CN112326840A - Acute aortic dissection patient-specific biomarker composition and application thereof - Google Patents
Acute aortic dissection patient-specific biomarker composition and application thereof Download PDFInfo
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Abstract
The present invention relates to the field of disease-specific metabolite profiles, in particular to acute aortic dissection patient-specific biomarker compositions and uses thereof. The invention obtains various related biomarkers by comparing and analyzing the metabolite spectrums of the acute aortic dissection group and the control group, and can accurately perform differential diagnosis on the acute aortic dissection by combining the metabolite spectrum data of the biomarkers of the high-quality acute aortic dissection group and the control group as a training set. Compared with the conventional diagnosis method, the method has the characteristics of minimal invasion, convenience, quickness, high sensitivity and good specificity.
Description
Technical Field
The present invention relates to the field of disease-specific metabolite profiles, in particular to acute aortic dissection patient-specific biomarker compositions and uses thereof.
Background
Acute Aortic Dissection (AAD) is an aggressive great vessel disease with a rapid onset and a very high early mortality, and early diagnosis is a prerequisite for clinical implementation of early treatment and is a key to reducing the early mortality of AAD. The imaging means is the gold standard for determining AAD at present, but has a diagnosis lag, which often results in delay of the determination of AAD. Clinically, the plasma biomarker D-Dimer is used in combination for auxiliary diagnosis at present. D-Dimer has higher sensitivity but lower specificity. Therefore, the differential diagnosis of AAD cannot be performed by the D-Dimer alone. The development of a specific and accurate AAD diagnosis method is of great significance.
Metabolomics (metabolomics) can systematically screen a group of metabolic compositions reflecting disease states by observing the change rule of metabolites of organisms under physiological and pathological states, and can explain life phenomena which cannot be explained by a single biomarker.
The application of metabonomics in the research of finding disease diagnosis markers has more and more remarkable results. Researchers have found biomarker compositions closely related to diagnosis of diseases such as prostate cancer, breast cancer, thoracic aortic aneurysm, hypertension, atherosclerosis and the like by using a metabonomics method.
Therefore, screening for metabolic markers associated with AAD, particularly the combined use of multiple metabolic markers, is of great significance for clinical diagnosis and treatment decisions of AAD.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides a specific biomarker composition for patients with acute aortic dissection and application thereof, and can overcome the defects of low hysteresis, low specificity and the like of the conventional acute aortic dissection diagnosis method.
In order to achieve the purpose, the invention adopts the technical scheme that: provided is a biomarker composition for diagnosing acute aortic dissection, which at least contains one or more of the following biomarkers 1-5:
the biomarker 1, the mass-to-charge ratio of which is 164.07 +/-0.4 amu, and the retention time of which is 1.82 +/-0.5 min;
biomarker 2 with mass-to-charge ratio of 524.34 + -0.4 amu and retention time of 6.40 + -0.5 min;
biomarker 4 with a mass-to-charge ratio of 552.37 ± 0.4amu and a retention time of 7.45 ± 0.5 min;
biomarker 5 with a mass to charge ratio of 596.39 ± 0.4amu with a retention time of 8.21 ± 0.5 min.
In the present invention, the unit of mass to charge ratio, amu, refers to the unit of atomic mass, also known as daltons (Da), which is a measure of the mass of an atom or molecule, and is defined as 1/12 to the mass of a carbon 12 atom.
In the present invention, one or more of the biomarkers can be selected for early diagnosis or differential diagnosis of acute aortic dissection, preferably at least three of them, i.e. biomarkers 1-3, are selected for evaluation, or the 5 biomarkers (biomarkers 1-5) are selected for evaluation at the same time, so as to obtain the desired sensitivity and specificity.
Without wishing to be bound by any theory, the inventors indicate that these biomarkers are endogenous compounds present in the human body. The metabolite profile of the subject's plasma is analyzed by the methods described herein, and the mass number values and retention times in the metabolite profile indicate the presence and corresponding location of the respective biomarker in the metabolite profile. At the same time, the biomarkers of the acute aortic dissection population exhibit a range of content in their metabolite spectrum.
As a preferred embodiment of the biomarker composition according to the present invention, the biomarker is derived from a human plasma sample.
As a preferred embodiment of the biomarker composition of the present invention, the mass-to-charge ratio and retention time are measured by a mass spectrometer with time-of-flight or quadrupole as mass analyzer; wherein each biomarker is determined by a method of liquid chromatography-mass spectrometry.
As a preferred embodiment of the biomarker composition of the present invention, the measurement conditions of the liquid chromatography-mass spectrometry are as follows:
(1) chromatographic conditions
A chromatographic column: a C18 column; mobile phase A: 0.1% aqueous formic acid, mobile phase B: 0.1% formic acid acetonitrile solution; gradient elution procedure: 0-2min, 2% -30% B; 2-9min, 30% -100% B; 9-11min, 100% B; 11-14min, 2% B; flow rate: 0.4 mL/min; sample introduction volume: 1 mul;
(2) conditions of Mass Spectrometry
ESI ion source, negative ion mode data collection, scan mass m/z 80-2000. Ion source parameters: the capillary voltage is 3.0kV, the taper hole voltage is 35V, the temperature in the source is 100 ℃, the temperature of the drying air flow is 350 ℃, the flow rate of the dryer is 600L/h, and the collision energy is 6 eV.
As a preferred embodiment of the biomarker composition according to the present invention, the diagnosis is an early diagnosis or a differential diagnosis.
The invention also provides a kit for diagnosing acute aortic dissection, which contains reagents for detecting any one of the biomarker compositions.
As a preferred embodiment of the kit of the present invention, the reagent is a ligand that can bind to the biomarker. The ligand may be an antibody; optionally, the reagent for detection may also carry a detectable label.
One skilled in the art knows that when further expanding the sample size, the normal content value interval (absolute value) of each biomarker in the sample can be derived using sample detection and calculation methods well known in the art. Thus, when the content of the biomarker is detected by methods other than mass spectrometry (for example, by using an antibody and an ELISA method), the absolute value of the content of the biomarker obtained by detection can be compared with the normal content value, and optionally, a statistical method can be combined to obtain an early diagnosis or a differential diagnosis.
As a preferred embodiment of the kit of the invention, the diagnosis comprises the step of establishing a training set of the content of the biomarker compositions of acute aortic dissection subjects and control subjects.
In a preferred embodiment of the kit of the present invention, the training set is a training set established by using a multivariate statistical classification model.
As a preferred embodiment of the kit of the present invention, the diagnosis comprises the steps of:
1) determining the content of each biomarker in the biomarker composition in the plasma of the subject by using a liquid chromatography-mass spectrometry combined method;
2) comparing the levels of each biomarker in the biomarker compositions in the plasma of the subjects with training set data for the biomarker compositions of acute aortic dissection subjects and control subjects using a ROC curve;
3) if the probability of the patient with non-acute aortic dissection obtained by ROC diagnosis is less than 0.5 or the probability of the patient with non-acute aortic dissection is more than 0.5, the assumed patient has high probability and high risk of suffering from acute aortic dissection or is diagnosed as the patient with acute aortic dissection.
In the present invention, methods for using the one-way analysis of variance and the ROC curve are well known in the art, and those skilled in the art can set and adjust parameters according to specific situations.
In one embodiment of the present invention, the content of each biomarker in the biomarker composition, and the data on the content of each biomarker in the training set are obtained by the following steps:
(1) collecting and processing samples: collecting a plasma sample of a clinical patient or a model animal; subjecting the sample to liquid-liquid extraction with organic solvent including but not limited to ethyl acetate, chloroform, ethanol, n-butanol, petroleum ether, dichloromethane, acetonitrile, etc.; or protein precipitation, wherein the protein precipitation method comprises adding organic solvent (such as methanol, ethanol, propanol, acetonitrile, isopropanol), precipitating various acid, alkali and salt, heating for precipitation, filtering/ultrafiltering, solid phase extracting, centrifuging, etc., and treating in single or comprehensive manner; the sample is dried or not dried and then dissolved with various organic solvents (e.g., methanol, acetonitrile, isopropanol, chloroform, etc., preferably methanol) or water (alone or in combination, without salt or with salt); the sample is not derivatized or is derivatized with a reagent (e.g., trimethylsilane, etc.).
(2) Ultra performance liquid chromatography mass spectrometry (UPLC-MS): a metabolite spectrum in plasma is obtained by adopting a method based on ultra-high performance liquid chromatography and mass spectrometry, and the metabolite spectrum is processed to obtain data such as peak height or peak area (peak intensity) of each peak, mass-to-charge ratio and retention time (retention time), wherein the peak area represents the content of a biomarker.
In one embodiment of the invention, the content of the biomarker is represented by the peak area of the mass spectrum.
In the present invention, the mass-to-charge ratio and the retention time have meanings well known in the art.
It is well known to those skilled in the art that the atomic mass units and retention times of the biomarkers in the biomarker compositions of the present invention may fluctuate within a range of + -0.4 amu, such as + -0.2 amu, such as + -0.1 amu, and the retention times may fluctuate within a range of + -0.5 min, such as + -0.75 min, such as + -0.5 min, such as + -0.25 min, when different liquid chromatography-mass spectrometry combined equipment and different detection methods are used.
The invention has the beneficial effects that:
(1) the invention adopts an ultra-high performance liquid chromatography-mass spectrometry combined analysis method to analyze the metabolite spectrums of the plasma samples of the acute aortic dissection group and the control group, analyzes and compares the plasma metabolite spectrums of the acute aortic dissection group and the control group by using pattern recognition, determines specific liquid chromatography-mass spectrometry data and related specific biomarkers, and provides a basis for subsequent theoretical research and clinical diagnosis.
(2) The endogenous micromolecules in the organism are the basis of life activities, and the metabolism change of the endogenous micromolecules in the organism is inevitably caused by the change of the disease state and the organism function. The invention obtains various related biomarkers by comparing and analyzing the metabolite spectrums of the acute aortic dissection group and the control group, and can accurately perform differential diagnosis on the acute aortic dissection by combining the metabolite spectrum data of the biomarkers of the high-quality acute aortic dissection group and the control group as a training set. Compared with the conventional diagnosis method, the method has the characteristics of minimal invasion, convenience, quickness, high sensitivity and good specificity.
Drawings
Fig. 1 is a graph of plasma mass spectrum BPI of an acute aortic dissection group, an acute coronary syndrome group and a healthy control group.
FIG. 2 is an OPLS-DA score plot.
FIG. 3 is a S-Plot.
FIG. 4 is a ROC diagram of variable 568.36 amu; wherein AUC is 0.923.
FIG. 5 is a ROC diagram of variable 164.074 amu; wherein AUC is 0.923.
Detailed Description
To more clearly illustrate the technical solutions of the present invention, the following embodiments are further described, but the present invention is not limited thereto, and these embodiments are only some examples of the present invention.
Blood samples of Acute Aortic Dissection (AAD), Acute Coronary Syndrome (ACS) and Healthy Control (HC) subjects of the present invention were obtained from the national hospital of guangdong province.
Example 1
Collecting samples: plasma from the volunteers was collected and immediately stored in a-80 ℃ cryorefrigerator. 20 plasma samples were collected from each of the acute aortic dissection group, the acute coronary syndrome group, and the healthy control group.
Processing of the sample: the frozen sample is thawed at room temperature, 70. mu.l of the plasma sample is taken and placed in a 2.0mL centrifuge tube, 280. mu.l of methanol is added for dilution, and the mixture is centrifuged at 12000rpm for 15min for standby.
The method utilizes ultra performance liquid chromatography combined analysis, and comprises the following specific steps:
(1) instrumentation and equipment
ACQUITY I class UPLC-Vion IMS Q-TOF mass spectrometer(Waters Corp.,Milford,USA)。
(2) Chromatographic conditions
A chromatographic column: c18 column (100 mm. times.2.1 mm, i.d.1.7 μm); mobile phase A: 0.1% aqueous formic acid, mobile phase B: 0.1% formic acid acetonitrile solution; gradient elution procedure: 0-2min, 2% -30% B; 2-9min, 30% -100% B; 9-11min, 100% B; 11-14min, 2% B; flow rate: 0.4 mL/min; sample introduction volume: 1 μ l.
(3) Conditions of Mass Spectrometry
ESI ion source, negative ion mode data collection, scan mass m/z 80-2000. Ion source parameters: the capillary voltage is 3.0kV, the taper hole voltage is 35V, the temperature in the source is 100 ℃, the temperature of the drying air flow is 350 ℃, and the flow rate of the dryer is 600L/h; collision energy was 6 eV.
(4) Data processing
The total ion spectrum file automatically executes the processes of baseline correction, peak identification, peak alignment, baseline noise deduction and the like through Masslynx software to obtain a BPI spectrum, and then carries out peak discrimination and normalization through Progenetics QI v2.3(Nonlinear Dynamics, Newcastle, U.K.) to finally obtain a three-dimensional matrix consisting of an appointed peak serial number (corresponding to retention time and mass-to-charge ratio), an observation point (sample number) and normalized peak intensity, wherein the matrix is used for all subsequent data analysis.
Multivariate statistical analysis was performed using ezlnfor V3.0.3 software, including Principal Component Analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) to identify statistically significant changes, extracting potential markers from scatter plots with Variable Importance (VIP) greater than 1 and p <0.05 as parameters.
(5) Comparing and determining characteristic metabolite profiles
The plasma metabolite spectrum of the acute aortic dissection patient is established by comparing the plasma metabolite spectrum of the acute aortic dissection group, the acute coronary syndrome group and the healthy control group (figure 1), and the result shows that the plasma metabolite spectrum of the acute aortic dissection group, the acute coronary syndrome group and the healthy control group are obviously different.
(6) Potential biomarker screening
The score plots for AAD vs ACS, ACS vs HC, and OPLS-DA for AAD vs HC are shown in FIG. 2. Screening is carried out according to the size of a VIP (variable immunity in the project) value in each OPLS-DA model and by combining the P value and the Q value of t-test (t-test) and the result of an S-plot (figure 3), and metabolites with the VIP value larger than 1 and the P value and the Q value smaller than 0.05 are selected as final significant difference metabolites of the model group. There were 5 potential biomarkers selected as shown in table 1.
TABLE I potential biomarkers
Example 2
Collecting samples: plasma from the volunteers was collected and immediately stored in a-80 ℃ cryorefrigerator. 80 plasma samples were collected from each of the acute aortic dissection group and the acute coronary syndrome group, and 40 plasma samples were collected from the healthy control group.
Processing of the sample: the frozen sample is thawed at room temperature, 70. mu.l of the plasma sample is taken and placed in a 2.0mL centrifuge tube, 280. mu.l of methanol is added for dilution, and the mixture is centrifuged at 12000rpm for 15min for standby.
The method utilizes ultra performance liquid chromatography combined analysis, and comprises the following specific steps:
(1) instrumentation and equipment
ACQUITY I class UPLC equipped with the Vion IMS Q-TOF mass spectrometer(Waters Corp.,Milford,USA)。
(2) Chromatographic conditions
A chromatographic column: c18 column (100 mm. times.2.1 mm, i.d.1.7 μm); mobile phase A: 0.1% aqueous formic acid, mobile phase B: 0.1% formic acid acetonitrile solution; gradient elution procedure: 0-2min, 2% -30% B; 2-9min, 30% -100% B; 9-11min, 100% B; 11-14min, 2% B; flow rate: 0.4 mL/min; sample introduction volume: 1 μ l.
(3) Conditions of Mass Spectrometry
ESI ion source, negative ion mode data collection, scan mass m/z 80-2000. Ion source parameters: the capillary voltage is 3.0kV, the taper hole voltage is 35V, the temperature in the source is 100 ℃, the temperature of the drying air flow is 350 ℃, and the flow rate of the dryer is 600L/h; collision energy was 6 eV.
(4) Data processing
The total ion spectrum file automatically executes the processes of baseline correction, peak identification, peak alignment, baseline noise deduction and the like through Masslynx software to obtain a BPI spectrum, and then carries out peak discrimination and normalization through Progenetics QI v2.3(Nonlinear Dynamics, Newcastle, U.K.) to finally obtain a three-dimensional matrix consisting of an appointed peak serial number (corresponding to retention time and mass-to-charge ratio), an observation point (sample number) and normalized peak intensity, wherein the matrix is used for all subsequent data analysis.
(5) One-way analysis of variance
Statistical analysis of the data was performed using SPSS19.0, mainly using one-way anova to determine whether there was a statistical difference in the variables represented by the biomarkers among the three groups of samples.
We extracted the following five variables from the three sets of samples for one-way anova, with the results shown in table 2. The results in the table show that the content of the five biomarkers can be used as a diagnostic target of the AAD disease, particularly the variable 568.36amu, and the variable can be used as a specific target for diagnosing the AAD disease, wherein the significant difference exists only between the HC group and the AAD group, and the significant difference does not exist between the ACS group and the AAD group, and between the ACS group and the HC group. Variables 596.39amu and 164.07amu all have significant differences between ACS and AAD groups, HC and AAD groups, and no significant difference between ACS and HC groups, and can serve as specific targets for AAD disease diagnosis and differential diagnosis from ACS.
TABLE 2 one-way ANOVA results for five variables in three sets of samples
Note: the significance level of the respective color average difference is 0.05.
(6) Receiver diagnostic curve (ROC)
By selecting peak area data of two biomarkers 164.07amu and 568.36amu of 40 normal groups and 80 acute aortic dissection groups and adopting ROC modeling as a test set, the test result is that AUC (area under the curve) is greater than 0.9 (shown in FIG. 4 and FIG. 5).
In conclusion, the five biomarkers have high accuracy and specificity and have good prospects in development of diagnostic methods, so that a basis is provided for diagnosis of acute aortic dissection diseases.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention and not for limiting the protection scope of the present invention, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. Biomarker composition for the diagnosis of acute aortic dissection, characterized by comprising at least one or several of the following biomarkers 1-5:
the biomarker 1, the mass-to-charge ratio of which is 164.07 +/-0.4 amu, and the retention time of which is 1.82 +/-0.5 min;
biomarker 2 with mass-to-charge ratio of 524.34 + -0.4 amu and retention time of 6.40 + -0.5 min;
biomarker 3 with mass-to-charge ratio of 568.36 + -0.4 amu and retention time of 7.18 + -0.5 min;
biomarker 4 with a mass-to-charge ratio of 552.37 ± 0.4amu and a retention time of 7.45 ± 0.5 min;
biomarker 5 with a mass to charge ratio of 596.39 ± 0.4amu with a retention time of 8.21 ± 0.5 min.
2. The biomarker composition according to claim 1, wherein the biomarker is derived from a human plasma sample.
3. The biomarker composition according to claim 1, wherein the mass-to-charge ratio and retention time are measured by a mass spectrometer with a time-of-flight or quadrupole mass analyzer; wherein each biomarker is determined by a method of liquid chromatography-mass spectrometry.
4. The biomarker composition according to claim 3, wherein the measurement conditions for the combination of liquid chromatography-mass spectrometry are as follows:
(1) chromatographic conditions
A chromatographic column: a C18 column; mobile phase A: 0.1% aqueous formic acid, mobile phase B: 0.1% formic acid acetonitrile solution; gradient elution procedure: 0-2min, 2% -30% B; 2-9min, 30% -100% B; 9-11min, 100% B; 11-14min, 2% B; flow rate: 0.4 mL/min; sample introduction volume: 1 mul;
(2) conditions of Mass Spectrometry
ESI ion source, negative ion mode data collection, scan mass m/z 80-2000. Ion source parameters: the capillary voltage is 3.0kV, the taper hole voltage is 35V, the temperature in the source is 100 ℃, the temperature of the drying air flow is 350 ℃, the flow rate of the dryer is 600L/h, and the collision energy is 6 eV.
5. The biomarker composition according to claim 1, wherein the diagnosis is an early diagnosis or a differential diagnosis.
6. A kit for diagnosing acute aortic dissection, comprising reagents for detecting the biomarker composition of any one of claims 1 to 5.
7. The kit of claim 6, wherein the reagent is a ligand that can bind to the biomarker.
8. The kit according to claim 6, wherein the diagnosis comprises the step of establishing a training set of the content of the biomarker composition for acute aortic dissection subjects and control subjects.
9. The kit of claim 8, wherein the training set is a training set established using a multivariate statistical classification model.
10. The kit according to claim 8, characterized in that said diagnosis comprises the following steps:
1) determining the content of each biomarker in the biomarker composition in the plasma of the subject by using a liquid chromatography-mass spectrometry combined method;
2) comparing the levels of each biomarker in the biomarker compositions in the plasma of the subjects with training set data for the biomarker compositions of acute aortic dissection subjects and control subjects using a ROC curve;
3) if the probability of the patient with non-acute aortic dissection obtained by ROC diagnosis is less than 0.5 or the probability of the patient with non-acute aortic dissection is more than 0.5, the assumed patient has high probability and high risk of suffering from acute aortic dissection or is diagnosed as the patient with acute aortic dissection.
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