WO2023010752A1 - 一种用于评估精神分裂症患者心脏损伤的标志物、检测方法和试剂盒 - Google Patents

一种用于评估精神分裂症患者心脏损伤的标志物、检测方法和试剂盒 Download PDF

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WO2023010752A1
WO2023010752A1 PCT/CN2021/138095 CN2021138095W WO2023010752A1 WO 2023010752 A1 WO2023010752 A1 WO 2023010752A1 CN 2021138095 W CN2021138095 W CN 2021138095W WO 2023010752 A1 WO2023010752 A1 WO 2023010752A1
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schizophrenia
patients
serum
indole
lactic acid
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张志珺
栾迪
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Shenzhen Institute of Advanced Technology of CAS
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    • 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
    • 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
    • G01N30/62—Detectors specially adapted therefor
    • G01N30/72—Mass spectrometers
    • 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
    • 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

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  • the invention belongs to the field of medical detection, and in particular relates to a marker, a detection method and a kit for evaluating heart damage in patients with schizophrenia.
  • Heart damage An important cause of death in patients with schizophrenia is heart damage, and early recognition is particularly important.
  • the 24-hour ambulatory electrocardiogram is more able to reflect the patient's heart injury and the state of the heart in dynamic and resting conditions. It is an important detection method for heart injury. It is difficult to obtain accurate data of 24-hour ambulatory electrocardiogram, and then it is impossible to obtain various indicators of the heart.
  • the present invention provides a biomarker that can be used to assess heart damage in schizophrenia and its detection methods and kits.
  • One aspect of the present invention provides a detection reagent for evaluating cardiac damage in patients with schizophrenia, wherein the detection reagent includes a reagent for detecting indole-3-lactic acid in serum.
  • the reagents include reagents for extracting indole-3-lactic acid from serum and reagents for quantitatively detecting indole-3-lactic acid.
  • Another aspect of the present invention provides a kit for assessing cardiac damage in patients with schizophrenia, which includes the above-mentioned detection reagent.
  • Another aspect of the present invention provides the use of the above-mentioned detection reagent in the preparation of a kit or detection preparation for assessing cardiac injury in patients with schizophrenia.
  • the heart injury condition is selected from abnormalities in the 24-hour ambulatory electrocardiogram, and further, the abnormalities are selected from hidden arrhythmias that are easily missed by conventional electrocardiograms; preferably tachyarrhythmia, bradyarrhythmia, Ectopic rhythm, conduction block, arrhythmia leading to sudden cardiac death, myocardial infarction, silent myocardial ischemia.
  • Another aspect of the present invention provides a method for assessing heart damage in patients with schizophrenia, the method comprising the following steps:
  • the method for detecting the concentration of indole-3-lactic acid in serum is selected from HPLC method or HPLC combined with mass spectrometry method.
  • the concentration of indole-3-lactic acid in the serum is higher than the normal value, it is considered to have heart damage.
  • Another aspect of the present invention provides a marker for assessing cardiac damage in patients with schizophrenia, the marker being selected from indole-3-lactic acid.
  • Another aspect of the present invention provides a method for screening serum metabolites as a marker for assessing cardiac injury in patients with schizophrenia, the method comprising the following steps:
  • step i) the ratio of the number of schizophrenia patients with heart damage to the schizophrenia patients without heart damage is 1:0.5-1.5.
  • step ii) the ratio of the number of people in the non-abnormal group to the abnormal group is 1:0.5-1.5.
  • the method for detecting metabolites is a method of high performance liquid chromatography coupled with mass spectrometry (LC-MS).
  • step i) the method of data analysis is PCA analysis with SIMCA-P software, and on this basis, the model construction of PLS-DA and OPLS-DA is carried out, so as to obtain the differential metabolites between groups.
  • the present invention breaks the technical prejudice and provides a serum detection method for assessing heart damage in patients with schizophrenia. None of the prior art mentions that schizophrenia can be assessed by the content of metabolites in serum through the method of metabolomics Patient with cardiac injury. It is well known that heart injury is an important factor affecting the life and health of patients with schizophrenia, and the unstable mental state of schizophrenic patients makes it difficult to diagnose and treat heart injury. Especially the ambulatory electrocardiogram that needs to detect for a long time, compliance is very low.
  • the present invention creatively screens the metabolites in the serum, and finds the metabolites related to the heart damage of patients with schizophrenia as markers in the metabolites, which can obtain the heart damage status more quickly and improve the patient's compliance.
  • the biomarker of the present invention can be detected by plasma, the detection method is simple, and the detection efficiency is higher than that of the 24-hour dynamic electrocardiogram.
  • Fig. 1 is total PCA score map (ESI+) in embodiment 1.
  • Figure 2 is the total PCA score graph (ESI-) in Example 1.
  • Fig. 3 is the PCA score figure (ESI+) of A-B two groups in embodiment 1.
  • Fig. 4 is the PCA score chart (ESI-) of A-B two groups in embodiment 1.
  • Fig. 5 is the PLS-DA score map and the sequence verification map (ESI+) of the A-B two groups in Example 1.
  • Fig. 6 is the PLS-DA score diagram and the sequence verification diagram (ESI-) of the A-B groups in Example 1.
  • Fig. 7 is the OPLS-DA score graph (ESI+) of A-B group in embodiment 1.
  • Fig. 8 is the OPLS-DA score map (ESI-) of the A-B group in Example 1.
  • Fig. 9 is a statistical graph (mean ⁇ standard deviation) in Example 2.
  • 40 patients with schizophrenia were selected, including 20 patients with heart injury group A and 20 patients without heart injury group B.
  • Peripheral blood was collected from 40 patients, and LC-MS metabolomics research was carried out, and the differential metabolites found between groups were screened, identified, pathway assigned and clustered.
  • the patient's serum sample was thawed at room temperature, and 100 ⁇ L of the sample was pipetted into a 1.5 mL EP tube with a pipette gun.
  • the chromatographic separation conditions are: column temperature is 40°C; flow rate is 0.3mL/min;
  • Mobile phase composition A water + 0.05% formic acid, B: acetonitrile;
  • the injection volume was 6 ⁇ L, and the autosampler temperature was 4°C.
  • the mobile phase gradient elution program is shown in Table 1.
  • Positive mode heater temperature 300°C; sheath gas flow: 45arb; auxiliary gas flow: 15arb; exhaust gas flow: 1arb; electrospray voltage: 3.0KV; capillary temperature: 350°C; S-Lens RF Level, 30%.
  • Negative mode heater temperature 300°C; sheath gas flow: 45arb; auxiliary gas flow: 15arb; exhaust gas flow: 1arb; electrospray voltage: 3.2KV; capillary temperature: 350°C; S-Lens RF Level, 60%.
  • Use Compound Discoverer software (Thermo Company) to extract and preprocess the LC/MS detection data, and normalize and post-edit the data in Excel 2010, and finally arrange it into a two-dimensional data matrix form, including retention time (RT( Retention time)), molecular weight (CompMW), observed amount (sample name), number of extractable substances (ID) and peak intensity.
  • RT Retention time
  • CompMW molecular weight
  • ID number of extractable substances
  • peak intensity peak intensity
  • the principal component analysis of the samples can generally reflect the metabolic difference between the two groups of samples and the variability of the samples within the group.
  • the purpose of normalization is to make the scale of all variables (a certain numerical feature, such as mean and standard deviation) on the same level, so as to avoid the concentration difference of different metabolites in complex biological samples.
  • the signal of some metabolites with high or low concentration caused by large concentration is masked, which affects the identification of biomarkers.
  • PCA analysis is a non-supervised model analysis method.
  • the model can be based on Compared with supervised model analysis methods such as PLS-DA analysis, PCA can more truly reflect the difference between groups and identify the variation within the group.
  • PLS-DA Partial Least Squares Discriminant Analysis
  • the main parameters to judge the quality of the model are R 2 Y (the value represents the interpretation rate of the model) and Q 2 value (the value is the prediction rate of the model).
  • the model will be sorted and verified to check whether the model is "overfitting". The model is unreliable for explaining the difference between the two groups and finding different substances, so it is not appropriate to use this data for subsequent analysis.
  • Whether the model is "overfitting” reflects whether the model is constructed accurately. The lack of “overfitting” indicates that the model can describe the sample well and can be used as a prerequisite for the search for model biomarker groups. “Overfitting” indicates that This model is not suitable for describing samples, nor is it suitable for post-analysis of this data.
  • the VIP Very Importance in the Projection value of the OPLS-DA model (threshold > 1) was used, combined with the p value of the t-test (p ⁇ 0.05) to find differentially expressed metabolites.
  • the qualitative method of the differential metabolites is: search the online database (Metlin) (comparing the mass-to-charge ratio m/z or accurate molecular mass mass of the mass spectrum).
  • Embodiment 2 large sample verification
  • liquid A is 50 mM ammonium acetate aqueous solution (containing 1.2% NH4OH), and liquid B is acetonitrile.
  • the sample was placed in an autosampler at 4°C, the column temperature was 35°C, the flow rate was 300 ⁇ L/min, and the injection volume was 2 ⁇ L.
  • the relevant liquid phase gradient is as follows: 0-3min, B solution linearly changes from 85% to 80%; 3-4min, B solution maintains at 80%; 4-6min, B solution linearly changes from 80% to 70%; 6-10min , B solution linearly changed from 70% to 50%; 10-12.5min, B solution was maintained at 50%; 12.5-12.6min B solution was linearly changed from 50% to 85%; 12.6-18min, B solution was maintained at 85%.
  • Solution A is 50 mM ammonium formate aqueous solution (containing 0.425% FA), and solution B is pure methanol.
  • the sample was placed in an autosampler at 4°C, the column temperature was 40°C, the flow rate was 400 ⁇ L/min, and the injection volume was 2 ⁇ L.
  • the relevant liquid phase gradient is as follows: 0-5min, B liquid changes linearly from 5% to 60%; 5-11min, B liquid changes linearly from 60% to 100%; 11-13min, B liquid maintains at 100%; min, B solution linearly changed from 100% to 5%; 13.1-16min, B solution maintained at 5%.
  • a QC sample is set at every interval of a certain number of experimental samples in the sample queue to detect and evaluate the stability and repeatability of the system.
  • Mass spectrometry was performed using a 5500QTRAP mass spectrometer (AB SCIEX) in positive/negative ion mode.
  • 5500QTRAP ESI source conditions are as follows:
  • the ion source parameters in positive ion mode are as follows:
  • Source temperature 450°C; Gas 1,60; Gas 2,60; CRU,30; ISVF,5000V
  • Negative ion mode ion source parameters are as follows:
  • Source temperature 450°C; Gas 1,60; Gas 2,60; CRU,30; ISVF,-5000V;
  • the MRM mode was used to detect the ion pairs to be tested, and the ion pair information of all neurotransmitters is shown in Appendix 1.
  • the metabolite value of each sample is unitless and represents the corrected peak area, which belongs to relative quantification.
  • #Abnormal refers to tachyarrhythmia, bradyarrhythmia, ectopic rhythm, conduction block, arrhythmia leading to sudden cardiac death, myocardial infarction, asymptomatic myocardial ischemia.
  • the patients were divided into two groups according to whether the ambulatory electrocardiogram was abnormal, and the one with statistical difference was indole-3-lactic acid, and the patients with schizophrenia with abnormal ambulatory electrocardiogram were higher than those without abnormality in ambulatory electrocardiogram.
  • the statistical results are shown in Figure 9.
  • the present invention has discovered a serological index that can be used as a serological indicator of heart damage in patients with schizophrenia, that is, indole-3-lactic acid, and can predict schizophrenia by detecting indole-3-lactic acid in serum It is very beneficial for the prediction of cardiac injury in patients with schizophrenia, because although it is very convenient and accurate to use 24-hour dynamic electrocardiogram for patients with non-psychiatric diseases, it is very convenient and accurate for patients with schizophrenia.
  • Monitoring is very difficult, especially during the onset of the disease, patients are likely to not cooperate with monitoring, or tear off the monitoring device from the fixed part or destroy the device during the monitoring process. Relatively, the time for blood drawing is short, and it can usually be completed with the cooperation of patients or other auxiliary personnel, and the time for testing is shorter than the 24-hour electrocardiogram cycle. It can improve diagnostic efficiency, improve accuracy and patient compliance.

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Abstract

一种用于评估精神分裂症患者心脏损伤的标志物、检测方法和试剂盒。用于评估精神分裂症患者心脏损伤情况的检测试剂包含从血清中提取吲哚-3-乳酸的试剂以及定量检测吲哚-3-乳酸的试剂。评估精神分裂症患者心脏损伤的血清检测方法，以精神分裂症患者心脏损伤相关的代谢物作为标志物，可以更快地获得心脏损伤情况，提高了患者的依从性。

Description

一种用于评估精神分裂症患者心脏损伤的标志物、检测方法和试剂盒 技术领域
本发明属于医学检测领域，具体涉及一种用于评估精神分裂症患者心脏损伤标志物、检测方法和试剂盒。
背景技术
精神分裂症患者的一个重要死亡原因是心脏损伤，早期识别尤为重要。在心脏损伤的检测中，24小时动态心电图更能够反应患者的心脏损伤情况以及动态和静息时的心脏状态，是心脏损伤的重要检测手段，但是由于精神分裂症患者的精神情况不稳定，导致难以获得24小时动态心电图的准确数据，进而无法获得心脏的各项指标。
如何快速获得精神分裂患者的心脏相关数据，降低精神分裂患者精神状态对检测结果的影响，是目前急需解决的问题。
发明内容
基于现有技术中存在的上述问题，本发明为解决精神分裂症患者心脏损伤无法诊断或预测的问题，提供了一种能够用于评估精神分裂症心脏损伤的生物标记物及其基于该生物标记物的检测方法和试剂盒。
本发明一个方面提供了一种用于评估精神分裂症患者心脏损伤情况的检测试剂，所述检测试剂中包含用于检测血清中吲哚-3-乳酸的试剂。
进一步地，所述试剂包括从血清中提取吲哚-3-乳酸的试剂以及定量检测吲哚-3-乳酸的试剂。
本发明另一个方面提供了一种用于评估精神分裂症患者心脏损伤情况的试剂盒，所述试剂盒中包含上述检测试剂。
本发明又一个方面提供了上述检测试剂在制备用于评估精神分裂症患者心脏损伤情况的试剂盒或检测制剂中的用途。
进一步地，所述心脏损伤情况选自24小时动态心电图存在异常，更进一步地，所述的异常选自易被常规心电图漏诊的隐匿性心律失常；优选为快速性心律失常、缓慢性心律失常、异位节律、传导阻滞、导致心源性猝死的心律失常、心肌梗死、无症状心肌缺血。
本发明再一个方面提供了评估精神分裂症患者心脏损伤情况的方法，所述方法包括以下步骤：
1)获得患有精神分裂症的受试者的血清样品，通过提取试剂从血清样品中提取吲哚-3-乳酸，并检测血清中吲哚-3-乳酸的浓度；
2)通过血清中吲哚-3-乳酸的浓度判断受试者是否患有心脏损伤。
进一步地，检测血清中吲哚-3-乳酸的浓度的方法选自HPLC方法或HPLC与质谱联用的方法。
进一步地，所述血清中吲哚-3-乳酸的浓度高于正常值则认为具有心脏损伤。
本发明再一个方面提供了一种评估精神分裂症患者心脏损伤情况的标志物，所述标志物选自吲哚-3-乳酸。
本发明再一个方面提供了一种筛选血清代谢产物作为评估精神分裂症患者心脏损伤情况标志物的方法，所述方法包括以下步骤：
i)以精神分裂症患者作为第一筛选队列，第一筛选队列中包含具有心脏损伤的精神分裂症患者和心脏未损伤的精神分裂症患者；通过代谢组学研究，对具有心脏损伤的筛选队列以及不具有心脏损伤的筛选队列的血清中的代谢物进行检测和数据分析，筛选获得组间差异代谢物；
ii)以精神分裂症患者作为第二筛选队列，对第二筛选队列进行24小时动态心电图检测，并根据24小时动态心电图结果划分为无异常组和有异常组；分别检测无异常组和有异常组的血清中的组间差异代谢物的含量或浓度，并进行统计分析，筛选具有统计学差异的组间差异代谢物即为评估精神分裂症患者心脏损伤情况标志物。
进一步地，在步骤i)中，具有心脏损伤的精神分裂症患者和心脏未损伤的精神分裂症患者的人数比为1:0.5-1.5。
进一步地，在步骤ii)中，无异常组和有异常组的人数比为1:0.5-1.5。
进一步地，在步骤i)中，代谢物进行检测的方法为高效液相和质谱联用(LC-MS)的方法。
进一步地，在步骤i)中，数据分析的方法为SIMCA-P软件进行PCA分析，并在此基础上进行PLS-DA、OPLS-DA的模型构建，从而获得组间差异代谢物。
有益效果
1)本发明打破了技术偏见提供了一种评估精神分裂症患者心脏损伤的血清检测方法，现有技术中均未提及通过代谢组学的方法可以通过血清中代谢物的含量评估精神分裂症患者心脏损伤情况。众所周知，心脏损伤是影响精神分裂症患者寿命和健康的重要因素，而精神分裂症患者的精神状态不稳定导致对于其心脏损伤的诊断和治疗存在困难。尤其是需要长时间 检测的动态心电图，依从性很低。本发明创造性地筛选了血清中的代谢物，发现了代谢物中与精神分裂症患者心脏损伤相关的代谢物作为标志物，可以更快地获得心脏损伤情况，提高了患者的依从性。
2)本发明的生物标记物能够通过血浆进行检测，检测方法简单，检测效率相比于24小时动态心电图更高。
附图说明
图1为实施例1中总PCA得分图(ESI+)。
图2为实施例1中总PCA得分图(ESI-)。
图3为实施例1中A-B两组的PCA得分图(ESI+)。
图4为实施例1中A-B两组的PCA得分图(ESI-)。
图5为实施例1中A-B两组的PLS-DA得分图及排序验证图(ESI+)。
图6为实施例1中A-B两组的PLS-DA得分图及排序验证图(ESI-)。
图7为实施例1中A-B两组的OPLS-DA得分图(ESI+)。
图8为实施例1中A-B两组的OPLS-DA得分图(ESI-)。
图9为实施例2中的统计图(平均值±标准差)。
具体实施方式
为了使本发明的上述目的、特征和优点能够更加明显易懂，下面对本发明的具体实施方式做详细的说明，但不能理解为对本发明的可实施范围的限定。
实施例1 小样本中筛选代谢物
筛选队列选择40例精神分裂症患者，其中有20例具有心脏损伤A组，20例不具备心脏损伤B组。对40例患者取外周血，并进行LC-MS代谢组学研究并对寻找到的组间差异代谢物进行筛选、鉴定、通路归属及聚类分析。
样本预处理
1.1.患者血清样本置于室温解冻，用移液枪吸取100μL样本于1.5mL EP管中。
1.2.加入300μL甲醇，涡旋混匀30s。
1.3.-40℃静置1h。
1.4.涡旋混匀30s，4℃静置0.5h。
1.5.置于4℃离心机中，12000rpm离心15min。
1.6.取出全部上清液于离心管中，-40℃静置1h。
1.7.置于4℃离心机中，12000rpm离心15min。
1.8.吸取200μL上清，并加入5μL内标(140μg/mL，2-氯苯丙氨酸)，转入进样小瓶中待检测。
LC/MS分析
2.1.仪器分析平台：LC-MS(Waters,UPLC；Thermo,Q Exactive)
2.2.色谱柱：Waters ACQUITY UPLC HSS T3柱(2.1mm×100mm，1.8μm)
2.3.色谱分离条件为：柱温为40℃；流速0.3mL/min；
流动相组成A：水+0.05％甲酸，B：乙腈；
进样量为6μL，自动进样器温度4℃。
流动相梯度洗脱程序见表1。
表1.流动相洗脱程序
Figure PCTCN2021138095-appb-000001
质谱检测参数：
正模式：加热器温度300℃；鞘气流速：45arb；辅助气流速：15arb；尾气流速：1arb；电喷雾电压：3.0KV；毛细管温度：350℃；S-Lens RF Level,30％。
负模式：加热器温度300℃；鞘气流速：45arb；辅助气流速：15arb；尾气流速：1arb；电喷雾电压：3.2KV；毛细管温度：350℃；S-Lens RF Level,60％。
数据分析
使用Compound Discoverer软件(Thermo公司)对LC/MS检测数据进行提取和预处理，并在Excel 2010中对数据进行归一化及后期编辑，最后整理成二维数据矩阵形式，包含保留时间(RT(Retention time))、分子量(CompMW)、观察量(样本名称)、可提取物质个数(ID)和峰强度等信息。本项目在正模式下共得到2894个Features，负模式下获得2186个Features，将编辑后的数据矩阵导入SIMCA-P 13.0(Umetrics AB，Umea，Sweden)软件进行多元统计分。
多元统计分析
-总体PCA分析
对样本进行主成分分析能从总体上反映两组样本之间的代谢差异和组内样本之间的变异度的大小，在使用SMICA-P软件正式分析前，对数据组进行归一化处理，以获得更加直观且可靠的结果，归一化的目的是使所有变量的尺度(某种数字特征，如均值和标准差)在同一等级上，从而避免复杂生物样品中不同代谢物的浓度差别较大导致的某些浓度过高或过低代谢物的信号被掩盖，进而影响对生物标记物的辨识。
为了判别两组之间是否具有差异，采用PCA建模方法对样本进行分析，本分析在正模式下共获得6个主成分，累积R 2X＝0.495，Q 2＝0.257；负模式下共获得10个主成分，累积R 2X＝0.571，Q 2＝0.0281。PCA得分图(Scores plot)如图1、图2所示。
对于PCA这种非监督性模型分析来说，判别模型质量好坏的主要参数为R 2X，该值代表模型的解释率，PCA分析是一种非监督性的模型分析方法，该模型能够根据数据的相似性对其进行归类，因而相对于监督性的模型分析方法如PLS-DA分析来说，PCA可以更真实地反映组间差异以及识别组内变异。
-A-B组
PCA分析
对B组及A组进行主成分分析，本分析在正模式下共获得5个主成分，累积R 2X＝0.467，Q 2＝0.233；负模式下共获得8个主成分，累积R 2X＝0.519，Q 2＝0.0239。PCA得分图(Scores plot)如图3和图4所示：
为了获得导致这种显著差异的代谢物信息，进一步采用监督性的多维统计方法即偏最小二乘方判别分析(PLS-DA)对两组样本进行统计分析。
其模型质量参数为：在正模式下，具有2个主成分，R 2X＝0.225，R 2Y＝0.804，Q 2＝-0.163；负模式下2个主成分，R 2X＝0.13，R 2Y＝0.821，Q 2＝-0.21。判别模型质量好坏的主要参数为R 2Y(该值代表模型的解释率)及Q 2值(该值为模型的预测率)。另外还会对模型进行排序验证，检验模型是否“过拟合”。模型对于解释两组之间差异及寻找差异物质是不可靠的，因此不宜利用此数据进行后续分析。
模型的是否“过拟合”体现了模型构建的是否准确，未“过拟合”说明模型能较好的描述样本，并可作为模型生物标记物群寻找的前提，“过拟合”则说明该模型不适合用来描述样本，也不宜以此数据做后期分析。
进一步采用有监督式方法OPLS-DA进行建模分析，结果正模式下得到1个主成分和1个正交成分，R 2X＝0.225，R 2Y＝0.804，Q 2＝-0.0237；负模式下得到1个主成分和1个正交成分， R 2X＝0.13，R 2Y＝0.821，Q 2＝-0.373，模型的参数R 2Y表示模型的解释率，Q 2表示模型的预测率。其得分图如图7和图8所示：
-A-B组差异性代谢产物的挖掘及鉴定
采用OPLS-DA模型的VIP(Variable Importance in the Projection)值(阈值>1)，并结合t-test的p值(p＜0.05)来寻找差异性表达代谢物。差异性代谢物的定性方法为：搜索在线数据库(Metlin)(比较质谱的质荷比m/z或者精确分子质量mass)。
采用LC/MS仪器对人血清样本进行检测。对所有样本中这些物质的峰的响应强度数据进行模型判别分析，我们首先使用SIMCA-P软件进行PCA分析，并在此基础上进行PLS-DA、OPLS-DA的模型构建，从而获得差异性表达代谢物。差异物质种类主要包括氨基酸类、脂肪酸类、有机酸类等。主要影响的通路有氨基酸代谢、脂肪酸代谢、脂质代谢等。
实验结果显示有差异的分子14个：
1)脱氧胆酸(Deoxycholic acid)、2)20-羟-二十烷四烯酸(20-Hydroxyeicosatetraenoic acid)、3)乳酸盐(Lactate)、4)皮质醇(Cortisol)、5)胆红素(Bilirubin)、6)甲硫氨酸(methionine)、7)肌酸(creatine)、8)胆碱(Choline)、9)丙酰肉碱(Propionylcarnitine)、10)顺式二十碳-11-烯酸(cis-gondoic acid)、11)吲哚乙酸(indoleacetate，IAA)、12)吲哚-3-乳酸(Indole-3-lactic acid)、13)二氢胸腺嘧啶(Dihydrothymined)、14)γ-谷氨酸亮氨酸(gamma-Glutamylleucine)。
通过本实验，发现了20例心脏损伤最严重的精神分裂症患者和相对应无心脏损伤的精神分裂症患者相比，血清中的14的指标可以作为潜在的判断精神分裂症患者心脏损伤的标准。
实施例2大样本验证
将这14种代谢物在199个样本中进行验证，并配合24小时动态心电图的数据进行对比，进一步筛选能够作为精神分裂症患者心脏损伤标准的标志物。
代谢物提取
取血浆样本200μL，每份样本加入800μL预冷甲醇/乙腈(1:1,v/v)涡旋混合，-20℃孵育1h沉淀蛋白，3000rcf 4℃离心20min，取上清真空干燥。加入300μL CH3OH/ACN/water(1:1:1，v/v/v)复溶液，3000rcf 4℃离心20min，取上清液进样分析。
色谱-质谱分析
A高效液相色谱条件
样品采用Agilent 1290Infinity LC超高效液相色谱系统进行分离。亲水色谱分析流动相：A液为50mM乙酸铵水溶液(含1.2％NH4OH)，B液为乙腈。样品置于4℃自动进样器中，柱 温35℃，流速为300μL/min，进样量2μL。相关液相梯度如下：0-3min，B液从85％线性变化到80％；3-4min，B液维持在80％；4-6min，B液从80％线性变化至70％；6-10min，B液从70％线性变化至50％；10-12.5min，B液维持在50％；12.5-12.6min B液从50％线性变化至85％；12.6-18min，B液维持在85％。
反相色谱分析流动相：A液为50mM甲酸铵水溶液(含0.425％FA)，B液为纯甲醇。样品置于4℃自动进样器中，柱温40℃，流速为400μL/min，进样量2μL。相关液相梯度如下：0-5min，B液从5％线性变化到60％；5-11min，B液从60％线性变化至100％；11-13min，B液维持在100％；13-13.1min，B液从100％线性变化至5％；13.1-16min，B液维持在5％。
样本队列中每间隔一定数量的实验样本设置一个QC样本，用于检测和评价系统的稳定性及重复性。
B质谱分析
采用5500QTRAP质谱仪(AB SCIEX)在正/负离子模式下进行质谱分析。5500QTRAP ESI源条件如下：
正离子模式离子源参数如下：
Source temperature,450℃；Gas 1,60；Gas 2,60；CRU,30；ISVF,5000V
负离子模式离子源参数如下：
Source temperature,450℃；Gas 1,60；Gas 2,60；CRU,30；ISVF,-5000V；
采用MRM模式检测待测离子对，所有神经递质的离子对信息见附件1。
数据处理
使用MultiQuant或Analyst软件定量分析；确定积分效果；根据对应的24小时动态心电图结果进行统计学分析，结果见下表。
Figure PCTCN2021138095-appb-000002
Figure PCTCN2021138095-appb-000003
*每个样本的代谢物值是没有单位的，代表的是矫正后峰面积，属于相对定量。
#有异常指快速性心律失常、缓慢性心律失常、异位节律、传导阻滞、导致心源性猝死的心律失常、心肌梗死、无症状心肌缺血。
以动态心电图有无异常分为两组，有统计学差异的为吲哚-3-乳酸，动态心电图有异常的精神分裂症患者高于无异常的精神分裂症患者。统计结果见图9。从大样本数据结果可知，本发明发现了一种能过作为精神分裂症患者心脏损伤的血清学指标，即吲哚-3-乳酸，通过检测血清中的吲哚-3-乳酸能够预测精神分裂症患者的心脏损伤情况，这对于精神分裂症患者的心脏损伤预测非常有利，因为虽然对于非精神疾病的患者而言采用24小时动态心电图是非常方便且准确的，但是对于精神分裂症患者而言监测难度非常高，尤其是在发病期间，患者很可能会出现不配合监测，或者在监测过程中将监测设备从固定部位撕扯掉或破坏设备的行为。而相对地，抽血的时间较短，通常情况下均能在患者或其他辅助人员的配合下完成，且化验的时间相较于24小时心电图周期更短。能够提高诊断效率，提高准确性和患者依从性。

Claims (10)

  1. 一种用于评估精神分裂症患者心脏损伤情况的检测试剂，其特征在于，所述检测试剂中包含用于检测血清中吲哚-3-乳酸的试剂；
    优选地，所述心脏损伤情况选自24小时动态心电图存在异常，更优选地，所述的异常选自易被常规心电图漏诊的隐匿性心律失常；最优选为快速性心律失常、缓慢性心律失常、异位节律、传导阻滞、导致心源性猝死的心律失常、心肌梗死、无症状心肌缺血。
  2. 如权利要求1所述的检测试剂，其特征在于，所述检测试剂包括从血清中提取吲哚-3-乳酸的试剂以及定量检测吲哚-3-乳酸的试剂。
  3. 一种用于评估精神分裂症患者心脏损伤情况的试剂盒，其特征在于，所述试剂盒中包含上述检测试剂；
    优选地，所述心脏损伤情况选自24小时动态心电图存在异常，更优选地，所述的异常选自易被常规心电图漏诊的隐匿性心律失常；最优选为快速性心律失常、缓慢性心律失常、异位节律、传导阻滞、导致心源性猝死的心律失常、心肌梗死、无症状心肌缺血。
  4. 权利要求1所述的检测试剂在制备用于评估精神分裂症患者心脏损伤情况的试剂盒或检测制剂中的用途；
    优选地，所述心脏损伤情况选自24小时动态心电图存在异常，更优选地，所述的异常选自易被常规心电图漏诊的隐匿性心律失常；最优选为快速性心律失常、缓慢性心律失常、异位节律、传导阻滞、导致心源性猝死的心律失常、心肌梗死、无症状心肌缺血。
  5. 一种评估精神分裂症患者心脏损伤情况的标志物，其特征在于，所述标志物选自吲哚-3-乳酸；
    优选地，所述心脏损伤情况选自24小时动态心电图存在异常，更优选地，所述的异常选自易被常规心电图漏诊的隐匿性心律失常；最优选为快速性心律失常、缓慢性心律失常、异位节律、传导阻滞、导致心源性猝死的心律失常、心肌梗死、无症状心肌缺血。
  6. 一种筛选血清代谢产物作为评估精神分裂症患者心脏损伤情况标志物的方法，其特征在于，所述方法包括以下步骤：
    i)以精神分裂症患者作为第一筛选队列，第一筛选队列中包含具有心脏损伤的精神分裂症患者和心脏未损伤的精神分裂症患者；通过代谢组学研究，对具有心脏损伤的筛选队列以 及不具有心脏损伤的筛选队列的血清中的代谢物进行检测和数据分析，筛选获得组间差异代谢物；
    ii)以精神分裂症患者作为第二筛选队列，对第二筛选队列进行24小时动态心电图检测，并根据24小时动态心电图结果划分为无异常组和有异常组；分别检测无异常组和有异常组的血清中的组间差异代谢物的含量或浓度，并进行统计分析，筛选具有统计学差异的组间差异代谢物即为评估精神分裂症患者心脏损伤情况标志物。
  7. 如权利要求6所述的方法，其特征在于，在步骤i)中，具有心脏损伤的精神分裂症患者和心脏未损伤的精神分裂症患者的人数比为1:0.5-1.5；
    在步骤ii)中，无异常组和有异常组的人数比为1:0.5-1.5。
  8. 如权利要求6所述的方法，其特征在于，在步骤i)中，代谢物进行检测的方法为LC-MS方法。
  9. 如权利要求6所述的方法，其特征在于，在步骤i)中，数据分析的方法为SIMCA-P软件进行PCA分析，并在此基础上进行PLS-DA、OPLS-DA的模型构建，从而获得组间差异代谢物。
  10. 评估精神分裂症患者心脏损伤情况的方法，其特征在于，所述方法包括以下步骤：
    1)获得患有精神分裂症的受试者的血清样品，通过提取试剂从血清样品中提取吲哚-3-乳酸，并检测血清中吲哚-3-乳酸的浓度；
    2)通过血清中吲哚-3-乳酸的浓度判断受试者是否患有心脏损伤；
    优选地，检测血清中吲哚-3-乳酸的浓度的方法选自HPLC方法或HPLC与质谱联用的方法；
    优选地，所述血清中吲哚-3-乳酸的浓度高于正常值则认为具有心脏损伤。
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