WO2023035467A1 - Inosine as biomarker for alzheimer's disease, and use thereof - Google Patents

Abstract

A biomarker for Alzheimer's disease and the use thereof. The biomarker for Alzheimer's disease is inosine. It is detected for the first time that the level of inosine in a stool sample of a patient with Alzheimer's disease is significantly lower than that in a stool sample of a normal person. Inosine in the stool serves as the biomarker for Alzheimer's disease, and the early diagnosis of Alzheimer's disease can be assisted by detecting the level of inosine in the stool, which facilitates non-invasive and rapid detection, and has the characteristics of timeliness, convenience, high specificity and high sensitivity.

Description

A kind of Alzheimer's disease biomarker inosine and its application technical field

The invention belongs to the field of biotechnology, and relates to an Alzheimer's disease biomarker inosine and its application.

Background technique

Alzheimer's disease (Alzheimer disease, AD), also known as senile dementia, is a progressive degenerative disease of the central nervous system that occurs in old age, characterized by progressive memory impairment and cognitive function decline and daily life. It is characterized by loss of life ability, accompanied by neuropsychiatric symptoms such as personality changes, which seriously affects social and life functions. Since the pathogenesis of Alzheimer's disease is not fully clear, and its early symptoms are relatively secretive, Alzheimer's disease patients are easily missed or misdiagnosed. Currently, the diagnosis of AD mainly relies on memory scales, PET, and cerebrospinal fluid and blood. The level detection of pathological indicators such as Aβ and phosphorylated tau, however, the clinical detection results of these diagnostic indicators are still controversial, and there is still no effective detection evidence for the early symptoms of AD. Therefore, a new marker for the early diagnosis of AD Drug development is one of the important research directions in the field of AD diagnosis and treatment.

CN106062563A discloses a biomarker and method for early diagnosis of Alzheimer's disease, said AD biomarker is at least four selected from brain-derived neurotrophic factor (BDNF), insulin-like growth factor-1 (IGF-1), tumor growth factor beta 1 (TGF-beta1), vascular endothelial growth factor (VEGF), interleukin 18 (IL-18), and monocyte chemoattractant protein-1 (MCP-1) biomarkers , by analyzing its expression level, it can assist the early diagnosis of AD, but the accuracy and universality need to be further verified.

To sum up, how to develop AD markers with high accuracy and universality to expand the judgment basis for early diagnosis of AD is an urgent problem in the field of AD detection.

Contents of the invention

Aiming at the deficiencies and actual needs of the prior art, the present invention provides an Alzheimer's disease biomarker inosine and its application. The present invention is based on high-resolution non-targeted metabolomics analysis technology for qualitative and quantitative analysis of human feces metabolites According to the analysis, inosine in feces is used as a marker of Alzheimer's disease for the first time, and the detection of inosine level in feces can assist in the early diagnosis of Alzheimer's disease, and it has the characteristics of timeliness, convenience, high specificity and high sensitivity.

For reaching above-mentioned purpose, the present invention adopts following technical scheme:

In the first aspect, a biomarker of Alzheimer's disease, said biomarker of Alzheimer's disease is inosine.

Inosine, also known as inosine or inosine nucleoside, with the chemical formula C ₁₀ H ₁₂ N ₄ O ₅ , is a nucleoside compound formed by the combination of hypoxanthine and ribose. In de novo synthesis, inosinic acid (IMP) can be used as a precursor for the synthesis of adenylic acid (AMP) and guanylic acid (GMP), which is suitable for leukopenia, thrombocytopenia, various heart disease, acute and chronic hepatitis and liver cirrhosis, etc.

The present invention conducts qualitative and quantitative analysis on fecal metabolites based on high-resolution non-targeted metabolomics analysis technology, and detects that the level of inosine in feces samples of Alzheimer's disease is significantly lower than that in normal feces samples, and uses inosine in feces as Alzheimer's disease. Biomarkers of Alzheimer's disease can assist in the early diagnosis of Alzheimer's disease by detecting the level of inosine in feces.

In the second aspect, the present invention provides the application of the Alzheimer's disease biomarker as described in the first aspect in constructing an early diagnosis model of Alzheimer's disease and/or preparing an early diagnosis device for Alzheimer's disease.

In a third aspect, the present invention provides an early diagnosis model of Alzheimer's disease, wherein the input variables of the early diagnosis model of Alzheimer's disease include the peak intensity value of inosine mass spectrum described in the first aspect.

Preferably, the output variables of the Alzheimer's disease early diagnosis model include differential expression multiples, and the calculation formula of the differential expression multiples is shown in equation (1):

Preferably, the criteria for judging positive for Alzheimer's disease is that the differential expression factor is ≤0.58.

In the present invention, by fully comparing and analyzing the peak intensity values of inosine mass spectrum in normal stool samples and AD stool samples, and carrying out rational design, an early diagnosis model of Alzheimer's disease is constructed, and the model uses inosine The peak intensity of mass spectrometry is the input variable, and the differential expression fold is the output variable, which can quickly output the results and fully characterize the samples with abnormal inosine levels, thereby assisting the early diagnosis of Alzheimer's disease.

In a fourth aspect, the present invention provides an early diagnosis device for Alzheimer's disease, which includes the following units:

Sample preparation unit: prepare the sample to be tested into a sample solution to be tested that can be used for separation by liquid chromatography;

Detection unit: using the liquid chromatograph to separate the sample solution to be tested, using a mass spectrometer to perform data processing on the separated sample, and measuring the peak intensity value of the inosine mass spectrum described in the first aspect in the sample;

Analysis unit: input the detected peak intensity value of inosine mass spectrum into the early diagnosis model of Alzheimer's disease described in the third aspect for analysis;

Evaluation unit: output the differential expression multiple corresponding to the sample, and judge whether it is positive for Alzheimer's disease.

In the early diagnosis device for Alzheimer's disease of the present invention, each unit cooperates effectively, is simple and efficient, and can quickly complete sample processing, detection and obtain differential expression multiples, and at the same time, use rationally designed judgment criteria to detect positive results for Alzheimer's disease. Evaluation is of great significance for the early diagnosis of Alzheimer's disease.

Preferably, the sample to be tested comprises a stool sample.

Preferably, the preparation method of the sample solution to be tested includes adding the sample to be tested into an aqueous acetonitrile solution, centrifuging and collecting the supernatant to obtain the sample solution to be tested.

Preferably, the preparation method of the sample solution to be tested comprises the following steps:

(1) Take the sample to be tested and add it to pre-cooled methanol/acetonitrile/water solution, mix and sonicate for 25-35 minutes (for example, it can be 26min, 27min, 28min, 29min or 32min), and place it at -20～-15°C (for example, it can be -19°C, -18°C, -16°C or -17°C) for 5-15min (for example, 6min, 7min, 8min, 9min, 10min, 12min or 14min), at 0-4°C (for example, 1 ℃, 2℃ or 3℃), 12000～16000×g (such as 12200×g, 12400×g, 12600×g, 12800×g, 13200×g, 12600×g, 15000×g or 15800×g) Centrifuge for 15-25 minutes (for example, 16 minutes, 17 minutes, 18 minutes, 19 minutes, 20 minutes, 21 minutes, 22 minutes, 23 minutes or 24 minutes), take the supernatant and vacuum-dry to obtain the pretreated sample;

(2) Add the pretreated sample to 80-120 μL of acetonitrile aqueous solution to re-dissolve, vortex, and place at 0-4°C, 12000-16000×g (for example, 12200×g, 12400×g, 12600×g, 12800×g, ×g, 13200×g, 12600×g, 15000×g or 15800×g) centrifuge for 10-20min (for example, 11min, 12min, 13min, 14min, 15min, 16min, 17min, 18min or 19min), take the supernatant , to obtain the sample solution to be tested.

Preferably, the volume ratio of methanol, acetonitrile and water in the methanol/acetonitrile/water solution is (1-2):(1-2):1 including but not limited to 1.2:2:1, 1.2:1:1, 2 :2:1, 1.4:1.5:1, 1.6:1.2:1, 1.8:2:1, 1.9:1.8:1 or 1.1:1.4:1.

Preferably, the volume ratio of acetonitrile and water in the aqueous acetonitrile solution is (1-2):1, including but not limited to 1.1:1, 1.2:1, 1.3:1, 1.5:1, 1.6:1, 1.7:1 , 1.8:1 or 1.9:1.

Preferably, the liquid chromatograph includes an ultra-high performance liquid chromatograph.

Preferably, the ultra-high performance liquid chromatograph comprises Agilent 1290 Infinity LC ultra-high performance liquid chromatograph.

Preferably, the mass spectrometer comprises a tandem time-of-flight mass spectrometer.

Preferably, the tandem time-of-flight mass spectrometer includes AB Triple TOF 6600 mass spectrometer.

Preferably, the data processing includes:

Use the tandem time-of-flight mass spectrometer to collect the first-order spectrum and second-order spectrum of the separated sample, and convert the first-order spectrum and second-order spectrum into mzXML format, and then perform peak alignment and retention time Calibrate, extract peak area and identify the structure, and determine the peak intensity value of the inosine mass spectrum described in the first aspect in the sample.

As a preferred technical solution, the Alzheimer's disease early diagnosis device includes the following units:

Sample preparation unit: prepare the sample to be tested into a sample solution to be tested that can be used for separation by liquid chromatography;

Detection unit: use the liquid chromatograph to separate the sample solution to be tested, use a tandem time-of-flight mass spectrometer to collect the first-order spectrum and second-order spectrum of the separated sample, and collect the first-order spectrum The graph and the secondary spectrogram are converted into mzXML format, and then peak alignment, retention time correction, peak area extraction and structural identification are performed, and the peak intensity value of the inosine mass spectrum described in the first aspect of the sample is determined;

Analysis unit: input the detected peak intensity value of inosine mass spectrum into the early diagnosis model of Alzheimer's disease described in the third aspect for analysis;

Evaluation unit: output the differential expression multiple corresponding to the sample, and judge whether it is positive for Alzheimer's disease.

In the present invention, the detection of the level of inosine in the stool sample can be used as a diagnostic basis, combined with other detection results, to assist in the early diagnosis of Alzheimer's disease, and it is expected to improve the accuracy of the diagnosis of Alzheimer's disease, but It cannot be used alone as a diagnostic indicator for 100% diagnosis of Alzheimer's disease.

In the present invention, through KEGG pathway analysis, it is found that Inosine belongs to the ABC transporters pathway in the membrane transport pathway (Membrane transport pathway).

In the fifth aspect, the present invention provides the application of the Alzheimer's disease biomarker described in the first aspect in screening drugs for treating and/or preventing Alzheimer's disease.

That is, the Alzheimer's disease biomarker described in the first aspect is used as a target to screen a drug for treating and/or preventing Alzheimer's disease.

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

The invention detects for the first time that the level of inosine in feces samples of Alzheimer's disease is significantly lower than that of normal feces samples, uses inosine in feces as a biomarker of Alzheimer's disease, and provides an early diagnosis model and device for Alzheimer's disease , by detecting the level of inosine in feces, it can assist in the early diagnosis of Alzheimer's disease, which is helpful for non-invasive and rapid detection, and has the characteristics of timeliness, convenience, high specificity and high sensitivity.

Description of drawings

Figure 1 is a diagram of inosine levels in feces samples of AD model mice and wild-type mice;

Figure 2 is a map of the levels of mannose in the cerebral cortex samples of AD model mice and wild-type mice;

Figure 3 is a graph showing the level of myo-inositol in the cerebral cortex samples of AD model mice and wild-type mice;

Fig. 4 is a graph showing glycine levels in cerebral cortex samples of AD model mice and wild-type mice.

Detailed ways

In order to further illustrate the technical means and effects adopted by the present invention, the present invention will be further described below in conjunction with the embodiments and accompanying drawings. It should be understood that the specific implementation manners described here are only used to explain the present invention, rather than to limit the present invention.

If no specific technique or condition is indicated in the examples, it shall be carried out according to the technique or condition described in the literature in this field, or according to the product specification. The reagents or instruments used were not indicated by the manufacturer, and they were all conventional products commercially available through formal channels.

In the present invention, based on high-resolution non-targeted metabolomics analysis technology, metabolites in normal feces and AD feces samples are qualitatively and quantitatively analyzed, and differential molecules with biological significance (i.e. inosine) are screened and identified. Inosine is used as potential AD markers, and further verified the effectiveness of inosine as an AD marker through KEEG analysis and metabolite analysis of cerebral cortex samples. Comparative analysis and mining can fully characterize the judging criteria (i.e., differential expression multiple) of samples with abnormal levels of inosine, thereby assisting the early diagnosis of Alzheimer's disease.

Example 1

In this example, the qualitative and quantitative analysis of metabolites was carried out on fecal samples of 9-month-old AD model mice (APP/PS1 transgenic mice, provided by the Model Animal Research Institute of Nanjing University) and wild-type (WT) mice.

The feces of 10 AD model mice and 10 wild-type mice cultured under the same conditions were collected respectively. After the feces samples were collected, they were quickly frozen on dry ice, and then stored in a -80°C refrigerator. The wild-type mouse samples were numbered sequentially. They are FWT-1-1～FWT-1-10, and the AD model mouse samples are numbered FTG-1-1～FTG-1-10 in turn, and the samples are detected by ultra-high performance liquid chromatography-tandem time-of-flight mass spectrometry. Inosine levels, specific methods include:

(1) Take the feces sample and add pre-cooled methanol/acetonitrile/water solution, wherein the volume ratio of pre-cooled methanol, acetonitrile and water is 2:2:1, vortex and mix, cryogenic ultrasound for 30 minutes, and place it at -20°C for 10 minutes. Centrifuge at 4°C and 14,000×g for 20 minutes, take the supernatant and vacuum-dry to obtain the pretreated sample;

(2) Add the pretreated sample to 100 μL of acetonitrile aqueous solution (volume ratio: acetonitrile: water = 1:1) to redissolve, vortex, centrifuge at 4°C, 14000×g for 15 min, and take the supernatant for analysis. Agilent 1290 Infinity LC Ultra High Performance Liquid Chromatography System (UHPLC) HILIC column was used for separation, the column temperature was 25°C; the flow rate was 0.5mL/min; the injection volume was 2μL; the mobile phase composition included: Phase A: a mixture of ammonium acetate and ammonia water Aqueous solution (the final concentration of ammonium acetate and ammonia water are both 25mM), phase B: acetonitrile; the gradient elution program is as follows: 0 ~ 0.5min, 95% phase B; 0.5 ~ 7min, phase B changes linearly from 95% to 65%; 7 ～8min, phase B changes linearly from 65% to 40%; 8～9min, phase B maintains at 40%; 9～9.1min, phase B changes linearly from 40% to 95%; 9.1～12min, phase B maintains at 95% %; The sample was placed in an autosampler at 4°C throughout the analysis process;

(3) AB Triple TOF 6600 mass spectrometer is used to collect the first-order and second-order spectra of the samples separated by ultra-high performance liquid chromatography in step (2). The ESI source conditions are as follows: Ion Source Gas1 (Gas1): 60 , Ion Source Gas2 (Gas2): 60, Curtain gas (CUR): 30, source temperature: 600℃, IonSapary Voltage Floating (ISVF) ±5500V (positive and negative two modes); TOF MS scan m/z range: 60- 1000Da, product ion scan m/z range: 25-1000Da, TOF MS scan accumulation time 0.20s/spectra, product ion scan accumulation time 0.05s/spectra; the secondary mass spectrum is obtained by information dependent acquisition (IDA) and high sensitivity Mode, Declustering potential (DP): ±60V (both positive and negative modes), Collision Energy: 35±15eV, IDA settings are as follows: Exclude isotopes within 4Da, Candidate ions to monitor per cycle: 10, the collected original Wiff format The data was converted into mzXML format by ProteoWizard, and then the XCMS software was used for peak alignment, retention time correction and peak area extraction, and the metabolite structure identification was carried out on the data extracted by XCMS, and the level of inosine in the sample was analyzed, and the R language tool ( R package (ropls)) for Fold Change Analysis (FC Analysis), Principal Component Analysis (PCA), Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) and T Test (Student's t-test), the results As shown in Figure 1 and Table 1, the level of inosine in feces samples of AD model mice was significantly lower than that of wild-type mice, indicating that inosine in feces can be used as a biomarker for Alzheimer's disease, and by detecting inosine in feces Levels can assist in the early diagnosis of Alzheimer's disease.

Table 1

the	Metabolites	VIP	Differential expression fold	pvalue	significant
AD model mice vs wild-type mice	Inosine	1.82	0.58	0.007	**

Note: ** is p<0.01.

In addition, through further annotation and analysis of the KEGG pathway, it was found that inosine belongs to the ABC transporters pathway in the Membrane transport pathway. The pump is driven by two transmembrane domains and two cytoplasmic ATP-binding domains. Under normal physiological conditions, the ABC transporter is a transporter of sugars, amino acids, phospholipids and peptides on the bacterial plasma membrane, and a transporter of phospholipids, lipophilic drugs, cholesterol and other small molecules on the plasma membrane of mammalian cells. The plasma membranes of cells in organs such as kidneys and kidneys are abundant, which can remove natural poisons and metabolic wastes from the body.

Example 2

In this example, the qualitative and quantitative analysis of metabolites was performed on the cerebral cortex samples of 9-month-old AD model mice and wild-type (WT) mice.

The cerebral cortex samples of 10 AD model mice and 10 wild-type mice cultured under the same conditions were collected respectively. The mouse cerebral cortex samples were sequentially numbered CTG-1-1~CTG-1-10, and the metabolites were qualitatively and quantitatively analyzed by ultra-high performance liquid chromatography-tandem time-of-flight mass spectrometry, and the specific methods included:

(1) After the mouse was killed by neck dissection, the skull was cut open with surgical scissors to expose the brain, and the brain was cut into two halves along the midbrain seam, and the cerebellum, brainstem, thalamus, hypocortex and hippocampus were removed, leaving the cerebral cortex , collect the left and right sides of the complete cerebral cortex as a sample, add pre-cooled methanol/acetonitrile/water solution (volume ratio 2:2:1), vortex mix, cryogenic ultrasound for 30min, place at -20°C for 10min, and store at 4°C , Centrifuge at 14000×g for 20min, take the supernatant and carry out vacuum drying to obtain the pretreated sample;

(2) Add the pretreated sample to 100 μL of acetonitrile aqueous solution (volume ratio: acetonitrile: water = 1:1) to redissolve, vortex, centrifuge at 4°C, 14000×g for 15 min, and take the supernatant for analysis. Adopt Agilent 1290 Infinity LC ultra-high performance liquid chromatography system (UHPLC) HILIC chromatographic column to separate, and condition is identical with embodiment 1;

(3) AB Triple TOF 6600 mass spectrometer is used to collect the first-order and second-order spectrograms of the samples separated by the ultra-high performance liquid chromatography in step (2), the conditions are the same as in Example 1, and the collected Wiff format The original data were converted into mzXML format by ProteoWizard, and then XCMS software was used for peak alignment, retention time correction and peak area extraction, and the metabolite structure identification was performed on the data extracted by XCMS, followed by univariate statistical analysis, multidimensional statistical analysis, difference Metabolite screening, differential metabolite correlation analysis and KEGG pathway analysis, among which, the variable weight value (Variable Importance for the Projection, VIP) obtained by the OPLS-DA model can be used to measure the expression pattern of each metabolite and classify each group of samples Distinguish the influence strength and explanatory ability, and mine the differential molecules with biological significance. In this embodiment, the VIP value and p-value are comprehensively considered to screen the significant differential metabolites. The results are shown in Figure 2-Figure 4 and Table 2, AD The levels of mannose (D-Mannose), myo-Inositol (myo-Inositol) and glycine (Glycine) in the cerebral cortex of model mice were significantly higher than those of wild-type mice, and the above metabolites belong to the ABC transporters pathway in the Membrane transport pathway , In addition, genetic studies on AD patients have found that ABCA7 is an important AD risk gene, and genetic polymorphism variation at the ABCA7 locus can significantly increase the risk of AD, and is associated with AD pathological phenotypes such as Aβ deposition and brain atrophy. It is closely related, indicating that the ABC transporters pathway in the Membrane transport pathway is related to Alzheimer's disease, and the present invention finds that inosine also belongs to the ABC transporters pathway in the Membrane transport pathway, indicating from another aspect that inosine in feces metabolites Level changes may reflect the abnormality of related metabolic pathways in the AD brain, which is of great significance for early clinical diagnosis.

Table 2

the	Metabolites	VIP	Differential expression fold	pvalue	significant
AD model mice vs wild-type mice	Mannose	2.67	1.55	0.002	**
AD model mice vs wild-type mice	Inositol	10.80	1.10	0.026	*
AD model mice vs wild-type mice	Glycine	1.93	1.13	0.045	*

Note: * is p<0.05, ** is p<0.01.

In summary, the present invention detects for the first time that the level of inosine in feces samples of Alzheimer's disease is significantly lower than that in normal feces samples, uses inosine in feces as a biomarker of Alzheimer's disease, and provides Alzheimer's disease The early diagnosis model and device can assist in the early diagnosis of Alzheimer's disease by detecting the level of inosine in feces, which is helpful for non-invasive and rapid detection, and has the characteristics of timeliness, convenience, high specificity and high sensitivity.

The applicant declares that the present invention illustrates the detailed methods of the present invention through the above-mentioned examples, but the present invention is not limited to the above-mentioned detailed methods, that is, it does not mean that the present invention must rely on the above-mentioned detailed methods to be implemented. Those skilled in the art should understand that any improvement of the present invention, the equivalent replacement of each raw material of the product of the present invention, the addition of auxiliary components, the selection of specific methods, etc., all fall within the scope of protection and disclosure of the present invention.

Claims (9)

1. A biomarker for Alzheimer's disease, characterized in that the biomarker for Alzheimer's disease is inosine.
2. Application of the Alzheimer's disease biomarker according to claim 1 in constructing an early diagnosis model of Alzheimer's disease and/or preparing an early diagnosis device for Alzheimer's disease.
3. A kind of Alzheimer's disease early diagnosis model, it is characterized in that, the input variable of described Alzheimer's disease early diagnosis model comprises the peak intensity value of the inosine mass spectrum described in claim 1, described Alzheimer's disease The output variables of the early diagnosis model include differential expression multiples, and the calculation formula of the differential expression multiples is as shown in equation (1):

   
4. The early diagnosis model of Alzheimer's disease according to claim 3, characterized in that the criterion for positive Alzheimer's disease is that the differential expression multiple is ≤0.58.
5. An early diagnosis device for Alzheimer's disease, characterized in that the device includes the following units:

   Sample preparation unit: prepare the sample to be tested into a sample solution to be tested that can be used for separation by liquid chromatography;

   Detection unit: use the liquid chromatograph to separate the sample solution to be tested, use a mass spectrometer to perform data processing on the separated sample, and measure the peak intensity value of the inosine mass spectrum according to claim 1 in the sample;

   Analysis unit: input the detected peak intensity value of inosine mass spectrum into the early diagnosis model of Alzheimer's disease described in claim 3 or 4 for analysis;

   Evaluation unit: output the differential expression multiple corresponding to the sample, and judge whether it is positive for Alzheimer's disease.
6. The device of claim 5, wherein the sample to be tested comprises a stool sample.
7. The device according to claim 5 or 6, wherein the data processing comprises:

   Use the tandem time-of-flight mass spectrometer to collect the first-order spectrum and second-order spectrum of the separated sample, and convert the first-order spectrum and second-order spectrum into mzXML format, and then perform peak alignment and retention time Correction, extraction of peak area and structure identification, determination of the peak intensity value of the inosine mass spectrum according to claim 1 in the sample.
8. The device according to any one of claims 5-7, wherein the device comprises the following units:

   Sample preparation unit: prepare the sample to be tested into a sample solution to be tested that can be used for separation by liquid chromatography;

   Detection unit: use the liquid chromatograph to separate the sample solution to be tested, use a tandem time-of-flight mass spectrometer to collect the first-order spectrum and second-order spectrum of the separated sample, and collect the first-order spectrum The graph and the secondary spectrogram are converted into mzXML format, and then peak alignment, retention time correction, peak area extraction and structural identification are carried out, and the peak intensity value of the inosine mass spectrum described in claim 1 in the measurement sample is determined;

   Analysis unit: input the detected peak intensity value of inosine mass spectrum into the early diagnosis model of Alzheimer's disease described in claim 3 or 4 for analysis;

   Evaluation unit: output the differential expression multiple corresponding to the sample, and judge whether it is positive for Alzheimer's disease.
9. Application of the Alzheimer's disease biomarker according to claim 1 in screening drugs for treating and/or preventing Alzheimer's disease.

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