WO2023016416A1 - 用于nmosd预测或复发监测的生物标志物及其应用 - Google Patents

用于nmosd预测或复发监测的生物标志物及其应用 Download PDF

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WO2023016416A1
WO2023016416A1 PCT/CN2022/110898 CN2022110898W WO2023016416A1 WO 2023016416 A1 WO2023016416 A1 WO 2023016416A1 CN 2022110898 W CN2022110898 W CN 2022110898W WO 2023016416 A1 WO2023016416 A1 WO 2023016416A1
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cfhl3
fga
cxcl10
cxcl12
prg4
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French (fr)
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施福东
金薇娜
李昕頔
田德财
魏常娟
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首都医科大学附属北京天坛医院
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Publication of WO2023016416A1 publication Critical patent/WO2023016416A1/zh

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    • 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
    • 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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/28—Neurological disorders
    • G01N2800/285—Demyelinating diseases; Multipel sclerosis

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  • the invention relates to a biomarker for predicting prognosis and recurrence of NMOSD, belonging to the technical field of biomedicine, in particular to a biomarker for NMOSD prediction or recurrence monitoring and application thereof.
  • NMOSD Neuromyelitis optica spectrum disease
  • MS multiple sclerosis
  • the mechanism is that the specific antibody produced by sensitized B lymphocytes binds to complement, deposits and destroys AQP4 on the surface of astrocytes, and at the same time, innate immune cells such as macrophages and eosinophils exude chemotaxis and secrete inflammatory factors. This in turn leads to demyelination, axonal and brain tissue necrosis.
  • innate immune cells such as macrophages and eosinophils exude chemotaxis and secrete inflammatory factors.
  • the main clinical manifestations are optic neuritis and acute transverse myelitis, which may be a single attack or multiple attacks, and the interval may be weeks, months or even years.
  • omics data analysis is usually used to explain the association between certain characteristic biochemical indicators and certain diseases, but it cannot explain the complex causal relationship. Advances in technology have given rise to the "omics era”, which allows us to collect and integrate data and information at different molecular levels.
  • the integration of these multi-omic data means that thousands of proteins (proteomics), genes (genomics), RNA (transcriptomics) and metabolites (metabolomics) can be studied simultaneously.
  • AI will provide new insights into complex biological systems and reveal networks of interactions between all molecular levels. This approach combines experimental data at multiple molecular levels with computational models and processes the system as a whole to facilitate data identification for diagnostic, prognostic, or therapeutic value.
  • Biomarkers can indicate the pathophysiological process of NMOSD, have predictive value for the risk of NMOSD, and provide a basis for clinical diagnosis and treatment. However, there is no recognized biomarker with high predictive value for the onset and disease progression of NMOSD so far, which cannot meet the clinical needs. Therefore, finding biomarkers that can quickly and accurately predict the occurrence, development and prognosis of diseases has an important clinical application prospect. At the same time, the integration of data information and clinical information obtained through omics technology will help to better understand the pathological process of NMOSD, find new intervention targets for NMOSD, and improve the clinical management of NMOSD patients.
  • this biomarker contributes to a better understanding of the pathophysiology of NMOSD, provides new opportunities for diagnosis and prognosis, and further Improving clinical services for patients with NMOSD.
  • the present invention discloses the application of a reagent for determining the level of biomarkers in biological samples in the preparation of neuromyelitis optica spectrum disease prediction or recurrence monitoring kits, the biomarkers are APOE, SRGN DBI , any one or two or more of HSPB1, THBS1, MAPRE2, FLNA, RAB11A, SRI, IGLL1, TLN1, CD59, FGA, CXCL10, CXCL12, PDGFA, CCL5.
  • the biomarker is any one or two or more of APOE, SRGN, CD59, HABP2, PRG4, FGA, S100A8, LTF, CXCL10, CXCL12, CFHR3.
  • the biomarker is any two or three of APOE, SRGN, CD59, HABP2, PRG4, FGA, S100A8, LTF, CXCL10, CXCL12, and CFHR3.
  • the biomarkers are APOE/FGA, APOE/CXCL10, APOE/CXCL12, APOE/S100A8, APOE/CFHL3, APOE/CD59, SRGN/PRG4, SRGN/HABP2, SRGN/FGA, SRGN/CXCL10, SRGN /CXCL12, SRGN/S100A8, SRGN/CFHL3, SRGN/LTF, PRG4/HABP2, PRG4/FGA, PRG4/CXCL10, PRG4/CXCL12, PRG4/S100A8, PRG4/CFHL3, PRG4/LTF, HABP2/FGA, HABP2/CXCL10 , HABP2/CXCL12, HABP2/S100A8, HABP2/CFHL3, HABP2/LTF, FGA/CXCL10, FGA/CXCL12, FGA/S100A8, FGA/CFHL3, FGA/LTF, FGA/
  • the biomarkers are APOE/CXCL10, APOE/S100A8, SRGN/CFHL3, PRG4/CFHL3, HABP2/CFHL3, FGA/CXCL10, FGA/CXCL12, FGA/S100A8, FGA/CFHL3, FGA/CD59, CXCL10 /CXCL12, CXCL10/S100A8, CXCL10/CFHL3, CXCL12/S100A8, CXCL12/LTF, S100A8/CFHL3, CFHL3/LTF, CFHL3/CD59, S100A8/CFHL3/CXCL10, S100A8/CFHL3/CXCL12, PRG1/SCL0HL3 Any one of /CFHL3/FGA.
  • the kit includes detection reagents for determining the levels of each biomarker in the subject.
  • the detection agent quantitatively determines the level of biomarkers in the biological sample by proteomics technology, including in DIA mode, and the specific steps are as follows:
  • the spectral library collects non-redundant high-quality peptide information of all detectable biological samples in the sample as a peptide identification template for subsequent data analysis; the high-quality peptide information here includes descriptions of peptide spectral peak characteristics. Fragment ion intensities and retention times.
  • DIA mode use high-resolution mass spectrometry to simultaneously collect the ion characteristics of each peptide in terms of fragment mass and retention time; compared with the traditional method of extracting a single ion for fragmentation analysis, DIA mode
  • the lower mass spectrometer was set as a wide precursor ion window cycle acquisition and simultaneous fragmentation of multiple peptide ions in the analysis mode. The complete collection of all detectable protein peak information in the sample is realized, so that a large number of samples can be analyzed with high repeatability.
  • Spectronaut software is used to deconvolute the spectrum collected in step 2), and realize the effective analysis of the quantitative determination of each protein in the biological sample to be tested.
  • the spectrum library is constructed using the data collected by DDA detection on the biological samples of interest.
  • the biological sample is exosomes in whole blood, serum or plasma, preferably exosomal proteins derived from peripheral plasma or astrocytes.
  • kit also includes an extractant for extracting exosomal proteins in biological samples.
  • the kit also includes a pretreatment agent for processing biological samples.
  • biomarker level is the protein or mRNA level of the biomarker.
  • the kit is used to monitor the risk of neuromyelitis optica spectrum disease in the subject within 5 years of prognosis. Preferably within 1 year.
  • the subject is a mammal, preferably a human.
  • the second object of the present invention is to provide a neuromyelitis optica spectrum disease prediction or recurrence monitoring kit, which includes a detection agent for determining the level of biomarkers in the subject, and is used to extract exosomal proteins from biological samples Reagents, pretreatment agents and buffers for processing biological samples.
  • the third object of the present invention is to provide a neuromyelitis optica spectrum disease prediction or recurrence monitoring system, which is used to detect the level of each biomarker in the biological sample provided by the subject, and compare it with the normal or reference expression level, And the comparison result is fed back to the system operator.
  • the present invention provides biomarkers and applications thereof for NMOSD prediction or recurrence monitoring.
  • Reagents or kits for neuromyelitis optica spectrum disease prediction or recurrence monitoring can be prepared by virtue of these biomarkers, so as to predict subjects The risk of developing neuromyelitis optica spectrum disease, or monitoring the probability of recurrence of neuromyelitis optica spectrum disease within 5 years in patients or subjects.
  • the biomarker set provided by the present invention helps to better understand the pathophysiology of NMOSD, and will provide new opportunities for diagnosis and prognosis, thereby improving clinical services for NMOSD patients.
  • Fig. 1 is the test diagram of using NTA particles to trace exosomes in the embodiment
  • Fig. 2 is the TEM of exosome in the embodiment
  • Figure 3 is a schematic diagram of the results of using western blot to detect exosome-specific proteins in the embodiment
  • Fig. 4 is the differential expression result of 41 kinds of biomarkers designed by the present invention in the exosome proteomic identification of NMOSD patient and healthy person's peripheral plasma and astrocyte source;
  • Fig. 5 is the differentially expressed protein screened by enzyme-linked immunosorbent assay in the embodiment
  • Fig. 6 is the correlation figure of protein concentration and NMOSD acute stage clinical handicap degree in the embodiment
  • Fig. 7 is the ROC curve of each combined biomarker group
  • Figure 8 shows the ROC curves for each combined biomarker panel.
  • NOSD neuronelitis optica spectrum disorder
  • biomarkers refer to biochemical indicators that can mark changes or possible changes in system, organ, tissue, cell and subcellular structure or function. It can be used for disease diagnosis, judgment of disease stage, or evaluation of the safety and effectiveness of new drugs or new treatments in the target population.
  • diagnosis and like terms refer to the identification of a particular disease.
  • prediction and related terms refer to a description of the likely outcome of a particular condition (eg, neuromyelitis optica spectrum disorder).
  • monitoring refers to a subject who may be at risk for neuromyelitis optica spectrum disorder.
  • the subject may be a patient who has not been diagnosed with a neuromyelitis optica spectrum disorder, but may be at risk of developing a neuromyelitis optica spectrum disorder due to various clinical or medical evaluations.
  • sample biological sample
  • test sample test sample
  • specimen sample from a subject
  • patient sample may be blood, tissue, Samples of urine, serum, plasma, amniotic fluid, cerebrospinal fluid, placental cells or tissue, endothelial cells, white blood cells, or monocytes.
  • Some of the methods discussed herein or other methods known in the art can be used to obtain samples directly from the patient, or can (e.g., by filtration, distillation, extraction, concentration, centrifugation, inactivation of interfering components and addition of reagents, etc. ) to preprocess the sample to change the characteristics of the sample.
  • CFHR3 and CFHL3 refer to the same protein.
  • the age of onset is between 18 and 80;
  • the included clinical information includes: general basic information and clinical characteristics of patients, Kurtzke's Expanded Disability Status Scale (EDSS) score, blood and cerebrospinal fluid related indicators, and acute phase treatment plan.
  • EDSS Expanded Disability Status Scale
  • the follow-up data included: EDSS score at the onset, 3 months, 6 months, and 1 year after the onset, recurrence times, blood routine and biochemical indicators, and imaging data, as well as treatment plan in remission period.
  • Collect plasma collect peripheral blood in purple tubes containing anticoagulant EDTA or heparin, and centrifuge within 30 minutes after sample collection, at 3000 rpm for 10 minutes, at 2-8°C. The upper plasma layer was collected and stored in batches at -80°C. Avoid repeated freezing and thawing of samples. Note: Samples should be centrifuged sufficiently to avoid hemolysis or the presence of particles.
  • PIC protease inhibitor
  • Extract exosome protein the specific steps are as follows:
  • proteomics technology to quantitatively measure protein expression levels in biological samples and screen out differentially expressed proteins
  • the sample was sent to the trap column for concentration and desalination, and then connected in series with a self-made C18 column (C18 column diameter 150 ⁇ m, column diameter 1.8 ⁇ m, column length about 35 cm), and a high-efficiency gradient (CAN, 98% , FA, 0.1%) separated at a speed of 500nL/min; within 5-120 minutes, the B-type fluid increased linearly from 5% to 25%; within 120-160 minutes, the flow rate of B-type fluid increased from 25% to 35%; in 160-170 minutes, the flow rate of type B fluid increased from 35% to 80%; in 170-175 minutes, the flow rate of type B fluid was 80%; in 175-180 minutes, the flow rate of type B fluid was 5 %.
  • the nanoliter liquid separation terminal is directly connected to the mass spectrometer and measures according to the following parameters:
  • DDA library construction detection The peptide fragments extracted by liquid phase method were ionized with nanoESI source, and then sent to tandem mass spectrometer Q-Exactive HF X (Thermo Fisher Scientific, San Jose, CA) for DDA detection.
  • Main parameter settings set the voltage of the ion source at 1.9kV; scan the mass spectrometer in the mass-to-charge ratio range of 350-1500 for the primary mass spectrometer scan; set the resolution to 120,000, the maximum ion implantation time (MIT ) is 100 milliseconds; the mass spectrum fragmentation method of the secondary mass spectrometer is HCD, and the fragmentation energy is NCE28; the resolution is 30,000, the maximum injection time is 100 milliseconds, and a power exclusion of 30 seconds is set.
  • the initial m/z value of the secondary mass spectrum is 100; in the second fragmentation, the selection of the parent body is: from 2+ to 6+ , the strongest 20 of which the peak intensity exceeds 5E4.
  • AGC is set as: the strongest parent of 3E64 in the first stage.
  • AGC is set to: 1E6, 2E5.
  • DIA mass spectrometry detection The peptide fragments separated by the liquid phase method were ionized with a nanoESI source, and then sent to a tandem mass spectrometer Q-Exactive HF X (Thermo Fisher Scientific, San Jose, CA) for DIA (Data Independent Acquisition).
  • Main parameter setting set the voltage of the ion source at 1.9kV; scan the mass spectrum at 1-400-1,250m/z; set the resolution at 120,000; the maximum ion injection time is 50 milliseconds; /z is divided into 45 windows for continuous windowing and acquisition.
  • the crushing method is HCD, the maximum ion implantation time (MIT) is selected as the automatic mode, the debris is detected in Orbitrap, the resolution is set to 30,000, the crushing energy is 22.5, 2527.5, and the AGC is 1E6.
  • Figure 4 also intuitively reflects the differential expression results of 41 biomarkers in the proteomic identification of exosomes derived from peripheral plasma and astrocytes of NMOSD patients and healthy people.
  • the present invention also discloses a kit for detecting the above 41 biomarkers, which includes a detection agent for determining the level of biomarkers in a subject, an extraction agent for extracting exosome proteins in biological samples, Pretreatment reagents and buffers for processing biological samples.
  • the detection agent can quantitatively determine the level of biomarkers in the biological sample by proteomics technology, and the extraction agent, pretreatment agent and buffer solution are all described in Examples 1 and 2.
  • the present invention also discloses a neuromyelitis optica spectrum disease prediction or recurrence monitoring system, the system includes the above kit, and the system is used to detect the level of each biomarker in the biological sample provided by the subject, and the normal or Compare with reference to the expression level, and feed back the comparison result to the system operator.
  • the biomarkers designed in the present invention for NMOSD prediction or recurrence monitoring can be used to prepare reagents or kits for neuromyelitis optica spectrum disease prediction or recurrence monitoring, so as to predict subjects suffering from neuromyelitis optica spectrum disease risk of neuromyelitis optica spectrum disorder in patients or subjects, or to monitor patients or subjects for recurrence of neuromyelitis optica spectrum disorder.
  • Contributing to a better understanding of the pathophysiology of NMOSD will provide new opportunities for diagnosis and prognosis, leading to improved clinical services for NMOSD patients.

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Abstract

一种用于NMOSD预测或复发监测的生物标志物及其应用，生物标志物为APOE，SRGN，NACA，HABP2，BLVRB，PRG4，S100A8，S100A9，TRAP5，IGFBP5，ST13，FST，LTF，CFHR3，CALD1，PRDX1，PRDX4，PRDX5，GRB2，PLXNB2，TIMP1，TOLLIP，DUSP3，MTPN，ARHGDIB，Wdr44，DBI，HSPB1，THBS1，MAPRE2，FLNA，RAB11A，SRI，IGLL1，TLN1，CD59，FGA，CXCL10，CXCL12，PDGFA，CCL5中的任意一种或两种或多种。生物标志物可制备用于视神经脊髓炎谱系疾病预测或复发监测的试剂或试剂盒，以预测受试者患视神经脊髓炎谱系疾病的风险，或监测患者或受试者视神经脊髓炎谱系疾病的复发几率。

Description

用于NMOSD预测或复发监测的生物标志物及其应用
本申请要求以下中国专利申请的优先权：
申请日：2021年8月10号
申请号：202110911380.4
发明名称：用于NMOSD预测或复发监测的生物标志物及其应用
技术领域
本发明涉及一种用于预测NMOSD预后和复发的生物标志物，属于生物医学技术领域，具体地涉及一种用于NMOSD预测或复发监测的生物标志物及其应用。
背景技术
视神经脊髓炎谱系疾病(NMOSD)是一种中枢神经系统免疫性脱髓鞘疾病，主要为视神经、脊髓同时或相继受累的急性或亚急性脱髓鞘病变。长期以来，对NMOSD是一种独立疾病或为多发性硬化(multiple sclerosis，MS)的一种变异型存有争议。自Lennon等2004年在视神经脊髓炎疾病(neuromyelitis optica，NMO)患者血清中发现水通道蛋白4(aquaporin-4，AQP4)抗体以来，NMOSD作为与MS不同的独立疾病，一种以体液免疫为主的中枢神经系统自身免疫性疾病已得到普遍的公认。发生机制是致敏B淋巴细胞产生的特异性抗体结合补体，沉积并破坏星形胶质细胞表面AQP4，同时巨噬细胞、嗜酸粒细胞等固有免疫细胞趋化渗出，分泌炎性因子，继而导致髓鞘脱失、轴索和脑组织坏死。临床主要表现为视神经炎与急性横贯性脊髓炎，可能单次发作或多次发作，其间隔期可能是几周、几月甚至几年。虽然有根据小规模临床研究或专家共识推荐的治疗方案(包括糖皮质激素、丙种球蛋白、硫唑嘌呤以及利妥昔单抗等)，但是由于缺乏针对NMOSD的大样本随机双盲对照临床试验，迄今尚无NMOSD最佳的治疗方案。
由于临床表现的异质性、复发后神经系统残疾的严重程度以及治疗反应的差异性，迫切需要可靠、敏感的NMOSD发病、复发和进展生物标志物。检测血清中的AQP4抗体(AQP4-IgG)可支持血清阳性NMOSD的诊断。然而，尚不清楚AQP4-IgG水平是否与疾病活动、严重程度、对治疗的反应或长期结果相关。此外，血清阴性NMOSD患者的生物标志物尚未确定和验证。因此，建立和验证可用于预测NMOSD预后和复发的生物标志物具有广阔的前景。
单一组学数据分析通常用来解释某种特征性的生化指标与某些疾病之间的关联，但无法说明其中复杂的因果关系。技术的进步催生了“组学时代”，这使得我们能够在不同的分子水平上收集和整合数据和信息。这些多组学数据的整合意味着可以同时研究成千上万的蛋白质(蛋白质组学)、基因(基因组学)、RNA(转录组学)和代谢物(代谢组学)。人工智能将提供对复杂生物系统的新见解，并揭示所有分子水平之间的相互作用网络。这种方法将多个分子水平的实验数据与计算模型相结合，并将系统作为一个整体进行处理，以利于进行诊断、预后或治疗价值的数据识别。
生物标记物可提示NMOSD病理生理过程，对NMOSD的发生风险具有预测价值，为临床诊断及治疗提供依据。但是至今尚无公认的对NMOSD发病及疾病进展预测价值高的生物标记物，无法满足临床需求。因此，寻找可快速准确的预测疾病发生、发展及预后的生物学标记物具有重要的临床应用前景。与此同时，通过组学技术获得的数据信息与临床信息整合将有助于更好地了解NMOSD病理过程，寻找NMOSD新的干预靶点，从而改善NMOSD患者的临床管理。
发明内容
为解决上述技术问题，一种用于NMOSD预测或复发监测的生物标志物及其应用，该生物标志物有助于更好地了解NMOSD的病理生理，为诊断和预后提供新的机会，并进一步改善NMOSD患者的临床服务。
为实现上述技术目的，本发明公开了一种用于确定生物样品中生物标志物水平的试剂在制备视神经脊髓炎谱系疾病预测或复发监测试剂盒中的应用，所述生物标志物为APOE，SRGN，NACA，HABP2，BLVRB，PRG4，S100A8，S100A9，TRAP5，IGFBP5，ST13，FST，LTF，CFHR3，CALD1，PRDX1，PRDX4，PRDX5，GRB2，PLXNB2，TIMP1，TOLLIP，DUSP3，MTPN，ARHGDIB，Wdr44，DBI，HSPB1，THBS1，MAPRE2，FLNA，RAB11A，SRI，IGLL1，TLN1，CD59，FGA，CXCL10，CXCL12，PDGFA，CCL5中的任意一种或两种或多种。
进一步地，所述生物标志物为APOE，SRGN，CD59，HABP2，PRG4，FGA，S100A8，LTF，CXCL10、CXCL12，CFHR3中的任意一种或两种或多种。
进一步地，所述生物标志物为APOE，SRGN，CD59，HABP2，PRG4，FGA，S100A8，LTF，CXCL10、CXCL12，CFHR3中的任意两种或三种。
进一步地，所述生物标志物为APOE/FGA，APOE/CXCL10，APOE/CXCL12，APOE/S100A8，APOE/CFHL3，APOE/CD59，SRGN/PRG4，SRGN/HABP2，SRGN/FGA，SRGN/CXCL10，SRGN/CXCL12，SRGN/S100A8，SRGN/CFHL3，SRGN/LTF，PRG4/HABP2，PRG4/FGA，PRG4/CXCL10，PRG4/CXCL12，PRG4/S100A8，PRG4/CFHL3，PRG4/LTF，HABP2/FGA，HABP2/CXCL10，HABP2/CXCL12，HABP2/S100A8，HABP2/CFHL3，HABP2/LTF，FGA/CXCL10，FGA/CXCL12，FGA/S100A8，FGA/CFHL3，FGA/LTF，FGA/CD59，CXCL10/CXCL12，CXCL10/S100A8，CXCL10/CFHL3，CXCL10/LTF，CXCL12/S100A8，CXCL12/LTF，S100A8/CFHL3，S100A8/LTF，CFHL3/LTF，CFHL3/CD59，SRGN/FGA/HABP2，S100A8/CFHL3/CXCL10，S100A8/CFHL3/CXCL12，PRG4/CFHL3/S100A8，CXCL10/CFHL3/FGA 中的任意一种或两种或多种的组合。
进一步地，所述生物标志物为APOE/CXCL10，APOE/S100A8，SRGN/CFHL3，PRG4/CFHL3，HABP2/CFHL3，FGA/CXCL10，FGA/CXCL12，FGA/S100A8，FGA/CFHL3，FGA/CD59，CXCL10/CXCL12，CXCL10/S100A8，CXCL10/CFHL3，CXCL12/S100A8，CXCL12/LTF，S100A8/CFHL3，CFHL3/LTF，CFHL3/CD59，S100A8/CFHL3/CXCL10，S100A8/CFHL3/CXCL12，PRG4/CFHL3/S100A8，CXCL10/CFHL3/FGA中的任意一种。
进一步地，所述试剂盒包含用于确定受试者体内各生物标志物水平的检测剂。
进一步地，所述检测剂通过蛋白质组学技术定量测定所述生物样品中生物标志物水平，包括在DIA模式下进行，具体步骤如下：
1)构建谱图库：谱图库收集样本所有可检测生物样品的非冗余的高质量肽段信息作为后续数据分析的肽段鉴定模板；这里的高质量肽段信息包括描述肽段谱峰特性的碎片离子强度和保留时间。
2)DIA模式下获取待测生物样品数据：利用高分辨质谱实现在碎片质量数和保留时间上同时采集各肽段离子特性；与传统的提取单一离子进行碎裂分析的方法相比，DIA模式下质谱被设定为宽母离子窗口循环采集并同时碎裂多种肽段离子的分析方式。实现了将样品中所有可检测的蛋白质谱峰信息完整采集，从而能够高重复性的分析大量样本。
3)数据分析：采用Spectronaut软件对步骤2)收集到的谱图进行去卷积，并实现有效分析待测生物样品中各蛋白质的定量测定。
进一步地，所述谱图库为利用对感兴趣的生物样品进行DDA检测采集的数据构建。
进一步地，所述生物样品为全血、血清或血浆中的外泌体，优选为外周血浆或星形胶质细胞来源的外泌体蛋白。
进一步地，所述试剂盒还包含用于提取生物样品中外泌体蛋白的 提取剂。
进一步地，所述试剂盒还包含用于对生物样品进行处理的预处理剂。
进一步地，所述生物标志物水平为生物标志物的蛋白质或mRNA水平。
进一步地，所述试剂盒用于监测受试者预后5年内发生视神经脊髓炎谱系疾病的风险。优选1年以内。
进一步地，所述受试者为哺乳动物，优选为人。
本发明的目的之二是提供一种视神经脊髓炎谱系疾病预测或复发监测试剂盒，它包括用于确定受试者体内生物标志物水平的检测剂，用于提取生物样品中外泌体蛋白的提取剂、用于对生物样品进行处理的预处理剂及缓冲液。
本发明的目的之三是提供一种视神经脊髓炎谱系疾病预测或复发监测系统，所述系统用来检测受试者提供的生物样品中各生物标志物水平，与正常或参照表达水平进行对比，并将比对结果反馈给系统操作人员。
本发明实施例提供的技术方案与现有技术相比具有如下优点：
1、本发明提供了用于NMOSD预测或复发监测的生物标志物及其应用，凭借这些生物标志物可制备用于视神经脊髓炎谱系疾病预测或复发监测的试剂或试剂盒，以预测受试者患视神经脊髓炎谱系疾病的风险，或监测患者或受试者视神经脊髓炎谱系疾病在5年以内的复发几率。
2、本发明提供的生物标志物组，有助于更好地了解NMOSD的病理生理，将为诊断和预后提供新的机会，从而改善NMOSD患者的临床服务。
附图说明
此处的附图被并入说明书中并构成本说明书的一部分，示出了符合本发明的实施例，并与说明书一起用于解释本发明的原理。
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，对于本领域普通技术人员而言，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1为实施例中采用NTA颗粒示踪外泌体测试图；
图2为实施例中外泌体的TEM；
图3为实施例中采用western blot检测外泌体特异性蛋白结果示意图；
图4为本发明设计的41种生物标志物在NMOSD患者与健康人的外周血浆和星形胶质细胞来源的外泌体蛋白质组学鉴定中的差异表达结果；
图5为实施例中采用酶联免疫吸附测定筛选的差异表达蛋白；
图6为实施例中蛋白浓度与NMOSD急性期临床残障程度相关性附图；
图7为各联合生物标志物组的ROC曲线；
图8为各联合生物标志物组的ROC曲线。
具体实施方式
为了能够更清楚地理解本发明的上述目的、特征和优点，下面将对本发明的方案进行进一步描述。需要说明的是，在不冲突的情况下，本发明的实施例及实施例中的特征可以相互组合。
术语解释
如本文中所使用的，术语“视神经脊髓炎谱系疾病(NMOSD)”是一种中枢神经系统免疫性脱髓鞘疾病，主要表现为视神经、脊髓同时或相继受累的急性或亚急性脱髓鞘病变。
如本文中所使用的，生物标志物，是指可以标记系统、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。其可用于疾病诊断、判断疾病分期或者用来评价新药或新疗法在目标人群中的安全性及有效性等用途。
如本文中所使用的，术语“诊断”和类似术语是指特定疾病的鉴定。
如本文中所使用的，术语“预测”和相关术语是指特定病症(例如视神经脊髓炎谱系疾病)的可能结果的描述。术语“监测”是指可能有患视神经脊髓炎谱系疾病风险的受试者。该受试者可以是未被诊断为有视神经脊髓炎谱系疾病的患者，但由于各种临床或医学评估，可能有患视神经脊髓炎谱系疾病的风险。
如本文中所使用的，“样品”、“生物样品”，“测试样品”、“样本”、“来自受试者的样品”和“患者样品”可以互换使用，并且可以是血液、组织、尿液、血清、血浆、羊水、脑脊液、胎盘细胞或组织、内皮细胞、白细胞或单核细胞的样品。以本文所讨论的某种方式或本领域已知的其它方式可以用于直接从患者获得样品，或者可以(例如通过过滤、蒸馏、提取、浓缩、离心，干扰组分的灭活和添加试剂等)预处理样品以改变样品的特性。
且本发明涉及到的41种蛋白的信息如下表1；
表1 蛋白信息列表
Figure PCTCN2022110898-appb-000001
Figure PCTCN2022110898-appb-000002
表1中CFHR3与CFHL3指代同一蛋白。
在下面的描述中阐述了很多具体细节以便于充分理解本发明，但本发明还可以采用其他不同于在此描述的方式来实施；显然，说明书中的实施例只是本发明的一部分实施例，而不是全部的实施例。
实施例1
实验对象及材料：
1、实验对象
本研究纳入自2018年10月至2019年11月首都医科大学附属北京天坛医院住院患者。
其中，上述NMOSD患者的临床诊断如下：
(1)发病年龄位于18～80之间；
(2)根据2015年Wingerchuk NMOSD诊断标准明确诊断为NMOSD患者；
(3)血AQP4抗体阳性；
(4)本次为急性发作：(a)新出现的或较前明显恶化的视神经炎、横突性脊髓炎或急性脑损伤等神经系统症状(即患者必须在症状发作后7天内就诊)。(b)新发症状必须持续至少48小时以上，并且不能归因于其他临床因素(例如发烧，感染，受伤，对伴随药物的不良反 应)。(c)新发症状必须符合由临床医师确认的感觉、运动或视敏度损害的客观临床体征。(d)发作性症状的单一发作(例如强直性痉挛)不被视为急性发作。(e)临床查体无明显变化，疲劳，情绪变化，膀胱/大便尿急或失禁的感觉症状不足以确定是否存在急性发作。
纳入临床信息包括：患者一般基本信息及临床特点，Kurtzke's Expanded Disability Status Scale(EDSS)评分，血及脑脊液相关指标，急性期治疗方案。
随访资料包括：发病时、发病后3月、6月、1年EDSS评分，复发次数，血常规及生化指标，以及影像学资料，以及缓解期治疗方案。
2、样本收集
NMOSD患者及健康对照组的样本收集和储存过程如下：
(1)收集血浆：外周血收集于含抗凝剂EDTA或肝素的紫色管中，样本采集后30min内离心，3000rpm 10min，2-8℃。收集上层血浆，分批储存于-80℃。样本避免反复冻融。注意：样本应充分离心，避免溶血或颗粒存在。
(2)提取外周血浆中外泌体：用免疫吸附法提取血浆中星形胶质细胞来源的外泌体，具体步骤如下：
(2.1)磁珠包被抗体，具体操作如下：
(2.11)取100ug星形胶质细胞表面谷氨酸转运体抗体(EAAT2-IgG)加入超滤管中，反复洗涤；
(2.12)将8-10uL终浓度为10mM生物素(Biotin)加入IgG中，室温下静置1-2小时；
(2.13)将IgG-Biotin全部加入磁珠中，室温下放入360°摇床摇2小时；
(2.14)将与抗体结合后的磁珠(IgG-Beads)上下翻倒20次，放入磁力架上，静置1min吸出上清液，加1mL PBS，重复该步骤3次后，加入1mL 0.1％PBSA(PBS溶解在BSA中形成的混合液)；
(2.15)以2mg Beads:6uL 10mM Biotin的比例加入适量10mM  Biotin，于室温下Vortex震荡2小时。
(2.2)提取外泌体，具体操作如下：
(2.21)取出样本，加入适量的蛋白酶抑制剂(PIC)；
(2.22)2000G，4℃，15min离心取上清；14000G，4℃，30min离心取上清；
(2.23)取500uL上清液加入100uL IgG-Beads中，4℃下360°旋转20小时；
(2.3)洗脱外泌体，具体操作如下：
(2.31)向结合IgG-Beads后的样本中加入70uL 0.1M甘氨酸(pH＝3.0)，于室温下震荡15分钟；
(2.32)放入磁力架，静置1min，留取上清，向上清中加入5uL 1mM Tris(pH＝7.0)，重复该步骤1次；
(2.4)定量和定性外泌体，具体操作如下：
(2.41)采用NTA颗粒示踪：结果如图1所示，结合图1可知，大多数EAAT2高表达的细胞外囊泡直径位于100到150nm之间，即位于外泌体的标准粒径范围内。
(2.42)采用TEM扫描，具体形貌图如图2，结合图2可知，血浆中星形胶质细胞来源的外泌体呈杯型或呈双凹盘状颗粒，其直径位于100nm左右。
(2.43)采用Western blot检测外泌体特异性蛋白，结果如图3所示，结合图3可知，表达EAAT2的外泌体蛋白裂解液在CD63蛋白标准品位置处均有阳性条带。
(3)提取外泌体蛋白，具体步骤如下：
(3.1)向外泌体样品中加入适量无SDS裂解液、终浓度含EDTA的1×Cocktail，置于冰上5分钟，加入终浓度10mM DTT；
(3.2)冰浴超声2分钟，25,000G，4℃离心15分钟，取上清液；
(3.3)加终浓度为10mM DTT，56℃中水浴1小时；
(3.4)加入终浓度55mM IAM，暗室放置45min；
(3.5)25000G，4℃离心15min取上清，上清液即为蛋白液。
实施例2
采用蛋白质组学技术定量测定生物样品中蛋白表达水平并筛选出差异表达蛋白；
1.质谱分析，具体步骤如下：
1)蛋白酶水解法：取各试样的蛋白质溶液100μg，以蛋白：酶＝40:1的比率，添加2.5μg的Trypsin酶，经37℃水解4小时。采用StrataX柱对最后酶解产物进行脱盐，并在真空中进行脱水。
2)High pH RP法：将全部标本中的等量肽片段分别与A(5％ACN,pH＝9.8)稀释，后进样，采用岛津LC-20AD液相法，采用5μm 4.6×250mm Gemini C18柱液相色谱法进行液相分析。以1mL/min的流量进行梯度洗脱：5％的流动相B(95％ACN,pH＝9.8)10分钟，5％-35％的流动相B 40min，35％-95％的流动相B 1min，流动相B保持3min，5％的流动相B保持10min。用214nm的波长监控洗脱峰，每分钟采集一组份，将其与层析洗脱峰图合并成10份，再进行低温干燥。
3)DDA建库和DIA定量检测(Nano-LC-MS/MS)：用A(2％ACN,0.1％FA)将已提取的多肽片段进行复溶化，20,000G经10min的离心，然后取出上清取样。用UltiMate 3000UHPLC进行了分离。将试样送入trap柱中浓缩和脱盐，然后与自制的C18柱(C18柱直径150μm，柱体直径1.8μm，柱体长度大约35cm)串联，用0至5min的高效梯度(CAN,98％,FA,0.1％)以500nL/min的速度进行分离；在5-120分钟内，B型流体由5％直线上升到25％；在120-160分钟内，B型流体的流量由25％上升到35％；在160-170分钟内，B型流体的流量由35％上升到80％；170-175分钟，B型流体的流量为80％；175-180分钟，B型流体的流量为5％。纳升液体分离终端与质谱分析器直接相连，并根据以下的参数进行测定：
4)DDA建库检测：将经液相法提取的多肽片段用nanoESI源电离，然后送入串联式质量光谱计Q-Exactive HF X(Thermo Fisher Scientific， San Jose，CA)进行DDA检测。主要参数设定：将离子源的电压设定在1.9kV；一级质谱扫描的在350-1500质荷比范围内进行质谱仪的扫描；解析度设定为120,000，最大离子植入时间(MIT)是100毫秒；二级质谱的质量光谱破碎方式是HCD，破碎的能量是NCE28；解析度为30,000，最大注入时间为100毫秒，设置了30秒的动力排除。二级质谱的初始m/z值为100；第二次破碎时，母体的选择是：从2 +至6 +，峰值强度超过5E4的最强的20个。AGC设定为：第一阶段3E64的最强的母体。AGC设定为：1E6,2E5。
5)DIA质谱检测：将经液相法分离的肽片段用nanoESI源电离，然后送入串联质谱计Q-Exactive HF X(Thermo Fisher Scientific，San Jose，CA)进行DIA(Data Independent Acquisition)方式。主要参数设定：将离子源的电压设定在1.9kV；1-400-1,250m/z的质量光谱扫描；解析度设定为120,000；最大的离子注射时刻是50毫秒；对400～1,250m/z分别划分成45个窗进行持续的开窗和获取。破碎方式为HCD，最大离子注入时间(MIT)选用自动模式，碎屑在Orbitrap中被探测，其分辨率设定为30,000，破碎能量为22.5、2527.5、AGC为1E6。
6)数据分析，采用Spectronaut软件对上述步骤收集到的谱图进行分析实现待测生物样品中各蛋白质的定量测定。筛选出的差异表达蛋白如下表2；
表2 差异表达蛋白列表
Figure PCTCN2022110898-appb-000003
由表2可知，外周血浆和星形胶质细胞来源的外泌体蛋白质组学 鉴定出19种上调蛋白和22种下调蛋白，其倍数变化>2，P<0.05。
图4也直观的体现出41种生物标志物在NMOSD患者与健康人的外周血浆和星形胶质细胞来源的外泌体蛋白质组学鉴定中的差异表达结果。
实施例3
采用ELISA技术定量验证差异表达蛋白
本实施例采用具有高特异性、高灵敏度的酶联免疫吸附(ELISA)技术对上述表2中列举的蛋白进行验证，其中各蛋白采用对应的ELISA试剂盒。得到图5，从图5可看出NMOSD患者血浆中APOE，SRGN，CD59，HABP2，PRG4，FGA，S100A8，LTF，CXCL10、CXCL12，CFHR3等各蛋白浓度显著高于健康对照血浆中蛋白浓度。这与上述采用蛋白质组学技术进行体外定量测定的结果保持一致。这直接的说明了可以通过确定生物样品中任意一种或两种或多种蛋白的含量并与正常含量进行对比，进而预测或复发监测疾病的发病几率。
本实施例还进一步地探讨了上述蛋白浓度与NMOSD急性期临床残障程度进行研究，具体是通过检测患者血浆中各生物标志物含量与EDSS评分的相关性，得到图6，由图6可知SRGN，FGA，PRG4，CXCL12，S100A8蛋白浓度的升高促进NMOSD急性期临床残障程度的进展，而CD59蛋白则在NMOSD急性期起到保护作用。
实施例4
各蛋白组合用于预测NMOSD复发性
对APOE，SRGN，CD59，HABP2，PRG4，FGA，S100A8，LTF，CXCL10、CXCL12，CFHR3等各蛋白进行任意方式的组合并进行ROC分析，分析结果如下表3、表4所示：
表3 ROC曲线评价列表(一)
Figure PCTCN2022110898-appb-000004
Figure PCTCN2022110898-appb-000005
表4 ROC曲线评价列表(二)
Figure PCTCN2022110898-appb-000006
Figure PCTCN2022110898-appb-000007
且部分组合的ROC曲线如图7、图8所示。结合上述表3、表4及图7、图8可知，采用本发明设计的联合生物标志物组用于预测NMOSD疾病的准确度比较高，为临床治疗提供依据。
实施例5
本发明还公开了一种用于检测上述41种生物标志物的试剂盒，它包括用于确定受试者体内生物标志物水平的检测剂，用于提取生物样品中外泌体蛋白的提取剂、用于对生物样品进行处理的预处理剂及缓冲液。其中，所述检测剂可以通过蛋白质组学技术定量测定所述生物样品中生物标志物水平，所述提取剂、预处理剂及缓冲液等均在实施例1、2中有描述。
实施例6
本发明还公开了一种视神经脊髓炎谱系疾病预测或复发监测系统，所述系统包括上述试剂盒，且所述系统用来检测受试者提供的生物样品中各生物标志物水平，与正常或参照表达水平进行对比，并将比对结果反馈给系统操作人员。
综上所述，本发明设计的用于NMOSD预测或复发监测的生物标志物可制备用于视神经脊髓炎谱系疾病预测或复发监测的试剂或试剂盒，以预测受试者患视神经脊髓炎谱系疾病的风险，或监测患者或受试者视神经脊髓炎谱系疾病的复发几率。有助于更好地了解NMOSD的病理生理，将为诊断和预后提供新的机会，从而改善NMOSD患者的临床服务。

Claims (12)

  1. 用于确定生物样品中生物标志物水平的试剂在制备视神经脊髓炎谱系疾病预测或复发监测试剂盒中的应用，其特征在于，所述生物标志物为APOE，SRGN，NACA，HABP2，BLVRB，PRG4，S100A8，S100A9，TRAP5，IGFBP5，ST13，FST，LTF，CFHR3，CALD1，PRDX1，PRDX4，PRDX5，GRB2，PLXNB2，TIMP1，TOLLIP，DUSP3，MTPN，ARHGDIB，Wdr44，DBI，HSPB1，THBS1，MAPRE2，FLNA，RAB11A，SRI，IGLL1，TLN1，CD59，FGA，CXCL10，CXCL12，PDGFA，CCL5中的任意一种或两种或多种。
  2. 根据权利要求1所述的应用，其特征在于，所述生物标志物为APOE，SRGN，CD59，HABP2，PRG4，FGA，S100A8，LTF，CXCL10、CXCL12，CFHR3中的任意一种或两种或多种。
  3. 根据权利要求2所述的应用，其特征在于，所述生物标志物为APOE，SRGN，CD59，HABP2，PRG4，FGA，S100A8，LTF，CXCL10、CXCL12，CFHR3中的任意两种或三种。
  4. 根据权利要求3所述的应用，其特征在于，所述生物标志物为APOE/FGA，APOE/CXCL10，APOE/CXCL12，APOE/S100A8，APOE/CFHL3，APOE/CD59，SRGN/PRG4，SRGN/HABP2，SRGN/FGA，SRGN/CXCL10，SRGN/CXCL12，SRGN/S100A8，SRGN/CFHL3，SRGN/LTF，PRG4/HABP2，PRG4/FGA，PRG4/CXCL10，PRG4/CXCL12，PRG4/S100A8，PRG4/CFHL3，PRG4/LTF，HABP2/FGA，HABP2/CXCL10，HABP2/CXCL12，HABP2/S100A8，HABP2/CFHL3，HABP2/LTF，FGA/CXCL10，FGA/CXCL12，FGA/S100A8，FGA/CFHL3，FGA/LTF，FGA/CD59，CXCL10/CXCL12，CXCL10/S100A8，CXCL10/CFHL3，CXCL10/LTF，CXCL12/S100A8，CXCL12/LTF，S100A8/CFHL3，S100A8/LTF，CFHL3/LTF，CFHL3/CD59，SRGN/FGA/HABP2，S100A8/CFHL3/CXCL10， S100A8/CFHL3/CXCL12，PRG4/CFHL3/S100A8，CXCL10/CFHL3/FGA中的任意一种或两种或多种的组合。
  5. 根据权利要求4所述的应用，其特征在于，所述生物标志物为APOE/CXCL10，APOE/S100A8，SRGN/CFHL3，PRG4/CFHL3，HABP2/CFHL3，FGA/CXCL10，FGA/CXCL12，FGA/S100A8，FGA/CFHL3，FGA/CD59，CXCL10/CXCL12，CXCL10/S100A8，CXCL10/CFHL3，CXCL12/S100A8，CXCL12/LTF，S100A8/CFHL3，CFHL3/LTF，CFHL3/CD59，S100A8/CFHL3/CXCL10，S100A8/CFHL3/CXCL12，PRG4/CFHL3/S100A8，CXCL10/CFHL3/FGA中的任意一种。
  6. 根据权利要求1～5中任意一项所述的应用，其特征在于，所述试剂盒包含用于确定受试者体内各生物标志物水平的检测剂，所述检测剂通过蛋白质组学技术定量测定所述生物样品中生物标志物水平，包括在DIA模式下进行，具体步骤如下：
    1)构建谱图库：谱图库收集样本所有可检测生物样品的非冗余的高质量肽段信息作为后续数据分析的肽段鉴定模板；
    2)DIA模式下获取待测生物样品数据：利用高分辨质谱实现在碎片质量数和保留时间上同时采集各肽段离子特性；
    3)数据分析：采用Spectronaut软件对步骤2)收集到的谱图进行去卷积，并实现有效分析待测生物样品中各蛋白质的定量测定。
  7. 根据权利要求6所述的应用，其特征在于，所述谱图库为利用对感兴趣的生物样品进行DDA检测采集的数据构建。
  8. 根据权利要求6所述的应用，其特征在于，所述生物样品为全血、血清或血浆中的外泌体，优选为外周血浆或星形胶质细胞来源的外泌体蛋白。
  9. 根据权利要求8所述的应用，其特征在于，所述试剂盒还包含用于提取生物样品中外泌体蛋白的提取剂，及用于对生物样品进行处理的预处理剂。
  10. 根据权利要求1或2或3或4或5或7或8或9所述的应用，其特征在于，所述试剂盒用于监测受试者预后5年内发生视神经脊髓炎谱系疾病的风险，所述受试者为哺乳动物，优选为人。
  11. 一种视神经脊髓炎谱系疾病预测或复发监测试剂盒，其特征在于，它包括用于确定受试者体内生物标志物水平的检测剂，用于提取生物样品中外泌体蛋白的提取剂、用于对生物样品进行处理的预处理剂及缓冲液。
  12. 一种视神经脊髓炎谱系疾病预测或复发监测系统，其特征在于，所述系统用来检测受试者提供的生物样品中各生物标志物水平，与正常或参照表达水平进行对比，并将比对结果反馈给系统操作人员。
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