CN114509573B - Diabetes kidney disease early warning model established based on synchronous detection of urine markers - Google Patents
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Abstract
The invention provides a diabetic kidney disease early warning model established by synchronously detecting urine markers based on a urine suspension chip, and the diabetic kidney disease early warning model is established by four urine biomarkers of vitamin D binding protein, human tumor necrosis factor receptor 2, retinol binding protein 4 and kidney injury molecule 1, wherein Y =0.14 multiplied by VDBP + TNFR2+0.01 multiplied by RBP4+15.47 multiplied by KIM-1-19.24. The invention creates the diabetic kidney disease early warning model established based on synchronous detection of urine markers, provides a new diagnosis means for early warning of DKD, and has certain potential clinical value in delaying DKD development and assisting DKD treatment. Clinical trials prove that the method for synchronously and jointly detecting VDBP, TNFR2, RBP4 and KIM-1 in 11 urine biological markers has higher specificity and sensitivity to the early diagnosis of DKD, the diagnostic value of the kit is superior to any other single index, and the kit has an application prospect in developing chips for early diagnosis of DKD.
Description
Technical Field
The invention belongs to the technical field of biological medicines, and particularly relates to a diabetic kidney disease early warning model established based on synchronous detection of urine markers.
Background
Diabetic nephropathy (DKD) is Chronic Kidney Disease (CKD) caused by Diabetes Mellitus (DM), manifested by persistent proteinuria and/or a predicted decrease in glomerular filtration rate (eGFR), which eventually progresses to End-stage renal disease (ESRD). DKD occurs in diabetic patients at rates as high as 40% and can lead to renal failure, cardiovascular disease and premature death. DKD has become the leading cause of CKD and ESRD in our country, its prevalence is high, the prognosis is poor, bring enormous burden for people's health and social economy in our country, therefore early diagnosis is vital. Microalbuminuria (MAU) was the earliest basis for clinical diagnosis of DKD and is also a biomarker of glomerular filtration membrane damage, the appearance of which often suggests that kidney architecture has been altered to varying degrees. With the progress of research, it was found that MAU lacks sensitivity and specificity as a marker for early diagnosis of DKD. Tubular injury already occurs before MAU occurs. Therefore, renal tubular injury is a major contributor to DKD progression. The abnormality of the tubular markers can reflect the severity of tubular injury of diabetic patients, so that a reliable and non-invasive novel biomarker in the earlier stage of diabetic nephropathy is highly required to be further searched.
The liquid phase chip is a new generation high flux molecular detection technology platform following gene chip and protein chip. The liquid phase suspension chip detection technology has the characteristics of high flux, high sensitivity, high specificity and the like, takes the polystyrene microsphere as a reaction interface, utilizes the specific monoclonal antibody of the screened urine biological index to carry out coating, and detects the level of the biomarker in the urine of a patient through the amplification effect of the detection microsphere so as to evaluate the risk of the early diabetic kidney disease of the patient. The liquid phase suspension chip is applied to the detection of specific biomarkers in diabetic patients, so that the early warning of diabetic nephropathy can be realized, the clinical multi-index combined detection steps are simplified, and the popularization is easy.
Disclosure of Invention
In view of the above, the invention provides an early warning model for diabetic nephropathy, which is established based on synchronous detection of urine markers, and provides application of novel urine biomarkers in early warning of diabetic nephropathy.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a urine biomarker for diagnosing diabetic nephropathy is one or more of vitamin D binding protein, human tumor necrosis factor receptor 2, retinol binding protein 4 and kidney injury molecule 1.
The markers are vitamin D binding protein, human tumor necrosis factor receptor 2, retinol binding protein 4 and kidney injury molecule 1.
A diabetic kidney disease early warning model established based on synchronous detection, a diabetic kidney disease prediction model established by four urine biomarkers of vitamin D binding protein, human tumor necrosis factor receptor 2, retinol binding protein 4 and kidney injury molecule 1,
Y=0.14×VDBP +TNFR2 +0.01×RBP4 +15.47×KIM-1－19.24；
y is the tangent value of the model;
VDBP is vitamin D binding protein, and the unit is ng/mL;
TNFR2 is the concentration of human tumor necrosis factor receptor 2 in ng/mL;
RBP4 is the concentration of retinol binding protein 4 in ng/mL;
KIM-1 is the concentration of kidney injury molecule 1 in ng/mL.
And (3) performing risk evaluation on early diabetic nephropathy according to the Y value, wherein the curve has diagnostic value as the curve is closer to the upper left corner, and the area under the ROC curve is larger, so that the curve has application value. When Y is more than or equal to 5.12, the patient is a type 2 diabetic nephropathy patient, and when Y is less than 5.12, the patient is a type 2 diabetic patient.
The method for establishing the diabetic kidney disease early warning model based on synchronous detection of urine markers obtains the diabetic kidney disease prediction model established by four urine biomarkers of vitamin D binding protein, human tumor necrosis factor receptor 2, retinol binding protein 4 and kidney injury molecule 1 according to regression analysis results.
The kit is a combination of VDBP, TNFR2, RBP4 and KIM-1 standard products.
The kit is a liquid phase suspension chip.
The application of the kit of the diabetes kidney disease early warning model is applied to diagnosing and distinguishing type 2 diabetes patients and type 2 diabetes kidney patients.
Application of the novel urine biomarker to early warning of diabetic nephropathy. Novel urine biomarkers include Vitamin D Binding Protein (VDBP), human tumor necrosis factor receptor 2 (TNFR 2), retinol binding protein 4 (RBP 4), kidney injury molecule 1 (KIM-1). The Luminex liquid phase suspension chip is used for detecting biomarkers in urine to early warn diabetic nephropathy, the diagnosis chip is a combination of standards comprising VDBP, TNFR2, RBP4 and KIM-1, and the standards are prepared solutions.
The use method of the diagnosis chip comprises the following steps: taking a morning urine sample of a subject, preparing a standard substance, detecting by a chip, and reading by a Luminex 200 machine to quantify the concentration of the urine biomarker of the subject.
Compared with the prior art, the diabetes kidney disease early warning model established based on synchronous detection of urine markers has the following beneficial effects:
the invention creates the diabetic kidney disease early warning model established based on synchronous detection of urine markers, provides a new diagnosis means for early warning of DKD, and has certain potential clinical value in delaying DKD development and assisting DKD treatment. Clinical trials prove that the method for synchronously and jointly detecting VDBP, TNFR2, RBP4 and KIM-1 in 11 urine biological markers has higher specificity and sensitivity to the early diagnosis of DKD, the diagnostic value of the kit is superior to any other single index, and the kit has an application prospect in developing chips for early diagnosis of DKD.
Drawings
FIG. 1 is a ROC plot of urine biomarkers VDBP, TNFR2, RBP4, KIM-1 for early diagnosis of DKD;
FIG. 2 is a ROC plot of urine biomarkers VDBP, TNFR2, RBP4, KIM-1 in combination diagnosis to differentiate diabetic patients from DKD patients. The sensitivity of the combined diagnosis of four urine markers of VDBP, TNFR2, RBP4 and KIM-1 is 0.903, and the AUC is 0.812, which is better than any one or two of the above.
Detailed Description
Unless defined otherwise, technical terms used in the following examples have the same meanings as commonly understood by one of ordinary skill in the art to which the present invention belongs. The test reagents used in the following examples, unless otherwise specified, were all conventional biochemical reagents; the experimental methods are conventional methods unless otherwise specified.
The invention is described in detail below with reference to embodiments and the accompanying drawings.
The method selects patients in outpatients of the department of commemorative hospital of the Zhuxiyi city of Tianjin to carry out case contrast research, the patients are divided into a diabetes group and an early DKD group, and fasting venous blood, clean midcourse urine and 24-hour urine of the patients are reserved to detect biochemical indexes of the blood and the urine; meanwhile, the Luminex liquid phase suspension chip is used for detecting the concentration of the novel urine biomarker, the level difference of each index between two groups is compared, the sensitivity and the specificity of the single and combined urine biomarker on DKD diagnosis are analyzed, and the reference value of the single and combined urine biomarker as DKD early diagnosis is explored.
1. Experimental sample
Collecting outpatient data of the Zhuxiyi commemorative hospital in Tianjin city, and randomly selecting 39 early DKD patients. Based on the early DKD patients, 39 patients with type 2 diabetes (T2 DM) were selected for age, sex, course of diabetes, Body Mass Index (BMI), blood pressure, HbA1c, blood lipids, renal function, and blood uric acid index matching. Recording general data: gender, age, height, weight, BMI, the course of diabetes, blood pressure (systolic pressure, diastolic pressure), whether to smoke, family history of diabetes, complications (coronary heart disease, stroke), etc. HbA1c, liver function (glutamic-pyruvic transaminase and glutamic-oxalacetic transaminase), kidney function (blood urea nitrogen, blood uric acid and blood creatinine), and blood lipid (triglyceride, total cholesterol, low density lipoprotein cholesterol, high density lipoprotein cholesterol) were tested. Calculating eGFR according to the CKD-EPI formula.
The T2DM patient and early DKD patient cohort criteria were as follows:
the diabetes diagnosis criteria and classification adopted the 1999 world health organization criteria. Early DKD patients: besides the characteristics of diabetes, the urine level of microalbumin (UMA) is 30-300 mg/24h or the urine albumin/creatinine ratio (UACR) is 30-300 mg/g.
Exclusion criteria: firstly, acute complications (diabetic ketoacidosis, hyperglycemia and hypertonicity, lactic acidosis and hypoglycemia coma) and serious chronic complications (such as gangrene of lower limbs and the like) of diabetes are combined; ② other types of diabetes (type 1 diabetes, special type diabetes, gestational diabetes); ③ patients with complicated infection, acute heart and lung dysfunction, malignant tumor, serious cardiovascular and cerebrovascular diseases, obvious liver dysfunction (serum glutamic-pyruvic transaminase or glutamic-oxalacetic transaminase exceeds the upper limit of normal by 2 times), and obvious hyperuricemia (blood uric acid is more than or equal to 480); fourthly, pregnant or lactating women; the existing diseases are combined with chronic diseases affecting liver and kidney functions, such as autoimmune diseases and the like; sixthly, urinary infection, renal calculus, renal artery stenosis, single excision or other kidney disease history are combined; seventhly, a great amount of albuminuria (UMA is more than or equal to 300mg/24h or UACR is more than or equal to 300 mg/g) and eGFR is less than 90ml for seeds and seeds -1 ・1.73m -2 Thereby, the number of the parts can be reduced.
2. Sample processing
Biochemical detection of blood and urine samples: two groups of patients leave venous blood with fasting for 8h, centrifuge at 3000rpm for 10 min, separate serum, subpackage and store at-80 deg.C for use. Detecting biochemical indexes: liver function (glutamic-pyruvic transaminase and glutamic-oxalacetic transaminase), kidney function (blood urea nitrogen, blood uric acid and blood creatinine), and blood lipid (triglyceride, total cholesterol, low density lipoprotein cholesterol, high density lipoprotein cholesterol). Measured by using a Hitachi 7600A-020 full-automatic biochemical analyzer.
Leaving two groups of patients to take 50ml of urine respectively in 24 hours and clean midnight urine in the morning, placing the urine in a sterile centrifugal tube, centrifuging the urine at 4 ℃ and 3000rpm for 10 minutes, leaving supernatant, subpackaging the urine and placing the urine at minus 80 ℃ for freezing and storing for later use to prevent proteolysis. And (5) reserving the urine for 24h, and measuring 24hUMA by a biochemical method.
Detecting novel urine biomarkers by using a Luminex liquid phase suspension chip: cystatin C (CysC), Epidermal Growth Factor (EGF), nephrin, retinol binding protein 4 (RBP 4), kidney injury molecule 1 (KIM-1), matrix metalloproteinase inhibitor 1 (TIMP-1), human tumor necrosis factor receptor 1 (TNFR 1), human tumor necrosis factor receptor 2 (TNFR 2), alpha 1-microglobulin (alpha 1-MG), beta 2-microglobulin (beta 2-MG) and Vitamin D Binding Protein (VDBP) in urine of two groups of patients are detected. Morning urine was centrifuged at 10000 rpm for 10 min, the supernatant was collected, and 50. mu.L of the stock solution was sampled and examined.
Chip name: luminex liquid phase suspension chip.
Chip platform and kit: suspension bead chip platform Luminex 200 system (Luminex Corporation, Austin, TX, USA); ② an instrument Calibration Kit Luminex 200 Validation Kit, Luminex 200 Calibration Kit; the detection Kit is set by a Human Premixed Multi-analytic Kit 1; the Human Premixed Multi-analytic Kit set 1; magnetic plate washer, Tecan.
Sample and standard preparation: urine samples (78 cases) were centrifuged at 10000 rpm for 10 min, the supernatant was collected, and 50. mu.L of the stock solution was applied for detection. To the standard bottle, add the corresponding amount of RD6-52 as specified, turn upside down several times, and place on a low speed horizontal shaker for 15 min. The standard is then diluted as per the instructions.
Chip detection operation: sample incubation: taking the microbeads, shaking for 30 s at 1400 rpm on a shaker, and diluting the microbeads by using RD 2-1; shaking the diluted microbeads for 30 s again by using an oscillator at 1400 rpm, and adding 50 mu L of the microbeads into a 96-well plate per well; 50 μ L of the prepared standard, sample and Blank were added to the corresponding wells, a sealing film was applied, and the mixture was placed on a plate shaker at 850 rpm and shaken under dark conditions at room temperature for 2 h. Incubation detection of antibodies: discarding the sample, and washing 3 times by using a plate washing machine; biotin Antibody Cocktail was diluted as required by the instructions using RD 2-1; mu.L of diluted Biotin Antibody Cocktail was added to each well, and a sealing membrane was attached, and the mixture was shaken at 850 rpm on a plate shaker, protected from light, and incubated at room temperature for 1 hour. ③ developing color: the Biotin Antibody Cocktail was discarded and washed 3 times using a plate washer; diluting Streptavidin-PE by using Wash Buffer according to the specification; adding 50 mu L of diluted Streptavidin-PE into each hole, attaching a sealing film, placing on a flat shaking table at 850 rpm, oscillating, keeping out of the sun, incubating at room temperature for 30 min; fourthly, washing for 3 times by using a plate washing machine; adding 100 mu L of Wash Buffer into each hole for resuspension, attaching a sealing film, placing on a flat plate shaker at 850 rpm, keeping out of the sun at room temperature, and oscillating for 2 min; sixthly, sending the product into a calibrated Luminex 200 machine for reading. The obtained fluorescence is automatically calculated and optimized by software to obtain an output file in an Excel format.
Standard quality control data: firstly, the experiment sets two repeated detections for the standard product. According to CV conditions, the% CV of the standard product with the content of more than 100% is less than 20%, which indicates good repeatability and meets the quality control requirement. Secondly, according to the fluorescence detection value (FI) obtained by the Standard, a multi-parameter mode is used for fitting the Standard Curve to obtain the Standard Curve (Standard Curve) and an equation thereof, and the concentration unit is pg/mL. In standard curve fitting, the software automatically corrects for some of the outliers and fits the valid points. ③ in the standard curve, the detected value of the standard (calculated according to the standard curve, Observed percentages)
The ratio to the Expected value (standard concentration) reflects the quality of the standard curve. (Obs/Exp). times.100 can be floated between 0-130%. According to the experimental result, the (Obs/Exp) x 100 of the standard substance with the concentration of more than 100% is between 70% and 130%, which shows that the standard curve works well.
Sample detection concentration condition: the original fluorescence detected by each sample is substituted into a standard curve formula, and the concentration of the sample is obtained through calculation and can be used for comparison among samples.
3. Data processing and analysis
Statistical analysis was performed on the general data, blood, urine biochemical indices, urine biomarkers of 39 diabetic patients and 39 early DKD patients using independent sample t test, rank sum test, all statistical tests were bilateral test, and P ≤ 0.05 was treated as significance level. And (3) drawing a Receiver Operating Characteristic (ROC) curve for the urine biomarker with the P less than 0.1 in the single-factor analysis, and evaluating the diagnosis efficiency through the sensitivity and the specificity of the area under the ROC curve (AUC) and the cut-off value. And (3) incorporating the urine biomarker with high diagnostic value into multivariate Logistic regression analysis, and establishing a DKD prediction model.
4. Results
(1) Two general clinical data comparisons: compared with the diabetic group, the retinopathy proportion of patients in the early DKD group is high (P is less than 0.05). Between groups there was no statistical difference in age, gender, BMI, systolic pressure, diastolic pressure, course of diabetes, HbA1c, triglycerides, total cholesterol, high density lipoprotein, low density lipoprotein, blood urea nitrogen, blood creatinine, blood uric acid, eGFR. (Table 1)
TABLE 1 clinical characterization
(2) Two novel sets of urine biomarker analyses: early DKD patients all showed an upward trend compared to DM patients for novel urine biomarkers, with significant differences in RBP4, KIM-1, VDBP (P < 0.05). CysC, EGF, nephrin, TIMP-1, TNFR1, TNFR2, alpha 1-MG, beta 2-MG differences were not statistically significant. (Table 2)
TABLE 2 comparison of levels of two novel urine biomarkers
Diagnostic value of urine biomarkers: in the single-factor analysis, 4 novel markers RBP4, KIM-1, TNFR2 and VDBP with P less than 0.1 are respectively drawn into ROC curves, 4 indexes have statistical significance (P less than 0.05), and the AUC (area under the ROC curve) is 0.681(95% CI: 0.541-0.822), 0.681(95% CI: 0.540-0.823), 0.662(95% CI: 0.517-0.807) and 0.785(95% CI: 0.659-0.910), so that the optimal VDBP effect is achieved. According to the corresponding level of the largest Youden index, the cutoff values of RBP4, KIM-1, TNFR2 and VDBP are respectively: 60 (sensitivity: 0.613, specificity: 0.720), 3.37 (sensitivity: 0.484, specificity: 0.880), 1.27 (sensitivity: 0.839, specificity: 0.520), 90 (sensitivity: 0.677, specificity: 0.920). FIG. 1 is a ROC plot of the individual urine biomarkers VDBP, TNFR2, RBP4, KIM-1 for early diagnosis of DKD.
Respectively combining four biomarkers of VDBP, RBP4, KIM-1 and TNFR2 to prepare an ROC curve: combination 1: RBP4+ KIM-1, combination 2: RBP4+ VDBP, combination 3: KIM-1+ VDBP, combination 4: RBP4+ KIM-1+ VDBP, combination 5: RBP4+ KIM-1+ TNFR2, combination 6: RBP4+ KIM-1+ VDBP + TNFR 2. Finally, the RBP4+ KIM-1+ VDBP + TNFR2 combination was most effective in diagnosis, with an AUC of 0.812(95% CI: 0.698-0.925) and a sensitivity of 0.903. The sensitivity and AUC of the combined detection of the four biomarkers RBP4+ KIM-1+ VDBP + TNFR2 are superior to those of single detection, and the diagnostic efficiency is optimal. FIG. 2 is a ROC plot of urine biomarkers VDBP, TNFR2, RBP4, KIM-1 in combination diagnosis to differentiate diabetic patients from DKD patients.
TABLE 3 AUC values, sensitivity, specificity of urine biomarkers for early DKD diagnosis
Table 3 is the AUC values, sensitivity, specificity of the urine biomarkers alone or in combination for early DKD diagnosis. Our results suggest that the combination of VDBP, TNFR2, RBP4 and KIM-1 has the best diagnostic efficacy, the sensitivity is 0.903, the AUC is 0.812, and the combination is better than any one or two of the combination; meanwhile, better specificity is ensured. The detection capability of the diabetic nephropathy is improved by combined detection, and the liquid phase suspension chip manufactured based on the four indexes can simultaneously detect urine biomarkers VDBP, TNFR2, RBP4 and KIM-1 of a patient, so that a novel method is provided for early diagnosis of the diabetic nephropathy. Samples can be obtained from subjects clinically and shipped to a laboratory for testing and evaluation using the chips of the invention.
(4) According to the results of Logistic regression analysis, a diabetic kidney disease prediction model established by four urine biomarkers of VDBP, TNFR2, RBP4 and KIM-1 is obtained:
Y=0.14×VDBP +TNFR2 +0.01×RBP4 +15.47×KIM-1－19.24
y ═ 5.12 is the diagnostic cut point value, at which time the sensitivity and specificity were 0.903 and 0.600, respectively.
The specific operation method of the liquid phase suspension chip is summarized as follows:
1. obtaining a urine sample of a test subject;
2. after chip detection and Luminex 200 machine reading, the concentrations of TNFR2, RBP4, KIM-1 and VDBP in urine of a subject can be obtained simultaneously;
3. according to diabetic kidney disease prediction model
Y=0.14×VDBP +TNFR2 +0.01×RBP4 +15.47×KIM-1－19.24；
Risk assessment of early DKD was performed.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and should not be taken as limiting the invention, so that any modifications, equivalents, improvements and the like, which are within the spirit and principle of the present invention, should be included in the scope of the present invention.
Claims (6)
1. A urine biomarker for diagnosing diabetic nephropathy, comprising:
the markers are vitamin D binding protein, human tumor necrosis factor receptor 2, retinol binding protein 4 and kidney injury molecule 1.
2. The detection method of the diabetic kidney disease early warning model established based on synchronous detection is characterized by comprising the following steps: a diabetic kidney disease prediction model established by four urine biomarkers of vitamin D binding protein, human tumor necrosis factor receptor 2, retinol binding protein 4 and kidney injury molecule 1, wherein Y =0.14 XVDBP + TNFR2+0.01 XRBP 4+15.47 XKIM-1-19.24;
y is the tangent value of the model;
VDBP is the concentration of vitamin D binding protein, and the unit is ng/mL;
TNFR2 is the concentration of human tumor necrosis factor receptor 2 in ng/mL;
RBP4 is the concentration of retinol binding protein 4 in ng/mL;
KIM-1 is the concentration of kidney injury molecule 1 in ng/mL.
3. The method for establishing the diabetic kidney disease early warning model based on synchronous detection as claimed in claim 2, is characterized in that: and obtaining a diabetic kidney disease prediction model established by four urine biomarkers of vitamin D binding protein, human tumor necrosis factor receptor 2, retinol binding protein 4 and kidney injury molecule 1 according to the regression analysis result.
4. Kit of diabetes kidney disease early warning model, its characterized in that: the kit comprises biomarkers, wherein the biomarkers are vitamin D binding protein, human tumor necrosis factor receptor 2, retinol binding protein 4 and kidney injury molecule 1.
5. The kit of the diabetic kidney disease early warning model according to claim 4, wherein: the kit comprises a liquid phase suspension chip.
6. The use of the marker of claim 1 or the detection method of claim 2 in the preparation of a kit for a diabetic kidney disease early warning model, characterized in that: is applied to distinguish type 2 diabetes mellitus patients from type 2 diabetes mellitus kidney patients.
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