CN115754067B - Use of detection reagent of myristoyl lysophosphatidylcholine in preparation of products for diagnosing CAP - Google Patents
Use of detection reagent of myristoyl lysophosphatidylcholine in preparation of products for diagnosing CAP Download PDFInfo
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Abstract
The invention relates to the fields of metabonomics analysis and clinical medicine, in particular to application of a detection reagent of myristoyl lysophosphatidylcholine in preparing a product for diagnosing CAP. Obtaining a plasma sample from a subject; determining the level of myristoyl lysophosphatidylcholine (LPC 14:0) in the sample, and comparing the LPC14:0 level of the subject to a predetermined reference value; wherein the predetermined reference value is based on an average LPC14:0 level in the population of healthy people and a reduced LPC14:0 level in the sample compared to the predetermined reference value indicates that the subject has community-acquired pneumonia. The exploration of the role of LPC14:0 in animal and cell models also enhances the prospect of the LPC14:0 serving as a therapeutic target for improving the clinical efficacy of CAP.
Description
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 preparing a product for diagnosing CAP.
Background
Community-acquired pneumonia (CAP) remains one of the most common causes of death worldwide, and 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 can lead to exacerbation of the condition and progression to severe CAP. Thus, timely diagnosis and treatment can improve the prognosis of CAP patients.
Metabonomics is a technique for systematically analyzing small molecule metabolites in biological systems. Some previous metabonomics studies on pneumonia provide a powerful method for finding new markers of CAP. For example, kelvin determines lipid metabolites as potential diagnostic biomarkers by studying the plasma of CAP and non-CAP patients by analyzing the plasma of CAP patients and non-CAP controls. Ning P found sphingosine and dehydroepiandrosterone sulfate (DHEA-S) in plasma as biomarkers, non-severe CAP and severe CAP could be distinguished by LC-MS/MS based metabonomics. Therefore, screening more plasma metabolic markers with strong identification specificity and high sensitivity has important application value for clinical diagnosis and treatment of CAP.
Disclosure of Invention
To achieve the above object, 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 an agent for determining the level of myristoyl lysophosphatidylcholine (LPC 14:0) in a sample for the preparation of a diagnostic product,
the product is used to diagnose community-acquired pneumonia, a reduced level of LPC14:0 in the sample compared to a predetermined reference value indicates that the subject has community-acquired pneumonia;
wherein the predetermined reference value is based on an average LPC14:0 level in the population of healthy people.
Further, reduced levels of 1-hexadecyl-2-lysophosphatidylcholine (LPC 16:1) and LPC14:0 in the sample compared to the predetermined reference value indicate that the subject has community-acquired pneumonia; wherein the predetermined reference value is based on average plasma LPC16:1 and LPC14:0 levels in the healthy human population.
Further, the product is useful for diagnosing recovery from a community-acquired pneumonia patient, or evaluating the effectiveness of a community-acquired pneumonia treatment regimen.
Still further, the treatment regimen comprises administering at least one therapeutic agent to the subject.
Still further, when the product is used to diagnose recovery in a community-acquired pneumonia patient, or to evaluate the effectiveness of a community-acquired pneumonia treatment regimen, wherein the predetermined reference value is based on the subject's plasma LPC16:1 and/or LPC14:0 level in the acute phase of community-acquired pneumonia, elevated LPC16:1 and/or LPC14:0 levels in the sample show good recovery or efficacy of the treatment regimen.
Further, the product is for diagnosing a lifestyle that is likely to be protected from community-acquired pneumonia, wherein an elevated level of LPC16:1 and/or LPC14:0 in the sample compared to a predetermined reference value is indicative of a lifestyle that is likely to be protected from community-acquired pneumonia.
Further, the level of LPC16:1 and/or LPC14:0 was determined in the samples and references by ultra high performance liquid tandem mass spectrometry.
In another aspect, the invention provides the use of said myristoyl lysophosphatidylcholine in the manufacture of a medicament for the treatment of community-acquired pneumonia.
Further, the medicament further comprises a pharmaceutically acceptable carrier.
The invention has the following beneficial effects:
the invention reveals the metabolic change of CAP through the metabonomics method of LC-MS/MS, and establishes a metabolic spectrum related to the severity of the disease, and the result shows that LPC14:0 can be used as a new marker for predicting the severity of the CAP. Furthermore, our search for the role of LPC14:0 in animal and cellular models has enhanced its prospect as a therapeutic target for enhancing the clinical efficacy of CAP.
Drawings
FIG. 1 is a non-targeted metabonomics and multivariate data analysis. (A) study design. (B) Finding PCA scores and OPLS-DA score graphs of acute and remission stage plasma samples of CAP patients in ESI mode in the queue; the shaded area is the 95% confidence area for each group. (C) The heat map shows the relative levels of differential metabolites in acute and remission plasma samples of CAP patients found in the cohort, with red indicating higher relative levels of metabolites and blue indicating lower relative levels of metabolites. (D) The thermogram shows the relative intensities of the differential metabolites at two times in the validation queue. 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 phase, RE remission phase, FA fatty acyl, gly glycerophospholipids.
FIG. 2 is a diagram of non-targeted metabolomics and multivariate data analysis in the discovery cohort. The quality control samples (QC) are tightly clustered on the PCA plot of the discovery queue (a) and the validation queue (B); the shaded area is the 95% confidence area for each group. (C) PCA and OPLS-DA score plots of the acute and the buffer phases plasma of the cohort were found in ESI+ mode; the shaded area is the 95% confidence area for each group. (D) The data is imported into software SIMCA14 and 200 permutation tests are performed on the model to obtain a permutation test map. CAP community acquired pneumonia, NSCAP non-severe CAP, SCAP severe CAP, AC acute phase, RE remission phase.
FIG. 3 is a validation of non-targeted metabolomics and multivariate data analysis in a cohort. (A) PCA score plots and OPLS-DA score plots of acute and remission plasma of the validation cohort in ESI+ and ESI-modes; the shaded area is the 95% confidence area for each group. (B) The data is imported into software SIMCA14 and 200 permutation tests are performed on the model to obtain a permutation test map. CAP community acquired pneumonia, NSCAP non-severe CAP, SCAP severe CAP, AC acute phase, RE remission phase.
FIG. 4 is a graph of metabolite quantification and predictive performance of CAP, (A) CAP Venn diagram showing differential metabolites common to both non-severe CAP and severe CAP disease groups. (B) Panels of metabolites LPC14:0 and LPC16:1 concentrations in CAP patients and healthy controls. (C) Spearman correlation heat maps of biomarkers LPC14:0, LPC16:1 and clinical parameters. Red and blue represent positive and negative correlations, respectively, with the darker the color, the stronger the correlation. (D) ROC curves analyze the predicted performance of LPC14:0, LPC16:1 and various clinical parameters in non-severe CAP and severe CAP disease. (E) Lung injury was assessed by H & E staining of lung tissue (bar=100 μm, magnification x 200) and lung injury score. (F) concentration of LPC14:0 in plasma and lung of control and ALI mice. * Compared to control group, # 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 phase, RE remission phase.
FIG. 5 is the effect of LPC14:0 pretreatment on LPS-induced oxidative damage in RAW264.7 cells. 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+LPC 14:0 or LPC 14:00 exposure alone was determined by CCK8 assay. RAW264.7 cells were pretreated with different concentrations of LPC14:0 (10, 20, 30, 40. Mu.M) for 1 hour, followed by LPS (1. Mu.g/mL) addition for 12 hours. (C, D) RAW264.7 cells were pretreated with LPC14:0 (20. Mu.M) for 1h, followed by LPS (20. Mu.g/mL) for 12h. (E, F) flow cytometry detects ROS levels. After harvesting the cells, 5 μl FITC Annexin V and 5 μl Propidium Iodide (PI) were added and incubated for 15min at room temperature in the dark. Flow cytometry examined the effect of LPC14:0 on LPS-induced apoptosis. RAW264.7 cells were pretreated with LPC14:0 (20. Mu.M) for 1h, followed by LPS (1. Mu.g/mL) for 12h. Cells were harvested and resuspended in 1mL serum-free medium containing 1. Mu.l DCFH-DA, incubated for 20 minutes in the dark at 37℃and washed three times with cold PBS. Flow cytometry detects ROS levels. (G, H) the effect of LPC14:0 pretreatment on LPS stimulated SOD and glutathione was tested using commercial SOD and GSH kits. All data are expressed as mean ± SEM (n=three or four independent experiments). * Compared to the control group, #vs LPS group, < p <0.05, < p <0.01, < p <0.001.
FIG. 6 is a graph showing LPC14:0 inhibition of LPS-induced inflammatory response and NLRP3 inflammatory platelet activation in RAW264.7 cells. 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. The (A-C) ELISA kit was used to measure the levels of IL-1. Beta., IL-6 and TNF-alpha in cell supernatants. (D) Western blot detection of protein expression of NLRP3, TXNIP, caspase-1 and IL-1β after protein extraction from cells. (E-H) protein expression was quantified using beta-actin as an internal reference. All data are expressed as mean ± SEM (n=four independent experiments). * Compared to the control group, #vs LPS group, < p <0.05, < p <0.01, < p <0.001.
FIG. 7 is the protective effect of LPC14:0 treatment on mouse LPS-induced ALI. LPC14:0 (10 mg/kg) was pre-administered by subcutaneous injection 2 hours prior to intratracheal infusion of LPS (5 mg/kg) and re-administered 12 hours later. Lung tissue and BLFA were collected 24 hours after LPS treatment. (A) Lung injury was assessed by H & E staining of lung tissue (bar=100 μm, magnification x 200). (B) the lung injury score is based primarily on the following variables: alveolar and interstitial oedema, inflammatory cell infiltration and hemorrhage. Severity was scored from 0 to 4: no damage = 0;25% injury = 1;50% injury = 2;75% injury = 3; diffuse injury = 4. Three sections were taken for each sample and observed and photographed under an optical microscope. Five fields from each slice were selected and randomly analyzed 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 activity of MPO in lung tissue using the kit. All data are expressed as mean ± SEM (n=3-4 per group). * Compared to the control group, #vs LPS group, < p <0.05, < p <0.01, < p <0.001.
FIG. 8 is a graph showing that LPC14:0 treatment inhibited LPS-induced inflammatory responses, oxidative stress, and activation of NLRP3 inflammatory minibodies in ALI mice. LPC14:0 (10 mg/kg) was pre-administered by subcutaneous injection 2 hours prior to intratracheal infusion of LPS (5 mg/kg) and re-administered 12 hours later. Lung tissue and BLFA were collected 24 hours after LPS treatment. (A-C) ELISA detects IL-1β, IL-6 and TNF- α levels in BLAF. (D-F) commercial kits were used to determine the content of GSH, SOD and MDA in lung tissue homogenates. (G) Protein was extracted from lung tissue and expression of NLRP3, txnip, caspase-1 and IL-1. Beta. Proteins was detected by Western blotting, a specific antibody. (H-K) protein expression was quantified using beta-actin as an internal control. All data are expressed as mean ± SEM (n=3-4 per group). * Compared to the control group, #vs LPS group, < p <0.05, < p <0.01, < p <0.001.
Detailed Description
The present invention will now be described in detail with reference to the drawings and specific examples, which should not be construed as limiting the invention. Unless otherwise indicated, the technical means used in the following examples are conventional means well known to those skilled in the art, and the materials, reagents, etc. used in the following examples are commercially available unless otherwise indicated.
Example 1: screening of CAP diagnostic markers
1. Materials and methods
1.1. Study population and design
Study participants were recruited from month 5 2020 to month 2021 in CAP patients admitted to the respiratory department of first hospital or Respiratory Intensive Care Unit (RICU) at the university of wenzhou medical science in china. The study was approved by the first affiliated hospital ethics committee of the university of wenzhou medical science (accession number 2020-111) and followed the declaration of helsinki (revised 2013). Each participant signed a written informed consent.
A total of 163 participants participated in the study, including 48 non-severe CAP patients and 34 severe CAP patients, and another 81 healthy volunteers matched with gender and age as controls. CAP diagnosis was based on the China 2016 CAP guide (Cao B, huang Y, she D Y, et al diagnosis and treatment of community-acquired pneumonia in adults:2016clinical practice guidelines by the Chinese Thoracic Society,Chinese Medical Association[J ]. The clinical respiratory journal,2018,12 (4): 1320-1360.). Exclusion criteria: diagnosing cancer or acute and chronic inflammatory diseases (such as nosocomial infection, active tuberculosis, rheumatoid arthritis, severe immunosuppression, etc.).
1.2. Sample collection and processing
Plasma samples were taken from CAP at two time points: first day of admission (acute phase) and prior to discharge (remission phase). An appropriate amount of peripheral venous blood was withdrawn and injected into a test tube containing heparin sodium, coagulated at room temperature for half an hour, and then the supernatant was collected after centrifugation at 3000g for 10 minutes.
To 200 μl of plasma sample was added 400 μl of cold methanol: acetonitrile (v: v=1:1) mixture to precipitate protein, vortexed for 60s, and the supernatant was collected by centrifugation. The supernatant was then aliquoted into clean tubes at N 2 Flow down dried and then redissolved in 100. Mu.L ACN/water (1:1, v: v) for UHPLC-MS/MS analysis. Quality Control (QC) sample solutions contain equal amounts from each samplePlasma, 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 an Shimadzu CBM-30A Lite LC system (Kyoto Shimadzu Corp., japan) using a Waters Acquity HSS T column (2.1X100 mm,1.8 μm) compatible with the API 6600Triple TOF (AB SCIEX, forst, calif.) mass detector coupling. The specific experimental method is as follows:
the mobile phase conditions for non-targeted UHPLC-MS/MS analysis are as follows: (A) 5mM ammonium acetate and 0.1% aqueous formic acid, (B) acetonitrile at a flow rate of 0.4mL/min. Gradient elution analysis was as follows: 0-1.5min,2% B;1.5-4min,2-60% B;36-13min,60-98% B;13-13.1min,98-2% B;13.1-18min,2-2% B. The column temperature was controlled at 40 ℃. The sample volume introduced into the injector was 2 μl. The collision energy for fragmentation was 40V.
After sample runs, the MassHunter workstation software collects raw data and processes it into mzXML format, and then uses XC-MS software (XC-MS plus, california, usa) for data preprocessing, including nonlinear retention time calibration, peak identification, filtering, calibration, matching, and identification.
1.4. Non-targeted metabonomics data analysis and metabolite identification
All LC-MS data were normalized with total area prior to univariate or multivariate data analysis. Multiplex analysis, including Principal Component Analysis (PCA) and supervised orthogonal partial least squares discriminant analysis (OPLS-DA) was performed using SIMCA 14.1 software (Umeas Umeta, sweden). PCA may display the distribution characteristics of the dataset, while OPLS-DA model may distinguish categories, more clearly show the differences between different sets of samples, and generate corresponding Variable Importance Projection (VIP) values. The model was validated by a permutation test (n=200) to avoid overfitting. R is R 2 Y and Q 2 The values may evaluate model performance, where R 2 Y represents the 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 (https:// www.omicshare.com/tools /) was performed using student t test through online website Kido.
Only variables meeting the False Discovery Rate (FDR) value <0.05, VIP value > 1.0 and Fold Change (FC) < 0.5 or FC > 2 were determined to be significantly different metabolites.
After screening for significantly different metabolites, these metabolites were further identified based on the exact m/z values and MS/MS signature fragments and validated by HMDB 4.0. A heatmap was drawn through the online site Metaboanalyst5.0 (https:// www.metaboanalyst.ca /). Venn diagram is drawn through an online website (http:// www.ehbio.com /).
1.5. Targeted UHPLC-MS/MS analysis
LPC14:0 and LPC16:1 in human plasma and mouse serum samples were quantified using a targeting assay. Was performed on an Shimadzu CBM-30A Lite LC system and API 6500Q-TRAP (AB SCIEX, foster, calif., U.S.A.) mass spectrometer and operated in ESI+ mode. Lipid separation was performed using a kineex C18 100A column (100×2.1mm,2.6 μm). The mobile phase conditions were analyzed as follows: (A) H 2 O: methanol: acetonitrile (3:1:1, V: V), 5mM ammonium acetate, (B) isopropanol, flow rate was 0.3mL/min. Gradient elution analysis was as follows: 0-0.5min,25% B;0.5-1.5min,25-40% B;1.5-3min,40-60% B;3-13min,60-98% B;13-13.1min,98-25% B;13.1-18min,25-25% B. The injection volume and column temperature remained the same as for the non-targeted analysis.
LPC14:0 (Sigma-Aldrich, >98% purity) standard solutions were prepared at concentrations ranging from 1 to 1000ng/mL and concentration calibration curves were established. In addition, LPC16:1 was measured by Multiple Reaction Monitoring (MRM) using 1-hexadecyl-2-lysophosphatidylcholine (LPC 16:0) (GlpBio, USA) as an internal standard (200 ng/mL), the method being 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
Finally, 163 participants were enrolled, and 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 chart is shown in fig. 1A.
Demographic and clinical characteristics of the participants are shown in table 1. Healthy control and CAP patients were not different in gender (p > 0.05), younger in age than CAP patients (p < 0.05). Non-severe CAP and severe CAP patients had no significant differences in age, sex, underlying disease and smoking history (p > 0.05). The PSI, APACHE II, LOS, WBC, NE%, PCT, CRP, BUN, scr and LDH values were significantly higher for severe CAP patients than for non-severe CAP patients (p < 0.05), while PaO2/FiO2 was lower and mechanical ventilation treatment (p < 0.05) was more likely required during hospitalization.
Table 1 demographic and clinical characteristics of 163 participants in this study
Note that: qualitative data are expressed as numbers (percentages) and quantitative data are expressed as mean ± 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, hospitalization time, paO2/FiO2 ratio of arterial oxygen pressure to inhaled oxygen concentration, leukocyte, NE% neutrophil percentage, CRP C reactive protein, procalcitonin, BUN blood urea nitrogen, sca serum creatinine, LDH lactate dehydrogenase.
a: acute phase data b: remission data. * Double-tailed paired student t-test, # Mann-Whitney U test, measured qualitative disorder variables using Fisher's exact test. Significance level, p <0.05, p <0.01, p <0.001; NS is not significant; all p-values adjusted were found by Benjamini Hochberg error-correction, and adjusted p-values <0.05 were considered statistically significant.
We compared the clinical parameters at both day 1 of CAP patient admission and pre-discharge, found that clinical parameters WBC, NE%, CRP, PCT and LDH all showed a significant decrease trend during remission (p < 0.05).
2.2. Non-targeted metabonomics and multivariate data analysis
In the discovery cohort, plasma samples were tested for 2606 and 6392 spectral features by non-targeted UHPLC-MS/MS analysis in ESI+ and ESI-modes, respectively. These obtained features were then analyzed using PCA and OPLS-DA. The QC was closely aligned on the PCA plot, indicating stable instrument operation (fig. 2A). PCA analysis showed a significant metabolic difference between acute and remission plasma samples, followed by OPLS-DA, the difference between the two groups being more pronounced (fig. 1B and fig. 2C). R is R 2 Y and Q 2 The values (Table 2) indicate that the OPLS-DA model is reliable, has good fit and predictive performance, and the key variance variables are determined by the VIP values it generates. 55 and 61 different metabolites were identified in the non-severe CAP and severe CAP disease groups (Table 3, table 4), mainly including fatty acyl, glycerophospholipids, sphingolipids, glycerolipids, steroid and steroid derivatives, etc., with glycerophospholipids being the majority of non-severe CAP38 (69%), severe CAP37 (61%). The heat map in fig. 1C shows the relative intensities of the above differential metabolites in the acute and remission phases. It can be seen that most glycerophospholipid metabolites are up-regulated during remission. We speculate that these substances may have a protective role in the disease process, so the validation phase is mainly focused on the analysis of glycerophospholipid metabolites.
TABLE 2 discovery and validation of R of OPLS-DA for non-severe CAP and severe CAP in queues 2 Y and Q 2 Value of
Note that: CAP community acquired pneumonia, NSCAP non-severe CAP, SCAP severe CAP, OPLS-DA orthogonal partial least squares discriminant analysis, R 2 Y represents the interpretation rate of the built model to the Y matrix, Q 2 Representing the predictive power of the model, ESI electrospray ionization.
Table 3 finds 55 different metabolites identified in non-Severe CAP acute and remission plasma samples in the cohort
Note that: CAP community-acquired pneumonia, mass-to-Mass charge ratio, RT retention time, VIP variable importance prediction, FDR error discovery rate, FC fold change.
Table 4 shows that 61 different metabolites were identified in severe CAP acute and remission plasma samples in the cohort
Note that: CAP community-acquired pneumonia, mass-to-Mass charge ratio, RT retention time, VIP variable importance prediction, FDR error discovery rate, FC fold change.
In the validation cohort, the candidate biomarkers were further screened for duplicate stable differential metabolites with the same trend of change by scaling up the sample size. Non-targeted metabolomics was still performed in the validation cohort, 3333 and 4078 spectral features were detected in esi+ and ESI-modes, respectively. QC was clustered tightly on the PCA plot (FIG. 2B), and the results of 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). FIG. 1D is a heat map of the relative intensities of these differential metabolites during the acute and remission phases. We finally screened 6 and 14 different metabolites (table 7 and 8), respectively, which repeated and tended to be consistent in both cohort studies.
Table 5 verifies the 6 different metabolites identified in non-severe CAP acute and remission plasma samples in the cohort
Note that: CAP community-acquired pneumonia, mass-to-charge ratio, RT retention time, VIP variable importance prediction, FDR error discovery rate, FC fold change
Table 6 verifies 15 different metabolites identified in severe CAP acute and remission plasma samples in the cohort
CAP community acquired pneumonia, mass-to-mass charge ratio, RT retention time, VIP variable importance prediction, FDR error discovery rate, change FC fold.
TABLE 7 screening of 6 repeat stable differential metabolites in non-severe CAP disease groups
Note that: CAP community-acquired pneumonia, mass-to-charge ratio, RT retention time, VIP variable importance prediction, FDR error discovery rate, FC fold change
Table 8 14 repeat stable differential metabolites selected in severe CAP disease group
Note that: CAP community-acquired pneumonia, mass-to-mass charge ratio, RT retention time, VIP variable importance prediction, FDR error discovery rate, FC fold change
To test for the presence of overfitting of the OPLS-DA model, the model was tested by 200 permutations of data input SIMCA14 and a permutation test chart was obtained (fig. 2D, 3B). As can be seen from the figure, all substituted R 2 Y and Q 2 The values are all lower than the original value. The slope of the regression line is large and the intercept to the left vertical axis is less than zero, which demonstrates that there is no overfitting and that the results of the OPLS-DA model are reliable.
2.3. Quantification of metabolites and predictive performance of CAP
The screened differential metabolites were analyzed by Venn diagram (FIG. 4A) and then two common differential metabolites, LPC14:0 and LPC16:1, were found in the two disease groups and were significantly different. Therefore, we intend to explore both of these metabolites further as potential biomarkers.
Then, the content of LPC14:0 and LPC16:1 in the human plasma sample is accurately determined by using UHPLC-MS/MS targeting and quasi-targeting analysis methods of LPC14:0 and LPC 16:1. As a result, as shown in the box-plot in fig. 4B, the concentrations of LPC14:0 and LPC16:1 in the acute phase of CAP patients were reduced compared to the healthy control group, while the concentration in the post-treatment recovery phase was increased, approaching the level of healthy people, with the concentration in the contemporaneous severe CAP disease group being lower than in the non-severe CAP disease group.
To study the diagnostic performance of these two metabolites, we performed a correlation analysis and plotted subject work characteristics (ROC) to assess their relationship to clinical features and diagnose sensitivity and specificity of CAP severity.
Clinical parameters (WBC, NE, PCT, CRP, BUN, scr, LDH) are commonly used in CAP clinical treatment to determine disease severity and treatment efficacy. Correlation between metabolites and clinical parameters was analyzed by Spearman correlation analysis (fig. 4C), and correlation coefficient data is shown in table 9. In the non-severe CAP disease group, LPC14:0 was inversely related to CRP (r= -0.430, p < 0.001) and PCT (r= -0511, p < 00.001), but there was no apparent correlation with WBC, NE, BUN, scr and LDH. . LPC16:1 was inversely related to CRP (r=0.309, p=0.002) and PCT (r=0.404, p < 0.001), with no correlation to other clinical parameters. In the severe CAP disease group, LPC14:0 was negatively correlated with WBCs (r= -0.304, p=0.012), NE% (r=0.356, p=0.0029), CRP (r=0.532, p < 0.001) and PCT (r=0.461, p < 00.001), with no correlation with Scr, LDH and BUN. LPC16:1 is inversely related to CRP (r= -0.479, p < 0.001) and PCT (r= -0420, p < 00.001), and has no correlation with other parameters.
TABLE 9 correlation analysis of LPC14:0 with non-severe CAP and severe CAP clinical parameters
Note that: CAP community-acquired pneumonia, NSCAP non-severe CAP, SCAP severe CAP, WBC white blood cells, NE% neutrophil percentage, CRP C reactive protein, procalcitonin, BUN blood urea nitrogen, scr serum creatinine, LDH lactate dehydrogenase, r: spearman correlation coefficient.
The area under the curve (AUC), the specificity and sensitivity of the ROC curve were used to evaluate the performance of both metabolites in predicting CAP severity. As shown in fig. 4D, LPC14:0 exhibited AUC values of 0.855, sensitivity of 0.750, specificity of 0.833, and significance p <0.001 at the time of diagnosis of non-severe CAP. AUC value of 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. AUC value for LPC16:1 was 0.848, sensitivity was 0.794, specificity was 0.882, significance was p <0.001. We also analyzed the diagnostic properties of CRP, PCT, WB, NE% and LDH, and the data are shown in table 10. Compared 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 ROC curve and sensitivity and specificity in non-severe CAP and severe CAP
Note that: CAP community acquired pneumonia, NSCAP non-severe CAP, SCAP severe CAP, ROC receptor operating characteristics, AUC area under curve, CI confidence interval, WBC white blood cells, NE% neutrophil percentage, CRP C reactive protein, procalcitonin, LDH lactate dehydrogenase
From the above results, we found that LPC14:0 correlated and predictive performance on CAP was superior to LPC16:1, whereas LPC16:1 was lower in lung tissue only in the mouse model of ALI induced with LPS. LPC14:0 showed significantly lower trend in both serum and lung tissues than healthy mice, which was substantially consistent with humans (FIGS. 4E-F). These results indicate that LPC14:0 can serve as a potential biomarker and therapeutic target for CAP; thus, the lipid was selected for subsequent in vitro and in vivo experiments.
Example 2: pharmaceutical application of LPC14:0
1. Method of
1.1 cell experiments
1.1.1 cell culture and CCK-8
RAW264.7 cells (China cell Bank of 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 LPS and LPC14:0 on cell viability was determined by CCK-8 at various drug concentrations. Cells were seeded in 96-well plates. Cells were then cultured in two 96-well plates and pre-treated with LPC14:0 (10, 20, 30, 40) μM for 1h, with one plate exposed to LPS (1 μg/mL) for 12h. 10uL of CCK-8 was added, incubated for 2h, and 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 LPC14:0 (20. Mu.M) for 1 hour. To 1X 10 5 Cells were added with 5. Mu.L of FITC Annexin V and 5. Mu.L of Propidium Iodide (PI) and incubated at 25℃for 15min in the absence of light. Flow cytometry detects the percentage of apoptosis and necrosis.
To measure ROS, cells were collected and incubated with 1mL of serum-free medium containing 1. Mu.L of DCFH-DA for 20 minutes in the dark at 37 ℃. After washing three times with cold PBS, the DCF fluorescence intensity of the cells was measured.
In addition, cells were collected after the same treatment, disrupted with ultrasound, and SOD and GSH levels were assessed using cell supernatants with an assay kit.
1.2 animal experiments
1.2.1 animal grouping and administration treatments
SPF-grade male C57BL/6 mice at 8 weeks of age were purchased from Zhejiang Weitonglihua laboratory animal science and technology Co., ltd (SYXK (Zhejiang) 2021-0017) and were adapted for 1 week. All animals were kept under SPF conditions. All experiments involving animals were performed in accordance with ethical policies and procedures approved by the ethical committee of the university of medical science in China (accession number 2021-0095).
For the first group of animals, mice were divided into two subgroups: control group (phosphate buffered saline (PBS) +1% BSA) and LPS group (5 mg/kg in PBS). LPS was instilled into the trachea to induce ALI in mice.
The second group of mice was randomly divided into four subgroups: control (phosphate buffered saline (PBS) +1% BSA), LPC14:0 only (10 mg/kg in 1% BSA, BSA diluted with PBS), LPS only (5 mg/kg in PBS), LPS (5 mg/kg) +LPC 14:0 (10 mg/kg). Mice were pretreated by subcutaneous injection of LPC14:0 (10 mg/kg), anesthetized with isoflurane (5% induction, 2% maintenance) after 2 hours, and LPS (5 mg/kg, diluted to 50ul with PBS) was injected into the trachea to induce mouse ALI. LPC14:0 (10 mg/kg) was subcutaneously administered again 10 hours after the intratracheal administration of LPS, and the control group was subcutaneously injected with 1% BSA and intratracheally instilled with PBS. 24 hours after LPS injection, mice were anesthetized with isoflurane and sacrificed by peeling, and then lung tissue samples, bronchoalveolar lavage (BALF) and serum were collected and stored at-80 ℃.
1.2.2 pneumosappan-eosin (H & E) and BALF assays
Histopathological examination was performed on lung tissue of mice not harvested for BALF. The tissue specimens were fixed in 4% paraformaldehyde for 48 hours, gradient dehydrated, paraffin embedded, then cut into 4 μm thick sections and stained with h & E.
After mice were sacrificed, 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. The protein concentration of untreated BLAF was determined using the BCA protein assay kit (Beyotime, china).
1.2.3 measurement of the lung wet/dry (W/D) ratio and the MPO content in lung tissue after 24 hours of LPS treatment the lung tissue was collected, washed with saline and blotted dry, weighed immediately to obtain a "wet" weight, and oven dried at 65 ℃ for 48 hours to obtain a "dry" weight. Their ratio may reflect oedema in lung tissue indirectly.
Lung tissue was homogenized and levels of Glutathione (GSH), superoxide dismutase (SOD), malondialdehyde (MDA) and Myeloperoxidase (MPO) in the homogenate were measured using a kit (institute of biotechnology in south tokyo, china).
1.2.4 ELISA
Cytokine was determined in BALF or cell culture supernatants using ELISA. BALF was obtained from each sample separately, centrifuged and the supernatant was collected. IL-1 beta, IL-6 and TNF-alpha protein levels were determined using ELISA kits (institute of biological engineering, nanjing, china).
In addition, RAW264.7 cells were cultured for 24 hours and then pretreated with LPC14:0 (20. Mu.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 optical densities at 450nm were measured.
1.2.5 Western blot analysis
20ug of protein was loaded in wells of a 10% polyacrylamide gel and subjected to sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) to isolate the protein. The proteins were then transferred to a polyvinylidene fluoride (PVDF) membrane, which was blocked in 5% skim milk for 1 hour at room temperature. Next, the membrane was incubated with primary antibody overnight at 4 ℃, then washed three times with TBST for 10 minutes each, then incubated with horseradish peroxidase (HRP) -conjugated secondary antibody for 1 hour at room temperature. And (3) detecting the expression of related proteins: NLRP3, TXNIP, caspase-1, IL-1β and β -actin served as internal reference proteins. Band detection was performed using ECL (Amersham Pharmacia Biotech, piscataway, NJ) and band intensity was quantified using Image lab gel analysis software.
2 results
2.1LPC 14:0 pretreatment reduces LPS-induced oxidative damage to RAW264.7 cells
We first investigated whether LPC14:0 pretreatment could protect RAW264.7 cells from LPS-induced oxidative stress. First, CCK-8 observed the effect of different doses of LPS and LPC14:0 on cell viability. The results showed that LPS was completely non-toxic to cells in the dosage range of 0.1-20. Mu.g/mL. LPS promoted cell proliferation (FIG. 5A) in the dose range of 0.1-1. Mu.g/mL, and thus 20. Mu.g/mL was used in the apoptosis experiments. LPC14:0, alone or in combination with LPS (1. Mu.g/ml), was non-toxic in the range of 0-20. Mu.M (FIG. 5B).
LPS stimulated RAW264.7 to produce ROS and triggered oxidative stress, resulting in oxidative damage of cells, while LPC14:0 pretreatment reduced apoptosis rate (FIGS. 5C, D). We further investigated the antioxidant effect of LPC 14:0. The results indicate that LPC14:0 pretreatment was effective in reducing ROS production (FIGS. 5E-F), and antioxidant enzyme (SOD, GSH) consumption (FIGS. 5G-H).
2.2LPC 14:0 inhibition of LPS-induced inflammatory response and NLRP3 inflammatory body activation in RAW264.7 cells
We continued to study the effect of LPC14:0 on LPS-induced inflammatory responses of RAW264.7 cells. We found that stimulation of RAW264.7 cells with LPS alone promoted secretion of IL-1β, IL-6 and TNF- α, while LPC14:0 inhibited the inflammatory factors described above (FIGS. 6A-C). Since LPC14:0 was found to be effective in reducing LPS-induced ROS production in RAW264.7 cells, while ROS stimulated the activation of TXNIP, and thus promoted the activation of NLRP3 inflammatory corpuscles, we continued to investigate whether LPC14:0 could block LPS-induced activation of NLRP3 inflammatory corpuscles in RAW 2647 cells. The results indicate that LPC14:0 treatment significantly inhibited LPS-induced expression of NLRP3, TXNIP, caspase-1 and IL-1β proteins (FIG. 6D-H).
2.3LPC 14:0 treatment reduces LPS-induced ALI (acute lung injury) in mice
Based on these in vitro results, we further investigated whether LPC14:0 treatment has protective effects on mouse ALI. As shown in fig. 7A, the lung tissue of the LPS group showed significant pathological changes, including intra-alveolar inflammatory cell accumulation, intra-alveolar hemorrhage, and alveolar wall thickening. However, LPC14:0 pretreatment significantly attenuated these lesions. Furthermore, LPC14:0 treatment reduced lung injury scores compared to LPS-treated group (fig. 7B). We determined the extent of pulmonary edema in mice by pulmonary W/D ratio and protein leakage in BALF. As shown in fig. 7C-D, the lung W/D ratio and protein concentration were significantly higher in LPS-stimulated mice than in control and LPC14:0 alone treated groups, while LPC14:0 pretreatment significantly reversed these inflammatory changes. In addition, LPS stimulation resulted in inflammatory cell aggregation in mouse BALF, LPC14:0 pretreatment was effective in inhibiting inflammatory cell aggregation (FIG. 7E). 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 14:0 treatment inhibiting LPS-stimulated inflammatory response, oxidative stress and NLRP3 inflammatory body activation in ALI mice
To observe the effect of LPC14:0 on LPS-induced inflammatory responses and oxidative stress in mice, we examined the secretion levels of inflammatory factors IL-1β, IL-6 and TNF- α in mouse BALF and the levels of GSH, SOD and MDA in lung homogenates. Our results indicate that LPC14:0 pretreatment, in addition to IL-6, not only effectively reduced the production of IL-1β, TNF- α and MDA, but also significantly reduced the consumption of SOD and GSH (FIG. 8A-F), which play a major role in inhibiting LPS-induced oxidative stress. In vitro cell experiments, we found that LPC14:0 effectively reduced LPS-induced activation of NLRP3 inflammatory corpuscles. Thus, this study further investigated whether LPC14:0 could block activation of NLRP3 inflammatory corpuscles in vivo. The results indicate that LPS stimulation significantly promoted expression of NLRP3, TXNIP, caspase-1 and IL-1β proteins, whereas LPC14:0 pretreatment significantly attenuated this effect (FIG. 8G-K).
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. It is therefore intended that the following claims be interpreted as including the 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 modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (9)
1. Use of an agent that determines the level of myristoyl lysophosphatidylcholine LPC14:0 in a sample for the preparation of a diagnostic product, characterized in that said product is used for diagnosing community-acquired pneumonia, a decrease in LPC14:0 in a sample compared to a predetermined reference value indicating that a subject has community-acquired pneumonia;
wherein the predetermined reference value is based on an average LPC14:0 level in the population of healthy people.
2. The use according to claim 1, wherein a decrease in 1-hexadecyl-2-lysophosphatidylcholine LPC16:1 and LPC14:0 in the sample compared to a predetermined reference value indicates that the subject has community-acquired pneumonia; wherein the predetermined reference value is based on average plasma LPC16:1 and LPC14:0 levels in the population of healthy people.
3. The use according to claim 2, wherein the product is for diagnosing recovery in a community-acquired pneumonia patient or evaluating 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. Use according to claim 4, wherein the predetermined reference value is based on plasma LPC16:1 and/or LPC14:0 levels of the subject in the acute phase of community acquired pneumonia, and an elevated LPC16:1 and/or LPC14:0 in the sample shows good recovery or an effective treatment regimen.
6. Use according to claim 2, wherein the product is for diagnosing a lifestyle likely to be protected against community-acquired pneumonia, wherein an elevated LPC16:1 and/or LPC14:0 in the sample compared to a predetermined reference value is indicative of a lifestyle capable of protecting against community-acquired pneumonia.
7. Use according to claim 2, characterized in that the level of LPC16:1 and/or LPC14:0 is determined in the sample and reference by ultra-high performance liquid tandem mass spectrometry.
8. Use of LPC14:0 as defined in claim 1 for the manufacture 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.
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