Use of two metabolic markers alone or in combination in the preparation of a kit for diagnosing general ligamentous laxity

Abstract

The present invention discloses the use of two metabolic markers alone or in combination in the preparation of a kit for diagnosing general ligamentous laxity. The metabolic markers hexadecanamide and propyl p-hydroxybenzoate provided by the present invention can be used alone or in combination to diagnose and distinguish healthy people from patients with general ligamentous laxity, with high diagnostic accuracy, and have the prospect of being developed into a kit for diagnosing general ligamentous laxity.

Description

Technical Field

[0001] The present invention belongs to the field of biochemistry, and relates to the application of metabolic markers in disease diagnosis, in particular to the application of two metabolic markers alone or in combination in the preparation of a kit for diagnosing generalized ligamentous laxity. Background Art

[0002] Generalized ligamentous laxity (GLL) is a congenital disease. Patients may show ligament laxity in all joints of the body, such as varus of the knee joint, hyperextension of the thumb and interphalangeal joints, etc. At present, the internationally commonly used diagnostic criteria for generalized ligamentous laxity are to use the range of motion of nine parts of the body as the evaluation sites, namely the elbow, hip joint, knee joint, little finger joint, and body flexion range of motion.

[0003] Biomarkers can be used as signal indicators reflecting changes in the structure and function of organisms, and are used to detect the occurrence and progression of complex diseases. In recent years, biomarkers in the "omics" field have been used as auxiliary means to pre-detect, accurately and sensitively judge the occurrence of diseases, and have achieved good results. The combined diagnosis of multiple biomarkers can distinguish the types of diseases and the stages of diseases, and assist in clinical treatment. Moreover, taking serum biomarkers as an example, this method has the advantages of being simple, rapid, economical and relatively non-invasive, and is widely used, which is very friendly to patients.

[0004] The present invention discovers metabolic markers with high diagnostic accuracy for generalized ligamentous laxity, and thus particularly proposes the present invention. Summary of the Invention

[0005] The purpose of the present invention is to provide the application of two metabolic markers alone or in combination in the preparation of a kit for diagnosing generalized ligamentous laxity.

[0006] The above object of the present invention is achieved by the following technical solutions:

[0007] The application of two metabolic markers alone or in combination in the preparation of a kit for diagnosing generalized ligamentous laxity, wherein the two metabolic markers are hexadecanamide and propylparaben.

[0008] A kit for diagnosing generalized ligamentous laxity, which contains a detection reagent for detecting hexadecanamide or / and propylparaben.

[0009] Advantageous Effects:

[0010] The present invention discovers that the metabolic markers Hexadecanamide and Propylparaben can be used alone or in combination to diagnose and distinguish healthy individuals from patients with generalized ligamentous laxity, with a high diagnostic accuracy, and has the prospect of being developed into a kit for diagnosing generalized ligamentous laxity. In addition, the diagnostic index provided by the present invention is a serum metabolite, and only a small amount of blood needs to be taken for detection, which is basically non-invasive. Description of the Drawings

[0011] Figure 1 Comparison of the content levels of two serum metabolites in the sera of healthy subjects and patients with generalized ligamentous laxity;

[0012] Figure 2 ROC curve of Hexadecanamide for distinguishing healthy subjects vs. patients with generalized ligamentous laxity;

[0013] Figure 3 ROC curve of Propylparaben for distinguishing healthy subjects vs. patients with generalized ligamentous laxity;

[0014] Figure 4 ROC curve of Hexadecanamide combined with Propylparaben for distinguishing healthy subjects vs. patients with generalized ligamentous laxity. Detailed Embodiments

[0015] The following specifically introduces the substantial content of the present invention in combination with the drawings and examples, but does not limit the protection scope of the present invention thereto.

[0016] Example 1: Diagnostic Efficacy of Metabolic Markers for Generalized Ligamentous Laxity

[0017] I. Experimental Samples and Reagents

[0018] Collect 35 healthy subjects and 65 patients with generalized ligamentous laxity from Jiangsu Provincial Hospital of Traditional Chinese Medicine. The healthy subjects are normal people with healthy physical examinations, and the patients with generalized ligamentous laxity are included according to the WHO diagnostic criteria for generalized ligamentous laxity. The age, gender, and body mass index of the patients in each group are matched, with no significant differences. The subjects or patients in each group are randomly divided into training set samples and validation set samples according to Table 1.

[0019] Table 1 Sample Quantities of Training Set Samples and Validation Set Samples

[0020] Healthy control subjects (HCS) Generalized ligamentous laxity patients (GLL) Training set 20 40 Validation set 15 25 Total number of samples 35 65

[0021] Exclusion Criteria:

[0022] ①Combined with other orthopedic diseases; ②Combined with serious primary diseases such as cardiovascular and cerebrovascular, liver, kidney, and hematopoietic systems; ③Those with mental illnesses who are unable to cooperate; ④Those who have participated in other clinical trials within the past month; ⑤Those who are unwilling to accept this study.

[0023] Main experimental reagents: acetonitrile, methanol, water.

[0024] II. Experimental methods

[0025] 1. Collection and storage of serum samples

[0026] Collect fasting peripheral blood from healthy subjects and patients with generalized ligamentous laxity in the early morning and place it in a tube without anticoagulant. Let it coagulate naturally at room temperature for 30 - 60 minutes. After the blood coagulates, centrifuge it at a speed of 2000 rpm for 10 minutes. Carefully aspirate the upper clear serum liquid into a sterile freeze-dried tube, label it, and store it in a 4°C refrigerator for later use.

[0027] 2. Determination of the content level of target metabolites in serum by HPLC-MS technology

[0028] Detection instrument: TripleTOF TM 5600+ high-resolution mass spectrometer (AB SCIEX, USA), ExionLC™ high-performance liquid chromatography system (AB SCIEX, USA), chromatographic column Phenomenex Kinetex 2.6μm C18 100A (2.1×100mm), Phenomenex, USA, medical centrifuge (Beijing Baiyang Medical Instrument Co., Ltd.), 100μL and 1000μL pipettes (Eppendorf, Germany), 1.5mL centrifuge tubes (Jiangsu Kangjie Medical Instrument Co., Ltd.), vortex shaker (IKA, Germany), refrigerated high-speed centrifuge (Thermo Fisher Scientific), KH3200V ultrasonic cleaner (Kunshan Hechuang Ultrasonic Instrument Co., Ltd.), ultrapure water instrument (Milli-Q, Merck Millipore, USA).

[0029] Sample processing: Take 100 μL of plasma from each sample and mix it with 400 μL of acetonitrile: methanol (1:1). Then vortex each sample for 30 seconds and place it in an ice bath for ultrasonic treatment for 10 minutes. Then place it in a -20°C refrigerator for 1 hour, and centrifuge it at high speed (12,000 rpm) in a low-temperature (4°C) centrifuge for 15 minutes. Take the supernatant and place it in a vacuum freeze dryer to evaporate to dryness. Add 100 μL of acetonitrile: water (1:1) to re-dissolve it, vortex for 30 seconds, place it in an ice bath for ultrasonic treatment for 5 minutes, and then centrifuge it at high speed (12,000 rpm) in a low-temperature (4°C) centrifuge for 15 minutes. Take 10 μL of the supernatant from each sample and mix them in one tube as the QC sample. The remaining samples are aliquoted for standby. Two tubes are used for injection in two column modes (40 μL / tube) and stored in a 4°C refrigerator for transfer and injection.

[0030] The detection peak area of the target serum metabolite in each sample represents its content level.

[0031] 3. Data processing method

[0032] In the training set, use Logistic regression to establish a regression equation for the target serum metabolite, generate a new variable logit[P], perform ROC curve analysis on this new variable, and obtain the optimal cut-off value according to the ROC curve; in the validation set, calculate the diagnostic accuracy of the target serum metabolite according to the predicted probability given by the SPSS 25.0 software.

[0033] III. Experimental results

[0034] 1. Differences in the content levels of target serum metabolites in the sera of healthy subjects and patients with generalized ligamentous laxity

[0035] In the training set, there were significant differences in the content levels of the metabolites hexadecanamide and propyl p-hydroxybenzoate in the sera of healthy subjects and patients with generalized ligamentous laxity, as Figure 1 shown.

[0036] 2. Diagnostic discrimination efficacy of target serum metabolites for healthy subjects vs generalized ligamentous laxity

[0037] 2.1 Construction of the regression equation in the training set

[0038] In the training set, taking the content level of the serum metabolite hexadecanamide in each sample as the independent variable and the group (healthy subjects, patients with generalized ligamentous laxity) as the dependent variable, the regression equation logit[p] = 1.702 + 4.183X1 was constructed, where: X1 is the content level of hexadecanamide.

[0039] In the training set, taking the content level of propylparaben, a serum metabolite of each sample, as the independent variable and the group (healthy subjects, patients with generalized ligamentous laxity) as the dependent variable, the regression equation logit[p] = 2.924 - 4.79X1 was constructed, where: X1 is the content level of propylparaben.

[0040] In the training set, taking the content levels of hexadecanamide and propylparaben, serum metabolites of each sample, as the independent variables and the group (healthy subjects, patients with generalized ligamentous laxity) as the dependent variable, the regression equation logit[p] = 7.296 + 5.215X1 - 9.004X2 was constructed, where: X1 is the content level of hexadecanamide and X2 is the content level of propylparaben.

[0041] 2.2 Determining the optimal discrimination threshold for the training set

[0042] In the training set, substituting the content level of hexadecanamide, a serum metabolite of each sample, into the above regression equation, the regression value logit[p] of each sample in the training set can be obtained. Using the possible regression values as diagnostic points, the sensitivity and specificity are calculated, and based on this, an ROC curve is plotted (as Figure 2 shown), and the AUC can reach 0.920, showing high accuracy. According to the ROC curve, the optimal cut-off value for diagnosing and differentiating healthy subjects from patients with generalized ligamentous laxity is 0.599.

[0043] In the training set, substituting the content level of propylparaben, a serum metabolite of each sample, into the above regression equation, the regression value logit[p] of each sample in the training set can be obtained. Using the possible regression values as diagnostic points, the sensitivity and specificity are calculated, and based on this, an ROC curve is plotted (as Figure 3 shown), and the AUC can reach 0.910, showing high accuracy. According to the ROC curve, the optimal cut-off value for diagnosing and differentiating healthy subjects from patients with generalized ligamentous laxity is 0.616.

[0044] In the training set, substituting the content levels of hexadecanamide and propylparaben, serum metabolites of each sample, into the above regression equation, the regression value logit[p] of each sample in the training set can be obtained. Using the possible regression values as diagnostic points, the sensitivity and specificity are calculated, and based on this, an ROC curve is plotted (as Figure 4 shown), and the AUC can reach 0.985, showing high accuracy. According to the ROC curve, the optimal cut-off value for diagnosing and differentiating healthy subjects from patients with generalized ligamentous laxity is 0.414.

[0045] 2.3 Verifying the diagnostic accuracy for the validation set

[0046] In the validation set, import the data of the content levels of the serum metabolite hexadecanamide in each sample into SPSS 25.0 software, and the regression value logit[p] of each sample in the validation set can be obtained, and the predicted probability can be obtained. The accuracy rate of the target metabolite in distinguishing healthy subjects from general ligamentous laxity is 85% (34 / 40), which is calculated by dividing the number of samples with correct prediction by the total number of samples.

[0047] In the validation set, import the data of the content levels of the serum metabolite propylparaben in each sample into SPSS 25.0 software, and the regression value logit[p] of each sample in the validation set can be obtained, and the predicted probability can be obtained. The accuracy rate of the target metabolite in distinguishing healthy subjects from general ligamentous laxity is 90% (36 / 40), which is calculated by dividing the number of samples with correct prediction by the total number of samples.

[0048] In the validation set, import the data of the content levels of the serum metabolites hexadecanamide and propylparaben in each sample into SPSS 25.0 software, and the regression value logit[p] of each sample in the validation set can be obtained, and the predicted probability can be obtained. The accuracy rate of the target metabolite in distinguishing healthy subjects from general ligamentous laxity is 100% (40 / 40), which is calculated by dividing the number of samples with correct prediction by the total number of samples.

[0049] The above embodiments show that the metabolic markers Hexadecanamide and Propylparaben provided by the present invention can be used for diagnosis and differentiation of healthy people and patients with general ligamentous laxity alone or in combination, and have a high diagnostic accuracy rate. Therefore, there is a prospect of developing and preparing a kit for diagnosing general ligamentous laxity. In addition, the diagnostic index provided by the present invention is a serum metabolite, and only a small amount of blood needs to be taken for detection, which is basically non-invasive.

[0050] Example 2: Diagnostic Kit

[0051] A diagnostic kit for diagnosing general ligamentous laxity contains a detection reagent for detecting Hexadecanamide or / and Propylparaben.

[0052] The function of the above embodiments is to specifically introduce the substantive content of the present invention. However, those skilled in the art should know that the protection scope of the present invention should not be limited to this specific embodiment.

Claims

1. Use of two metabolic markers alone or in combination in the preparation of a kit for diagnosing general ligament laxity, wherein the two metabolic markers are hexadecanamide and propylparaben.

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