Method, system and equipment for predicting depression and treatment effect thereof

Abstract

The invention discloses a method, a system and equipment for predicting depression and a treatment effect thereof. According to the method for predicting the depression / predicting the depression treatment effect / selecting the depression treatment scheme, the risk that the to-be-detected sample suffers from the depression can be well predicted by detecting the level of the MMP3 by means of a computer system and equipment, the depression treatment effect can be well predicted, the depression treatment scheme can be well selected, and the method is suitable for popularization and application. The invention provides a new direction and means for early treatment and effective treatment of depression, and has more practical significance for clinical guidance of depression.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent medical treatment, and specifically relates to a method, system and device for predicting depression and its treatment effect. Background Art

[0002] Depression (also known as melancholy or depressive disorder) is characterized by a significant and persistent low mood and is the main type of mood disorder. Clinically, it can be seen that the low mood is disproportionate to the situation. The depression of emotions can range from melancholy to grief, inferiority and depression, and even pessimism and world-weariness. There may be suicidal attempts or behaviors; even stupor; some cases have obvious anxiety and motor agitation; severe cases may have psychotic symptoms such as hallucinations and delusions. Each attack lasts for at least 2 weeks, and even several years for the elderly. Most cases tend to relapse. Most attacks can be relieved, and some may have residual symptoms or become chronic.

[0003] Currently, there are no objective biomarkers for diagnosing depression and evaluating the efficacy of treatment, which leads to patients not believing that they have depression and not actively seeking treatment. Although some patients are willing to receive a certain treatment, the treatment is not suitable for the patient, resulting in poor or even ineffective treatment. Delayed treatment leads to an increase in mental disability and suicide.

[0004] In summary, with the increase in the number of people suffering from depression, there is an urgent need for objective diagnostic methods for depression and methods to predict the efficacy of treatment. Summary of the invention

[0005] To overcome the deficiencies of the prior art, the present invention provides a method, system and device for predicting depression and its treatment effect.

[0006] To achieve the above purpose, the present invention adopts the following technical solution.

[0007] A first aspect of the present invention provides a method for predicting depression / predicting the effect of depression treatment / selecting a depression treatment plan, the method comprising: Obtain target gene expression data of the sample to be tested; Predicting whether the sample to be tested suffers from depression / predicting the treatment effect of a patient with depression / a classification result of whether to select the treatment plan based on the target gene expression data, wherein the target gene is selected from MMP3; The samples to be tested include samples of suspected depression or samples of depression patients who have received treatment or depression patients who are to receive treatment.

[0008] Furthermore, classification prediction is performed based on the expression data of the target gene to obtain a classification result of whether the sample to be tested suffers from depression. If the level of the target gene is low, the classification result is obtained that the sample to be tested suffers from depression. If the level of the target gene is high, the classification result is obtained that the sample to be tested does not suffer from depression.

[0009] Furthermore, classification prediction is performed based on the expression data of the target gene to obtain a classification result of the therapeutic effect of the sample to be tested. If the level of the target gene increases, a classification result is obtained that the sample to be tested has a therapeutic effect. If the level of the target gene does not increase, a classification result is obtained that the sample to be tested does not have a therapeutic effect.

[0010] Further, a treatment regimen is selected based on the expression data of the target gene. If the level of the target gene increases, a classification result of selecting the treatment regimen is obtained. If the level of the target gene does not increase, a classification result of not selecting the treatment regimen is obtained.

[0011] A second aspect of the present invention provides a system for predicting depression, the system comprising: An acquisition unit is used to acquire target gene expression data of the sample to be tested, wherein the target gene is selected from MMP3; Classification unit: Perform classification prediction based on the expression data of the target gene to obtain a classification result of whether the sample to be tested suffers from depression. If the level of the target gene is low, the classification result of the sample to be tested suffering from depression is obtained; if the level of the target gene is high, the classification result of the sample to be tested not suffering from depression is obtained.

[0012] A third aspect of the present invention provides a system for predicting the therapeutic effect of depression, the system comprising: An acquisition unit is used to acquire target gene expression data of the sample to be tested, wherein the target gene is selected from MMP3; Classification unit: Perform classification prediction based on the expression data of the target gene to obtain a classification result of the therapeutic effect of the sample to be tested. If the level of the target gene increases, the classification result that the sample to be tested has a therapeutic effect is obtained. If the level of the target gene does not increase, the classification result that the sample to be tested does not have a therapeutic effect is obtained.

[0013] A fourth aspect of the present invention provides a system for selecting a treatment plan for depression, the system comprising: An acquisition unit is used to acquire target gene expression data of the sample to be tested, wherein the target gene is selected from MMP3; Classification unit: Select a treatment plan based on the expression data of the target gene. If the level of the target gene increases, a classification result of selecting the treatment plan is obtained. If the level of the target gene does not increase, a classification result of not selecting the treatment plan is obtained.

[0014] A fifth aspect of the present invention provides a computer device, the computer device comprising: Memory: used to store program instructions; Processor: calling program instructions, which, when executed, are used to execute the steps of the method described in the first aspect of the present invention.

[0015] A sixth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the first aspect of the present invention.

[0016] A seventh aspect of the present invention provides use of a reagent for detecting the expression level of MMP3 in the preparation of a product for diagnosing depression.

[0017] Furthermore, the reagent is selected from a probe that specifically recognizes the MMP3 gene, a primer that specifically amplifies the MMP3 gene, or a binding agent that specifically binds to a protein encoded by the MMP3 gene.

[0018] Furthermore, the primer or probe is labeled with a labeling substance.

[0019] Furthermore, the labeling substance includes a fluorescent substance, a radioactive isotope or an enzyme.

[0020] Furthermore, the product includes a chip, a test paper, a test kit or a nucleic acid membrane strip.

[0021] Furthermore, the chip includes a gene chip and a protein chip.

[0022] Furthermore, the kit includes a gene detection kit and a protein detection kit.

[0023] Furthermore, the kit also includes instructions.

[0024] Furthermore, the kit also includes a buffer solution.

[0025] Advantages and beneficial effects of the present invention: The present application discloses a method for predicting depression / predicting the effect of depression treatment / selecting a treatment plan for depression. With the help of a computer system and equipment, the method can well predict the risk of depression in a sample to be tested by detecting the level of MMP3. It can also well predict the effect of depression treatment and select a treatment plan for depression, providing a new direction and means for the early treatment and effective treatment of depression, and is more practical for the clinical guidance of depression. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic flow chart of the method provided by the present invention; Figure 2 It is a schematic flow chart of the system provided by the invention; Figure 3 is a schematic diagram of a computer device provided by the present invention; Figure 4 It is the expression trend and visualization diagram of MMP3 gene in normal samples and patients with depression; Figure 5 It is the expression trend and visualization diagram of the decrease in serum cortisol caused by music therapy; Figure 6 is the expression trend and visualization diagram of the fact that drug treatment did not lead to a decrease in serum cortisol; Figure 7 is a schematic diagram of Luminex analysis and visualization of the increase in serum MMP3 levels caused by music therapy; Figure 8 is a schematic diagram of Luminex analysis and visualization showing that drug treatment did not result in an increase in serum MMP3 levels; Fig. 9 ELISA analysis and visualization schematic diagram of the increase in serum MMP3 levels caused by music therapy; | Fig.10 Schematic diagram of ELISA analysis and visualization showing that drug treatment did not result in an increase in serum MMP3 levels. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0028] In some of the processes described in the specification and claims of the present invention and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to be different types.

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0030] Figure 1 The present invention provides a method for predicting depression / predicting the effect of depression treatment / selecting a depression treatment plan. Specifically, the method comprises the following steps: 101: Obtain target gene expression data of the sample to be tested.

[0031] In some embodiments, the sample to be tested or the person to be tested or the subject refers to any animal (e.g., mammal), including but not limited to humans, non-human primates, rodents, etc., which will be the recipient of a specific treatment. In a preferred embodiment, the sample to be tested is a human.

[0032] In some embodiments, the sample includes a sample suspected of depression or a patient with depression who has received treatment or a patient with depression who is to be treated.

[0033] 102: Predicting whether the sample to be tested suffers from depression / predicting the treatment effect of a patient with depression / a classification result of whether to select the treatment plan based on the target gene expression data, wherein the target gene is selected from MMP3.

[0034] Classification prediction is performed based on the expression data of the target gene to obtain a classification result of whether the sample to be tested suffers from depression. If the level of the target gene is low, the classification result is obtained that the sample to be tested suffers from depression. If the level of the target gene is high, the classification result is obtained that the sample to be tested does not suffer from depression.

[0035] In some embodiments, Figure 4As shown, the expression of MMP3 in the test sample (which can be a sample suspected of depression) is extracted, and the expression trend of MMP3 in the healthy control and the test sample is statistically analyzed and visualized. The results show that the level of MMP3 in the test sample is significantly lower than that in the healthy control.

[0036] Specific experimental methods: Luminex detection of serum cytokines in healthy controls and clinical patients The serum of healthy controls (n=23) and patients with depression (n=61) was obtained from the Third Center of PLA General Hospital and 984 Hospital. The cytokine levels were detected using Luminex kits from R&D. The concentrations were calculated according to the standard curve.

[0037] The inclusion criteria for the healthy control group were: adults aged 18-80 years, without mood disorders, acute diseases, or severe cardiopulmonary diseases. The inclusion criteria for the depression group were: adults aged 18-80 years, with a clear diagnosis of mood disorders, acute diseases, or severe cardiopulmonary diseases.

[0038] Exclusion criteria: life-threatening condition.

[0039] Classification prediction is performed based on the expression data of the target gene to obtain a classification result of the therapeutic effect of the sample to be tested. If the level of the target gene increases, a classification result is obtained that the sample to be tested has a therapeutic effect. If the level of the target gene does not increase, a classification result is obtained that the sample to be tested does not have a therapeutic effect.

[0040] A treatment regimen is selected based on the expression data of the target gene. If the level of the target gene increases, a classification result of selecting the treatment regimen is obtained. If the level of the target gene does not increase, a classification result of not selecting the treatment regimen is obtained.

[0041] In some embodiments, Figure 5-10 As shown, Luminex and ELISA were used to detect the levels of cortisol or MMP3 in the test samples (which could be samples of patients with depression who had received treatment or patients with depression who were to be treated), and the expression trends of cortisol or MMP3 in the test samples were statistically analyzed and visualized. The results showed: 1) Changes in serum cortisol levels in patients with depression after treatment: 25 patients with clinical depression were randomly assigned to a drug treatment group (n=10) and a music therapy group (n=15). The drug treatment group took oral fluoxetine, 20 mg per day, a single dose. In addition to drug treatment, the music therapy group listened to Mozart's "Symphony No. 40 in G Minor" K.550 once a day for about half an hour. Serum ELISA analysis was performed before and after 3 weeks of treatment, and it was found that music therapy could reduce serum cortisol ( Figure 5 , n=15), while drug treatment failed to reduce serum cortisol ( Figure 6 , n=10); 2) Luminex reveals changes in serum MMP3 levels in patients with depression after treatment: The serum of the above clinical depression patients was also analyzed by Luminex for MMP3 levels, and it was found that music therapy can increase serum MMP3 levels ( Figure 7 , n=15), while drug treatment could not increase serum MMP3 levels ( Figure 8 , n=10); 3) ELISA confirmed the changes in serum MMP3 levels in patients with depression after treatment: In order to prevent the non-specificity of antibody detection, the serum of the above clinical depression patients was also analyzed by ELISA for MMP3 levels. Because they are different symbiotic products, completely different antibody pairs are used. It was found that music therapy can increase serum MMP3 levels ( Fig. 9 , n=15), while drug treatment could not increase serum MMP3 levels ( Fig.10 , n=10).

[0042] Specific experimental methods: 1) Luminex detection of serum cytokines in clinical patients The patient serum was obtained from the Third Center of PLA General Hospital and 984 Hospital, and the cytokine levels were detected using Luminex kits from R&D Company. The concentrations were calculated according to the standard curve.

[0043] 2) Clinical patient serum MMP3 ELISA detection The patient serum was obtained from the Third Center of PLA General Hospital and 984 Hospital, and the MMP3 level was detected using the ELISA kit (SEK10467-5) of Sino Biological Company. The OD450 value was read.

[0044] 3) Serum cortisol testing in clinical patients The patient serum was obtained from the Third Center of PLA General Hospital and 984 Hospital. The cortisol level was detected using the ELISA kit (ab108665) from Abcam. The concentration was calculated according to the standard curve.

[0045] Figure 2 The present invention provides a system for predicting depression / predicting the effect of depression treatment / selecting a depression treatment plan, and the system specifically includes: A system for predicting depression, the system comprising: Acquisition unit: used to acquire target gene expression data of the sample to be tested, wherein the target gene is selected from MMP3.

[0046] Classification unit: Perform classification prediction based on the expression data of the target gene to obtain a classification result of whether the sample to be tested suffers from depression. If the level of the target gene is low, the classification result of the sample to be tested suffering from depression is obtained; if the level of the target gene is high, the classification result of the sample to be tested not suffering from depression is obtained.

[0047] A system for predicting the effect of depression treatment, the system comprising: Acquisition unit: used to acquire target gene expression data of the sample to be tested, wherein the target gene is selected from MMP3.

[0048] Classification unit: Perform classification prediction based on the expression data of the target gene to obtain a classification result of the therapeutic effect of the sample to be tested. If the level of the target gene increases, the classification result that the sample to be tested has a therapeutic effect is obtained. If the level of the target gene does not increase, the classification result that the sample to be tested does not have a therapeutic effect is obtained.

[0049] A system for selecting a treatment for depression, the system comprising: Acquisition unit: used to acquire target gene expression data of the sample to be tested, wherein the target gene is selected from MMP3.

[0050] Classification unit: Select a treatment plan based on the expression data of the target gene. If the level of the target gene increases, a classification result of selecting the treatment plan is obtained. If the level of the target gene does not increase, a classification result of not selecting the treatment plan is obtained.

[0051] In some embodiments, the system includes a processor, which may be a single-core or multi-core processor or more than one processor for parallel processing. The system also includes a memory (e.g., random access memory, read-only memory, flash memory), an electronic storage unit (e.g., a hard disk), a communication interface (e.g., a network adapter) for communicating with one or more other systems, and peripheral devices, such as cache memory, other memory, data storage, and / or an electronic display adapter. The memory, electronic storage unit, communication interface, and peripheral devices communicate with the processor via a communication bus (solid line), such as a motherboard. The storage unit may be a data storage unit (or data repository) for storing data. The system may be operably coupled to a computer network by means of a communication interface. The network may be the Internet, an intranet and / or an extranet, or an intranet and / or an extranet communicating with the Internet. In some cases, the network is a communication and / or data network. The network may include one or more computer servers, which may support distributed computing, such as cloud computing. In some cases, with the aid of the system, the network may implement a peer-to-peer network, which may enable a device coupled to the system to operate as a client or server.

[0052] In some embodiments, the processor may execute a series of machine-readable instructions, which may be embodied in a program or software. The instructions may be stored in a memory location, such as a memory. The instructions may be directed to the processor, which may then program or otherwise configure the processor to implement the method of the present invention. Examples of operations performed by the processor may include reading, decoding, executing, and writing back.

[0053] In some implementations, the processor may be part of a circuit such as an integrated circuit, and one or more other components of the system may be included in the circuit, which in some cases is an application specific integrated circuit.

[0054] In some embodiments, the electronic storage unit can store files, such as drivers, libraries, and saved programs. The electronic storage unit can store user data, such as user preferences and user programs. In some cases, the system can include one or more additional data storage units that are external to the computer system, such as located on a remote server that communicates with the system via an intranet or the Internet.

[0055] In some embodiments, the system can communicate with one or more remote computer systems via a network. For example, the system can communicate with a remote computer system of a user (e.g., a physician). Examples of remote computer systems include personal computers, tablet or tablet PCs, phones, smart phones, or personal digital assistants. Users can access the system via a network.

[0056] Figure 3 A computer device provided by the present invention comprises: Memory: used to store program instructions.

[0057] Processor: calls program instructions, and when the program instructions are executed, it is used to execute the steps of the above method.

[0058] The present invention also provides a computer-readable storage medium on which a computer program is stored, and the computer program implements the steps of the above method when executed by a processor.

[0059] In some embodiments, the computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface storage, optical disk, or CD-ROM; or may be various devices including one or any combination of the above memories.

[0060] In some embodiments, executable instructions may be in the form of a program, software, software module, script, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0061] As an example, executable instructions may, but need not, correspond to a file in a file system, may be stored as part of a file storing other programs or data, such as in one or more scripts in a HyperText Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files storing one or more modules, subroutines, or code portions).

[0062] By way of example, executable instructions may be deployed to be executed on one computing device, or on multiple computing devices located at one site, or on multiple computing devices distributed across multiple sites and interconnected by a communication network.

[0063] In some embodiments, executable instructions can be completed by instructing related hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the process of the embodiments of the above methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0064] The present invention provides application of a reagent for detecting the expression level of MMP3 in preparing a product for diagnosing depression.

[0065] The reagent is selected from a probe that specifically recognizes the MMP3 gene, a primer that specifically amplifies the MMP3 gene, or a binding agent that specifically binds to a protein encoded by the MMP3 gene.

[0066] In some embodiments, a probe refers to a molecule that can bind to a specific sequence or subsequence or other part of another molecule. Unless otherwise indicated, a probe generally refers to a polynucleotide probe that can bind to another polynucleotide (often referred to as a target polynucleotide) through complementary base pairing. Depending on the stringency of the hybridization conditions, the probe can bind to a target polynucleotide that lacks complete sequence complementarity with the probe. The probe can be directly or indirectly labeled, including primers. Hybridization methods include, but are not limited to, solution phase, solid phase, mixed phase, or in situ hybridization assays.

[0067] In some embodiments, a primer refers to a short nucleic acid sequence, which, as a nucleic acid sequence having a short free 3' terminal hydroxyl group (free 3' hydroxyl group), can form a base pair with a complementary template and serve as a starting point for replicating the template.

[0068] The primer or probe is labeled with a labeling substance.

[0069] In some embodiments, label refers to the composition that can produce the detectable signal indicating the presence of target polynucleotide in the assay sample. Suitable label includes but is not limited to radioisotope, nucleotide chromophore, enzyme, substrate, fluorescent molecule, chemiluminescent part, magnetic particle, bioluminescent part. Therefore, label is any composition that can be detected by device or method, including but not limited to spectrum, photochemistry, biochemistry, immunochemistry, electricity, optics, chemical detection device or any other suitable device. In some embodiments, label can be detected visually without the aid of device. Label is used to refer to any chemical group or part with detectable physical property or can cause chemical group or part to show any compound of detectable physical property, such as catalytic substrate conversion into detectable product enzyme. Label also encompasses the compound that suppresses the performance of specific physical property. Label can also be a compound as a member of a pair of binding, and another member thereof has detectable physical property.

[0070] Among them, radioactive isotopes include but are not limited to 3 H. 14 C. 35 S. 125 I. 131 I.

[0071] Enzymes include, but are not limited to, horseradish peroxidase, beta-galactosidase, luciferase, alkaline phosphatase, acetylcholinesterase.

[0072] Fluorescent molecules include, but are not limited to, FITC, rhodamine, and lanthanide phosphors.

[0073] The products include chips, test strips, test kits or nucleic acid membrane strips.

[0074] In some embodiments, a kit refers to a set of components provided in the context of a system for sequencing nucleotides and / or isolating nucleotide sequences and / or diagnosing a subject with a disease or infection based on the presence, absence, and / or amount of expressed nucleotide sequences from a sample or cell.

[0075] The kit comprises a gene detection kit and a protein detection kit. The gene detection kit comprises a reagent or a chip for detecting the transcription level of the MMP3 gene, and the protein detection kit comprises a reagent or a chip for detecting the expression level of the MMP3 protein.

[0076] In some embodiments, the kit further comprises one or more substances from the following group: a container, a positive control, a negative control, a buffer, a preservative, and a protein stabilizer.

[0077] The kit may also be accompanied by an instruction manual for use of the kit, which describes how to use the kit for testing, and how to use the test results to judge tumor development and select a treatment plan.

[0078] The components of the test kit can be packaged in the form of an aqueous medium or in a lyophilized form. Suitable containers in the test kit usually include at least a vial, test tube, flask, PET bottle, syringe or other container, in which a component can be placed, and preferably, can be appropriately divided. When there is more than one component in the test kit, the test kit will usually also include a second, third or other additional container, in which additional components are placed separately. However, the components of different combinations can be contained in a vial. The test kit of the present invention also usually includes a container for accommodating reactants, which is sealed for commercial sale. This container can include a plastic container of injection molding or blow molding, in which the required vial can be retained.

[0079] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0080] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0081] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0082] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0083] A person skilled in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the storage medium may include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc.

[0084] A person skilled in the art can understand that all or part of the steps in the above-mentioned embodiment method can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. The above-mentioned storage medium can be a read-only memory, a disk or an optical disk, etc.

[0085] The above is a detailed introduction to a computer device provided by the present invention. For a person skilled in the art, according to the concept of the embodiments of the present invention, there may be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for predicting depression / predicting the effect of depression treatment / selecting a depression treatment plan, characterized in that: The method comprises: Obtain target gene expression data of the sample to be tested; Predicting whether the sample to be tested suffers from depression / predicting the treatment effect of a patient with depression / a classification result of whether to select the treatment plan based on the target gene expression data, wherein the target gene is selected from MMP3; The samples to be tested include samples of suspected depression or samples of depression patients who have received treatment or depression patients who are to receive treatment.

2. The method for predicting depression / predicting the effect of depression treatment / selecting a depression treatment plan according to claim 1, characterized in that: Classification prediction is performed based on the expression data of the target gene to obtain a classification result of whether the sample to be tested suffers from depression. If the level of the target gene is low, the classification result is obtained that the sample to be tested suffers from depression. If the level of the target gene is high, the classification result is obtained that the sample to be tested does not suffer from depression.

3. The method for predicting depression / predicting the effect of depression treatment / selecting a depression treatment plan according to claim 1, characterized in that: Classification prediction is performed based on the expression data of the target gene to obtain a classification result of the therapeutic effect of the sample to be tested. If the level of the target gene increases, a classification result is obtained that the sample to be tested has a therapeutic effect. If the level of the target gene does not increase, a classification result is obtained that the sample to be tested does not have a therapeutic effect.

4. The method for predicting depression / predicting the effect of depression treatment / selecting a depression treatment plan according to claim 1, characterized in that: A treatment regimen is selected based on the expression data of the target gene. If the level of the target gene increases, a classification result of selecting the treatment regimen is obtained. If the level of the target gene does not increase, a classification result of not selecting the treatment regimen is obtained.

5. A system for predicting depression, characterized in that: The system comprises: An acquisition unit is used to acquire target gene expression data of the sample to be tested, wherein the target gene is selected from MMP3; Classification unit: Perform classification prediction based on the expression data of the target gene to obtain a classification result of whether the sample to be tested suffers from depression. If the level of the target gene is low, the classification result of the sample to be tested suffering from depression is obtained; if the level of the target gene is high, the classification result of the sample to be tested not suffering from depression is obtained.

6. A system for predicting the effect of depression treatment, characterized in that: The system comprises: An acquisition unit is used to acquire target gene expression data of the sample to be tested, wherein the target gene is selected from MMP3; Classification unit: Perform classification prediction based on the expression data of the target gene to obtain a classification result of the therapeutic effect of the sample to be tested. If the level of the target gene increases, the classification result that the sample to be tested has a therapeutic effect is obtained. If the level of the target gene does not increase, the classification result that the sample to be tested does not have a therapeutic effect is obtained.

7. A system for selecting a treatment plan for depression, characterized in that: The system comprises: An acquisition unit is used to acquire target gene expression data of the sample to be tested, wherein the target gene is selected from MMP3; Classification unit: Select a treatment plan based on the expression data of the target gene. If the level of the target gene increases, a classification result of selecting the treatment plan is obtained. If the level of the target gene does not increase, a classification result of not selecting the treatment plan is obtained.

8. A computer device, characterized in that: The computer device comprises: Memory: used to store program instructions; Processor: calling program instructions, when the program instructions are executed, it is used to execute the steps of the method described in any one of claims 1-4.

9. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the steps of the method described in any one of claims 1 to 4 are implemented.

10. Use of reagents for detecting MMP3 expression levels in the preparation of products for diagnosing depression; Preferably, the reagent is selected from a probe that specifically recognizes the MMP3 gene, a primer that specifically amplifies the MMP3 gene, or a binding agent that specifically binds to a protein encoded by the MMP3 gene; Preferably, the primer or probe is labeled with a labeling substance; Preferably, the labeling substance includes a fluorescent substance, a radioactive isotope or an enzyme; Preferably, the product comprises a chip, a test paper, a test kit or a nucleic acid membrane strip; Preferably, the chip includes a gene chip and a protein chip; Preferably, the kit includes a gene detection kit and a protein detection kit; Preferably, the kit further comprises instructions; Preferably, the kit further comprises a buffer.

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