Marker for diagnosis or prognosis evaluation of children with epilepsy as well as detection method and application of marker

Abstract

The invention relates to a divisional application with the application number of 202411710591.1, discloses a marker for diagnosis or prognosis evaluation of children with epilepsy as well as a detection method and application of the marker, and belongs to the field of detection. The marker comprises one or more of the following purine metabolites: uric acid, creatinine, xanthine, hypoxanthine, guanine, adenine, adenosine, adenosine triphosphate, adenosine diphosphate and adenylic acid. The difference of blood / urine purine metabolite concentrations of an epilepsy child and a healthy control is reported, a disease prediction model based on the difference of various indexes of blood / urine purine is constructed, a comprehensive scoring algorithm is established, a detection result is convenient to interpret, and a clinical basis is provided for diagnosis and prognosis evaluation of child epileptic seizure.

Description

[0001] This invention is a divisional application of a Chinese application with an application date of November 27, 2024, an application number of 202411710591.1, and an invention creation name of "A Marker for Diagnosing or Prognostically Evaluating Children with Epilepsy, and Its Detection Method and Application". Technical Field

[0002] This invention relates to the field of biological detection, and particularly to a marker for diagnosing or prognostically evaluating children with epilepsy, and its detection method and application. Background Art

[0003] Epilepsy is a common neurological disorder characterized by recurrent symptoms and is a serious global health problem. Epilepsy is a common, complexly etiologically, and recurrent neurological syndrome in childhood. The clinical manifestations of epilepsy are diverse, including both episodic symptoms and chronic health problems, especially in children. Due to the rapid brain development stage, children with epilepsy often have developmental retardation and cognitive impairment.

[0004] Early and accurate diagnosis and effective treatment can improve the quality of life and cognitive function. If not effectively treated, it may develop into refractory epilepsy in an average of 9.1 years (median 5 years), seriously affecting the quality of life of children. The prerequisite for effective treatment is early and correct diagnosis. Due to various reasons, the diagnosis of epilepsy is often delayed. Epileptic seizures will exacerbate acute injuries and lead to poor prognoses, including cerebral palsy, developmental retardation, and mental defects.

[0005] The diagnosis of epilepsy relies on the description of epileptic seizure symptoms and electroencephalogram (EEG) examination. However, epileptic seizures are unpredictable and patients often have difficulty recalling seizure symptoms, and EEG examination is difficult to perform immediately. Therefore, the diagnosis of epilepsy faces major clinical challenges, especially in situations where rapid diagnosis is required. So far, electroencephalogram (EEG) is the gold standard for epilepsy diagnosis. However, EEG often has difficulty recording the seizure period, and there are problems such as long duration, high cost, and the need for highly skilled professionals to interpret. Therefore, there is an urgent clinical need for a diagnostic method that can rapidly evaluate epileptic seizures. Thus, new biomarkers for epileptic seizure diagnosis and prognostic evaluation are the current research focus.

[0006] Currently, many biomarkers have been confirmed to be related to the pathological changes occurring during epileptic seizures, including inflammatory markers in biological fluids such as cytokines (e.g., interleukins), markers of neuronal injury (e.g., neuron-specific enolase), and markers of astrocyte reaction (e.g., glial fibrillary acidic protein, protein S100β), as well as more recently, microRNA. However, these require difficult-to-obtain biological samples (such as cerebrospinal fluid), large amounts of blood, or further blood processing, which may lead to the sensitivity of hemolysis, molecular instability, and the lack of a rapid and cost-effective analysis platform, resulting in different outcomes. An ideal epilepsy biomarker should be as easy to obtain as possible (such as blood, urine), minimally invasive, not require special processing, and be measured through a repeatable, easy-to-use, and economically feasible analysis platform. At the same time, it should have high sensitivity and specificity. In recent years, the potential value of purines and their metabolites as blood biomarkers for children with epilepsy has received extensive attention.

[0007] Early research results have confirmed that adenosine accumulates extracellularly in brain cells in response to high levels of neuronal activity, thereby acting as an endogenous anticonvulsant. Adenosine can affect epileptogenesis, development, and progression through receptor-dependent and independent mechanisms. There are also studies indicating that adenosine triphosphate and adenosine, as neuromodulators, play important roles in epileptic seizures. They play opposite roles between neuronal excitability and brain energy homeostasis and affect the occurrence and development of epilepsy through different mechanisms. After an epileptic seizure, significant changes may occur in the concentration of purines in the blood and the expression of different metabolites in the purinergic signaling cascade. Although Beamer et al.'s research preliminarily proposed that the blood levels of adenosine and its breakdown products can be used as biomarkers for epilepsy, the number of cases in their study was small and only 3 metabolites with relatively high expression levels - inosine, xanthine, and hypoxanthine were detected. However, the inventors found through verification that the diagnostic performance and accuracy of diagnosing epilepsy by combining these three metabolites were poor.

[0008] These research results indicate that purines and their metabolites may play a certain role in the occurrence and progression of epilepsy, but mostly through animal models and preliminary clinical studies. In addition, although blood and urine are relatively easy-to-obtain samples, there is currently a lack of systematic clinical research on the relationship between blood or urine markers and epileptic seizures and their application value. This aspect of research first requires a large number of clinically diagnosed child samples as a basis; secondly, there are a wide variety of metabolites related to epilepsy in current studies, and a large number of experiments and data analyses are needed to screen out biomarkers with diagnostic value; finally, the content of metabolites related to epileptic pathological changes in blood or urine is generally not high. For example, the content of adenosine and its metabolites in the blood is relatively low, and the content of adenosine diphosphate is at the ng level. Improving the detection sensitivity of biomarkers is also one of the technical difficulties.

[0009] At present, there is still a lack of rapid diagnostic methods for children with epilepsy and biomarkers that are highly accurate and easy to detect. Summary of the Invention

[0010] Object of the Invention

[0011] To overcome the above deficiencies, such as the lack of rapid diagnostic methods for children with epilepsy and biomarkers that are highly accurate and easy to detect, the object of the present invention is to provide a biomarker for diagnosing or prognosticating children with epilepsy, as well as its detection method and application. Uric acid, creatinine, xanthine, hypoxanthine, guanine, adenine, adenosine, adenosine triphosphate, adenosine diphosphate, and adenylic acid of the present invention can be used as biomarkers for epilepsy diagnosis and prognosis evaluation. The present invention reports the differences in blood / urine purine and its metabolite concentrations between children with epilepsy and healthy controls, constructs a disease prediction model based on the changes in various blood / urine purine indicators, and establishes a comprehensive scoring algorithm to facilitate the interpretation of test results, providing a clinical basis for the diagnosis and prognosis evaluation of childhood epilepsy seizures.

[0012] Solution

[0013] To achieve the object of the present invention, the technical solutions adopted by the present invention are as follows:

[0014] In the first aspect, the present invention provides a biomarker for diagnosing or prognosticating children with epilepsy, including one or more of the following purine metabolites: uric acid, creatinine, xanthine, hypoxanthine, guanine, adenine, adenosine, adenosine triphosphate (ATP), adenosine diphosphate (ADP), and adenylic acid (AMP).

[0015] In the second aspect, there is provided a biomarker for diagnosing or prognosticating children with epilepsy, which includes a combination of purine metabolites in urine: adenine and adenosine diphosphate.

[0016] In the third aspect, there is provided a biomarker for diagnosing or prognosticating children with epilepsy, which includes a combination of purine metabolites in blood: uric acid, hypoxanthine, adenine, adenosine, and adenylic acid.

[0017] In the fourth aspect, there is provided an application of detecting the concentration value of purine metabolites in urine in the preparation of a kit or an analysis system for diagnosing or prognosticating children with epilepsy; wherein, the combination of purine metabolites in urine includes adenine and adenosine diphosphate. Optionally, the expression levels of adenine and adenosine diphosphate in urine are detected by tandem mass spectrometry.

[0018] Fifth aspect, there is provided an application of detecting the concentration value of purine metabolites in blood in preparing a kit or an analysis system for diagnosing or prognostically evaluating children with epilepsy; wherein, the purine metabolite combination in blood includes: uric acid, hypoxanthine, adenine, adenosine and adenylic acid. Optionally, the expression levels of uric acid, hypoxanthine, adenine, adenosine and adenylic acid in blood are detected by tandem mass spectrometry.

[0019] Sixth aspect, there is provided a method for detecting a marker for non-diagnostic purposes, including a method for detecting the concentration value of the marker described in the first, second or third aspect in blood or urine (or the method for detecting the concentration value of the purine metabolite combination in blood or urine in the marker combination described in the first, second or third aspect above, or the application described in the fourth or fifth aspect includes): using tandem mass spectrometry for quantitative detection and analysis of purines;

[0020] Optionally, the method for detecting the concentration value of the purine metabolite combination in blood or urine includes: performing tandem mass spectrometry analysis through the optimized parent ions and characteristic fragment ions of the purine metabolite and 2 isotope internal standards.

[0021] Optionally, the urine pretreatment method includes: adding acetonitrile to urine, centrifuging to take the supernatant and drying it by rotation, adding 0.75% ammonia water solution containing internal standard for reconstitution, and centrifuging to take the supernatant for injection.

[0022] Optionally, the blood sample uses serum, and the serum pretreatment method includes: adding acetonitrile containing internal standard to serum, centrifuging to take the supernatant and drying it by rotation, adding 0.75% ammonia water solution for reconstitution, and centrifuging to take the supernatant for injection.

[0023] Quantitative analysis calculates the content of purines by measuring the intensity of specific ion signals.

[0024] Liquid chromatography-tandem mass spectrometry (LC-MS / MS) combines the separation ability of liquid chromatography and the high selectivity and sensitivity of tandem mass spectrometry, and is particularly suitable for the analysis of trace components in complex biological samples.

[0025] The present invention uses liquid chromatography-tandem mass spectrometry technology (LC-MS / MS) to establish a method for simply, rapidly and accurately detecting purines and their metabolites in the blood or urine of children with epilepsy, and at the same time provides a reference basis for the detection of epileptic seizures and assisting doctors in treatment.

[0026] Seventh aspect, there is provided an analysis system for diagnosing and evaluating children with epilepsy, including a data analysis module, the data analysis module is used to collect the concentration value of the purine metabolite combination of the target object to be predicted, use the concentration value of the purine metabolite combination as an input feature, and is also used to calculate the prediction value of whether the target object is epilepsy according to the concentration value of the purine metabolite combination; the input feature is the marker described in the first, second or third aspect.

[0027] In the eighth aspect, an analysis system for diagnosing or prognostically evaluating children with epilepsy is provided. Using the concentration values of the purine metabolite combination in urine as input features, the predicted value of whether the target object has epilepsy is calculated. The model prediction formula is:

[0028] pre = (-0.429 to 0.055) × adenine + (-17.546 to 9.210) × adenosine diphosphate;

[0029] wherein, adenine and adenosine diphosphate are the concentration values of each index in urine. When the predicted value of the urine index is greater than 0.6904, it is considered epilepsy positive, otherwise it is a healthy child.

[0030] In the ninth aspect, an analysis system for diagnosing or prognostically evaluating children with epilepsy is provided. Using the concentration values of the purine metabolite combination in blood as input features, the predicted value of whether the target object has epilepsy is calculated. The model prediction formula is:

[0031] pre = (-0.004 to 0.002) × uric acid + (0.004 to 0.006) × hypoxanthine + (0.118 to 0.706) × adenine + (-0.077 to 0.497) × adenosine + (-21.207 to -10.057) × adenosine monophosphate;

[0032] wherein, uric acid, hypoxanthine, adenine, adenosine, and adenosine monophosphate are the concentration values of each index in blood. When the predicted value of the blood index is greater than 0.5518, it is considered epilepsy positive, otherwise it is a healthy child.

[0033] In the tenth aspect, a kit for diagnosing children with epilepsy, evaluating the efficacy or prognosis, or evaluating related drugs is provided. The kit includes the biomarker and / or its detection reagent described in the first, second, or third aspect.

[0034] Beneficial effects

[0035] (1) The present invention has established a highly sensitive purine and its metabolite detection system: The present invention provides a rapid, simple, and effective purine and its metabolite detection system, which can achieve detection at a level as low as ng / ml in urine and blood.

[0036] (2) The present invention fills the blank of non-invasive detection biomarkers for epilepsy: The present invention proposes that 10 purine metabolite biomarkers may be used as non-invasive tools for epilepsy diagnosis. Through a large number of clinical diagnostic analyses, it is proved that the combined diagnosis of uric acid, hypoxanthine, adenine, adenosine, and adenosine monophosphate in blood, and the combined diagnosis of adenine and adenosine diphosphate in urine can be used as the value of non-invasive detection biomarkers for epilepsy.

[0037] (3) Another major innovation of the present invention is a concise result analysis system: The analysis system of the present invention is not the result analysis of single-index detection (the diagnostic efficiency of a single index is low). The present invention imports the detection results of the screened biomarkers into a comprehensive scoring system formed by independent modeling, and comprehensively scores the results of 2 / 5 types of purine metabolites detected in blood / urine, overcoming the problem of low diagnostic efficiency of a single index. It avoids the trouble brought to clinical interpretation by inconsistent single results, and the comprehensive interpretation makes the reliability and reference value of the results more meaningful and is more convenient for clinical promotion and application.

[0038] (4) The test operation of the present invention is simple, and it can achieve the clinical goal of early diagnosis and early treatment. At present, the clinical EEG technology is difficult to perform immediate detection and the EEG interpretation has certain subjectivity. The present invention detects the detection indexes of blood / urine purines and their metabolites, which helps to perform immediate and objective evaluation of epileptic seizures. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] One or more embodiments are illustrated by way of example in the accompanying drawings, and these exemplary illustrations do not constitute a limitation on the embodiments. The special word "exemplary" here means "serving as an example, an embodiment or an illustration". Any embodiment illustrated here as "exemplary" does not have to be construed as superior or better than other embodiments.

[0040] Figure 1 It is a heat map of the correlation between the purine index of the present invention and the occurrence of epilepsy; wherein: A is a correlation matrix diagram, and B is a correlation heat map.

[0041] Figure 2 It is the prediction ROC curve of the single index and combined prediction of blood / urine in the present invention for epilepsy (wherein: A is urine; B is blood).

[0042] Figure 3 It is the prediction ROC curve of using the concentrations of xanthine and hypoxanthine in blood in existing literature as biomarkers for epilepsy diagnosis. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0044] In addition, for a better illustration of the present invention, numerous specific details are given in the following specific embodiments. Those skilled in the art should understand that the present invention can also be implemented without certain specific details. In some embodiments, raw materials, components, methods, means, etc. well-known to those skilled in the art are not described in detail in order to highlight the gist of the present invention.

[0045] Unless otherwise clearly stated, throughout the specification and claims, the term "comprising" or its variations such as "including" or "having" etc. will be understood to include the stated elements or components, without excluding other elements or other components.

[0046] The raw materials used in the present invention are all commercially available.

[0047] The present invention provides a detection method for detecting the concentrations of various purine indicators (uric acid, creatinine, xanthine, hypoxanthine, guanine, adenine, adenosine, adenosine triphosphate, adenosine diphosphate, adenylic acid) in the blood and urine of epilepsy patients. The required reagents and detection steps are as follows:

[0048] 1) Reagent and sample pretreatment:

[0049] Isotope internal standard: uric acid-1,3- 15 N2 (purchased from Aladdin, U471861-25mg), creatinine-(methyl-d3) (purchased from Aladdin, C471935-5mg).

[0050] Configuration method of internal standard stock solution and working solution:

[0051] UA- 15 N2 stock solution: Dissolve uric acid-1,3- 15 N2 solid powder with 1M NaOH solution to prepare a 5mg / mL internal standard stock solution, and store it in a -80°C refrigerator.

[0052] Cr-D3 stock solution: Dissolve creatinine-(methyl-d3) solid powder with distilled water to prepare a 5mg / mL internal standard stock solution, and store it in a -80°C refrigerator.

[0053] Mixed internal standard working solution (UA- 15 N2, 50μg / mL; Cr-D3, 100μg / mL): Take 100μL of UA- 15 N2 stock solution, 200μL of Cr-D3 stock solution, add 9.7mL of distilled water, mix well and set aside. Store it in a -80°C refrigerator.

[0054] 2) Urine sample extraction method:

[0055] Take 50 μL of urine sample, add 150 μL of acetonitrile, vortex for 30 s, place in a refrigerator at 4 °C for 10 min. Centrifuge at 10000 g for 10 min. Take 100 μL of the supernatant and dry it by vacuum centrifugation. Add 50 μL of 0.75% ammonia water solution (containing internal standard) for reconstitution, vortex for 30 s, and centrifuge at 10000 g for 10 min. Take 40 μL of the supernatant for injection preparation.

[0056] Among them, the preparation method of 0.75% ammonia water solution (containing internal standard) is as follows: 300 μL of ammonia water (25%), 1 mL of mixed internal standard working solution (UA- 15 N2, 50 μg / mL; Cr-D3, 100 μg / mL), 8.7 mL of distilled water.

[0057] 3) Serum sample extraction method:

[0058] Take 50 μL of serum sample, add 160 μL of acetonitrile (containing internal standard), vortex for 30 s, place in a refrigerator at 4 °C for 10 min. Centrifuge at 10000 g for 10 min. Take 120 μL of the supernatant and dry it by vacuum centrifugation. Add 50 μL of 0.75% ammonia water solution for reconstitution, vortex for 30 s, and centrifuge at 10000 g for 10 min. Take 40 μL of the supernatant for injection preparation.

[0059] Among them, the preparation method of acetonitrile (containing internal standard) is as follows: 2 mL of mixed internal standard working solution (UA- 15 N2, 50 μg / mL; Cr-D3, 100 μg / mL), 30 mL of acetonitrile.

[0060] Among them, the preparation method of 0.75% ammonia water solution is as follows: 300 μL of ammonia water (25%), 9.7 mL of distilled water.

[0061] 4) Liquid phase method

[0062] Sampling system: Waters I Class LC System;

[0063] Chromatographic column: HSS T3 (100×2.1 mm, 1.8 um);

[0064] Mobile phase: A_water (5 mM ammonium formate); B_methanol: water (1:1, 5 mM ammonium formate);

[0065] Column temperature: 30 °C;

[0066] Injection volume: 5 μl;

[0067] The program settings for gradient elution are shown in Table 1:

[0068] Table 1. Gradient elution program

[0069]

[0070] 5) Mass spectrometry detection method

[0071] Collection system: SCIEX Qtrap 4500 Mass System;

[0072] Ion source: ESI, pos;

[0073] Collection mode: MRM;

[0074] The optimized precursor ions and characteristic fragment ions of 10 components + 2 isotope internal standards are shown in Table 2 below.

[0075] Table 2. Optimized precursor ions and characteristic fragment ions of 10 components + 2 isotope internal standards

[0076]

[0077]

[0078] 6) Data processing and analysis

[0079] The peak area is obtained through the Analyst software of ScieX company. The uric acid content is calculated by the ratio of the peak area of uric acid - 15 N2 isotope internal standard, and the other components are calculated by the ratio of the peak area of creatinine - d3 isotope internal standard.

[0080] 7) Detection of real samples

[0081] Five samples are selected from each of the case group and the control group, and the proposed sample processing method and detection method of the present invention are used to detect purines and their metabolites. Using the data processing and analysis proposed by us, the detection results are shown in Table 3 and Table 4:

[0082] Table 3. Detection results of 10 purines and their metabolites in urine

[0083]

[0084] Table 4. Detection results of 9 purines and their metabolites in blood

[0085]

[0086] According to Table 3 and Table 4, the detection method of the present invention can detect adenosine triphosphate and adenosine diphosphate at the ng level in urine, and can detect adenosine diphosphate at the ng level in blood, improving from the traditional detection level of ug / mL to ng / mL. It overcomes the technical difficulty of difficult detection due to relatively low content, improves the detection sensitivity of purines and their metabolites, and provides a strong backing for the screening of biomarkers.

[0087] Test Example:

[0088] Establish a prediction and analysis model and software for childhood epilepsy:

[0089] Based on the multiple logistic regression algorithm, this invention establishes a scoring model for epilepsy by calculating binary classification probabilities.

[0090] First, prepare and organize the data matrix to be analyzed. Use the ggcorrplot and pheatmap tools in R language, and use the cor() function to calculate the correlation coefficients (i.e., the pairwise correlation magnitudes between various purine indicators), and then use the corrplot package for visualization (such as Figure 1 ), perform heatmap drawing (the heatmap is drawn for the purine indicators in the blood / urine of children in the control group and the case group), and conduct inter-group correlation analysis.

[0091] Secondly, preprocess the data, check the integrity of the data. Use the purine indicators in the blood / urine as the input variables and whether the child has the disease as the dependent variable. Correctly encode and perform a preliminary screening on the original data. After deleting the data with a difference between the predicted value and the true value greater than 0.55 in the control as outliers, use stratified sampling to divide the dataset into a training set and a test set at a ratio of 7:3. Then construct and train a multiple logistic regression model, and use the trained model to calculate the probability that each sample belongs to the case group on the test set. Subsequently, evaluate the model performance according to different performance indicators, and test the AUC value of the model, that is, the area under the ROC curve. The AUC value ranges from 0.5 to 1, indicating that the prediction model performance is better than random guessing; the closer the AUC is to 1, the better. The prediction result of the model for each sample is a probability value. Obtain an optimal critical point from the ROC curve as the cut-off value sought. The found cut-off value indicates that this model has at least one threshold that can accurately separate the data above and below the threshold.

[0092] 1. Sample Processing

[0093] Collect blood samples and urine samples of 147 clinical samples (98 children with epilepsy and 49 healthy control children) who visited the Capital Institute of Pediatrics using EDTA anticoagulant tubes. A total of 9 purine types in the blood (uric acid, creatinine, xanthine, hypoxanthine, adenine, adenosine, adenosine triphosphate, adenosine diphosphate, adenylic acid) and 10 purine types in the urine (uric acid, creatinine, xanthine, hypoxanthine, guanine, adenine, adenosine, adenosine triphosphate, adenosine diphosphate, adenylic acid) were detected. Take 50 μL of each sample for blood and urine sample extraction for liquid phase and mass spectrometry detection.

[0094] 2. Clinical Sample Test Results

[0095] The mean values and standard errors of each purine index in urine are shown in Table 5. There were no significant differences in the urine uric acid, creatinine, xanthine, hypoxanthine, guanine, adenosine, adenosine triphosphate, and adenylate indices between the control group and the epilepsy case group. There were significant differences in adenine and adenosine diphosphate.

[0096] Table 5. Statistical analysis of purine content in urine samples of the case group and the control group (Mean±SEM)

[0097] Purine index Control group (n = 49) Case group (n = 98) Z value p value Uric acid (ug / mL) 22.21±1.979 19.02±1.07 -1.072 0.284 Creatinine (ug / mL) 2.579±0.299 2.152±0.1672 -1.344 0.179 Xanthine (ug / mL) 1.773±0.3322 1.797±0.2317 -0.9 0.368 Hypoxanthine (ug / mL) 18.77±3.627 23.42±2.466 -1.75 0.08 Guanine (ug / mL) 1.268±0.2891 1.423±0.1885 -0.731 0.465 Adenine (ug / mL) 1.21±0.148 0.9389±0.0781 -2.178 0.029 Adenosine (ug / mL) 9.827±1.064 11.1±1.059 -0.316 0.752 Adenosine triphosphate (ng / mL) 11.57±1.915 8.357±1.057 -1.693 0.09 Adenosine diphosphate (ng / mL) 12.62±1.951 10.31±1.733 -2.227 0.026 Adenylic acid (ng / mL) 241.9±33.72 200.6±16.92 -0.518 0.605 。

[0098] The mean values and standard errors of each purine index in blood are shown in Table 6. For the detailed analysis of the significance of each index difference, see Figure 1 。The results showed that there were no significant differences in blood creatinine, xanthine, adenosine triphosphate, and adenosine diphosphate between the control group and the epilepsy case group; there were significant differences in uric acid, adenine, and adenylate, and extremely significant differences in hypoxanthine and adenosine.

[0099] Table 6. Statistical analysis of purine content in blood samples of the case group and the control group (Mean±SEM)

[0100]

[0101]

[0102] 3. Result analysis

[0103] The analysis results of 147 subjects (98 children with epilepsy and 49 healthy children) using blood and urine tests respectively showed that the method for detecting and scoring purine content in children's blood and urine described in the present invention has high predictive value for diseases.

[0104] The formula of the multiple logistic regression model obtained in the present invention is as follows:

[0105] Urine: pre = (-0.187)×adenine + (-4.168)×adenosine diphosphate;

[0106] Among them, adenine and adenosine diphosphate are the concentration values of each index in urine.

[0107] Blood: pre = (-0.001)×uric acid + 0.005×hypoxanthine + 0.412×adenine + 0.210×adenosine + (-15.632)×adenylate;

[0108] Among them, uric acid, hypoxanthine, adenine, adenosine, and adenylate are the concentration values of each index in blood respectively.

[0109] In the purine detection of urine samples, both adenine and adenosine diphosphate have predictive value for epilepsy (AUC > 0.5). The ROC curve results are as shown in Figure 2 Figure A in Figure 2 . The AUC values of adenine and adenosine diphosphate are 0.6095 and 0.5749 respectively. Multiple logistic regression analysis was used to calculate the combined prediction probability of two purine indicators (adenine and adenosine diphosphate) in urine. The results of ROC analysis on the combined prediction value of each indicator showed that the AUC value of the combined two purine indicators (adenine and adenosine diphosphate) in urine in the training set was 0.6074, the sensitivity was 62.86%, and the specificity was 66.67%. The AUC of the combined prediction of adenine and adenosine diphosphate in the test set was 0.6406, the sensitivity was 60.71%, and the specificity was 68.75%.

[0110] In the purine detection of blood samples, the ROC curve analysis results are as shown in Figure 2 Figure B in Figure 2 . Uric acid, hypoxanthine, adenine, adenosine, and adenosine monophosphate have certain predictive value for the diagnosis of epilepsy as single indicators (AUC > 0.5). The AUC values of uric acid, hypoxanthine, adenine, adenosine, and adenosine monophosphate are 0.6177, 0.7719, 0.5861, 0.6416, and 0.6922 respectively. The AUC value of the combined diagnosis of the combined five purine indicators (uric acid, hypoxanthine, adenine, adenosine, and adenosine monophosphate) in blood in the training set was 0.8485, the sensitivity was 85.71%, and the specificity was 72.73%. The AUC of the combined five purine indicators (uric acid, hypoxanthine, adenine, adenosine, and adenosine monophosphate) in blood in the test set was 0.8371, the sensitivity was 67.86%, and the specificity was 87.50%; it has relatively high diagnostic efficacy.

[0111] Compared with the combined diagnosis of two purine indicators in urine, the combined diagnosis of five purine indicators (uric acid, hypoxanthine, adenine, adenosine, and adenosine monophosphate) in blood has higher predictive value, better sensitivity and specificity for the diagnosis of epilepsy (especially childhood epilepsy).

[0112] According to the literature of Beamer et al., inosine, xanthine, and hypoxanthine have the potential to be used as epilepsy markers, but due to the small sample size, it cannot accurately reflect whether they are effective in diagnosis. Since the inosine mentioned in it is not within the inclusion indicators of the present invention, the above-mentioned 147 clinical samples (98 case groups and 49 control group samples) were used to verify the two indicators (xanthine and hypoxanthine in blood) mentioned in the literature. The results are as shown in Figure 3 .

[0113] Figure 3 The results showed that the AUC of xanthine in blood 黄嘌呤= 0.5116 (standard error = 0.0500; 95% confidence interval (0.4142 - 0.6089); p-value = 0.8196; specificity 71.43%, sensitivity 40.82%), the AUC of hypoxanthine in blood 次黄嘌呤 = 0.7813 (standard error = 0.0384; 95% confidence interval (0.7062 - 0.8565); p-value < 0.0001; specificity 91.84%, sensitivity 52.04%), the AUC of the combined diagnosis of these two blood indicators (xanthine, hypoxanthine) 黄嘌呤+次黄嘌呤 = 0.7878 (standard error = 0.0381; 95% confidence interval (0.7131 - 0.8625); p-value < 0.0001; specificity 95.92%, sensitivity 47.96%). Although the combined diagnosis of the two has a certain predictive value for the diagnosis of epilepsy, the sensitivity and diagnostic efficacy are relatively low, far lower than the AUC value (0.8485), sensitivity and specificity of the combined diagnosis of the 5 purine indicators (uric acid, hypoxanthine, adenine, adenosine, adenylic acid) in the blood of this application

[0114] Compared with the results of the above single blood indicator or combined prediction indicators of two indicators, the combined detection of the 5 purine indicators (uric acid, hypoxanthine, adenine, adenosine, adenylic acid) in the blood of the present invention improves the detection sensitivity and specificity, and improves the diagnostic efficacy. Moreover, the detection sensitivity of the present invention can reach the ng / mL level, while the detection sensitivity in the literature is only umol / L or ug / mL

[0115] In summary, the present invention provides a convenient, rapid and effective means for detecting the purine content in the blood and urine of children, and for the diagnosis and prognosis evaluation of childhood epilepsy

[0116] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention

Claims

1. A marker for diagnosis or prognosis assessment of epilepsy in children, characterized in that: Including one or more of the following purine metabolites: uric acid, creatinine, xanthine, hypoxanthine, guanine, adenine, adenosine, adenosine triphosphate, adenosine diphosphate, adenosine monophosphate.

2. A marker for diagnosis or prognosis assessment of epilepsy in children, characterized in that: It includes a combination of purine metabolites in urine: adenine and adenosine diphosphate.

3. A marker for diagnosis or prognosis assessment of epilepsy in children, characterized in that: It includes a combination of purine metabolites in the blood: uric acid, hypoxanthine, adenine, adenosine, and adenylic acid.

4. The use of detecting the concentration of purine metabolites in urine in the preparation of a kit or analysis system for diagnosing or evaluating the prognosis of children with epilepsy; wherein: The composition of purine metabolites in urine includes adenine and adenosine diphosphate; Optionally, the expression levels of adenine and adenosine diphosphate in urine are detected by tandem mass spectrometry.

5. Application of the detection of the concentration of purine metabolites in the blood in the preparation of a kit or analysis system for diagnosis or prognosis assessment of children with epilepsy; wherein: The composition of purine metabolites in the blood includes uric acid, hypoxanthine, adenine, adenosine, and adenylic acid; Optionally, the expression levels of uric acid, hypoxanthine, adenine, adenosine and adenylic acid in the blood are detected by tandem mass spectrometry.

6. A method for detecting markers of epilepsy in blood or urine for non-diagnostic purposes, characterized in that: A method for detecting the concentration value of a marker according to any one of claims 1 to 3 in blood or urine: quantitative detection and analysis of purine using a tandem mass spectrometry method; And / or, a method comprising detecting the concentration value of a marker according to any one of claims 1 to 3 in blood or urine by performing tandem mass spectrometry analysis of parent ions and characteristic fragment ions optimized by purine metabolites and two isotope internal standards; And / or, the urine pretreatment method comprises: adding acetonitrile to the urine, centrifuging to obtain the supernatant, spinning to dryness, adding 0.75% ammonia solution containing an internal standard to re-dissolve, centrifuging to obtain the supernatant for sampling; And / or, the blood sample is serum, and the pretreatment method of the serum includes: adding acetonitrile containing an internal standard to the serum, centrifuging to obtain the supernatant and spinning to dryness, adding 0.75% ammonia solution to re-dissolve, and centrifuging to obtain the supernatant for sampling.

7. An analysis system for diagnosing or evaluating the prognosis of epilepsy in children, characterized in that: It includes a data analysis module, which is used to collect the concentration value of the purine metabolite combination of the target object to be predicted, using the concentration value of the purine metabolite combination as an input feature, and is also used to calculate the prediction value of whether the target object has epilepsy based on the concentration value of the purine metabolite combination; the input feature is the marker described in any one of claims 1 to 3.

8. An analysis system for diagnosing or evaluating the prognosis of epilepsy in children, characterized in that: Taking the concentration value of the purine metabolite combination in urine as the input feature, the prediction value of whether the target object has epilepsy is calculated. The model prediction formula is: pre=(-0.429~0.055)×adenine+(-17.546~9.210)×adenosine diphosphate; Among them, adenine and adenosine diphosphate are the concentration values ​​of each indicator in urine; Optionally, when the predicted value of the urine indicator is greater than 0.6904, it is considered to be positive for epilepsy, otherwise it is a healthy child.

9. An analysis system for diagnosing or evaluating the prognosis of epilepsy in children, characterized in that: Taking the concentration value of the purine metabolite combination in the blood as the input feature, the prediction value of whether the target object has epilepsy is calculated. The model prediction formula is: pre=(-0.004~0.002)×uric acid+(0.004~0.006)×hypoxanthine+(0.118~0.706)×adenine+(-0.077~0.497)×adenosine+(-21.207~-10.057)×adenylic acid; Among them, uric acid, hypoxanthine, adenine, adenosine, and adenylic acid are the concentration values ​​of each index in the blood; Optionally, when the predicted value of the blood index is greater than 0.5518, it is considered to be positive for epilepsy, otherwise it is a healthy child.

10. A kit for diagnosing childhood epilepsy, evaluating efficacy or prognosis, or evaluating related drugs, characterized in that: The kit comprises the marker and / or its detection reagent according to any one of claims 1 to 3.

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