Biomarkers for the Auxiliary Diagnosis of Depression and Their Applications

Abstract

The present invention relates to a detection method for a plasma biomarker kit for major depressive disorder, which is used to detect plasma biomarkers for major depressive disorder. The present invention provides an application method for detecting one or more of the proteins ErbB3, MIF, NSE, and HGFR in plasma as a biomarker for major depressive disorder. The method of the present invention is used to assist in the diagnosis of major depressive disorder and improve the sensitivity and specificity of depression screening for the general population.

Description

Technical Field

[0001] The present invention relates to the technical field of clinical medicine psychiatry, and more specifically, to the technical field of depression, especially an auxiliary diagnostic detection technology for judging depression. Background Art

[0002] Depression (Major depressive disorder) is a severe chronic mental illness characterized by core symptoms such as low mood, slow thinking, decreased cognitive function, and psychomotor retardation. It is characterized by high prevalence, high recurrence rate, high suicide rate, and high disability rate. The overall 12-month prevalence of depression is approximately 6%, and the lifetime risk of illness increases by about 3 times (15 - 18%), meaning that almost one-fifth of people will experience at least one depressive episode at some point in their lives. Currently, there are approximately 350 million depression patients globally, and about 95 million in our country. The number of people who commit suicide due to depression each year is approximately 280,000. Depression seriously affects the physical health, daily life, and social and psychological functions of patients, causing a heavy social and economic burden. In 2010, depression was listed by the World Health Organization (WHO) as the second largest disease burden globally and is expected to rank first by 2030, becoming one of the most urgent mental health problems to be solved globally.

[0003] Regrettably, currently, the diagnosis of depression mainly relies on clinical phenomenology and lacks practical and effective objective biological indicators. Research results show that the diagnostic consistency of depression over ten years is only 45.5%, which severely limits the ability of clinicians to correctly diagnose the disease in the early stage of depression onset, making the clinical diagnosis and treatment of depression fall into a dilemma. In fact, currently, on the one hand, only a trial-and-error strategy can be used to determine the diagnosis of patients and administer the antidepressant drugs that doctors believe are the most effective to each patient: this means prolonged remission periods, patient suffering, poor compliance, the occurrence of treatment adverse reactions, the deterioration of suicidal thoughts, and high social costs. On the other hand, because usually, people's emotions can fluctuate with genetics, situations, events, or the social and economic environment, and the trial-and-error strategy may also misdiagnose the depressive state of the general population as mild depression. Therefore, there is an urgent need to explore biological markers that may be used for differential diagnosis of depression and the general population.

[0004] Currently, most research on the development of biological markers for the differential diagnosis of depression mainly focuses on basic research such as hematology, genetics, and imaging. However, the research results are inconsistent and even contradictory. This has led to numerous difficulties for these studies under current medical conditions, and there are few practical clinical applications. Even if good biological markers are discovered, they cannot be effectively promoted due to limitations such as the awareness of medical staff, medical insurance, and material equipment. At the same time, due to the strong subjectivity in the clinical evaluation process or the complexity of the specific experimental designs involved, clinical translational applications are still restricted. Among all possible biomarkers, peripheral blood biomarkers are the easiest to obtain because of their applicability and easy accessibility in clinical practice, and they are not easily affected by material equipment and clinical subjective judgments.

[0005] Therefore, it is extremely necessary to establish a method that can use plasma biological indicators to quickly diagnose depression. Summary of the Invention

[0006] The object of the present invention is to address the deficiencies in the early recognition and accurate diagnosis of depression in the prior art, and to provide an application method for accurately screening and assisting in the diagnosis of depression: that is, measuring the differential expression levels of one or more of the four proteins, namely Human epidermal growth factor receptor 3 (ErbB3), macrophage migration inhibitory factor (MIF), Neuron-specific enolase (NSE), and Hepatocyte growth factor receptor (HGFR), in plasma, which serves as an objective indicator for clinical diagnosis.

[0007] To achieve the above object, the present invention provides an application of a biomarker in the preparation of a product for the auxiliary diagnosis of depression. The main feature is that the biomarker is one or more of the proteins ErbB3, MIF, NSE, and HGFR.

[0008] The present invention also provides an application of a reagent for detecting the content of a biomarker in the preparation of a kit for the auxiliary diagnosis of depression. The main feature is that the biomarker is one or more of the proteins ErbB3, MIF, NSE, and HGFR.

[0009] The present invention also provides an application of a kit in the auxiliary diagnosis of depression. The main feature is that the kit is used to detect the content of a biomarker, and the biomarker is one or more of the proteins ErbB3, MIF, NSE, and HGFR.

[0010] Preferably, the test sample is plasma.

[0011] The present invention provides a method of using the differential expression levels of one or more of ErbB3, MIF, NSE, and HGFR proteins as plasma biomarkers for melancholic depression. The method of the present invention can be used for the auxiliary diagnosis of depression, improving the sensitivity and specificity of depression screening. Description of the Drawings

[0012] Figure 1 For the differential expression levels of 4 proteins to distinguish patients with depression from healthy controls. Specifically, it is the comparison of the differential expression levels (unit: pg / ml) of NSE (A), ErbB3 (B), MIF (C), and HGFR (D) proteins between patients with depression and healthy controls. The bar graph represents the mean, and the error bar is the standard error (SE). In the figure, "**" represents that the difference between the two groups is P < 0.001 after correction by the Bonferroni method.

[0013] Figure 2 For the ROC curve results of 4 proteins to distinguish depression from healthy controls. Specifically, they are the ROC curve results of NSE (A), ErbB3 (B), MIF (C), and HGFR (D) proteins respectively for distinguishing depression from healthy controls. The abscissa is 1 - specificity, the ordinate is sensitivity, and AUC (Area Under Curve) is the area enclosed by the ROC curve and the coordinate axes. Detailed Embodiments

[0014] To further understand the present invention, the preferred embodiments of the present invention will be described below in conjunction with examples. However, it should be understood that these descriptions are only for further illustrating the features and advantages of the present invention, rather than limiting the claims of the invention.

[0015] Considering that depression is a disease with extremely high clinical heterogeneity, with great heterogeneity in its clinical symptoms, treatment strategies, treatment effects, prognosis, and even biological phenotypes, the present invention provides a method for the auxiliary diagnosis of depression by detecting the differential expression levels of one or more of 4 proteins, namely ErbB3, MIF, NSE, and HGFR, in plasma. It can be used as an objective biological indicator for depression and applied to patients considered to have depressive episodes or depressive states during mental examinations. Through the detection results of one or more of the 4 plasma proteins, calculate their differential expression levels of proteins to obtain a reference value for the auxiliary diagnosis of depression, further diagnose the patients, avoid misdiagnosis and mistreatment, improve the accuracy of diagnosis and the pertinence of treatment by clinicians, and improve the prognosis of the disease.

[0016] The protein chip technology can be used to detect the expression levels of one or more of ErbB3, MIF, NSE, and HGFR proteins in patients, which can effectively distinguish between patients with depression and healthy control groups, and thus can be used as an objective indicator for the precise screening and auxiliary diagnosis of depression. In addition, a comprehensive mental examination can be combined to further diagnose patients with depressive symptoms and avoid false positives.

[0017] Therefore, the detection of differential expression levels of one or more of ErbB3, MIF, NSE, and HGFR proteins in plasma for the early identification and auxiliary diagnosis of patients with depression, and the clear distinction from healthy controls can be directly provided for clinicians' reference, enabling them to determine a precise treatment plan in a short time, thereby shortening the diagnosis and treatment time, improving work efficiency, and the accuracy of the diagnosis and treatment plan.

[0018] In the present invention, the biomarker is one or more of ErbB3, MIF, NSE, and HGFR proteins, which is applicable to the screening and auxiliary diagnosis of patients with depression or depressive episodes.

[0019] In the present invention, the terms "depression", "depressive symptoms", "depressive episode", and their meanings are as follows:

[0020] Major depressive disorder is a general term for a class of diseases mainly manifested by low mood or mood, accompanied by varying degrees of cognitive and behavioral changes, and may be accompanied by psychotic symptoms such as hallucinations and delusions, characterized by high prevalence, high recurrence rate, high suicide rate, and high disability rate. At present, the international classification of diseases, 10th revision (ICD-10), the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5), and other classification and diagnosis systems are mainly used in clinical practice to diagnose depression.

[0021] A major depressive episode is a disease state characterized by depression, with the core features of low mood, loss of interest, and anhedonia, and is often accompanied by other cognitive, physical, and behavioral manifestations, such as inattention, slow reaction, sleep disorders, reduced behavioral activities, and fatigue. A single depressive episode lasts at least 2 weeks, often recurs, and most episodes can be relieved, some may have residual symptoms or turn chronic, which can cause serious social function impairment.

[0022] Depressive symptoms refer to the clinical manifestations of patients during a depressive episode, which can be mainly divided into a core symptom cluster, a psychological symptom cluster, and a somatic symptom cluster. Among them, the core symptom cluster includes low mood, loss of interest, and anhedonia; the psychological symptom cluster includes anxiety, slow thinking, cognitive symptoms, self-blame, suicide attempts and behaviors, psychomotor retardation or agitation, psychotic symptoms, insight, etc.; the somatic symptom cluster includes sleep disorders, eating and weight disorders, loss of energy, diurnal variation of depressive mood (worse in the morning and better in the evening), sexual dysfunction, and other non-specific somatic symptoms.

[0023] In the present invention, the four proteins (NSE, ErbB3, MIF, and HGF R) involved are all human proteins. The basic information and functions of these four main proteins are introduced one by one below.

[0024] Human neuron-specific enolase (NSE, also known as ENO2) is an enolase, belonging to a "metal-activated metalloenzyme", which can catalyze the dehydration of 2-phospho-D-glycerate to phosphoenolpyruvate in the glycolysis pathway and the reverse reaction in gluconeogenesis. It is essential for the anaerobic conversion of glucose into metabolites suitable for oxidation. In vertebrate organisms, there are three enolase isoenzymes expressed by different genes. Enolase α is ubiquitous; enolase β is muscle-specific, and enolase γ is neuron-specific, and all known eukaryotic enolases are dimers.

[0025] Human epidermal growth factor receptor 3 (HER3 / ErbB3) is a membrane-bound protein encoded by the human ERBB3 gene. The ErbB3 protein is a member of the epidermal growth factor receptor (EGFR) family of receptor tyrosine kinases. Like other EGFR family members, it consists of an extracellular ligand-binding domain, a transmembrane domain, and an intracellular domain. ErbB3 is present in the blood, various peripheral organs, and the brain. In terms of function, as a member of the EGFR family, the tyrosine protein kinase plays an important role as a cell surface receptor for neuregulin. It binds to and is activated by neuregulin-1 (NRG1); ligand binding increases the phosphorylation of tyrosine residues and promotes its binding to the p85 subunit of phosphatidylinositol 3-kinase. It can also bind to adenosine triphosphate (ATP) and nucleotides, mediating intracellular signal transduction. In addition, it can initiate relevant pathways for cell proliferation or differentiation.

[0026] Macrophage migration inhibitory factor (MIF) is a pleiotropic immunomodulatory cytokine with a unique structure. It has functions similar to chemokines and is a pro-inflammatory cytokine. First discovered in 1966, it mainly participates in the innate immune response (natural immunity) to bacterial pathogens and also in cell-mediated immunity, immune regulation, and inflammatory processes. It plays a role in regulating macrophage function in host defense mainly by inhibiting the anti-inflammatory effect of glucocorticoids. It is mainly distributed in the blood and the brain.

[0027] Hepatocyte growth factor receptor (HGFR) is a glycosylated receptor tyrosine kinase, which is the product encoded by the MET gene of the proto-oncogene receptor tyrosine kinase. The encoded pre-protein undergoes proteolytic processing to produce a 50 kDa extracellular α-chain and a 145 kDa transmembrane β-chain. These subunits are linked by disulfide bonds to form a mature dimer, and this dimerization and activation play a role in cell survival, embryogenesis, and cell migration and invasion. In addition, the β-subunit of the receptor HGFR can be further processed to form the M10 peptide.

[0028] The term "ROC curve" (receiver operator characteristic curve), the operating characteristic curve, used in the present invention refers to a graphical curve that shows the performance of a binary classification system as its discrimination threshold changes. This curve is created by plotting the true positive rate against the false positive rate under different threshold settings. Here, the true positive rate is called sensitivity; the false positive rate is counted as 1 - specificity. Therefore, the ROC curve is a clinical usage method for selecting the optimal cut-off value based on the graphical display of the true positive rate (sensitivity) against the false positive rate (1 - specificity) within a range of a series of cut-off values. Its accuracy is represented by the area under the ROC curve (AUC), thus providing a practical parameter for comparing test performance. In the ROC curve, the closer the AUC value is to 1, the more sensitive and specific the test is, while an AUC value close to 0.5 indicates that the test is neither sensitive nor specific.

[0029] When referring to the differences between a test sample and a control sample or a reference sample, the terms "statistical difference" or "statistical significance" refer to the situation where the probability of the groups being the same is less than 5% (e.g., P < 0.05) when using an appropriate statistical analysis method, that is, the probability of obtaining the same result on a completely random basis is less than 5 times in 100 attempts. Similarly, if the probability of the groups being the same is less than 1‰ (e.g., P < 0.001), that is, the probability of obtaining the same result on a completely random basis is less than 1 time in 1000 attempts. In the present invention, we selected an appropriate statistical analysis method. For example, depending on whether the research variable is normally distributed (using the Kolmogorov-Smirnov test), we chose to use parametric model tests such as the t-test or ANOVA test (for normal distribution), or non-parametric models such as the Mann-Whitney U test or Kruskal-Wallis test (for non-normal distribution). At the same time, the antibody microarray detection data of 4 proteins were also logarithmically transformed (base 2) so that the protein detection data after log2 transformation conformed to the normal distribution (determined by the Kolmogorov-Smirnov test).

[0030] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. The following embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention. For the experimental methods without specific conditions indicated in the embodiments, they are generally carried out according to conventional conditions or according to the conditions recommended by the manufacturers.

[0031] Example

[0032] S1 Clinicians first included first-episode or recurrent acute-phase patients who met the diagnostic criteria for depression in ICD-10 / DSM-5 and were currently in a depressive episode, and included healthy controls for mental assessment and clinical assessment. Please refer to Figure 1 as shown.

[0033] In this embodiment, a total of 120 research subjects were included, including 30 healthy controls and 90 patients with depression.

[0034] In this embodiment, the inclusion and exclusion criteria for the healthy control group and the patients with depression were as follows:

[0035] Healthy control

[0036] Inclusion criteria:

[0037] (1) Aged 18 - 55 years old;

[0038] (2) Without a history of mental illness or family history of mental illness;

[0039] (3) The total score of the HAMD-17 scale ≤ 5 points;

[0040] (4) Have no history of neurodegenerative diseases, brain trauma, or cerebrovascular diseases;

[0041] (5) Have no substance abuse or substance addiction;

[0042] (6) Have no unstable angina pectoris, myocardial infarction, congestive heart failure, severe liver cirrhosis, acute or chronic renal failure, severe diabetes, aplastic anemia, epilepsy, and other severe somatic diseases of the heart, liver, kidney, endocrine, and blood systems, or diseases that may interfere with the test assessment (laboratory abnormal indicators are more than 2 times higher than the normal value);

[0043] (7) Voluntarily participate in the study and sign the informed consent form.

[0044] Exclusion criteria:

[0045] (1) Exclude those with mental diseases, severe somatic diseases, cerebrovascular diseases, or a history of brain trauma;

[0046] (2) Exclude those who have had severe allergic reactions or have a history of immune system diseases;

[0047] (3) Have used anti-inflammatory drugs or immunosuppressants within 1 month;

[0048] (4) Have had a brain trauma or are accompanied by severe somatic diseases;

[0049] (5) Pregnant women, lactating women, or those planning to conceive.

[0050] Patients with depression

[0051] Inclusion criteria:

[0052] (1) Meet the diagnostic criteria for depressive episode in ICD-10 / DSM-5, and are currently in the acute phase of the first or recurrent depressive episode;

[0053] (2) Aged 18 - 55 years old;

[0054] (3) The total score of the 17-item Hamilton Depression Rating Scale (HAMD-17) is ≥ 17 points;

[0055] (4) Have not taken any antidepressants, received any physical therapy, or psychological therapy within half a year before enrollment;

[0056] (5) Have a certain level of education and can understand the research-related content;

[0057] (6) Voluntarily participate in this study and sign the written informed consent form.

[0058] Exclusion criteria:

[0059] (1) Secondary depression caused by other organic diseases;

[0060] (2) Secondary depression caused by drugs;

[0061] (3) Alcohol or other substance abuse and dependence;

[0062] (4) Pregnant women, lactating women or those planning pregnancy;

[0063] (5) Severe suicidal attempt (score of "suicide" in HAMD-17 item 3 ≥ 3 points, or suicidal behavior during the current depressive episode);

[0064] (6) Comorbid with other mental disorders;

[0065] (7) Patients with severe physical diseases.

[0066] S2 Collect plasma samples and measure the levels of ErbB3, MIF, NSE and HGFR proteins in the plasma of patients using protein chip technology.

[0067] In this embodiment, a quantitative protein chip kit is used to detect the expression levels of ErbB3, MIF, NSE and HGFR proteins in plasma samples.

[0068] The kit includes the following items: quantitative protein glass chip (QAH-CUSTOM), sample diluent, 20× wash solution I, 20× wash solution II, standard mixture, immunoglobulin G antibodies against ErbB3, MIF, NSE and HGFR proteins, Cy3-streptavidin, slide washer and dryer, sealing strip, etc.

[0069] The specific detection implementation method is as follows:

[0070] (1) Dry the quantitative protein chip:

[0071] Take out the quantitative protein chip, balance it at room temperature for 20 - 30 minutes, and then place the chip in a vacuum dryer for 1 - 2 hours to completely dry the protein chip.

[0072] (2) Prepare the standard:

[0073] ① Add 500 μL of sample diluent to the small tube of cytokine standard mixture to redissolve the standard. Before opening the small tube, first centrifuge it quickly, gently pipette up and down to dissolve the powder, and label this small tube as Std 1.

[0074] ② Label 6 clean centrifuge tubes as Std2, Std3 to Std7 respectively, and add 200 μL of sample diluent to each small tube.

[0075] (3) Pipette 100 μL of Std 1 into Std 2 and mix gently. Then, pipette 100 μL from Std 2 into Std 3 and perform gradient dilution up to Std7 in this way to obtain the standard solution.

[0076] (3) Pipette 100 μL of the sample dilution into another new centrifuge tube, label it as CT, and use it as the negative control.

[0077] (4) Take out the completely dried glass slide chip, add 100 μL of the sample dilution to each well, incubate on a shaker at room temperature for 1 hour to block the quantitative antibody chip. Then wash with the buffer solution.

[0078] (5) Aspirate the buffer solution from each well, add 60 μL of the standard solution and the sample (the sample is loaded after 2-fold dilution) into the wells, and incubate overnight at 4°C.

[0079] (6) Wash the glass slide using a chip washer. In this application, the Thermo Scientific Well WashVersa chip washer is used for glass slide washing, which mainly consists of two steps. First, wash with 1× Wash Solution I, 250 μL of 1× Wash Solution I per well, wash 10 times, shake for 10 s each time, and select a high shaking intensity. Dilute 20× Wash Solution I with deionized water. Then, switch to the 1× Wash Solution II channel for washing, 250 μL of 1× Wash Solution II per well, wash 6 times, shake for 10 s each time, and select a high shaking intensity. Dilute 20× Wash Solution II with deionized water.

[0080] (7) Incubate the antibody mixture

[0081] Centrifuge the eppendorf tube containing the mixture of NSE, ErbB3, MIF, and HGF R antibodies, then add 1.4 ml of the sample dilution to each respectively. After mixing evenly, centrifuge quickly again. Then add 80 μL of the adiponectin antibody to each well and incubate on a shaker at room temperature for 2 hours.

[0082] (8) Wash again, and the steps are the same as (6).

[0083] (9) Incubate Cy3-streptavidin

[0084] Centrifuge the eppendorf tube of Cy3-streptavidin, then add 1.4 ml of the sample dilution. After mixing evenly, centrifuge quickly again. Add 80 μL of Cy3-streptavidin to each well, wrap the quantitative protein chip with aluminum foil to avoid light, and incubate on a shaker at room temperature for 1 hour.

[0085] (10) Wash again, and the steps are the same as (6).

[0086] (11) Place the chip in a washer-dryer, centrifuge at 1000 rpm and dry it thoroughly.

[0087] (12) Perform fluorescence detection on the dried glass chip. In this embodiment, an InnoScan300 Microarray Scanner fluorescence scanner is used to scan the signal, and the scanning parameters are: WaveLengh: 532 nm; Resolution: 10 μm. Use Cy3 or the green channel (excitation frequency = 532 nm), and use Mapix software to capture the signal value.

[0088] S3 Use the QAH-CUST data analysis software to perform data analysis to obtain the expression levels of ErbB3, MIF, NSE, and HGF R proteins in plasma samples. Specifically as follows:

[0089] First, perform normalization on the original detection data of the protein chip experiment, that is, the original data obtained by chip scanning is subjected to chip background removal, and the data of the standard product is averaged for normalization. Since the original measurement data is skewed, the original measurement data is subjected to double logarithmic transformation (log2) and then follows a normal distribution, which is then used for subsequent statistical analysis. In addition, the degree of data dispersion is also analyzed. For data outside the mean ± 2 standard errors (SD), it is not included in the data statistics. In this embodiment, the original measurement values and discrete values of the differential expression of NSE, ErbB3, MIF, and HGF R proteins are shown in Table 1 below.

[0090] Table 1 Original measurement values of 4 plasma proteins and their values after double logarithmic transformation

[0091]

[0092]

[0093]

[0094] Note: The italicized numbers in the above table are discrete values, that is, outside the mean ± 2 standard deviations (SD), and are regarded as outliers.

[0095] S4 The statistical results of the present invention are as Figure 2 shown. The differential expressions of NSE, ErbB3, MIF, and HGF R plasma proteins are significant in healthy control groups and the depression group. Among them, the expression levels of NSE, ErbB3, and MIF proteins in the depression group are significantly increased, while the expression level of HGF R protein is significantly decreased, and the differences are all statistically significant (in this embodiment, Figure 1 "**" P < 0.001).

[0096] In addition, further analysis of the data showed that the results of the ROC curve were as follows Figure 2 shown in Figure 2 . The AUC and 95% confidence intervals of NSE, ErbB3, MIF, and HGFR proteins for differentiating patients with depression from healthy controls were 0.795 (0.711 - 0.879), 0.805 (0.724 - 0.886), 0.749 (0.655 - 0.842), and 0.760 (0.669 - 0.853), respectively, indicating that NSE, ErbB3, MIF, and HGFR proteins, as objective biomarkers for depression, have extremely excellent diagnostic efficiency.

[0097] By detecting the levels of ErbB3, MIF, NSE, and HGFR proteins in the present invention, patients with anxious depression can be accurately diagnosed, avoiding the influence on the accuracy and pertinence of treatment plans due to misdiagnosis and missed diagnosis, and improving work efficiency.

[0098] In this specification, the present invention has been described with reference to its specific embodiments. However, it is obvious that various modifications and variations can still be made without departing from the spirit and scope of the present invention. Therefore, the specification should be regarded as illustrative rather than restrictive.

Claims

1. Use of a biomarker in the preparation of a product for the auxiliary diagnosis of depression, characterized in that, The biomarkers described above are ErbB3, MIF, NSE, and HGFR proteins.

2. Use of a reagent for detecting the content of a biomarker in the preparation of a kit for auxiliary diagnosis of depression, characterized in that, The biomarkers described above are ErbB3, MIF, NSE, and HGFR proteins.

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