| Background:Asthma is a chronic airway inflammatory disease that seriously endangers human health,and its prevalence is increasing year by year.Most asthma patients can achieve clinical symptoms control through standardized drug treatment,but some severe asthma patients are still not ideal for symptom control even under active drug treatment.Phenotypic-based individualized therapy is a new direction in the treatment of asthma.Identifying the characteristics of a particular phenotype will contribute to the prognosis assessment of asthma and may contribute to the choice of individualized treatment options.But due to the heterogeneity of asthma,the phenotype does not explain all patients,and treatment does not benefit all asthma patients.Biomarkers can provide information about disease diagnosis,prognosis assessment,phenotype,and treatment response.Therefore,further research is needed to find more biomarkers,and the use of appropriate biomarkers for anatomical phenotype of asthma can contribute to the development and guidance of asthma drugs.Studies have found that lipid metabolism may be involved in the pathogenesis of asthma.Lipids are a basic component of biofilms and a metabolite of the body,playing a key role in cellular energy storage,composition and signaling.Through lipidomics analysis,lipids that are abnormally expressed in the body’s disease state can be found,which can be used for the study of disease biomarkers and pathogenesis.Therefore,we can study the potential lipid biomarkers of asthma,which may be used to find new therapeutic targets and to guide individualized treatment of asthma.Objectives:In this study,ultra high performance liquid chromatography-electrospray ionisation-mass spectrometry(UHPLC-ESI-MS)method was used to analyze the lipids of asthma patients and the purpose is to find potential lipid biomarkers for asthma.Methods:1.Collection of subjects 35 asthma patients(asthma group)and 32 healthy subjects(control group)diagnosed in the First Affiliated Respiratory Medicine Department of Zhengzhou University from July 2018 to December 2018 were included in the study.We collected blood from all subjects and separate plasma for analysis and collected basic information such as age,sex,and body mass index.2.Detection of plasma malondialdehyde Based on the reaction of MDA and thiobarbituric acid,which the color reaction of the red product can be produced,the MDA in the plasma of the two groups was quantitatively detected.3.Plasma lipidomics analysis Plasma lipid analysis was performed by UHPLC-ESI-MS method,and peak identification,lipid identification,and quantification were performed using LipidSearch software version 4.1 software,and the total peak area was normalized to the extracted data.Multivariate statistical analysis and univariate statistical analysis were performed on the preprocessed date by Paretocaling using Simca-P14.1 software.Multivariate statistical analysis include principal component analysis and partial least squares-discriminant analysis(PLS-DA),orthogonal-partial least squares-discriminant analysis(OPLS-DA),univariate statistical analysis include T test,fold change analysis,R software was used to draw heat map.4.Screening of significant differential lipids Lipids satisfying both the variable importance for the projection(VIP)>1 and P < 0.05 were selected as lipids with significant differences.The receiver operating characteristic(ROC)curves of significant differential lipids were plotted using SPSS 21.0 software,and the areas under the ROC curves were compared using the Z test.The measured data of the normal distribution is expressed by x?±s and compared by t test.P < 0.05 difference was statistically significant.Results:1.There are no significant difference in age,gender and BMI between asthmatic group and control group(P>0.05).2.The plasma MDA content in the asthma group is(7.75±1.83)μM,which is higher than that in the control group(5.28±1.94)μM,and the difference is statistically significant(P<0.05).3.The PLS-DA model and the OPLS-DA model can distinguish plasma samples between the asthma group and the control group,and the models have not been fitted.4.1311 lipids are detected in the asthma group and the control group,which are 711 glycerophospholipids,350 sphingolipids,233 glycerides,20 fatty acyl groups,13 sterols,9 glycolipids,2 pregnenol ketone fat.5.There are 16 significant differential lipids in plasma between the asthma group and the control group,which are PC(18:1p/18:2),PC(16:0/18:1),and PC(18:0/22:5),PC(18:0e/20:4),PC(18:1p/20:3),PC(40:4),PC(32:1),PC(18:1/22:5),PC(18:0/20:3),SM(d20:0/18:2),PS(39:0),SM(d18:1/18:1),SM(d18:0/18:1),SM(d22:1/18:1),PE(18:1/18:2),PS(18:0/20:4).Compared with the control group,except for PE(18:1/18:2)and PS(18:0/20:4),the other 14 significant differential lipids in the asthma group are up-regulated.6.Correlation analysis of significant differential lipids show a positive correlation between sphingomyelin(SM)and phosphatidylcholine(PC).7.Among the 14 up-regulated significant differential lipids,the areas under the ROC curves of PC(18:1p/18:2)、PC(16:0/18:1)、PC(18:0/22:5)、PC(18:0e/20:4)、PC(18:1p/20:3)、PC(40:4)、PC(32:1)、PC(18:1/22:5)are 0.687,0.685,0.677,0.676,0.675,0.664,0.655,0.641,respectively.And the difference are statistically significant(P <0.05).Conclusions:1.Asthma patients have lipid metabolism disorders,with mainly changes in the metabolism of glycerophospholipids and sphingomyelin.2.PC(18:1p/18:2),PC(16:0/18:1),PC(18:0/22:5),PC(18:0e/20:4),PC(18: 1p/20:3),PC(40:4),PC(32:1),and PC(18:1/22:5)may be potential lipid biomarkers of asthma. |
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