A set of markers for predicting the efficacy of ketamine in the treatment of refractory depression and its application

Abstract

The present invention provides a group of markers for predicting the efficacy of ketamine in treating refractory depression and their applications, belonging to the field of molecular biomedical technology. The present invention provides a group of markers for predicting the efficacy of ketamine in treating refractory depression, the markers comprising at least two of A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 proteins or at least two of the protein encoding genes. The markers for predicting the efficacy of ketamine in treating refractory depression of the present invention have high accuracy, sensitivity and specificity for predicting the efficacy of ketamine in treating refractory depression, and can judge whether the subject is an effective patient for ketamine treatment early, accurately and quickly, and apply them to the clinical treatment of refractory depression.

Description

Technical Field

[0001] The present invention belongs to the technical field of molecular biomedicine, and in particular relates to a group of markers for predicting the efficacy of ketamine in treating refractory depression and applications thereof. Background Art

[0002] Depression is a common mental disorder, which is often chronic and recurrent, and has a great impact on the social function of patients. The World Health Organization (WHO) Global Burden of Disease Collaborative Study predicts that by 2020, depression will become the second largest source of disease burden after coronary heart disease. Most patients with depression respond to drug treatment and psychotherapy, but 40% of patients do not respond to various treatments, which is commonly known as refractory depression (TRD). TRD may be related to personality disorders, comorbid anxiety disorders, delayed initial treatment, substance abuse, family history, onset time and depression type. Some studies have found that TRD has a higher tendency to commit suicide, is more likely to relapse, has a poor prognosis, has a heavier social burden, and has a higher disease burden. There is currently no specific drug for the treatment of refractory depression.

[0003] Ketamine is an NMDA receptor antagonist with a wide range of effects in the population, including analgesia, anesthesia, hallucinations, dissociative effects, increased blood pressure and bronchial dilation. Ketamine is mainly used for the induction and maintenance of general anesthesia. Other uses include sedation, analgesia and treatment of bronchospasm in intensive care. Ketamine is also used to treat depression. Studies have shown that ketamine is not effective for all types of depression, and some patients with refractory depression have poor or no effect when treated with ketamine. Ketamine itself has significant side effects, such as psychiatric side effects such as anxiety, cardiovascular side effects such as increased blood pressure and increased heart rate, and nervous system side effects such as headache and dizziness. Therefore, judging the effectiveness of ketamine in treating refractory depression before treatment can better provide treatment strategies and reduce the side effects of ketamine caused by medication discomfort. However, there are currently no clinical molecular markers that can accurately and effectively predict the efficacy of ketamine in treating refractory depression. Summary of the invention

[0004] In view of the above problems, the purpose of the present invention is to provide a group of markers for predicting the efficacy of ketamine in treating refractory depression and their application, so as to judge whether the subject is a refractory depression patient suitable for ketamine treatment at an early, accurate and rapid rate.

[0005] To achieve the above object, the technical solution adopted by the present invention is: a group of markers for predicting the efficacy of ketamine in treating refractory depression, the markers including at least two of A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 proteins or at least two of the protein encoding genes. The inventors of the present application have found through a large number of experimental screening and verification that A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 proteins are differentially expressed in patients with refractory depression who are effective and ineffective in ketamine treatment. The above-mentioned marker combination is used in the personalized treatment of refractory depression, which has high accuracy, sensitivity and specificity, and can judge whether the subject is an effective patient for ketamine treatment early, accurately and quickly, and is applied to the clinical treatment of refractory depression.

[0006] As a preferred embodiment of the marker for predicting the efficacy of ketamine in treating refractory depression according to the present invention, A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 are the accession numbers of the proteins in the UniProt database.

[0007] The present invention also provides use of the marker in preparing a product for predicting the efficacy of ketamine in treating refractory depression.

[0008] The present invention also provides the use of a reagent for detecting A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 in a sample in the preparation of a product for predicting the efficacy of ketamine in treating refractory depression.

[0009] As a preferred embodiment of the application of the present invention, the reagent includes at least one of the following (a)-(e):

[0010] (a) a reagent for detecting the protein expression level of A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 or P0DOX3;

[0011] (b) probes for detecting genes encoding A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 or P0DOX3;

[0012] (c) primers for amplifying genes encoding A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 or P0DOX3;

[0013] (d) nucleic acid aptamers for detecting genes encoding A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 or P0DOX3;

[0014] (e) A binding agent that specifically binds to A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 or P0DOX3 protein.

[0015] As a preferred embodiment of the application described in the present invention, the binding agent includes antibodies, antibody functional fragments, conjugated antibodies, and peptides that specifically bind to A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 proteins.

[0016] As a preferred embodiment of the application of the present invention, the sample includes body fluid, tissue or excrement. More preferably, the body fluid includes blood, extracellular fluid, tissue fluid, lymph fluid, cerebrospinal fluid or aqueous humor.

[0017] The present invention also provides a product for predicting the efficacy of ketamine in treating refractory depression, comprising a reagent for detecting at least two of A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 proteins or at least two of the protein encoding genes.

[0018] As a preferred embodiment of the product of the present invention, it includes a kit, a chip, a test paper, and a high-throughput detection platform. More preferably, the kit includes an ELISA kit, an immunoblotting detection kit, an immunohistochemistry detection kit, and an electrochemiluminescence detection kit.

[0019] The present invention also provides a system for predicting the efficacy of ketamine in treating refractory depression, the system comprising a detection component for detecting the expression levels of A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 proteins and a result judgment component for judging whether the subject is a refractory depression patient suitable for ketamine treatment. Furthermore, the detection component includes an ELISA kit, an immunoblot detection kit, a flow cytometric analysis kit, an immunohistochemical detection kit, an immunochromatographic detection kit, an electrochemiluminescent detection kit, an ELISA detection device, an immunoblot detection device, a flow cytometric analysis device, an immunohistochemical detection device, an immunochromatographic detection device, an electrochemiluminescent detection device, and a mass spectrometry analysis platform; the result judgment component contains an input module, an analysis module, and an output module, wherein the input module is used to input the expression levels of A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70, and P0DOX3, and the analysis module is used to analyze whether the subject is suitable for ketamine treatment according to the expression levels of A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70, and P0DOX3; the output module is used to output the analysis results of the analysis module.

[0020] The beneficial effects of the present invention are as follows: the present invention provides a group of markers for predicting the efficacy of ketamine in treating refractory depression and applications thereof. The present invention provides a group of markers for predicting the efficacy of ketamine in treating refractory depression. The marker combination has high accuracy, sensitivity and specificity in predicting the efficacy of ketamine in treating refractory depression, and can accurately and quickly determine whether a subject is an effective patient for ketamine treatment at an early stage, and can be applied to the clinical treatment of refractory depression. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 The log2 expression graph of A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70, and P0DOX3 in the samples;

[0022] Figure 2 The ROC curves of A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, and B4DG70 in the samples are shown;

[0023] Figure 3 is the ROC curve diagram of P0DOX3 protein in the sample;

[0024] Figure 4ROC curve for the combination of A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 in predicting the therapeutic efficacy of ketamine. DETAILED DESCRIPTION

[0025] In order to more concisely and clearly demonstrate the technical solution, purpose and advantages of the present invention, the technical solution of the present invention is described in detail below in conjunction with specific embodiments and drawings.

[0026] Example 1

[0027] In this example, markers related to the efficacy of ketamine in treating refractory depression were screened, and the specific method is as follows:

[0028] (1) Sample collection: Select subjects and judge their condition based on the scale score, which is scored by professional physicians. Collect venous blood from patients before treatment. Then start taking medication (ketamine) for treatment. According to the Hamilton depression scale (Hamilton depression scale, HAMD) score reduction rate of patients after 2 weeks of ketamine treatment as the efficacy evaluation result, they are divided into ketamine treatment effective group (HAMD 2-week reduction rate ≥ 50%) and ineffective group (HAMD 2-week reduction rate <50%). The effective group is considered to be patients who are sensitive to the ketamine treatment regimen, and the ineffective group is considered to be patients who are resistant to the ketamine treatment regimen. In the data set, effective: ineffective = 32:28 (ratio of people).

[0029] (2) Detection of protein expression level: Blood samples from the effective group and the ineffective group were subjected to mass spectrometry analysis to detect protein expression levels. The protein expression data were sorted, proteins that were not quantified in more than 80% of the samples were eliminated, and then the null value was replaced with the minimum value.

[0030] (3) The 60 samples were randomly divided into a model training set (42 cases) and a model validation set (18 cases) in a ratio of 7:3. The training set was used to establish a random forest prediction model, and the validation set was used to determine the predictive effect of the established model on the efficacy of ketamine in the treatment of refractory depression. The Boruta package of R language was run 100 times to screen out important proteins, including 42 protein types such as A0N5G3, P01817, and B7Z550. The random forest model of the randomForst package of R language was then used with a five-fold cross validation and repeated 100 times. The results showed that the prediction effect of the training set had a 100% accuracy rate. The model found that the effectiveness of ketamine treatment can be determined by seven proteins, including whether A0N5G3, Q5EFE5, A8K6C9, and B4DG70 proteins are underexpressed, and whether P01817, B7Z550, and P0DOX3 are overexpressed. After the model was obtained, it was verified in the validation set. The accuracy of the model in the validation set was about 95%, and the ROC curve was drawn. Compared with the patients who did not respond to ketamine treatment, the expression levels of A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 proteins in the effective patients were different, among which A0N5G3 (log2fc=-0.355, p<0.05), Q5EFE5 (log2fc=-1.418, p<0.05), A8K6C9 (log2fc=-0.199, p<0.05) and P0DOX3 proteins in the effective patients were different. 0.01) and B4DG70 (log2fc=-0.325, p<0.05) protein expression levels were lower in the effective group and had significant differences. The expression levels of some proteins, namely P01817 (log2fc=0.504, p>0.05), B7Z550 (log2fc=-0.148, p>0.05) and P0DOX3 (log2fc=0.523, p>0.05) had no difference between the two groups. Figure 1 shown.

[0031] Example 2 Diagnostic Efficacy Verification

[0032] This example verifies the diagnostic efficacy of the markers screened in Example 1. The specific method is as follows: Use the R package "pROC" and SPSS (version 25.0) to draw the receiver operating curve (ROC), analyze the AUC value, sensitivity and specificity, and judge the diagnostic efficacy of the indicators alone or in combination. When judging the diagnostic efficacy of the combination of indicators, the expression level of each protein is subjected to logistics regression, and the probability of whether each individual is effective for ketamine treatment is calculated through the fitted regression curve, and different probability division thresholds are determined. According to the determined probability division thresholds, the sensitivity, specificity and accuracy of the combined detection scheme are calculated. The results are shown in Tables 1 and Figures 2 to 4 As shown. Figure 4 It can be seen that the AUC for predicting the efficacy of ketamine in the treatment of refractory depression using the combination of A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 is 0.948, indicating that the prediction model established by this marker combination has a good prediction effect.

[0033] Table 1

[0034]

[0035]

[0036] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the essence and scope of the technical solution of the present invention.

Claims

1. A set of markers for predicting the efficacy of ketamine in the treatment of refractory depression, characterized in that: The markers are a combination of A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 proteins; A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 are the accession numbers of proteins in the UniProt database.

2. Use of a reagent for detecting the expression levels of A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 proteins in a sample in the preparation of a product for predicting the efficacy of ketamine in the treatment of refractory depression; A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 are the registration numbers of the proteins in the UniProt database.

3. The use according to claim 2, characterized in that: The sample is blood.

4. A product for predicting the efficacy of ketamine in treating refractory depression, characterized in that: A reagent for detecting the expression level of A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 proteins; A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 are the accession numbers of proteins in the UniProt database.

5. The product according to claim 4, characterized in that Including test kits, chips, test strips, and high-throughput detection platforms.

6. A system for predicting the efficacy of ketamine in treating refractory depression, characterized in that: The system includes a detection component for detecting the expression levels of A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 proteins and a result judgment component for judging whether the subject is a patient with refractory depression suitable for ketamine treatment; A0N5G3, P01817, B7Z550, Q5EFE5, A8K6C9, B4DG70 and P0DOX3 are the accession numbers of proteins in the UniProt database.

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