CN113030301A - Application of LPE (16:0) in preparation of kit for early diagnosis of diabetic nephropathy - Google Patents

Application of LPE (16:0) in preparation of kit for early diagnosis of diabetic nephropathy Download PDF

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CN113030301A
CN113030301A CN202110212872.4A CN202110212872A CN113030301A CN 113030301 A CN113030301 A CN 113030301A CN 202110212872 A CN202110212872 A CN 202110212872A CN 113030301 A CN113030301 A CN 113030301A
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lpe
diabetic nephropathy
kit
preparation
serum
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CN113030301B (en
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刘史佳
徐晓燕
徐婷婷
周栋
安晓飞
张露
朱琳
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Jiangsu Provincial Hospital of Chinese Medicine
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Abstract

The invention discloses an application of LPE (16:0) in preparation of a kit for early diagnosis of diabetic nephropathy. The serum lipid LPE (16:0) provided by the invention can diagnose and distinguish healthy people and early diabetic nephropathy, and has high diagnosis accuracy, so that the serum lipid LPE has a prospect of being developed and prepared into a reagent or a kit for diagnosing early diabetic nephropathy. In addition, the diagnostic index provided by the invention is serum lipid, and the detection can be realized only by adopting a small amount of blood, so that the detection is basically noninvasive.

Description

Application of LPE (16:0) in preparation of kit for early diagnosis of diabetic nephropathy
Technical Field
The invention belongs to the field of biochemistry, relates to application of a metabolic marker in disease diagnosis, and particularly relates to application of LPE (16:0) in preparation of a kit for early diagnosis of diabetic nephropathy.
Background
The biomarkers can be used as signal indicators reflecting the change of organism structure and function, and can be used for detecting the occurrence and the progression of complex diseases. In recent years, biomarkers in the field of omics are used as auxiliary means for judging the occurrence condition of diseases accurately and sensitively in advance, and a good effect is achieved. The combined diagnosis of multiple biomarkers can distinguish the type of the disease and the stage of the disease, and can assist clinical treatment. And taking a serum marker as an example, the method has the advantages of simplicity, rapidness, economy and relative non-invasiveness, is widely adopted and is very friendly to patients.
The invention is especially proposed for developing serum markers or compositions thereof for diagnosing diabetes and diabetic nephropathy.
Disclosure of Invention
The invention aims to provide application of LPE (16:0) in preparation of a kit for early diagnosis of diabetic nephropathy.
The above purpose of the invention is realized by the following technical scheme:
application of serum lipid LPE (16:0) in preparation of reagent and kit for diagnosing early diabetic nephropathy.
A kit for diagnosing early diabetic nephropathy comprises a detection reagent for detecting serum lipid LPE (16: 0).
Has the advantages that:
1. the diagnostic index provided by the invention is serum lipid, and the detection can be realized only by adopting a small amount of blood, so that the detection is basically noninvasive;
2. the serum lipid LPE (16:0) provided by the invention can diagnose and distinguish healthy people and early diabetic nephropathy, and has high diagnosis accuracy, so that the serum lipid LPE has a prospect of being developed and prepared into a reagent or a kit for diagnosing early diabetic nephropathy.
Drawings
FIG. 1 is a graph of the level of lipid LPE (16:0) in serum of patients with HCs and DKDE;
FIG. 2 is a ROC curve for independent diagnosis of DKDE vs HCs by LPE (16: 0).
Detailed Description
The following detailed description of the present invention is provided in connection with the accompanying drawings and examples, but not intended to limit the scope of the invention.
Example 1: diagnostic efficacy of serum lipids on early diabetic nephropathy
First, experimental sample and reagent
169 Healthy Subjects (HCs) and 124 early diabetic nephropathy patients (DKDE) with type 2 diabetes mellitus were collected in the department of TCM of Jiangsu province. Healthy subjects were healthy normal persons, and DKDE was confirmed according to 2015 american guidelines for diabetes and kidney pathology. The age, sex and body mass index of each group of patients were matched without significant difference. Each group of subjects or patients was randomly divided into training set samples and validation set samples as per table 1.
TABLE 1 training set samples and validation set sample numbers
Figure BDA0002949475060000021
Exclusion criteria: firstly, primary kidney diseases are diagnosed definitely; ② other systemic diseases which can cause lipid urine; ③ acute complications of diabetes and urinary system infection exist in nearly 1 month; fourthly, serious primary diseases such as cardiovascular and cerebrovascular diseases, liver diseases, kidney diseases, hemopoietic systems and the like are combined; fifthly, patients with mental disease unable to cooperate; sixthly, the pregnant or nursing women or the person ready for pregnancy; seventhly, other clinical testers are added in the period of about 1 month; is reluctant to accept the researchers.
The main experimental reagents are as follows: methanol, MTBE, isopropanol, acetonitrile, ammonium acetate, ammonium hydroxide.
Second, Experimental methods
1. Serum sample collection and storage
Collecting fasting peripheral blood of a patient in the early morning, placing the fasting peripheral blood in a test tube without anticoagulant, naturally agglutinating for 30-60min at room temperature, after blood coagulation, centrifuging at 2000rpm for 10min, carefully sucking supernatant clear serum liquid into a sterile freeze-drying tube, marking, and storing in a refrigerator at-80 ℃ for later use.
2. UHPLC technology for measuring content level of target lipid in serum
A detection instrument: UHPLC system (Shimazu Nexera X2 LC-30AD, Japan), ESI-Triple quadruple mass spectrometer (SCIEX Triple Quad 5500+, Singapore);
chromatographic conditions are as follows: waters ACQUITY UPLC BEH HILIC (100 mm. times.2.1 mm I.D.,1.7 μm; Waters, Milford, MA, USA). The column temperature was 35 ℃ and the flow rate was 500. mu.l/min. The injection volume was 5. mu.l. The mobile phase consists of two solvents, phase A containing 10mM ammonium acetate (NH)4OAc) water acetonitrile (5:95, v/v) solution, phase B containing 10mM ammonium acetate (NH)4OAc) water acetonitrile (50:50, v/v, ammonium hydroxide pH 8.2). Gradient elution: 0-10.0min, 0.1% -20% B; 10.0-11.0min, 20% -98% B; 11.0-13.0min, 98% B; 13.0-13.1min, 98% -0.1% B; 13.1-16.0min, 0.1% B;
mass spectrum conditions: the mass spectrometer was operated in positive and negative ionization mode with electrospray voltage (capillary voltage) of 4500/-4500V. Typical source conditions are as follows with a curtain gas setting of 35. The ion source temperature was adjusted to 500 ℃. The ion gas source 1(GS1) and the ion gas source 2(GS2) were set to 50 and 60, respectively. The fouling reduction potential was set at 80/-80 volts. In positive and negative modes, the collision exit potential is set to 9/-11 v;
sample treatment: mu.l serum was mixed with 225. mu.l ice methanol. Each sample was then vortexed for 10 seconds and then 750. mu.l of cold MTBE was added, and the mixture was vortexed for 10 seconds and shaken for 10 minutes in a 4 ℃ orbital mixer. Add 188. mu.l of room temperature LC/MS grade water, vortex for 20 seconds, centrifuge at 14000rcf for 2 min. The supernatant was transferred to a clean tube and then evaporated in a SpeedVac sample concentrator for 2h at 45 ℃. The dry oil was dissolved with 100. mu.l of an isopropanol/acetonitrile/water (30:65:5, v/v/v) mixture, the sample vortexed for 10 seconds and then centrifuged at 14000rcf for 10 minutes at 4 ℃.
The content level was represented by the detection peak area of each target lipid in each sample.
3. Data processing method
Training centralization, establishing a regression equation of the single or multiple target serum lipid content levels by using Logistic regression, generating a new variable logit [ P ], carrying out ROC curve analysis on the new variable, and obtaining an optimal cut-off value according to the ROC curve; and (4) in verification set, calculating the diagnosis accuracy of the target serum lipid according to the prediction probability given by SPSS 25.0 software.
Third, experimental results
1. The content level difference of LPE (16:0) in DKDE and HCs serum
In training set, there was a significant difference in the serum levels of lipid LPE (16:0) in healthy subjects and patients in early stage of diabetic nephropathy, as shown in FIG. 1, respectively.
2. Diagnostic differential efficacy of serum lipid LPE (16:0) on DKDE and HCs
2.1 training set construction of logistic regression equation
In the training set, the level of serum lipid LPE (16:0) in each sample is used as an independent variable, and the group (DKDE, HCs) is used as a dependent variable, so as to construct a regression equation, wherein [ p ] ═ 0.695+3.779X1, wherein: x1 is the content level of LPE (16: 0).
2.2 training set determination of optimal discrimination thresholds
In the training set, the content level of the serum lipid LPE (16:0) of each sample is substituted into the regression equation to obtain the regression value logit [ p ] of each sample in the training set, the possible regression value is used as a diagnosis point, the sensitivity and the specificity are calculated, and accordingly, an ROC curve (shown in figure 2) is drawn, the AUC can reach 0.802, and the accuracy is high. The optimal cut-off value for diagnosing and distinguishing DKDE and HCs is 0.400 according to the ROC curve.
2.3 validation set validation diagnostic accuracy
In the validation set, the data of the content level of the serum lipid LPE (16:0) of each sample is introduced into SPSS 25.0 software, so that a regression value logit [ p ] of each sample in the validation set can be obtained, and the prediction probability is obtained, and the accuracy of the DKDE and the HCs of the target lipid differentiation is 74.8 percent (92/123) by dividing the number of correct predicted samples by the total number of samples.
Example 2: diagnostic kit
A kit for diagnosing early diabetic nephropathy comprises a detection reagent for detecting serum lipid LPE (16: 0).
The above-described embodiments are intended to be illustrative of the nature of the invention, but those skilled in the art will recognize that the scope of the invention is not limited to the specific embodiments.

Claims (2)

1. Application of serum lipid LPE (16:0) in preparation of reagent and kit for diagnosing early diabetic nephropathy.
2. A kit for diagnosing early diabetic nephropathy comprises a detection reagent for detecting serum lipid LPE (16: 0).
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CN113416777A (en) * 2021-07-09 2021-09-21 四川省医学科学院·四川省人民医院 Biomarker related to occurrence and development of diabetic nephropathy and application thereof
CN113552369A (en) * 2021-07-23 2021-10-26 江苏省中医院 Use of protein marker combination for diagnosis of type 2 diabetes and type 2 diabetic nephropathy
CN115219705A (en) * 2022-07-14 2022-10-21 中国医学科学院北京协和医院 Application of biomarker in Cushing syndrome diagnosis

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CN109709228A (en) * 2019-01-14 2019-05-03 上海市内分泌代谢病研究所 Lipid combines marker in the detection reagent of preparation diagnosis diabetes or the purposes of detectable substance
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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113416777A (en) * 2021-07-09 2021-09-21 四川省医学科学院·四川省人民医院 Biomarker related to occurrence and development of diabetic nephropathy and application thereof
CN113552369A (en) * 2021-07-23 2021-10-26 江苏省中医院 Use of protein marker combination for diagnosis of type 2 diabetes and type 2 diabetic nephropathy
CN113552369B (en) * 2021-07-23 2023-10-20 江苏省中医院 Use of protein markers in combination for diagnosis of type 2 diabetes mellitus, type 2 diabetic nephropathy
CN115219705A (en) * 2022-07-14 2022-10-21 中国医学科学院北京协和医院 Application of biomarker in Cushing syndrome diagnosis

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