CN117007822A - Marker for screening risk of schizophrenia and application thereof - Google Patents

Abstract

The present invention relates to the field of disease diagnosis, and in particular to a marker for screening the risk of schizophrenia and its use. The detection results of the kit, system and device based on total cholesterol, IDH2 protein and PPARγ protein of the present invention are very consistent with the clinical diagnosis results of schizophrenia, showing very excellent performance, and its detection method is simple, easy to operate and has clinical application. The prospects are very good.

Description

A marker for screening risk of schizophrenia and its use

Technical field

The present invention relates to the field of disease diagnosis, and specifically to a marker for screening the risk of schizophrenia and its use.

Background technique

Schizophrenia is one of the most common major mental illnesses in clinical practice, seriously endangering human physical and mental health and placing a heavy burden on society and families. Although schizophrenia has always attracted much attention, the cause of schizophrenia is very complex, and so far there is no clear conclusion on its cause. In addition, like other mental diseases, the diagnosis of schizophrenia mainly relies on clinical manifestations and lacks relevant physiological, biochemical and other diagnostic indicators. Therefore, it is easily affected by the patient's cultural level and subjective consciousness, and misdiagnosis and missed diagnosis often occur. Therefore, seeking an objective, effective, convenient and feasible biological marker has become an urgent clinical problem to be solved.

Biomarkers have been widely used in clinical applications. They can not only be used for early diagnosis of diseases, but also for the formulation of disease treatment plans, judgment of disease prognosis, and evaluation of drug efficacy. There are currently molecular markers for the diagnosis of schizophrenia based on genes in plasma and serum, but most of them are single biomarkers with poor sensitivity and specificity and cannot meet clinical needs. Combining multiple markers can To effectively make up for this shortcoming, there is currently a lack of markers that can be effectively combined for screening schizophrenia.

Contents of the invention

The problem to be solved by the present invention is to provide a schizophrenia risk screening tool with high detection rate, high sensitivity, good reproducibility of results, and suitable for large-scale population screening, including a kit, a system and a device.

The specific technical solutions of the present invention are as follows:

Use of IDH2 protein, total cholesterol and/or PPARγ protein in preparing markers for risk screening of schizophrenia.

The present invention also provides the use of reagents for detecting total cholesterol concentration, IDH2 protein expression level and/or PPARγ protein expression level in blood samples in preparing kits, systems and/or devices for screening the risk of schizophrenia.

Further, the blood sample is blood, serum or plasma, preferably human peripheral blood serum; the reagents include enzyme-linked immunosorbent assay reagents, immunoblotting reagents, immunoelectrophoresis reagents, tissue immunostaining reagents, and immunoprecipitation. Reagents for analysis methods, radioimmunoassay reagents, radioimmunoassay reagents, complement fixation analysis reagents, fluorescence-activated cell sorting reagents, mass analysis reagents or protein microarray reagents.

The present invention also provides a kit for screening the risk of schizophrenia, which includes reagents for detecting total cholesterol concentration, IDH2 protein expression level and/or PPARγ protein expression level in blood samples.

Further, the blood sample is blood, serum or plasma, preferably human peripheral blood serum; the reagents include enzyme-linked immunosorbent assay reagents, immunoblotting reagents, immunoelectrophoresis reagents, tissue immunostaining reagents, and immunoprecipitation. Reagents for analytical methods, radioimmunoassay reagents, radioimmunoassay reagents, complement fixation analysis reagents, fluorescence-activated cell sorting reagents, mass analysis reagents or protein microarray reagents, preferably for enzyme-linked immunosorbent assays Reagents.

The present invention also provides a system for screening the risk of schizophrenia, including the following modules:

Data acquisition module: obtain total cholesterol concentration, IDH2 protein expression level and/or PPARγ expression level in blood samples;

Database module: The database is composed of clinical characteristics of healthy humans and schizophrenia humans, total cholesterol concentration in blood samples, IDH2 protein expression level and/or PPARγ expression level data, and is randomly split into a training set and a test set;

Machine learning module: build a random forest model;

Training module: Use the training set to train the random forest model and obtain the trained random forest model;

Test module: Use the test set to verify the trained random forest model;

Result output module: Outputs the result of high or low risk of schizophrenia.

Further, the blood sample is blood, serum or plasma, preferably human peripheral blood serum; the clinical characteristics include age, gender and BMI.

The present invention also provides a method for constructing the aforementioned system, which includes the following steps:

(1) Construct a data acquisition module for inputting total cholesterol concentration, IDH2 protein expression level and/or PPARγ expression level data;

(2) Collect clinical characteristics of healthy and schizophrenic natural persons, total cholesterol concentration, IDH2 protein expression level and/or PPARγ expression level data in blood samples, and build a database module; randomly split the data in the database into training sets and test set;

(3) Use the random forest algorithm to build a random forest model and obtain a machine learning module;

(4) Construct a training module that uses the training set to analyze and train the random forest model;

(5) Build a test module that uses the test set to verify and optimize the trained random forest model;

(6) Construct an output module that outputs the calculation results of the machine learning module.

The present invention also provides a device for screening the risk of schizophrenia, including the following device:

1) Detection device: The detection device has built-in reagents for detecting the total cholesterol concentration, IDH2 protein expression level and PPARγ protein expression level in blood samples;

2) Analysis device: The analysis device has a built-in data input port for receiving the detection results of the aforementioned detection device;

The analysis device has a built-in analysis model Y=1/(1+e ^{(1.634*TC-0.00107*IDH2-0.03664*PPARγ+10.883} ), which calculates the prevalence of schizophrenia based on total cholesterol concentration, IDH2 protein expression level and PPARγ expression level Probability Y, used to determine the risk of schizophrenia.

Further, the blood sample is blood, serum or plasma, preferably human peripheral blood serum; the Y greater than 0.5 indicates a high risk of suffering from schizophrenia, and the Y less than 0.5 indicates a low risk of suffering from schizophrenia.

The present invention discovered the relationship between total cholesterol, IDH2 and PPARγ and schizophrenia. By collecting peripheral blood of healthy controls and schizophrenia patients, the changes in total cholesterol levels of each group of people were detected and analyzed by biochemical kits, and the changes of total cholesterol levels of each group of people were detected and analyzed by ELISA. Changes in IDH2 and PPARγ levels; it was found that compared with healthy controls, serum total cholesterol levels in schizophrenia patients were significantly reduced, while IDH2 and PPARγ levels were significantly increased. Furthermore, the present invention further proves the reliability and specificity of total cholesterol, IDH2 and PPARγ as joint markers for diagnosing schizophrenia and/or assessing the risk of schizophrenia by constructing a schizophrenia diagnostic model and ROC curve analysis. .

The present invention is a kit and device for simultaneously detecting total cholesterol concentration, IDH2 protein expression level and/PPARγ protein expression level in blood samples. The detection results are very consistent with the clinical diagnosis results of schizophrenia, reflecting very excellent performance. The detection method is simple, low-cost, easy to operate, and has excellent clinical application prospects.

Obviously, according to the above content of the present invention, according to the common technical knowledge and common means in the field, without departing from the above basic technical idea of the present invention, various other forms of modifications, replacements or changes can also be made.

The above contents of the present invention will be further described in detail below through specific implementation methods in the form of examples. However, this should not be understood to mean that the scope of the above subject matter of the present invention is limited to the following examples. All technologies implemented based on the above contents of the present invention belong to the scope of the present invention.

Description of the drawings

Figure 1 shows the quantitative results of total cholesterol in peripheral serum of schizophrenia patients and healthy controls.

Figure 2 is a graph showing the quantitative results of IDH2 in peripheral serum of schizophrenia patients and healthy controls.

Figure 3 is a graph showing the quantitative results of PPARγ in peripheral serum of schizophrenia patients and healthy controls.

Figure 4 shows the ROC curve results in the training set and test set of the schizophrenia diagnostic model constructed based on total cholesterol, IDH2 and PPARγ levels in the training set.

Detailed ways

The raw materials and equipment used in the present invention are all known products and are obtained by purchasing commercially available products.

Example 1. Relationship between total cholesterol, IDH2 and PPARγ levels in peripheral serum and schizophrenia

1. Clinical treatment

The study subjects were peripheral serum samples from 166 schizophrenia patients and 79 healthy controls. The diagnosis of schizophrenia was made and confirmed by two psychiatrists with extensive clinical experience based on the diagnostic criteria in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM IV), Positive and Negative Symptom Scales. (PANSS) is used to assess the severity of schizophrenia symptoms. Patients with the above mental disorders were recruited from the Department of Psychiatry, the First Affiliated Hospital of Chongqing Medical University, and samples of healthy controls were obtained from the Physical Examination Center of the First Affiliated Hospital of Chongqing Medical University. The clinical characteristics of the subjects are shown in Table 1:

Table 1: Demographic and clinical characteristics of subjects

Note: HCs: healthy people without mental illness; schizophrenia: patients with schizophrenia; mark ^"a" indicates Chi-square test; mark ^"b" indicates Mann-Whitney U test.

5 mL of median cubital venous blood was obtained from all subjects, left to stand at room temperature for 30 min, centrifuged at 1000×g for 15 min, serum was taken and aliquoted and frozen in a -80°C refrigerator.

2. Detection method

The Positive and Negative Syndrome Scale (PANSS) was used to assess the severity of schizophrenia symptoms.

Use Roche COBAS C8000 fully automatic biochemical analyzer to detect the total cholesterol content in serum samples; use Shanghai Jianglai Company's human IDH2 ELISA kit (Cat No.: JL47327) to detect the IDH2 level in serum samples according to the kit instructions. The detection of this kit The range is 100mIU/L-2400mIU/L; use the human PPARγ ELISA kit of Jiangsu Enzyme Immunoassay Company (Cat. No.: MM-13769H1) and follow the kit instructions to detect the PPARγ level in the serum sample. The detection range of the kit is 20ng/L. -480ng/L.

3. Establishment of the model of the present invention

(1) Data analysis

All data were statistically analyzed using SPSS20.0 and R 4.0 software. Data are expressed as mean ± standard error, and statistical analysis was performed using t test, chi-square test, or non-parametric Mann-Whitney U test. Differences were considered statistically significant when p < 0.05.

(2) Constructing a diagnostic model for schizophrenia

Using the random forest machine learning model, not only the method is simple and easy to operate, but also the generated schizophrenia diagnostic model has high sensitivity and specificity; the details are as follows: the research subjects are divided into training sets (healthy control, n=52; schizophrenia patients with schizophrenia, n=113) and the test set (healthy controls, n=27; patients with schizophrenia, n=53). After adjusting for age, gender and BMI, the total cholesterol, IDH2 and PPARγ levels in the training set samples were used to establish Diagnostic model:

Y＝1/(1+e ^{(1.634*TC-0.00107*IDH2-0.03664*PPARγ+10.883)} (Note: Y represents the probability of schizophrenia. If the Y value is greater than 0.5, it can be determined that the risk of schizophrenia is high. , if the Y value is less than 0.5, the risk of schizophrenia is judged to be low; TC represents the total cholesterol concentration measured in peripheral serum, IDH2 represents the IDH2 level measured in peripheral serum, PPARγ represents the IDH2 level measured in peripheral serum), and in Test and verify the test set samples; use GraphPad Prism 8.3 software to analyze the receiver operating characteristics of the model and draw the ROC curve. The area under the ROC curve (AUC) of 0.9-1 indicates excellent diagnostic performance.

4. Results

The results of total cholesterol content in peripheral serum of schizophrenia patients and healthy controls are shown in Table 2 and Figure 1. The results of IDH2 levels in peripheral serum of schizophrenia patients and healthy controls are shown in Table 3 and Figure 2. Schizophrenia patients The results of PPARγ levels in peripheral serum of patients and healthy controls are shown in Table 4 and Figure 3. The diagnostic efficiency analysis of the diagnostic model established based on serum total cholesterol, IDH2 and PPARγ levels is shown in Figure 4.

Table 2 Results of total cholesterol content in serum of schizophrenia patients and healthy controls

HCs Schizophrenia p value Sample size(n) 79 166 - Total cholesterol level mean ± standard error (mM) 5.91±0.14 3.93±0.08 1.37E-29

Note: HCs: healthy people without mental illness; schizophrenia: patients with schizophrenia;

As can be seen from Table 2 and Figure 1, the total cholesterol level in the serum of patients with schizophrenia is significantly lower than that of healthy controls without mental illness, and the difference between the two groups is very significant (p value is 1.37E-29).

Table 3 Results of serum IDH2 levels in schizophrenia patients and healthy controls

HCs Schizophrenia p value Sample size(n) 79 166 - Mean ± standard error (mIU/L) 1.62±4.21 1.93±4.89 5.22E-05

As can be seen from Table 3 and Figure 2, the serum IDH2 level of patients with schizophrenia is significantly higher than that of healthy controls without mental illness, and the difference between the two groups is very significant (p value is 5.22E-05).

Table 4 Results of PPARγ levels in serum of schizophrenia patients and healthy controls

HCs Schizophrenia p value Sample size(n) 79 166 - Mean ± standard error (ng/L) 4.51±4.27 4.99±3.19 3.56E-22

As can be seen from Table 4 and Figure 3, the PPARγ level in the serum of patients with schizophrenia was significantly higher than that of healthy controls without mental illness, and the difference between the two groups was very significant (p value was 3.56E-22).

Figure 4: The area under the ROC curve of the model in the training set is 0.9489, and the area under the ROC curve of the model in the test set is 0.9609, both between 0.9-1, indicating that the model is constructed based on the levels of total cholesterol, IDH2 and PPARγ in the training set. Receiver operating characteristic results were excellent. It is confirmed that total cholesterol, IDH2 and PPARγ can be used as joint diagnostic markers for schizophrenia, providing an effective basis for clinical diagnosis of schizophrenia.

Experimental results show that total cholesterol, IDH2 and PPARγ can be used to assist in the clinical diagnosis of schizophrenia. And through model establishment, it was confirmed that total cholesterol, IDH2 and PPARγ can be used as joint markers of schizophrenia, providing an effective basis for the diagnosis of schizophrenia.

In summary, the kit and risk screening system of the present invention can screen the risk of schizophrenia in the population to be tested by detecting the levels of total cholesterol, IDH2 and PPARγ in peripheral serum: if the total cholesterol level is low and IDH2 and PPARγ If the protein level of IDH2 is high, the risk of schizophrenia is high; if the total cholesterol level is high and the protein levels of IDH2 and PPARγ are low, the risk of schizophrenia is low. In addition, by constructing a model, the present invention confirms that total cholesterol, IDH2 and PPARγ can be used as joint diagnostic markers for schizophrenia, providing an effective basis for assisting clinical diagnosis of schizophrenia, and has good clinical application prospects.

Claims (10)

1. Use of idh2 protein, total cholesterol and/or ppary protein for the preparation of a marker for risk screening for schizophrenia.
2. 2. Use of a reagent for detecting total cholesterol concentration, IDH2 protein expression level and/or pparγ protein expression level in a blood sample for the preparation of a kit, system and/or device for screening for risk of developing schizophrenia.
3. 3. Use according to claim 2, wherein the blood sample is blood, serum or plasma, preferably human peripheral blood serum; the reagent includes a reagent for enzyme-linked immunosorbent assay, a reagent for immunoblotting, a reagent for immunoelectrophoresis, a reagent for tissue immunostaining, a reagent for immunoprecipitation analysis, a reagent for radioimmunoassay, a reagent for complement fixation analysis, a reagent for fluorescence-activated cell sorting, a reagent for mass analysis, or a reagent for protein microarray.
4. 4. A kit for screening for the risk of developing schizophrenia, characterized in that it comprises reagents for detecting the concentration of total cholesterol, the expression level of IDH2 protein and/or the expression level of pparγ protein in a blood sample.
5. 5. Kit according to claim 4, wherein the blood sample is blood, serum or plasma, preferably human peripheral blood serum; the reagent includes a reagent for enzyme-linked immunosorbent assay, a reagent for immunoblotting, a reagent for immunoelectrophoresis, a reagent for tissue immunostaining, a reagent for immunoprecipitation analysis, a reagent for radioimmunoassay, a reagent for complement fixation analysis, a reagent for fluorescence-activated cell sorting, a reagent for mass analysis, or a reagent for protein microarray, preferably a reagent for enzyme-linked immunosorbent assay.
6. 6. A system for screening for risk of developing schizophrenia, comprising: the device comprises the following modules:

   and a data acquisition module: obtaining the total cholesterol concentration, IDH2 protein expression level and/or PPARgamma expression level in the blood sample;

   a database module: the clinical characteristics of healthy human bodies and schizophrenic human bodies and the total cholesterol concentration in blood samples are used for forming a database by the IDH2 protein expression level and/or PPARgamma expression level data, and the database is randomly split into a training set and a testing set;

   a machine learning module: constructing a random forest model;

   training module: training the random forest model by using a training set to obtain a trained random forest model;

   and a testing module: verifying the trained random forest model by using the test set;

   and a result output module: outputting the result of high or low risk of developing schizophrenia.
7. 7. The system of claim 6, wherein the blood sample is blood, serum or plasma, preferably human peripheral blood serum; the clinical characteristics include age, gender and body mass index BMI.
8. 8. A method of constructing a system as claimed in claim 6 or 7, comprising the steps of:

   (1) Constructing a data acquisition module for inputting data of total cholesterol concentration, IDH2 protein expression level and/or PPARgamma expression level;

   (2) Collecting clinical characteristics of natural people with healthy and schizophrenia and total cholesterol concentration in blood samples, IDH2 protein expression level and/or PPARgamma expression level data, and constructing a database module; randomly splitting data in a database into a training set and a testing set;

   (3) Constructing a random forest model by adopting a random forest algorithm to obtain a machine learning module;

   (4) Constructing a training module for analyzing and training the random forest model by adopting a training set;

   (5) Constructing a test module for verifying and optimizing the trained random forest model by using the test set;

   (6) An output module that outputs the calculation result of the machine learning module is constructed.
9. 9. A device for screening for risk of developing schizophrenia, characterized in that: comprises the following devices:

   1) A detection device; the detection device is internally provided with reagents for detecting the total cholesterol concentration, the IDH2 protein expression level and the PPARgamma protein expression level in a blood sample;

   2) Analysis device: the analysis device is internally provided with a data input port for receiving the detection result of the detection device;

   the analysis model Y=1/(1+e) is built in the analysis device ^{(1.634*TC-0.00107*IDH2-0.03664*PPARγ+10.883} ) Based on the total cholesterol concentration, IDH2 protein expression level and pparγ expression level, a schizophrenia disease probability Y is calculated for discriminating the risk of developing schizophrenia.
10. 10. The device according to claim 9, wherein the blood sample is blood, serum or plasma, preferably human peripheral blood serum; a Y greater than 0.5 indicates a high risk of developing schizophrenia, and a Y less than 0.5 indicates a low risk of developing schizophrenia.