WO2023206759A1 - 一种阿尔兹海默症生物标志物及其应用 - Google Patents

一种阿尔兹海默症生物标志物及其应用 Download PDF

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WO2023206759A1
WO2023206759A1 PCT/CN2022/100604 CN2022100604W WO2023206759A1 WO 2023206759 A1 WO2023206759 A1 WO 2023206759A1 CN 2022100604 W CN2022100604 W CN 2022100604W WO 2023206759 A1 WO2023206759 A1 WO 2023206759A1
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alzheimer
acid
disease
sample
differential expression
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French (fr)
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陈宇
陈艺菁
李寅虎
樊颖颖
陈岳文
陈静
柴岳
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中国科学院深圳先进技术研究院
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    • G01N30/02—Column chromatography
    • G01N30/26—Conditioning of the fluid carrier; Flow patterns
    • G01N30/28—Control of physical parameters of the fluid carrier
    • G01N30/30—Control of physical parameters of the fluid carrier of temperature
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    • G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02—Column chromatography
    • G01N30/26—Conditioning of the fluid carrier; Flow patterns
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    • G—PHYSICS
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    • G01N30/02—Column chromatography
    • G01N30/26—Conditioning of the fluid carrier; Flow patterns
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    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
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    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6893—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
    • G01N33/6896—Neurological disorders, e.g. Alzheimer's disease
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02—Column chromatography
    • G01N30/26—Conditioning of the fluid carrier; Flow patterns
    • G01N30/28—Control of physical parameters of the fluid carrier
    • G01N30/32—Control of physical parameters of the fluid carrier of pressure or speed
    • G01N2030/324—Control of physical parameters of the fluid carrier of pressure or speed speed, flow rate

Definitions

  • This application belongs to the field of biotechnology and relates to an Alzheimer's disease biomarker and its application.
  • AD Alzheimer's disease
  • AD is a progressive degenerative disease of the central nervous system that occurs in old age, characterized by progressive memory impairment and cognitive function decline, as well as daily It is characterized by loss of living ability, accompanied by neuropsychiatric symptoms such as personality changes, which seriously affects social and life functions. Since the pathogenesis of Alzheimer's disease has not yet been fully understood, and its early symptoms are relatively secretive, patients with Alzheimer's disease are easily missed or misdiagnosed.
  • diagnosis of AD mainly relies on memory scales, PET, and cerebrospinal fluid and blood tests. Level detection of pathological indicators such as A ⁇ and phosphorylated tau protein.
  • the clinical detection results of these diagnostic indicators are still controversial, and there is still a lack of effective detection evidence for early symptoms of AD. Therefore, new methods for early diagnosis of AD are needed. The development of markers 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.
  • the AD biomarker is at least four selected from the group consisting of brain-derived neurotrophic factor (BDNF) and insulin-like growth factor-1.
  • Biomarkers in (IGF-1), tumor growth factor beta 1 (TGF- ⁇ 1), vascular endothelial growth factor (VEGF), interleukin 18 (IL-18), and monocyte chemoattractant protein-1 (MCP-1) by analyzing its expression level, it can assist in the early diagnosis of AD.
  • AD neurodegenerative diseases
  • the host and intestinal flora produce a large number of metabolites in the process of metabolizing food substances.
  • the diversity and abundance changes of the intestinal flora will have an important impact on the types and concentrations of small molecule metabolites in the body.
  • Data show that AD
  • the composition of the intestinal flora of patients is different from that of healthy peers, and more and more evidence shows that disorders of various metabolic pathways may mediate the pathogenesis and development of AD.
  • the imbalance of bacterial flora in AD may be important in the occurrence of metabolic disorders. Association, and changes in the body's peripheral metabolism may further lead to metabolic disorders in the central nervous system through blood circulation.
  • studying the relationship between intestinal flora metabolic homeostasis and the onset of AD and screening new AD biomarkers will help expand the basis for early diagnosis of AD and can be combined with other marker detection to improve AD diagnosis.
  • the accuracy is helpful for early warning of diseases, pathological classification, and prediction and evaluation of development stages.
  • This application provides an Alzheimer's disease biomarker and its application.
  • This application conducts qualitative and quantitative analysis of human fecal metabolites based on targeted metabolomics analysis technology, and uses the metabolites in feces as Alzheimer's disease markers. , detecting metabolite levels in feces can assist in the early diagnosis of Alzheimer's disease, and is timely, convenient, non-invasive, highly specific and sensitive.
  • this application provides an Alzheimer's disease biomarker, which Alzheimer's disease biomarker includes ⁇ -Muricholic acid (Beta-Muricholic acid), taurine- ⁇ -Muricholic acid ( Tauro- ⁇ -muricholic acid), Ursolic acid (Ursocholic acid), 7-Dehydrocholic acid (7-Dehydrocholic acid), Deoxycholic acid (Deoxycholic acid), Glycolithocholic acid-3-sulfate (Glycolithocholic acid -3-Sulfate), isodeoxycholic acid (Isodeoxycholic acid), hyodeoxycholic acid (Hyodeoxycholic acid) or omega-muricholic acid (Omega-muricholic acid) any one or a combination of at least two.
  • ⁇ -Muricholic acid Beta-Muricholic acid
  • taurine- ⁇ -Muricholic acid Tauro- ⁇ -muricholic acid
  • Ursolic acid Ursocholic acid
  • This application conducts qualitative and quantitative analysis of fecal metabolites based on targeted metabolomics analysis technology, and detects ⁇ -murinecholic acid, taurine- ⁇ -murinecholic acid, ursolic acid, 7-
  • the levels of dehydrocholic acid, deoxycholic acid, glycolithocholic acid-3-sulfate, isodeoxycholic acid, hyodeoxycholic acid, and ⁇ -murinecholic acid were significantly higher than those in normal stool samples, which were considered as Alzheimer's disease Alzheimer's disease biomarkers can assist in the early diagnosis of Alzheimer's disease by detecting levels in stool.
  • this application 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.
  • this application provides an Alzheimer's disease early diagnosis model.
  • the input variables of the Alzheimer's disease early diagnosis model include the mass spectrum peak intensity of the Alzheimer's disease biomarker described in the first aspect. value.
  • the output variables of the Alzheimer's disease early diagnosis model include differential expression folds, and the calculation formula of the differential expression folds is as shown in equation (1):
  • the criterion for determining Alzheimer's disease positivity is that the differential expression fold is ⁇ 1.22.
  • the differential expression multiple of ⁇ -mururcholic acid is ⁇ 1.56, the differential expression multiple of taurine- ⁇ -mururocholic acid is ⁇ 1.45, the differential expression multiple of ursolic acid is ⁇ 2.13, and the 7- The differential expression multiple of dehydrocholic acid is ⁇ 2.06, the differential expression multiple of the deoxycholic acid is ⁇ 1.25, the differential expression multiple of the glycolithocholic acid-3-sulfate is ⁇ 2.53, and the differential expression multiple of the isodeoxycholic acid
  • the expression fold is ⁇ 1.22, the differential expression fold of the porodeoxycholic acid is ⁇ 1.22, or the differential expression fold of the ⁇ -murine cholic acid is ⁇ 2.00.
  • an early diagnosis model for Alzheimer's disease was constructed through full comparative analysis of the mass spectrum peak intensity values of Alzheimer's disease biomarkers in normal stool samples and AD stool samples, and rational design.
  • the model uses the mass spectrum peak intensity values of Alzheimer's disease biomarkers as input variables and differential expression folds as output variables. It can quickly output results and fully characterize samples with abnormal levels of Alzheimer's disease biomarkers. Thus assisting in the early diagnosis of Alzheimer’s disease.
  • this application provides an early diagnosis device for Alzheimer's disease, which device includes the following units:
  • the sample preparation unit is used to perform the following steps:
  • the detection unit is used to perform the following steps:
  • the analysis unit is used to perform the following steps:
  • each unit cooperates effectively, is simple and efficient, and can quickly complete sample processing, detection and obtain differential expression multiples. At the same time, it can conduct Alzheimer's disease positivity with reasonably designed judgment criteria. Assessment is of great significance for the early diagnosis of Alzheimer’s disease.
  • the sample to be tested includes a stool sample.
  • the preparation method of the sample solution to be tested includes adding the sample to be tested into a methanol-acetonitrile aqueous solution, centrifuging and collecting the supernatant to obtain the sample solution to be tested.
  • the preparation method of the sample solution to be tested includes the following steps:
  • 12000 ⁇ 16000 ⁇ g for example, it can be 12200 ⁇ g, 12400 ⁇ g, 12600 ⁇ g, 12800 ⁇ g, 13200 ⁇ g, 12600 ⁇ g, 15000 ⁇ g or 15800 ⁇ g
  • Centrifuge for 15-25min for example, it can be 16min, 17min, 18min, 19min, 20min, 21min, 22min, 23min or 24min), take the supernatant and vacuum dry it to obtain a pretreated sample;
  • 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.
  • the volume ratio of acetonitrile and water in the acetonitrile aqueous 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.
  • the liquid chromatograph includes an ultra-high performance liquid chromatograph.
  • the ultra-high performance liquid chromatograph includes Agilent 1290 Infinity LC ultra-high performance liquid chromatograph.
  • the mass spectrometer includes a triple quadrupole mass spectrometer.
  • the triple quadrupole mass spectrometer includes an AB 5500/6500 Q-trap mass spectrometer (AB SCIEX).
  • the data processing includes:
  • the Alzheimer's disease early diagnosis device includes the following units:
  • the sample preparation unit is used to perform the following steps:
  • the detection unit is used to perform the following steps:
  • the analysis unit is used to perform the following steps:
  • the peak intensity value of the detected Alzheimer's disease biomarker mass spectrum is input into the Alzheimer's disease early diagnosis model according to any one of claims 3 to 5 for data analysis, and the differential expression fold corresponding to the sample is output, and Determine whether it is positive for Alzheimer's disease.
  • the detection of Alzheimer's disease biomarker levels in stool samples can be used as a diagnostic basis, combined with other test results, to assist in the early diagnosis of Alzheimer's disease, and is expected to improve Alzheimer's disease. Diagnostic accuracy, but does not alone serve as a diagnostic indicator that can 100% diagnose Alzheimer's disease.
  • Beta-Muricholic acid (b-MCA), Tauro- ⁇ -muricholic acid (b-TMCA), Ursocholic acid (UCA), and 7-Dehydrocholic acid (7-DHCA) all belong to primary bile acids (Primary bile acid), while Deoxycholic acid (DCA), Glycolithocholic acid-3-Sulfate, Isodeoxycholic acid (IsoDCA), Hyodeoxycholic acid (HDCA), Omega-muricholic acid ( ⁇ -MCA) are secondary bile acids (Secondary bile acid) acid), bile acids directly synthesized from cholesterol as raw materials in liver cells are called primary bile acids, including cholic acid and chenodeoxycholic acid.
  • Primary bile acids including cholic acid and chenodeoxycholic acid.
  • Primary bile acids can also be combined with glycine or taurine to generate conjugated primary bile acids. , respectively, are glycocholic acid, glycochenodeoxycholic acid, taurocholic acid and taurochenodeoxycholic acid.
  • Primary bile acids are acted upon by bacteria in the intestine and undergo 7-alpha dehydroxylation to generate bile acids, which are called bile acids. They are secondary bile acids, including deoxycholic acid and lithocholic acid.
  • 95% of various bile acids in the intestine are reabsorbed by the intestinal wall, and the rest are excreted in the feces.
  • this application 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.
  • Alzheimer's disease biomarker described in the first aspect as a target to screen drugs for treating and/or preventing Alzheimer's disease.
  • This application detects for the first time that the level of specific metabolites in Alzheimer's disease stool samples is significantly higher than that in normal stool samples, using it as an Alzheimer's disease biomarker, and provides an early diagnosis model and device for Alzheimer's disease, through Detecting specific metabolite levels in feces can assist in the early diagnosis of Alzheimer's disease, facilitate non-invasive and rapid detection, and is timely, convenient, highly specific and sensitive.
  • Figure 1 shows the levels of ⁇ -murinecholic acid in fecal samples of AD model mice and wild-type mice;
  • Figure 2 is a graph showing the levels of taurine- ⁇ -murine cholic acid in fecal samples of AD model mice and wild-type mice;
  • Figure 3 shows the levels of ursolic acid in fecal samples of AD model mice and wild-type mice
  • Figure 4 shows the levels of 7-dehydrocholic acid in fecal samples of AD model mice and wild-type mice
  • Figure 5 is a graph showing deoxycholic acid levels in fecal samples of AD model mice and wild-type mice;
  • Figure 6 is a graph showing glycolithocholic acid-3-sulfate levels in fecal samples of AD model mice and wild-type mice;
  • Figure 7 is a graph showing the levels of isodeoxycholic acid in fecal samples of AD model mice and wild-type mice;
  • Figure 8 is a graph showing porodeoxycholic acid levels in fecal samples of AD model mice and wild-type mice;
  • Figure 9 is a graph showing the levels of ⁇ -murine cholic acid in fecal samples of AD model mice and wild-type mice.
  • This example conducts qualitative and quantitative analysis of metabolites in fecal samples of 9-month-old AD model mice (APP/PS1 transgenic mice, provided by the Model Animal Institute of Nanjing University) and wild-type (WT) mice.
  • AD model mice and 9 AD model mice cultured under the same conditions were collected (mice were housed in a specific pathogen-free environment, with a 12-hour light/dark cycle, the temperature was maintained at 24°C, and sterile drinking water and standard feed were provided).
  • ultra-high performance liquid chromatography-mass spectrometry was used to detect ⁇ -murinecholic acid, taurine- ⁇ -murinecholic acid, ursolic acid, 7-dehydrocholic acid, and Deoxycholic acid, glycolithocholic acid-3-sulfate, isodeoxycholic acid, hyodeoxycholic acid, and omega-murinecholic acid levels by:
  • the Agilent 1290 Infinity LC ultra-high performance liquid chromatography system (UHPLC) is used for separation through HILIC and C18 chromatographic columns in sequence.
  • the HILIC column temperature is 25°C; the flow rate is 0.3mL/min; the injection volume is 2 ⁇ L; the mobile phase composition includes : Phase A: Mix 90% water with 10% acetonitrile by volume and add ammonium formate with a final concentration of 2mM (mmol/L).
  • Phase B Add 0.4% (volume percentage) formic acid to methanol; the gradient elution procedure is as follows: 0 ⁇ 1.0min, 85% B phase; 1.0 ⁇ 3min, B phase linearly changes from 85% to 80%; 3 ⁇ 4min, 80% B phase; 4 ⁇ 6min, B phase linearly changes from 80% to 70%; 6 ⁇ 10min, B changes linearly from 70% to 50%; 10 ⁇ 12.5min, B phase maintains 50%; 12.5 ⁇ 12.6min, B phase linearly changes from 50% to 85%; 12.6 ⁇ 18min, B phase maintains 85% ;
  • phase B mix according to volume ratio 99.5% acetonitrile and 0.5% ammonia
  • the gradient elution program is as follows: 0 to 5 minutes, phase B changes linearly from 5% to 60%; 5 to 11 minutes, phase B changes linearly from 60% to 100%; 11 to 13 minutes, phase B Maintained at 100%; 13-13.1min, phase B changes linearly from 100% to 5%; 13.1-16min, phase B maintained at 5%; throughout the analysis process, the sample is placed in the 4°C autosampler; in the sample queue Insert isotope standards (from Cambridge Isotope Laboratories) to monitor and evaluate the stability of the system and the reliability of experimental data;
  • AB 6500 QTRAP mass spectrometer (AB SCIEX) to perform mass spectrometry analysis of the sample after ultra-high performance liquid chromatography separation in step (4).
  • the ESI source conditions are as follows: sheath gas temperature, 350°C; dry gas temperature, 350°C; sheath gas flow, 11L/min; dry gas flow, 10L/min; capillary voltage, 4000V or-3500V in positive or negative modes, respectively; nozzle voltage, 500V; and nebulizer pressure, 30psi, monitored in MRM mode, using MultiQuant software Peak extraction was performed on the original MRM data, and the ratio of the peak area of each substance to the corresponding isotope standard internal standard peak area was obtained as the normalized peak intensity value of these metabolites, and the average peak intensity was plotted.
  • Alzheimer's disease biomarkers can assist in the early diagnosis of Alzheimer's disease by detecting the levels of Alzheimer's disease biomarkers in stool.
  • This example performs a classification analysis on the Alzheimer's disease biomarkers in the example.
  • Beta-Muricholic acid b-MCA
  • Tauro- ⁇ -muricholic acid b-TMCA
  • Ursocholic acid UAA
  • 7-Dehydrocholic acid 7-DHCA
  • primary bile acids belong to (Primary bile acid)
  • DCA Deoxycholic acid
  • Glycolithocholic acid-3-Sulfate Isodeoxycholic acid (IsoDCA), Hyodeoxycholic acid (HDCA)
  • Omega-muricholic acid ⁇ -MCA belongs to secondary bile acid (Secondary bile acid).
  • primary bile acids In liver cells, bile acids directly synthesized from cholesterol as raw materials are called primary bile acids, including cholic acid and chenodeoxycholic acid. Primary bile acids are also It can be combined with glycine or taurine to produce conjugated primary bile acids, namely glycocholic acid, glycochenodeoxycholic acid, taurocholic acid and taurochenodeoxycholic acid. Primary bile acids are affected by bacteria in the intestines. The bile acids generated by 7-alpha dehydroxylation are called secondary bile acids, including deoxycholic acid and lithocholic acid. On average, 95% of various bile acids in the intestine are reabsorbed by the intestinal wall, and the rest follow. Fecal excretion, these results suggest that changes in fecal metabolite levels may reflect abnormalities in AD-related metabolic pathways, which is of great significance for early clinical diagnosis.
  • this application detects ⁇ -murinecholic acid, taurine- ⁇ -murinecholic acid, ursolic acid, 7-dehydrocholic acid, deoxycholic acid, and glycine in Alzheimer’s disease stool samples for the first time.
  • the levels of lithocholic acid-3-sulfate, isodeoxycholic acid, hyodeoxycholic acid and ⁇ -murinecholic acid were significantly higher than those in normal fecal samples.
  • the corresponding metabolites in feces were used as Alzheimer's disease biomarkers and provided Alzheimer's disease early diagnosis models and devices can assist in the early diagnosis of Alzheimer's disease by detecting metabolite levels in feces, contribute to non-invasive and rapid detection, and are timely, convenient, highly specific and sensitive.

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Abstract

一种阿尔兹海默症生物标志物及其应用。阿尔兹海默症生物标志物包括β-鼠胆酸、牛磺-β-鼠胆酸、熊果酸、7-脱氢胆酸、脱氧胆酸、甘氨石胆酸-3-硫酸盐、异脱氧胆酸、猪去氧胆酸或ω-鼠胆酸中的任意一种或至少两种组合。首次检测到阿尔兹海默症粪便样本中特定代谢物水平显著高于正常粪便样本，将粪便样本中特定代谢物作为阿尔兹海默症生物标志物，通过检测粪便中水平能够辅助阿尔兹海默症早期诊断，有助于无创快速检测，且具备及时、方便、高特异性及高灵敏度的特点。

Description

一种阿尔兹海默症生物标志物及其应用 技术领域
本申请属于生物技术领域，涉及一种阿尔兹海默症生物标志物及其应用。
背景技术
阿尔兹海默症(Alzheimer disease，AD)，又称老年痴呆症，是一种发生于老年期的进行性发展的中枢神经系统退行性变性疾病，以渐进性记忆障碍及认知功能下降和日常生活能力丧失为特征，伴随人格改变等神经精神症状，严重影响社交与生活功能。由于阿尔兹海默症发病机制尚未完全明确，加上其早期症状比较隐秘，阿尔兹海默症患者容易被漏诊或错诊，目前对于AD的诊断主要依靠记忆量表、PET以及脑脊液、血液中Aβ、磷酸化tau蛋白等病理指标的水平检测，然而这些诊断指标在临床中的检测结果仍存在一定争议，而且对于AD发病早期的症状尚缺乏有效的检测证据，因此，对AD早期诊断新的标志物开发是AD诊疗领域的重要研究方向之一。
CN106062563A公开了一种用于阿尔兹海默症的早期诊断的生物标志物及方法，所述AD生物标志物是至少四种选自脑源性神经营养因子(BDNF)、胰岛素样生长因子-1(IGF-1)、肿瘤生长因子β1(TGF-β1)、血管内皮生长因子(VEGF)、白介素18(IL-18)和单核细胞趋化蛋白-1(MCP-1)中的生物标志物，通过分析其表达水平，能够辅助AD的早期诊断。
有研究发现多种神经精神疾病如帕金森、抑郁症、自闭症等与肠道菌群失衡有关，并且80％以上AD患者存在肠道菌群失衡的现象，提示肠道菌群稳态与AD等神经退行性疾病的发病进程密切相关。宿主和肠道菌群在代谢食物物质的过程中产生大量的代谢物，肠道菌群的多样性以及丰度的改变会对机体中 小分子代谢物的种类和浓度产生重要影响，有数据显示AD患者肠道菌群组成与健康同龄人不同，且越来越多证据表明各种代谢途径的紊乱可能介导AD的病理发生和发展，AD中的菌群失衡可能与机体代谢紊乱的发生有重要关联，而机体外周代谢改变又可能通过血液循环进一步导致中枢神经系统代谢紊乱。
综上所述，研究肠道菌群代谢稳态与AD发病的关系，筛选新的AD生物标志物，有助于扩充AD早期诊断的判断依据，可与其他标志物检测相互结合，提高AD诊断的准确性，有助于疾病的早期预警、病理分型以及发展阶段的预测评估等。
发明内容
本申请提供一种阿尔兹海默症生物标志物及其应用，本申请基于靶向代谢组学分析技术对人粪便代谢物进行定性定量分析，将粪便中代谢物作为阿尔兹海默症标志物，通过检测粪便中代谢物水平能够辅助阿尔兹海默症早期诊断，且具备及时、方便、无创、高特异性及高灵敏度的特点。
第一方面，本申请提供一种阿尔兹海默症生物标志物，所述阿尔兹海默症生物标志物包括β-鼠胆酸(Beta-Muricholic acid)、牛磺-β-鼠胆酸(Tauro-β-muricholic acid)、熊果酸(Ursocholic acid)、7-脱氢胆酸(7-Dehydrocholic acid)、脱氧胆酸(Deoxycholic acid)、甘氨石胆酸-3-硫酸盐(Glycolithocholic acid-3-Sulfate)、异脱氧胆酸(Isodeoxycholic acid)、猪去氧胆酸(Hyodeoxycholic acid)或ω-鼠胆酸(Omega-muricholic acid)中的任意一种或至少两种组合。
本申请基于靶向代谢组学分析技术对粪便代谢物进行定性定量分析，检测到阿尔兹海默症粪便样本中β-鼠胆酸、牛磺-β-鼠胆酸、熊果酸、7-脱氢胆酸、 脱氧胆酸、甘氨石胆酸-3-硫酸盐、异脱氧胆酸、猪去氧胆酸和ω-鼠胆酸水平均显著高于正常粪便样本，将其作为阿尔兹海默症生物标志物，通过检测粪便中水平能够辅助阿尔兹海默症早期诊断。
第二方面，本申请提供如第一方面所述的阿尔兹海默症生物标志物在构建阿尔兹海默症早期诊断模型和/或制备阿尔兹海默症早期诊断装置中的应用。
第三方面，本申请提供一种阿尔兹海默症早期诊断模型，所述阿尔兹海默症早期诊断模型的输入变量包括第一方面所述的阿尔兹海默症生物标志物的质谱峰强度值。
优选地，所述阿尔兹海默症早期诊断模型的输出变量包括差异表达倍数，所述差异表达倍数的计算公式如方程式(1)所示：
Figure PCTCN2022100604-appb-000001
优选地，阿尔兹海默症阳性的判断标准为所述差异表达倍数≥1.22。
优选地，所述β-鼠胆酸的差异表达倍数≥1.56、所述牛磺-β-鼠胆酸的差异表达倍数≥1.45、所述熊果酸的差异表达倍数≥2.13、所述7-脱氢胆酸的差异表达倍数≥2.06、所述脱氧胆酸的差异表达倍数≥1.25、所述甘氨石胆酸-3-硫酸盐的差异表达倍数≥2.53、所述异脱氧胆酸的差异表达倍数≥1.22、所述猪去氧胆酸的差异表达倍数≥1.22或所述ω-鼠胆酸的差异表达倍数≥2.00。
本申请中，通过对正常粪便样本和AD粪便样本中阿尔兹海默症生物标志物的质谱峰强度值进行充分对比分析，并进行理性设计，构建了一种阿尔兹海默症早期诊断模型，所述模型以阿尔兹海默症生物标志物的质谱峰强度值为输入变量，以差异表达倍数为输出变量，能够快速输出结果，且充分表征阿尔兹海默症生物标志物水平异常的样本，从而辅助阿尔兹海默症早期诊断。
第四方面，本申请提供一种阿尔兹海默症早期诊断装置，所述装置包括如下单元：
样本配制单元，用于执行包括以下步骤：
用于将待测样本配制成可用于液相色谱仪分离的待测样本溶液；
检测单元，用于执行包括以下步骤：
利用所述液相色谱仪分离所述待测样本溶液，利用质谱仪对分离后样本进行检测，进行数据处理，测定样本中第一方面所述的阿尔兹海默症生物标志物的质谱峰强度值；
分析单元，用于执行包括以下步骤：
将检测到的阿尔兹海默症生物标志物质谱的峰强度值输入第三方面所述的阿尔兹海默症早期诊断模型进行数据分析，输出样本对应的差异表达倍数，并判断是否为阿尔兹海默症阳性。
本申请的阿尔兹海默症早期诊断装置中，各单元间有效配合，简单高效，能够快速完成样本处理、检测及获得差异表达倍数，同时以经过合理设计的判断标准进行阿尔兹海默症阳性评估，对于阿尔兹海默症早期诊断具有重要意义。
优选地，所述待测样本包括粪便样本。
优选地，所述待测样本溶液的配制方法包括将待测样本加入甲醇-乙腈水溶液中，离心并收集上清液，得到所述待测样本溶液。
优选地，所述待测样本溶液的配制方法包括以下步骤：
(1)取待测样本加入预冷甲醇/乙腈/水溶液中，混合并超声25～35min(例如可以是26min、27min、28min、29min或32min)，置于-20～-15℃(例如可以是-19℃、-18℃、-16℃或-17℃)静置5～15min(例如可以是6min、7min、8min、9min、10min、12min或14min)，于0～4℃(例如可以是1℃、2℃或3℃)、 12000～16000×g(例如可以是12200×g、12400×g、12600×g、12800×g、13200×g、12600×g、15000×g或15800×g)离心15～25min(例如可以是16min、17min、18min、19min、20min、21min、22min、23min或24min)，取上清进行真空干燥，得到预处理样本；
(2)将所述预处理样本加入80～120μL乙腈水溶液中复溶，涡旋，于0～4℃、12000～16000×g(例如可以是12200×g、12400×g、12600×g、12800×g、13200×g、12600×g、15000×g或15800×g)离心10～20min(例如可以是11min、12min、13min、14min、15min、16min、17min、18min或19min)，取上清液，得到所述待测样本溶液。
优选地，所述甲醇/乙腈/水溶液中甲醇、乙腈和水的体积比为(1～2):(1～2):1包括但不限于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或1.1:1.4:1。
优选地，所述乙腈水溶液中乙腈和水的体积比为(1～2):1，包括但不限于1.1:1、1.2:1、1.3:1、1.5:1、1.6:1、1.7:1、1.8:1或1.9:1。
优选地，所述液相色谱仪包括超高效液相色谱仪。
优选地，所述超高效液相色谱仪包括Agilent 1290 Infinity LC超高效液相色谱仪。
优选地，所述质谱仪包括三重四级杆质谱仪。
优选地，所述三重四级杆质谱仪包括AB 5500/6500 Q-trap质谱仪(AB SCIEX)。
优选地，所述数据处理包括：
使用MultiQuant软件对MRM原始数据进行峰提取，计算阿尔兹海默症生物标志物的峰面积和内标峰面积的比值，作为质谱峰强度值。
作为优选的技术方案，所述阿尔兹海默症早期诊断装置包括如下单元：
样本配制单元，用于执行包括以下步骤：
将待测样本配制成可用于液相色谱仪分离的待测样本溶液；
检测单元，用于执行包括以下步骤：
利用所述液相色谱仪分离所述待测样本溶液，利用质谱仪对分离后样本进行检测，使用MultiQuant软件对MRM原始数据进行峰提取，计算阿尔兹海默症生物标志物的峰面积和内标峰面积的比值，作为质谱峰强度值；
分析单元，用于执行包括以下步骤：
将检测到的阿尔兹海默症生物标志物质谱的峰强度值输入权利要求3-5任一项所述的阿尔兹海默症早期诊断模型进行数据分析，输出样本对应的差异表达倍数，并判断是否为阿尔兹海默症阳性。
本申请中，对粪便样本中阿尔兹海默症生物标志物水平进行检测，可以作为一种诊断依据，与其他检测结果结合，辅助阿尔兹海默症早期诊断，预期可以提高阿尔兹海默症诊断的准确性，但并不单独作为能够100％诊断阿尔兹海默症的诊断指标。
本申请中，通过分类分析发现Beta-Muricholic acid(b-MCA)、Tauro-β-muricholic acid(b-TMCA)、Ursocholic acid(UCA)、7-Dehydrocholic acid(7-DHCA)同属于初级胆汁酸(Primary bile acid)，而Deoxycholic acid(DCA)、Glycolithocholic acid-3-Sulfate、Isodeoxycholic acid(IsoDCA)、Hyodeoxycholic acid(HDCA)、Omega-muricholic acid(ω-MCA)则属于次级胆汁酸(Secondary bile acid)，肝细胞内，以胆固醇为原料直接合成的胆汁酸称为初级胆汁酸，包括胆酸和鹅脱氧胆酸，初级胆汁酸也可以与甘氨酸或牛磺酸结合，生成结合型初级胆汁酸，分别是甘氨胆酸、甘氨鹅脱氧胆酸，牛磺胆酸及牛磺鹅脱氧胆酸， 初级胆汁酸在肠道中受细菌作用，进行7-α脱羟作用生成的胆汁酸，称为次级胆汁酸，包括脱氧胆酸和石胆酸，肠道中的各种胆汁酸平均有95％被肠壁重吸收，其余的随粪便排出，这些结果提示粪便代谢物水平变化可能反映AD相关代谢通路的异常，对临床早期诊断具有重要意义。
第五方面，本申请提供第一方面所述的阿尔兹海默症生物标志物在筛选治疗和/或预防阿尔兹海默症的药物中的应用。
即以第一方面所述的阿尔兹海默症生物标志物作为靶点筛选治疗和/或预防阿尔兹海默症的药物。
与现有技术相比，本申请具有以下有益效果：
本申请首次检测到阿尔兹海默症粪便样本中特定代谢物水平显著高于正常粪便样本，将其作为阿尔兹海默症生物标志物，并提供阿尔兹海默症早期诊断模型和装置，通过检测粪便中特定代谢物水平能够辅助阿尔兹海默症早期诊断，有助于无创快速检测，且具备及时、方便、高特异性及高灵敏度的特点。
附图说明
图1为AD模型小鼠和野生型小鼠的粪便样本中β-鼠胆酸水平图；
图2为AD模型小鼠和野生型小鼠的粪便样本中牛磺-β-鼠胆酸水平图；
图3为AD模型小鼠和野生型小鼠的粪便样本中熊果酸水平图；
图4为AD模型小鼠和野生型小鼠的粪便样本中7-脱氢胆酸水平图；
图5为AD模型小鼠和野生型小鼠的粪便样本中脱氧胆酸水平图；
图6为AD模型小鼠和野生型小鼠的粪便样本中甘氨石胆酸-3-硫酸盐水平图；
图7为AD模型小鼠和野生型小鼠的粪便样本中异脱氧胆酸水平图；
图8为AD模型小鼠和野生型小鼠的粪便样本中猪去氧胆酸水平图；
图9为AD模型小鼠和野生型小鼠的粪便样本中ω-鼠胆酸水平图。
具体实施方式
为进一步阐述本申请所采取的技术手段及其效果，以下结合实施例和附图对本申请作进一步地说明。可以理解的是，此处所描述的具体实施方式仅仅用于解释本申请，而非对本申请的限定。
实施例中未注明具体技术或条件者，按照本领域内的文献所描述的技术或条件，或者按照产品说明书进行。所用试剂或仪器未注明生产厂商者，均为可通过正规渠道商购获得的常规产品。
本申请实施例中实验仪器和试剂包括：
AB 5500/6500 Q-trap质谱仪(AB SCIEX)；
Agilent 1290 Infinity LC超高压液相色谱仪(Agilent)；
低温高速离心机(Eppendorf 5430R)；
色谱柱：Waters，ACQUITY UPLC BEH Amide 1.7μm，2.1mm×100mm column；Waters，ACQUITY UPLC BEH C18 1.7μm，2.1mm×100mm column；
乙腈(Merck，1499230-935)；
乙酸铵(Sigma，70221)；
甲醇(Fisher，A456-4)；
氨水(Sigma，221228)；
甲酸铵(Sigma，70221)；
甲酸(Sigma，00940)；
同位素标准品(Cambridge Isotope Laboratories)。
实施例1
本实施例对9月龄AD模型小鼠(APP/PS1转基因小鼠，由南京大学模式动物研究所提供)与野生型(WT)小鼠的粪便样本进行代谢物定性定量分析。
分别采集在相同条件下培养的(小鼠饲养在无特定病原体的环境中，12小时光照/黑暗循环，温度保持在24℃，提供灭菌饮用水和标准饲料)10只AD模型小鼠和9只野生型小鼠的粪便，采用超高效液相色谱-质谱联用分别检测粪便样本中的β-鼠胆酸、牛磺-β-鼠胆酸、熊果酸、7-脱氢胆酸、脱氧胆酸、甘氨石胆酸-3-硫酸盐、异脱氧胆酸、猪去氧胆酸和ω-鼠胆酸水平，具体方法包括：
(1)取粪便样本加入预冷甲醇/乙腈/水溶液(体积比为2:2:1)，涡旋混合，低温超声30min，置于-20℃静置10min，于4℃、14000×g离心20min，取上清进行真空干燥，得到预处理样本；
(2)将所述预处理样本加入100μL乙腈水溶液(体积比为乙腈:水＝1:1)中复溶，涡旋，于4℃、14000×g离心15min，取上清液，以备进样分析；
(3)采用Agilent 1290 Infinity LC超高效液相色谱系统(UHPLC)依次经HILIC和C18色谱柱进行分离，HILIC色谱柱柱温25℃；流速0.3mL/min；进样量2μL；流动相组成包括：A相：按体积比将90％水混合10％乙腈并加入终浓度为2mM(mmol/L)的甲酸铵，B相：甲醇中加入0.4％(体积百分比)甲酸；梯度洗脱程序如下：0～1.0min，85％B相；1.0～3min，B相从85％线性变化至80％；3～4min，80％B相；4～6min，B相从80％线性变化至70％；6～10min，B从70％线性变化至50％；10～12.5min，B相维持50％；12.5～12.6min，B相从50％线性变化至85％；12.6～18min，B相维持在85％；
C18色谱柱柱温40℃，流速0.4mL/min，进样量2μL；流动相组成A相：水中加入终浓度为5mM的乙酸铵和0.2％(体积百分比)氨水，B相：按体积 比混合99.5％乙腈和0.5％氨水；梯度洗脱程序如下：0～5min，B相从5％线性变化至60％；5～11min，B相从60％线性变化至100％；11～13min，B相维持在100％；13～13.1min，B相从100％线性变化至5％；13.1～16min，B相维持在5％；整个分析过程中样本置于4℃自动进样器中；样本队列中插入同位素标准品(来自于Cambridge Isotope Laboratories)，用于监测和评价系统的稳定性及实验数据的可靠性；
(5)采用AB 6500 QTRAP质谱仪(AB SCIEX)对步骤(4)超高效液相色谱系分离后的样本质谱分析，ESI源条件如下sheath gas temperature，350℃；dry gas temperature，350℃；sheath gas flow，11L/min；dry gas flow，10L/min；capillary voltage，4000V or-3500V in positive or negative modes，respectively；nozzle voltage，500V；and nebulizer pressure，30psi，采用MRM模式监测，使用MultiQuant软件对MRM原始数据进行峰提取，得到各物质的峰面积和相对应的同位素标准品内标峰面积的比值，作为这些代谢物归一化后的峰强度值，以峰强度平均值作图，结果如图1～图9所示，随后，基于各个样本归一化后的代谢物峰强度值，使用OPLS-DA分析去检测不同组别代谢物组成的差异，并筛选变量重要性(VIP)大于1的代谢物，然后，使用秩和检验对不同组别间的代谢物进行差异分析，获得p值小于0.05的差异代谢物，最后将筛选VIP>1和p<0.05的组间差异代谢物作为阿尔兹海默症生物标志物。
结果如图1～图9及表1所示，AD模型小鼠粪便样本中各阿尔兹海默症生物标志物水平显著高于野生型小鼠，表明可将粪便中特定代谢物作为阿尔兹海默症生物标志物，通过检测粪便中阿尔兹海默症生物标志物水平能够辅助阿尔兹海默症早期诊断。
表1
Figure PCTCN2022100604-appb-000002
注：*为p<0.05，**为p<0.01，***为p<0.001。
实施例2
本实施例对实施例中阿尔兹海默症生物标志物进行分类分析，通过分类分析发现Beta-Muricholic acid(b-MCA)、Tauro-β-muricholic acid(b-TMCA)、Ursocholic acid(UCA)、7-Dehydrocholic acid(7-DHCA)初级胆汁酸同属于(Primary bile acid)，而Deoxycholic acid(DCA)、Glycolithocholic acid-3-Sulfate、Isodeoxycholic acid(IsoDCA)、Hyodeoxycholic acid(HDCA)、Omega-muricholic acid(ω-MCA)则属于次级胆汁酸(Secondary bile acid)，肝细胞内，以胆固醇为原料直接合成的胆汁酸称为初级胆汁酸，包括胆酸和鹅脱氧胆酸，初级胆汁酸也可以与甘氨酸或牛磺酸结合，生成结合型初级胆汁酸，分别是甘氨胆酸、甘氨鹅脱氧胆酸，牛磺胆酸及牛磺鹅脱氧胆酸，初级胆汁酸在肠道中受细菌作 用，进行7-α脱羟作用生成的胆汁酸，称为次级胆汁酸，包括脱氧胆酸和石胆酸，肠道中的各种胆汁酸平均有95％被肠壁重吸收，其余的随粪便排出，这些结果提示粪便代谢物水平变化可能反映AD相关代谢通路的异常，对临床早期诊断具有重要意义。
综上所述，本申请首次检测到阿尔兹海默症粪便样本中β-鼠胆酸、牛磺-β-鼠胆酸、熊果酸、7-脱氢胆酸、脱氧胆酸、甘氨石胆酸-3-硫酸盐、异脱氧胆酸、猪去氧胆酸和ω-鼠胆酸水平显著高于正常粪便样本，将粪便中相应代谢物作为阿尔兹海默症生物标志物，并提供阿尔兹海默症早期诊断模型和装置，通过检测粪便中代谢物水平能够辅助阿尔兹海默症早期诊断，有助于无创快速检测，且具备及时、方便、高特异性及高灵敏度的特点。
申请人声明，本申请通过上述实施例来说明本申请的详细方法，但本申请并不局限于上述详细方法，即不意味着本申请必须依赖上述详细方法才能实施。所属技术领域的技术人员应该明了，对本申请的任何改进，对本申请产品各原料的等效替换及辅助成分的添加、具体方式的选择等，均落在本申请的保护范围和公开范围之内。

Claims (10)

  1. 一种阿尔兹海默症生物标志物，其包括β-鼠胆酸、牛磺-β-鼠胆酸、熊果酸、7-脱氢胆酸、脱氧胆酸、甘氨石胆酸-3-硫酸盐、异脱氧胆酸、猪去氧胆酸或ω-鼠胆酸中的任意一种或至少两种组合。
  2. 如权利要求1所述的阿尔兹海默症生物标志物在构建阿尔兹海默症早期诊断模型和/或制备阿尔兹海默症早期诊断装置中的应用。
  3. 一种阿尔兹海默症早期诊断模型，其中，所述阿尔兹海默症早期诊断模型的输入变量包括权利要求1所述的阿尔兹海默症生物标志物的质谱峰强度值；
    所述阿尔兹海默症早期诊断模型的输出变量包括差异表达倍数，所述差异表达倍数的计算公式如方程式(1)所示：
    Figure PCTCN2022100604-appb-100001
  4. 根据权利要求3所述的阿尔兹海默症早期诊断模型，其中，阿尔兹海默症阳性的判断标准为所述差异表达倍数≥1.22。
  5. 根据权利要求4所述的阿尔兹海默症早期诊断模型，其中，阿尔兹海默症阳性的判断标准为：
    所述β-鼠胆酸的差异表达倍数≥1.56、所述牛磺-β-鼠胆酸的差异表达倍数≥1.45、所述熊果酸的差异表达倍数≥2.13、所述7-脱氢胆酸的差异表达倍数≥2.06、所述脱氧胆酸的差异表达倍数≥1.25、所述甘氨石胆酸-3-硫酸盐的差异表达倍数≥2.53、所述异脱氧胆酸的差异表达倍数≥1.22、所述猪去氧胆酸的差异表达倍数≥1.22或所述ω-鼠胆酸的差异表达倍数≥2.00。
  6. 一种阿尔兹海默症早期诊断装置，其包括如下单元：
    样本配制单元，用于执行包括以下步骤：
    用于将待测样本配制成可用于液相色谱仪分离的待测样本溶液；
    检测单元，用于执行包括以下步骤：
    利用所述液相色谱仪分离所述待测样本溶液，利用质谱仪对分离后样本进行检测，进行数据处理，测定样本中权利要求1所述的阿尔兹海默症生物标志物的质谱峰强度值；
    分析单元，用于执行包括以下步骤：
    将检测到的阿尔兹海默症生物标志物质谱的峰强度值输入权利要求3-5任一项所述的阿尔兹海默症早期诊断模型进行数据分析，输出样本对应的差异表达倍数，并判断是否为阿尔兹海默症阳性。
  7. 根据权利要求6所述的装置，其中，所述待测样本包括粪便样本。
  8. 根据权利要求6或7所述的装置，其中，所述数据处理包括：
    使用MultiQuant软件对MRM原始数据进行峰提取，计算阿尔兹海默症生物标志物的峰面积和内标峰面积的比值，作为质谱峰强度值。
  9. 根据权利要求6-8任一项所述的装置，其中，所述装置包括如下单元：
    样本配制单元，用于执行包括以下步骤：
    将待测样本配制成可用于液相色谱仪分离的待测样本溶液；
    检测单元，用于执行包括以下步骤：
    利用所述液相色谱仪分离所述待测样本溶液，利用质谱仪对分离后样本进行检测，使用MultiQuant软件对MRM原始数据进行峰提取，计算阿尔兹海默症生物标志物的峰面积和内标峰面积的比值，作为质谱峰强度值；
    分析单元，用于执行包括以下步骤：
    将检测到的阿尔兹海默症生物标志物的质谱峰强度值输入权利要求3-5任一项所述的阿尔兹海默症早期诊断模型进行数据分析，输出样本对应的差异表达倍数，并判断是否为阿尔兹海默症阳性。
  10. 权利要求1所述的阿尔兹海默症生物标志物在筛选治疗和/或预防阿尔兹海默症的药物中的应用。
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