CN113447600B

CN113447600B - Biomarker for diagnosing cerebral infarction of patient with leukoencephalopathy and application of biomarker

Info

Publication number: CN113447600B
Application number: CN202110999855.XA
Authority: CN
Inventors: 陈显扬; 宋王婷; 张珂; 韩佳睿; 薛腾
Original assignee: Baofeng Biotech Beijing Co ltd
Current assignee: Baofeng Biotech Beijing Co ltd
Priority date: 2021-08-27
Filing date: 2021-08-27
Publication date: 2021-11-02
Anticipated expiration: 2041-08-27
Also published as: CN113447600A

Abstract

The invention provides application of a biomarker glucosylceramide in preparing a detection reagent for diagnosing cerebral infarction of a patient with leukoencephalopathy, and the risk of cerebral infarction of the patient with leukoencephalopathy is judged by combining the biomarker glucosylceramide with beta-hydroxyethyl ethanolamine, tomatidine, phosphatidylserine or decanoyl carnitine, so that cerebral infarction can be prevented in advance.

Description

Biomarker for diagnosing cerebral infarction of patient with leukoencephalopathy and application of biomarker

Technical Field

The invention belongs to the technical field of biological detection, and particularly relates to a biomarker for diagnosing cerebral infarction of a patient with a leukoencephalopathy and application thereof.

Background

With the aging of society, the incidence of stroke is rapidly increasing, and stroke death is the second leading cause of death worldwide. International comparative studies show that the incidence of stroke in our country is higher than the international average level, wherein ischemic stroke (cerebral infarction) is ischemic necrosis of brain tissue caused by stenosis or occlusion of cerebral artery, and accounts for more than 70% of all strokes. White matter disease (WML) is a common neurodegenerative disease, the most typical pathology of which is the destruction of white matter integrity or demyelination, and the disease is commonly seen in many diseases such as stroke, alzheimer disease, parkinson disease, multiple sclerosis, schizophrenia, etc. The typical response of white brain matter to various noxious stimuli is demyelination, which may be a secondary manifestation of neurological disorders such as infection, intoxication, degeneration, post-traumatic injury, cerebral infarction, and the like. The leukoencephalopathy mainly causes symptoms of cognitive disorder, speech disorder, mental behavior disorder, gait disorder, urination disorder and the like of a patient. Cerebral infarction combined with leukoencephalopathy can seriously increase family burden of patients, reduce life quality of the patients and bring heavy burden to individuals and the whole society, and the cerebral infarction combined with leukoencephalopathy is a key point and a difficulty in research in the field of medicine and health at present.

The diagnosis of cerebral infarction mainly depends on medical history and physical examination, and is assisted by imaging examination, and different imaging examinations have the defects of long time consumption, high cost and the like, so that valuable biomarkers are needed to be developed to predict risks, diagnose rapidly and accurately, and distinguish different types of cerebral apoplexy and other diseases. In general, the condition of most patients with leukoencephalopathy is reversible, so that the symptoms can be obviously improved by taking proper preventive measures for the patients with leukoencephalopathy, wherein early screening is a crucial means. At present, no peripheral blood biomarker with high accuracy and strong specificity exists. The pathogenesis of cerebral infarction combined with leukoencephalopathy is not clear, and a clear and effective treatment target point is lacked clinically, so that the treatment and recovery of patients are not facilitated. At present, imaging methods such as CT, MRI and the like are widely used for diagnosing cerebral infarction and leukoencephalopathy, but the imaging methods have the defects of complex operation, patient moving, high cost and the like, and have important clinical values for guiding the treatment of cerebral apoplexy and improving the prognosis of patients by searching blood biological markers with indicating effects on cerebral infarction diagnosis and disease evolution. As a promising tool for finding novel biomarkers of cerebral infarction combined with white brain disease, metabolomics can reflect the state of the organism by analyzing the changes of endogenous metabolites, and further identify specific biomarkers or marker groups.

How to find an easy-to-detect biomarker for predicting and diagnosing the cerebral infarction combined with the leukoencephalopathy is an urgent technical problem to be solved.

Disclosure of Invention

In order to solve the technical problems, the invention provides application of glucosylceramide combined with beta-hydroxyethyl ethanolamine, tomatidine, phosphatidylserine or decanoyl carnitine in preparing a detection reagent for diagnosing cerebral infarction of a patient with leukoencephalopathy.

In order to achieve the purpose, the invention adopts the following technical scheme that:

application of biomarker glucosylceramide combined with beta-hydroxyethyl ethanolamine, tomatidine, phosphatidylserine or decanoyl carnitine in preparation of detection reagent for diagnosing cerebral infarction of patients with leukoencephalopathy.

Use as described above, preferably in the determination of the risk of cerebral infarction of a leukoencephalopathy, by combining glucosylceramide with beta-hydroxyethylethanolamine, tomatidine, phosphatidylserine or decanoylcarnitine.

For the above applications, preferably, the content of glucosylceramide is represented as F2, the content of β -hydroxyethylethanolamine is represented as F3, the TC value is calculated according to TC = -0.4782 + 0.8007 × F2-0.4380 × F3, and if TC is greater than or equal to 0.615, the combination of white-brain lesion and cerebral infarction is determined; if TC is less than 0.615.

For the above applications, preferably, the content of glucosylceramide is F2, the content of tomatidine is F4, the TC value is calculated according to TC = -5.4480 + 1.4507 XF 2+ 2.7045 XF 4, and if TC is greater than or equal to 0.507, the combination of leukoencephalopathy and cerebral infarction is judged; if TC is less than 0.507, the disease is white brain lesion.

For the above applications, preferably, the content of glucosylceramide is F2, the content of phosphatidylserine is F5, the TC value is calculated according to TC = -1.1960 + 1.1011 XF 2-0.0837 XF 5, and if the TC is more than or equal to 0.541, the combination of white brain lesion and cerebral infarction is judged; if TC is less than 0.541, the patient is a white brain disease.

The application is preferably that the content of glucosylceramide is F2, the content of decanoyl carnitine is F6, the TC value is calculated according to TC = -1.49895+1.24498 XF 2+0.02589 XF 6, and if the TC is more than or equal to 0.523, the combination of leukoencephalopathy and cerebral infarction is judged; if TC is less than 0.523, the disease is white brain lesion.

The use as described above, preferably, the detection reagent is suitable for patients with leukoencephalopathy.

The invention has the beneficial effects that:

the invention provides a model for distinguishing the cerebral infarction combined leukoencephalopathy by using a novel molecular marker, which can be applied to a detection kit for early detection, diagnosis and prediction of the cerebral infarction combined leukoencephalopathy.

The biomarker for diagnosing the cerebral infarction of the patient with the leukoencephalopathy, provided by the invention, is a combination of any two of glucosylceramide and beta-hydroxyethyl ethanolamine, tomatidine, phosphatidylserine or decanoyl carnitine, and is used for predicting the cerebral infarction risk of the patient with the leukoencephalopathy according to a TC value by combining the contents of any two of beta-hydroxyethyl ethanolamine, tomatidine, phosphatidylserine or decanoyl carnitine in blood according to the content of the glucosylceramide, so that the diagnosis of whether the patient with the leukoencephalopathy has the tendency to suffer from the cerebral infarction is facilitated, and the diagnosis can be used for preventing in advance.

Drawings

FIG. 1 is a sample of VIP >1 in positive ion mode;

FIG. 2 is a sample of VIP >1 in negative ion mode;

FIG. 3 is a score plot of (O) PLS-DA in positive ion mode;

FIG. 4 is a score plot of (O) PLS-DA in negative ion mode;

FIG. 5 is a diagram of S-plot in positive ion mode;

FIG. 6 is a diagram of S-plot in negative ion mode;

FIG. 7 is a ROC curve based on a logistic regression model (variables F2+ F3);

FIG. 8 is a ROC curve based on a logistic regression model (variables F2+ F4);

FIG. 9 is a ROC curve based on a logistic regression model (variables F2+ F5);

FIG. 10 is a ROC curve based on a logistic regression model (variables F2+ F6).

Detailed Description

The following examples are intended to further illustrate the invention but should not be construed as limiting it. Modifications and substitutions may be made thereto without departing from the spirit and scope of the invention.

Unless otherwise indicated, the technical means used in the examples are conventional means well known to those skilled in the art, and the reagents used in the present invention are of analytical purity or above, wherein ultra performance liquid chromatography is used: UPLC; the model is as follows: ACQUITY UPLC I-Class System, manufacturer: waters, Manchester, UK; analysis and identification software: prognesis QI, manufacturer: waters.

Example 1

1. Sample pretreatment

Selecting a patient population: high signals appear in white matter for MRI nuclear magnetic detection, and 48 patients are sent to doctors due to acute cerebral infarction: 1: 1, age range: 45 or more.

Control population: high signal appears in white matter for MRI nuclear magnetic detection, no history of cerebral infarction, 54 people in total, male and female proportion: 1: 1, age range: 45 or more.

Collected serum samples of the above population were thawed on ice, 200 μ L of serum was extracted with 600 μ L of pre-cooled isopropanol, vortexed with a vortex shaker (model MX-S, Scilogex, usa) for 1min, incubated at room temperature for 10min, the extraction mixture was then stored overnight at-20C, centrifuged at 4000r in a refrigerated centrifuge (model D3024R, Scilogex, usa) for 20min, the supernatant was transferred to a new centrifuge tube, diluted to 1: 10. the samples were stored at-80C prior to LC-MS analysis. In addition, a pooled serum sample was also prepared by combining 10 μ L of each extraction mixture.

Wherein the reagents used in the present invention: isopropanol, acetonitrile, formic acid, ammonium formate, leucine enkephalin and sodium formate, wherein the manufacturers are Fisher.

2. Ultra-high performance liquid chromatography-mass spectrometry combined method for lipidomics

The samples were analyzed by ACQUITY UPLC (Waters, USA) connected to an ESI-bearing Xevo-G2XS high-resolution time of flight (QTOF) mass spectrometer (ESI-QTOF/MS; model: Xevo G2-S Q-TOF; manufacturer: Waters, Manchester, UK). A CQUITY UPLC BEH C18 column (2.1X 100 mM, 1.7 μm, Waters) was used with mobile phases of 10 mM ammonium formate-0.1% formic acid-acetonitrile (A, 60: 40, v/v) and 10 mM ammonium formate-0.1% formic acid-isopropanol-acetonitrile (B, 90: 10, v/v). Prior to large scale studies, pilot experiments including 10, 15 and 20 minute elution periods were performed to assess the potential impact of mobile phase composition and flow rate on lipid retention time. In PIM, abundant lipid precursor ions and fragments are separated in the same order, with similar peak shapes and ionic strengths. In addition, the mixed QC samples with 10 minute elution periods also showed similar basal peak intensities of precursors and debris as the test samples. The flow rate of the mobile phase was 0.4 mL/min. The column was initially eluted with 40% B, then a linear gradient to 43% B in 2 minutes, then increasing the percentage of B to 50% in 0.1 min. In the next 3.9 minutes, the gradient further increased to 54% B, then the amount of B increased to 70% in 0.1 minutes. In the final part of the gradient, the amount of B increased to 99% in 1.9 min. Finally, solution B returned to 40% in 0.1min and the column was equilibrated for 1.9 min before the next injection. The sample injection amount is 5 mu L each time, and a Xevo-G2XS QTOF mass spectrometer is used for detecting the lipid under positive and negative modes, wherein the collection range is m/z 50-1200 years, and the collection time is 0.2 s/time. The ion source temperature is 120 ℃, the desolventizing temperature is 600 ℃, the gas flow is 1000L/h, and nitrogen is used as flowing gas. The capillary voltage was 2.0kV (+)/cone voltage was 1.5kV (-), and the cone voltage was 30V. Standard mass measurements were performed with leucine enkephalin, calibrated with sodium formate solution. Samples were randomly ordered. One QC sample was injected every 10 samples and analyzed to investigate the reproducibility of the data.

Data acquisition was performed using data acquisition software (MassLynx4.1; manufacturer: Waters), results analysis:

3. method for searching serum difference substance by using multivariate statistics

Mass spectral data were converted into statistical data form using Progenesis QI and orthogonal partial least squares discriminant analysis (OPLS-DA) combined with Orthogonal Signal Correction (OSC) and PLS-DA (partial minimum discriminant analysis) methods to screen for differential variables by removing irrelevant differences. As shown in figure 1 and figure 2, VIP value is a variable importance projection of a PLS-DA first main component, VIP >1 is generally taken as a metabonomic common judgment standard and is taken as one of the standards for differential metabolite screening; fig. 3 and 4 are scoring graphs obtained by dimension reduction of the first principal component and the second principal component in two groups, namely, a leukoencephalopathy group (represented by WML) and a leukoencephalopathy-combined-cerebral-infarction group (represented by WS), wherein the abscissa represents the difference between groups, the ordinate represents the difference in groups, and the results of the two groups are better separated. Fig. 5 and 6 are S-plot diagrams, in which the abscissa represents the co-correlation coefficient between the principal component and the metabolite, and the ordinate represents the correlation coefficient between the principal component and the metabolite, and the positive ion mode has 171 difference impurities and the negative ion mode has 47 difference impurities, while satisfying p <0.05 and VIP > 1.

4. Jode index analysis

To further narrow the range, VIP threshold was increased to 2, while showing a fold difference between normal and patient of less than 0.83 fold, or more than 1.2 fold, with P values less than 0.01, to finally give the following 6 compounds, as detailed in table 1.

They were then subjected to the calculation of youden joden index to reflect the diagnosis and prediction effect of individual indices on the whole, and the area under the curve (AUC), specificity and sensitivity results of individual metabolites predicting white brain lesions are shown in table 1.

TABLE 1 analysis of Johnson index of lipid associated with leukoencephalopathy and cerebral infarction

Numbering	Compound Chinese name	AUC value	Sensitivity of the composition	Specificity of
					F1	Phosphatidylinositol (22:0/19:0)	0.850	0.8	0.8
F2	Glucosylceramide (d18:0/24:1(15Z))	0.727	0.6	0.8
					F3	Beta-hydroxyethylethanolamine	0.719	0.66	0.7
F4	Tomato alkali	0.669	0.88	0.46
					F5	Phosphoesterylserine (22:6/20:1)	0.663	0.98	0.32
F6	Decanoyl carnitine	0.651	0.68	0.58

5. Ten-fold cross validation result of internal population

In order to improve the biological diagnosis effect of the variable-quantity compound, a proper model needs to be found according to the biomarkers for further analysis.

And randomly dividing the internal population into 10 parts, selecting 1 part as a verification set, and selecting the others as training sets, repeating the steps for ten times, and investigating the optimal variable combination. The secondary results, including AUC, sensitivity, specificity, were averaged and statistically significant calculated as shown in table 2 below:

TABLE 2

Combination of	Logistic regression AUC	Sensitivity of the composition	Specificity of
				F2+F3	0.8	1	1
F2+F4	0.849	1	1
				F2+F5	0.813	1	1
F2+F6	0.809	1	1

There was no significant p <0.05 difference in AUC values between combinations.

The logistic regression model A, B, C, D was built based on the above as follows:

the "model a" variable was F2+ F3, the TC value was calculated according to the formula TC = -0.4782 + 0.8007 xf 2-0.4380 xf 3, where F2 is glucosyl ceramide (d18:0/24:1(15Z)), F3 is β -hydroxyethylethanolamine, and the risk of cerebral infarction in patients with leukosis was predicted from the TC value: if TC is more than or equal to 0.615, judging the leukoencephalopathy and cerebral infarction; if TC is less than 0.615, the disease is white brain lesion.

The "model B" variable was F2+ F4, the TC value was calculated according to the formula TC = -5.4480 + 1.4507 × F2+ 2.7045 × F4, where F2 is glucosyl ceramide (d18:0/24:1(15Z)), F4 is tomatidine, and the risk of cerebral infarction in patients with leukoencephalopathy was predicted from the TC value: if TC is more than or equal to 0.507, judging the leukoencephalopathy and cerebral infarction; if TC is less than 0.507, the disease is white brain lesion.

The "model C" variable was F2+ F5, the TC value was calculated according to the formula TC = -1.1960 + 1.1011 × F2-0.0837 × F5, where F2 is glucosyl ceramide (d18:0/24:1(15Z)), F5 is phosphatidylserine (22:6/20:1), and the risk of cerebral infarction in patients with leukosis was predicted from the TC value: if TC is more than or equal to 0.541, the patient is judged to have leukoencephalopathy and cerebral infarction; if TC is less than 0.541, the patient is a white brain disease.

The "model D" variable was F2+ F6, the TC value was calculated according to the formula TC = -1.49895+1.24498 × F2+0.02589 × F6, where F2 is glucosyl ceramide (D18:0/24:1(15Z)), F6 decanoyl carnitine, and the risk of cerebral infarction in patients with leukosis was predicted from the TC value: if TC is more than or equal to 0.523, judging the leukoencephalopathy and cerebral infarction; if TC is less than 0.523, the disease is white brain lesion.

Example 2

Model validation the sample population 168 (external population) was subjected to logistic regression model validation, in which patients with MRI nuclear magnetic detection had high signal in white matter and had no history of cerebral infarction 74; 94 persons presenting high signal in white brain matter and being sent to medicine due to acute cerebral infarction were tested for the contents of F2, F3, F4, F5 and F6 as in example 1 to verify the accuracy of the model results in example 1, and corresponding ROC curves were plotted, with the following results:

the variables of the "model a" are F2+ F3, and the ROC graph results are shown in fig. 7, Sensitivity =1, Specificity =1, and Accuracy = 1.

The "model B" variables were F2+ F4, and the ROC graph results are shown in fig. 8, Sensitivity =1, Specificity =1, and Accuracy = 1.

The "model C" variable is F2+ F5, and the ROC graph results are shown in fig. 9, Sensitivity =1, Specificity =1, and Accuracy = 1.

The "model D" variable is F2+ F6, and the ROC graph results are shown in fig. 10, Sensitivity =1, Specificity =1, and Accuracy = 1.

And (3) displaying data: f2 is glucosyl ceramide (d18:0/24:1(15Z)) per se, and any one of other four biomarkers, namely beta-hydroxyethyl ethanolamine, tomatidine, phosphatidylserine (22:6/20:1) and decanoyl carnitine, shows very high diagnostic capability, and can be applied to clinical kits in the future.

Therefore, the method is adopted to process the serum sample of the patient and carry out detection, the measured data is substituted into the model, and the logical regression model is utilized to judge whether the white matter patient has the risk of cerebral infarction.

Claims

1. Application of biomarker glucosylceramide combined with beta-hydroxyethyl ethanolamine, tomatidine, phosphatidylserine or decanoyl carnitine in preparation of detection reagent for diagnosing cerebral infarction of patients with leukoencephalopathy.

2. The use of claim 1, wherein glucosylceramide is combined with β -hydroxyethylethanolamine, tomatidine, phosphatidylserine or decanoylcarnitine to determine whether there is a risk of a leukoencephalopathy developing a cerebral infarction.

3. The use according to claim 2, wherein the content of glucosylceramide is denoted as F2, the content of β -hydroxyethylethanolamine is denoted as F3, the TC value is calculated according to TC = -0.4782 + 0.8007 xf 2-0.4380 xf 3, and if TC is greater than or equal to 0.615, then it is determined that leukoencephalopathy is associated with cerebral infarction; if TC is less than 0.615, the disease is white brain lesion.

4. The use of claim 2, wherein the content of glucosylceramide is denoted as F2, the content of tomatidine is denoted as F4, the TC value is calculated according to TC = -5.4480 + 1.4507 xf 2+ 2.7045 xf 4, and if TC is greater than or equal to 0.507, the combination of leukoencephalopathy and cerebral infarction is judged; if TC is less than 0.507, the disease is white brain lesion.

5. The use according to claim 2, wherein the content of glucosylceramide is denoted as F2, the content of phosphatidylserine is denoted as F5, the TC value is calculated according to TC = -1.1960 + 1.1011 xf 2-0.0837 xf 5, and if TC is greater than or equal to 0.541, the combination of white-brain lesion and cerebral infarction is judged; if TC is less than 0.541, the patient is a white brain disease.

6. The use according to claim 2, wherein the content of glucosylceramide is denoted as F2, the content of decanoylcarnitine is denoted as F6, the TC value is calculated from TC = -1.49895+1.24498 xf 2+0.02589 xf 6, and if TC is equal to or greater than 0.523, a leukoencephalopathy with cerebral infarction is judged; if TC is less than 0.523, the disease is white brain lesion.

7. The use of claim 2, wherein the detection reagent is suitable for use in a patient with a leukoencephalopathy.