WO2022144028A1 - 用于评估受试者心血管疾病风险的代谢标志物组合及其应用 - Google Patents

用于评估受试者心血管疾病风险的代谢标志物组合及其应用 Download PDF

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WO2022144028A1
WO2022144028A1 PCT/CN2022/070155 CN2022070155W WO2022144028A1 WO 2022144028 A1 WO2022144028 A1 WO 2022144028A1 CN 2022070155 W CN2022070155 W CN 2022070155W WO 2022144028 A1 WO2022144028 A1 WO 2022144028A1
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cardiovascular
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risk
metabolic
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French (fr)
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贾伟
谢国祥
林志龙
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深圳市绘云生物科技有限公司
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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
    • G01N30/88—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86
    • 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
    • G01N30/88—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86
    • G01N2030/8809—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86 analysis specially adapted for the sample
    • G01N2030/8813—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86 analysis specially adapted for the sample biological materials
    • 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
    • G01N30/88—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86
    • G01N2030/8809—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86 analysis specially adapted for the sample
    • G01N2030/884—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86 analysis specially adapted for the sample organic compounds

Definitions

  • the present invention relates to the field of cardiovascular and cerebrovascular diseases, in particular to a metabolic marker for assessing the risk of cardiovascular and cerebrovascular diseases in subjects and its application.
  • Cardiovascular and cerebrovascular diseases are a general term for cardiovascular and cerebrovascular diseases, which generally refer to ischemic or hemorrhagic diseases of the heart, brain and whole body caused by hyperlipidemia, blood viscosity, atherosclerosis, hypertension, etc. Diseases, including hypertension (increased blood pressure), coronary heart disease (heart attack), cerebrovascular disease (stroke), peripheral vascular disease, heart failure, rheumatic heart disease, congenital heart disease, and cardiomyopathy, among others.
  • Cardiovascular and cerebrovascular diseases have high morbidity and mortality, and the pathogenesis is complex.
  • most of the markers currently used for the diagnosis of cardiovascular and cerebrovascular diseases cannot provide more reference value for clinicians due to lack of sensitivity and specificity. Therefore, finding efficient, sensitive and accurate biomarkers for the diagnosis and/or risk prediction of cardiovascular and cerebrovascular diseases has become an urgent problem to be solved in clinical diagnosis and treatment.
  • the current traditional biomarker detection methods include thin-layer chromatography, liquid chromatography, immunochemical methods, gas chromatography, etc. These traditional methods are difficult to meet the needs of the medical industry, especially the precision medical industry. High standards for range and dynamic range.
  • Existing mass spectrometry-based detection methods for cardiovascular and cerebrovascular disease research mainly use non-targeted relative quantitative or semi-quantitative methods, or absolute quantitative methods for a single type of compound to diagnose or evaluate diseases, resulting in the accuracy of the detection results. There are certain limitations in comprehensiveness, and there is still a certain distance from truly effective clinical mass spectrometry detection and risk assessment.
  • biomarkers Therefore, based on the newly developed biomarkers, it is also of great significance to establish high-standard biomarker detection methods and systems that meet medical standards, especially precision medicine.
  • the present invention provides a combination of metabolic markers for assessing the risk of cardiovascular and cerebrovascular diseases in a subject, and its use in preparing a product for diagnosing cardiovascular and cerebrovascular diseases or evaluating cardiovascular and cerebrovascular drugs, a kit, a quantitative detection method and a computer system It has the advantages of high sensitivity, good specificity, quantification and/or high detection throughput in assessing or predicting the risk of cardiovascular and cerebrovascular diseases.
  • the present invention provides the following technical solutions:
  • the present invention discloses a combination of metabolic markers for assessing the risk of cardiovascular and cerebrovascular diseases in a subject
  • the combination of metabolic markers includes ceramide Cer d18:1/16:0, ceramide Cer d18:1/ 18:0, ceramide Cer d18:1/24:0, phenylacetylglutamine, trimethylamine, betaine and choline
  • the cardiovascular and cerebrovascular diseases are selected from hypertension, coronary heart disease, atherosclerosis, atrial Fibrillation, heart failure, stroke, peripheral vascular disease, heart failure, rheumatic heart disease, congenital heart disease or cardiomyopathy.
  • the combination of metabolic markers further comprises one or more of the following metabolic markers: ceramide Cer d18:1/24:1, ceramide GlcCer d18:1/12:0, three Hexosylceramide d18:1/24:0, sphingosine 1-phosphate, trimethylamine oxide, carnitine and creatinine.
  • the combination of metabolic markers further comprises one or more of the following metabolic markers: aspartic acid, N-acetylalanine, glycine, N-acetylaspartic acid, N -Acetyl threonine, N-acetyl-1-methylhistidine, indole acetic acid, cortisol, citric acid, leucine, isoleucine, valine, pyrimidine, succinic acid, acetyl coenzyme, glutamic acid amino acid, oxaloacetate and alpha-ketoglutarate.
  • the subject is a human.
  • the metabolic markers are obtained by detecting a biological sample of a subject, the biological sample being selected from plasma or serum.
  • the present invention also discloses the use of the aforementioned combination of metabolic markers in the preparation of a product for diagnosing cardiovascular and cerebrovascular diseases or evaluating cardiovascular and cerebrovascular drugs, wherein the product uses the expression level of the aforementioned combination of metabolic markers as an evaluation index .
  • the product is selected from the group consisting of kits, diagnostic devices and computer systems.
  • the present invention also discloses a kit for detecting the aforementioned combination of metabolic markers, the kit includes a standard substance of metabolic markers and a metabolic marker extractant, and the metabolic marker extractant is selected from organic The mixture of solvent and water, the organic solvent is selected from one or more of isopropanol, methanol and acetonitrile.
  • the present invention also discloses a method for quantitative detection of the aforementioned combination of metabolic markers, the method comprising: after processing a biological sample of a subject, using liquid chromatography tandem mass spectrometry (LC-MS/MS) ) method to quantitatively detect the combination of metabolic markers in biological samples.
  • LC-MS/MS liquid chromatography tandem mass spectrometry
  • the liquid chromatography includes high performance liquid chromatography (HPLC), ultra-high performance liquid chromatography (UPLC), and nanoliter liquid chromatography (Nano-LC), and the tandem mass spectrometry includes a quadrupole Mass spectrometry (Quadrupole, Q), time of flight mass spectrometry (Time of Flight, TOF), ion hydrazine mass spectrometry (Ion Trap) and high-resolution orbital hydrazine mass spectrometry (Orbitrap).
  • HPLC high performance liquid chromatography
  • UPLC ultra-high performance liquid chromatography
  • Nano-LC nanoliter liquid chromatography
  • the tandem mass spectrometry includes a quadrupole Mass spectrometry (Quadrupole, Q), time of flight mass spectrometry (Time of Flight, TOF), ion hydrazine mass spectrometry (Ion Trap) and high-resolution orbital hydrazine mass spectrometry (Orbitrap).
  • the separation conditions of the liquid chromatography include: mobile phase A is a methanol solution containing additives, the additives are selected from any one of ammonium formate, ammonium acetate, and trichloroacetic acid, and mobile phase B is selected from One or a combination of isopropanol, methanol, acetonitrile, ethanol, and propylene glycol; the chromatographic column is selected from C8 and C18 silica gel packing columns, the column temperature is set to 25-45 ° C, and the flow rate is 0.2-0.6 ml/min;
  • the detection conditions of the mass spectrometry include: using triple quadrupole mass spectrometry multiple reaction monitoring (MRM) mode for data acquisition, selecting characteristic transition information of metabolic markers, and using standard products for information confirmation and detection method establishment, and internal standards are used at the same time. Quantitative calibration was carried out on the product to obtain the precise concentration value and related ratio value of each metabolic marker in the biological sample.
  • MRM triple quadrupole mass
  • the separation conditions of the liquid chromatography may include: injection of 5 microliters, mobile phase A is 60% methanol + 10 mmol ammonium formate, mobile phase B is 90% isopropanol + 10% methanol + 10 mmol ammonium formate, the column is a 100 mmol C18 column, the column temperature is set to 40 °C, the flow rate is 0.3 mL/min, 0-0.5 min to maintain 50% B, 0.5-1.8 min to switch from 50% B B linear to 75% B, 1.8-3.0 minutes linear from 75% B to 80% B, 3.0-3.4 minutes linear from 80% B to 98% B, 3.4-4.3 minutes to maintain 98% B, 4.3-4.5 The minute changes linearly from 98%B to 50%B, and maintains 50%B for 4.5-6 minutes;
  • the mass spectrometry is selected from quadrupole mass spectrometry, time-of-flight mass spectrometry, ion hydrazine mass spectrometry and high-resolution orbital hydrazine mass spectrometry;
  • the conditions of the mass spectrometry and the setting of the mass spectrometry qualitative and quantitative detection mode include: selecting electrospray The ion source (ESI) selects the ion scanning mode according to the response of the detected target compound; the triple quadrupole mass spectrometry multiple reaction monitoring (MRM) mode is used for data acquisition, the characteristic transition information of the metabolic markers is selected, and the standard substance is used for the information Confirmation and detection methods were established, and internal standards were used for quantitative correction to obtain the precise concentration values and related ratio values of each metabolic marker in the biological sample.
  • ESI electrospray The ion source
  • MRM multiple reaction monitoring
  • processing the biological sample includes adding the biological sample to a precipitating agent selected from a mixed solvent of isopropanol and methanol; in some specific embodiments, the precipitating agent It is a mixed solvent of isopropanol and methanol; its volume ratio can be 1:1-1:10, and as a preferred method, the volume ratio can be 1:3-1:5.
  • a precipitating agent selected from a mixed solvent of isopropanol and methanol
  • the precipitating agent It is a mixed solvent of isopropanol and methanol; its volume ratio can be 1:1-1:10, and as a preferred method, the volume ratio can be 1:3-1:5.
  • the present invention also discloses a computer system for assessing the risk of cardiovascular and cerebrovascular diseases in a subject, the system comprising an information acquisition module and a cardiovascular and cerebrovascular disease risk assessment module;
  • the information acquisition module is at least configured to perform the following operations: acquire detection information of a combination of metabolic markers in the subject sample, where the combination of metabolic markers is selected from the aforementioned combination of metabolic markers;
  • the cardiovascular and cerebrovascular disease risk assessment module is at least configured to perform the following operations: according to the metabolic marker group level obtained by the information acquisition module, evaluate whether the subject suffers from cardiovascular and cerebrovascular disease or has a cardiovascular and cerebrovascular disease.
  • Risk of disease the cardiovascular and cerebrovascular diseases are selected from hypertension, coronary heart disease, atherosclerosis, atrial fibrillation, heart failure, stroke, peripheral vascular disease, heart failure, rheumatic heart disease, congenital heart disease and cardiomyopathy .
  • the cardiovascular and cerebrovascular disease risk assessment module is at least configured to perform the following operations: input the level of the metabolic marker group acquired by the information acquisition module into a diagnostic model, and evaluate the subject according to the diagnostic model Whether the patient has cardiovascular and cerebrovascular disease or is at risk of cardiovascular and cerebrovascular disease.
  • the diagnostic model is as follows:
  • the C1 is the concentration value obtained when the ceramide Cer d18:1/16:0 in the sample is expressed in ⁇ M concentration units
  • the C2 is the ceramide Cer d18:1/18:0 in the sample in ⁇ M
  • the concentration value taken when the concentration unit is expressed the C3 is the concentration value taken when the ceramide Cer d18:1/24:0 in the sample is expressed in ⁇ M concentration unit
  • the C4 is the phenylacetylglutamine in the sample
  • the C5 is the concentration value taken when the trimethylamine in the sample is expressed in ⁇ M concentration unit
  • the C6 is the concentration value of betaine in the sample expressed in ⁇ M concentration unit
  • the concentration value taken, the C7 is the concentration value taken when the choline in the sample is expressed in the concentration unit of ⁇ M;
  • the subject is assessed to have the cardiovascular and cerebrovascular disease or to have the risk of cardiovascular and cerebrovascular disease, wherein
  • the threshold is selected from 0.4-0.5, preferably 0.4243, it is predicted that the subject has a risk of coronary heart disease
  • the threshold is selected from 1.0-1.2, preferably 1.019, it is predicted that the subject has a risk of heart failure
  • the threshold is selected from 1.4-1.42, preferably 1.412, it is predicted that the subject has a risk of atrial fibrillation
  • the threshold is selected from 0.3-0.31, preferably 0.303, when the subject is predicted to be at risk of atherosclerosis.
  • the system further includes a sample detection module for at least performing the operation of detecting the level of the marker in the sample.
  • the system is used at least to perform liquid chromatography tandem mass spectrometry (LC-MS/MS) operations for the detection of biomarkers;
  • the liquid chromatography may be selected from high performance liquid chromatography (HPLC) ), ultra-high performance liquid chromatography (UPLC) and nano-liter liquid chromatography (Nano-LC),
  • the tandem mass spectrometry can be selected from quadrupole mass spectrometry (Quadrupole, Q), time of flight mass spectrometry (Time of Flight, TOF), Ion Trap and high-resolution orbital hydrazine mass spectrometry (Orbitrap).
  • the separation conditions of the liquid chromatography include: mobile phase A is a methanol solution containing additives, the additives are selected from any one of ammonium formate, ammonium acetate and trichloroacetic acid, and mobile phase B is selected from One or a combination of isopropanol, methanol, acetonitrile, ethanol and propylene glycol; the chromatographic column is selected from C8 and C18 silica gel packing columns, the column temperature is set to 25-45 ° C, and the flow rate is 0.2-0.6 ml/min;
  • the detection conditions of the mass spectrometry include: using triple quadrupole mass spectrometry multiple reaction monitoring (MRM) mode for data acquisition, selecting characteristic transition information of metabolic markers, and using standard products for information confirmation and detection method establishment, and internal standards are used at the same time. Quantitative calibration was carried out on the product to obtain the precise concentration value and related ratio value of each metabolic marker in the biological sample.
  • MRM triple quadrupole mass spectrome
  • the separation conditions of the liquid chromatography may include: injection of 5 microliters, mobile phase A is 60% methanol + 10 mmol ammonium formate, mobile phase B is 90% isopropanol + 10% methanol + 10 mmol ammonium formate, the column is a 100 mmol C18 column, the column temperature is set to 40 °C, the flow rate is 0.3 mL/min, 0-0.5 minutes to maintain 50% B, 0.5-1.8 minutes from 50% B linear to 75% B, 1.8-3.0 minutes linear from 75% B to 80% B, 3.0-3.4 minutes linear from 80% B to 98% B, 3.4-4.3 minutes to maintain 98% B, 4.3-4.5 The minute changes linearly from 98%B to 50%B, and maintains 50%B for 4.5-6 minutes;
  • the mass spectrometry is selected from quadrupole mass spectrometry, time-of-flight mass spectrometry, ion hydrazine mass spectrometry and high-resolution orbital hydrazine mass spectrometry;
  • the conditions of the mass spectrometry and the setting of the mass spectrometry qualitative and quantitative detection mode include: selecting electrospray The ion source (ESI) selects the ion scanning mode according to the response of the detected target compound; the triple quadrupole mass spectrometry multiple reaction monitoring (MRM) mode is used for data acquisition, the characteristic transition information of the metabolic markers is selected, and the standard substance is used for the information Confirmation and detection methods were established, and internal standards were used for quantitative correction to obtain the precise concentration values and related ratio values of each metabolic marker in the biological sample.
  • ESI electrospray The ion source
  • MRM multiple reaction monitoring
  • the system further includes a sample pre-processing module, the sample pre-processing module is at least used to perform the operations of protein precipitation and marker group extraction; the operations include processing the subject sample with Isopropanol and methanol mixed solvent is used for extraction, and after centrifugation, the supernatant is taken for detection, and the volume ratio can be 1:1-1:10.
  • the present invention finds and verifies 32 differential metabolites relative to normal subjects for the first time in samples of subjects with cardiovascular and cerebrovascular diseases, of which 7 differential metabolites are particularly important. Based on the above findings, the present invention provides a brand-new combination of metabolic markers and its application, and establishes a quantitative detection method and computer evaluation system for the corresponding combination of metabolite markers, which is helpful for improving the sensitivity and specificity of the diagnosis of cardiovascular and cerebrovascular diseases.
  • the present invention establishes a prediction model based on 7 particularly important differential metabolites of cardiovascular and cerebrovascular diseases.
  • the AUC 0.897
  • the sensitivity is 85.0%
  • the specificity is 89.4% , with an accuracy of 86.7%.
  • the computer system of the present invention has the advantages of high sensitivity, specificity and good accuracy when using the model to evaluate the risk of cardiovascular and cerebrovascular diseases of the subject.
  • the differential metabolites and prediction models found in the present invention can also be used for risk assessment of cardiovascular diseases such as heart failure, atrial fibrillation and atherosclerosis in subjects.
  • the present invention uses high performance liquid chromatography tandem mass spectrometry to detect the level of markers in the sample, and further optimizes the detection conditions, realizing the simultaneous targeted quantitative detection of multiple biomarkers, solving the problem of
  • the detection specificity, accuracy and diversity of cardiovascular and cerebrovascular disease markers also have the advantages of small sample detection volume and high throughput.
  • FIG. 1 is a representative ion chromatogram of liquid chromatography mass spectrometry of the metabolic markers of the present invention in blood.
  • Figure 3 is a calibration curve for the ceramide molecule Cer d18:1/18:0 in 5% BSA.
  • Figure 4 is a calibration curve for phenylacetylglutamine in 5% BSA.
  • Figure 5 is a calibration curve for the ceramide molecule Cer d18:1/24:0 in 5% BSA.
  • Figure 6 is a calibration curve for the ceramide molecule Cer d18:1/24:1 in 5% BSA.
  • Figure 7 is a calibration curve for L-carnitine in 5% BSA.
  • Figure 8 is a calibration curve for trihexosylceramide in 5% BSA.
  • Figure 9 is a calibration curve for trimethylamine oxide in 5% BSA.
  • Figure 10 is a calibration curve for creatinine in 5% BSA.
  • Figure 11 is a calibration curve for trimethylamine in 5% BSA.
  • Figure 12 is a calibration curve for betaine in 5% BSA.
  • Figure 13 is a calibration curve for choline in 5% BSA.
  • Figure 14 is an operating characteristic curve (ROC) of 147 patients with coronary heart disease and 94 control samples.
  • Figure 15 is the operating characteristic curve (ROC) of 919 patients with coronary heart disease and 116 control samples.
  • Figure 16 is a receiver operating characteristic (ROC) curve for heart failure patients and controls.
  • Figure 17 is a receiver operating characteristic (ROC) curve for atrial fibrillation patients and controls.
  • Figure 18 is a receiver operating characteristic (ROC) curve for atherosclerotic patients and controls.
  • the markers to be tested were dissolved in a 9:1 solvent of isopropanol:acetonitrile into 0.1 mM stock solutions, respectively. It was then further diluted with 50 mg/mL bovine serum albumin (BSA, Aladdin) solution to make a mixed calibrator (standard) curve working solution.
  • BSA bovine serum albumin
  • Ceramide Cer d18:1/16:0, Ceramide Cer d18:1/18:0, Ceramide GlcCer d18:1/12:0, and 1-phosphate sheath can be added to the mixed calibrator working solution Amino alcohol, its concentration points are 2 ⁇ M, 1 ⁇ M, 0.4 ⁇ M, 0.2 ⁇ M, 0.08 ⁇ M and 0.04 ⁇ M; Ceramide Cerd18:1/24:0, Ceramide Cerd18:1 can also be added to the mixed calibrator working solution /24:1, trihexosylceramide d18:1/24:), and phenylacetylglutamine at each concentration point of 10 ⁇ M, 5 ⁇ M, 2 ⁇ M, 1 ⁇ M, 0.4 ⁇ M ⁇ M, and 0.2 ⁇ M; also in mixed calibrators Trimethylamine oxide, trimethylamine, choline, L-carnitine, betaine, and creatinine were added to the working solution at concentrations of 100 ⁇ M, 50 ⁇ M, 20
  • the internal calibrator ceramide molecule Cerd18:1/17:0, deuterated trimethylamine oxide and deuterated tryptophan were dissolved into 0.1mM stock solutions, respectively, and then diluted to 300nM with isopropanol:methanol 8:2 solvent The mixed internal standard working solution.
  • a total of 518 plasma samples, calibrator (standard) curve working solution and quality control substance were taken 10 microliters into the V-bottom 96-well plate, and then 190 microliters of internal calibrator working solution was added, and the aluminum seal was attached.
  • Membranes were shaken at 650 rpm for 20 minutes. Then centrifuge at 4000 ⁇ g for 20 minutes, and take 100 microliters of supernatant for high performance liquid chromatography-mass spectrometry detection.
  • the separation conditions and parameters of liquid chromatography are as follows: inject 5 microliters, mobile phase A is 60% methanol + 10 mM ammonium formate, mobile phase B is 90% isopropanol + 10% methanol + 10 mM ammonium formate, chromatographic column is 100 mM A C18 reversed-phase column (Waters Acquity BEH C18), the column temperature was set to 40 °C, and the flow rate was 0.3 mL/min.
  • the detection parameters of mass spectrometry are mainly: using triple quadrupole mass spectrometry multiple reaction monitoring (MRM) mode for data acquisition, and the ion spectrum is shown in FIG. 1 .
  • MRM triple quadrupole mass spectrometry multiple reaction monitoring
  • a calibration standard curve for each metabolic marker is established, as shown in Figure 2- Figure 13, where the abscissa represents the concentration ( ⁇ M) of the corresponding detection substance, and the ordinate represents the peak area of the mass spectrum signal.
  • the calibration standard curve obtained in this embodiment can be used to query the concentration of the corresponding substance to be tested in the serum sample of the subject.
  • the coronary heart disease samples and healthy control samples of the test items were mixed into QC samples in equal amounts, and then tested together with the standard, and the quantitative recovery test of standard curve linearity, quantitative LOQ, spiked and non-spiked comparisons was performed.
  • the target QC samples are interspersed in the project samples for quantitative repeatability testing at intervals to ensure that the detection of the samples meets the quality control.
  • Table 1 shows the relevant results of some metabolites.
  • variable weight VIP value VIP>1
  • P value P ⁇ 0.05
  • Control 32 differential metabolites including: Ceramide Cer d18:1/16:0, Ceramide Cer d18:1/18:0, Ceramide Cer d18:1/24:0, Ceramide Cer d18:1 /24:1, Ceramide GlcCer d18:1/12:0, Trihexosylceramide d18:1/24:0, Sphingosine 1-Phosphate, Phenylacetylglutamine, Trimethylamine Oxide, Trimethylamine, Choline , L-carnitine, betaine, creatinine, aspartic acid, N-acetylalanine, glycine, N-acetylaspartic acid, N-acetylthreonine, N-acetyl-1-methylhistidine acid, indoleacetic acid, cortisol, citric acid, leucine, isoleucine, valine, pyrimidine, succinic acid, acetyl coenzyme, glutamic acid, ox
  • the logistic regression model was used to verify that 7 metabolites (respectively: ceramide molecule Cer d18:1/16:0, ceramide molecule Cer d18:1/18:0, ceramide molecule Cer d18:1/ 24:0, phenylacetylglutamine, trimethylamine, betaine, choline) as a marker of coronary heart disease is particularly important.
  • the markers were then evaluated in coronary heart disease plasma/serum samples using a clinical diagnostic performance curve (ROC curve).
  • Model score P C1*0.9414+C2*5.6311+C3*0.5817+C4*0.09151–C5*0.03620+C6*0.05425+C7*0.02096+2.2141.
  • the C1 is the concentration value obtained when the ceramide Cer d18:1/16:0 in the sample is expressed in ⁇ M concentration units; if the concentration value is expressed in mM, it needs to be converted to ⁇ M first, and then take its concentration value As can be brought into the model, for example, if the detection concentration of ceramide Cer d18:1/16:0 in the sample is 0.02mM, it needs to be converted into 20 ⁇ M, and 20 is taken as the C1 value and brought into the model for calculation, The following C2-C7 are handled in the same way;
  • the optimal diagnostic threshold value of 0.4243 was obtained by receiver operating characteristic (ROC) curve analysis (see Figure 14 in the specification). Subsequently, the concentration value of each sample is detected by the diagnostic marker, and then the score value is calculated according to the diagnostic model, and whether the subject has the disease or has the risk of disease is evaluated by comparison with the diagnostic threshold.
  • ROC receiver operating characteristic
  • the established marker diagnostic model was applied to another 147 patients with coronary heart disease and 94 control samples, the score value of each sample was calculated, and the verified diagnostic specificity, sensitivity, and accuracy were calculated, as shown in Table 2 below. , the results show that the prediction model has better prediction results of coronary heart disease.
  • AUC 0.871
  • the sensitivity was 85.0%
  • the specificity was 89.4%
  • the accuracy was 86.7% (Table 2).
  • the established marker diagnostic model was applied to another 919 patients with coronary heart disease and 116 control samples, the score value of each sample was calculated, and then the verified diagnostic specificity, sensitivity, and accuracy were calculated, as shown in Table 3 below.
  • the results show that the prediction model has better prediction results of coronary heart disease.
  • AUC 0.959 (Fig. 15)
  • the sensitivity was 97.8%
  • the specificity was 91.4%
  • the accuracy was 97.2% (Table 3).
  • the established marker diagnosis model was applied to 134 patients with atrial fibrillation and 111 control samples, the score value of each sample was calculated, and then the diagnostic specificity, sensitivity and accuracy were obtained by statistics. Good atrial fibrillation predictor outcome.
  • AUC 0.836
  • the sensitivity was 82.8%
  • the specificity was 82.9%
  • the accuracy was 82.9
  • the threshold was 1.412, see Table 5 and Figure 17.
  • Embodiment 11 Validation of marker diagnostic model
  • the established marker diagnostic model was applied to 123 atherosclerotic patients and 98 control samples, the score value of each sample was calculated, and the verified diagnostic specificity, sensitivity and accuracy were calculated, and the results showed that the predictive model was Has a good predictor of atherosclerosis.
  • AUC 0.838
  • the sensitivity was 81.3%
  • the specificity was 79.6%
  • the accuracy was 80.5%
  • the threshold was 0.303, see Table 6 and Figure 18.
  • Example 12 Establishment of a computer system for detecting cardiovascular and cerebrovascular diseases
  • this example establishes a computer system for assessing the risk of cardiovascular and cerebrovascular diseases in a subject, including an information acquisition module, a cardiovascular and cerebrovascular disease risk assessment module, a sample detection module and a sample preprocessing module.
  • the information acquisition module is at least configured to perform the following operations: acquire detection information of a combination of metabolic markers in the sample of the subject, where the combination of metabolic markers is selected from the aforementioned combination of metabolic markers.
  • the cardiovascular and cerebrovascular disease risk assessment module is at least configured to perform the following operations: according to the metabolic marker group level obtained by the information acquisition module, evaluate whether the subject suffers from cardiovascular and cerebrovascular disease or has a cardiovascular and cerebrovascular disease.
  • Risk of disease the cardiovascular and cerebrovascular diseases are selected from hypertension, coronary heart disease, atherosclerosis, atrial fibrillation, heart failure, stroke, peripheral vascular disease, heart failure, rheumatic heart disease, congenital heart disease or cardiomyopathy Specifically comprising inputting the level of the metabolic marker group obtained by the information acquisition module into a diagnostic model, and evaluating whether the experimenter suffers from cardiovascular and cerebrovascular diseases or has a risk of cardiovascular and cerebrovascular diseases according to the diagnostic model; the described The diagnostic model looks like this:
  • the C1 is the concentration value obtained when the ceramide Cer d18:1/16:0 in the sample is expressed in ⁇ M concentration units
  • the C2 is the ceramide Cer d18:1/18:0 in the sample in ⁇ M
  • the concentration value taken when the concentration unit is expressed the C3 is the concentration value taken when the ceramide Cer d18:1/24:0 in the sample is expressed in ⁇ M concentration unit
  • the C4 is the phenylacetylglutamine in the sample
  • the C5 is the concentration value taken when the trimethylamine in the sample is expressed in ⁇ M concentration unit
  • the C6 is the concentration value of betaine in the sample expressed in ⁇ M concentration unit.
  • the concentration value taken, the C7 is the concentration value taken when the choline in the sample is expressed in the concentration unit of ⁇ M;
  • the subject is assessed to have the cardiovascular and cerebrovascular disease or to have a risk of cardiovascular and cerebrovascular disease, wherein:
  • the threshold is selected from 0.4-0.5, preferably 0.4243, it is predicted that the subject has a risk of coronary heart disease
  • the threshold is selected from 1.0-1.2, preferably 1.019, it is predicted that the subject has a risk of heart failure
  • the threshold is selected from 1.4-1.42, preferably 1.412, it is predicted that the subject has a risk of atrial fibrillation
  • the threshold is selected from 0.3-0.31, preferably 0.303, when the subject is predicted to be at risk of atherosclerosis.
  • the sample detection module is at least used for performing the operation of detecting the level of the marker in the sample; specifically, it includes at least performing the operation of liquid chromatography tandem mass spectrometry (LC-MS/MS) for detecting the biomarker;
  • the liquid chromatography can be selected from high performance liquid chromatography (HPLC), ultra-high performance liquid chromatography (UPLC) and nanoliter liquid chromatography (Nano-LC), and the tandem mass spectrometry can be selected from quadrupole mass spectrometry (Quadrupole, Q) , Time of Flight (TOF), Ion Trap and high-resolution orbital hydrazine (Orbitrap);
  • the separation conditions of the liquid chromatography include: injection of 5 microliters, mobile phase A is 60% methanol + 10 mmol ammonium formate, mobile phase B is 90% isopropanol + 10% methanol + 10 mmol ammonium formate,
  • the column was a 100 mmol C18 column, the column temperature was set to 40 °C, the flow rate was 0.3 mL/min, 50% B was maintained for 0-0.5 minutes, and 0.5-1.8 minutes were linearly changed from 50% B to 75% B, 1.8- 3.0 minutes linear change from 75%B to 80%B, 3.0-3.4 minutes linear change from 80%B to 98%B, 3.4-4.3 minutes maintain 98%B, 4.3-4.5 minutes linear change from 98%B to 50%B B, 4.5-6 minutes to maintain 50% B;
  • the detection conditions of the mass spectrometry include: using triple quadrupole mass spectrometry multiple reaction monitoring (MRM) mode for data acquisition, selecting characteristic transition information of metabolic markers, and using standard substances to confirm information and establish a detection method, and use internal
  • MRM multiple reaction monitoring
  • the standard is quantitatively calibrated to obtain the precise concentration value and related ratio value of each metabolic marker in the biological sample.
  • Described sample pretreatment module described sample pretreatment module is at least used for performing the operation of protein precipitation and marker group extraction; Described operation includes to described experimenter sample with isopropanol: methanol is extracted, after centrifugation, take The supernatant was used for detection.

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Abstract

本发明公开一种用于评估受试者心脑血管疾病风险的代谢标志物组合，包括神经酰胺Cer d18:1/16:0、神经酰胺Cer d18:1/18：0、神经酰胺Cer d18:1/24：0、苯乙酰谷氨酰胺、三甲胺、甜菜碱和胆碱；所述心脑血管疾病选自冠心病、动脉粥样硬化、房颤、心衰。本发明代谢标志物组合在评估或预测心脑血管疾病患病风险方面具有灵敏度高、特异性好、可定量和检测通量高等优点。

Description

用于评估受试者心血管疾病风险的代谢标志物组合及其应用
本申请要求申请日为2021年1月4日的中国专利申请CN2021100006559的优先权。本申请引用上述中国专利申请的全文。
技术领域
本发明涉及心脑血管领域，具体涉及一种用于评估受试者心脑血管疾病风险的代谢标志物及其应用。
背景技术
心脑血管疾病是心脏血管和脑血管疾病的统称，泛指由于高脂血症、血液黏稠、动脉粥样硬化、高血压等所导致的心脏、大脑及全身组织发生的缺血性或出血性疾病，包括高血压(血压升高)、冠心病(心脏病发作)、脑血管疾病(中风)、周围血管疾病、心力衰竭、风湿性心脏病、先天性心脏病和心肌病等。
心脑血管疾病发病率和死亡率高，发病机制复杂。而目前用于心脑血管疾病诊断的标志物，大多由于缺乏灵敏度和特异性而不能为临床医生提供更多的参考价值。因此，寻找高效、灵敏、准确的生物标志物，用于心脑血管疾病的诊断和/或患病风险的预测，成为临床诊断和治疗亟需解决的问题。
同时，目前传统的生物标志物检测方法有薄层色谱法、液相色谱法、免疫化学方法、气相色谱法等，这些传统方法难以满足医疗行业，尤其是精准医疗行业对特异性、精准性、适用范围和动态范围的高标准。现有基于质谱技术的心脑血管疾病研究检测方法主要以非靶向相对定量或半定量的方式，或者以单一类型化合物的绝对定量方式进行疾病诊断或评估检测，导致其检测结果的准确性和全面性存在一定的局限性，离真正有效的临床质谱检测和风险评估还有一定距离。
因此，基于新开发的生物标志物，建立满足医疗尤其是精准医疗的高标准生物标志物检测方法及系统，同样具有重要意义。
发明内容
本发明提供用于评估受试者心脑血管疾病风险的代谢标志物组合、及其在制备诊断心脑血管疾病或评价心脑血管药物的产品中的用途、试剂盒、定量检测方法和计算机系统，在评估或预测心脑血管疾病患病风险方面具有灵敏度高、特异性好、可定量和/或检测通量高等优点。
为实现上述发明目的，本发明特提供以下技术方案：
在第一方面，本发明公开用于评估受试者心脑血管疾病风险的代谢标志物组合，所述代谢标志物组合包括神经酰胺Cer d18:1/16:0、神经酰胺Cer d18:1/18：0、神经酰胺Cer d18:1/24：0、苯乙酰谷氨酰胺、三甲胺、甜菜碱和胆碱；所述心脑血管疾病选自高血压、冠心病、动脉粥样硬化、房颤、心衰、中风、周围血管疾病、心力衰竭、风湿性心脏病、先天性心脏病或心肌病。
在一些具体的实施方式中，所述代谢标志物组合还包括以下代谢标志物的一种或多种：神经酰胺Cer d18:1/24:1、神经酰胺GlcCer d18:1/12:0、三已糖神经酰胺d18:1/24:0、1-磷酸鞘氨醇、氧化三甲胺、肉碱和肌酸酐。
在一些具体的实施方式中，所述代谢标志物组合还包括以下代谢标志物的一种或多种：天冬氨酸、N-乙酰丙氨酸、甘氨酸、N-乙酰天冬氨酸、N-乙酰苏氨酸、N-乙酰-1-甲基组氨酸、吲哚乙酸、皮质醇、柠檬酸、亮氨酸、异亮氨酸、缬氨酸、嘧啶、琥珀酸、乙酰辅酶、谷氨酸、草酰乙酸和α-酮戊二酸。
在一些具体的实施方式中，所述受试者为人类。
在一些具体的实施方式中，所述代谢标志物通过检测受试者的生物样本而获得，所述生物样本选自血浆或血清。
在第二方面，本发明还公开前述的代谢标志物组合在制备诊断心脑血管疾病或评价心脑血管药物的产品中的用途，所述产品以前述的代谢标志物组合的表达水平作为评估指标。
在一些具体的实施方式中，所述产品选自试剂盒、诊断装置和计算机系统。
在第三方面，本发明还公开一种检测前述的代谢标志物组合的试剂盒，所述试剂盒包括代谢标志物的标准品和代谢标志物提取剂，所述代谢标志物提取剂选自有机溶剂和水的混合物，有机溶剂选自异丙醇、甲醇和乙腈中的一种或多种。
在第四方面，本发明还公开一种前述代谢标志物组合的定量检测方法，所述方法包括对受试者的生物样本进行处理后，以液相色谱串联质谱联用(LC-MS/MS)方法对生物样本中的代谢标志物组合进行定量检测。
在一些具体的实施方式中，所述液相色谱包括高效液相色谱(HPLC)、超高效液相色谱(UPLC)和纳升液相色谱(Nano-LC)，所述串联质谱包括四级杆质谱(Quadrupole,Q)、飞行时间质谱(Time of Flight,TOF)、离子肼质谱(Ion Trap)和高分辨轨道肼质谱(Orbitrap)。
在一些具体的实施方式中，所述液相色谱的分离条件包括：流动相A为含添加剂的甲醇溶液，添加剂选自甲酸铵、乙酸铵、三氯乙酸中任一种，流动相B选自异丙醇、甲醇、 乙腈、乙醇、丙二醇中一种或几种的组合；色谱柱选自C8和C18硅胶填料柱，柱温设置为25-45℃，流速为0.2-0.6毫升/分；所述质谱的检测条件包括：采用三重四级杆质谱多反应监测(MRM)模式进行数据采集，选择代谢标志物的特征离子对信息，并采用标准品进行信息确认和检测方法建立，同时采用内标准品进行定量校正，得到生物样本中各代谢标志物的精准浓度值及相关比例值。
作为示例性的具体的实施方式，所述液相色谱的分离条件可包括：进样5微升，流动相A为60％甲醇+10毫摩尔甲酸铵，流动相B为90％异丙醇+10％甲醇+10毫摩尔甲酸铵，色谱柱为100毫摩尔的C18柱，柱温设置为40℃，流速为0.3mL/分钟，0-0.5分钟维持50％B，0.5-1.8分钟从50％B线性变化至75％B，1.8-3.0分钟从75％B线性变化至80％B，3.0-3.4分钟从80％B线性变化至98％B，3.4-4.3分钟维持98％B，4.3-4.5分钟从98％B线性变化至50％B，4.5-6分钟维持50％B；
在一些具体的实施方式中，所述质谱选自四级杆质谱、飞行时间质谱、离子肼质谱和高分辨轨道肼质谱；所述质谱的条件和设定质谱定性定量检测模式包括：选择电喷离子源(ESI)，根据检测目标化合物的响应选择离子扫描模式；采用三重四级杆质谱多反应监测(MRM)模式进行数据采集，选择代谢标志物的特征离子对信息，并采用标准品进行信息确认和检测方法建立，同时采用内标准品进行定量校正，得到生物样本中各代谢标志物的精准浓度值及相关比例值。
在一些具体的实施方式中，对生物样本进行处理，包括将生物样本加到沉淀剂中，所述沉淀剂选自异丙醇和甲醇的混合溶剂；在一些具体的实施方式中，所述沉淀剂为异丙醇和甲醇的混合溶剂；其体积比可以为1：1-1：10，作为优选方式，体积比可以为1：3-1：5。
在第五方面，本发明还公开一种用于评估受试者心脑血管疾病风险的计算机系统，所述系统包括信息获取模块和心脑血管疾病风险评估模块；
其中，所述信息获取模块至少用于执行以下操作：获取受试者样品中的代谢标志物组合检测信息，所述代谢标志物组合选自前所述的代谢标志物组合；
所述心脑血管疾病风险评估模块至少用于执行以下操作：根据所述信息获取模块获取的代谢标志物组水平，评估所述受试者是否患有心脑血管疾病或具有心脑血管疾病的患病风险；所述心脑血管疾病选自高血压、冠心病、动脉粥样硬化、房颤、心衰、中风、周围血管疾病、心力衰竭、风湿性心脏病、先天性心脏病和心肌病。
在一些具体的实施方式中，所述心脑血管疾病风险评估模块至少用于执行以下操作：将所述信息获取模块获取的代谢标志物组的水平输入诊断模型，根据诊断模型评估所述受试者是否患有心脑血管疾病或具有心脑血管疾病的患病风险。
在一些具体的实施方式中，所述诊断模型如下所示：
P＝C1*0.9414+C2*5.6311+C3*0.5817+C4*0.09151–C5*0.03620+C6*0.05425+C7*0.02096+2.2141；
其中，所述C1为样品中神经酰胺Cer d18:1/16:0按μM的浓度单位表示时所取的浓度值，所述C2为样品中神经酰胺Cer d18:1/18：0按μM的浓度单位表示时所取的浓度值，所述C3为样品中神经酰胺Cer d18:1/24：0按μM的浓度单位表示时所取的浓度值，所述C4为样本中苯乙酰谷氨酰胺按μM的浓度单位表示时所取的浓度值，所述C5为样本中三甲胺按μM的浓度单位表示时所取的浓度值，所述C6为样本中甜菜碱按μM的浓度单位表示时所取的浓度值，所述C7为样本中胆碱按μM的浓度单位表示时所取的浓度值；
如果所述受试者的P值在一定的阈值范围，则评估所述受试者患有所述心脑血管疾病或者具有心脑血管疾病患病风险，其中
所述阈值选自0.4-0.5，优选0.4243时，预测所述受试者具有冠心病风险；
所述阈值选自1.0-1.2，优选1.019时，预测所述受试者具有心衰风险；
所述阈值选自1.4-1.42，优选1.412时，预测所述受试者具有房颤风险；
所述阈值选自0.3-0.31，优选0.303时，预测所述受试者具有动脉粥样硬化风险。
在一些具体的实施方式中，所述系统还包括样品检测模块，至少用于执行检测样品中所述标志物水平的操作。
在一些具体的实施方式中，所述系统至少用于执行检测生物标志物的液相色谱串联质谱联用(LC-MS/MS)操作；所述液相色谱可选自高效液相色谱(HPLC)、超高效液相色谱(UPLC)和纳升液相色谱(Nano-LC)，所述串联质谱可选自四级杆质谱(Quadrupole,Q)、飞行时间质谱(Time of Flight,TOF)、离子肼质谱(Ion Trap)和高分辨轨道肼质谱(Orbitrap)。
在一些具体的实施方式中，所述液相色谱的分离条件包括：流动相A为含添加剂的甲醇溶液，添加剂选自甲酸铵、乙酸铵和三氯乙酸中任一种，流动相B选自异丙醇、甲醇、乙腈、乙醇和丙二醇中一种或几种的组合；色谱柱选自C8和C18硅胶填料柱，柱温设置为25-45℃，流速为0.2-0.6毫升/分；所述质谱的检测条件包括：采用三重四级杆质谱多反应监测(MRM)模式进行数据采集，选择代谢标志物的特征离子对信息，并采用标准品进行信息确认和检测方法建立，同时采用内标准品进行定量校正，得到生物样本中各代谢标志物的精准浓度值及相关比例值。
作为示例性的具体的实施方式，所述液相色谱的分离条件可包括：进样5微升，流动相A为60％甲醇+10毫摩尔甲酸铵，流动相B为90％异丙醇+10％甲醇+10毫摩尔甲酸铵，色谱柱为100毫摩尔的C18柱，柱温设置为40℃，流速为0.3mL/分钟，0-0.5分钟维持50％B， 0.5-1.8分钟从50％B线性变化至75％B，1.8-3.0分钟从75％B线性变化至80％B，3.0-3.4分钟从80％B线性变化至98％B，3.4-4.3分钟维持98％B，4.3-4.5分钟从98％B线性变化至50％B，4.5-6分钟维持50％B；
在一些具体的实施方式中，所述质谱选自四级杆质谱、飞行时间质谱、离子肼质谱和高分辨轨道肼质谱；所述质谱的条件和设定质谱定性定量检测模式包括：选择电喷离子源(ESI)，根据检测目标化合物的响应选择离子扫描模式；采用三重四级杆质谱多反应监测(MRM)模式进行数据采集，选择代谢标志物的特征离子对信息，并采用标准品进行信息确认和检测方法建立，同时采用内标准品进行定量校正，得到生物样本中各代谢标志物的精准浓度值及相关比例值。
在一些具体的实施方式中，所述系统还包括样品前处理模块，所述样品前处理模块至少用于执行蛋白沉淀和标志物组提取的操作；所述操作包括对所述受试者样本用异丙醇和甲醇混合溶剂进行提取，离心后取上清液用于检测，其体积比可以为1：1-1：10，作为优选方式，体积比可以为1：3-1：5。
有益效果
(1)本发明首次在心脑血管疾病受试者样本中发现并验证了相对正常受试者的32种差异代谢物，其中7种差异代谢物尤为重要。基于上述发现，本发明提供一种全新的代谢标志物组合及其应用，建立相应的代谢物标志物组合定量检测方法和计算机评估系统，有助于提高心脑血管疾病诊断的灵敏度和特异性。
(2)本发明基于7种尤为重要的心脑血管疾病差异代谢物，建立预测模型，该模型在用于区分147个冠心病患者时，AUC＝0.897，灵敏度为85.0％，特异度为89.4％，准确性为86.7％。本发明所述计算机系统运用该模型评估受试者的心脑血管疾病风险时，具有灵敏度和特异性高、准确性好的优点。本发明发现的差异代谢物和预测模型还可用于受试者心衰、房颤和动脉粥样硬化等心血管疾病的风险评估。
(3)本发明在优选方案中采用高效液相色谱串联质谱联用的方式检测样品中的标志物水平，并进一步优化其检测条件，实现了多种生物标志物的同时靶向定量检测，解决心脑血管疾病标志物的检测特异性、精准性和多样性问题，同时具有样本检测量小，通量高的优点。
附图说明
图1是本发明代谢标志物在血液中的液相色谱质谱代表型离子色谱图。
图2中在5％BSA中的神经酰胺分子Cerd18:1/16:0的校准曲线。
图3是在5％BSA中的神经酰胺分子Cer d18:1/18:0的校准曲线。
图4是在5％BSA中的苯乙酰谷氨酰胺的校准曲线。图5是在5％BSA中的神经酰胺分子Cer d18:1/24:0的校准曲线。
图6是在5％BSA中的神经酰胺分子Cer d18:1/24:1的校准曲线。
图7是在5％BSA中的左旋肉碱的校准曲线。
图8是在5％BSA中的三已糖神经酰胺的校准曲线。
图9是在5％BSA中的氧化三甲胺的校准曲线。
图10是在5％BSA中的肌酐的校准曲线。
图11是在5％BSA中的三甲胺的校准曲线。
图12是在5％BSA中的甜菜碱的校准曲线。
图13是在5％BSA中的胆碱的校准曲线。
图14是147例冠心病患者以及94例对照样本工作特征曲线(ROC)。
图15是919例冠心病患者以及116例对照样本工作特征曲线(ROC)。
图16是心衰患者和对照组受试者工作特征曲线(ROC)。
图17是房颤患者和对照组受试者工作特征曲线(ROC)。
图18是动脉粥样硬化患者和对照组受试者工作特征曲线(ROC)。
具体实施方式
下面将结合实施例对本发明的实施方案进行详细描述，但是本领域技术人员将会理解，下列实施例仅用于说明本发明，而不应视为限制本发明的范围。实施例中未注明具体条件者，按照常规条件或制造商建议的条件进行。所用试剂或仪器未注明生产厂商者，均为可以通过市购获得的常规产品。
实施例一、血液样本采集
采用临床EDTA抗凝的真空采血管，对冠心病患者和健康对照正常人进行静脉采集3-5ml空腹静脉血。采集后1小时内1500g×15分钟分离血浆。等量(150微升)分装于200微升离心管中，快速置于-80℃保存备用并做好信息登记。其中包括：(1)训练集：冠心病患者临床血浆样本183例，健康人对照血浆样本94例；(2)验证集：冠心病患者临床血浆样本147例，健康人对照血浆样本94例。
实施例二、校准品(标准品)曲线工作液、内校准品以及质控品的制备
将待测标志物标准品分别用异丙醇:乙腈为9:1的溶剂溶解成0.1mM的储备液。然后进一步用50mg/mL的牛血清白蛋白(BSA，阿拉丁)溶液稀释成混合校准品(标准品)曲线 工作液。
示例性地，可在混合校准品工作液中加入神经酰胺Cer d18:1/16:0、神经酰胺Cer d18:1/18:0、神经酰胺GlcCer d18:1/12:0和1-磷酸鞘氨醇，其浓度点分别为2μM、1μM、0.4μM、0.2μM、0.08μM和0.04μM；还可在混合校准品工作液中加入神经酰胺Cer d18:1/24:0、神经酰胺Cerd18:1/24:1、三己糖神经酰胺d18:1/24:)和苯基乙酰基谷氨酰胺的各浓度点为10μM、5μM、2μM、1μM、0.4μMμM和0.2μM；还可在混合校准品工作液中加入氧化三甲胺、三甲胺、胆碱、左旋肉碱、甜菜碱、肌酸酐，其浓度点为100μM、50μM、20μM、10μM、4μM和2μM。注意，本实施例仅为示例性地描述混合校准样品工作液中的代谢标志物，而非穷举。
内校准品神经酰胺分子Cerd18:1/17:0、氘代氧化三甲胺和氘代色氨酸分别溶解成0.1mM的储备液，然后用异丙醇:甲醇为8:2的溶剂稀释成300nM的混合内标工作液。
根据样本中各标记组合物的浓度范围，制备相对浓度高、中、低的三个质控样品。
实施例三、血浆样本的前处理及诊断标记组合物提取
上述共518例血浆样本和校准品(标准品)曲线工作液以及质控品分别取10微升至V底96孔板中，然后再加入190微升内校准品工作液，贴上铝制封口膜，650rpm震荡混匀20分钟。然后4000×g离心20分钟，取100微升上清液待高效液相色谱-质谱检测。
实施例四、诊断标记组合物的高效液相色谱-质谱检测
液相色谱分离条件和参数主要为：进样5微升，流动相A为60％甲醇+10mM甲酸铵，流动相B为90％异丙醇+10％甲醇+10mM甲酸铵，色谱柱为100mM的C18反相柱(Waters Acquity BEH C18)，柱温设置为40℃，流速为0.3mL/分钟。洗脱梯度：0-0.5分钟维持50％B，0.5-1.8分钟从50％B线性变化至75％B，1.8-3.0分钟从75％B线性变化至80％B，3.0-3.4分钟从80％B线性变化至98％B，3.4-4.3分钟维持98％B，4.3-4.5分钟从98％B线性变化至50％B，4.5-6分钟维持50％B。
质谱检测参数主要为：采用三重四级杆质谱多反应监测(MRM)模式进行数据采集，离子谱图参见附图1。
实施例五、标准曲线
建立各代谢标志物的校正标准曲线，示例性地，如图2-图13所示，其中横坐标代表相应检测物质的浓度(μM)，纵坐标代表质谱信号峰面积。本实施例得到的校正标准曲线可以用于查询受试者血清样本中相应待测物质的浓度。
实施例六、质量控制
将测试项目的冠心病样本和健康对照样本取等量混合成QC样本，然后与标准品一起检测，进行标准曲线线性、定量LOQ、加标和非加标对比的定量回收率测试，同时非加标的QC样本穿插在项目样本中进行间隔的定量重复性测试，确保样本的检测符合质量控制，示例性地，表1示出部分代谢物的相关结果。
表1质量控制检测结果
Figure PCTCN2022070155-appb-000001
实施例七、标志物诊断模型建立
通过多维OPLS-DA模型提供的变量权重VIP值(VIP＞1)及Mann-Whitney U检验所提供的P值(P＜0.05)的选择标准，从训练集样本中得到用于区分冠心病及正常对照的32种差异性代谢物，包括：神经酰胺Cer d18:1/16:0、神经酰胺Cer d18:1/18:0、神经酰胺Cer d18:1/24:0、神经酰胺Cer d18:1/24:1、神经酰胺GlcCer d18:1/12:0、三已糖神经酰胺d18:1/24:0、1-磷酸鞘氨、苯乙酰谷氨酰胺、氧化三甲胺、三甲胺、胆碱、左旋肉碱、甜菜碱、肌酸酐，天冬氨酸、N-乙酰丙氨酸、甘氨酸、N-乙酰天冬氨酸、N-乙酰苏氨酸、N-乙酰-1-甲基组氨酸、吲哚乙酸、皮质醇、柠檬酸、亮氨酸、异亮氨酸、缬氨酸、嘧啶、琥珀酸、乙酰辅酶、谷氨酸、草酰乙酸和alpha-酮戊二酸。
利用逻辑回归模型进行验证，发现其中的7个代谢物(分别是：神经酰胺分子Cer d18:1/16:0，神经酰胺分子Cer d18:1/18：0，神经酰胺分子Cer d18:1/24：0，苯乙酰谷氨酰胺，三甲胺，甜菜碱，胆碱)作为冠心病标志物的作用尤为重要。随后应用临床诊断性 能曲线(ROC曲线)对标志物在冠心病血浆/血清样本进行评价。
根据各诊断标志物在冠心病和正常对照组之间的差异倍数大小、显著性大小及其浓度值大小范围等综合因素，通过逻辑回归模型建立优于单一标志物指标的得分诊断模型：
模型得分P＝C1*0.9414+C2*5.6311+C3*0.5817+C4*0.09151–C5*0.03620+C6*0.05425+C7*0.02096+2.2141。
其中，所述C1为样品中神经酰胺Cer d18:1/16:0按μM的浓度单位表示时所取的浓度值；如果浓度值用mM表述，需先换算为μM后，再取其浓度值作为可带入至模型，示例性地，如果样品中神经酰胺Cer d18:1/16:0的检测浓度为0.02mM，则需将其换算为20μM，取20作为C1值带入模型进行计算，下述C2-C7均采用同样方式处理；
所述C2为样品中神经酰胺Cer d18:1/18：0按μM的浓度单位表示时所取的浓度值；所述C3为样品中神经酰胺Cer d18:1/24：0按μM的浓度单位表示时所取的浓度值；所述C4为样本中苯乙酰谷氨酰胺按μM的浓度单位表示时所取的浓度值；所述C5为样本中三甲胺按μM的浓度单位表示时所取的浓度值；所述C6为样本中甜菜碱按μM的浓度单位表示时所取的浓度值；所述C7为样本中胆碱按μM的浓度单位表示时所取的浓度值。
通过受试者工作特征曲线(ROC)曲线分析得到最佳诊断阈值0.4243(参见说明书附图14)。后续通过每个样本的诊断标志物检测其浓度值，再根据诊断模型计算得分值，通过与诊断阈值的比较评估受试者是否患病或具有患病风险。
实施例八、标志物诊断模型的验证
将建立的标志物诊断模型应用于另外147例冠心病患者以及94例对照样本，计算每个样本的得分值，然后统计得到验证的诊断特异性、灵敏度、准确率，如下表2格所示，结果表明该预测模型具有较好的冠心病预测结果。7个代谢物组用于区分147个冠心病患者时AUC＝0.871，灵敏度为85.0％，特异度为89.4％，准确性为86.7％(表2)。
表2实施例7所述预测模型的诊断冠心病效果评估
Figure PCTCN2022070155-appb-000002
将建立的标志物诊断模型应用于另外919例冠心病患者以及116例对照样本，计算每个样本的得分值，然后统计得到验证的诊断特异性、灵敏度、准确率，如下表3所示，结 果表明该预测模型具有较好的冠心病预测结果。7个代谢物组用于区分919个冠心病患者时AUC＝0.959(图15)，灵敏度为97.8％，特异度为91.4％，准确性为97.2％(表3)。
表3实施例7所述预测模型的诊断冠心病效果评估
Figure PCTCN2022070155-appb-000003
实施例九、标志物诊断模型的验证
将建立的标志物诊断模型应用于121例心衰患者以及89例对照样本，计算每个样本的得分值，然后统计得到验证的诊断特异性、灵敏度、准确率，结果表明该预测模型具有较好的心衰预测结果。7个代谢物组用于区分121个心衰患者时AUC＝0.905，灵敏度为88.4％，特异度为83.1％，准确度86.2％，阈值1.019，见表4和附图16。
表4实施例7所述预测模型的诊断心衰效果评估
Figure PCTCN2022070155-appb-000004
实施例十、标志物诊断模型的验证
将建立的标志物诊断模型应用于134例房颤患者以及111例对照样本，计算每个样本的得分值，然后统计得到验证的诊断特异性、灵敏度、准确率，结果表明该预测模型具有较好的房颤预测结果。7个代谢物组用于区分134个房颤患者时AUC＝0.836，灵敏度为82.8％，特异度为82.9％，准确性82.9，阈值1.412，见表5和附图17。
表5实施例7所述预测模型的诊断房颤效果评估
Figure PCTCN2022070155-appb-000005
Figure PCTCN2022070155-appb-000006
实施例十一、标志物诊断模型的验证
将建立的标志物诊断模型应用于123例动脉粥样硬化患者以及98例对照样本，计算每个样本的得分值，然后统计得到验证的诊断特异性、灵敏度、准确率，结果表明该预测模型具有较好的动脉粥样硬化预测结果。7个代谢物组用于区分123个动脉粥样硬化患者时AUC＝0.838，灵敏度为81.3％，特异度为79.6％，准确性80.5％，阈值0.303，见表6和附图18。
表6实施例7所述预测模型的诊断动脉粥样硬化效果评估
Figure PCTCN2022070155-appb-000007
实施例十二、检测心脑血管疾病的计算机系统的建立
根据实施例1-11，本实施例建立一种用于评估受试者心脑血管疾病风险的计算机系统，包括信息获取模块、心脑血管疾病风险评估模块、样品检测模块和样品前处理模块。
其中，所述信息获取模块至少用于执行以下操作：获取受试者样品中的代谢标志物组合检测信息，所述代谢标志物组合选自前所述的代谢标志物组合。
所述心脑血管疾病风险评估模块至少用于执行以下操作：根据所述信息获取模块获取的代谢标志物组水平，评估所述受试者是否患有心脑血管疾病或具有心脑血管疾病的患病风险；所述心脑血管疾病选自高血压、冠心病、动脉粥样硬化、房颤、心衰、中风、周围血管疾病、心力衰竭、风湿性心脏病、先天性心脏病或心肌病；具体包括将所述信息获取模块获取的代谢标志物组的水平输入诊断模型，根据诊断模型评估所述受试者是否患有心脑血管疾病或具有心脑血管疾病的患病风险；所述诊断模型如下所示：
P＝C1*0.9414+C2*5.6311+C3*0.5817+C4*0.09151–C5*0.03620+C6*0.05425+C7*0.02096+2.2141；
其中，所述C1为样品中神经酰胺Cer d18:1/16:0按μM的浓度单位表示时所取的浓度值，所述C2为样品中神经酰胺Cer d18:1/18：0按μM的浓度单位表示时所取的浓度值，所述C3为样品中神经酰胺Cer d18:1/24：0按μM的浓度单位表示时所取的浓度值，所述C4为样本中苯乙酰谷氨酰胺按μM的浓度单位表示时所取的浓度值，所述C5为样本中三甲胺按μM 的浓度单位表示时所取的浓度值，所述C6为样本中甜菜碱按μM的浓度单位表示时所取的浓度值，所述C7为样本中胆碱按μM的浓度单位表示时所取的浓度值；
如果所述受试者的P值对应于不同阈值范围，则评估所述受试者患有所述心脑血管疾病或者具有心脑血管疾病患病风险，其中：
所述阈值选自0.4-0.5，优选0.4243时，预测所述受试者具有冠心病风险；
所述阈值选自1.0-1.2，优选1.019时，预测所述受试者具有心衰风险；
所述阈值选自1.4-1.42，优选1.412时，预测所述受试者具有房颤风险；
所述阈值选自0.3-0.31，优选0.303时，预测所述受试者具有动脉粥样硬化风险。
所述样品检测模块，至少用于执行检测样品中所述标志物水平的操作；具体包括至少用于执行检测生物标志物的液相色谱串联质谱联用(LC-MS/MS)操作；所述液相色谱可选自高效液相色谱(HPLC)、超高效液相色谱(UPLC)和纳升液相色谱(Nano-LC)，所述串联质谱可选自四级杆质谱(Quadrupole,Q)、飞行时间质谱(Time of Flight,TOF)、离子肼质谱(Ion Trap)和高分辨轨道肼质谱(Orbitrap)；
所述液相色谱的分离条件包括：进样5微升，流动相A为60％甲醇+10毫摩尔甲酸铵，流动相B为90％异丙醇+10％甲醇+10毫摩尔甲酸铵，色谱柱为100毫摩尔的C18柱，柱温设置为40℃，流速为0.3mL/分钟，0-0.5分钟维持50％B，0.5-1.8分钟从50％B线性变化至75％B，1.8-3.0分钟从75％B线性变化至80％B，3.0-3.4分钟从80％B线性变化至98％B，3.4-4.3分钟维持98％B，4.3-4.5分钟从98％B线性变化至50％B，4.5-6分钟维持50％B；
所述质谱的检测条件包括：采用三重四级杆质谱多反应监测(MRM)模式进行数据采集，选择代谢标志物的特征离子对信息，并采用标准品进行信息确认和检测方法建立，同时采用内标准品进行定量校正，得到生物样本中各代谢标志物的精准浓度值及相关比例值。所述样品前处理模块，所述样品前处理模块至少用于执行蛋白沉淀和标志物组提取的操作；所述操作包括对所述受试者样本用异丙醇:甲醇进行提取，离心后取上清液用于检测。
最后应说明的是：以上各实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述各实施例对本发明进行了详细的说明，但本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分或者全部技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的范围。

Claims (15)

  1. 用于评估受试者心脑血管疾病风险的代谢标志物组合，其特征在于，所述代谢标志物组合包括神经酰胺Cer d18:1/16:0、神经酰胺Cer d18:1/18：0、神经酰胺Cer d18:1/24：0、苯乙酰谷氨酰胺、三甲胺、甜菜碱和胆碱；所述心脑血管疾病选自冠心病、动脉粥样硬化、房颤、心衰。
  2. 如权利要求1所述的代谢标志物组合，其特征在于，所述代谢标志物组合还包括以下代谢标志物的一种或多种：神经酰胺Cer d18:1/24:1、神经酰胺Glc Cer d18:1/12:0、三已糖神经酰胺d18:1/24:0、1-磷酸鞘氨醇、氧化三甲胺、肉碱或肌酸酐。
  3. 如权利要求2所述的代谢标志物组合，其特征在于，所述代谢标志物组合还包括以下代谢标志物的一种或多种：天冬氨酸、N-乙酰丙氨酸、甘氨酸、N-乙酰天冬氨酸、N-乙酰苏氨酸、N-乙酰-1-甲基组氨酸、吲哚乙酸、皮质醇、柠檬酸、亮氨酸、异亮氨酸、缬氨酸、嘧啶、琥珀酸、乙酰辅酶、谷氨酸、草酰乙酸和α-酮戊二酸。
  4. 如权利要求1至3任一所述的代谢标志物组合，其特征在于，所述受试者为人类；所述代谢标志物通过检测受试者的生物样本而获得，所述生物样本选自血浆或血清。
  5. 如权利要求1至3任一所述的代谢标志物组合在制备诊断心脑血管疾病或评价心脑血管药物的诊断产品中的用途，所述产品以权利要求1至3任一所述的代谢标志物组合的表达水平作为评估指标。
  6. 如权利要求5所述的用途，其特征在于，所述诊断产品选自试剂盒、诊断装置和计算机系统。
  7. 一种检测如权利要求1至3任一所述的代谢标志物组合的试剂盒，其特征在于，所述试剂盒包括代谢标志物的标准品和代谢标志物提取剂，所述代谢标志物提取剂为有机溶剂和水的混合物，有机溶剂选自异丙醇、甲醇和乙腈中的一种或多种。
  8. 一种用于评估受试者心脑血管疾病风险的计算机系统，其特征在于，所述系统包括信息获取模块和心脑血管疾病风险评估模块；
    其中，所述信息获取模块至少用于执行以下操作：获取受试者样品中的代谢标志物组合检测信息，所述代谢标志物组合选自权利要求1至3任一项所述的代谢标志物组合；
    所述心脑血管疾病风险评估模块至少用于执行以下操作：根据所述信息获取模块获取的代谢标志物组水平，评估所述受试者是否患有心脑血管疾病或具有心脑血管疾病的患病风险；所述心脑血管疾病选自冠心病、动脉粥样硬化、房颤和心衰。
  9. 如权利要求8所述的系统，其特征在于，所述心脑血管疾病风险评估模块至少用于执行以下操作：将所述信息获取模块获取的代谢标志物组的水平输入诊断模型，根据诊断模型评估所述受试者是否患有心脑血管疾病或具有心脑血管疾病的患病风险。
  10. 如权利要求9所述的系统，其特征在于，所述诊断模型如下所示：
    P＝C1*0.9414+C2*5.6311+C3*0.5817+C4*0.09151–C5*0.03620+C6*0.05425+C7*0.02096+2.2141；
    其中，所述C1为样品中神经酰胺Cer d18:1/16:0按μM的浓度单位表示时所取的浓度值，所述C2为样品中神经酰胺Cer d18:1/18：0按μM的浓度单位表示时所取的浓度值，所述C3为样品中神经酰胺Cer d18:1/24：0按μM的浓度单位表示时所取的浓度值，所述C4为样本中苯乙酰谷氨酰胺按μM的浓度单位表示时所取的浓度值，所述C5为样本中三甲胺按μM的浓度单位表示时所取的浓度值，所述C6为样本中甜菜碱按μM的浓度单位表示时所取的浓度值，所述C7为样本中胆碱按μM的浓度单位表示时所取的浓度值；
    如果所述受试者的P值对应不同阈值范围时，则评估所述受试者患有所述心脑血管疾病或者具有心脑血管疾病患病风险，其中：所述阈值选自0.4-0.5，预测所述受试者具有冠心病风险；所述阈值选自1.0-1.2，预测所述受试者具有心衰风险；所述阈值选自1.4-1.42，预测所述受试者具有房颤风险；所述阈值选自0.3-0.31，预测所述受试者具有动脉粥样硬化风险。
  11. 如权利要求10所述的系统，其特征在于，所述阈值为0.4243时，预测所述受试者具有冠心病风险；所述阈值为1.019时，预测所述受试者具有心衰风险；所述阈值为1.412时，预测所述受试者具有房颤风险；所述阈值为0.303时，预测所述受试者具有动脉粥样硬化风险。
  12. 如权利要求10所述的系统，其特征在于，所述系统还包括样品检测模块，至少用于执行检测样品中所述标志物水平的操作。
  13. 如权利要求12所述的系统，其特征在于，所述样品检测模块至少用于执行检测生物标志物的液相色谱串联质谱联用操作；所述液相色谱可选自高效液相色谱、超高效液相色谱和纳升液相色谱，所述串联质谱可选自四级杆质谱、飞行时间质谱、离子肼质谱和高分辨轨道肼质谱。
  14. 如权利要求13所述的系统，其特征在于，所述液相色谱的流动相A为含添加剂的甲醇溶液，添加剂选自甲酸铵、乙酸铵和三氯乙酸中任一种，流动相B选自异丙醇、甲醇、乙腈、乙醇和丙二醇中一种或几种的组合；色谱柱选自C8和C18硅胶填料柱，柱温设置为25-45℃，流速为0.2-0.6毫升/分；所述质谱的检测条件包括：采用三重四级杆质谱多反应监测模式进行数据采集，选择代谢标志物的特征离子对信息，并采用标准品进行信息确认和检测方法建立，同时采用内标准品进行定量校正，得到生物样本中各代谢标志物的精准浓度值及相关比例值。
  15. 如权利要求10所述的系统，其特征在于，所述系统还包括样品前处理模块，所述样品前处理模块至少用于执行蛋白沉淀和标志物组提取的操作；所述操作包括对所述受试者样本用异丙醇和甲醇混合溶剂进行提取，离心后取上清液用于检测。
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