0092] In some implementations, the application is for detection purposes.

[0093] In some implementations, steps to aid in the assessment of renal outcomes in diabetic patients include:

[0094] The sample to be tested is incubated with the antibody chip, so that the markers in the sample specifically bind to the capture antibodies coated on the chip.

[0095] The detection antibody and fluorescein-streptavidin solution were added sequentially for incubation and signal amplification, followed by fluorescence detection.

[0096] The levels of detected biomarkers were compared with standards or preset thresholds, and the renal prognostic trend was assessed in conjunction with whether the patient had received interventions such as Yishen Huashi Granules.

[0097] In some implementations, the steps for assisting in the detection of diabetic kidney disease include:

[0098] The expression levels of the above-mentioned biomarkers in the test sample are detected using antibody microarrays or antibody microarray kits; the expression levels of the biomarkers are compared with a health reference or detection threshold, and whether they exceed the threshold range helps to determine whether the subject has diabetic kidney disease.

[0099] In some implementations, the sample to be tested includes one or more of serum, plasma, and tissue lysate.

[0100] In a fourth aspect of this application, a combination of biomarkers for detecting diabetic kidney disease is provided, the biomarker combination including CTACK, HGF and MIP-1α; further, the biomarker combination also includes Prolatin, TIM-1 and IL3.

[0101] In some embodiments, the above-described biomarker combination can be used as a calibrator or quality control material for the quality control of the above-described diabetic nephropathy detection kit.

[0102] In some implementations, the above-described biomarker combination can be used as an adjunct to the detection or prognostic assessment of diabetic kidney disease.

[0103] The following are some examples.

[0104] The embodiments of this application will be described in detail below with reference to examples. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of this application. For experimental methods in the following embodiments where conditions are not specified, reference should be made to the guidelines given in this application, or to experimental manuals or conventional conditions in the art, or to the conditions recommended by the manufacturer, or to experimental methods known in the art.

[0105] In the following examples, the measurement parameters of the raw material components may have slight deviations within the weighing accuracy range unless otherwise specified. Temperature and time parameters are subject to acceptable deviations due to instrument testing accuracy or operational precision.

[0106] In the following examples, the DKD rat model was constructed by feeding the rats with Purina #5008 high-fat diet (protein 23.6%, fat 6.9%, crude fiber 3.3%).

[0107] Rat model of drug administration: The low (L), medium (M), and high (H) dose groups of Yishen Huashi Granules were given 54 mg / kg, 108 mg / kg, and 216 mg / kg (converted from 90, 180, and 360 mg / mL stock solutions at 0.6 mL / 100g body weight) of Yishen Huashi Granules solution for 8 weeks.

[0108] Patients receiving medication: Yishen Huashi Granules, three times a day, one sachet each time.

[0109] In the examples described below, the CTACK, HGF, MIP-1α, Prolatin, TIM-1, and IL3 ELISA kits were all purchased from Raybiotech Inc.

[0110] Example 1: DKD Marker Screening Chip

[0111] The GSR-CAA-67 antibody chip (Raybiotech Inc., catalog number GSR-CAA-67) was used to screen for DKD biomarkers.

[0112] The 67 markers are represented by the following chip combinations, see Tables 1 and 2:

[0113] Table 1. Chip combinations of 27 markers

[0114]

[0115] In Table 1, POS1 and POS2 correspond to biotin-labeled BSA protein, NEG corresponds to BSA protein, and the rest correspond to specific antibodies of 27 biomarkers.

[0116] Table 2. Chip combinations of 40 markers

[0117]

[0118] In Table 2, POS1 and POS2 correspond to biotin-labeled BSA proteins, while the rest correspond to specific antibodies against 40 biomarkers.

[0119] Example 2 Screening of DKD biomarkers

[0120] Kidney tissue samples were prepared from 4 normal rats, 3 DKD rat models, 3 low-dose drug-treated rat models (intervention group 1), 3 medium-dose drug-treated rat models (intervention group 2), and 3 high-dose drug-treated rat models (intervention group 3). Sixteen kidney tissue samples were lysed and added to the microarray wells according to the procedure.

[0121] The specific steps are as follows:

[0122] 1. Complete drying of the glass slide chip: Take the glass slide chip out of the box, and after equilibration at room temperature for 20-30 minutes, open the packaging bag, remove the sealing strip, and then place the chip in a vacuum desiccator or dry at room temperature for 1-2 hours.

[0123] 2. Chip operation procedure: Add 50~100µL of sample to each well, and add 50~500ug / mL of tissue lysis buffer after the protein concentration is determined.

[0124] 3. Cleaning: Remove the sample from each well, wash 5 times with washing solution, 5 minutes each time, shake on a shaker at room temperature, 150µL of 1× washing solution per well, and remove the washing solution completely after each wash. Dilute the washing solution with deionized water to 20×.

[0125] 4. Incubation of the antibody mixture: Centrifuge the tube containing the antibody mixture, then add 1.4 mL of sample diluent, mix thoroughly, and centrifuge again quickly. Add 80 µL of detection antibody to each well and incubate on a shaker at room temperature for 2 hours.

[0126] 5. Washing: Remove the detection antibody from each well, wash 5 times with washing buffer for 5 minutes each time on a shaker at room temperature, using 150µL of washing buffer per well, and remove all washing buffer after each wash.

[0127] 6. Incubation of Cy3-Streptavidin: Centrifuge the Cy3-Streptavidin tube, then add 1.4 mL of sample diluent, mix well, and centrifuge again quickly. Add 80 µL of Cy3-Streptavidin to each well, wrap the slide with aluminum foil to protect it from light, and incubate on a shaker at room temperature for 1 hour.

[0128] 7. Cleaning: Remove Cy3-streptavidin from each well, wash 5 times with washing solution, 5 minutes each time, shake on a shaker at room temperature, using 150µL of washing solution per well, and remove the washing solution completely after each wash.

[0129] 8. Fluorescence detection

[0130] 8.1 Remove the slide frame, being careful not to touch the side of the slide with the antibody printed on it.

[0131] 8.2 Place the slide in the slide cleaning tube, add about 30 mL of cleaning solution to completely cover the slide, shake on a shaker at room temperature for 15 minutes, and then discard the cleaning solution.

[0132] 8.3 Remove residual washing solution from the slides. Place the slides in a slide cleaning / drying tube without capping and centrifuge at 1000 rpm for 3 min.

[0133] 8.4 The signal was scanned using a laser scanner such as Axon GenePix, using Cy3 or the green channel (excitation frequency = 532nm).

[0134] 9. Extracting data from the chip and performing data analysis using analysis software.

[0135] Test results are shown Figure 19 The results showed that the six indicators CTACK, HGF, MIP-1α, Prolatin, TIM-1, and IL3 were differentially expressed in normal rats, DKD rat models, low-dose drug-treated rat models, medium-dose drug-treated rat models, and high-dose drug-treated rat models.

[0136] The scan results of GSR-CYT3 and GSR-CYT4 are shown in the figure below. Figure 1As shown, 27 and 40 protein signals collected by GSR-CYT3 and GSR-CYT4 chips, respectively, were normalized, and the results are shown in Tables 3 and 4, respectively. Based on the normalized data, the protein expression levels of the normal rat group and the model group were analyzed differentially, and the results are shown in Table 5. Here, AveExp (diabetic nephropathy) represents the average expression level of the protein in all samples of the diabetic nephropathy group, usually a standardized value (e.g., intensity value after log2 transformation). AveExp. (normal) represents the average expression level of the protein in all samples of the normal control group. logFC (logarithmic fold change) indicates that logFC > 0: upregulated / high expression in the diabetic nephropathy group, and logFC < 0: downregulated / low expression in the diabetic nephropathy group. logFC is usually based on log2; logFC = 1 indicates a doubling of expression, and logFC = -1 indicates a halving of expression. foldchange represents the fold change, which is a linear value of logFC; foldchange > 1: upregulated; foldchange < 1: downregulated. For example, foldchange = 2.5 indicates that the expression level of this protein in the diabetic nephropathy group is 2.5 times that in the normal group. P.Value represents the P-value. adj.P.Val represents the corrected P-value. Due to multiple hypothesis testing (testing thousands of proteins), the false positive rate may be high. This column shows the P-value after multiple testing correction. Generally, adj.P.Val < 0.05 or < 0.01 is used as the gold standard for judging whether the differential expression is significant. Regulation represents a textual description of the direction of change in protein expression based on logFC and significance threshold: up or UP: significant upregulation; down or DOWN: significant downregulation; stable or -: no significant change. entrezID represents the unique number of the gene corresponding to this protein in the Entrez Gene database, used for gene function annotation and enrichment analysis. uniprotID represents the unique number of this protein in the UniProt database. model_1, model_2, and model_3 represent the raw expression data of three biological replicates in the diabetic nephropathy model group. con_1, con_2, and con_3 represent the raw expression levels of three biological replicates from the normal control group. sham represents the expression levels of the sham-operated group or another control group. In some animal experimental designs, a sham-operated group is included in addition to the normal control (con) to exclude the influence of the surgical procedure itself.

[0137] According to the data in Table 5, there are significant differences in the expression of nine proteins: MIP-1α, IL-1b, CTACK, HGF, Prolactin, IL-4, IL-3, TIM-1, and TNFα.

[0138] To comprehensively assess the ability of these differentially expressed proteins to distinguish between different experimental groups, PCA (principal component analysis) was performed on these differentially expressed proteins. The results are as follows: Figures 2-5 As shown, the differential proteins in each group have a good distinguishing effect, which also indicates that differential proteins can distinguish various treatments to a certain extent.

[0139] Table 3. Results after normalization of 27 protein signals

[0140]

[0141] Table 4. Results after normalization of 40 protein signals

[0142]

[0143] Table 5. Differentially expressed proteins in the normal control group and the model group.

[0144]

[0145] GO and KEGG analysis

[0146] GO and KEGG enrichment analyses were performed on the above targets using R. A p-value < 0.05 was set as the threshold for significant enrichment. GO analysis included three sub-items: biological process, cell component, and molecular function.

[0147] We used R language to perform KEGG pathway annotation on the above targets to further clarify the main signal transduction and metabolic pathways in which these proteins are involved.

[0148] like Figure 6-7 As shown, the greener the color, the more significant the result; the larger the bubbles, the more proteins involved in this function (KEGG & GO agree). Figure 8 As shown, KEGG enrichment analysis revealed significant differences in PI3K-AKT, JAK-STAT, IL17, and Toll-like receptor pathways.

[0149] The protein expression levels in the kidney tissues of the intervention group 3 and the model group were analyzed differentially, and the results are shown in Table 6.

[0150] Table 6. Intervention 3 vs. Model Group: Differentially Expressed Proteins

[0151]

[0152] Proteomics results

[0153] Cluster analysis was performed on the differentially expressed proteins in intervention 3 and the model group, and cluster heatmaps were used to observe the upregulation and downregulation of different proteins when compared between different groups.

[0154] like Figure 9-11 As shown, in the volcano plot, the differentially expressed proteins in the intervention 3 vs. model group showed no obvious skewness, and the distribution of up- and down-regulated differentially expressed proteins was relatively balanced. The differentially expressed proteins that met the threshold (TRUE marker) mainly showed an up-regulated trend. The clustering heatmap visually presented the expression patterns of different proteins in each group. The differential expression of each protein between the intervention 3 and model groups could be observed through the color gradient (red for up-regulation and blue for down-regulation). The scatter plot further verified that among the differentially expressed proteins between the intervention 3 and model groups, up-regulated proteins were the main category of differentially expressed proteins.

[0155] KEGG enrichment analysis results are as follows: Figure 12 As shown, this group of differentially expressed proteins did not exhibit any significant pathways.

[0156] Furthermore, a differential analysis of protein expression levels between intervention group 3 and intervention group 1 was performed, and the results are shown in Table 7.

[0157] Table 7. Intervention 3 vs. Intervention 1: Differentially expressed proteins

[0158]

[0159] Cluster analysis was performed on the differentially expressed proteins between intervention 3 and intervention 1, and cluster heatmaps were used to observe the upregulation and downregulation of different proteins when compared between different groups.

[0160] like Figure 13-15 As shown, intervention 3 vs intervention 1: differentially expressed proteins (volcano plot shows a certain degree of skewness, the main differentially expressed proteins are those in the drug 3 model, all of which are upregulated proteins).

[0161] like Figure 16 As shown in the KEGG enrichment analysis results, there are significant differences between the TNF and IL17 pathways.

[0162] PCA analysis was performed on all grouped samples, and the results are as follows: Figure 17 As shown in the diagram, when all samples are evaluated together, the intervention group 3 is distinguished from the other groups, while the model group and the other two groups are not as clearly distinguished, as shown in the cluster heatmap. Figure 18 Similarly, it can be seen that the levels of each protein in each sample of the three intervention groups are high (high expression level in red).

[0163] like Figure 19As shown, the trends of nine proteins with differences between the Con group and the Model group (assuming that the differentially expressed proteins are unilaterally influenced by the modeling results, and selected accordingly) were compared. Among them, two proteins showed differences after drug administration and were common differences selected from both the model and normal groups. CTACK, HGF, MIP-1α, Prolatin, and TIM-1 showed drug dose effects (returning to the normal group trend). Prolactin was a common differentially expressed protein between the model and control groups, and between the model and drug dose 2. MIP-1α was a common differentially expressed protein between the model and control groups, and between the model and drug dose 3.

[0164] Example 3: ELISA Validation of DKD Biomarkers

[0165] Forty-seven individuals were given blood samples (serum plus plasma) and divided into three groups: a healthy control group (HC Serum), a non-medicated group (Frist Serum), a group receiving medication for 6 months (Last Serum), and another group (Other Frist Serum). These samples were used for ELISA biomarker validation. The CTACK ELISA Kit (Raybiotech Inc.) was used. The specific operating steps are as follows:

[0166] 1. Kit Components

[0167] CTACK Microplate (Item A): A 96-well plate coated with anti-Human CTACK antibody;

[0168] Wash Buffer Concentrate (20×) (Item B): 25 mL of 20× concentrated wash buffer;

[0169] Standards Protein (Item C): Recombinant Human CTACK Standard;

[0170] Assay Diluent C: 30 mL diluent;

[0171] Assay Diluent B (Item E): 15 mL, 5× concentrated diluent;

[0172] Detection Antibody CTACK (Item F): Biotin-labeled anti-CTACK antibody;

[0173] HRP-Streptavidin concentrate (Item G): 200 µL 400× concentrated HRP-Streptavidin;

[0174] TMB One-Step Substrate Reagent (Item H): 12 mL of 3,3',5,5'-tetramethylbenzidine (TMB);

[0175] Stop Solution (Item I): 8 mL of 0.2 M sulfuric acid.

[0176] 2. Reagent Preparation

[0177] 1) Equilibrate the kit and samples to room temperature (18-25℃);

[0178] 2) Dilute the sample 2 times before loading;

[0179] 3) Dilute Assay Diluent B (Item E) 5 times with deionized water before use;

[0180] 4) Preparation of standard: Centrifuge the Item C tube, then add 400µL of Assay Diluent C to the standard tube and mix well to obtain a 100 ng / mL standard stock solution. Prepare eight 1.5 mL centrifuge tubes. Add 450 µL of Assay Diluent C buffer to the first tube, then add 50 µL of 100 ng / mL standard stock solution to the first tube. Mix well to obtain a concentration of 10000 pg / mL, and label this as STD1. Add 400 µL of Assay Diluent C buffer to the remaining seven tubes, and label them STD2, STD3, STD4, STD5, STD6, ​​STD7, and STD8 respectively. Then, serially dilute the standard with 10000 pg / mL STD1. Add 200 µL of the 10000 pg / mL standard solution (i.e., STD1) to the STD2 tube, mix well, and then add 200 µL of the solution from the STD2 tube to the STD3 tube. Repeat this process until STD7 is prepared. STD8 is simply 400 µL of Assay Diluent C, i.e., 0 pg / mL standard. Figure 20 As shown;

[0181] 5) Washing solution dilution: Dilute the concentrated washing solution 20 times with deionized water for later use;

[0182] 6) Centrifuge the antibody detection tube (Item F), add 100µL of 1× Assay Diluent B (Item E) to dissolve it completely, gently pipette up and down, and then dilute it 80 times with 1× Assay Diluent B before use;

[0183] 7) Centrifuge HRP-streptavidin (Item G), then dilute it 500 times with 1×Assay Diluent B before use;

[0184] 3. Operating Steps

[0185] 1) Equilibrate the kit and samples to room temperature (18-25℃); use duplicate wells for both standards and samples.

[0186] 2) After the antibody-coated ELISA plate has been equilibrated to room temperature, add 100 µL of the prepared standard and sample to the corresponding well, seal the entire strip with sealing film, and incubate overnight at 4°C.

[0187] 3) Add the prepared 1× washing solution to the plate washer and wash the plate strips 4 times with the plate washer, adding 300 µL of washing solution to each well;

[0188] 4) After washing the plate thoroughly, add 100 µL of the prepared detection antibody (biotin-labeled antibody) to each well and incubate at room temperature for 1 hour;

[0189] 5) The cleaning steps are the same as in step 3;

[0190] 6) Add 100 µL of the prepared HRP-streptavidin to each well and incubate at room temperature for 45 min;

[0191] 7) The cleaning steps are the same as in step 3;

[0192] 8) Add 100 µL LTMB colorimetric solution to each well and incubate at room temperature in the dark for 30 min;

[0193] 9) Add 50 µL of stop solution to each well and immediately read the value at 450 nm using a microplate reader.

[0194] Similarly, the operating procedures for the HGF, MIP-1α, Prolatin, TIM-1, and IL3 ELISA kits are the same as those for the CTACK ELISA kit.

[0195] 4. ELISA Results:

[0196] The results of the microarray analysis using kidney tissue were compared with the results of the ELISA analysis using blood samples to demonstrate the expression levels of different protein factors in multiple groups. The protein factors detected included: CTACK (skin-guided T-cell attraction chemokine); MIP1A (macrophage inflammatory protein 1A); HGF (hepatocyte growth factor); IL-3 (interleukin-3); and Prolactin (prolactin).

[0197] Experimental Groups:

[0198] 1. HC (normal group);

[0199] 2. First (untreated patients);

[0200] 3. Last (patients receiving medication). Results are as follows: Figures 21-24 As shown, the results of the microarray analysis using kidney tissue are as follows ( Figure 24 A) and ELISA results verified using blood samples ( Figure 24 As can be seen from the comparison chart in B), the trends of CTACK serum validation results are consistent with those of the chip, the trends of HGF plasma validation results are consistent with those of the chip, and the trends of MIP-1α serum and plasma validation results are consistent with those of the chip.

[0201] Therefore, CTACK, HGF, and MIP-1α can be used as alternative indicators for the chip.

[0202] Example 4: Composition of the reagent kit

[0203] 1. Solid-phase support: The reaction chamber is formed by a glass slide, a soft silicone pad, a rigid frame, and a U-shaped frame clamp. The rigid frame is divided into 2×8 wells, forming a 16-well frame. The size of the soft silicone pad corresponds to the rigid frame and the standard glass slide. Each small compartment of the rigid frame forms a small reaction chamber, and the standard glass slide in each small reaction chamber is bound with specific antibodies at corresponding concentrations for CTACK, HGF, and MIP-1α indicators.

[0204] 2. Washing solution: 20× concentrated washing solution containing Tween 20. 1× washing solution is pH 7.2, containing 0.1% Tween 20 and 0.1 mol / L phosphate buffer.

[0205] 3. Diluents: 2 bottles of 15mL 5× concentrated diluent D for diluting samples, and 1 bottle of 15mL 5× concentrated diluent B for diluting antibodies and HRP-streptavidin.

[0206] 1× Diluent B is a 15 mM, pH 7.4 PBS buffer. The solute and its mass, molar, or volume concentration in Diluent B are as follows: 0.5% casein, 2-4% sucrose, 150 mM NaCl. 1× Diluent D is a 15 mM, pH 6.5 PBS buffer. The solute and its mass, molar, or volume concentration in the sample diluent are as follows: 2-4% sucrose, 150 mM NaCl.

[0207] 4. Detection antibodies: A mixture of biotinylated detection antibodies targeting CTACK, HGF, and MIP-1α indicators.

[0208] 5. 200µl of 300× concentrated fluorescein-streptavidin solution.

[0209] 6. Sample processing solution: 2×10mL of cell lysis buffer.

[0210] 7. Standards: Antigen mixtures targeting CTACK, HGF, and MIP-1α indicators.

[0211] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0212] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims, and the specification and drawings can be used to interpret the content of the claims.

Claims

1. An antibody chip for detecting a combination of biomarkers for diabetic kidney disease, characterized in that, The invention includes a solid-phase carrier and a capture antibody coated on the surface of the solid-phase carrier, the capture antibody being capable of specifically binding to a combination of biomarkers for diabetic kidney disease, the biomarker combination including CTACK, HGF, and MIP-1α.

2. The antibody chip for detecting a combination of biomarkers for diabetic nephropathy as described in claim 1, characterized in that, The biomarker combination also includes Prolatin, TIM-1, and IL3.

3. The antibody chip for detecting a combination of biomarkers for diabetic nephropathy as described in claim 1 or 2, characterized in that, It meets one or more of the following characteristics: The capture antibodies for each marker in the marker combination are separately placed in different reaction tanks; The solid support includes a glass slide; Optionally, the solid support further includes one or more of a soft silicone pad, a rigid frame, and a U-shaped frame clamp, wherein the soft silicone pad and the rigid frame are combined with the glass slide to form multiple independent reaction tanks.

4. An antibody chip kit for detecting a combination of biomarkers for diabetic kidney disease, characterized in that, Includes the antibody chip according to any one of claims 1 to 3; Optionally, it may also include one or more of the following: washing solution or its concentrate, diluent or its concentrate, horseradish peroxidase-streptavidin solution, fluorescein-streptavidin solution or its concentrate, detection antibody, sample processing solution, and standards.

5. The antibody chip kit for detecting a combination of biomarkers for diabetic nephropathy as described in claim 4, characterized in that, The washing solution comprises 0.1% (w / v) to 0.2% (w / v) of Tween-20 and 0.1 to 0.2 mol / L of phosphate buffer; Optionally, the pH of the phosphate buffer solution is 7.1 to 7.

3.

6. The antibody chip kit for detecting a combination of biomarkers for diabetic nephropathy as described in claim 4, characterized in that, The diluent includes diluent B and diluent D; Optionally, the diluent B comprises 14 mM to 16 mM PBS buffer, 0.4% (w / v) to 0.6% (w / v) casein, 2% (w / v) to 4% (w / v) sucrose, and 140 mM to 160 mM sodium chloride, wherein the pH of the PBS buffer is 7.3 to 7.5; Optionally, the diluent D comprises 14 mM to 16 mM PBS buffer, 2% (w / v) to 4% (w / v) sucrose and 140 mM to 160 mM sodium chloride, wherein the pH of the PBS buffer is 6.4 to 6.

6.

7. The antibody chip kit for detecting a combination of biomarkers for diabetic nephropathy as described in claim 4, characterized in that, The sample processing solution is a cell lysis buffer or its concentrate; Optionally, the cell lysis buffer includes HEPES buffer and a protease inhibitor.

8. The antibody chip kit for detecting a combination of biomarkers for diabetic nephropathy as described in any one of claims 4 to 7, characterized in that, It also meets one or more of the following conditions: The detection antibody is a biotinylated specific antibody against a combination of biomarkers for diabetic kidney disease, the combination of biomarkers including CTACK, HGF and MIP-1α, and optionally, the combination of biomarkers also including Prolatin, TIM-1 and IL3; The standard is a mixture of biomarkers for diabetic kidney disease.

9. The use of the antibody chip as described in claim 1 or 2, or the antibody chip kit as described in any one of claims 3 to 8, in detecting a combination of biomarkers for diabetic nephropathy or in assisting in the assessment of renal prognosis in diabetic patients or in assisting in the detection of diabetic nephropathy, wherein the biomarker combination includes CTACK, HGF, and MIP-1α. In the auxiliary assessment of renal prognosis in diabetic patients, the diabetic patients were given Yishen Huashi Granules. The application is not for disease detection purposes; Optionally, the combination of markers may also include Prolatin, TIM-1, and IL3.

10. A biomarker combination for detecting diabetic kidney disease, characterized in that, The combination of markers includes CTACK, HGF, and MIP-1α; Optionally, it also includes Prolatin, TIM-1, and IL3.

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