WO2022033571A1 - 用于诊断和治疗认知障碍的方法及其应用 - Google Patents

用于诊断和治疗认知障碍的方法及其应用 Download PDF

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WO2022033571A1
WO2022033571A1 PCT/CN2021/112405 CN2021112405W WO2022033571A1 WO 2022033571 A1 WO2022033571 A1 WO 2022033571A1 CN 2021112405 W CN2021112405 W CN 2021112405W WO 2022033571 A1 WO2022033571 A1 WO 2022033571A1
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cognitive impairment
content
detection method
measured
diagnosing
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陈显扬
宋王婷
韩佳睿
薛腾
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宝枫生物科技（北京）有限公司
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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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    • G01N33/6896—Neurological disorders, e.g. Alzheimer's disease
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    • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
    • A61P25/00—Drugs for disorders of the nervous system
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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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    • G01N33/48—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
    • 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
    • G01N30/04—Preparation or injection of sample to be analysed
    • G01N30/06—Preparation
    • G01N2030/062—Preparation extracting sample from raw material
    • G—PHYSICS
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    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2405/00—Assays, e.g. immunoassays or enzyme assays, involving lipids
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2405/00—Assays, e.g. immunoassays or enzyme assays, involving lipids
    • G01N2405/04—Phospholipids, i.e. phosphoglycerides
    • G—PHYSICS
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    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2405/00—Assays, e.g. immunoassays or enzyme assays, involving lipids
    • G01N2405/08—Sphingolipids
    • 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
    • G01N2800/2814—Dementia; Cognitive disorders
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/52—Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis

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  • the invention belongs to the technical field of biological detection, and particularly relates to a method for diagnosing and treating cognitive impairment and its application.
  • AD Alzheimer's disease
  • Senile plaques with extracellular ⁇ -amyloid deposition throughout the brain of AD patients, and neuronal cell death with intracellular hyperphosphorylated tau protein, are the main causes of Alzheimer's disease, a disease that causes progressive memory impairment, Cognitive deficits, changes in personality, etc. Worldwide, more than 5 million people suffer from Alzheimer's disease, and many more suffer from cognitive impairment.
  • MCI Cognitive impairment
  • MCI mild cognitive impairment
  • AD Alzheimer's disease
  • Scale detection requires questions and answers, consumes a lot of medical resources, and is time-consuming and labor-intensive; imaging detection requires expensive equipment such as MRI, PET, etc., which cannot be widely popularized; cerebrospinal fluid sampling is invasive and difficult to sample. Patients and their families Much reluctance to cooperate. At present, there are no high-accuracy and specific peripheral blood biomarkers for MCI and AD.
  • Metabolomics is an emerging omics technology that is playing an increasingly important role in biological research because it can reveal the unique chemical fingerprints of the body's cellular metabolism. Metabolomics, as an unbiased approach to the study of small-molecule metabolites, offers hope for discovering more biomarkers of cognitive impairment. Growing evidence suggests neurological disorders, accompanied by disturbances in bile acids, fatty acids and amino acids. And these results demonstrate that metabolic disturbances may predict the development of cognitive impairment, but it is unclear which substances can be clearly detected as cognitive impairment.
  • the present invention provides biomarkers for diagnosing cognitive impairment.
  • the present invention adopts the following technical scheme as:
  • biomarker for the diagnosis of cognitive impairment is SM(d18:1/24:1(15Z)).
  • biomarker for diagnosing cognitive impairment is SM(d18:1/24:1(15Z)).
  • the biomarkers further include TG (16:0/18:0/18:4(6Z, 9Z, 12Z, 15Z)), PC (P-16:0/22: 4(7Z,10Z,13Z,16Z)) or PC(P-18:0/18:4(6Z,9Z,12Z,15Z)).
  • the content of SM (d18:1/24:1(15Z)) and TG (16:0/18:0/18:4(6Z, 9Z, 12Z, 15Z))
  • BM3 is SM(d18:1/24:1(15Z) ) content
  • BM2 is the content of TG (16:0/18:0/18:4 (6Z, 9Z, 12Z, 15Z))
  • cognitive impairment is predicted according to the TC value: if TC ⁇ 0.5, it is determined as cognitive impairment Obstacle; if TC ⁇ 0.5, it is normal.
  • the content unit of the SM (d18:1/24:1(15Z)) and PC (P-16:0/22:4(7Z, 10Z, 13Z, 16Z)) is In mg/L
  • the present invention also provides a detection method for diagnosing cognitive impairment, comprising detecting the content of SM (d18:1/24:1(15Z)), and TG (16:0/18) in the serum of a subject :0/18:4(6Z,9Z,12Z,15Z)), PC(P-16:0/22:4(7Z,10Z,13Z,16Z)) or PC(P-18:0/18:4 (6Z, 9Z, 12Z, 15Z)), and determine whether there is cognitive impairment by calculating the TC value.
  • the detection method adopts ultra-high performance liquid chromatography-mass spectrometry.
  • the detection conditions of the ultra-high performance liquid chromatography-mass spectrometry are to use a C18 chromatographic column
  • the mobile phase is 10mM ammonium formate-0.1% formic acid-acetonitrile as phase A and 10mM ammonium formate-0.1% formic acid-isopropanol -Acetonitrile is used as phase B
  • the ion source temperature is 120°C
  • the desolvation temperature is 600°C
  • the gas flow is 1000L/h
  • nitrogen is used as the flowing gas
  • the capillary voltage is 2.0kV(+)/cone voltage is 1.5kV(- )
  • the cone voltage is 30V.
  • a method for the treatment of cognitive impairment comprising: (a) using the above-mentioned detection method to diagnose a cognitively impaired patient, (b) treating the diagnosed patient with a cognitive impairment treatment drug, (c) by the above-mentioned method Diagnose recovery conditions.
  • a detection kit for diagnosing cognitive impairment comprising standard substance SM (d18:1/24:1(15Z)), and TG (16:0/18:0/18:4(6Z,9Z, 12Z,15Z)), PC(P-16:0/22:4(7Z,10Z,13Z,16Z)) or PC(P-18:0/18:4(6Z,9Z,12Z,15Z))
  • mobile phase A containing solute 10mM ammonium formate and 0.1% formic acid
  • solvent is acetonitrile:water with a volume ratio of 60:40
  • mobile phase B containing solute 10mM ammonium formate and 0.1% formic acid
  • solvent is A 90:10 volume ratio of isopropanol:acetonitrile.
  • the present invention provides a biomarker for diagnosing cognitive impairment
  • the biomarker is SM(d18:1/24:1(15Z)), combined with TG(16:0/18:0/18:4( 6Z, 9Z, 12Z, 15Z)), PC(P-16:0/22:4(7Z,10Z,13Z,16Z)) or PC(P-18:0/18:4(6Z,9Z,12Z, 15Z)), detect its content, predict cognitive impairment according to TC value, help diagnose whether there is a tendency of cognitive impairment, and can be used for early prevention.
  • Figure 1 is a sample with VIP>1 in positive and negative ion mode
  • Fig. 2 is the score map of (O)PLS-DA in positive and negative ion mode
  • Figure 3 is an S-plot diagram in positive and negative ion mode
  • Fig. 4 is the ROC curve based on logistic regression model (variable is BM3+BM2);
  • Fig. 5 is the ROC curve based on logistic regression model (variable is BM3+BM4)
  • Figure 6 is the ROC curve based on the logistic regression model (variables are BM3+BM5).
  • Model building sample group of 80 people (internal population, that is, the sample group used when building the prediction model)
  • Control population male to female ratio was 1:1, age range: over 45 years old, MMSE scale score > 26, and Moca scale score > 27, MRI showed no abnormality.
  • Patient population 1:1 male to female ratio, age range, over 45 years old, MMSE scale score ⁇ 26, and Moca scale score ⁇ 27, MRI partial abnormality.
  • Model validation sample population of 80 people (external population, that is, the sample used for model validation (non-internal population)), the sampling standard is the same as above.
  • Sample collection Select serum from patients with normal and cognitive impairment after clinical evaluation.
  • the collected serum samples were thawed on ice, 200 ⁇ L of plasma was extracted with 600 ⁇ L of pre-chilled isopropanol, vortexed for 1 min, incubated at room temperature for 10 min, and then the extraction mixture was stored at -20 °C overnight, and after centrifugation at 4000 r for 20 min, the supernatant was Transfer to a new centrifuge tube and dilute to 1:10 with isopropanol/acetonitrile/water (2:1:1 by volume). Samples were stored at -80°C prior to LC-MS analysis. In addition, pooled plasma samples were also prepared by combining 10 ⁇ L of each extraction mixture together.
  • the capillary voltage was 2.0 kV(+) / the cone voltage was 1.5 kV(-) and the cone voltage was 30V.
  • Sodium formate and leucine enkephalin were used as calibration solutions (provided with waters mass spectrometer). Samples were randomly ordered. A quality control (QC) sample was injected every 10 samples and analyzed to investigate the repeatability of the data.
  • FIG. 1 shows the metabolites with VIP>1 in the positive and negative ion mode, and the VIP value is the variable importance projection of the first principal component of OPLSDA.
  • VIP>1 is the commonly used evaluation standard for metabolomics, as one of the criteria for differential metabolite screening.
  • Figure 2 is the score map of (O)PLS-DA in positive and negative ion mode, where C is the score map of (O)PLS-DA in positive ion mode, D is the score map of (O)PLS-DA in negative ion mode, the first principal component and the second principal component in the two groups of cognitive impairment group (DIS) and blank control group (CK) are obtained by dimensionality reduction.
  • the abscissa represents the difference between groups, and the ordinate represents the difference within the group, and the results of the two groups are well separated, indicating that this scheme can be used.
  • Figure 3 shows the S-plot in the positive and negative ion mode
  • E is the S-plot in the positive ion mode
  • F is the S-plot in the negative ion mode.
  • the VIP threshold was increased to 3, and the fold difference between normal and patients was less than 0.8 times, or increased by more than 1.2 times, and the following 10 compounds were finally obtained, as shown in Table 1.
  • variable compounds with YOUDEN AUC value greater than 0.9 were selected for further analysis.
  • the internal population is randomly divided into 7 parts, 1 part is selected as the validation set, and the other is the training set. This is repeated seven times to examine the best variable combination.
  • BM3 is SM(d18:1/24 : 1(15Z))
  • BM2 is the content of TG (16:0/18:0/18:4(6Z,9Z,12Z,15Z))
  • the "model C” variable is the above BM3+BM5, the variable is TG(13:0/17:1(9Z)/20:2(11Z,14Z))+SM(d18:1/24:1(15Z)),
  • the calculation formula is: 48.98-4.266 ⁇ 10-5 ⁇ BM3-1.897 ⁇ 10-4 ⁇ BM5, to calculate the TC value, in the formula, BM3 is the content of SM(d18:1/24:1(15Z)), and BM5 is PC( P-18:0/18:4 (6Z, 9Z, 12Z, 15Z)) content, predict cognitive impairment according to TC value: if TC ⁇ 0.749, it is judged as cognitive impairment; if TC ⁇ 0.749, it is normal .
  • BM1, BM3, BM4 and BM5 showed a downward trend in the cognitive impairment group, and BM2 was the opposite.
  • a detection kit for diagnosing cognitive impairment comprising standard substance S, standard substance SM (d18:1/24:1(15Z)), and TG (16:0/18:0/18:4(6Z) ,9Z,12Z,15Z)), PC(P-16:0/22:4(7Z,10Z,13Z,16Z)) or PC(P-18:0/18:4(6Z,9Z,12Z,15Z) )), mobile phase A liquid: containing 10 mM ammonium formate and 0.1% formic acid as the solute, and the solvent is acetonitrile: water with a volume ratio of 60:40; mobile phase B liquid: containing 10 mM ammonium formate and 0.1% solute % Formic acid in a 90:10 volume ratio of isopropanol:acetonitrile.
  • the preparation method of 10mM ammonium formate-0.1% formic acid-acetonitrile (A, acetonitrile: water is 60:40, v/v) is to weigh 0.63 g of ammonium formate, 10 g of formic acid, and acetonitrile-water solution (acetonitrile: water is 60 g) : 40, v/v) dissolve and make up to 1000mL.
  • the preparation method of 10mM ammonium formate-0.1% formic acid-isopropanol-acetonitrile (B, isopropanol:acetonitrile is 90:10, v/v) is to weigh 0.63 g of ammonium formate, 10 g of formic acid, and use isopropanol-acetonitrile
  • the solution (isopropanol:acetonitrile 90:10, v/v) was dissolved and made up to 1000 mL.
  • the detection of the sample is carried out by using the sample pretreatment and ultra-high performance liquid chromatography-mass spectrometry detection method in Example 1, and the standard standard SM (d18:1/24:1(15Z)), and TG (16:0/18:0/18:4(6Z,9Z,12Z,15Z)), PC(P-16:0/22:4(7Z,10Z,13Z,16Z)) or PC(P-18 :0/18:4 (6Z, 9Z, 12Z, 15Z)) as a reference for detection.

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Abstract

生物标志物SM(d18:1/24:1(15Z))在制备诊断认知障碍试剂或试剂盒中的应用。用于诊断和治疗认知障碍的方法，该诊断方法通过检测生物标志物SM(d18:1/24:1(15Z))以及TG(16:0/18:0/18:4(6Z,9Z,12Z,15Z))，PC(P-16:0/22:4(7Z,10Z,13Z,16Z))或PC(P-18:0/18:4(6Z,9Z,12Z,15Z))的含量，用来判断患者是否存在认知障碍。

Description

用于诊断和治疗认知障碍的方法及其应用 技术领域
本发明属于生物检测技术领域，具体涉及用于诊断和治疗认知障碍的方法及其应用。
背景技术
众所周知，认知障碍是一种进行性神经退行性疾病，认知障碍如果不能及早的被发现、关注和干预，就容易发展成为痴呆，例如阿尔兹海默症(AD)。
AD患者的整个大脑中细胞外β-淀粉样蛋白沉积的老年斑，和细胞内过磷酸化tau蛋白神经细胞死亡，是构成阿尔兹海默症的主要原因，这是一种导致渐进性记忆障碍、认知缺陷、个人性格的变化等的疾病。在全世界有超过500万名以上患有阿尔茨海默病，而处于认知障碍的患者数量更多。
研究表明，认知障碍者已超过千万，但是，目前为止，尽管有许多对发病机制的研究，但是依然没有发现很好的诊断标志物。
认知障碍(mild cognitive impairment，MCI)是正常认知与AD之间的中间状态。研究显示，轻度认知障碍(MCI)在65岁以上人群中患病率为10％至20％，向AD转化的累积概率为33％。因此，对于AD以及AD前期的MCI的早期诊断和及时干预，将把防治AD疾病的关口前移，可望有效延缓AD疾病的进展，降低家庭的负担，对于整个社会和医学发展都有意义。目前，临床上诊断轻度认知障碍(mild cognitive impairment，MCD)和阿尔茨海默病(A1 zheimer disease，AD)的主要方法有量表检测、影像学检测、脑脊液生物标志物检测。量表检测，需要提问和回答，消耗非常大的医学资源，耗时耗力；影像学检测需用到MRI、PET等昂贵设备无法大量普及；脑脊液取样具有创伤性，取样难度大，患者及家属多不愿配合。目前尚无种准确性高，特异性强的MCI和AD外周血生物标志物。
代谢组学是一种新兴的组学技术，在生物学研究中发挥着越来越重要的作用，因为它能够揭示机体细胞代谢的独特化学指纹特征。代谢组学作为一种无偏的小分子代谢物研究方法，为发现更多的认知障碍的生物标志物提供了希望。越来越多的证据表明神经系统疾病，伴随着胆汁酸，脂肪酸和氨基酸的紊乱。并且这些结果证明代谢紊乱可能预示着认知障碍的发生，但具体哪种物质能明确检测出作为辨别是认知障碍，还不清楚。
发明内容
为了能有效预测和诊断认知障碍，本发明提供了用于诊断认知障的生物标记物。
为实现上述目的，本发明采用以下的技术方案为：
用于诊断认知障碍的生物标记物，该生物标记物为SM(d18:1/24:1(15Z))。如上所述的诊断认知障碍的生物标志物在制备检测试剂中的应用。
如上所述的应用，优选地，所述生物标志物还包括TG(16:0/18:0/18:4(6Z,9Z,12Z,15Z))，PC(P-16:0/22:4(7Z,10Z,13Z,16Z))或PC(P-18:0/18:4(6Z,9Z,12Z,15Z))。
如上所述的应用，优选地，所述SM(d18:1/24:1(15Z))与TG(16:0/18:0/18:4(6Z,9Z,12Z,15Z))的含量单位为mg/L时，根据计算公式TC＝79.43-2.199×10 -4×BM3+1.206×10 -4×BM2，计算TC值，公式中BM3为SM(d18:1/24:1(15Z))的含量，BM2为TG(16:0/18:0/18:4(6Z,9Z,12Z,15Z))的含量，根据TC值预测认知障碍：若TC≥0.5，则判定为认知障碍；若TC＜0.5，则为正常。
如上所述的应用，优选地，所述SM(d18:1/24:1(15Z))与PC(P-16:0/22:4(7Z,10Z,13Z,16Z))的含量单位为mg/L时，根据计算公式TC＝604.8–5.028×10 -4×BM3-1.909×10 -3×BM4，计算TC值，公式中BM3为SM(d18:1/24:1(15Z))，BM4为PC(P-16:0/22:4(7Z,10Z,13Z,16Z))，根据TC值预测认知障碍：若TC≥0.421，则判定为认知障碍；若TC＜0.421，则为正常。
如上所述的应用，优选地，所述SM(d18:1/24:1(15Z))与PC(P-18:0/18:4(6Z,9Z,12Z,15Z))的含量单位为mg/L时，根据计算公式：TC＝48.98-4.266×10 - 5×BM3-1.897×10 -4×BM5，计算TC值，公式中BM3为SM(d18:1/24:1(15Z))，BM5为PC(P-18:0/18:4(6Z,9Z,12Z,15Z))，根据TC值预测认知障碍：若TC≥0.749，则判定为认知障碍；若TC＜0.749，则为正常。
本发明还提供了一种用于诊断认知障碍的检测方法，其包括检测受试者血清中的SM(d18:1/24:1(15Z))的含量，和TG(16:0/18:0/18:4(6Z,9Z,12Z,15Z))、PC(P-16:0/22:4(7Z,10Z,13Z,16Z))或PC(P-18:0/18:4(6Z,9Z,12Z,15Z))中任一种的含量，通过计算TC值判断是否存在认知障碍。
如上所述的检测方法，优选地，测得的SM(d18:1/24:1(15Z))的含量记为BM3，测得的TG(16:0/18:0/18:4(6Z,9Z,12Z,15Z))的含量为BM2，计算TC值按公式TC＝79.43-2.199×10 -4×BM3+1.206×10 -4×BM2进行，若TC≥0.5，则判定为认知障碍；若TC＜0.5，则为正常。
如上所述的检测方法，优选地，测得的SM(d18:1/24:1(15Z))的含量记为BM3，测得的PC(P-16:0/22:4(7Z,10Z,13Z,16Z))的含量记为BM4，计算TC值按公式TC＝604.8–5.028×10 -4×BM3-1.909×10 -3×BM4，若TC≥0.421，则判定为认知障碍；若TC＜0.421，则为正常。
如上所述的检测方法，优选地，测得的SM(d18:1/24:1(15Z))的含量记为BM3，测得的PC(P-18:0/18:4(6Z,9Z,12Z,15Z))的含量记为BM5，计算TC值按公式TC＝48.98-4.266×10 -5×BM3-1.897×10 -4×BM5，若TC≥0.749，则判定为认知障碍；若TC＜0.749，则为正常。
如上所述的检测方法，优选地，检测方法采用超高效液相色谱-质谱联用。
进一步，优选地，超高效液相色谱-质谱联用的检测条件为采用C18色谱柱，流动相为10mM甲酸铵-0.1％甲酸-乙腈作为A相和10mM甲酸铵-0.1％甲酸-异丙醇-乙腈作为B相，离子源温度为120℃，去溶温度为600℃，气体流量为1000L/h，以氮气为流动气体；毛细管电压为2.0kV(+)/锥体电压为1.5kV(-)，锥体电压为30V。
一种治疗认知障碍的方法，其包括：(a)采用如上所述的检测方法诊断认知障碍患者，(b)将确诊的患者使用认知障碍治疗药物治疗，(c)通过上述的方法诊断康复状况。
一种用于诊断认知障碍的检测试剂盒，其包括标准品SM(d18:1/24:1(15Z))，和TG(16:0/18:0/18:4(6Z,9Z,12Z,15Z))、PC(P-16:0/22:4(7Z,10Z,13Z,16Z))或PC(P-18:0/18:4(6Z,9Z,12Z,15Z))中的任一种，流动相A：含溶质为10mM甲酸铵和0.1％甲酸，溶剂为体积比为60:40的乙腈：水；流动相B：含溶质为10mM甲酸铵和0.1％甲酸，溶剂为体积比为90:10的异丙醇：乙腈。
本发明的有益效果在于：
本发明提供的一种诊断认知障碍的生物标记物，该该生物标记物为SM(d18:1/24:1(15Z))，结合TG(16:0/18:0/18:4(6Z,9Z,12Z,15Z))、PC(P-16:0/22:4(7Z,10Z,13Z,16Z))或PC(P-18:0/18:4(6Z,9Z,12Z,15Z))，检测其含量，根据TC值预测认知障碍，有助于诊断是否存在认知障碍的倾向，可用于提前预防。
附图说明
图1为正负离子模式下VIP＞1的样本；
图2为正负离子模式下(O)PLS-DA的得分图；
图3为正负离子模式下S-plot图；
图4为基于逻辑回归模型的ROC曲线(变量为BM3+BM2)；
图5为为基于逻辑回归模型的ROC曲线(变量为BM3+BM4)；
图6为为基于逻辑回归模型的ROC曲线(变量为BM3+BM5)。
具体实施方式
以下实施例用于进一步说明本发明，但不应理解为对本发明的限制。在不背离本发明精神和实质的前提下，对本发明所作的修饰或者替换，均属于本发明的范畴。
若未特别指明，实施例中所用的技术手段为本领域技术人员所熟知的常规手段。
实施例1
一、患者人群标准
1.模型建立样本群80人(内部人群，即指建立预测模型时所用样本群体)
对照人群：男女比例为1：1，年龄范围：45岁以上，MMSE量表分数>26分，并且Moca量表分数>27分，MRI核磁检测显示无异常。
患者人群：男女比例为1：1，年龄范围，45岁以上，MMSE量表分数<26分，并且Moca量表分数<27分，MRI核磁检测部分显示异常。
2.模型验证样本群体80人(外部人群，即指验证模型时所用的样本(非内部人群))取样标准同上。
二、实验仪器及试剂
样本采集：选取经临床评价为正常和认知障碍的患者血清进行试验。
实验仪器：1.冷冻离心机：型号D3024R，Scilogex公司，美国；2.漩涡振荡器：型号MX-S，Scilogex公司，美国；3.高分辨质谱仪：ESI-QTOF/MS；型号：Xevo G2-S Q-TOF；厂家：Waters,Manchester,UK；4.超高效液相色谱：UPLC；型号：ACQUITY UPLC I-Class系统；厂家：Waters,Manchester,UK；5.数据采集软件：MassLynx4.1；厂家：Waters；6.分析鉴定软件：Progenesis QI；厂家：Waters。
实验试剂：异丙醇、乙腈，甲酸，甲酸氨，亮氨酸脑啡肽，甲酸钠；厂家均为Fisher。
三、实验方法
1.样品前处理
收集的血清样本在冰上解冻，200μL的血浆用600μL的预冷异丙醇萃取，涡流1min，室温孵育10min，然后将萃取混合物在-20℃下储存过夜，4000r离心20min后，将上清液转移到新的离心管，用异丙醇/乙腈/水(按体积比为2：1：1)稀释至1：10。样品在LC-MS分析前保存在-80℃。此外，还将每个萃取混合物的10μL组合在一起制备混合血浆样品。
2.脂质组学的超高效液相色谱-质谱联用方法
样品用ACQUITY UPLC(Waters，美国)连接到带有ESI的Xevo-G2XS高分辨飞行时间(QTOF)质谱仪(Waters)进行分析。采用CQUITY UPLC BEH  C18色谱柱(2.1×10 0mm，1.7μm，Waters)，流动相为10mM甲酸铵-0.1％甲酸-乙腈(A，乙腈：水为60：40，v/v)和10mM甲酸铵-0.1％甲酸-异丙醇-乙腈(B，异丙醇：乙腈为90：10，v/v)。在大规模研究之前，进行了包括10分钟、15分钟和20分钟洗脱期的中试实验，以评估流动相组成和流速对脂质保留时间的潜在影响。在正离子模式(PIM)中，丰富的脂质前体离子和碎片以相同的顺序分离，具有相似的峰形和离子强度。此外，具有10分钟洗脱期的混合质控(QC)样品也表现出与测试样品相似的前体和碎片的基峰强度。流动相流速为0.4mL/min。该柱最初用40％B洗脱，然后在2分钟内线性梯度到43％B，然后在0.1min内将B的百分比增加到50％。在接下来的3.9分钟内，梯度进一步增加到54％B，然后B的量0.1分钟内增加到70％。在梯度的最后部分，B的量在1.9分钟内增加到99％。最后，溶液B在0.1分钟内返回到40％，并且在下一次进样之前将色谱柱平衡1.9分钟。每次进样量为5μL，用Xevo-G2XS型QTOF质谱仪检测正负两种模式下的脂质，采集范围为m/z50～1200年，采集时间为0.2s/次。离子源温度为120℃，去溶温度为600℃，气体流量为1000L/h，以氮气为流动气体。毛细管电压为2.0kV(+)/锥体电压为1.5kV(-)，锥体电压为30V。甲酸钠和亮氨酸脑啡肽作校正液(waters质谱仪器自带)。样品被随机排序。每10个样本注入一个质控(QC)样本并进行分析，以调查数据的重复性。
四、结果分析：
1.利用多元统计学寻找血清差异物质
对于内部人群采用正交偏最小二乘判别分析(OPLS-DA)结合了正交信号矫正(OSC)和PLS-DA方法，通过去除不相关的差异来筛选差异变量。如图1为正负离子模式下VIP＞1的代谢物，VIP值为OPLSDA第一主成分的变量重要性投影，通常以VIP>1为代谢组学常用评判标准，作为差异代谢物筛选的标准之一，其中，A正离子模式，B为负离子模式；图2为正负离子模式下(O)PLS-DA的得分图，其中，C为正离子模式下(O)PLS-DA的得分图，D为负离子模式下(O)PLS-DA的得分图，认知障碍组(DIS表示)和空白对照组(CK表示)两个分组中的第一主成分和第二主成分通过降维的方 式所得的得分图，横坐标表示组间差异，纵坐标表示组内差异，且两组结果分离较好，说明此方案可以使用。图3为正负离子模式下S-plot图，E为正离子模式下S-plot图，F为负离子模式下S-plot图，横坐标表示主成分与代谢物的协相关系数，纵坐标表示主成分与代谢物的相关系数，同时满足p<0.05，VIP>1的条件下，负离子模式有59个差异物，正离子模式有117个差异物。
2.约登指数分析
为了进一步缩小范围，将VIP阈值提高到3，同时体现正常和患者之间的倍数差异在0.8倍以下，或者增加1.2倍以上，最终得到以下10个化合物，具体见表1。
然后对他们进行youden约登指数计算，用来反映单个指标对整体的诊断和预测效果，结果如下表1：
表1认知障碍相关脂质的约登指数分析
Figure PCTCN2021112405-appb-000001
表1列出来单个代谢物预测认知障碍的曲线下面积(AUC)、敏感度和特异性，相关参数显示以上20种脂质中，SM(d18:2/24:1)的预测能力最好(AUC＝0.944)。而24：1，就是表示含有神经酸链。
3.内部人群七折交叉验证结果
根据上述结果，挑选YOUDEN AUC值大于0.9的变量化合物，进行下一步的分析。
表2
Figure PCTCN2021112405-appb-000002
将内部人群随机分为7份，选择1份为验证集，其他为训练集，如此反复七次，考察最佳的变量组合。将其次的结果，包括AUC，敏感度，特异性都取平均值，并进行统计学显著性计算，结果如下表3。
表3
Figure PCTCN2021112405-appb-000003
组合之间，AUC值并没有显著性p<0.05差异。
基于上述建立逻辑回归模型A、B、C如下：
"模型A"变量为上述BM3+BM2，计算公式为：TC＝79.43-2.199×10 -4×BM3+1.206×10 -4×BM2，计算TC值，公式中BM3为SM(d18:1/24:1(15Z))的含量，BM2为TG(16:0/18:0/18:4(6Z,9Z,12Z,15Z))的含量，根据TC值预测认知障碍：若TC≥0.5，则判定为认知障碍；若TC＜0.5，则为正常；
"模型B"变量为上述BM3+BM4，计算公式为：TC＝604.8–5.028×10 -4×BM3-1.909×10 -3×BM4，计算TC值，公式中BM3为SM(d18:1/24:1(15Z))的含量，BM4为PC(P-16:0/22:4(7Z,10Z,13Z,16Z))的含量，根据TC值预测认知障碍：若TC≥0.421，则判定为认知障碍；若TC＜0.421，则为正常。
"模型C"变量为上述BM3+BM5，变量为TG(13:0/17:1(9Z)/20:2(11Z,14Z))+SM(d18:1/24:1(15Z))，计算公式为：48.98-4.266×10 -5×BM3-1.897×10 -4×BM5，计算TC值，公式中BM3为SM(d18:1/24:1(15Z))的含量，BM5为PC(P-18:0/18:4(6Z,9Z,12Z,15Z))的含量，根据TC值预测认知障碍：若TC≥0.749，则判定为认知障碍；若TC＜0.749，则为正常。
4.外部数据集，逻辑回归模型验证
通过外部人群的数据集验证上述结果的准确性，并绘制相应的ROC曲线图。结果如下：
"模型A"变量为上述BM3+BM2，结果如图4，Sensitivity(敏感性)＝1，Specificity(特异性)＝1，Accuracy(准确度)＝1。
"模型B"变量为上述BM3+BM4，结果如图5，Sensitivity(敏感性)＝1，Specificity(特异性)＝0.833，Accuracy(准确度)＝1。
"模型C"变量为上述BM3+BM5，变量为TG(13:0/17:1(9Z)/20:2(11Z,14Z))+SM(d18:1/24:1(15Z))，结果如图6，Sensitivity(敏感性)＝1，Specificit y(特异性)＝0.833，Accuracy(准确度)＝1。
数据显示：SM(d18:1/24:1(15Z))，或结合TG(16:0/18:0/18:4(6Z,9Z,12Z,15Z))，PC(P-16:0/22:4(7Z,10Z,13Z,16Z))，PC(P-18:0/18:4(6Z,9Z,12Z,15Z))都表现出非常高的诊断能力，都能进行临床试剂盒的应用。
通过对样本信息的对比分析可知：以上5种生物标记物，与正常组相比，BM1、BM3、BM4和BM5在认知障碍组均呈下降趋势，BM2则相反。
实施例2
一种用于诊断认知障碍的检测试剂盒，其包括标准品S标准品SM(d18:1/24:1(15Z))，和TG(16:0/18:0/18:4(6Z,9Z,12Z,15Z))、PC(P-16:0/22:4(7Z,10Z,13Z,16Z))或PC(P-18:0/18:4(6Z,9Z,12Z,15Z))中的任一种，流动相A液：含溶质为10mM甲酸铵和0.1％甲酸，溶剂为体积比为60:40的乙腈：水；流动相B液：含溶质为10mM甲酸铵和0.1％甲酸，溶剂为体积比为90:10的异丙醇：乙腈。其中，10mM甲酸铵-0.1％甲酸-乙腈(A，乙腈：水为60：40，v/v)的配置方法为称取甲酸铵0.63g，甲酸10g，用乙腈-水溶液(乙腈：水为60：40，v/v)溶解并定容至1000mL。
10mM甲酸铵-0.1％甲酸-异丙醇-乙腈(B，异丙醇：乙腈为90：10，v/v)的配置方法为称取甲酸铵0.63g，甲酸10g，用异丙醇-乙腈溶液(异丙醇：乙腈为90：10，v/v)溶解并定容至1000mL。
对于样品的检测是采用实施例1中的样品前处理和超高效液相色谱-质谱联用检测方法进行，同时将标准品标准品SM(d18:1/24:1(15Z))，和TG(16:0/18:0/18:4(6Z,9Z,12Z,15Z))、PC(P-16:0/22:4(7Z,10Z,13Z,16Z))或PC(P-18:0/18:4(6Z,9Z,12Z,15Z))作为参照进行检测。
实施例3
一种治疗认知障碍的方法，其包括：(a)采用如实施例2中的试剂盒及检测方法诊断认知障碍患者，(b)对于检测获得SM(d18:1/24:1(15Z))的含量记为BM3，测得的TG(16:0/18:0/18:4(6Z,9Z,12Z,15Z))的含量为BM2，计算TC值按公式TC＝79.43-2.199×10 -4×BM3+1.206×10 -4×BM2进行，若TC≥0.5；或测得的PC(P-16:0/22:4(7Z,10Z,13Z,16Z))的含量记为BM4，计算TC值按公式TC＝604.8–5.028×10 -4×BM3-1.909×10 -3×BM4，若TC≥0.421；或测得的PC(P-18:0/18:4(6Z,9Z,12Z,15Z))的含量记为BM5，计算TC值按公式TC＝48.98-4.266×10 -5×BM3-1.897×10 -4×BM5，若TC≥0.749；被认为是患有认知障碍，检测结果有10个患者，用上述方法进行确诊，并用MRI核磁检测进一步确认，按照常规方法给美金刚药治疗2个月后，通过上述方法进行筛查判断，结果表明患者的病情得到好转、控制。这与用MRI核磁检测确 认结果一致，说明本发明的筛查方法判断的结果与核磁诊断确认结果一样准确，说明本发明的诊断方法准确、可靠。

Claims (7)

  1. 一种诊断认知障碍的检测方法，其特征在于，其包括检测受试者血清中的SM(d18:1/24:1(15Z))的含量，和TG(16:0/18:0/18:4(6Z,9Z,12Z,15Z))、PC(P-16:0/22:4(7Z,10Z,13Z,16Z))或PC(P-18:0/18:4(6Z,9Z,12Z,15Z))中的任一种的含量，通过计算TC值判断是否存在认知障碍。
  2. 根据权利要求1所述的检测方法，其特征在于，测得的SM(d18:1/24:1(15Z))的含量记为BM3，测得的TG(16:0/18:0/18:4(6Z,9Z,12Z,15Z))的含量为BM2，计算TC值按公式TC＝79.43-2.199×10 -4×BM3+1.206×10 -4×BM2进行，若TC≥0.5，则判定为认知障碍；若TC＜0.5，则为正常。
  3. 根据权利要求1所述的检测方法，其特征在于，测得的SM(d18:1/24:1(15Z))的含量记为BM3，测得的PC(P-16:0/22:4(7Z,10Z,13Z,16Z))的含量记为BM4，计算TC值按公式TC＝604.8–5.028×10 -4×BM3-1.909×10 -3×BM4，若TC≥0.421，则判定为认知障碍；若TC＜0.421，则为正常。
  4. 根据权利要求1所述的检测方法，其特征在于，测得的SM(d18:1/24:1(15Z))的含量记为BM3，测得的PC(P-18:0/18:4(6Z,9Z,12Z,15Z))的含量记为BM5，计算TC值按公式TC＝48.98-4.266×10 -5×BM3-1.897×10 -4×BM5，若TC≥0.749，则判定为认知障碍；若TC＜0.749，则为正常。
  5. 根据权利要求1所述的检测方法，其特征在于，检测方法采用超高效液相色谱-质谱联用。
  6. 一种治疗认知障碍的方法，其包括：(a)采用如权利要求1-5中任一项所述的检测方法诊断认知障碍患者，(b)将确诊的患者使用认知障碍治疗药物进行治疗，(c)通过如权利要求1-5中任一项所述的方法诊断康复状况。
  7. 一种用于诊断认知障碍的检测试剂盒，其特征在于，其包括标准品SM(d18:1/24:1(15Z))，和TG(16:0/18:0/18:4(6Z,9Z,12Z,15Z))、PC(P-16:0/22:4(7Z,10Z,13Z,16Z))或PC(P-18:0/18:4(6Z,9Z,12Z,15Z))中的任一种，流动相A：含溶质为10mM甲酸铵和0.1％甲酸，溶剂为体积比为60:40的乙腈：水； 流动相B：含溶质为10mM甲酸铵和0.1％甲酸，溶剂为体积比为90:10的异丙醇：乙腈。
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