Biological markers for classification diagnosis of melancholic depression and applications thereof

Abstract

The present application relates to a kind of melancholic depression plasma biomarker kit detection method, for detecting the plasma biomarker of melancholic depression.The present application provides a kind of application method by detecting plasma adiponectin (Adiponectin) protein as the application method of melancholic depression biomarker, the present application method is used for the subtype classification diagnosis of melancholic depression for non-diagnostic purposes, improve the sensitivity and specificity of melancholic depression screening.

Description

Technical Field

[0001] This invention relates to the field of clinical medical psychiatry, and more specifically, to the field of depression, particularly to auxiliary diagnostic testing techniques for the identification and subtype classification of melancholic depression. Background Technology

[0002] Major depressive disorder (MDD) is a severe chronic mental illness characterized by core symptoms such as depressed mood, slowed thinking, cognitive decline, and psychomotor retardation. It is characterized by high prevalence, high relapse rate, high suicide rate, and high disability rate. The overall 12-month prevalence of MDD is approximately 6%, while the lifetime risk increases by about three times (15-18%), meaning that almost one in five people will experience at least one depressive episode at some point in their lives. Currently, there are approximately 95 million people with MDD in China, and about 280,000 people commit suicide due to depression each year. Therefore, MDD has become one of the most pressing mental health problems that need to be addressed.

[0003] Unfortunately, less than one-third of patients with depression experience remission or complete recovery without relapse one year after their first episode of depression, while one-third of these patients never experience remission or recovery even after four consecutive treatment trials. Of these, 20% to 33% even develop treatment-resistant depression. This stark difference in treatment outcomes may be related to the significant heterogeneity among patients with depression, one source of which is their diagnostic criteria. The current diagnostic criteria for depression, as defined by the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), are based on a minimum number of symptom features from a multivariate symptom profile (at least five of the nine included symptom features must be present, with at least one being "depressed mood" or "diminished interest or pleasure"). Approximately 227 different combinations of symptoms meet the diagnostic criteria for depression, leading to significant differences in symptom patterns, disease trajectories, and treatment responses among patients with the same diagnosis. Therefore, homogeneous patient subgroups or subtypes help reduce heterogeneity among patients with depression, improve the diagnosis and treatment of depression, improve patient prognosis, and are more conducive to understanding specific etiological mechanisms and developing more patient-specific diagnostic and therapeutic biomarkers. Thus, the accurate identification of specific clinical subtypes with certain characteristics among patients with depression has extremely important clinical significance.

[0004] Regarding clinical subtypes of depression, the three subtypes with the highest number of "pure" subtype patients are, in order, anxious depression, melancholic depression, and atypical depression. Among them, melancholic depression affects approximately 25-50% of people with depression. Large-scale clinical surveys in China show that melancholic depression accounts for about 53.4% ​​of all depression patients, and may be as high as 81.3% in female patients. Its main clinical features include: lack of emotional response to normally pleasant environments, generalized anhedonia, lack of motivation, psychomotor retardation, cognitive impairment, and typical symptoms of vegetative-organ dysfunction, including early awakening, diurnal mood changes, worse mood in the morning, and weight loss.

[0005] Depressive-type depression is a more severe subtype of depression. Compared to non-depressive-type depression, patients with depressive-type depression have a worse prognosis and a lower chance of being cured. Furthermore, the clinical treatment of this subtype differs significantly from other subtypes. According to depression treatment guidelines, the first-line antidepressant for depressive-type depression is selective serotonin reuptake inhibitors (SSRIs) such as fluoxetine. These drugs are more effective than those for non-depressive-type depression, and low-dose fluoxetine has an earlier onset of action and a higher remission rate in depressive-type depression. In addition, norepinephrine-dopamine reuptake inhibitors (SNDRIs) such as bupropion are as effective as SSRIs in treating depressive-type depression. Furthermore, psychotherapy and physical therapy can be combined to treat depressive-type depression.

[0006] In summary, as one of the three most prevalent clinical subtypes of depression, melancholic depression is a more severe form of depression. Its core symptoms, course, treatment, prognosis, and biological factors differ significantly from other clinical subtypes of depression. Therefore, finding objective biomarkers for accurate identification of melancholic depression has extremely important clinical application value. Summary of the Invention

[0007] The purpose of this invention is to address the shortcomings of existing technologies in identifying different subtypes of depression by providing a method for accurate screening and subtype classification diagnosis of melancholic depression: namely, measuring the differential expression level of plasma adiponectin protein to provide an objective indicator for clinical diagnosis.

[0008] To achieve the above objectives, the present invention provides an application of a biomarker in the preparation of products for screening or subtype classification diagnosis of depression, the main feature of which is that the biomarker is adiponectin protein.

[0009] Preferably, the product is a product used for screening depressive disorder.

[0010] Preferably, the product is a product used for subtype classification diagnosis of depressive depression.

[0011] The present invention also provides the application of a reagent for detecting the content of a biomarker in the preparation of a kit for screening or subtype classification diagnosis of depression, the main feature of which is that the biomarker is adiponectin protein.

[0012] The present invention also provides an application of a kit in the screening or subtype classification diagnosis of depression, the main feature of which is that the kit is used to detect the content of a biomarker, wherein the biomarker is adiponectin protein.

[0013] Ideally, the sample to be tested should be plasma.

[0014] This invention provides a method for using differential expression levels of adiponectin protein as a plasma biomarker for depressive depression. This method can be used to screen for depression, especially depressive depression, and can also be used for subtype classification and diagnosis of depressive depression for non-diagnostic purposes, thus improving the sensitivity and specificity of depressive depression screening. Attached Figure Description

[0015] Figure 1 This is a schematic diagram illustrating the overall process of subtype classification and diagnosis of depressive depression by detecting plasma adiponectin protein levels.

[0016] Figure 2 This study uses differential plasma adiponectin protein expression levels for subtype classification and diagnosis of melancholic depression. It compares plasma adiponectin protein expression levels (pg / ml) in patients with melancholic depression with healthy controls, as well as patients with atypical depression and anxiety-related depression. The center point is the median, and the error bar is the 95% confidence interval of the mean. (The figure shows...) "The adiponectin expression level, representing the melancholic depression group, after double logarithmic transformation (log2), showed a statistically significant difference compared to other groups, i.e., after correction using the Bonferroni method." P <0.001. In this invention, the median and 95% confidence interval of plasma adiponectin protein expression levels in melancholic depression are 1.12 × 10⁻⁶. 5 (1.06×10 5 ~1.19×10 5 The adiponectin expression level was significantly higher than that in healthy individuals and in atypical and anxiety-related depression. The median and 95% confidence interval of the adiponectin protein level were 8.19 × 10⁻⁶ pg / ml. 4 (7.67×104 ~9.04×10 4 ) pg / ml, 9.05 × 10 4 (8.27×10 4 ~9.73×10 4 pg / ml, 8.37 × 10 4 (7.31×10 4 ~9.30×10 4 )pg / ml.

[0017] Figure 3 The ROC curve results for plasma adiponectin protein in differentiating between depressive depression and healthy controls, as well as atypical depression and anxiety-related depression are shown. Specifically, adiponectin protein was used to differentiate between depressive depression and healthy controls (C), atypical depression (A), and anxiety-related depression (B). The x-axis represents 1-specificity, the y-axis represents sensitivity, and AUC (Area Under Curve) is the area under the ROC curve. Detailed Implementation

[0018] To further understand the present invention, preferred embodiments of the present invention are 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, and not for limiting the scope of the claims.

[0019] Given that depression is a highly heterogeneous clinical disease, exhibiting significant heterogeneity in clinical symptoms, treatment strategies, treatment effects, prognosis, and even biological phenotypes, this invention provides a method for subtyping and diagnosing melancholic depression by detecting plasma adiponectin protein. This method can be used to compare melancholic depression with healthy controls, and as a subtyping biomarker for other clinical subtypes of depression, such as atypical depression and anxiety-related depression. It provides an objective marker for the auxiliary diagnosis of melancholic depression, an important subtype of depression, and can be applied to patients diagnosed with depression through routine psychiatric examinations. By calculating the differential expression level of plasma adiponectin protein through detection results, a reference value for the auxiliary diagnosis of melancholic depression is obtained. This further diagnoses and subtypes patients with depressive episodes on psychiatric examinations, helping to improve the accuracy of clinicians' diagnoses, avoid misdiagnosis and mistreatment, and improve disease prognosis.

[0020] Protein chip technology can be used to detect the expression level of adiponectin protein in patients. On the one hand, it can effectively distinguish patients with melancholic depression from healthy controls, as well as patients with other clinical subtypes of depression, mainly the two other clinical subtypes with the largest number of patients with depression, including atypical depression and anxiety depression, thus serving as an objective indicator for accurate screening and auxiliary diagnosis of melancholic depression. On the other hand, it can also be used to further confirm and classify patients with depression on mental examination, avoiding false positives.

[0021] Therefore, the detection of differential expression levels of plasma adiponectin protein can provide diagnostic clues for subtypes of depressive depression, which can be directly provided to clinicians for reference, enabling them to determine accurate treatment plans in a shorter time, thereby shortening the diagnosis and treatment time and improving work efficiency and the accuracy of treatment plans.

[0022] In this invention, the biomarker is adiponectin, which is suitable for the classification and diagnosis of depressive depression.

[0023] In this invention, the terms "depression," "depressive symptoms," and "depressive episode" and their meanings are as follows: Major depressive disorder is a general term for a group of diseases characterized primarily by depressed mood or emotional state, accompanied by varying degrees of cognitive and behavioral changes. It may also include psychotic symptoms such as hallucinations and delusions. It is characterized by high prevalence, high relapse rate, high suicide rate, and high disability rate. Currently, clinical diagnosis of depression mainly uses classification and diagnostic systems such as the International Classification of Diseases, 10th Revision (ICD-10) and the Diagnostic and Statistical Manual of Mental Disorders, 5th Revision (DSM-5).

[0024] A major depressive episode is a disease state characterized by depression, with depressed mood, loss of interest, and anhedonia as its core features. It is often accompanied by other cognitive, physical, and behavioral manifestations, such as poor concentration, slowed reaction time, sleep disturbances, reduced activity, and fatigue. A single depressive episode lasts at least two weeks and often recurs. Most episodes resolve, but some may leave residual symptoms or become chronic, potentially causing severe impairment of social functioning.

[0025] Depressive symptoms refer to the clinical manifestations of a patient during a depressive episode, and can be mainly divided into core symptom clusters, psychological symptom clusters, and somatic symptom clusters. The core symptom cluster includes depressed mood, loss of interest, and anhedonia; the psychological symptom cluster includes anxiety, slowed thinking, cognitive symptoms, guilt and self-blame, suicide attempts and behaviors, psychomotor retardation or agitation, psychotic symptoms, and insight; the somatic symptom cluster includes sleep disturbances, eating and weight disorders, loss of energy, diurnal variation in depressive mood, sexual dysfunction, and other nonspecific physical symptoms.

[0026] In this invention, adiponectin is a human protein, and its basic information and functions are as follows: Human adiponectin is an endogenous bioactive polypeptide encoded by the adiponectin, C1Q, and collagen domain-containing genes (ADIPOQ). It is one of the most abundant protein products expressed in adipose tissue, composed of 244 amino acids with a molecular weight of 30 kDa. It is abundant in the bloodstream and adipose tissue, but absent in the brain. Adiponectin monomers and trimers are its bioactive forms or receptor-affinity ligands, specifically binding to G protein-coupled receptors or adiponectin receptors on skeletal muscle or liver cell membranes, thereby regulating fatty acid oxidation and glucose metabolism. Adiponectin's main function is as an important adipose-derived factor involved in controlling lipid metabolism and insulin sensitivity, exhibiting direct anti-diabetic, anti-atherosclerotic, and anti-inflammatory activities. Adiponectin can also negatively regulate the expression of tumor necrosis factor-α (TNF-α) and antagonize TNF-α function in various tissues, including the liver and macrophages. In addition, it can play a role in cell growth, angiogenesis and tissue remodeling by binding and isolating various growth factors with different binding affinities.

[0027] The term "ROC curve" (receiver operator characteristic curve) used in this 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 referred to as sensitivity; the false positive rate is denoted as 1-specificity. Therefore, the ROC curve is a graphical display of the true positive rate (sensitivity) against the false positive rate (1-specificity) within a range of cutoff values, allowing for the selection of the optimal cutoff value for clinical use. Its accuracy is expressed as 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.

[0028] When it comes to differences between test samples and control or reference samples, the terms "statistical difference" or "statistical significance" refer to a probability that the groups are identical when appropriate statistical analysis methods are used (e.g., P The probability of obtaining the same result in 100 trials is less than 0.05 (i.e., the probability of obtaining the same result in 100 trials is less than 5). Similarly, if the probability of each group obtaining the same result is less than 1‰ (e.g., the probability of obtaining the same result in 100 trials is less than 0.05), the probability of obtaining the same result in 100 trials is less than 5. P In the case of <0.001), that is, the probability of obtaining the same result on a completely random basis is less than 1 in 1000 attempts. In this invention, we selected appropriate statistical analysis methods, for example, based on whether the research variable is normally distributed (using the Kolmogorov-Smirnov test), we chose to use parametric model tests such as... t The adiponectin protein microarray data were subjected to either a normal distribution test (ANOVA) or a non-parametric model such as the Mann-Whitney U test or the Kruskal-Wallis test (non-normal distribution). Additionally, a double logarithmic transformation (log2 transformation) was performed on the adiponectin protein microarray data to ensure that the transformed data conformed to a normal distribution (as determined by the Kolmogorov-Smirnov test).

[0029] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. The following embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Experimental methods not specifying specific conditions in the embodiments are generally performed under conventional conditions or according to the conditions recommended by the manufacturer. Example

[0030] S1 clinicians first enroll patients who meet the diagnostic criteria for depression in ICD-10 / DSM-5 and are currently in the acute phase of a depressive episode, either experiencing their first or relapsed episode. Healthy controls are also included. Mental and clinical assessments are conducted. Please refer to [link to relevant documentation]. Figure 1 As shown.

[0031] In this embodiment, a total of 120 subjects were included, including 30 healthy controls, 30 patients with melancholic depression, 30 patients with atypical depression, and 30 patients with anxiety depression.

[0032] In this embodiment, the inclusion and exclusion criteria for healthy controls and patients with depression and its three different clinical subtypes (melancholic depression, atypical depression, and anxiety depression) are as follows: Health comparison Inclusion criteria: (1) Age 18-55 years old; (2) No history of mental illness or family history of mental illness; (3) The total score of the HAMD-17 scale is ≤5 points; (4) No history of neurodegenerative diseases, brain injury, or cerebrovascular disease; (5) No substance abuse or addiction; (6) No unstable angina, myocardial infarction, congestive heart failure, severe cirrhosis, acute or chronic renal failure, severe diabetes, aplastic anemia, epilepsy, or other serious physical diseases of the heart, liver, kidney, endocrine, or blood system, or diseases that may interfere with the test assessment (abnormal laboratory indicators are more than twice the normal value). (7) Voluntarily participate in the research and sign an informed consent form.

[0033] Exclusion criteria: (1) Exclude individuals with a history of mental illness, serious physical illness, cerebrovascular disease, or brain injury; (2) Exclude those who have had severe allergic reactions or have had immune system diseases; (3) Use of anti-inflammatory drugs or immunosuppressants within the past month; (4) Patients who have suffered a head injury or have a serious physical illness; (5) Pregnant women, breastfeeding women, or women planning to become pregnant.

[0034] Depression patients Inclusion criteria: (1) Patients who meet the diagnostic criteria for depressive episode in ICD-10 / DSM-5 and are currently in the acute phase of a depressive episode, either as the first or recurrent episode. (2) Age 18-55 years old; (3) A total score of ≥17 on the 17-item Hamilton Depression Rating Scale (HAMD-17); (4) The patient had not taken any antidepressants or received any physical or psychological treatment within the six months prior to enrollment. (5) Possessing a certain level of education and being able to understand the relevant research content; (6) Voluntarily participate in this study and sign a written informed consent form.

[0035] Exclusion criteria: (1) Secondary depression caused by other organic diseases; (2) Drug-induced secondary depression; (3) Abuse and dependence on alcohol or other substances; (4) Pregnant, breastfeeding women, or women planning to become pregnant; (5) Serious suicide attempt (HAMD-17 item 3 "Suicide" score ≥ 3, or suicidal behavior during the current depressive episode); (6) Comorbid other mental disorders; (7) Patients with serious physical illnesses.

[0036] Among them, the three clinical subtypes of depression (melancholic depression, atypical depression, and anxiety depression) are mainly classified and determined based on the 30-item Self-Rating Depression Scale (IDS-30) and the HAMD-17 scale, as shown below: (1) Depressive disorder The determination is primarily based on the scores of relevant items in IDS-30, requiring that the following conditions be met simultaneously: ① In either item 9 (mood changes) or item 21 (the capacity for pleasure or enjoyment (excluding sexual activity)) of the IDS-30, the score must be ≥2. ② At least 3 of the following 5 characteristics are present: extreme despair or depression, or emotional emptiness, extremely pronounced depressive mood; depressive symptoms are more severe in the morning; irritability; psychomotor agitation or bradykinesia; severe anorexia or weight loss.

[0037] (2) Atypical depression The determination is primarily made based on the relevant entries in IDS-30, requiring that the following conditions be met simultaneously: ① Item 21 of IDS-30 scores ≥ 2 points; ② Increased appetite or significant weight gain; ③ Sensitive to interpersonal relationships; ④ Lead paralysis (heaviness, or a feeling of heaviness in the arms or legs).

[0038] (3) Anxiety-related depression The diagnosis of anxiety-related depression is mainly based on relevant items of the HAMD-17 scale, requiring the following conditions to be met simultaneously: ① The anxiety / somatic factor score (including items 10, 11, 12, 13, 15 and 17) on the HAMD-17 scale is ≥ 7; ② At least two of the following five items are present: feeling nervous or anxious; feeling unusually anxious; having difficulty concentrating due to worry; being afraid of terrible things happening; and being afraid of losing control of oneself.

[0039] S2 collects plasma samples and uses protein chip technology to measure the patient's plasma adiponectin protein level.

[0040] In this embodiment, a quantitative protein chip kit was used to detect the expression level of adiponectin protein in plasma samples.

[0041] This kit contains the following items: quantitative protein glass chip (QAH-CUSTOM), sample diluent, 20× wash buffer I, 20× wash buffer II, standard mixture, immunoglobulin G antibody against adiponectin protein, Cy3-streptavidin, slide cleaner and dryer, sealing strip, etc.

[0042] The specific testing methods are as follows: (1) Drying and quantitative protein chip: Remove the quantitative protein chip, equilibrate it at room temperature for 20-30 minutes, and then place the chip in a vacuum desiccator for 1-2 hours to completely dry the protein chip.

[0043] (2) Configure standard products: ① Add 500µL of sample diluent to the tube containing the cytokine standard mixture to reconstitute the standard. Before opening the tube, centrifuge quickly and gently blow the dissolved powder up and down. Label this tube as Std 1.

[0044] ② Label six clean centrifuge tubes as Std2, Std3 to Std7, and add 200µL of sample diluent to each tube.

[0045] ③ Take 100µL of Std 1 and add it to Std 2 and mix gently. Then take 100µL of Std 2 and add it to Std 3. Repeat this gradient dilution to Std 7 to obtain the standard solution.

[0046] (3) Draw 100µL of sample dilution into another new centrifuge tube, label it CT, and use it as a negative control.

[0047] (4) Remove the completely dried glass slide chip, add 100 µL of sample dilution to each well, incubate on a shaker at room temperature for 1 hour, and block the quantitative antibody chip. Then wash with buffer.

[0048] (5) Remove the buffer solution from each well, add 60µL of standard solution and sample (sample diluted 2 times before loading) to the well, and incubate overnight at 4°C.

[0049] (6) Cleaning slides using a chip washer. In this application, the Thermo Scientific Well WashVersa chip washer was used to clean the slides. The process mainly consists of two steps. First, the slides are cleaned with 1× Wash Solution I, 250µL per well, for 10 washes, with agitation for 10 seconds each time. The agitation intensity is selected as high. 20× Wash Solution I is diluted with deionized water. Then, the slides are cleaned using the 1× Wash Solution II channel, 250µL per well, for 6 washes, with agitation for 10 seconds each time. The agitation intensity is selected as high. 20× Wash Solution II is diluted with deionized water.

[0050] (7) Incubate the antibody mixture Centrifuge the Eppendorf tube containing the adiponectin antibody mixture, then add 1.4 ml of sample diluent, mix well, centrifuge again quickly, and then add 80 µL of adiponectin antibody to each well. Incubate on a shaker at room temperature for 2 hours.

[0051] (8) Clean again, following the same steps as (6).

[0052] (9) Incubation of Cy3-streptavidin Centrifuge the Cy3-streptavidin Eppendorf tube, then add 1.4 ml of sample diluent, mix well, and centrifuge again quickly. Add 80 µL of Cy3-streptavidin to each well, wrap the quantitative protein chip with aluminum foil, and incubate in the dark on a shaker at room temperature for 1 hour.

[0053] (10) Clean again, following the same steps as (6).

[0054] (11) Place the chip in a washer-dryer and centrifuge it at 1000 rpm to dry it thoroughly.

[0055] (12) Fluorescence detection was performed on the dried glass chip. In this embodiment, an InnoScan 300 Microarray Scanner was used to scan the signal. The scanning parameters were: Wavelength: 532nm; Resolution: 10µm. The signal value was captured using Mapix software with either Cy3 or the green channel (excitation frequency = 532nm).

[0056] S3 used QAH-CUST data analysis software to analyze data and obtain the expression level of adiponectin protein in plasma samples. Specifically: First, the raw detection data from the protein chip experiment were normalized. This involved removing the chip background from the raw data obtained from the chip scan, averaging the data from the standards, and then normalizing the data. Because the raw measurement data exhibited a skewed distribution, a double logarithmic transformation (log2) was performed to ensure a normal distribution before use in subsequent statistical analysis. Furthermore, the dispersion of the data was analyzed; data deviating from the mean ± 2 standard errors (SD) were not included in the statistical analysis. In this embodiment, the number of discrete data points (mean ± 2 SD) in the healthy control group and the groups with depressive depression, atypical depression, and anxiety depression were 1, 3, 3, and 2, respectively. The specific raw measurement values ​​and discrete values ​​of adiponectin are shown in Table 1 below.

[0057] S4. Statistical results of the present invention are as follows: Figure 2 As shown, the depressive depression group, healthy controls, and atypical depression and anxiety depression groups... "Statistical difference in adiponectin protein expression levels" P <0.01. Therefore, plasma adiponectin levels were significantly elevated in the melancholic depression group, and the difference was statistically significant compared with healthy controls and the two most numerous clinical subtypes of depression, atypical depression and anxiety depression.

[0058] Furthermore, further analysis of the data yielded the following ROC curve results: Figure 3 As shown, the AUC values ​​and 95% confidence intervals of adiponectin protein in patients with melancholic depression compared to healthy controls and patients with atypical and anxiety-type depression were 0.967 (0.926–1.000), 0.888 (0.801–0.974), and 0.936 (0.874–0.998), respectively. This indicates that adiponectin can serve as an objective biomarker for melancholic depression and possesses extremely excellent diagnostic efficacy for subtype classification.

[0059] The adiponectin protein level detection method in this invention can accurately diagnose patients with depressive depression, avoiding the impact of misdiagnosis and missed diagnosis on the accuracy and specificity of treatment plans, and improving work efficiency.

[0060] In this specification, the invention has been described with reference to specific embodiments thereof. However, it will be apparent that various modifications and variations can be made without departing from the spirit and scope of the invention. Therefore, this specification should be considered illustrative rather than restrictive.

Claims

1. The application of a biomarker in the preparation of products for screening or subtyping and diagnosing depressive disorder, characterized in that, The biomarker is adiponectin protein.

2. The application of a reagent for detecting the content of a biomarker in the preparation of a kit for screening or subtyping and diagnosing depressive disorder, characterized in that, The biomarker is adiponectin protein.

3. The application according to claim 2, characterized in that, The sample tested was plasma.

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