Detection reagent for detecting depression by sugar chain marker, preparation method and application

Abstract

The invention provides a detection reagent for detecting depression based on an oligosaccharide chain and a preparation method and application thereof, the detection reagent is prepared by mixing the following reagents: a reagent A, which is prepared by adding SDS with the mass concentration of 1-5% into an ammonium bicarbonate solution with the concentration of 10mM and the pH value of 8.3; the reagent B is prepared by mixing 0.05-10 units / 10 microliters of glycosamine acylase, NP-40 with the mass concentration of 10% and an ammonium bicarbonate solution with the concentration of 10 mM and the pH value of 8.3, and the pH value of the mixed solution is 5-9; the reagent C is an organic matter reducing agent with the concentration of 0.02 mM to 1M, which is prepared by dissolving 8-aminopyrene-1, 3, 6-trisulfonic acid in DMSO (Dimethylsulfoxide); and a reagent D: a stop solution. The invention firstly proposes that the sugar chain map can be used as the auxiliary diagnosis marker of the depression patient, has high sensitivity and high specificity for the diagnosis of depression, has the prospect of being developed into a clinical auxiliary diagnosis kit for depression, can overcome the difficulty and pain point of clinical diagnosis of depression at present, and has a wide application prospect. The method is of great significance to diagnosis and clinical intervention of depression.

Description

Technical Field

[0001] The present invention relates to a sugar chain marker detection reagent, and specifically to a detection reagent, a preparation method and application of one or several sugar chains as biomarkers to distinguish depression patients from healthy people, belonging to the field of biomedicine technology. Background Art

[0002] Depression is a common mental illness characterized by repeated and persistent low moods and physical symptoms. Currently, there are 95 million people suffering from depression in my country, and the number is increasing year by year. However, the recognition rate of depression in hospitals at the prefecture and city level and above is less than 20% nationwide. The low diagnosis rate of depression and high suicide rate have a serious impact on Chinese society. Therefore, the diagnosis and treatment of depression has become a health and social issue that the public is increasingly concerned about.

[0003] The pathogenesis of depression is complex, involving dysfunction of multiple systems and multiple links, which can be manifested as abnormal dynamic balance of multiple biochemical substances. Although depression has always received much attention from the international community, its diagnosis is still a major problem restricting the treatment of depression. At present, the diagnosis of depression is mainly based on the patient's complaints and clinical manifestations, combined with depression test forms and conventional medical and behavioral tests, but it is limited by subjective factors such as the patient's ability to express and the doctor's clinical experience. There are often misdiagnoses, missed diagnoses, and difficulties in treatment for some patients. At present, there are no practical and clear objective indicators for diagnosing depression.

[0004] More than 70% of proteins in the human body are modified by glycosylation. As the "third life chain" that reveals the mysteries of life, sugar chains (Glycan) are involved in all aspects of cellular and organismal biological processes and are the material basis of normal and pathological processes. Changes in glycosylation not only reflect the state of the cell genome, transcriptome, proteome and metabolome, but also reflect its external microenvironment. Through a series of explorations, the present invention found that in patients with depression, the sugar chain map is different from that of healthy people, thus providing a new method for clinical practice. Therefore, the present invention focuses on exploring the application value of sugar chain maps in patients with depression. Summary of the invention

[0005] In view of the limitations of the prior art, the purpose of the present invention is to provide a sugar chain composition as a biomarker for auxiliary diagnosis of depression, which is used to distinguish between depression patients and healthy people and provide a new technical means for guiding depression patients to receive treatment.

[0006] To achieve the above-mentioned purpose, the present invention provides a detection reagent for detecting depression using a sugar chain marker.

[0007] The technical solution adopted by the present invention is as follows:

[0008] A detection reagent for detecting depression based on oligosaccharide chains, comprising the following reagents:

[0009] Reagent A: Prepared by adding 1-5% SDS to 10 mM ammonium bicarbonate solution with a pH of 8.3;

[0010] Reagent B: 0.05-10 units / 10 μl of glycosaminoglycans, 10% NP-40, and 10 mM ammonium bicarbonate solution at pH 8.3, with the pH value of the mixed solution being 5-9;

[0011] Reagent C: 8-aminopyrene-1,3,6-trisulfonic acid dissolved in DMSO to prepare an organic reducing agent with a concentration of 0.02 mM to 1 M;

[0012] Reagent D: Stop solution.

[0013] Preferably, the volume ratio of reagent A, reagent B and reagent C is 1:1:1.

[0014] Preferably, the volumes of reagent A, reagent B and reagent C are all 5 μl.

[0015] Preferably, the reagent D is ultrapure water.

[0016] The present invention also provides a method for preparing a detection reagent for detecting depression based on oligosaccharide chains, comprising the following steps:

[0017] Step 1 Preparation of oligosaccharide chains

[0018] Add 5 μl of reagent A to 5 μl of inactivated serum sample for denaturation, cool to room temperature, add 5 μl of reagent B, react at 37°C for 3 h, and then dry;

[0019] Step 2: Labeling of oligosaccharide chains

[0020] Add 5 μl of reagent C to the sample obtained after drying in step 1, react at 60°C for 1 h, then perform fluorescent labeling, and then add 100 μl of reagent D to terminate the labeling reaction;

[0021] Step 3: Separation and analysis of oligosaccharide chains

[0022] Take 10 μL of the liquid obtained in step 2, separate the sugar chains using a sequencer, and obtain a sugar chain map;

[0023] Step 4: Data processing and analysis

[0024] Peak quantification of N-glycome profiles: The peak height of each peak was divided by the sum of the heights of all peaks to calculate the relative content of each peak.

[0025] A composition is used in a detection reagent for detecting depression by oligosaccharide chains, wherein the composition is composed of 15 sugar chains in serum: A3G3S3 (trisialylated galactosyl triantennary N-sugar chain), A2G2S(6)2 (disialylated galactosyl biantennary N-sugar chain), cFA3G3S3 (trisialylated galactosyl α-1,6 core fucosylated triantennary N-sugar chain), A2G2S(3)2 (disialylated galactosyl biantennary N-sugar chain), cFA2BG2S2 (disialylated galactosyl α-1,6 core fucosylated bisected biantennary N-sugar chain), A3G3S2 (disialylated galactosyl triantennary N-sugar chain), cFA3G3S(3)2 (disialylated galactosyl α-1,6 core fucosylated triantennary N-sugar chain), and cFA2G2S(6)1 (monosialylated galactosyl α-1,6 core fucosylated biantennary N-glycan), cFA2BG2S(3)1 (monosialylated galactosyl α-1,6 core fucosylated biantennary N-glycan), cFA2-2 (non-galactosyl α-1,6 core fucosylated biantennary N-glycan), cFA2B (non-galactosyl α-1,6 core fucosylated biantennary N-glycan). -glycans), cFA2(6)G1 (monogalactosyl α-1,6 core fucosylated biantennary N-glycans), cFA2(3)G1 (monogalactosyl α-1,6 core fucosylated biantennary N-glycans), A2G2 (galactosyl biantennary N-glycans) and cFA2G2 (galactosyl α-1,6 core fucosylated biantennary N-glycans), the composition is calculated by the formula

[0026] The value of DE=0.26×A3G3S3+0.82×A2G2S(6)2-0.89×A2G2S(3)2-1.58×cFA2G2S(6)1-1.00×cF A2-2+0.79×cFA2G2 is used to detect whether it is depression.

[0027] Preferably, the sample type in step 1 is blood, serum or plasma.

[0028] Preferably, the depression includes patients with depression with or without mental illness.

[0029] Preferably, the composition distinguishes depression patients from healthy people based on the value of sugar chain model DE.

[0030] Preferably, the composition detects whether the patient is suffering from depression according to the value of DE of the sugar chain model, and when DE is less than 0.14, the patient is in a non-depressive state, and when DE is greater than or equal to 0.14, the patient is in a depressive state.

[0031] The present invention has the following beneficial effects:

[0032] (1) The present invention quantifies each peak of the sugar chain spectrum, and then compares and analyzes the relative content results of each peak in patients with depression and healthy people, and finds that the N-sugar chain compositions A3G3S3, A2G2S(6)2, A2G2S(3)2, cFA2G2S(6)1, cFA2-2 and cFA2G2 have significant statistical differences between the two groups (p<0.05); therefore, based on the composition

[0033] The model DE established by 0.26×A3G3S3+0.82×A2G2S(6)2-0.89×A2G2S(3)2-1.58×cFA2G2S(6)1-1.00×cFA2-2+0.79×cFA2G2 had an AUC value of 0.958 under the ROC curve when distinguishing patients with depression. When the cutoff value of the model was 0.14, it had a sensitivity of 79.4% and a specificity of 100.0% for the detection of depression, indicating that the N-glycan composition in serum

[0034] 0.26×A3G3S3+0.82×A2G2S(6)2-0.89×A2G2S(3)2-1.58×cFA2G2S(6)1-1.00×cFA2-2+0.79×cFA2G2 can be used as a marker for auxiliary diagnosis of depression.

[0035] (2) The sugar chain detection method proposed in the present invention is based on the capillary microelectrophoresis technology (DSA-FACE) of the DNA sequencer. After the glycoprotein N-sugar chains in the serum sample are fluorescently labeled, they are separated by capillary microelectrophoresis. The glycoprotein content obtained by measuring the fluorescence signal is the natural oligosaccharide N-sugar group profile. The present invention detects the correlation between the changes in sialic acid oligosaccharide chains under physiological and pathological conditions and the disease state, and can establish a prediction model of the N-sugar chain composition based on these changes to assist in the diagnosis of depression.

[0036] (3) The present invention is the first to discover that there are differences between the sugar chain profiles in the blood of patients with depression and those of healthy people. It is therefore the first to propose that sugar chain profiles can be used as auxiliary diagnostic markers for patients with depression. A group of sugar chain markers were discovered and verified using a binary logistic regression model. These markers have high sensitivity and specificity for the diagnosis of depression and have the prospect of being developed into a clinical auxiliary diagnostic kit for depression.

[0037] (4) The present invention detects the relative content of sugar chains in the blood and uses combined markers to assist in the diagnosis of depression patients, which can overcome the difficulties and pain points in the current clinical diagnosis of depression and has important significance for the diagnosis and clinical intervention of depression.

[0038] (5) The natural N-glycome profile model constructed based on the method of the present invention can enable many patients to undergo routine, non-invasive testing, helping doctors and patients to timely monitor the occurrence and progression of depression. The detection technology of the present invention has the advantages of high sensitivity, simple operation, trace amount (5 μl serum), high repeatability, good stability, and high throughput (96-well plate), and can be promoted for use in clinical practice. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a comparison chart of sugar chains between healthy people and patients with depression.

[0040] The sugar chain composition consists of 15 kinds of sugar chains, namely 1-A3G3S3, 2-A2G2S(6)2, 3-cFA3G3S3, 4-A2G2S(3)2, 5-cFA2BG2S2, 6-A3G3S2, 7-cFA3G3S(3)2, 8-cFA2G2S(6)1, 9-cFA2BG2S(3)1, 10-cFA2-2, 11-cFA2B, 12-cFA2(6)G1, 13-cFA2(3)G1, 14-A2G2 and 15-cFA2G2; the differential sugar chains consist of 1-A3G3S3, 2-A2G2S(6)2, 4-A2G2S(3)2, 8-cFA2G2S(6)1, 10-cFA2-2 and 15-cFA2G2.

[0041] Figure 2 This is the ROC curve of the sugar chain model DE established based on sugar chain markers in distinguishing patients with depression from healthy people.

[0042] Based on the sugar chain markers A3G3S3 (trisialylated galactosyl triantennary N-glycan), A2G2S(6)2 (disialylated galactosyl biantennary N-glycan), A2G2S(3)2 (disialylated galactosyl biantennary N-glycan), cFA2G2S(6)1 (monosialylated galactosyl α-1,6 core fucosylated biantennary N-glycan), cFA2- The sugar chain model DE established by cFA2 (galactosyl α-1,6 core-fucosylated biantennary N-glycan) and cFA2G2 (galactosyl α-1,6 core-fucosylated biantennary N-glycan) was 0.26×A3G3S3+0.82×A2G2S(6)2-0.89×A2G2S(3)2-1.58×cFA2G2S(6)1-1.00×cF A2-2+0.79×cFA2G2; the area under the ROC curve AUC for distinguishing patients with depression from healthy subjects was 0.958. DETAILED DESCRIPTION

[0043] The present invention will be further described in detail below in conjunction with examples and accompanying drawings. It should be noted that the following examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. The application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the application.

[0044] The implementation content of the present application is further described in detail below through specific examples, and the experiments involved in the following examples are explained as follows.

[0045] Embodiment 1

[0046] 1. Test samples: This experiment collected blood samples from 31 patients with clinical diagnosis of depression and 63 blood samples from healthy people as controls. All participants signed informed consent. The clinical information of the samples is shown in Table 1.

[0047] Table 1 Clinical information of depression and healthy subjects

[0048] Depression (N=31) Healthy people (N=63) Age (mean ± SD) 39.23±14.84 37.27±12.60 Gender (female / male) 20 / 11 44 / 19

[0049] 2. Experimental equipment: capillary electrophoresis analyzer, PCR, centrifuge.

[0050] 3. Reagent preparation:

[0051] Reagent A: prepared by adding 1-5% SDS to a 10 mM ammonium bicarbonate solution with a pH of 8.3;

[0052] Reagent B: 0.05-10 units / 10 μl of glycosaminoglycans, 10% NP-40, and 10 mM ammonium bicarbonate solution at pH 8.3, with the pH value of the mixed solution being 5-9;

[0053] Reagent C: 8-aminopyrene-1,3,6-trisulfonic acid dissolved in DMSO to prepare an organic reducing agent with a concentration of 0.02mM to 1M;

[0054] Reagent D: Stop solution.

[0055] 4. Sugar chain map detection:

[0056] Step 1 Preparation of oligosaccharide chains

[0057] Add 5 μl of reagent A to 5 μl of inactivated serum sample for denaturation; after cooling to room temperature, add 5 μl of reagent B, react at 37°C for 3 hours, and then dry.

[0058] Step 2: Labeling of oligosaccharide chains

[0059] (1) Add 5 μl of reagent C to the dried sample and react at 60°C for 1 h for fluorescent labeling;

[0060] (2) After the fluorescent labeling is completed, add 100 μl of reagent D to terminate the labeling reaction.

[0061] Step 3: Separation and analysis of oligosaccharide chains

[0062] Take 10 μl of the oligosaccharide chain labeled liquid and perform N-oligosaccharide chain separation and detection on the ABI3500dx instrument to obtain the natural oligosaccharide N-glycome map.

[0063] Step 4: Data processing and analysis

[0064] (1) Peak quantification of N-glycome profiles: The peak height of each peak was divided by the sum of the heights of all peaks to calculate the relative content of each peak.

[0065] (2) Analysis of N-glycome data of patients with depression and healthy people: The N-glycome data of patients with depression and healthy people were compared and analyzed. The peak height of each peak was divided by the sum of all peak heights, and the relative content of each peak was quantitatively calculated, that is, the peak quantification of the N-glycome spectrum. Then, the 15 N-oligosaccharide chain peaks in the quantified N-glycome spectrum of the depression group and the healthy control group were compared and statistically analyzed. The composition of the N-glycome profile consists of A3G3S3, A2G2S(6)2, cFA3G3S3, A2G2S(3)2, cFA2BG2S2, A3G3S2, cFA3G3S(3)2, cFA2G2S(6)1, cFA2BG2S(3)1, cFA2-2, cFA2B, cFA2(6)G1, cFA2(3)G1, A2G2 and cFA2G2. The composition is used to detect depression by calculating the value of the formula DE=0.26×A3G3S3+0.82×A2G2S(6)2-0.89×A2G2S(3)2-1.58×cFA2G2S(6)1-1.00×cF A2-2+0.79×cFA2G2.

[0066] The peaks of the sugar chain map were quantified, and then the relative content results of each peak in patients with depression (31 cases) and healthy people (63 cases) were compared and analyzed. It was found that the N-sugar chain compositions A3G3S3, A2G2S(6)2, A2G2S(3)2, cFA2G2S(6)1, cFA2-2 and cFA2G2 were significantly different between the two groups (p<0.05); therefore, based on the composition

[0067] The model DE established by 0.26×A3G3S3+0.82×A2G2S(6)2-0.89×A2G2S(3)2-1.58×cFA2G2S(6)1-1.00×cFA2-2+0.79×cFA2G2 had an AUC value of 0.958 under the ROC curve when distinguishing patients with depression. When the cutoff value of the model was 0.14, it had a sensitivity of 79.4% and a specificity of 100.0% for the detection of depression, indicating that the N-glycan composition in serum

[0068] 0.26×A3G3S3+0.82×A2G2S(6)2-0.89×A2G2S(3)2-1.58×cFA2G2S(6)1-1.00×cFA2-2+0.79×cFA2G2 can be used as a marker for auxiliary diagnosis of depression.

[0069] The model DE was validated using patients with depression (21 cases) and healthy people (32 cases), with a sensitivity of 76.19% and a specificity of 96.88%. The specific results are shown in Table 2, indicating that the DE model established by the N-sugar chain composition in serum can be used as a marker for auxiliary diagnosis of depression.

[0070] Table 2 Depression DE verification results

[0071] type quantity Sensitivity Specificity depression 21 76.19％(16 / 21) - healthy 32 - 96.88％(31 / 32)

[0072] Embodiment 2

[0073] 1. Test samples: serum from patients with depression and healthy people.

[0074] 2. Experimental equipment: capillary electrophoresis analyzer, PCR, centrifuge.

[0075] 3. Reagent Preparation:

[0076] 1) Reagent A: prepared by adding 1% SDS to a 10 mM ammonium bicarbonate solution;

[0077] 2) Reagent B: 0.05 units / 10 μl of glycosaminoglycans, 10% NP-40, and 10 mM ammonium bicarbonate solution at a pH of 8.3, with a solution pH of 5;

[0078] 3) Reagent C: 8-aminopyrene-1,3,6-trisulfonic acid dissolved in DMSO to prepare an organic reducing agent with a concentration of 0.02 mM;

[0079] 4) Reagent D: ultrapure water.

[0080] 4. N-glycome profile detection is the same as in Example 1.

[0081] Embodiment 3

[0082] 1. Test samples: serum from patients with depression and healthy people.

[0083] 2. Experimental equipment: capillary electrophoresis analyzer, PCR, centrifuge.

[0084] 3. Reagent Preparation:

[0085] 1) Reagent A: prepared by adding 5% SDS to 10 mM ammonium bicarbonate solution;

[0086] 2) Reagent B: prepared by mixing 10 units / 10 μl of glycosaminoglycans, 10% NP-40, and 10 mM ammonium bicarbonate solution at a pH of 8.3. The pH value of the solution is 9;

[0087] 3) Reagent C: 8-aminopyrene-1,3,6-trisulfonic acid dissolved in DMSO to prepare an organic reducing agent with a concentration of 1 M;

[0088] 4) Reagent D: ultrapure water.

[0089] 4. N-glycome profile detection is the same as in Example 1.

[0090] Compared with the prior art, the detection method of the present invention detects the correlation between the changes in sialic acid oligosaccharide chains under physiological and pathological conditions and the disease state, and then establishes a prediction model of the N-sugar chain composition based on these changes to assist in judging the state of depression. The natural N-sugar group map model constructed based on the method of the present invention can allow many patients to undergo routine, non-invasive testing, help doctors and patients to timely monitor the occurrence and progression of depression, and can be promoted and used in clinical practice.

[0091] The specific embodiments described above in conjunction with the accompanying drawings further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention, but is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that any modification, equivalent replacement, improvement, etc. that can be made without creative work within the detection technology principle, sample type and sugar chain structure of the present invention should be included in the scope of protection of the present invention.

Claims

1. A detection reagent for detecting depression based on oligosaccharide chains, characterized in that: It is composed of the following reagents: Reagent A: Prepared by adding 1-5% SDS to 10 mM ammonium bicarbonate solution with a pH of 8.3; Reagent B: 0.05-10 units / 10 μl of glycosaminoglycans, 10% NP-40, and 10 mM ammonium bicarbonate solution at pH 8.3, with the pH value of the mixed solution being 5-9; Reagent C: 8-aminopyrene-1,3,6-trisulfonic acid dissolved in DMSO to prepare an organic reducing agent with a concentration of 0.02 mM to 1 M; Reagent D: Stop solution.

2. The detection reagent for detecting depression based on oligosaccharide chains according to claim 1, characterized in that: The volume ratio of reagent A, reagent B and reagent C is 1:1:

1.

3. The detection reagent for detecting depression based on oligosaccharide chains according to claim 2, characterized in that: The volumes of the reagent A, reagent B and reagent C are all 5 μl.

4. The detection reagent for detecting depression based on oligosaccharide chains according to claim 1, characterized in that: The reagent D is ultrapure water.

5. A method for preparing a detection reagent for detecting depression based on oligosaccharide chains according to claim 1, characterized in that: The following steps are involved: Step 1 Preparation of oligosaccharide chains Add 5 μl of reagent A to 5 μl of inactivated serum sample for denaturation, cool to room temperature, add 5 μl of reagent B, react at 37°C for 3 h, and then dry; Step 2: Labeling of oligosaccharide chains Add 5 μl of reagent C to the sample obtained after drying in step 1, react at 60°C for 1 h, then perform fluorescent labeling, and then add 100 μl of reagent D to terminate the labeling reaction; Step 3: Separation and analysis of oligosaccharide chains Take 10 μL of the liquid obtained in step 2, separate the sugar chains using a sequencer, and obtain a sugar chain map; Step 4: Data processing and analysis Peak quantification of N-glycome profiles: The relative content of each peak was calculated by dividing the peak height of each peak by the sum of the heights of all peaks.

6. The method for preparing a detection reagent for detecting depression based on oligosaccharide chains according to claim 5, characterized in that: The sample type in step 1 is blood, serum or plasma.

7. Use of a composition in a detection reagent for oligosaccharide chain detection of depression, characterized in that: The composition is composed of A3G3S3, A2G2S(6)2, cFA3G3S3, A2G2S(3)2, cFA2BG2S2, A3G3S2, cFA3G3S(3)2, cFA2G2S(6)1, cFA2BG2S(3)1, cFA2-2, cFA2B, cFA2(6)G1, cFA2(3)G1, A2G2 and cFA2G2 in serum. The composition detects whether depression occurs by calculating the value of the formula DE=0.26×A3G3S3+0.82×A2G2S(6)2-0.89×A2G2S(3)2-1.58×cFA2G2S(6)1-1.00×cFA2-2+0.79×cFA2G2.

8. Use of the oligosaccharide chain in a detection reagent for detecting depression according to claim 7, characterized in that: The depression includes patients with depression with or without mental illness.

9. Use of the oligosaccharide chain in a detection reagent for detecting depression according to claim 7, characterized in that: The composition distinguishes depression from healthy people based on the value of sugar chain model DE.

10. Use of the oligosaccharide chain in a detection reagent for detecting depression according to claim 9, characterized in that: The composition detects whether the patient is suffering from depression according to the value of DE of the sugar chain model. When DE is less than 0.14, the patient is in a non-depressive state, and when DE is greater than or equal to 0.14, the patient is in a depressive state.

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