Sphingolipid metabolic marker, analysis method therefor and use thereof

Abstract

Disclosed in the present invention are a sphingolipid metabolic marker, an analysis method therefor and a use thereof. The sphingolipid metabolic marker can be effectively used for early diagnosis, course monitoring and prognosis assessment of asthma, and has the advantages of high sensitivity, rapidness, convenience and accurate and reliable result. The sphingolipid metabolic marker at least comprises one of the following substances: galactosylceramide d18:1 / 16:0 and galactosylceramide d18:1 / 14:0.

Description

Sphingolipid metabolism markers and their analysis methods and applications Technical Field

[0001] The present invention relates to the technical field of biomedical testing, and in particular to a sphingolipid metabolism marker, an analysis method for the sphingolipid metabolism marker, and an application of the sphingolipid metabolism marker in dynamic monitoring of the course of asthma. Background Art

[0002] Bronchial asthma (asthma) is a common chronic respiratory disease characterized by airway inflammation and hyperresponsiveness that seriously endangers human health. In recent years, its incidence has continued to rise worldwide, affecting more than 300 million people worldwide, and more than 300,000 people die from asthma each year. There are nearly 50 million asthma patients in China, and the asthma mortality rate is much higher than in developed countries. Early diagnosis, disease course monitoring, and standardized treatment of asthma play an important role in improving asthma control and improving patients' quality of life.

[0003] Currently, the main diagnosis of asthma includes blood cell analysis, lung function monitoring and allergen detection, combined with clinical symptoms such as wheezing, shortness of breath, chest tightness or cough. Pathological staging and grading diagnosis do not have biochemical indicators and rely solely on clinical manifestations. It is worth noting that these methods are only measures taken after the onset of asthma and cannot predict the risk of the disease, and there is a serious lag. Therefore, a novel, non-invasive, and easy-to-detect dynamic monitoring marker that runs through diagnosis, staging, grading, and prognosis is of vital importance for early risk warning, disease course management, and prognosis assessment of asthma.

[0004] Metabolomics can sensitively and comprehensively measure changes in endogenous metabolites during physiological and pathological states. It can systematically study the relationship between disease and metabolite composition in the body, facilitating a comprehensive understanding and evaluation of disease states and the discovery of new biomarkers. Therefore, metabolomics has enormous clinical value in disease diagnosis, risk prediction, and prognosis assessment.

[0005] Summary of the Invention

[0006] In order to overcome the defects of the prior art, the technical problem to be solved by the present invention is to provide a sphingolipid metabolism marker that can be effectively used for the early diagnosis, disease course monitoring and prognosis evaluation of asthma, with high sensitivity, rapidity and convenience, and accurate and reliable results.

[0007] The technical solution of the present invention is that the sphingolipid metabolism marker includes at least one of the following substances: galactosylceramide d18:1 / 16:0 and galactosylceramide d18:1 / 14:0.

[0008] The analysis method of sphingolipid metabolism markers was performed by logistic regression analysis to obtain the fitted regression curve: Y = Logit (p) = 37.604a-1116.674b+44.959c-2.948d+181.759e+0.439f-3.741

[0009] Where Y is the diagnosis probability, Logit(p) is the logistic regression function, and af are the concentration ratios of sphingosine 1-phosphate, phosphorylated ceramide sphingolipid d18:1 / 14:1, sphingolipid d18:1 / 16:0, sphingolipid d18:1 / 18:0, sphingolipid d18:1 / 20:0, and sphingolipid d18:1 / 24:1 to sphingolipid d18:1 / 24:0, respectively.

[0010] The sphingolipid metabolic markers and analysis methods of the present invention can be effectively used for the early diagnosis, disease course monitoring and prognosis evaluation of asthma. They are highly sensitive, rapid and convenient, and the results are accurate and reliable. They can be used for multiple monitoring of asthma patients during the clinical control period, chronic persistent period and acute attack period, providing a basis for clinical decision-making and a certain foundation for subsequent basic research and clinical research. They have great application and research value.

[0011] Also provided is the application of sphingolipid metabolism markers for dynamic monitoring of the course of asthma.

[0012] Also provided are chips, test strips or kits for dynamically monitoring the course of asthma using sphingolipid metabolic markers to obtain ratio levels between metabolites in biological samples of test subjects and to determine the disease status of asthma in the test subjects. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] FIG1 shows a basic flow chart of the asthma metabolomics study of the present invention.

[0014] Figure 2 shows the results of high-resolution mass spectrometry of a sample according to one embodiment of the present invention. Figure 2A shows the total ion current of a full scan of positive ions obtained by high-resolution mass spectrometry of the sample; Figure 2B shows the total ion current of a full scan of negative ions obtained by high-resolution mass spectrometry of the sample; Figure 2C shows the corresponding accurate mass and molecular formula of a sphingolipid (d18:1 / 24:0) obtained by high-resolution mass spectrometry of the sample; and Figure 2D shows a chromatogram of a sphingolipid (d18:1 / 24:0) obtained by high-resolution mass spectrometry of the sample.

[0015] Figure 3 shows the PCA and OPLS-DA model score graphs of the healthy control group and the asthma group in one embodiment of the present invention. Figure 3A is a PCA model score graph, where circles represent the healthy control group and diamonds represent the asthma group. Figure 3B is a three-dimensional stereogram of PCA, where light-colored balls represent the healthy control group and dark-colored balls represent the asthma group. It can be clearly seen from the above figures that the model can clearly distinguish healthy people from asthma patients. Figure 3C is an OPLS-DA model score graph, where circles represent the healthy control group and diamonds represent the asthma group. The results show that HC (healthy control) and asthma patients can be significantly distinguished.

[0016] FIG4 shows a differential metabolic pathway diagram of asthma.

[0017] FIG5 shows the structures of sphingolipid metabolites.

[0018] Figure 6 shows the MRM extraction profiles of target sphingolipid metabolites and internal standards in a pooled human plasma sample.

[0019] FIG7 shows the standard curve of target sphingolipid metabolites based on the standard addition method.

[0020] FIG8 shows the regression curves and ROC analysis results of multiple metabolic markers fitted based on sphingolipid ratios obtained through logistic regression analysis.

[0021] Figure 9 shows the changes in target sphingolipid metabolites in self-control patients in the stable asthma stage (S) and severe asthma stage (A) (biomarkers such as sphingolipid d18:1 / 20:0, sphingolipid d18:1 / 18:0, sphingolipid d18:1 / 16:0, and sphingolipid d18:1 / 24:1 were all upregulated in the acute phase). DETAILED DESCRIPTION

[0022] This sphingolipid metabolism marker includes at least one of the following substances: galactosylceramide d18:1 / 16:0 and galactosylceramide d18:1 / 14:0.

[0023] Preferably, the sphingolipid metabolic markers further include 1-phosphate sphingosine, phosphorylated ceramide sphingolipid d18:1 / 14:1, sphingolipid d18:1 / 20:0, sphingolipid d18:1 / 18:0, sphingolipid d18:1 / 16:0, sphingolipid d18:1 / 24:1 and their respective concentration ratios to sphingolipid d18:1 / 24:0 obtained by targeted metabolomics screening. Specifically, the sphingolipid metabolic markers further include at least one of the following: 1-phosphate sphingosine, phosphorylated ceramide sphingolipid d18:1 / 14:1, sphingolipid d18:1 / 20:0, sphingolipid d18:1 / 18:0, sphingolipid d18:1 / 16:0, sphingolipid d18:1 / 24:1, the concentration ratio of 1-phosphate sphingosine to sphingolipid d18:1 / 24:0, phosphorylated ceramide sphingolipid The concentration ratio of d18:1 / 14:1 to sphingolipid d18:1 / 24:0, the concentration ratio of sphingolipid d18:1 / 20:0 to sphingolipid d18:1 / 24:0, the concentration ratio of sphingolipid d18:1 / 18:0 to sphingolipid d18:1 / 24:0, the concentration ratio of sphingolipid d18:1 / 16:0 to sphingolipid d18:1 / 24:0, and the concentration ratio of sphingolipid d18:1 / 24:1 to sphingolipid d18:1 / 24:0.

[0024] The analysis method of sphingolipid metabolism markers was performed by logistic regression analysis to obtain the fitted regression curve: Y = Logit (p) = 37.604a-1116.674b+44.959c-2.948d+181.759e+0.439f-3.741

[0025] Where Y is the diagnosis probability, Logit(p) is the logistic regression function, and af are the concentration ratios of sphingosine 1-phosphate, phosphorylated ceramide sphingolipid d18:1 / 14:1, sphingolipid d18:1 / 16:0, sphingolipid d18:1 / 18:0, sphingolipid d18:1 / 20:0, and sphingolipid d18:1 / 24:1 to sphingolipid d18:1 / 24:0, respectively.

[0026] The sphingolipid metabolic markers and analysis methods of the present invention can be effectively used for the early diagnosis, disease course monitoring and prognosis evaluation of asthma. They are highly sensitive, rapid and convenient, and the results are accurate and reliable. They can be used for multiple monitoring of asthma patients during the clinical control period, chronic persistent period and acute attack period, providing a basis for clinical decision-making and a certain foundation for subsequent basic research and clinical research. They have great application and research value.

[0027] Also provided is the application of sphingolipid metabolism markers for dynamic monitoring of the course of asthma.

[0028] Also provided are chips, test strips or kits for dynamically monitoring the course of asthma using sphingolipid metabolic markers to obtain ratio levels between metabolites in biological samples of test subjects and to determine the disease status of asthma in the test subjects.

[0029] Preferably, the biological sample is a blood-derived biological sample such as plasma, serum, whole blood, dried whole blood spots, or dried plasma spots.

[0030] Preferably, the metabolite level in the biological sample of the test subject is obtained by one or more of the following methods: chromatography, spectroscopy, mass spectrometry, chemical analysis, and immunoassay.

[0031] Preferably, the chromatography includes high performance liquid chromatography, thin layer chromatography, and gas chromatography; the spectroscopy includes nuclear magnetic resonance spectroscopy, refractive index spectroscopy, ultraviolet spectroscopy, and near-infrared spectroscopy; the chemical analysis includes electrochemical analysis and radiochemical analysis; the mass spectrometry is triple quadrupole mass spectrometry, and the method for rapid quantitative detection of metabolic markers by mass spectrometry is to first use a chromatographic column for gradient elution, and then collect data in the electrospray ion source ESI positive ion MRM mode. In the mass spectrometry, positive ion scanning is used, and all metabolic markers and internal standards are analyzed by one injection for detection.

[0032] Preferably, the biological sample is pretreated before detection as follows: accurately aspirate 80 μL of plasma or serum, add 10 μL of internal standard working solution, add 480 μL of isopropanol / methanol solution, 9:1, v / v, precipitate protein, vortex for 10 minutes, centrifuge at 12000 rpm for 10 minutes, take the supernatant, vacuum concentrate and evaporate to dryness, reconstitute with 80 μL of methanol, vortex for 10 minutes, and centrifuge at 12000 rpm for 15 minutes to obtain the test solution for quantitative analysis.

[0033] Preferably, 15-50 μL of human whole blood is aspirated and dropped onto a dried blood spot collection card, and dried at room temperature for 1-4 hours until the color turns dark red to obtain a dried blood spot sample; one or more dried blood spot samples with a diameter of 3-8 mm are removed from the dried blood spot using a punch; the dried blood spot sample is added to a solid phase extraction column with phospholipid / protein removal function, and eluted using an organic reagent containing 5%-50% water.

[0034] The embodiments of the present invention are described in detail below.

[0035] Example 1

[0036] Non-targeted metabolomics technology was used to screen markers and enrich metabolic pathways between asthma patients and healthy subjects.

[0037] 1. Sample source:

[0038] After approval by the Ethics Committee of the China-Japan Friendship Hospital, plasma samples were collected from 100 HCs (healthy controls), 154 stable asthma patients, and 112 severe asthma patients. All participants were from the China-Japan Friendship Hospital, and all asthma patients were diagnosed with bronchial asthma after evaluation by clinicians based on the "Guidelines for the Prevention and Treatment of Bronchial Asthma (2020 Edition)", and a history of respiratory diseases such as tuberculosis, pulmonary fibrosis, and chronic obstructive pulmonary disease was excluded. The age and gender of HCs were matched with those of asthma patients to exclude metabolic differences caused by gender and age. Plasma was collected in the early morning on an empty stomach. All samples were stored at -80°C until use.

[0039] 2. Main reagents:

[0040] LC / MS-grade acetonitrile was purchased from Merck, HPLC-grade methanol was purchased from Merck, and formic acid was purchased from CNW. All other reagents were of commercial analytical grade. Deionized water was prepared using a Milli-Q ultrapure water system from Millipore.

[0041] 3. Research Methods

[0042] 3.1 Sample preparation:

[0043] Sample pretreatment: 20 μL of plasma (healthy control group, stable asthma group, and severe asthma group) was collected and added to 180 μL of precipitant containing internal standard (methanol:acetonitrile = 1:1). The mixture was vortexed for 3 min and centrifuged at 13,000 rpm for 10 min. 100 μL of the sample was collected for non-targeted metabolomics analysis.

[0044] 3.2 Chromatographic / mass spectrometry conditions:

[0045] The results were detected by high-resolution mass spectrometer QE-Orbitrap. The mobile phases were: A was an aqueous solution containing 0.1% formic acid and 2.5 mmol / L ammonium formate, and D was acetonitrile. The gradient elution program for sample determination was as follows: 0-1.0 min, 95% A; 1.0-5.0 min, 95%-40% A; 5.0-8.0 min, 40%-0% A; 8.0-11.0 min, 0% A; 11.0-14.0 min, 0%-40% A; 14.0-15.0 min, 40%-95% A; 15.0-18.0 min, 95% A, analysis time 0-18 min, 5 μL injection each time, flow rate 0.25 mL / min, chromatographic column: ACQUITY BEH C18 1.7 μm, 2.1×50 mm, column temperature 30°C, and the temperature of the autosampler was maintained at 4°C. Data were collected in positive and negative ion modes using an electrospray ionization (ESI) source with a spray voltage of 3000 V, an evaporation temperature of 350°C, a capillary temperature of 350°C, an S-lens RF of 50, a full scan resolution of 70,000, and a scan range of 70–1050 m / z. The data-dependent second-stage MS / dd-MS2 scan (MS / DD-MS2) had a resolution of 17,500, an AGC target of 1e5, a maximum time interval of 50 ms, and NCEs of 20, 40, and 60. The ultra-high-resolution mass spectrometry results are shown in Figure 2.

[0046] 3.3 Metabolic pathway analysis:

[0047] Metaboanalyst 5.0 was used to analyze the differences in endogenous metabolites in plasma (healthy control group, stable asthma group, and severe asthma group), and endogenous metabolites with VIP values ​​> 1, P values ​​< 0.05, and Foldchange (FC) > 1.5 or < 0.5 were identified. Pathway Analysis in the MetaboAnalyst 5.0 website was then used to analyze the differential metabolic pathways in bone marrow tissue and bone marrow supernatant, and metabolic pathways with impact values ​​greater than 0.1 were selected as the main differential metabolic pathways in asthma.

[0048] 4. Data processing and statistical analysis:

[0049] Endogenous metabolites were identified using high-resolution mass spectrometry (mzCloud) to obtain the exact mass of each endogenous metabolite to five decimal places. Each endogenous metabolite was identified by its molecular formula. A previously established database of over 1,200 endogenous metabolites (including carbohydrates, lipids, fatty acids, and amino acids) was then used with Tracefinder software. Peak areas of corresponding endogenous metabolites were automatically matched to the Tracefinder database. MetaboAnalyst 5.0 was then used to analyze the data and create an OPLS-DA model to identify differences in metabolic patterns and significant categorical trends between healthy individuals and asthmatics. Finally, differential metabolic markers were selected based on criteria such as VIP > 1, P < 0.05, and FC > 1.5 or < 0.5.

[0050] 5. Results:

[0051] Principal component analysis (PCA) was calculated using the MetaboAnalyst 5.0 website. PCA (Figures 3A and 3B) revealed differences in plasma between the healthy control group and the asthma group, while OPLS-DA (Figure 3C) demonstrated complete separation between the two groups. Endogenous substances with a VIP > 1, a P value less than 0.05, and a FC > 1.5 or < 0.5 were selected for further analysis of the major differential metabolic pathways in asthma patients. Table 1 shows the rate of change of differentially expressed metabolites in asthma, obtained using the OPLS-DA model. The results show a total of 29 differentially expressed metabolites. Compared with the healthy control group, the proportions of 10 endogenous substances in the asthma group were primarily increased, while the proportions of the other 19 showed a primarily decreased trend. These results suggest that asthma affects the metabolism and secretion of endogenous substances in plasma, leading to significant changes in their levels, primarily in lipids. Among these, the areas under the receiver operating characteristic (ROC) curves for galactosylceramide d18:1 / 16:0 and galactosylceramide d18:1 / 14:0 were as high as 0.97. The detailed structures are shown in Figure 5.

[0052] Table 1

[0053] Study on differences in metabolic pathways of endogenous substances:

[0054] Figure 4 shows the metabolic pathways of asthma analyzed using MetaboAnalyst 5.0. Table 3 shows that there are five metabolic pathways with significant differences between the healthy control group and the asthma group, with Impact values ​​greater than 0.1. This indicates that the pathways affected by both groups primarily include sphingolipid metabolism. The analysis results indicate that asthma affects the metabolism and synthesis of sphingolipids, leading to changes in the content of endogenous substances in the patients' bodies. Therefore, metabolites in the sphingolipid metabolic pathway were ultimately selected as targets for distinguishing healthy individuals from asthma patients for targeted metabolomics analysis.

[0055] Table 2

[0056] Example 2

[0057] Validation of markers between asthma patients and healthy subjects using targeted sphingolipid metabolomics analysis.

[0058] (1) Sample collection:

[0059] Plasma samples were collected from 100 HC (healthy controls), 98 stable asthma patients, and 94 severe asthma patients. All participants were from the China-Japan Friendship Hospital. Asthma patients were diagnosed with bronchial asthma after evaluation by clinicians based on the "Guidelines for the Prevention and Treatment of Bronchial Asthma (2020 Edition)", and a history of respiratory diseases such as tuberculosis, pulmonary interstitial fibrosis, and chronic obstructive pulmonary disease was excluded. The age and gender of HC were matched with those of asthma patients to exclude metabolic differences caused by gender and age. Blood was collected in the early morning on an empty stomach. Fasting plasma samples were collected from the subjects and stored in a -80°C refrigerator for future use.

[0060] (2) Sample testing:

[0061] 1. Instrument information:

[0062] Mass spectrometry: Clinical IVD Triple Quadrupole LC / MS System (K6460, Serial No.: SG1638K003, Agilent) equipped with an electrospray ionization (ESI) source. Liquid chromatography: 1200RRLC system ultra-high performance liquid chromatography. ORTEX-2GENE vortex mixer (Scientific Industry); METLER TOLEDO AG135 electronic balance (Mettler, Switzerland); Milli-Q ultrapure water system (No. 041572, Merck).

[0063] 2. Sample Pretreatment: Accurately pipette 80 μL of plasma or serum, add 10 μL of internal standard working solution, and precipitate proteins with 480 μL of isopropanol / methanol solution (9:1, v / v). Vortex for 10 minutes, centrifuge at 12,000 rpm for 10 minutes, remove the supernatant, evaporate to dryness under vacuum, reconstitute with 80 μL of methanol, vortex for 10 minutes, and centrifuge at 12,000 rpm for 15 minutes to obtain the test solution for quantitative analysis. Dried Blood Spot: Pipette 15-50 μL of human whole blood onto a dried blood spot collection card and dry at room temperature for 1-4 hours until the color turns deep red. Use a hole punch to remove one or more dried blood spot slabs with a diameter of 3-8 mm from the dried blood spot. Apply the dried blood spot slab to a solid-phase extraction cartridge with phospholipid / protein removal capabilities and elute with an organic reagent containing 5%-50% water.

[0064] 3. Instrument parameters:

[0065] Chromatographic conditions: The chromatographic column specifications were: Agilent Poroshell 300 SB-C8 (2.1×75 mm 5 μm), the column temperature was 40°C, the autosampler temperature was maintained at 4°C, the mobile phase A was water containing 0.1% formic acid and 1.0 mM ammonium acetate, and the mobile phase D was methanol. The mobile phase was gradient eluted from 40% D to 70% D from 0 to 2.0 min, from 70% D to 90% D from 2.0 to 8.0 min, and from 90% D to 96% D from 8.0 to 10.0 min. Each injection was 10 μL, and the flow rate was 0.4 mL / min.

[0066] Mass spectrometry conditions: electrospray ionization (ESI) positive ion detection mode, during data acquisition in MRM mode, the spray voltage was 2500-5000 V, the dryer temperature was 150-350°C, the sheath gas temperature was 250-400°C, the spray gas flow rate was 10-50 psi, the sheath gas flow rate was 5-20 L / min, the capillary temperature was 150-320°C, and the MRM ion pairs monitored the target sphingolipid metabolites.

[0067] (3) Result analysis:

[0068] 1. Standard curves and linear ranges of each sphingolipid metabolite

[0069] The structure diagram of sphingolipid metabolites determined by targeted metabolomics is shown in Figure 5, and the MRM extraction diagram of target sphingolipid metabolites and internal standards in mixed human plasma samples is shown in Figure 6. Matrix standards with a series of concentrations of each sphingolipid metabolite were added to the mixed plasma sample, and samples were continuously injected from low concentration to high concentration. The standard addition method was used to calculate the standard curve with the added concentration of each analyte as the horizontal axis (X) and the peak area of ​​the analyte minus the background peak area as the vertical axis (Y). The linear equation of the matrix standard curve and the linear correlation coefficient value R2 were obtained (Figure 7). The results showed that the peak areas of sphingosine 1-phosphate (S1P), sphingolipid d18:1 / 16:0 (Ceramide16:0), sphingolipid d18:1 / 18:0 (Ceramide18:0), sphingolipid d18:1 / 20:0 (Ceramide20:0), sphingolipid d18:1 / 22:0 (Ceramide22:0), sphingolipid d18:1 / 24:0 (Ceramide24:0), dihydrosphingolipid d18:0 / 24:0 (dhCeramide24:0), sphingolipid d18:1 / 24:1 (Ceramide24:1), and sphingolipid d18:1 / 26:0 (Ceramide26:0) were linearly correlated with their concentrations within their respective concentration ranges, with correlation coefficients R2 greater than 0.98 (Table 3).

[0070] Table 3

[0071] 2. Quality Control Sample Analysis

[0072] Mixed plasma samples were used as quality control samples: the intra-batch precision RSD of each sphingolipid tested was <12.45%; the inter-batch precision RSD was <13.25%, which met the quality control requirements for endogenous metabolite analysis (Table 4).

[0073] Table 4

[0074] 3. Analysis of Asthma-Related Human Serum Samples

[0075] The target sphingolipid metabolites in the plasma samples of healthy subjects (H), patients in the stable asthma stage (S), and patients in the severe asthma stage (A) were quantitatively analyzed. The measured plasma concentrations of the target sphingolipid metabolites in each group of samples are shown in Table 5. Further t-tests were performed on target sphingolipid metabolites between the groups. The results showed that sphingosine 1-phosphate (S1P), phosphorylated ceramide sphingolipid d18:1 / 14:1 (CeramideP14:1), sphingolipid d18:1 / 16:0 (Ceramide16:0), sphingolipid d18:1 / 18:0 (Ceramide18:0), sphingolipid d18:1 / 20:0 (Ceramide20:0), and sphingolipid d18:1 / 24:1 (Ceramide24:1) showed significant differences (p < 0.01) (Table 5). No significant differences were found in the t-tests for other sphingolipid metabolites (p > 0.05).

[0076] Further, a ROC curve was used to identify diagnostic biomarkers for severe asthma. Using SPSS software, the group was set as the state variable and the target sphingolipid metabolite concentration was used as the test variable. A larger test result indicated a more positive test. In large-scale data analysis, an area under the ROC curve greater than 0.7 was considered diagnostically sound. With asymptotic significance at p < 0.05, an area under the ROC curve greater than 0.65 was also considered diagnostically sound. The areas under the receiver operating characteristic (ROC) curves (AUCs) of sphingosine 1-phosphate (S1P), phosphorylated ceramide sphingolipid d18:1 / 14:1 (CeramideP14:1), sphingolipid d18:1 / 16:0 (Ceramide16:0), sphingolipid d18:1 / 18:0 (Ceramide18:0), sphingolipid d18:1 / 20:0 (Ceramide20:0), and sphingolipid d18:1 / 24:1 (Ceramide24:1) between the severe asthma stage (A) and the stable asthma stage (S) were calculated (Table 6).

[0077] The diagnostic ability of sphingolipid biomarkers in the severe asthma stage was evaluated based on the area under the ROC curve. Further comparisons were made: (1) ROC analysis of the biomarker concentration measured directly by the sample; (2) ROC analysis of the ratio of the biomarker concentration measured by the sample to the sphingolipid d18:1 / 24:0 (Ceramide 24:0) concentration. The summarized ROC analysis data are shown in Table 6. The results show that the ratio of the biomarker concentration to the sphingolipid 24:0 concentration can also be used as a biomarker indicating the severe asthma stage. Further logistic regression analysis was performed to obtain the regression curve of multiple metabolic markers fitted based on the ratio of sphingolipid markers to sphingolipid d18:1 / 24:0 concentrations: Y = Logit (p) = 37.604a-1116.674b+44.959c-2.948d+ The results were as follows: 181.759e+0.439f-3.741 (Y is the diagnosis probability, Logit(p) is the logistic regression function, and af are the concentration ratios of sphingosine 1-phosphate, phosphorylated ceramide sphingolipid d18:1 / 14:1, sphingolipid d18:1 / 16:0, sphingolipid d18:1 / 18:0, sphingolipid d18:1 / 20:0, and sphingolipid d18:1 / 24:1 to sphingolipid d18:1 / 24:0). After fitting, the area under the receiver operating characteristic (ROC) curve for the comparison between severe asthma (A) and stable asthma (S) was 0.811 (Figure 8), which increased the accuracy of asthma diagnosis.

[0078] Table 5

[0079] Table 6

[0080] Example 3

[0081] Specific case analysis.

[0082] This study included four self-control patients, that is, the same patients were in different states of stable asthma (S) and severe asthma (A). The results showed that the diagnostic biomarkers sphingolipid d18:1 / 16:0, sphingolipid d18:1 / 18:0, sphingolipid d18:1 / 20:0, and sphingolipid d18:1 / 24:1 were all upregulated in the severe asthma stage (A) of the four self-control patients ( Figure 9 ). Taken together, these results suggest that sphingolipid d18:1 / 16:0, sphingolipid d18:1 / 18:0, sphingolipid d18:1 / 20:0, and sphingolipid d18:1 / 24:1 can serve as biomarkers for dynamic monitoring of the course of asthma.

[0083] Example 4

[0084] In order to verify the detection effect of metabolic markers, the following group experiments were designed.

[0085] The same method as in Example 2 was used to perform 10 repeated tests on the plasma metabolite markers of 15 suspected asthma patients. The metabolite markers were grouped as follows:

[0086] 1) Sphingolipid d18:1 / 20:0 alone detection group;

[0087] 2) sphingolipid d18:1 / 18:0 alone detection group;

[0088] 3) sphingolipid d18:1 / 16:0 alone detection group;

[0089] 4) sphingolipid d18:1 / 24:1 alone detection group;

[0090] 5) Joint testing team.

[0091] Due to individual differences and instrument and reagent errors during the detection process, missed detections often occur during the actual detection of metabolite markers, resulting in adverse consequences such as delays in the patient's condition. Based on this, this example statistically analyzed the missed detection rates of the above five groups of metabolite detections. The specific results are shown in Table 7.

[0092] Table 7

[0093] As can be seen from Table 7, simultaneous detection of metabolic markers (sphingolipid composition) can effectively reduce the missed detection rate for asthma.

[0094] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention are still within the scope of protection of the technical solution of the present invention.

Claims

1. A sphingolipid metabolism marker, characterized in that: At least one of the following substances is included: galactosylceramide d18:1 / 16:0, galactosylceramide d18:1 / 14:

0.

2. The sphingolipid metabolism marker according to claim 1, characterized in that: The sphingolipid metabolic markers also include 1-phosphate sphingosine, phosphorylated ceramide sphingolipid d18:1 / 14:1, sphingolipid d18:1 / 20:0, sphingolipid d18:1 / 18:0, sphingolipid d18:1 / 16:0, sphingolipid d18:1 / 24:1 obtained by targeted metabolomics screening, and their concentration ratios to sphingolipid d18:1 / 24:

0.

3. The method for analyzing sphingolipid metabolism markers according to claim 2, characterized in that: The fitted regression curve obtained by Logistic regression analysis is: Y = Logit (p) = 37.604a-1116.674b + 44.959c-2.948d + 181.759e + 0.439f-3.741 Wherein, Y is the diagnosis probability, Logit(p) is the logistic regression function, and af are the concentration ratios of sphingosine 1-phosphate, phosphorylated ceramide sphingolipid d18:1 / 14:1, sphingolipid d18:1 / 16:0, sphingolipid d18:1 / 18:0, sphingolipid d18:1 / 20:0, sphingolipid d18:1 / 24:1 and sphingolipid d18:1 / 24:0, respectively.

4. The use of the sphingolipid metabolism marker according to claim 1 or 2, characterized in that: The sphingolipid metabolism marker is used for dynamic monitoring of the course of asthma.

5. The use of the sphingolipid metabolism marker according to claim 1 or 2, characterized in that: A chip, test strip or kit used for dynamic monitoring of the course of asthma obtains the ratio level between metabolites in the biological sample of the test subject and is used to determine the disease condition of asthma in the test subject.

6. The use of the sphingolipid metabolism marker according to claim 5, characterized in that: The biological sample is plasma, serum, whole blood, dried whole blood spots, or dried plasma spots.

7. The use of the sphingolipid metabolism marker according to claim 6, characterized in that: The metabolite level in the biological sample of the test subject is obtained by one or more of the following methods: chromatography, spectroscopy, mass spectrometry, chemical analysis, and immunoassay.

8. The use of the sphingolipid metabolism marker according to claim 7, characterized in that: The chromatography includes high performance liquid chromatography, thin layer chromatography, and gas chromatography; the spectroscopy includes nuclear magnetic resonance spectroscopy, refractive index spectroscopy, ultraviolet spectroscopy, and near infrared spectroscopy; the chemical analysis includes electrochemical analysis and radiochemical analysis; the mass spectrometry is triple quadrupole mass spectrometry, and the method of rapid quantitative detection of metabolic markers by mass spectrometry is to first use a chromatographic column for gradient elution, and then collect data in the electrospray ion source ESI positive ion MRM mode. In the mass spectrometry, positive ion scanning is used, and all metabolic markers and internal standards are analyzed by one injection for detection.

9. The use of the sphingolipid metabolism marker according to claim 7, characterized in that: The biological sample was pretreated before detection as follows: 80 μL plasma or serum was accurately aspirated, 10 μL internal standard working solution was added, 480 μL isopropanol / methanol solution was added, 9:1, v / v, protein was precipitated, vortexed for 10 min, centrifuged at 12000 rpm for 10 min, the supernatant was taken, vacuum concentrated and evaporated, reconstituted with 80 μL methanol, vortexed for 10 min, centrifuged at 12000 rpm for 15 min, and the test solution was obtained for quantitative analysis.

10. The use of the sphingolipid metabolism marker according to claim 7, characterized in that: 15-50 μL of human whole blood is dropped onto a dried blood spot collection card and dried at room temperature for 1-4 hours until the color changes to dark red to obtain a dried blood spot sample; one or more dried blood spot samples with a diameter of 3-8 mm are taken from the dried blood spot using a puncher; the dried blood spot sample is added to a solid phase extraction column with a phospholipid / protein removal function, and eluted with an organic reagent containing 5%-50% water.

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