Detection kit and detection method for juvenile depression marker

Abstract

The invention belongs to the technical field of teenager depression marker detection, and particularly relates to a teenager depression marker detection kit and a teenager depression marker detection method, the kit comprises an extraction liquid, an internal standard substance, a quality control substance and a mobile phase additive, the internal standard substance comprises a stable isotope labeled metabolic marker, the quality control substance comprises a standard metabolic marker, and the mobile phase additive comprises a mobile phase. The detection method comprises the following steps: S1, dissolving an internal standard substance by using a methanol-containing aqueous solution to prepare an internal standard stock solution; s2, methanol is added into the internal standard stock solution for dilution, uniform mixing is performed, and an extraction working solution is prepared; s3, taking a quality control product / sample, adding an extraction working solution, carrying out oscillation incubation, centrifuging, and taking supernate as a to-be-detected sample; s4, the sample to be detected is detected through a liquid chromatograph-mass spectrometer, various biomarkers related to depression in the body of the teenager can be rapidly and accurately detected, and an objective and reliable basis is provided for early diagnosis and illness state evaluation of the depression of the teenager.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of juvenile depression marker detection, and particularly relates to a juvenile depression marker detection kit and a detection method. BACKGROUND

[0002] Although the clinical manifestations of children and adolescents with depression are similar to those of adults in many aspects, they are easily overlooked. The common symptoms of adolescents may be irritability. Children and adolescents may not express guilt as adults do, and have some difficulty in describing sad emotions. Moreover, their sleep disturbance patterns may also be different from those of adults with depressive disorders, and they may complain of some unexplained abdominal pain, headache, anorexia and other symptoms. For adolescents, the poor academic performance and social function caused by depression are prominent. Juvenile depression is a serious mental illness that affects the physical and mental health and quality of life of adolescents.

[0003] Early and accurate diagnosis is crucial for the treatment and prognosis of juvenile depression. However, the current diagnosis of juvenile depression mainly relies on clinical symptom assessment and the subjective judgment of doctors: scales can only reflect subjective experiences in a certain period of time, and it is difficult to fully and dynamically present the true state of patients; while in terms of physiological indicators, electroencephalogram, electrocardiogram and other auxiliary functions, they lack specificity and cannot be used as the sole basis for diagnosis; observer assessment, such as information provided by parents and teachers, is subjective and one-sided, and they may ignore some subtle symptoms due to limited understanding of depression, or be influenced by their own expectations when judging the child's condition. In general, juvenile depression lacks objective and accurate biological detection indicators, resulting in low accuracy and reliability of diagnosis, and easy misdiagnosis and missed diagnosis.

[0004] With the continuous deepening of biomedical research, more and more studies have shown that there are many potential biomarkers related to depression in the human body, such as tryptophan-kynurenine pathway, which has been reported to be related to depression; the diagnostic accuracy of the combination of P5C, proline and glutamate for depression can reach 91.2%; and in the group of children and adolescents, adolescents with severe depression show significant purine metabolism disorder, and inosine in plasma may be selected as an independent biomarker for diagnosis. Through the detection of these biomarkers, objective evidence can be provided for the diagnosis of juvenile depression, and the possibility of early warning, screening and objective diagnosis of current juvenile depression can be provided.

[0005] In existing technologies, such as patent CN120009439A, a method for constructing serum endogenous biomarkers and a diagnostic model for depression was proposed. This study found that N-methyl-L-alanine, γ-aminobutyric acid, N-acetylneuraminic acid, N-acetylglycine, L-methionine, L-phenylalanine, thymidine, xanthine, decanoylcarnitine, aspartate-phenylalanine, and uric acid can serve as potential biomarkers for depression; the concentration ratio of N-acetylglycine to thymidine can be used to construct a diagnostic model for depression. However, the above combinations have not been validated in adolescent patients with depression. Previously, there were no specific test kits based on this technology for detecting biomarkers of depression in adolescents.

[0006] Other similar detection technologies, such as existing methods for detecting biomarkers like neurotransmitters and inflammatory factors, suffer from insufficient sensitivity and specificity. They cannot accurately detect trace biomarkers related to depression in adolescents and are easily affected by other substances in the sample, leading to inaccurate test results. These technologies fail to meet the needs for early and accurate diagnosis of depression in adolescents. Summary of the Invention

[0007] To address the problems in the existing technology, this invention provides a detection kit and method for biomarkers of adolescent depression, which aims to rapidly and accurately detect multiple biomarkers related to depression in adolescents, providing an objective and reliable basis for the early diagnosis and assessment of adolescent depression.

[0008] The technical problem solved by this invention is achieved by the following technical solution:

[0009] The present invention aims to provide a detection kit for biomarkers of adolescent depression, comprising an extract, an internal standard, a quality control, and a mobile phase additive. The internal standard includes a stable isotope-labeled metabolic biomarker, and the quality control includes standard metabolic biomarkers, including cyclic adenosine monophosphate, glucuronic acid, glutamic acid, and undecenoylcarnitine.

[0010] Extraction solution: Used to precipitate proteins in samples and release target biomarkers, facilitating subsequent separation and detection.

[0011] Internal standards: used to correct errors in the testing process and improve the accuracy and repeatability of test results.

[0012] Mobile phase additives: enable the effective separation of multiple biomarkers through gradient elution.

[0013] Quality control materials: These are standard metabolic markers at known concentrations used to calibrate the mass spectrometer, ensuring the accuracy and sensitivity of mass spectrometry detection. Quality control materials include low- and medium-concentration standards of the target analyte.

[0014] Further, the extraction solution uses methanol.

[0015] Further, the internal standard includes 13 C5-cyclic adenosine phosphate, 13 C6-glucuronic acid, 13 C5-glutamic acid and methyl- 32 H3-undecylenoyl carnitine.

[0016] Further, the mobile phase additive includes mobile phase A: 0.1% formic acid 1mM ammonium acetate solution; mobile phase B: 0.1% formic acid 1mM ammonium acetate acetonitrile solution.

[0017] A detection method of a detection kit for a juvenile depression marker, comprising the following steps:

[0018] S1: Dissolve the internal standard by using a methanol aqueous solution, and prepare an internal standard stock solution;

[0019] S2: Dilute the internal standard stock solution by adding methanol, mix well, and prepare an extraction working solution;

[0020] S3: Take the quality control sample / sample, add the extraction working solution, centrifuge after oscillation incubation, and take the supernatant as a sample to be detected;

[0021] S4: Detect the sample to be detected by using a liquid chromatograph mass spectrometer.

[0022] Further, in S2, the ratio of the internal standard stock solution and methanol is 1:99, v / v.

[0023] Further, in S3, the ratio of the extraction working solution and the sample is 6-10:1.

[0024] Further, in S3, vortex oscillation for 3 min, incubation at-20℃ for 60 min, and then centrifugation at-10℃ at 16000g for 15-20 min.

[0025] Further, the chromatographic conditions are as follows:

[0026] A Waters Xevo TQD ultra-high performance liquid chromatograph mass spectrometer, a Waters BEH Amide 1.7μm 2.1*100mm chromatographic column; mobile phase A is 0.1% formic acid 1mM ammonium acetate aqueous solution, mobile phase B is 0.1% formic acid 1mM ammonium acetate acetonitrile solution, and the column temperature is 30℃;

[0027] The mass spectrometry conditions and detection parameters are as follows:

[0028] Spray voltage 3.5kV, capillary temperature 320℃, sheath gas flow 35L / min, auxiliary gas flow 10L / min, scan range m / z 50-1000.

[0029] Further, the elution condition is:

[0030] The gradient elution flow rate is 0.3mL / min, the injection amount is 5uL, the elution program is: 0-1min, 5% mobile phase B; 1-3min, 5-10% mobile phase B; 3-6min, 10-65% mobile phase B; 6-16min, 65-95% mobile phase B; 16-17.5min, 95% mobile phase B; 17.5-18min, 95-5% mobile phase B; 18-21min, 5% mobile phase B.

[0031] The target biomarker is quantitatively analyzed in a multiple reaction monitoring (MRM) mode.

[0032] Metabolic marker name Parent ion Daughter ion Collision energy Scan mode Cyclic adenosine monophosphate 330.06 136 30 ES+ Glutamic acid 147.13 104 22 ES+ Glucuronic acid 193.03 113.1 25 ES- Undecylenoyl carnitine 328.25 85 28 ES+ .

[0033] Result analysis: the concentration of the to-be-tested substance is calculated according to the following formula:

[0034] C1=A1xC0 / A2xRRF

[0035] Wherein: C1 is the concentration (umol / L) of the to-be-tested substance; A1 is the mass spectrum response value of the to-be-tested substance; A2 is the mass spectrum response value of the internal standard corresponding to the to-be-tested substance; C0 is the concentration of the internal standard corresponding to the to-be-tested substance; RRF: the response factor corresponding to the to-be-tested substance, is 21.254.

[0036] Compared with the prior art, the beneficial technical effects of the present application are:

[0037] The detection kit and method for adolescent depression markers of the present application adopt LC-MS technology, can accurately detect and quantitatively analyze multiple adolescent depression related biomarkers at the same time, avoid the limitations of single biomarker detection, improve the accuracy and reliability of diagnosis, and are simple and fast, can process multiple samples at the same time, the detection process is short, and the detection result can be obtained in a short time, which provides convenience for clinical diagnosis. The required sample amount is only 20uL, the sensitivity is high; the kit contains quality control products, which can control the quality of the detection process, and ensure the accuracy and repeatability of the detection result.

[0038] The above description is only a summary of the technical scheme of the present application, in order to more clearly understand the technical means of the present application, it can be implemented according to the content of the specification, and in order to make the above content and purposes, characteristics and advantages of the present application more obvious and easy to understand, the following specific embodiments of the present application are described. DETAILED DESCRIPTION

[0039] The technical solutions of the present application will be further described in detail below in combination with specific examples. It should be understood that the following examples are only illustratively described and explained the present application, and should not be interpreted as limiting the scope of protection of the present application. Any technology realized based on the above description of the present application is covered within the scope of the present application.

[0040] In addition, unless otherwise specified, various raw materials, reagents, instruments and equipment used in the present application can be purchased or prepared by existing methods.

[0041] Example 1: Detection of adolescent depression markers

[0042] Preparation of internal standard stock solution:

[0043] Add 80 μL of methanol and 20 μL of ultrapure water to the internal standard freeze-dried bottle, shake gently to dissolve, and ultrasonic at low temperature for 1.5-2 h until completely dissolved. Prepare the internal standard stock solution, seal and store at 2-8°C in the dark.

[0044] Preparation of extraction working solution:

[0045] Remove the required amount of internal standard stock solution for the preparation of human, dilute with methanol according to the ratio of internal standard stock solution: methanol (1:99, v / v), mix well, and prepare the extraction working solution. Seal and store at 2-8°C in the dark.

[0046] Sample collection:

[0047] Use EDTA anticoagulant vacuum blood collection tubes to collect blood samples from adolescent subjects, gently invert several times to mix thoroughly, and place the blood collection tubes in a low-temperature centrifuge (centrifugation conditions: centrifugal force 8000r, centrifugation temperature 4°C, centrifugation time 10 min). After centrifugation, take the supernatant and store at -80°C.

[0048] Sample processing:

[0049] Take 20 μL of quality control product / sample, add 180 μL of extraction working solution, vortex for 3 min, incubate at -20°C for 60 min, then centrifuge at 16000g at -10°C for 20 min, and take the supernatant as the sample to be detected.

[0050] Elution conditions:

[0051] Gradient elution flow rate was 0.3 mL / min, injection volume was 5 μL. Elution program was: 0-1 min, 5% mobile phase B; 1-3 min, 5-10% mobile phase B; 3-6 min, 10-65% mobile phase B; 6-16 min, 65-95% mobile phase B; 16-17.5 min, 95% mobile phase B; 17.5-18 min, 95-5% mobile phase B; 18-21 min, 5% mobile phase B.

[0052] Analytical performance:

[0053] Linear range and lower limit of quantification

[0054]

[0055] Example 2: Kit performance verification

[0056] 1. Linear range

[0057] The isotopic internal standard quantitative method was used to establish the calibration curve, and the content of the analyte was calculated, with the concentration ratio of the standard as the X axis and the peak area ratio of the standard and the internal standard as the Y axis. The linear regression equation and linear correlation coefficient of the related analyte are shown in the table below, the linearity is good, the linear correlation coefficient r is all ≥0.99, which meets the acceptance standard.

[0058] Indicator Linear range Linear equation Correlation coefficient Cyclic adenosine monophosphate 0.2-50 Y = 0.09027X + 0.00902 0.9998 Glutamic acid 251-4078 Y = 0.08988X + 0.00986 0.9969 Glucuronic acid 192-2500 Y = 0.08979X + 0.00982 0.9941 Undecylenoyl carnitine 0.2-120 Y = 0.08982X + 0.0098 0.9954 .

[0059] 2. Lower limit of quantification

[0060] Ten samples with lower limit of quantification concentration were determined in parallel, and the detection results are shown in the table below, the relative deviation is less than 15%, and the CV is less than 10%, which meets the use requirements.

[0061] Cyclic adenosine monophosphate lower limit of quantification data

[0062]

[0063]

[0064] Glutamic acid lower limit of quantification data

[0065]

[0066] Glucuronic acid lower limit of quantification data

[0067]

[0068] Undecylenoyl carnitine lower limit of quantification data

[0069]

[0070]

[0071] 3. Precision verification

[0072] Take the same sample, repeat the detection 10 times according to the above detection method, and calculate the relative standard deviation (RSD) of the concentration of each target biomarker. The results show that the RSD of the concentration of each target biomarker is less than 10%, indicating that the kit has good repeatability.

[0073] Detection number Cyclic adenosine monophosphate Glutamic acid Glucuronic acid Undecylenoyl carnitine 1 4.344 691.444 463.618 10.027 2 4.318 688.734 465.438 10.318 3 4.213 670.862 477.128 9.367 4 4.339 689.520 492.431 9.500 5 4.139 686.701 476.536 9.759 6 4.221 688.587 495.614 9.403 7 4.349 687.353 469.710 9.798 8 4.320 694.684 479.957 9.424 9 4.256 662.933 466.310 10.491 10 4.164 692.840 475.771 10.390 CV 2.93％ 1.49％ 2.29％ 4.41％ .

[0074] 4. Accuracy

[0075] Add standard biomarkers of high, medium and low concentrations to the blank sample of known concentration to prepare a spiked sample, and detect according to the above detection method. Each concentration level is detected in parallel for 6 times, and the recovery rate is calculated. The results show that the recovery rate of each target biomarker is between 80%-110%, indicating that the kit has high accuracy.

[0076] Cyclic adenosine monophosphate

[0077] Detection number Low concentration marker detection value Medium concentration marker detection value High concentration marker detection value 1 0.333 19.596 49.684 2 0.287 18.587 50.330 3 0.338 19.208 50.320 4 0.327 19.230 50.544 5 0.298 18.566 51.308 6 0.328 18.891 50.377 Detection average 0.319 19.013 50.427 Actual concentration 0.35 20 50 Recovery rate 91.14％ 95.07％ 100.854％

[0078] Glutamic acid

[0079]

[0080]

[0081] Glucuronic acid

[0082] Detection number Low concentration marker detection value Medium concentration marker detection value High concentration marker detection value 1 162.108 930.686 1868.828 2 167.540 912.558 1901.310 3 165.598 933.327 1907.126 4 175.213 951.143 1861.532 5 171.752 948.838 1864.690 6 169.578 907.584 1923.055 Detection average 168.632 930.689 1887.757 Actual concentration 200 1000 2000 Recovery rate 84.316％ 93.069％ 94.388％

[0083] Undecylenoyl carnitine

[0084] Detection number Low concentration marker detection value Medium concentration marker detection value High concentration marker detection value 1 0.42 36.193 93.074 2 0.451 37.718 92.727 3 0.434 35.917 88.129 4 0.449 35.820 92.362 5 0.45 38.285 93.280 6 0.425 37.529 91.682 Detection average 0.438 36.910 91.876 Actual concentration 0.5 40 100 Recovery rate Detection number Low concentration marker detection value Medium concentration marker detection value High concentration marker detection value Detection average Actual concentration Recovery rate Detection number Low concentration marker detection value Medium concentration marker detection value High concentration marker detection value Detection average Actual concentration Recovery rate Detection number Low concentration marker detection value Medium concentration marker detection value High concentration marker detection value Detection average Actual concentration Recovery rate Detection number Low concentration marker detection value Medium concentration marker detection value High concentration marker detection value Detection average Actual concentration Recovery rate Detection number Low concentration marker detection value Medium concentration marker detection value High concentration marker detection value Detection average Actual concentration Recovery rate Detection number Low concentration marker detection value Medium concentration marker detection value High concentration marker detection value Detection average Actual concentration Recovery rate Detection number Low concentration marker detection value Medium concentration marker detection value High concentration marker detection value Detection average Actual concentration Recovery rate Detection number Low concentration marker detection value Medium concentration marker detection value High concentration marker detection value Detection average Actual concentration Recovery rate Detection number Low concentration marker detection value Medium concentration marker detection value High concentration marker detection value Detection average Actual concentration Recovery rate Detection number Low concentration marker detection value Medium concentration marker detection value High concentration marker detection value Detection average Actual concentration Recovery rate Detection number Low concentration marker detection value Medium concentration marker detection value High concentration marker detection value Detection average Actual concentration Recovery rate Detection number Low concentration marker detection value Medium concentration marker detection value High concentration marker detection value Detection average Actual concentration Recovery rate Detection number Low concentration marker detection value Medium concentration marker detection value High concentration marker 87.6％ 92.275％ 971.876％ .

[0085] 5. Stability

[0086] After the kit is placed under storage conditions of-20℃ for a certain period of time, the quality control sample is detected, and the change of the detection result is observed. The results show that under the specified storage conditions, the kit can remain stable within the effective period, and the detection result is reliable.

[0087] The above-mentioned example numbers of the present application are only for description, and do not represent the advantages and disadvantages of the examples.

[0088] The above describes the embodiments of the present application, but the present application is not limited to the above-described specific embodiments, and the above-described specific embodiments are only illustrative but not restrictive, and those skilled in the art can make many forms under the inspiration of the present application without departing from the purpose of the present application and the scope protected by the claims, which all belong to the protection of the present application.

Claims

1. A detection kit for biomarkers of adolescent depression, characterized in that, It includes extract, internal standards, quality control materials, and mobile phase additives. The internal standards include stable isotope-labeled metabolic markers, and the quality control materials include standard metabolic markers. The metabolic markers include cyclic adenosine monophosphate, glucuronic acid, glutamic acid, and undecenoylcarnitine.

2. The detection kit for biomarkers of adolescent depression as described in claim 1, characterized in that: Methanol was used as the extraction solution.

3. The detection kit for biomarkers of adolescent depression as described in claim 1, characterized in that: Internal standard products include 13 C5-cyclic adenosine monophosphate, 13 C6-glucuronic acid, 13 C5-glutamic acid and methyl- 32 H3-Undecenoylcarnitine.

4. The detection kit for biomarkers of adolescent depression as described in claim 1, characterized in that: The mobile phase additives include mobile phase A: 0.1% formic acid 1mM ammonium acetate solution; mobile phase B: 0.1% formic acid 1mM ammonium acetate acetonitrile solution.

5. The detection method of the detection kit for a biomarker of adolescent depression as described in any one of claims 1-4, characterized in that: Includes the following steps: S1: Dissolve the internal standard in an aqueous methanol solution to prepare the internal standard stock solution; S2: Add methanol to the internal standard stock solution to dilute, mix well, and prepare the extraction working solution; S3: Take the quality control sample / sample, add the extraction working solution, shake and incubate, then centrifuge, and take the supernatant as the sample to be tested; S4: The sample to be tested was analyzed using liquid chromatography-mass spectrometry.

6. The detection method of the detection kit for adolescent depression biomarkers as described in claim 5, characterized in that: In S2, the ratio of internal standard stock solution to methanol is 1:99, v / v.

7. The detection method of the detection kit for a biomarker of adolescent depression as described in claim 5, characterized in that: In S3, the ratio of extraction working solution to sample is 6-10:

1.

8. The detection method of the detection kit for adolescent depression biomarkers as described in claim 5, characterized in that: In S3, vortex for 3 min, incubate at -20℃ for 60 min, and then centrifuge at 16000g for 15-20 min at -10℃.

9. The detection method of the detection kit for adolescent depression biomarkers as described in claim 5, characterized in that: The chromatographic conditions are as follows: The ultra-high performance liquid chromatography-mass spectrometry system was a Waters Xevo TQD, with a Waters BEH Amide 1.7μm 2.1*100mm column; mobile phase A was 0.1% formic acid 1mM ammonium acetate aqueous solution, mobile phase B was 0.1% formic acid 1mM ammonium acetate acetonitrile solution, and the column temperature was 30℃; The mass spectrometry conditions and detection parameters are as follows: Spray voltage 3.5kV, capillary temperature 320℃, sheath gas flow rate 35L / min, auxiliary gas flow rate 10L / min, scanning range m / z 50-1000.

10. The detection method of the detection kit for adolescent depression biomarkers as described in claim 5, characterized in that: The elution conditions are: The gradient elution flow rate was 0.3 mL / min, and the injection volume was 5 μL. The elution program was as follows: 0-1 min, 5% mobile phase B; 1-3 min, 5-10% mobile phase B; 3-6 min, 10-65% mobile phase B; 6-16 min, 65-95% mobile phase B; 16-17.5 min, 95% mobile phase B; 17.5-18 min, 95-5% mobile phase B; 18-21 min, 5% mobile phase B.

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