CN113552369B - Use of protein markers in combination for diagnosis of type 2 diabetes mellitus, type 2 diabetic nephropathy - Google Patents
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Abstract
The invention discloses an application of a protein marker combination in diagnosis of type 2 diabetes and type 2 diabetic nephropathy, wherein the protein markers are cathepsin D, alpha 2-Macroglobulin and CD324. The protein marker can be used for diagnosing and distinguishing healthy people from type 2 diabetes patients, diagnosing and distinguishing healthy people from type 2 diabetes nephropathy patients, diagnosing and distinguishing type 2 diabetes patients from type 2 diabetes nephropathy end stage patients, diagnosing and distinguishing type 2 diabetes nephropathy early stage patients from type 2 diabetes nephropathy end stage patients, has high diagnosis efficiency, and has the prospect of being developed into a kit for diagnosing type 2 diabetes and type 2 diabetes nephropathy.
Description
Technical Field
The invention belongs to the field of disease detection and diagnosis, relates to discovery and application of disease diagnosis markers, and in particular relates to application of protein markers in diagnosis of type 2 diabetes and type 2 diabetic nephropathy.
Background
Diabetic kidney disease (Diabetic kidney disease, DKD) refers to chronic kidney disease (Chronic kidney disease, CKD) caused by diabetes, DKD is a common chronic complication of diabetes and is an important cause of End-stage renal disease (End-stage renal disease, ESRD). CKD stage 1-2 has few symptoms and is usually not found until late stages. As CKD progresses, the risk of cardiovascular morbidity and mortality increases.
DKD is a clinical diagnosis made based on elevated urinary albumin and/or estimated decrease in glomerular filtration rate while excluding other CKD. Microalbuminuria (microalbuminuria/urinary creatinine 30-300 mg/g) is recognized as an early clinical marker for type 1 and type 2 diabetic nephropathy. However, when patients develop microalbuminuria, CKD3 has been entered. Thus, the diagnostic methods currently used have considerable limitations both in early DKD and in diagnosis of its proteinuria progression.
The invention is provided for searching more DKD early markers to evaluate kidney functions so as to improve the accuracy of DKD diagnosis, delay the progress of kidney functions and improve the survival rate and life quality of patients.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides the application of the protein marker combination in diagnosis of type 2 diabetes and type 2 diabetic nephropathy.
The above object of the present invention is achieved by the following technical scheme:
use of a combination of protein markers for the preparation of a kit for diagnosing type 2 diabetes mellitus, type 2 diabetic nephropathy; wherein the protein markers are Cathepsin D, alpha 2-Macroglobulin and CD324; the diagnosis of type 2 diabetes and type 2 diabetic nephropathy includes diagnosis of healthy people and type 2 diabetes patients, diagnosis of healthy people and type 2 diabetic nephropathy patients (including early stage and late stage), diagnosis of type 2 diabetes patients and type 2 diabetic nephropathy end stage patients, and diagnosis of type 2 diabetic nephropathy early stage patients and type 2 diabetic nephropathy end stage patients.
A kit for diagnosing type 2 diabetes and type 2 diabetic nephropathy, which contains detection reagents for detecting cathepsin D, alpha 2-Macroglobulin and CD324 proteins; wherein the protein markers are Cathepsin D, alpha 2-Macroglobulin and CD324; the diagnosis of type 2 diabetes and type 2 diabetic nephropathy includes diagnosis of healthy people and type 2 diabetes patients, diagnosis of healthy people and type 2 diabetic nephropathy patients (including early stage and late stage), diagnosis of type 2 diabetes patients and type 2 diabetic nephropathy end stage patients, and diagnosis of type 2 diabetic nephropathy early stage patients and type 2 diabetic nephropathy end stage patients.
Performing ROC analysis on three protein diagnosis rates by adopting four machine learning algorithms, namely Linear Discriminant Analysis (LDA), support Vector Machine (SVM), random Forest (RF) and Logistic regression (Logi), wherein the area under the ROC curve of the three protein combined diagnosis and differentiation healthy subjects and type 2 diabetes patients is up to 0.98-0.99 in AUC, and the accuracy is 0.88-0.93; the area under the ROC curve of the healthy subjects and the early-stage patients with type 2 diabetic nephropathy is diagnosed and distinguished in a combined way, the AUC is as high as 0.85-0.89, and the accuracy is 0.75-0.89; the area under the ROC curve of the healthy subjects and the end-stage patients of the type 2 diabetic nephropathy is distinguished by combined diagnosis, the AUC is as high as 0.92-0.98, and the accuracy is 0.93; the area under the ROC curve of the combined diagnosis and distinction type 2 diabetes patients and type 2 diabetic nephropathy patients reaches 0.86-0.90 AUC, and the accuracy is 0.77-0.82; the area under ROC curve of the early stage patient and the late stage patient of the type 2 diabetic nephropathy is distinguished by combined diagnosis, the AUC is as high as 0.83-0.87, and the accuracy is 0.77-0.84. Therefore, the three proteins have extremely high diagnostic value in the aspect of diagnosing type 2 diabetes and type 2 diabetic nephropathy, have high diagnostic accuracy, are easier to operate than the existing diagnostic standard, and can be used for preparing diagnostic kits for diagnosing type 2 diabetes and type 2 diabetic nephropathy.
The beneficial effects are that:
the invention discovers that the protein Cathepsin D, alpha 2-Macroglobulin and CD324 can be used for diagnosing and distinguishing healthy people from type 2 diabetes patients, diagnosing and distinguishing healthy people from type 2 diabetes nephropathy patients (including early stage and late stage), diagnosing and distinguishing type 2 diabetes patients from type 2 diabetes nephropathy end stage patients and diagnosing and distinguishing type 2 diabetes nephropathy early stage patients from type 2 diabetes nephropathy end stage patients, has high diagnosis efficiency, and has the prospect of developing a kit for diagnosing type 2 diabetes and type 2 diabetes nephropathy.
Drawings
FIG. 1 shows the expression levels of three proteins of alpha 2-Macroglobulin, cathepsin D and CD324 in healthy subjects, type 2 diabetic patients, early stage patients and late stage patients of type 2 diabetic nephropathy;
FIG. 2 is a ROC curve of a 2-Macroglobulin, cathepsin D, CD324 protein combined diagnosis to distinguish healthy subjects, type 2 diabetics, early stage diabetic nephropathy patients and late stage diabetic nephropathy patients.
Detailed Description
The following describes the essential aspects of the invention in detail with reference to the drawings and examples, but is not intended to limit the scope of the invention.
Example 1: diagnostic efficacy of alpha 2-Macroglobulin, cathepsin D, CD324 protein in combination diagnosis of healthy subjects, type 2 diabetics, early stage patients with type 2 diabetic nephropathy and late stage patients with type 2 diabetic nephropathy
1. Experimental sample and reagent
Sample: 30 healthy subjects (HC), 30 pure type 2 diabetics (2-DM), 30 early-stage patients (DKD-E) and 30 late-stage patients (DKD-A) of type 2 diabetic nephropathy are collected and detected, and the age, sex and body mass index matching of each group of patients are not significantly different;
the group entering standard of healthy subjects for healthy people with normal physical examination indexes, type 2 diabetes patients, early-stage patients of type 2 diabetic nephropathy and late-stage patients of type 2 diabetic nephropathy is as follows:
type 2 diabetic: according to the American Diabetes Association (ADA) published "2015 American diabetes guide", blood glucose on empty stomach is >7.0mmol/L after at least 8h, blood glucose is >11.1mmol/L after 75g glucose is orally taken for 2h in the early morning; has hyperglycemia symptoms (such as diuresis, polydipsia, polyphagia), and random blood glucose >11.1mmol/L.
Early stage diabetic nephropathy patient type 2: besides the characteristics of type 2 diabetes mellitus, the urine albumin excretion rate (UAE) is continuously increased by 20-200 mug/min, or the urine albumin is 30-300 mg/24h, the urine creatinine is 30-300 mug/mg, and the UACR is more than 30-300 mg/g; the pathology is characterized by thickening basal lamina, obvious proliferation of mesangial stroma, and can appear glomerular nodular lesions, diffuse lesions and arteriolar glass-like lesions.
Type 2 diabetic nephropathy end stage patients: in addition to having type 2 diabetes characteristics, UAE persists at greater than 200 μg/min, UACR >300mg/g, or urine protein >0.5g/24h, typical changes in pathology occur, most patients develop hypertension, glomerular filtration rate begins to decline gradually, and some patients manifest as nephrotic syndrome.
Exclusion criteria: (1) primary kidney disease with definitive diagnosis; (2) other systemic diseases that can cause proteinuria; (3) acute complications of diabetes and urinary infections occur within approximately 1 month; (4) is combined with serious primary diseases such as cardiovascular and cerebrovascular diseases, liver diseases, kidney diseases, hematopoietic system diseases and the like; (5) unable partner suffering from mental illness; (6) pregnant or lactating women, or those who are ready for gestation; (7) other clinical trials were enrolled in approximately 1 month; (8) is not willing to accept the present investigator.
Case rejection criteria: (1) case selection does not meet inclusion criteria, meets exclusion criteria; (2) before statistical analysis of the data, statistics staff and main researchers discuss and judge whether the cases are rejected.
Main experimental reagent: TMT labeling kits are purchased from Thermo corporation.
2. Experimental method
1. Serum sample collection and storage
Collecting early morning fasting peripheral blood of a patient, placing the early morning fasting peripheral blood in a test tube without an anticoagulant, naturally coagulating for 30-60min at room temperature, centrifuging at 2000rpm for 10min, carefully sucking the supernatant clear serum liquid in a sterile freeze-drying tube, marking, and storing in a refrigerator at-80 ℃ for later use.
2. Determination of the relative content of target proteins in serum by TMT
Detection instrument: an HPLC liquid phase system Easy nLc with nano-liter flow rate, Q-exact mass spectrometer;
chromatographic conditions: each fractionated sample was separated using a nanoliter flow HPLC liquid phase system Easy nLc. Buffer A was 0.1% aqueous formic acid and buffer B was 0.1% aqueous acetonitrile (84% acetonitrile). The chromatographic column was equilibrated with 95% solution A and samples were loaded from an autosampler to a loading column (Thermo Scientific Acclaim pep map100,100 μm 2cm,nanoViper C18), separated by an analytical column (Thermo scientificEASY column,10cm, ID75 μm,3 μm, C18-A2) at a flow rate of 300nL/min;
mass spectrometry conditions: the sample was chromatographed and then mass analyzed using a Q-exact mass spectrometer. The detection mode is positive ions, the scanning range of parent ions is 300-1800m/z, the primary mass spectrum resolution is 70,000at 200m/z, the AGC (Automatic gain control) target is 1e6, the maximum IT is 50ms, and the dynamic exclusion time (Dynamic exclusion) is 60.0s. The mass-to-charge ratio of the polypeptide and the polypeptide fragments is obtained by collecting 20 fragment patterns (MS 2 scan) after each full scan (full scan), wherein MS2 Activation Type is HCD, isolation window is 2m/z, secondary mass spectrum resolution is 17,500at 200m/z (TMT 6-plex) or 35,000at 200m/z (TMT 10-plex), normalized Collision Energy is 30ev, and Underfill is 0.1%;
sample processing: the samples were subjected to protein extraction by SDT (4% (w/v) SDS,100mM Tris/HCI pH7.6,0.1M DTT) lysis and protein quantification by BCA. Each sample was subjected to trypsin enzymatic hydrolysis using Filter aided proteome preparation (FASP) and peptide fragment quantification (OD 280) using the appropriate amount of protein. Each sample was labeled with 100. Mu.g of the peptide fragment according to the instructions of the TMT labeling kit from Thermo company.
3. Enzyme-linked immunosorbent assay (ELISA) for verifying target protein
The detection adopts a quantitative sandwich enzyme-linked immunoassay technology. Monoclonal antibodies directed against the human proteins described above were pre-coated onto microwell plates. The standard and sample are delivered to the wells and the proteins in the sample are bound to the wells by immobilized antibodies. After washing away free material, an enzyme-linked polyclonal antibody against the human protein is added to the well. After washing to remove unbound antibody-enzyme reagent, a substrate solution is added to the wells, the color being proportional to the total level of bound protein in the initial step. The color development was stopped and the intensity of the color was measured. The expression unit of the protein is nanograms per milliliter.
4. Data processing method
30 serum samples from each group (HC, 2-DM, DKD-E and DKD-A) were equally distributed to 3 serum pools and proteomic data from 12 libraries were collected. After filtering out the N/A values, the expression profile of 581 proteins was finally used for analysis. For all pairwise comparisons between the four groups, a t-test of two samples was performed for each protein. The differentially expressed proteins were defined with absolute log2 (fold change) 0.3 or more and p-value 0.05 or less. All differentially expressed proteins were pooled together and systematically clustered into four classes.
ELISA was performed on 88 kidney patients in 90 samples, wherein HC 23, DM 23, DKD-E20 and DKD-A22. A total of 8 proteins were measured and multifactorial analysis was performed using partial least squares discriminant analysis (PLS-DA). Finally, predictive analysis was performed with 3 protein markers (. Alpha.2-Macroglobulin, cathepsin D, CD 324). For all pairing comparisons, four machine learning algorithms LDA, SVM, RF and Logi are adopted to perform ROC curve analysis and calculate prediction accuracy.
3. Experimental results
1. ELISA detection of the difference in the serum levels of target proteins in healthy subjects, type 2 diabetic patients, early stage patients with type 2 diabetic nephropathy and late stage patients with type 2 diabetic nephropathy
The levels of α2-Macroglobulin, cathepsin D, CD324 in serum were progressively up-regulated in type 2 diabetics, early stage diabetic nephropathy patients and late stage diabetic nephropathy patients compared to healthy subjects (as shown in figure 1).
3. ELISA detection of three proteins Joint diagnosis ROC curves for distinguishing healthy subjects, type 2 diabetes patients, early stage patients with type 2 diabetes kidney disease and late stage patients with type 2 diabetes kidney disease (as shown in FIG. 2)
3.1, three proteins combine to differentiate between VS type 2 diabetics in healthy subjects: ROC analysis is carried out on three protein diagnosis rates by adopting four machine learning algorithms of LDA, SVM, RF and Logi, the area under the ROC curve of the healthy subjects and the type 2 diabetes mellitus patients is distinguished by the three protein diagnosis, the AUC is 0.98-0.99, and the accuracy is 0.88-0.93.
3.2 three proteins in combination to differentiate early stage patients of VS type 2 diabetic nephropathy in healthy subjects
ROC analysis is carried out on three protein diagnosis rates by adopting four machine learning algorithms of LDA, SVM, RF and Logi, the area under the ROC curve AUC of the healthy subjects and the early-stage patients with type 2 diabetic nephropathy is 0.85-0.89, and the accuracy is 0.75-0.89.
3.3 three proteins in combination to differentiate healthy subjects from end stage patients with VS type 2 diabetic nephropathy
ROC analysis is carried out on three protein diagnosis rates by adopting four machine learning algorithms of LDA, SVM, RF and Logi, and the area under the ROC curve AUC of the healthy subjects and the patients with advanced stage 2 diabetic nephropathy is 0.92-0.98, and the accuracy is 0.93.
3.4 three proteins combine to distinguish between type 2 diabetic patients and advanced stage VS type 2 diabetic nephropathy
ROC analysis is carried out on three protein diagnosis rates by adopting four machine learning algorithms of LDA, SVM, RF and Logi, the area under the ROC curve AUC of the three protein diagnosis patients with type 2 diabetes mellitus and the type 2 diabetic nephropathy is 0.86-0.90, and the accuracy is 0.77-0.82.
3.5 three proteins in combination to distinguish between early stage patients with type 2 diabetic nephropathy and late stage patients with type 2 VS diabetic nephropathy
And performing ROC analysis on three protein diagnosis rates by adopting four machine learning algorithms of LDA, SVM, RF and Logi, wherein the area under the ROC curve AUC of the early stage patient with type 2 diabetic nephropathy and the late stage patient with type 2 diabetic nephropathy is 0.83-0.87, and the accuracy is 0.77-0.84.
Therefore, cathepsin D, alpha 2-Macroglobulin and CD324 proteins can be used for diagnosing and distinguishing healthy people from type 2 diabetic patients, diagnosing and distinguishing healthy people from type 2 diabetic nephropathy patients (including early stage and late stage), diagnosing and distinguishing type 2 diabetic nephropathy patients from type 2 diabetic nephropathy end stage patients and diagnosing and distinguishing type 2 diabetic nephropathy early stage patients from type 2 diabetic nephropathy end stage patients, and the kit has high diagnosis efficiency and has the prospect of being developed into a kit for diagnosing type 2 diabetes and type 2 diabetic nephropathy.
Example 2: diagnostic kit
A kit for diagnosing type 2 diabetes and type 2 diabetic nephropathy, which contains detection reagents for detecting Cathepsin D, alpha 2-Macroglobulin and CD324 proteins; wherein the protein markers are Cathepsin D, alpha 2-Macroglobulin and CD324; the diagnosis of type 2 diabetes and type 2 diabetic nephropathy includes diagnosis of healthy people and type 2 diabetes patients, diagnosis of healthy people and type 2 diabetic nephropathy patients, diagnosis of type 2 diabetes patients and type 2 diabetic nephropathy end stage patients, and diagnosis of type 2 diabetic nephropathy early stage patients and type 2 diabetic nephropathy end stage patients.
The above-described embodiments serve to describe the substance of the present invention in detail, but those skilled in the art should understand that the scope of the present invention should not be limited to this specific embodiment.
Claims (4)
1. Use of a combination of protein markers for the preparation of a kit for diagnosing and distinguishing healthy people from type 2 diabetics; wherein the protein markers are Cathepsin D, alpha 2-Macroglobulin and CD324.
2. Use of a combination of protein markers for the preparation of a kit for diagnosing and distinguishing healthy persons from patients with type 2 diabetic nephropathy; wherein the protein markers are Cathepsin D, alpha 2-Macroglobulin and CD324.
3. Use of a combination of protein markers for the preparation of a kit for diagnosing and distinguishing between type 2 diabetic patients and type 2 diabetic nephropathy end-stage patients; wherein the protein markers are Cathepsin D, alpha 2-Macroglobulin and CD324.
4. The use of a protein marker combination for preparing a kit for diagnosing and distinguishing early stage patients of type 2 diabetic nephropathy from late stage patients of type 2 diabetic nephropathy; wherein the protein markers are Cathepsin D, alpha 2-Macroglobulin and CD324.
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