CN115754067A

CN115754067A - Application of detection reagent of myristoyl lysophosphatidylcholine in preparation of product for diagnosing CAP

Info

Publication number: CN115754067A
Application number: CN202211475107.2A
Authority: CN
Inventors: 高红昌; 熊芬; 李玉苹; 南文纲; 张茜; 李晨
Original assignee: Wenzhou Medical University
Current assignee: Wenzhou Medical University
Priority date: 2022-11-23
Filing date: 2022-11-23
Publication date: 2023-03-07
Anticipated expiration: 2042-11-23
Also published as: CN115754067B

Abstract

The invention relates to the fields of metabonomics analysis and clinical medicine, in particular to an application of a detection reagent of myristoyl lysophosphatidylcholine in preparation of a product for diagnosing CAP. Obtaining a plasma sample from a subject; determining the level of myristoyl lysophosphatidylcholine (LPC 14); wherein the predetermined reference value is based on an average LPC14 0 level in a population of healthy people and a decreased LPC 14. The present invention's exploration of the role of LPC 14.

Description

Application of detection reagent of myristoyl lysophosphatidylcholine in preparation of product for diagnosing CAP

Technical Field

The invention relates to the fields of metabonomics analysis and clinical medicine, in particular to application of a detection reagent of myristoyl lysophosphatidylcholine in preparation of a product for diagnosing CAP.

Background

Community-acquired pneumonia (CAP) remains one of the most common causes of death worldwide, with a global incidence of adult CAP of 0.3% to 0.5%. The diagnosis and treatment of CAP remains a serious challenge due to drug abuse and the emergence of drug-resistant bacteria. Failure to provide timely or correct diagnosis and treatment may lead to worsening of the disease and progression to severe CAP. Mortality in outpatient CAP patients is less than 5%, while hospitalized and Intensive Care Unit (ICU) CAP patients are 5-10% and 35-40%, respectively. Thus, timely diagnosis and treatment can improve the prognosis of patients with CAP.

Metabolomics is a technology for systematically analyzing small molecule metabolites in biological systems. Some previous metabolomic studies on pneumonia have provided a powerful approach to finding new biomarkers for CAP. For example, kelvin, by analyzing plasma from CAP patients and non-CAP controls, has identified lipid metabolites as potential diagnostic biomarkers by studying plasma from CAP and non-CAP patients. Ning P found sphingosine and dehydroepiandrosterone sulfate (DHEA-S) in plasma to be biomarkers that can distinguish non-severe CAP from severe CAP by LC-MS/MS based metabolomics methods. Therefore, more plasma metabolic markers with strong identification specificity and high sensitivity are screened, and the method has important application value for clinical diagnosis and treatment of CAP.

Disclosure of Invention

In order to achieve the above objects, the present invention provides the use of a detection reagent for myristoyl lysophosphatidylcholine in the preparation of a product for diagnosing CAP.

The specific scheme for realizing the invention is as follows:

in one aspect, the invention provides the use of a reagent for determining the level of myristoyl lysophosphatidylcholine (LPC 14) 0 in a sample for the manufacture of a diagnostic product,

the product is used for diagnosing community-acquired pneumonia, and a reduced LPC14:0 level in a sample compared to a predetermined reference value indicates that a subject suffers from community-acquired pneumonia;

wherein the predetermined reference value is based on an average LPC14 level in a population of healthy people.

Further, decreased levels of 1-hexadecyl-2-lysophosphatidylcholine (LPC 16) and LPC 14; wherein the predetermined reference value is based on the mean plasma LPC16 and LPC14 level in a healthy human population.

Further, the product is used for diagnosing recovery of community-acquired pneumonia patients or evaluating effectiveness of community-acquired pneumonia treatment schemes.

Still further, the treatment regimen comprises administering to the subject at least one therapeutic agent.

Further, when the product is used for diagnosing recovery in a patient with community-acquired pneumonia, or for evaluating the effectiveness of a community-acquired pneumonia treatment regimen, wherein the predetermined reference value is based on the plasma LPC16 1 and/or LPC14 0 level of the subject in the acute phase of community-acquired pneumonia, the elevated LPC16 1 and/or LPC14 0 level in the sample shows good recovery or the effectiveness of the treatment regimen.

Further, the product is for use in diagnosing a lifestyle that is likely to prevent community-acquired pneumonia, wherein an elevated LPC 16.

Further, the levels of LPC 16.

In another aspect, the invention provides the use of the myristoyl lysophosphatidylcholine in the manufacture of a medicament for the treatment of community-acquired pneumonia.

Further, the medicament also comprises a pharmaceutically acceptable carrier.

The invention has the following beneficial effects:

according to the invention, the metabolic change of CAP is revealed through an LC-MS/MS metabonomics method, and a metabolic spectrum related to the severity of diseases is established, and the result shows that the LPC 14. Furthermore, our search for the role of LPC 14.

Drawings

Figure 1 is non-targeted metabolomics and multivariate data analysis. And (A) research design. (B) Finding PCA scores and OPLS-DA score plots for CAP patient acute and remission plasma samples in ESI mode in cohort; the shaded areas are the 95% confidence areas for each group. (C) The heat map shows the relative levels of differential metabolites found in acute and remission plasma samples of CAP patients in cohort, with red indicating higher relative levels of metabolites and blue indicating lower relative levels of metabolites. (D) The heat map represents the relative intensity of the differential metabolites for the two phases in the validation cohort. CAP: community acquired pneumonia, PCA: principal component analysis, OPLS-DA: orthogonal partial least squares discriminant analysis, NSCAP non-severe CAP, SCAP severe CAP, AC acute stage, RE remission stage, FA fatty acyl, gly glycerophospholipid.

Figure 2 is a non-targeted metabolomics and multivariate data analysis in discovery cohort. Quality control samples (QC) are tightly clustered on PCA plots of discovery cohort (a) and validation cohort (B); the shaded areas are the 95% confidence areas for each group. (C) Finding PCA and OPLS-DA score maps of acute and remission plasma in the cohort under ESI + mode; the shaded areas are the 95% confidence areas for each group. (D) Data was imported into software SIMCA14 and 200 permutation tests were performed on the model to obtain a permutation verification map. CAP community acquired pneumonia, NSCAP non-severe CAP, SCAP severe CAP, AC acute stage, RE remission stage.

Figure 3 is a non-targeted metabolomics and multivariate data analysis in validation cohort. (A) Principal Component Analysis (PCA) score plots and Operational Phase (OPLS) -DA score plots of acute phase and remission phase plasma of the validation cohort in ESI + and ESI-mode; the shaded areas are the 95% confidence areas for each group. (B) Data was imported into software SIMCA14 and 200 permutation tests were performed on the model to obtain a permutation verification map. CAP community acquired pneumonia, NSCAP non-severe CAP, SCAP severe CAP, AC acute stage, RE remission stage.

FIG. 4 is quantification of metabolites and predicted performance of CAP, (A) CAP Venn diagram shows differential metabolites common to non-severe CAP and severe CAP disease groups. (B) Boxplots of the concentrations of the metabolites LPC14 and LPC16 in CAP patients and healthy controls. (C) Spearman correlation heat map of the biomarkers LPC 14. Red and blue represent positive and negative correlations, respectively, the darker the color, the stronger the correlation. (D) ROC curves analyze the predictive performance of LPC 14. (E) Lung injury was assessed by lung tissue H & E staining (Bar =100 μm, magnification x 200) and lung injury score. (F) concentration of LPC14:0 in plasma and lungs of control and ALI mice. * Compared to control, # AC and RE, # p <0.05, # p <0.01, # p <0.001.CAP community acquired pneumonia, NSCAP non-severe CAP, SCAP severe CAP, AC acute stage, RE remission stage.

Figure 5 is a graph of the effect of LPC 14. RAW264.7 cells were placed under different concentrations of LPS (0.1, 1, 10, 20, 30. Mu.g/mL) for 12h. (A) cell viability after LPS-only exposure was determined by CCK 8. RAW264.7 cells were placed under different concentrations of LPS (0.1, 1, 10, 20, 30. Mu.g/mL) for 12 hours. (B) Cell viability after LPS + LPC14 0 or LPC14 only 00 exposure was determined by the CCK8 assay. RAW264.7 cells were pretreated with different concentrations of LPC14 (10, 20, 30, 40. Mu.M) for 1 hour, followed by the addition of LPS (1. Mu.g/mL) for 12 hours. (C, D) RAW264.7 cells were pretreated with LPC14 0 (20. Mu.M) for 1h, followed by addition of LPS (20. Mu.g/mL) for 12h. (E, F) flow cytometry to detect ROS levels. After collecting the cells, 5. Mu.L of FITC Annexin V and 5. Mu.L of Propidium Iodide (PI) were added and incubated for 15min at room temperature in the dark. Flow cytometry examined the effect of LPC 14. RAW264.7 cells were pretreated with LPC14 (20. Mu.M) for 1h, followed by the addition of LPS (1. Mu.g/mL) for 12h. Cells were harvested and resuspended in 1mL serum-free medium containing 1. Mu.l DCFH-DA, incubated at 37 ℃ in the dark for 20 minutes, and washed three times with cold PBS. Flow cytometry detects ROS levels. (G, H) the effect of LPC14 pre-treatment on LPS-stimulated SOD and glutathione was tested using commercially available SOD and GSH kits. All data are expressed as mean ± SEM (n = three or four independent experiments). * Compared to control group, # vs LPS group, # p <0.05, # p <0.01, # p <0.001.

Figure 6 is a graph of LPC 14. RAW264.7 cells were pretreated with LPC14:0 (20. Mu.M) for 1 hour, then stimulated with LPS (1. Mu.g/mL) for 12 hours, and cells and cell supernatants were collected. (A-C) ELISA kits were used to measure the levels of IL-1 β, IL-6 and TNF- α in the cell supernatants. (D) Western blot detection of protein expression of NLRP3, TXNIP, caspase-1 and IL-1 beta after protein extraction from cells. (E-H) protein expression was quantified using β -actin as an internal reference. All data are expressed as mean ± SEM (n = four independent experiments). * Compared to control group, # vs LPS group, # p <0.05, # p <0.01, # p <0.001.

Figure 7 is the protective effect of LPC 14. LPC14 (10 mg/kg) was previously administered by subcutaneous injection 2 hours before intratracheal infusion of LPS (5 mg/kg) and again 12 hours later. Lung tissue and BLFA were collected 24 hours after LPS treatment. (A) Lung injury was assessed by lung tissue H & E staining (Bar =100 μm, magnification × 200). (B) lung injury score is based mainly on the following variables: alveolar and interstitial edema, inflammatory cell infiltration, and hemorrhage. Severity was scored as 0-4: no damage =0;25% injury =1;50% injury =2;75% injury =3; diffuse injury =4. Three sections per sample were observed and photographed under an optical microscope. Five fields were selected from each section and analyzed randomly, and the average was used as the sample score. (C) measuring the W/D ratio in the lung tissue. (D-E) measurement of protein content and cell number in BALF. (F) determining the MPO activity in lung tissue using the kit. All data are expressed as mean ± SEM (n =3-4 per group). * Compared to control group, # vs LPS group, # p <0.05, # p <0.01, # p <0.001.

Figure 8 is that LPC 14. LPC14 (10 mg/kg) was previously administered by subcutaneous injection 2 hours before intratracheal infusion of LPS (5 mg/kg) and again 12 hours later. Lung tissue and BLFA were collected 24 hours after LPS treatment. (A-C) ELISA was performed to detect the levels of IL-1. Beta., IL-6 and TNF-. Alpha.in BLAF. (D-F) the content of GSH, SOD and MDA in lung homogenates was determined using a commercial kit. (G) Extracting proteins from lung tissues, and detecting the expression of NLRP3, txnip, caspase-1 and IL-1 beta proteins by using specific antibody Western blotting. (H-K) protein expression was quantified using β -actin as an internal control. All data are expressed as mean ± SEM (n =3-4 per group). * Compared to control group, # vs LPS group, # p <0.05, # p <0.01, # p <0.001.

Detailed Description

The invention is described in detail below with reference to the figures and the specific embodiments, but the invention should not be construed as being limited thereto. The technical means used in the following examples are conventional means well known to those skilled in the art, and materials, reagents and the like used in the following examples can be commercially available unless otherwise specified.

Example 1: screening for CAP diagnostic markers

1. Materials and methods

1.1. Study population and design

Study participants were enrolled from month 5 to month 2021 in CAP patients admitted to the respiratory medicine or Respiratory Intensive Care Unit (RICU) of the first hospital affiliated at the wenzhou medical university in wenzhou, china. The study was approved by the ethical committee of the first subsidiary hospital of the university of medical science of wenzhou (serial No. 2020-111) and followed the declaration of helsinki (revised 2013). Each participant signed a written informed consent.

A total of 163 participants were enrolled in the study, including 48 non-severe CAP patients and 34 severe CAP patients, and an additional 81 healthy volunteers matched for gender and age as controls. The diagnosis of CAP is based on The Chinese 2016 CAP guide (Cao B, huang Y, shell D Y, et al, diagnosis and treatment of community-acquired pulmonary in additions: 2016clinical practice by The Chinese clinical practice society, chinese Medical Association J, the clinical laboratory journal,2018,12 (4): 1320-1360.). Exclusion criteria: it is diagnosed as cancer or acute and chronic inflammatory diseases (such as hospital infection, active tuberculosis, rheumatoid arthritis, severe immunosuppression, etc.).

1.2. Sample collection and processing

Plasma samples were collected from CAP at two time points: day one admission (acute phase) and before discharge (remission phase). An appropriate amount of peripheral venous blood was drawn and injected into a test tube containing heparin sodium, coagulated at room temperature for half an hour, and then centrifuged at 3000g for 10 minutes to collect the supernatant.

To 200 μ L of plasma sample was added 400 μ L of cold methanol: acetonitrile (v: v = 1) mixture to precipitate proteins, vortexed for 60s, and centrifuged to collect the supernatant. The supernatant was then aliquoted into clean tubes at N ₂ Dried under flow and then redissolved in 100 μ L ACN/water (1, v. Quality Control (QC) sample solutions contained equal amounts of plasma from each sample, one QC sample was randomly selected from 10 experimental samples.

1.3. Non-targeted and targeted UHPLC-MS/MS analysis

Sample analysis was performed on the Shimadzu CBM-30A Lite LC System (Kyoto Shimadzu, japan) using a Waters Acquity HSS T3 column (2.1X 100mm,1.8 μm) compatible with an API 6600Triple TOF (AB SCIEX, foster, calif.) mass detector coupling. The specific experimental method is as follows:

non-targeted UHPLC-MS/MS analysis mobile phase conditions were as follows: (A) 5mM ammonium acetate and 0.1% aqueous formic acid, (B) acetonitrile, flow rate of 0.4mL/min. Gradient elution analysis was as follows: 0-1.5min,2% by weight B;1.5-4min,2-60% by weight B;36-13min,60-98% by weight B;13-13.1min,98-2% by weight of B;13.1-18min,2-2% B. The column temperature was controlled at 40 ℃. The sample volume introduced into the injector was 2. Mu.L. The impact energy for fragmentation was 40V.

After sample runs, massHunter workstation software collects the raw data and processes it into mzXML format, followed by data pre-processing using XC-MS software (XC-MS plus, calif., USA), including nonlinear retention time calibration, peak identification, filtering, calibration, matching, and identification.

1.4. Non-targeted metabolomics data analysis and metabolite identification

All LC-MS data were normalized to total area prior to univariate or multivariate data analysis. Make itMultivariate analysis including Principal Component Analysis (PCA) and supervised orthogonal partial least squares discriminant analysis (OPLS-DA) was performed with SIMCA 14.1 software (Umea Umetrics, sweden). The PCA can display the distribution characteristics of the data set, while the OPLS-DA model can distinguish between classes, more clearly show the differences between different groups of samples, and generate corresponding Variable Importance Projection (VIP) values. The model was validated by displacement test (n = 200) to avoid overfitting. R is ² Y and Q ² The values may evaluate model performance, where R ² Y denotes fitting of the model, Q ² Representing its predictability, the more the values of these two parameters converge to 1.0, the more reliable the model.

Univariate statistical analysis was performed by the online site Kido using student's t-test (https:// www. Omicshare. Com/tools /).

Only variables that met False Discovery Rate (FDR) values <0.05, VIP values > 1.0, and Fold Changes (FC) < 0.5 or FC > 2 were identified as significantly different metabolites.

After screening out the distinctly different metabolites, these were further identified on the basis of the exact m/z values and MS/MS signature fragments and verified by HMDB 4.0. A heat map is drawn through the online site Metabioanalysis 5.0 (https:// www. Metabioanalysis. Ca. /). The Venn diagram is drawn through an online site (http:// www. Ehbio. Com /).

1.5. Targeted UHPLC-MS/MS analysis

LPC14 and LPC16 in human plasma and mouse serum samples were quantified using a targeted assay. This was done on an Shimadzu CBM-30A Lite LC system and API 6500Q-TRAP (AB SCIEX, foster, calif., USA) mass spectrometer and operated in ESI + mode. Lipid separation was performed using a Kinetex C18A column (100X 2.1mm,2.6 μm). The mobile phase conditions were analyzed as follows: (A) H ₂ Methanol acetonitrile (3. Gradient elution analysis was as follows: 0-0.5min,25% by volume B;0.5-1.5min,25-40% by weight of B;1.5-3min,40-60% by weight B;3-13min,60-98% by weight B;13-13.1min,98-25% by weight B;13.1-18min,25-25% by weight B. The injection volume and column temperature remained the same as for non-targeted analysis.

LPC14 (Sigma-Aldrich, >98% purity) standard solutions were prepared at concentrations ranging from 1 to 1000ng/mL and concentration calibration curves were established. In addition, LPC16 was measured by Multiple Reaction Monitoring (MRM) using 1-hexadecyl-2-lysophosphatidylcholine (LPC 16: 0) (GlpBio, USA) as an internal standard (200 ng/mL), with a method that was linear over a concentration range of 1 to 1000 ng/mL. Metabolite concentrations were measured using AB SciexMultiQuant software (version 2.1, AB SCIEX, CA, USA).

2. Results

2.1. Demographic and clinical characteristics of participants

163 participants were finally co-enrolled, CAP patients were divided into a discovery cohort (n = 31) and a validation cohort (n = 51), the remaining 81 human healthy controls. The participant design flow diagram is shown in fig. 1A.

Demographic and clinical characteristics of the participants are shown in table 1. Healthy controls and CAP patients did not differ in gender (p > 0.05), and were younger in age than CAP patients (p < 0.05). Patients with non-severe CAP and severe CAP had no significant difference in age, sex, underlying disease and smoking history (p > 0.05). Patients with severe CAP have significantly higher PSI, APACHE II, LOS, WBC, NE%, PCT, CRP, BUN, scr and LDH values than patients with non-severe CAP (p < 0.05), whereas PaO2/FiO2 is lower and is more likely to require mechanical ventilation treatment during hospitalization (p < 0.05).

TABLE 1 demographic and clinical characteristics of 163 participants in this study

Note: qualitative data are expressed as numbers (percentages) and quantitative data as means ± standard deviation or median (quartile range).

CAP community acquired pneumonia, NSCAP non-severe CAP, SCAP severe CAP, PSI pneumonia severity index, APACHE II acute physiology and chronic health assessment II, length of stay, paO2/FiO2 ratio of arterial oxygen pressure to inspired oxygen concentration, leukocyte, NE% neutrophil percentage, CRP C-reactive protein, PCT procalcitonin, BUN blood urea nitrogen, scr serum creatinine, LDH lactate dehydrogenase.

a: acute phase data b: remission period data. * Two-tailed paired student's t-test, # Mann-Whitney U-test, qualitative unordered variables measured using Fisher's exact test. Significance levels, # p <0.05, # p <0.01, # p <0.001; NS is not significant; all adjusted p-values were corrected by Benjamini Hochberg false discovery rate, adjusted p-values <0.05 being considered statistically significant.

We compared the clinical parameters of CAP patients at both time points, day 1 of admission and prior to discharge, and found that the clinical parameters WBC, NE%, CRP, PCT and LDH all showed a significant decline (p < 0.05) during remission.

2.2. Non-targeted metabolomics and multivariate data analysis

In the discovery cohort, plasma samples detected 2606 and 6392 spectral features by non-targeted UHPLC-MS/MS analysis in ESI + and ESI-modes, respectively. These obtained features were subsequently analyzed using PCA and OPLS-DA. QC was closely aligned on PCA plot, indicating that the instrument was running stably (fig. 2A). PCA analysis showed significant metabolic differences between acute and remission plasma samples, followed by OPLS-DA, with differences between the two groups being more pronounced (fig. 1B and fig. 2C). R ² Y and Q ² The values (table 2) indicate that the OPLS-DA model is reliable, with good fit and predictive performance, and that the key difference variable is determined by the VIP value it generates. 55 and 61 different metabolites were identified in the non-severe CAP and severe CAP disease groups (table 3, table 4), respectively, mainly including fatty acyl, glycerophospholipids, sphingolipids, glycerolipids, steroids and steroid derivatives, among which glycerophospholipids account for the majority, 38 cases of non-severe CAP (69%), 37 cases of severe CAP (61%). The heat map in fig. 1C shows the relative intensities of the above-mentioned differential metabolites in the acute and remission phases. It can be seen that most of the glycerophospholipid metabolites are up-regulated during the remission phase. We speculate that these substances may have a protective role in the disease process, so the validation phase is mainly focused on glycerophosphorusAnalysis of lipid metabolites.

Table 2 finds R for OPLS-DA for non-severe CAP and severe CAP in queues and validation queues ² Y and Q ² Value of

Note: orthogonal partial least squares discriminant analysis of CAP community acquired pneumonia, NSCAP non-severe case CAP, SCAP severe case CAP, OPLS-DA, R ² Y represents the interpretation rate of the model to be built on the Y matrix, Q ² The prediction capability of the model, ESI electrospray ionization, is represented.

Table 3 reports 55 differential metabolites identified in the cohort of plasma samples from the acute and remission phases of non-severe CAP

Note: CAP community acquired pneumonia, mass-to-Mass ratio of Mass, RT retention time, VIP variable importance prediction, FDR false discovery rate, and FC multiple.

Table 4 findings in the cohort 61 different metabolites were identified in severe CAP acute and remission plasma samples

Note: CAP community-acquired pneumonia, mass-to-Mass ratio of Mass, RT retention time, VIP variable importance prediction, FDR false discovery rate, FC fold change.

In the validation cohort, by expanding the sample size, differential metabolites that are stable in repetition and have the same trend of change are further screened as candidate biomarkers. Non-targeted metabolomics was still performed in the validation cohort, with 3333 and 4078 spectral features detected in ESI + and ESI-mode, respectively. QC were tightly clustered on the PCA plot (FIG. 2B), and the results for PCA and OPLS-DA are shown in FIG. 3A. By the same screening conditions, 6 and 15 phospholipid differential metabolites were found in the two disease groups, respectively (table 5, table 6). Figure 1D is a heat map of the relative intensities of these differential metabolites in the acute and remission phases. We finally screened 6 and 14 different metabolites, respectively (table 7 and table 8), which appeared repeatedly and trended consistently in both cohort studies.

Table 5 validation of the 6 different metabolites identified in the non-severe CAP acute and remission plasma samples in cohort

Note: CAP community acquired pneumonia, mass-to-Charge ratio of Mass, RT retention time, VIP variable importance prediction, FDR false discovery rate, FC fold change

Table 6 validation of the 15 different metabolites identified in severe CAP acute and remission plasma samples in cohort

CAP community acquired pneumonia, mass-to-mass ratio, RT retention time, VIP variable importance prediction, FDR false discovery rate, change FC fold.

TABLE 7 screening of 6 repeat stable differential metabolites in the non-Severe CAP disease group

Note: CAP community acquired pneumonia, mass-to-charge ratio, RT retention time, VIP variable importance prediction, FDR false discovery rate, FC fold change

TABLE 8 14 repeat stable differential metabolites screened in the severe CAP disease group

Note: CAP community-acquired pneumonia, mass-to-charge ratio, RT retention time, VIP variable importance prediction, FDR false discovery rate, FC fold change

To test whether there is overfitting of the OPLS-DA model, the model was tested by inputting the data into SIMCA14 for 200 permutations and displacement verification plots were obtained (fig. 2D, fig. 3B). As can be seen from the figure, all of the substituted R ² Y and Q ² The values are all lower than the original values. The slope of the regression line is large and the intercept with the left vertical axis is less than zero, which demonstrates that the results of the OPLS-DA model are reliable without overfitting.

2.3. Quantification of metabolites and predicted performance of CAP

The screened differential metabolites were analyzed by venn plot (fig. 4A), and then two common differential metabolites, LPC14 and LPC16, were found in the two disease groups and they had significant differences. Therefore, we intend to further explore these two metabolites as potential biomarkers.

Then, the content of LPC 14. As a result, as shown in the box plot in fig. 4B, it was revealed that the concentrations of LPC 14.

To investigate the diagnostic performance of these two metabolites, we performed correlation analyses and plotted Receiver Operating Characteristic (ROC) curves to assess their relationship to clinical characteristics and sensitivity and specificity in diagnosing CAP severity.

Clinical parameters (WBC, NE%, PCT, CRP, BUN, scr, LDH) are commonly used indicators in clinical treatment of CAP to judge disease severity and treatment efficacy. The correlation between metabolites and clinical parameters was analyzed by Spearman correlation analysis (fig. 4C) with correlation coefficient data shown in table 9. In the non-severe CAP disease group, LPC 14. . LPC16:1 was negatively associated with CRP (r =0.309, p = 0.002) and PCT (r =0.404, p- <0.001), with no association with other clinical parameters. In the severe CAP disease group, LPC14 was negatively correlated with WBCs (r = -0.304, p = -0.012), NE% (r =0.356, p = -0.0029), CRPs (r =0.532, p-t-0.001), and PCT (r =0.461, p-t-00.001), and was not correlated with Scr, LDH, and BUN. LPC16:1 is negatively correlated with CRP (r = -0.479, p <0.001) and PCT (r = -0420, p < <00.001), with no correlation with other parameters.

TABLE 9LPC 14 0 correlation analysis with non-severe CAP and severe CAP clinical parameters

Note: CAP community acquired pneumonia, NSCAP non-severe CAP, SCAP severe CAP, WBC leukocytes, NE% neutrophil percentage, CRP C reactive protein, PCT procalcitonin, BUN blood urea nitrogen, scr serum creatinine, LDH lactate dehydrogenase, r: spearman correlation coefficient.

The area under the curve (AUC), specificity and sensitivity of the ROC curve were used to evaluate the performance of these two metabolites in predicting CAP severity. As shown in fig. 4D, LPC 14. The AUC value for LPC16:1 was 0.785, sensitivity 0.563, specificity 0.896, significance p <0.05. In predicting severe CAP, the AUC of LPC14 0 was 0.868, the sensitivity was 0.882, the specificity was 0.853, and the significance p <0.01. The AUC value for LPC16:1 was 0.848, sensitivity 0.794, specificity 0.882, significance p <0.001. We also analyzed the diagnostic performance of CRP, PCT, WB, NE% and LDH, with the data shown in table 10. In comparison to these clinical parameters, LPC14:0 and LPC16:1 performed better than WB, NE% and LDH, slightly lower than CRP and PCT.

TABLE 10 Area Under Curve (AUC) of the ROC curve and its sensitivity and specificity in non-severe CAP and severe CAP

Note: CAP community-acquired pneumonia, NSCAP non-severe CAP, SCAP severe CAP, ROC receptor operating characteristics, AUC area under curve, CI confidence interval, WBC leukocytes, NE% neutrophil percentage, CRP C-reactive protein, PCT procalcitonin, LDH lactate dehydrogenase

From the above results, we found that the correlation and predictive performance of LPC14 0 to CAP is superior to LPC16:1, whereas LPC 16. LPC14:0 was significantly lower in both serum and lung tissue than healthy mice, with a trend that was essentially identical to humans (FIGS. 4E-F). These results suggest that LPC 14; thus, the lipids were selected for subsequent in vitro and in vivo experiments.

Example 2: pharmaceutical use of LPC14

1. Method of producing a composite material

1.1 cell assay

1.1.1 cell culture and CCK-8

RAW264.7 cells (Chinese cell Bank, beijing, china) were cultured in DMEM medium containing 10% FBS, 100U/mL penicillin, 100U/mL streptomycin and 3mM glutamine at 37 ℃ with 5% carbon dioxide.

The effect of different drug concentrations of LPS and LPC14:0 on cell viability was determined by CCK-8. Cells were seeded in 96-well plates. Cells were then cultured in two 96-well plates and pretreated with LPC14 0 (10, 20, 30, 40) μ M for 1h, with one plate exposed to LPS (1 μ g/mL) for 12h. 10uL of CCK-8 was added, incubated for 2h, and then the absorbance was measured at 450 nm.

1.1.2 quantification of apoptosis, determination of ROS and antioxidant enzymes (GSH, SOD)

RAW264.7 cells were cultured for 24 hours, starved for 1 hour, and pretreated with LPC14 (20 μ M) for 1h. To 1X 10 ⁵ Cells were added 5. Mu.L FITC Annexin V and 5. Mu.L Propidium Iodide (PI) and incubated at 25 ℃ for 15min in the absence of light. Flow cytometry measures the percentage of apoptosis and necrosis.

To measure ROS, cells were harvested and incubated with 1mL serum-free medium containing 1. Mu.L of DCFH-DA in the dark for 20 minutes at 37 ℃. After three washes with cold PBS, the DCF fluorescence intensity of the cells was measured.

In addition, cells were collected after the same treatment, disrupted with ultrasonication, and the SOD and GSH levels were evaluated with the assay kit using cell supernatants.

1.2 animal experiments

1.2.1 animal grouping and administration treatment

SPF-grade male C57BL/6 mice at 8 weeks of age were purchased from Experimental animals technology, inc. of Weitonglihua, zhejiang (SYXK (Zhejiang) 2021-0017), and were bred adaptively for 1 week. All animals were kept under SPF conditions. All experiments involving animals were conducted according to ethical policies and procedures approved by the ethical committee of the university of medical science, wenzhou, china (No.: 2021-0095).

For the first group of animals, mice were divided into two subgroups: control (phosphate buffered saline (PBS) +1% BSA) and LPS group (5 mg/kg in PBS). LPS was instilled into the trachea to induce mouse ALI.

The second group of mice was randomly divided into four subgroups: control (phosphate buffered saline (PBS) +1% BSA), LPC14 only group 0 (10 mg/kg BSA in 1%, diluted with PBS), LPS only group (5 mg/kg PBS), LPS (5 mg/kg) + LPC14 (10 mg/kg). Mice were pretreated by subcutaneous injection of LPC14 (10 mg/kg), anesthetized with isoflurane 2 hours later (5% induction, 2% maintenance), and LPS (5 mg/kg, diluted to 50ul with PBS) was injected into the trachea to induce mice ALI. LPC14 (10 mg/kg) was administered to LPS intratracheally for 10 hours and then administered again subcutaneously, control group was injected subcutaneously 1% bsa and intratracheally instilled PBS. 24 hours after LPS injection, mice were anesthetized with isoflurane and sacrificed by peeling, and then mouse lung tissue samples, bronchoalveolar lavage fluid (BALF) and serum were collected and stored at-80 ℃.

1.2.2 Lung hematoxylin-eosin (H & E) and BALF assays

Lung tissue of mice without BALF collected was histopathologically examined. Tissue specimens were fixed in 4% paraformaldehyde for 48 hours, gradient dehydrated, paraffin embedded, and then cut into 4 μm thick sections and stained with h & E.

After sacrifice, BALF was collected by intratracheal injection of 1.0mL cold PBS. BALF was collected into particles by centrifugation at 300g for 20 min at 4 ℃, red blood cells were lysed, washed three times with cold PBS, then centrifuged again and resuspended by counting the total number of cells in PBS. Protein concentration of untreated BLAF was determined using BCA protein assay kit (Beyotime, china).

1.2.3 measurement of lung wet/dry (W/D) ratio and GSH, SOD, MDA and MPO content in lung tissue LPS treatment 24 hours before collection of lung tissue, washing with saline and blotting, weighing immediately to obtain a "wet" weight, then oven drying at 65 ℃ for 48 hours to obtain a "dry" weight. Their ratio may indirectly reflect edema in the lung tissue.

Lung tissue was homogenized and the levels of Glutathione (GSH), superoxide dismutase (SOD), malondialdehyde (MDA) and Myeloperoxidase (MPO) in the homogenate were measured using a kit (nanjing bioengineering institute, china).

1.2.4 enzyme-linked immunosorbent assay

Cytokines were measured in BALF or cell culture supernatants using ELISA. BALF was obtained from each sample separately, centrifuged, and the supernatant collected. IL-1 β, IL-6 and TNF- α protein levels were determined using an ELISA kit (institute of bioengineering, tokyo, nanjing, china).

Furthermore, RAW264.7 cells were cultured for 24 hours, and then pretreated with LPC14 0 (20 μ M) for 1 hour. After 12 hours of stimulation with LPS (1. Mu.g/mL), cell-free supernatants were collected to detect secretion of IL-1. Beta., IL-6 and TNF-. Alpha.and the optical density at 450nm was measured.

1.2.5 Western blot analysis

20ug of protein was loaded in the wells of a 10% polyacrylamide gel, and sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) was performed to separate the proteins. The proteins were then transferred to polyvinylidene fluoride (PVDF) membranes, which were blocked in 5% skim milk for 1 hour at room temperature. Next, the membrane was incubated with the primary antibody overnight at 4 ℃, then washed three times with TBST for 10 minutes each, and then incubated with horseradish peroxidase (HRP) conjugated secondary antibody for 1 hour at room temperature. And (3) related protein expression detection: NLRP3, TXNIP, caspase-1, IL-1 beta and beta-actin serve as internal reference proteins. Band detection was performed using ECL (Amersham Pharmacia Biotech, piscataway, NJ) and the band intensity was quantified using Image lab gel analysis software.

2 results

2.1LPC 14

We first investigated whether LPC 14. First, CCK-8 observed the effect of different doses of LPS and LPC14 on cell viability. The results show that LPS is completely non-toxic to cells in the dose range of 0.1-20. Mu.g/mL. LPS promoted cell proliferation in the dose range of 0.1-1. Mu.g/mL (FIG. 5A), so 20. Mu.g/mL was used in apoptosis experiments. LPC14, 0, administered alone or in combination with LPS (1. Mu.g/ml), was non-toxic in the range of 0-20. Mu.M (FIG. 5B).

LPS stimulates RAW264.7 to produce ROS and trigger oxidative stress, resulting in oxidative damage to cells, whereas LPC 14. We further investigated the antioxidant effect of LPC 14. The results indicate that LPC 14.

2.2lpc 14

We continued to investigate the effect of LPC14:0 on LPS-induced inflammatory responses of RAW264.7 cells. We found that LPS-only stimulation of RAW264.7 cells promoted secretion of IL-1 β, IL-6 and TNF- α, whereas LPC14:0 inhibited the above inflammatory factors (FIGS. 6A-C). Since LPC14:0 was found to be effective in reducing LPS-induced ROS production in RAW264.7 cells, while ROS can stimulate the activation of TXNIP, thereby promoting the activation of NLRP3 inflammasome, we continued to investigate whether LPC14:0 can block LPS-induced activation of NLRP3 inflammasome in RAW2647 cells. The results indicate that LPC 14.

2.3lpc 14

Based on these in vitro experimental results, we further investigated whether LPC14:0 treatment protected ALI in mice. As shown in fig. 7A, the lung tissue of the LPS group showed significant pathological changes, including accumulation of inflammatory cells in the alveoli, intra-alveolar bleeding and thickening of alveolar walls. However, LPC 14. Furthermore, LPC14 treatment decreased lung injury score compared to LPS treated group (fig. 7B). We determined the extent of pulmonary edema in mice by lung W/D ratio and protein leakage in BALF. As shown in fig. 7C-D, the lung W/D ratio and protein concentration of LPS-stimulated mice were significantly higher than the control group and the LPC 14-0 treated group alone, while LPC 14. Furthermore, LPS stimulation led to inflammatory cell aggregation in mouse BALF, and LPC 14. As shown in fig. 7F, LPC14 0 pretreatment effectively inhibited LPS-induced increase in MPO activity, an indicator of neutrophil accumulation in the lung.

2.5lpc 14 treatment inhibition of inflammatory response to ALI mouse LPS stimulation, oxidative stress and NLRP3 inflammasome activation in ALI mice

To observe the effect of LPC14:0 on LPS-induced inflammatory response and oxidative stress in mice, we examined the secretion levels of inflammatory factors IL-1 β, IL-6 and TNF- α in mouse BALF and the levels of GSH, SOD and MDA in lung homogenate. Our results indicate that, in addition to IL-6, LPC 14. In vitro cell experiments, we found that LPC 14. Therefore, this study further explored whether LPC 14. The results indicate that LPS stimulation significantly promoted the expression of NLRP3, TXNIP, caspase-1 and IL-1. Beta. Proteins, while LPC 14.

While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.

It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims

1. Use of an agent for determining the level of myristoyl lysophosphatidylcholine (LPC 14) in a sample for the manufacture of a diagnostic product for diagnosing community-acquired pneumonia, wherein a decreased LPC14 0 level in the sample compared to a predetermined reference value indicates that the subject has community-acquired pneumonia;

2. The use according to claim 1, wherein a decreased level of 1-hexadecyl-2-lysophosphatidylcholine (LPC 16; wherein the predetermined reference value is based on the mean plasma LPC16 and LPC14 level in a healthy human population.

3. The use according to claim 2, wherein the product is used to diagnose recovery in a patient with community-acquired pneumonia, or to evaluate the effectiveness of a community-acquired pneumonia treatment regimen.

4. The use of claim 3, wherein the treatment regimen comprises administering at least one therapeutic agent to the subject.

5. The use according to claim 4, wherein the predetermined reference value is based on plasma LPC 16.

6. Use according to claim 2, wherein the product is for diagnosing a lifestyle that is likely to prevent community-acquired pneumonia, wherein an elevated level of LPC 16.

7. Use according to claim 2, wherein the level of LPC 16.

8. Use of myristoyl lysophosphatidylcholine according to claim 1 for the preparation of a medicament for the treatment of community-acquired pneumonia.

9. The use according to claim 8, wherein the medicament further comprises a pharmaceutically acceptable carrier.