Alzheimer's disease biomarker based on blood metabolites and application thereof

Abstract

The invention relates to an Alzheimer's disease biomarker based on blood metabolites and application of the Alzheimer's disease biomarker. The biomarker comprises any one or a combination of at least two of orthocholic acid, beta-ursodesoxycholic acid, L-kynurenine or ribose lactone. By detecting the specific metabolite level, early diagnosis of Alzheimer's disease can be assisted, rapid detection is facilitated, and the kit has the characteristics of timeliness, convenience, high specificity and high sensitivity.

Description

Technical Field

[0001] The present invention belongs to the field of biotechnology and relates to a biomarker for Alzheimer's disease based on blood metabolites and its application. Background Art

[0002] Alzheimer disease (AD) is a progressive neurodegenerative disease of the central nervous system that occurs in old age, characterized by progressive memory impairment, cognitive decline, and loss of daily living ability, accompanied by neuropsychiatric symptoms such as personality changes, seriously affecting social and life functions, and has become a major public health problem affecting the world. Dementia usually occurs after the age of 65. However, with the development of society, factors such as the accelerating pace of life, high work pressure, and irregular diet and work and rest have led to an increasingly younger population of AD patients, and many elderly people in their 50s or even 40s have developed the disease. Since the pathogenesis of Alzheimer's disease has not been fully elucidated and its early symptoms are relatively hidden, Alzheimer's disease patients are easily misdiagnosed or missed. Therefore, finding biomarkers with high sensitivity and high accuracy is of great significance for the diagnosis and drug intervention of Alzheimer's disease. Currently, the diagnosis of AD mainly relies on memory scales, PET, and the detection of the levels of pathological indicators such as Aβ and phosphorylated tau in cerebrospinal fluid and blood. However, the detection results of these diagnostic indicators in clinical practice still have certain controversies, and there is still a lack of effective detection evidence for the early symptoms of AD.

[0003] Blood contains proteins, polypeptides, nucleic acids, lipids, and other metabolites, and blood specimens are easy to obtain and have little invasiveness. Therefore, blood-based biomarkers will help to clarify the complexity and heterogeneity of AD and can provide a rapid, non-invasive, and low-cost early detection strategy. In recent years, with the development of high-throughput omics technologies such as genomics, transcriptomics, proteomics, and metabolomics, the research and development of new biomarkers have been accelerated. In particular, metabolomics, through technologies such as magnetic resonance spectroscopy and mass spectrometry, monitors the dynamic changes of metabolite profiles, shows great advantages in screening disease-related biomarkers, and has broad application prospects in elucidating the molecular pathogenic mechanism of AD and the pathophysiological changes caused by it. Therefore, screening AD early diagnosis biomarkers based on blood metabolites is expected to improve the accuracy of AD diagnosis and contribute to early warning of the disease, pathological typing, and prediction and evaluation of the development stage. Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the purpose of the present invention is to provide a biomarker for Alzheimer's disease based on blood metabolites and its application.

[0005] To achieve the purpose of the present invention, the following technical solutions are adopted:

[0006] In a first aspect, the present invention provides an Alzheimer's disease biomarker based on blood metabolites, and the biomarker comprises any one or a combination of at least two of chenodeoxycholic acid, β-ursodeoxycholic acid, L-kynurenine or ribonolactone.

[0007] The present invention for the first time detects that the levels of four metabolites in the blood of Alzheimer's disease are significantly higher than those of normal samples, uses them as Alzheimer's disease biomarkers, and provides an early diagnosis model and device for Alzheimer's disease. By detecting the levels of specific metabolites, it can assist in the early diagnosis of Alzheimer's disease, contribute to rapid detection, and has the characteristics of timeliness, convenience, high specificity and high sensitivity.

[0008] In a second aspect, the present invention provides an application of the Alzheimer's disease biomarker based on blood metabolites according to the first aspect in constructing an early diagnosis model for Alzheimer's disease and / or preparing an early diagnosis device for Alzheimer's disease.

[0009] In a third aspect, the present invention provides an early diagnosis model for Alzheimer's disease, and the input variables of the early diagnosis model for Alzheimer's disease include the mass spectrometry peak intensity values of the Alzheimer's disease biomarkers described in the first aspect;

[0010] The output variables of the early diagnosis model for Alzheimer's disease include the fold change in expression.

[0011] Preferably, the calculation formula of the fold change in expression is as follows:

[0012]

[0013] Preferably, the judgment criterion for positive Alzheimer's disease is:

[0014] The fold change in expression of chenodeoxycholic acid ≥ 2.225, the fold change in expression of β-ursodeoxycholic acid ≥ 2.216, the fold change in expression of L-kynurenine ≥ 0.780, and the fold change in expression of ribonolactone ≥ 1.561.

[0015] In the present invention, an early diagnosis model for Alzheimer's disease is constructed. The model takes the mass spectrometry peak intensity values of Alzheimer's disease biomarkers as input variables and the fold change in expression as output variables, can quickly output results, and fully characterizes samples with abnormal levels of Alzheimer's disease biomarkers, thereby assisting in the early diagnosis of Alzheimer's disease.

[0016] In a fourth aspect, the present invention provides an early diagnosis device for Alzheimer's disease, and the device comprises the following units:

[0017] A sample preparation unit for performing the following steps:

[0018] For preparing a sample to be tested into a sample solution to be tested that can be separated by a liquid chromatograph;

[0019] A detection unit, configured to perform the following steps:

[0020] Separating the sample solution to be tested by using the liquid chromatograph, detecting the separated sample by using a mass spectrometer, performing data processing, and determining the mass spectrometry peak intensity value of the Alzheimer's disease biomarker described in the first aspect in the sample;

[0021] An analysis unit, configured to perform the following steps:

[0022] Inputting the detected peak intensity value of the Alzheimer's disease biomarker mass spectrometry into the Alzheimer's disease early diagnosis model described in the third aspect for data analysis, outputting the corresponding differential expression multiple of the sample, and determining whether it is positive for Alzheimer's disease.

[0023] In the early Alzheimer's disease diagnosis device of the present invention, each unit cooperates effectively, is simple and efficient, can quickly complete sample processing, detection and obtain the differential expression multiple, and at the same time performs Alzheimer's disease positive evaluation with a reasonably designed judgment criterion, which is of great significance for the early diagnosis of Alzheimer's disease.

[0024] Preferably, the sample to be tested includes serum.

[0025] Preferably, the data processing includes:

[0026] Using MultiQuant software to perform peak extraction on the MRM raw data, and calculating the ratio of the peak area of the Alzheimer's disease biomarker to the peak area of the internal standard as the mass spectrometry peak intensity value.

[0027] Preferably, the device includes the following units:

[0028] A sample preparation unit, configured to perform the following steps:

[0029] For preparing a sample to be tested into a sample solution to be tested that can be separated by a liquid chromatograph;

[0030] A detection unit, configured to perform the following steps:

[0031] Separating the sample solution to be tested by using the liquid chromatograph, detecting the separated sample by using a mass spectrometer, using MultiQuant software to perform peak extraction on the MRM raw data, and calculating the ratio of the peak area of the Alzheimer's disease biomarker to the peak area of the internal standard as the mass spectrometry peak intensity value.

[0032] An analysis unit, configured to perform the following steps:

[0033] Input the mass spectrometry peak intensity values of the detected Alzheimer's disease biomarkers into the Alzheimer's disease early diagnosis model described in the third aspect for data analysis, output the differential expression multiple corresponding to the sample, and determine whether it is positive for Alzheimer's disease.

[0034] Fifth aspect, the present invention provides an application of the Alzheimer's disease biomarker based on blood metabolites described in the first aspect as a target in screening drugs for treating or preventing Alzheimer's disease.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] The qualitative and quantitative information of blood metabolites is based on targeted metabolomics analysis technology. An ultra-high performance liquid chromatography-triple quadrupole mass spectrometer (UHPLC-QTRAP MS) is used to detect metabolites in the sample. This technology has high selectivity and high sensitivity, and uses a specifically developed sample preparation and chromatographic separation method to qualitatively and quantitatively analyze more than three hundred common intestinal flora metabolites.

[0037] The present invention first detected that the levels of 4 metabolites in the blood of Alzheimer's disease were significantly higher than those in normal samples. These were used as Alzheimer's disease biomarkers, and an early diagnosis model and device for Alzheimer's disease were provided. By detecting the levels of specific metabolites, it can assist in the early diagnosis of Alzheimer's disease, contribute to rapid detection, and has the characteristics of timeliness, convenience, high specificity, and high sensitivity. The present invention uses a combination of 4 blood metabolite markers and their mass spectrometry peak intensity values as detection indicators for auxiliary judgment of the symptoms of Alzheimer's disease, with the characteristics of high detection accuracy, convenience, speed, and safety and non-invasiveness, and has important clinical guiding significance for assisting in diagnosing AD-related indicators. Description of the Drawings

[0038] Figure 1 It is the mass spectrometry peak intensity map of chenodeoxycholic acid in the blood samples of AD model mice (AD) and wild-type control mice (WT).

[0039] Figure 2 It is the mass spectrometry peak intensity map of β-ursodeoxycholic acid in the blood samples of AD model mice (AD) and wild-type control mice (WT).

[0040] Figure 3 It is the mass spectrometry peak intensity map of L-kynurenine in the blood samples of AD model mice (AD) and wild-type control mice (WT).

[0041] Figure 4 It is the mass spectrometry peak intensity map of ribonolactone in the blood samples of AD model mice (AD) and wild-type control mice (WT). Detailed Embodiments

[0042] The technical solution of the present invention will be further described below through specific embodiments. Those skilled in the art should understand that the embodiments are only for helping to understand the present invention and should not be regarded as specific limitations on the present invention.

[0043] Experimental instruments and reagents involved in the following content:

[0044] AB 5500 / 6500 Q-trap mass spectrometer (AB SCIEX)

[0045] Agilent 1290 Infinity LC ultra-high pressure liquid chromatograph (Agilent)

[0046] Low-temperature high-speed centrifuge (Eppendorf 5430R)

[0047] Chromatographic column: Waters, ACQUITY UPLC BEH Amide 1.7 μm, 2.1 mm × 100 mm column

[0048] Waters, ACQUITY UPLC BEH C18 1.7 μm, 2.1 mm × 100 mm column

[0049] Acetonitrile (Merck, 1499230-935)

[0050] Ammonium acetate (Sigma, 70221)

[0051] Methanol (Fisher, A456-4)

[0052] Ammonia water (Sigma, 221228)

[0053] Ammonium formate (Sigma, 70221)

[0054] Formic acid (Sigma, 00940)

[0055] Isotope standard (Cambridge Isotope Laboratories)

[0056] Example 1

[0057] In this example, qualitative and quantitative analysis of metabolites was performed on blood samples of 9-month-old male AD model mice (FTG group, 10 mice) and WT wild-type control group (FWT group, 9 mice).

[0058] Sample extraction method

[0059] Serum samples were collected from diseased individuals and normal healthy control donors. An appropriate amount of the sample was added to pre-cooled methanol / acetonitrile / water solution (2:2:1, v / v), vortexed, ultrasonically treated at low temperature for 30 min, left standing at -20 °C for 10 min, centrifuged at 14000 g at 4 °C for 20 min, the supernatant was taken and dried under vacuum. When performing mass spectrometry analysis, it was re-dissolved by adding 100 μL of acetonitrile aqueous solution (acetonitrile: water = 1:1, v / v), vortexed, centrifuged at 14000 g at 4 °C for 15 min, and the supernatant was taken for injection analysis.

[0060] Chromatography - Mass spectrometry analysis

[0061] (1) Chromatographic conditions

[0062] The samples were separated using an Agilent 1290 Infinity LC ultra-high performance liquid chromatography system (UHPLC) with HILIC and C18 chromatographic columns; the column temperature of the HILIC chromatographic column was 35 °C; the flow rate was 0.3 mL / min; the injection volume was 2 μL; the mobile phase composition A: water + 100 mM ammonium acetate + 1.2% ammonia water, B: acetonitrile; the gradient elution program was as follows: 0 - 1.0 min, 85% B; 1.0 - 3.0 min, B linearly changed from 85% to 80%; 3.0 - 4.0 min, 80% B; 4.0 - 6.0 min, B linearly changed from 80% to 70%; 6.0 - 10.0 min, B linearly changed from 70% to 50%; 10 - 12.5 min, B was maintained at 50%; 12.5 - 12.6 min, B linearly changed from 50% to 85%; 12.6 - 18 min, B was maintained at 85%. The column temperature of the C18 chromatographic column was 40 °C; the flow rate was 0.4 mL / min; the injection volume was 2 μL; the mobile phase composition A: water + 50 mM ammonium formate + 0.4% formic acid, B: methanol; the gradient elution program was as follows: 0 - 5 min, B linearly changed from 5% to 60%; 5 - 11 min, B linearly changed from 60% to 100%; 11 - 13 min, B was maintained at 100%; 13 - 13.1 min, B linearly changed from 100% to 5%; 13.1 - 16 min, B was maintained at 5%; during the whole analysis process, the samples were placed in a 4 °C autosampler. To avoid the influence caused by the fluctuation of the instrument detection signal, the samples were analyzed continuously in a random order. QC samples were inserted into the sample queue to monitor and evaluate the stability of the system and the reliability of the experimental data.

[0063] (2) Mass spectrometry conditions

[0064] Mass spectrometry analysis was performed using an AB 6500 QTRAP mass spectrometer (AB SCIEX). The ESI source conditions were as follows: sheath gas temperature, 350 °C; dry gas temperature, 350 °C; sheath gas flow, 11 L / min; dry gas flow, 10 L / min; capillary voltage, 4000 V or -3500 V in positive or negative modes, respectively; nozzle voltage, 500 V; and nebulizer pressure, 30 psi. The MRM mode was used for monitoring.

[0065] (3) Data analysis process

[0066] Peak extraction was performed on the MRM raw data using MultiQuant or Analyst software to obtain the ratio of the peak area of each substance to the peak area of the internal standard. The content was calculated according to the standard curve.

[0067] Results of the inter-group difference comparison analysis ( Figures 1-4 ) showed that the levels of several metabolites, namely Apocholic acid, Beta-Ursodeoxycholic acid (b-UDCA), L-Kynurenine, and Ribonolactone, in the AD group were significantly different from those in the control group, indicating that these metabolites play an important role in differentiating this disease model. These results suggest that changes in blood metabolite levels may reflect abnormalities in related metabolic pathways in the AD brain and are of great significance for early clinical diagnosis.

[0068] The applicant declares that the present invention uses the above embodiments to illustrate a biomarker for Alzheimer's disease based on blood metabolites and its application, but the present invention is not limited to the above embodiments, that is, it does not mean that the present invention must rely on the above embodiments to be implemented. Those skilled in the art should understand that any improvement of the present invention, equivalent replacement of the raw materials of the products of the present invention, addition of auxiliary components, and selection of specific methods, etc., all fall within the protection scope and the disclosure scope of the present invention.

[0069] The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present invention, various simple modifications can be made to the technical solutions of the present invention, and these simple modifications all fall within the protection scope of the present invention.

[0070] In addition, it should be noted that, in the above specific embodiments, the various specific technical features described can be combined in any appropriate manner without conflict. To avoid unnecessary repetition, the present invention will not separately describe various possible combination methods.

Claims

1. A blood metabolite-based Alzheimer's biomarker, characterized in that The biomarker includes any one or a combination of at least two of cholic acid, β-ursodeoxycholic acid, L-kynurenine, or ribonolactone.

2. Use of the blood metabolite-based Alzheimer's biomarker according to claim 1 in constructing an early diagnosis model for Alzheimer's and / or preparing an early diagnosis device for Alzheimer's.

3. An early diagnosis model for Alzheimer's, characterized in that The input variable of the early diagnosis model for Alzheimer's disease includes the mass spectrometry peak intensity value of the Alzheimer's disease biomarker described in claim 1. The output variable of the early diagnosis model for Alzheimer's disease includes the fold change in expression.

4. The early diagnosis model for Alzheimer's according to claim 3, characterized in that The calculation formula for the fold change in expression is as follows:

5. The early diagnosis model for Alzheimer's according to claim 3 or 4, characterized in that The judgment criterion for positive Alzheimer's disease is: The fold change in expression of cholic acid ≥ 2.225, the fold change in expression of β-ursodeoxycholic acid ≥ 2.216, the fold change in expression of L-kynurenine ≥ 0.780, and the fold change in expression of ribonolactone ≥ 1.

561.

6. An early diagnosis device for Alzheimer's, characterized in that The device includes the following units: A sample preparation unit for performing the following steps: To prepare the sample to be tested into a sample solution to be tested that can be separated by a liquid chromatograph. A detection unit for performing the following steps: To separate the sample solution to be tested using the liquid chromatograph, detect the separated sample using a mass spectrometer, perform data processing, and determine the mass spectrometry peak intensity value of the Alzheimer's disease biomarker described in claim 1 in the sample. An analysis unit for performing the following steps: To input the detected peak intensity value of the Alzheimer's disease biomarker mass spectrometry into the early diagnosis model for Alzheimer's disease described in any one of claims 3-5 for data analysis, output the fold change in expression corresponding to the sample, and determine whether it is positive for Alzheimer's disease.

7. The device according to claim 6, characterized in that The sample to be tested includes serum.

8. The device according to claim 6 or 7, characterized in that The data processing includes: Using MultiQuant software to perform peak extraction on the MRM raw data, and calculating the ratio of the peak area of the Alzheimer's disease biomarker to the peak area of the internal standard as the mass spectrometry peak intensity value.

9. The device according to any one of claims 6-8, characterized in that The device includes the following units: A sample preparation unit for performing the following steps: To prepare the sample to be tested into a sample solution to be tested that can be separated by a liquid chromatograph. A detection unit for performing the following steps: To separate the sample solution to be tested using the liquid chromatograph, detect the separated sample using a mass spectrometer, use MultiQuant software to perform peak extraction on the MRM raw data, and calculate the ratio of the peak area of the Alzheimer's disease biomarker to the peak area of the internal standard as the mass spectrometry peak intensity value. An analysis unit for performing the following steps: To input the detected peak intensity value of the Alzheimer's disease biomarker mass spectrometry into the early diagnosis model for Alzheimer's disease described in any one of claims 3-5 for data analysis, output the fold change in expression corresponding to the sample, and determine whether it is positive for Alzheimer's disease.

10. Use of the blood metabolite-based Alzheimer's biomarker according to claim 1 as a target in screening drugs for treating or preventing Alzheimer's.

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