WO2024108603A1 - 基于粪便代谢物的神经退行性疾病标志物及其应用 - Google Patents

基于粪便代谢物的神经退行性疾病标志物及其应用 Download PDF

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WO2024108603A1
WO2024108603A1 PCT/CN2022/134517 CN2022134517W WO2024108603A1 WO 2024108603 A1 WO2024108603 A1 WO 2024108603A1 CN 2022134517 W CN2022134517 W CN 2022134517W WO 2024108603 A1 WO2024108603 A1 WO 2024108603A1
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neurodegenerative disease
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biomarker
determining
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陈宇
陈艺菁
李寅虎
樊颖颖
陈岳文
杨玉洁
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中国科学院深圳先进技术研究院
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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
    • G01N30/62—Detectors specially adapted therefor
    • G01N30/72—Mass spectrometers
    • G—PHYSICS
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    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • 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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • 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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • 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
    • G01N33/92—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving lipids, e.g. cholesterol, lipoproteins, or their receptors
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
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    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients

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  • the present invention relates to the field of biotechnology, and in particular to a neurodegenerative disease marker based on fecal metabolites and an application thereof.
  • Neurodegenerative diseases are a type of disease that results in dysfunction due to the gradual loss of neuronal structure or function, including Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), amyotrophic lateral sclerosis (ALS), and spinal muscular atrophy (SMA).
  • AD Alzheimer’s disease
  • PD Parkinson’s disease
  • HD Huntington’s disease
  • ALS amyotrophic lateral sclerosis
  • SMA spinal muscular atrophy
  • Alzheimer's and Parkinson's diseases With the development of society, the accelerated pace of life, increased work pressure, irregular diet and work and rest, and many other factors have led to the younger and younger population suffering from Alzheimer's and Parkinson's diseases. Originally, most of the patients were diagnosed after the age of 65, but now many people are in their 50s or even 40s. In addition, since the pathogenesis of neurodegenerative diseases has not been fully clarified, and their early symptoms are relatively hidden, patients are easily missed or misdiagnosed.
  • Alzheimer's disease Take Alzheimer's disease as an example.
  • This progressive degenerative disease of the central nervous system that occurs in old age is characterized by progressive memory impairment, cognitive decline, and loss of daily living ability, accompanied by neuropsychiatric symptoms such as personality changes.
  • the screening of Alzheimer's disease is mainly based on neuropsychological scales, imaging examinations, and biochemical index test results.
  • different detection methods have their limitations.
  • memory scales can be used to assess clinical symptoms, but the sensitivity and specificity of diagnosis are low.
  • positron emission tomography has the advantages of being non-invasive, in vivo, and real-time, but the detection cost is high.
  • biomarkers are biochemical indicators that can mark changes or possible changes in the structure or function of systems, organs, tissues, cells and subcellular structures, in order to understand the current biological state of the body, thereby providing a reference for the prevention, early diagnosis and treatment of neurodegenerative diseases.
  • biomarkers currently include ⁇ -amyloid protein and phosphorylated tau protein in cerebrospinal fluid, but the collection of cerebrospinal fluid is traumatic, which limits its clinical application.
  • the purpose of the present invention is to overcome the shortcomings of the prior art and solve the problem of low sensitivity and accuracy of existing neurodegenerative disease biomarkers based on fecal metabolites mentioned in the above background technology.
  • the present invention provides the following technical solutions:
  • a neurodegenerative disease biomarker comprising any one or more of acetylcholine, dopamine, caproic acid, azelaic acid, suberic acid, sebacic acid, 11Z,14Z,17Z-eicosatrienoic acid, 10,13-nonadecadienoic acid, and docosanoic acid.
  • the neurodegenerative disease biomarker is a combination of any one of azelaic acid, suberic acid, sebacic acid, 10,13-nonadecadienoic acid, docosanoic acid and acetylcholine, dopamine, caproic acid, and 11Z,14Z,17Z-eicosatrienoic acid.
  • the neurodegenerative disease biomarker is a combination of acetylcholine, dopamine, caproic acid, azelaic acid, suberic acid, sebacic acid, 11Z,14Z,17Z-eicosatrienoic acid, 10,13-nonadecadienoic acid, and docosanoic acid.
  • a method for determining the risk of occurrence of a neurodegenerative disease in a subject diagnosing a neurodegenerative disease in a subject, or determining the state of a neurodegenerative disease in a subject, the method comprising: S1, determining the level of the neurodegenerative disease biomarker in a biological sample from the subject; and S2, determining or diagnosing the risk of occurrence of a neurodegenerative disease, the presence of a neurodegenerative disease, or the state of a neurodegenerative disease with high specificity based on the level of the neurodegenerative disease biomarker, wherein the neurodegenerative disease biomarker
  • the substances include any one or more of acetylcholine, dopamine, caproic acid, azelaic acid, suberic acid, sebacic acid, 11Z,14Z,17Z-eicosatrienoic acid, 10,13-nonadecadienoic acid, and docosanoic acid, and an increase in acetylcholine, dopamine, caproic
  • the step S1 further includes: providing a biological sample from a subject.
  • the level of the neurodegenerative disease biomarker is determined by mass spectrometry peak height value and/or mass spectrometry peak area value.
  • the biological sample is selected from feces.
  • step S2 comprises comparing the level of the biomarker in the biological sample with a reference level of the biomarker, wherein the reference level is: an average level obtained from a population that does not suffer from a neurodegenerative disease; and/or an average or median level from a group of individuals including patients with a neurodegenerative disease, and wherein the level of the biomarker above or below a predetermined relative or absolute limit level, respectively, indicates a risk of developing a neurodegenerative disease, the presence of a neurodegenerative disease, or the presence of a severe neurodegenerative disease.
  • the reference level is: an average level obtained from a population that does not suffer from a neurodegenerative disease; and/or an average or median level from a group of individuals including patients with a neurodegenerative disease, and wherein the level of the biomarker above or below a predetermined relative or absolute limit level, respectively, indicates a risk of developing a neurodegenerative disease, the presence of a neurodegenerative disease, or the presence of a severe neurodegenerative disease.
  • step S2 the specificity of determining the risk of a neurodegenerative disease in a subject, diagnosing a neurodegenerative disease in a subject, or determining the status of a neurodegenerative disease in a subject has an accuracy of at least 90%, preferably at least 95%.
  • the third aspect of the present invention provides a kit comprising a detection tool and an instruction manual, wherein the instruction manual records the process and indicators for diagnosing a subject, and is characterized in that the detection tool consists of a tool for determining the biomarkers of the neurodegenerative disease, and optionally, the kit contains instructions on how to use the kit in the method of determining the risk of a neurodegenerative disease in a subject, diagnosing a neurodegenerative disease in a subject, or determining the status of a neurodegenerative disease in a subject.
  • the fourth aspect of the present invention provides a use of the neurodegenerative disease biomarker in screening drugs for treating or preventing neurodegenerative diseases.
  • the beneficial effect of the present invention is that the neurodegenerative disease biomarkers provided by this scheme can be used to assist in the judgment of symptoms of neurodegenerative diseases, have the characteristics of high detection accuracy, convenience, speed, safety and non-invasiveness, and have important clinical guiding significance for assisting in the diagnosis of neurodegenerative disease-related indicators.
  • Figure 1 is a graph showing acetylcholine content
  • Figure 2 is a comparison chart of the mean values of acetylcholine content
  • Figure 3 is a graph showing dopamine content
  • Figure 4 is a comparison chart of mean dopamine content
  • Fig. 5 is a graph showing the caproic acid content
  • FIG6 is a comparison chart of the mean values of caproic acid content
  • Figure 7 is a graph showing the content of 11Z, 14Z, and 17Z-eicosatrienoic acid
  • Figure 8 is a comparison chart of the mean values of 11Z, 14Z, and 17Z-eicosatrienoic acid contents
  • Figure 9 is a graph showing azelaic acid content
  • Figure 10 is a comparison chart of the mean values of azelaic acid content
  • Figure 11 is a graph showing suberic acid content
  • FIG12 is a comparison chart of the mean values of suberic acid content
  • Fig. 13 is a graph showing sebacic acid content
  • FIG14 is a comparison chart of mean values of sebacic acid content
  • Figure 15 is a graph showing the content of 10,13-nonadecadienoic acid
  • Figure 16 is a comparison chart of the mean values of 10,13-nonadecadienoic acid content
  • FIG17 is a graph showing docosanoic acid content
  • FIG. 18 is a comparison chart of mean values of docosanoic acid content.
  • AB 5500/6500 Q-trap mass spectrometer was purchased from AB SCIEX.
  • Agilent 1290 Infinity LC ultrahigh pressure liquid chromatograph was purchased from Agilent.
  • Low temperature high speed centrifuge 5430R was purchased from Eppendorf.
  • Chromatographic columns were purchased from Waters, and there were two types: ACQUITY UPLC BEH Amide 1.7 ⁇ m, 2.1mm ⁇ 100mm column; ACQUITY UPLC BEH C18 1.7 ⁇ m, 2.1mm ⁇ 100mm column.
  • Acetonitrile was purchased from Merck, product number 1499230-935.
  • Ammonium acetate was purchased from Sigma, product number 73594.
  • Methanol was purchased from Fisher, product number A456-4.
  • Ammonia water was purchased from Sigma, product number 221228. Ammonium formate was purchased from Sigma, product number 70221. Formic acid was purchased from Sigma, product number 00940. Isotope standards were purchased from Cambridge Isotope Laboratories.
  • the sensitivity (also known as the true positive rate) described in the present invention refers to the proportion of samples that are actually positive and are judged as positive, that is, the ability to correctly judge cases that are actually sick as sick.
  • Specificity (also known as the true negative rate) refers to the proportion of samples that are actually negative and are judged as negative, that is, the ability to correctly judge cases that are actually not sick.
  • Accuracy also known as efficiency is expressed as the percentage of the total number of true positives and true negatives to the total number of subjects.
  • the present invention provides a highly sensitive and accurate biomarker for neurodegenerative diseases based on fecal metabolites.
  • the combination contains a total of 8 fecal metabolite markers, and the mass spectrum peak intensity values thereof are used as detection indicators, which can be used to assist in the diagnosis of symptoms of neurodegenerative diseases. Because it has the characteristics of high detection accuracy, convenience, speed, safety and non-invasiveness, it has important clinical guiding significance for assisting the diagnosis of neurodegenerative diseases.
  • the present invention provides a method for determining the risk of occurrence of a neurodegenerative disease in a subject, diagnosing a neurodegenerative disease in a subject, or determining the status of a neurodegenerative disease in a subject, comprising: determining the level of a neurodegenerative disease biomarker in a biological sample from the subject; based on the level of the neurodegenerative disease biomarker, determining or diagnosing the risk of occurrence of a neurodegenerative disease, the presence of a neurodegenerative disease, or the status of a neurodegenerative disease with high specificity.
  • the present invention provides a kit, comprising a detection tool and instructions, wherein the detection tool consists of a tool for determining a biomarker of a neurodegenerative disease, and the instructions contain relevant content on how to use the kit in the above method.
  • the following article will use Alzheimer's disease as an example to introduce the specific biomarker detection process and results.
  • Example 1 Sample extraction and pretreatment
  • mice The 9-month-old mice were divided into two groups.
  • One group was the feces group of male Alzheimer's disease model mice, namely the Fecal Transgenic (FTG) group, with a total of 10 mice; the other group was the WT wild-type feces control group, namely the Fecal Wild Type (FWT) group, with a total of 9 mice.
  • FGS Fecal Transgenic
  • WT Fecal Wild Type
  • Example 2 During mass spectrometry analysis, 100 ⁇ L of acetonitrile aqueous solution was added to the pretreated sample obtained in Example 1 for reconstitution, wherein the volume ratio of acetonitrile to water was 1:1. The sample was then vortexed and centrifuged at 14,000 ⁇ g and 4° C. for 15 min, and the supernatant was sampled for analysis.
  • the qualitative and quantitative information of fecal metabolites is based on targeted metabolomics analysis technology, using ultra-high performance liquid chromatography-triple quadrupole mass spectrometry (UHPLC Q-TRAP/MS) for detection.
  • UHPLC Q-TRAP/MS ultra-high performance liquid chromatography-triple quadrupole mass spectrometry
  • This technology has high selectivity and high sensitivity, and uses targeted sample preparation and chromatographic separation methods to qualitatively and quantitatively analyze more than 300 common intestinal flora metabolites.
  • the column temperature of C18 chromatographic column was 40°C, the flow rate was 0.4mL/min, and the injection volume was 2 ⁇ L; the mobile phase A was water, 5mM ammonium acetate and 0.2% ammonia water, and the mobile phase B was 99.5% acetonitrile and 0.5% ammonia water; the elution gradient was: 0-5min B phase changed linearly from 5% to 60%, 5-11min B phase changed linearly from 60% to 100%, 11-13min B phase was maintained at 100%, 13-13.1min B phase changed linearly from 100% to 5%, 13.1-16min B phase was maintained at 5%; the samples were placed in the automatic sampler at 4°C during the entire analysis process.
  • QC samples were inserted into the sample queue, that is, samples obtained by mixing all samples to be tested with the same volume and following the same pretreatment method as the samples to be tested, which were used to monitor and evaluate the stability of the system and the reliability of experimental data.
  • Mass spectrometry conditions The mass spectrometer was an AB 6500 QTRAP system from AB SCIEX. Electrospray ionization (ESI) was used as the ionization mode, and the parameters were set as follows: sheath gas temperature 350°C; drying gas temperature 350°C; sheath gas flow rate 11 L/min; drying gas flow rate 10 L/min; capillary voltage 4000 V in positive ion mode and -3500 V in negative ion mode; nozzle voltage 500 V; nebulization pressure 30 psi; mass spectrometry multiple reaction monitoring (MRM) was used.
  • ESI Electrospray ionization
  • the inter-group difference analysis of the two groups of mice showed that the levels of the following metabolites in the AD group were significantly different from those in the control group, indicating that these metabolites play an important role in distinguishing the Alzheimer's disease model: Acetylcholine, Dopamine, Hexanoic acid, Azelaic acid, Suberic acid, Sebacic acid, 11Z,14Z,17Z-Eicosatrienoic acid, 10,13-Nonadecadienoic acid, and Docosanoic acid.
  • Figures 1-8 show the contents of acetylcholine, dopamine, caproic acid and 11Z,14Z,17Z-eicosatrienoic acid, respectively.
  • the average contents of these biomarkers in mice with Alzheimer's disease tend to increase relative to those in mice without the disease, suggesting that the subjects are at risk of developing Alzheimer's disease.
  • azelaic acid, suberic acid, sebacic acid, docosanoic acid and 10,13-nonadecadienoic acid in the feces of mice with Alzheimer's disease all showed a decreasing trend in their respective measurement dimensions.
  • these five biomarkers have overall synchronous and coordinated changes. In practical applications, one or more of them can be selectively selected for testing to save cost and time.
  • acetylcholine has the effect of enhancing memory. Excessive activity of acetylcholinesterase in Alzheimer's patients will accelerate the degradation of acetylcholine, causing cognitive and memory impairment. Dopamine has multiple functions such as regulating movement and emotional response and memory. Its abnormal secretion can lead to Parkinson's disease. At the same time, Alzheimer's patients lack dopamine in their brains and will experience symptoms of Parkinson's disease such as tremor, rigidity, and bradykinesia. The abnormal metabolism of peripheral neurotransmitters in the body and their effects on the central nervous system are still unclear.
  • Parkinson's patients also have abnormal secretion of neurotransmitters such as dopamine and acetylcholine.
  • neurotransmitters such as dopamine and acetylcholine.
  • changes in fatty acids such as plasma eicosatrienoic acid are closely related to Parkinson's disease, suggesting that the dynamic changes of these neurotransmitters and fatty acids in feces can be used as visible biomarkers for early diagnosis and tracking of Parkinson's disease progression.
  • the present invention uses the mass spectrometry peak intensity values of 8 fecal metabolic markers as detection targets or evaluation indicators, which can be used to assist in the judgment of symptoms of neurodegenerative diseases. It has the characteristics of high detection accuracy, convenience, speed, safety and non-invasiveness, and has important clinical guiding significance for assisting the diagnosis of indicators related to neurodegenerative diseases.

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Abstract

本发明涉及生物技术领域，具体涉及一种基于粪便代谢物的神经退行性疾病标志物及其应用。本方案提供的生物标志物具有高灵敏度、高准确度的特点，将其质谱峰强度值作为检测指标，能够以检测精确度高、方便快捷以及安全无创的方式为神经退行性疾病的临床早期辅助诊断提供重要参考。

Description

基于粪便代谢物的神经退行性疾病标志物及其应用 技术领域
本发明涉及生物技术领域，具体涉及一种基于粪便代谢物的神经退行性疾病标志物及其应用。
背景技术
神经退行性疾病是神经元结构或功能逐渐丧失导致功能障碍的一类疾病，包括阿尔兹海默症(Alzheimer disease，AD)、帕金森病(Parkinson’s disease，PD)、亨廷顿氏病(Huntington disease，HD)、肌萎缩侧索硬化症(Amyotrophic lateral sclerosis，ALS，俗称渐冻人症)以及脊髓性肌萎缩症(Spinal muscular atrophy，SMA)等。神经退行性疾病的发生严重影响了患者的生活与社交，目前已成为影响全球的重大公共健康问题。其中，阿尔兹海默症和帕金森病主要发生于中、老年，亨廷顿氏病、肌萎缩侧索硬化症以及脊髓性肌萎缩症在各年龄都可能发生。随着社会发展，生活节奏加快、工作压力变大、饮食与作息不规律等诸多因素导致阿尔兹海默症和帕金森病的患病人群日趋年轻化，原本多于65岁后发病，现在却有不少50多岁甚至40多岁的人患病。此外，由于神经退行性疾病的发病机制尚未完全明确，加上其早期症状比较隐秘，导致患者容易被漏诊或错诊。
以阿尔兹海默症为例，这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、认知功能下降以及日常生活能力丧失为特征，并伴随有人格改变等神经精神症状。现阶段对阿尔兹海默症的筛查主要通过神经心理学量表、影像学检查以及生化指标检查结果。然而，不同检测方式均有其局限性。比如，记忆量表能够用于评估临床症状，但诊断的灵敏度和特异性较低。又比如，正电子发射型计算机断层显像具有无创、在体、实时等优势，但检测成本较高。
为此，人们研究了多样的生物标志物，即可以标记系统、器官、组织、细胞及亚细胞结构或功能的改变或可能发生的改变的生化指标，以获知机体当前所处生物学状态，从而为神经退行性疾病的预防、早期诊断和治疗提供参考。以阿尔兹海默症为例，目前被广泛接受的生物标志物有脑脊液中的β-淀粉样蛋白和磷酸化tau蛋白，但脑脊液采集具有创伤性，限制了其临床应用。
进一步地，有研究通过获取方便的粪便了解肠道菌群情况，希望能以快速、非侵入且成本低廉的策略完成神经退行性疾病的早期诊断。在最近的研究中，人们发现多种神经精神疾病，如帕金森、抑郁症、自闭症等均与肠道菌群失衡有关，并且80％以上阿尔兹海默症患者存在肠道菌群失衡的现象，这提示肠道菌群稳态与阿尔兹海默症等神经退行性疾病的发病进程存在密切关联。
有数据显示，神经退行性疾病患者肠道菌群组成与健康同龄人不同，使得宿主和肠道菌群在代谢食物物质的过程中产生了大量不同的代谢物，这种肠道菌群多样性和丰度的改变也会对机体中小分子代谢 物的种类和浓度产生重要影响。此外，各种代谢途径的紊乱可能会反向介导神经退行性疾病的病理发生和发展。有研究表明，机体发生代谢紊乱可能会导致神经退行性疾病中菌群的失衡，同时，机体外周代谢的改变又可能通过血液循环进一步加大中枢神经系统代谢的紊乱。与此同时，随着衰老及年龄增长，肠黏膜屏障的通透性增加，导致一些机会致病菌和其代谢产物穿过屏障入侵内部组织器官，诱发了慢性肠道及全身炎症，这一现象也为阿尔兹海默症患病风险与年龄的高度正相关性提供了一种合理的解释。
因此，研究肠道菌群代谢稳态与神经退行性疾病发病的关系，基于粪便代谢物筛选神经退行性疾病早期诊断生物标志物，预期可以提高神经退行性疾病诊断的准确性，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。然而，基于粪便代谢物，寻找具有高灵敏度、高准确度的潜在生物标志物仍是一项困难的工作。
发明内容
本发明的目的在于克服现有技术不足，解决上述背景技术中提到的现有基于粪便代谢物的神经退行性疾病生物标志物灵敏度和准确度较低问题。
为实现上述目的，本发明提供以下技术方案：
本发明的第一方面，提供一种神经退行性疾病生物标志物，包括乙酰胆碱、多巴胺、己酸、壬二酸、辛二酸、癸二酸、11Z,14Z,17Z-二十碳三烯酸、10,13-十九碳二烯酸、二十二烷酸中的任意一种或多种。
优选地，所述神经退行性疾病生物标志物为壬二酸、辛二酸、癸二酸、10,13-十九碳二烯酸、二十二烷酸中的任意一种和乙酰胆碱、多巴胺、己酸、11Z,14Z,17Z-二十碳三烯酸的组合。
更优选地，所述神经退行性疾病生物标志物为乙酰胆碱、多巴胺、己酸、壬二酸、辛二酸、癸二酸、11Z,14Z,17Z-二十碳三烯酸、10,13-十九碳二烯酸、二十二烷酸的组合。
本发明的第二方面，提供一种确定受试者中神经退行性疾病发生风险、诊断受试者中神经退行性疾病或确定受试者中神经退行疾病的状态的方法，所述方法包括：S1、测定来自受试者的生物样品中所述神经退行性疾病生物标志物的水平；和S2、基于所述神经退行性疾病生物标志物的水平，以高的特异性确定或诊断发生神经退行性疾病的风险、神经退行性疾病的存在或神经退行性疾病的状态，其中所述神经退行性疾病生物标志物包括乙酰胆碱、多巴胺、己酸、壬二酸、辛二酸、癸二酸、11Z,14Z,17Z-二十碳三烯酸、10,13-十九碳二烯酸、二十二烷酸中的任意一种或多种，并且其中乙酰胆碱、多巴胺、己酸和/或11Z,14Z,17Z-二十碳三烯酸的增多，和/或壬二酸、辛二酸、癸二酸、10,13-十九碳二烯酸和/或二十二烷酸的减少指示发生神经退行性疾病的风险、神经退行性疾病的存在或严重神经退行性疾病的存在。
在一些实施例中，所述步骤S1前还包括：提供来自受试者的生物样品。
在一些实施例中，所述步骤S1中，所述神经退行性疾病生物标志物的水平通过质谱峰高度值和/或质谱峰面积值确定。
在一些实施例中，所述步骤S1中，所述生物样品选自粪便。
在一些实施例中，所述步骤S2包括将所述生物样品中所述生物标志物的水平与所述生物标志物的参比水平进行比较，其中所述参比水平是：从未患有神经退行性疾病的群体获得的平均水平；和/或来自包括神经退行性疾病的患者的个体的组的平均或中值水平，并且其中分别在预定的相对或绝对界限水平之上或之下，所述生物标志物的水平指示发生神经退行性疾病的风险、神经退行性疾病的存在或严重神经退行性疾病的存在。
在一些实施例中，所述步骤S2中，所述确定受试者中神经退行性疾病发生风险、诊断受试者中神经退行性疾病或确定受试者中神经退行疾病的状态的特异性具有至少90％，优选至少95％的准确性。
本发明的第三方面，提供一种试剂盒，包括检测工具和说明书，所述说明书记载了诊断受试者的流程和指标，其特征在于，所述检测工具由用于测定所述神经退行性疾病生物标志物的工具组成，任选地，所述试剂盒含有关于如何在所述确定受试者中神经退行性疾病发生风险、诊断受试者中神经退行性疾病或确定受试者中神经退行疾病的状态的方法中使用所述试剂盒的说明书。
本发明的第四方面，提供一种所述神经退行性疾病生物标志物在筛选治疗或预防神经退行性疾病药物中的应用。
与现有技术相比，本发明的有益效果是本方案所提供的神经退行性疾病生物标志物，能够用于神经退行性疾病的症状辅助判断，具有检测精确度高、方便快捷以及安全无创的特点，对辅助诊断出神经退 行性疾病相关指标具有重要的临床指导意义。
附图说明
图1为乙酰胆碱含量图；
图2为乙酰胆碱含量均值对比图；
图3为多巴胺含量图；
图4为多巴胺含量均值对比图；
图5为己酸含量图；
图6为己酸含量均值对比图；
图7为11Z,14Z,17Z-二十碳三烯酸含量图；
图8为11Z,14Z,17Z-二十碳三烯酸含量均值对比图；
图9为壬二酸含量图；
图10为壬二酸含量均值对比图；
图11为辛二酸含量图；
图12为辛二酸含量均值对比图；
图13为癸二酸含量图；
图14为癸二酸含量均值对比图；
图15为10,13-十九碳二烯酸含量图；
图16为10,13-十九碳二烯酸含量均值对比图；
图17为二十二烷酸含量图；
图18为二十二烷酸含量均值对比图。
具体实施方式
下面将结合具体实施方式对本专利的技术方案作进一步详细地 说明，应该指出，以下详细说明都是示例性的，旨在对本申请提供进一步的说明。除非另有指明，本文使用的所有技术和科学术语具有与本申请所属技术领域的普通技术人员通常理解的相同含义。
本发明试验及仪器来源：AB 5500/6500Q-trap质谱仪购于AB SCIEX公司。Agilent 1290 Infinity LC超高压液相色谱仪购于Agilent公司。低温高速离心机5430R购于Eppendorf公司。色谱柱购于Waters公司，共有两种：ACQUITY UPLC BEH Amide 1.7μm，2.1mm×100mm column；ACQUITY UPLC BEH C18 1.7μm，2.1mm×100mm column。乙腈购于Merck公司，产品编号为1499230-935。乙酸铵购于Sigma公司，产品编号为73594。甲醇购于Fisher公司，产品编号为A456-4。氨水购于Sigma公司，产品编号为221228。甲酸铵购于Sigma公司，产品编号为70221。甲酸购于Sigma公司，产品编号为00940。同位素标准品购于Cambridge Isotope Laboratories公司。
需要说明的是，本发明中所述灵敏度(Sensitivity，也称真阳性率)是指在实际为阳性的样本中将其判断为阳性的比例，即能将实际患病的病例正确地判断为患病的能力。特异度(Specificity，也称真阴性率)是指在实际为阴性的样本中将其判断为阴性的比例，即能正确判断实际未患病的病例的能力。准确度(Accuracy，也称效率)则用真阳性与真阴性总数占受试者总数的百分率表示。
本发明提供一种基于粪便代谢物的高灵敏度、高准确度的神经退行性疾病生物标志物。该组合共含8种粪便代谢标志物，以其质谱峰强度值作为检测指标，能够用于神经退行性疾病的症状辅助判断。因 其具有检测精确度高、方便快捷以及安全无创的特点，所以对辅助诊断神经退行性疾病具有重要的临床指导意义。
基于上述生物标志物，本发明提供一种确定受试者中神经退行性疾病发生风险、诊断受试者中神经退行性疾病或确定受试者中神经退行疾病的状态的方法，包括：测定来自受试者的生物样品中神经退行性疾病生物标志物的水平；基于神经退行性疾病生物标志物的水平，以高的特异性确定或诊断发生神经退行性疾病的风险、神经退行性疾病的存在或神经退行性疾病的状态。
此外，本发明提供一种试剂盒，包括检测工具和说明书，其中检测工具由用于测定神经退行性疾病生物标志物的工具组成，说明书中记载了含有关于如何在上述方法中使用试剂盒的相关内容。
下文将以阿尔兹海默症为例介绍具体生物标志物的检测流程和结果。
实施例1：样品提取和预处理
将9月龄的小鼠分为两组，一组为阿尔兹海默症雄性模型小鼠粪便组，即Fecal Transgenic(FTG)组，共10只；另一组为WT野生型粪便对照组，即Fecal Wild Type(FWT)组，共9只。
取适量从阿尔兹海默症患病个体和正常健康对照供体中采集的血清样品，加入预冷的甲醇/乙腈/水溶液，其中甲醇、乙腈、水的体积比为2:2:1。之后进行涡旋混合并于低温下超声30min，而后在-20℃静置10min，于14,000×g、4℃的条件下离心20min，取上清液进行真空干燥，得到预处理样品。
实施例2：LC-MS/MS分析
(1)质谱分析样品的制备。
质谱分析时，向实施例1得到的预处理样品中加入100μL乙腈水溶液复溶，其中乙腈和水的体积比为1:1。之后经涡旋混合在14,000×g、4℃的条件下离心15min，并取上清液进样分析。
(2)LC-MS/MS条件。
粪便代谢物的定性定量信息基于靶向代谢组学分析技术，采用超高效液相色谱-三重四级杆质谱联用仪(UHPLC Q-TRAP/MS)进行检测。该技术具有高选择能力和高灵敏度，使用针对性开发的样品制备及色谱分离方法，能够定性和定量分析三百多种常见的肠道菌群代谢产物。
色谱条件。采用Agilent 1290 Infinity LC型超高效液相色谱系统搭配HILIC和C18色谱柱分离样品。HILIC色谱柱柱温35℃，流速0.3mL/min，进样量2μL；流动相A为90％水、2mM甲酸铵和10％乙腈，流动相B为甲醇和0.4％甲酸；洗脱梯度：0-1.0min为85％B相，1.0-3.0min B相从85％线性变化至80％，3.0-4.0min为80％B相，4.0-6.0min B相从80％线性变化至70％，6.0-10.0min B相从70％线性变化至50％，10-12.5min B相维持在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A为水、5mM乙酸铵和0.2％氨水，流动相B为99.5％乙腈和0.5％氨水；洗脱梯度：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％；整个分析过程中样品置于4℃自动进样器中。为避免仪器检测信号波动带来的影响，采用随机顺序进行样本的连续分析。样本队列中插入QC样品，即混合相同体积的所有待检测样本后按照与待测样本相同的前处理方法得到的样本，用于监测和评价系统的稳定性及实验数据的可靠性。
质谱条件。质谱仪为AB SCIEX公司的AB 6500 QTRAP系统。采用电喷雾离子源(ESI)作为离子化方式，参数设置如下：鞘气温度350℃；干燥气温度350℃；鞘气流速11L/min；干燥气流速10L/min；毛细管电压正离子模式下为4000V，负离子模式下为-3500V；喷嘴电压500V；雾化压力30psi；采用质谱多反应监测(Multiple Reaction Monitoring，MRM)。
数据分析。使用MultiQuant或Analyst软件对MRM原始数据进行峰提取，得到各物质的峰面积和内标峰面积的比值，并根据标准曲线计算含量。
(3)结果分析。
如图1-18所示，对两组小鼠进行组间差异对比分析，可以发现AD组小鼠如下几种代谢物水平与对照组相比有显著差异，说明了该部分代谢物对于阿尔兹海默症模型的区分有重要作用：乙酰胆碱(Acetylcholine)、多巴胺(Dopamine)、己酸(Hexanoic acid)、壬二酸(Azelaic acid)、辛二酸(Suberic acid)、癸二酸(Sebacic acid)、11Z,14Z,17Z-二十碳三烯酸(11Z,14Z,17Z-Eicosatrienoic Acid)、10,13- 十九碳二烯酸(10,13-Nonadecadienoic acid)、二十二烷酸(Docosanoicacid)。
具体来讲，图1-8分别为乙酰胆碱、多巴胺、己酸和11Z,14Z,17Z-二十碳三烯酸的含量情况，患阿尔兹海默症小鼠的此部分生物标志物含量平均值相对于未患疾病小鼠有增多趋势，提示受试者存在患阿尔兹海默症的风险。此外，如图9-18所示，患阿尔兹海默症小鼠粪便中壬二酸、辛二酸、癸二酸、二十二烷酸和10,13-十九碳二烯酸在各自衡量维度下均呈现减少的趋势。同时，这5种生物标志物整体有同步协调的变化，在实际应用中，可有选择性地择一或多进行检测，以节省成本和时间。
进一步地，对以上代谢物进行分类分析，发现进一步通过分类分析发现乙酰胆碱和多巴胺属于神经递质(Neurotransmitter)，己酸、壬二酸、辛二酸、癸二酸、11Z,14Z,17Z二十碳三烯酸、二十二烷酸和10,13-十九碳二烯酸则属于脂肪酸(Fatty acids)。这些结果提示AD患者体内存在神经递质和脂肪酸等代谢通路的异常，而粪便代谢物水平变化可能反映阿尔兹海默症患者脑中相关代谢通路的异常，对临床早期诊断具有重要意义。
神经递质中，乙酰胆碱有增强记忆力的作用，阿尔兹海默症患者体内乙酰胆碱酯酶的活性过高会加速乙酰胆碱的降解，从而使人出现认知和记忆障碍。多巴胺具有调节运动和情绪反应以及记忆力等多种功能，其异常分泌会导致帕金森病，与此同时，阿尔兹海默症患者脑内缺乏多巴胺会出现震颤、僵直、运动迟缓等帕金森氏症的症状。机 体外周神经递质的代谢异常及其对中枢神经系统的影响尚不清楚。
此外，血脑屏障被破坏后，游离脂肪酸和富含脂质的脂蛋白从外部侵入大脑可能会导致阿尔兹海默症。一种称为“脂质入侵模型”(Lipid Invasion Model)的新解释认为，由于血脑屏障受损而进入大脑的脂质是影响全世界数千万人患退行性疾病的决定性原因。该模型解释了白蛋白结合的游离脂肪酸是如何通过被破坏的血脑屏障，侵入并诱导生物能量变化和氧化应激，刺激小胶质细胞驱动的神经炎症，并导致顺行性健忘症。不过，这些脂肪酸的外周来源尚不明确。
此外，帕金森患者体内也存在多巴胺、乙酰胆碱等神经递质分泌异常。同时，血浆二十碳三烯酸等脂肪酸的变化与帕金森病密切相关，提示粪便中这些神经递质和脂肪酸的动态变化可作为早期诊断和追踪帕金森病进展的可见生物标志物。
本发明以8种粪便代谢标志物的质谱峰强度值作为检测靶点或评估指标，能够用于神经退行性疾病的症状辅助判断，具有检测精确度高、方便快捷以及安全无创的特点，对辅助诊断出神经退行性疾病相关指标具有重要的临床指导意义。
以上所述仅是本发明的一些实施方式。对于本领域技术人员来说，在不脱离本发明创造构思的前提下，还可以做出若干变形和改进，这些都属于本发明的保护范围。

Claims (10)

  1. 一种神经退行性疾病生物标志物，其特征在于，所述生物标志物包括：乙酰胆碱、多巴胺、己酸、壬二酸、辛二酸、癸二酸、11Z,14Z,17Z-二十碳三烯酸、10,13-十九碳二烯酸、二十二烷酸中的任意一种或多种。
  2. 根据权利要求1所述的神经退行性疾病生物标志物，其特征在于，所述生物标志物为壬二酸、辛二酸、癸二酸、10,13-十九碳二烯酸、二十二烷酸中的任意一种和乙酰胆碱、多巴胺、己酸、11Z,14Z,17Z-二十碳三烯酸的组合，优选地，权利要求1中限定的全部生物标志物。
  3. 一种确定受试者中神经退行性疾病发生风险、诊断受试者中神经退行性疾病或确定受试者中神经退行疾病的状态的方法，所述方法包括：
    S1、测定来自受试者的生物样品中所述神经退行性疾病生物标志物的水平；和
    S2、基于所述神经退行性疾病生物标志物的水平，以高的特异性确定或诊断发生神经退行性疾病的风险、神经退行性疾病的存在或神经退行性疾病的状态，
    其中所述神经退行性疾病生物标志物包括乙酰胆碱、多巴胺、己酸、壬二酸、辛二酸、癸二酸、11Z,14Z,17Z-二十碳三烯酸、10,13-十九碳二烯酸、二十二烷酸中的任意一种或多种，
    并且其中乙酰胆碱、多巴胺、己酸和/或11Z,14Z,17Z-二十碳三烯酸的增多，和/或壬二酸、辛二酸、癸二酸、10,13-十九碳二烯酸和/或二十二烷酸的减少指示发生神经退行性疾病的风险、神经退行性疾病的存在或严重神经退行性疾病的存在。
  4. 根据权利要求3所述的方法，其特征在于，所述步骤S1前还包括：提供来自受试者的生物样品。
  5. 根据权利要求3或4所述的方法，其特征在于，所述步骤S1中，所 述神经退行性疾病生物标志物的水平通过质谱峰高度值和/或质谱峰面积值确定。
  6. 根据权利要求3-5中任一项所述的方法，其特征在于，所述步骤S1中，所述生物样品选自粪便。
  7. 根据权利要求3-6中任一项所述的方法，其特征在于，所述步骤S2包括将所述生物样品中所述生物标志物的水平与所述生物标志物的参比水平进行比较，其中所述参比水平是：
    从未患有神经退行性疾病的群体获得的平均水平；和/或
    来自包括神经退行性疾病的患者的个体的组的平均或中值水平，并且
    其中分别在预定的相对或绝对界限水平之上或之下，所述生物标志物的水平指示发生神经退行性疾病的风险、神经退行性疾病的存在或严重神经退行性疾病的存在。
  8. 根据权利要求3-7中任一项所述的方法，其特征在于，所述步骤S2中，所述确定受试者中神经退行性疾病发生风险、诊断受试者中神经退行性疾病或确定受试者中神经退行疾病的状态的特异性具有至少90％，优选至少95％的准确性。
  9. 一种试剂盒，包括检测工具和说明书，所述说明书记载了诊断受试者的流程和指标，其特征在于，所述检测工具由用于测定乙酰胆碱、多巴胺、己酸、壬二酸、辛二酸、癸二酸、11Z,14Z,17Z-二十碳三烯酸、10,13-十九碳二烯酸、二十二烷酸中的任意一种或多种的工具组成，任选地，所述试剂盒含有关于如何在权利要求3-8中任一项所述确定受试者中神经退行性疾病发生风险、诊断受试者中神经退行性疾病或确定受试者中神经退行疾病的状态的方法中使用所述试剂盒的说明书。
  10. 权利要求1或2所述的神经退行性疾病生物标志物在筛选治疗或预防神经退行性疾病药物中的应用。
PCT/CN2022/134517 2022-11-25 2022-11-25 基于粪便代谢物的神经退行性疾病标志物及其应用 WO2024108603A1 (zh)

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WO2007050318A2 (en) * 2005-10-24 2007-05-03 Duke University Lipidomics approaches for central nervous system disorders
CN101663031A (zh) * 2007-02-20 2010-03-03 马泰克生物科学公司 来自长链多不饱和脂肪酸的氧脂素及其制备方法和使用方法
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