Screening Serum Markers To Predict The Efficacy Of Anti-IgE Monoclonal Antibody Therapy In Asthma Based On Bioinformatics

BackgroundBronchial asthma is a chronic airway disease that is heterogeneous in terms of age of onset,associated risk factors,severity,comorbidities,and response to treatment.Chronic inflammation of the airways is the essence of asthma pathogenesis and is an important mechanism leading to airway hyperresponsiveness,causing variable and reversible airflow limitation.However,with the prolongation of the disease,recurrent episodes of long-term persistent inflammation and repair of the airways lead to tissue proliferation and airway remodeling,resulting in irreversible airflow limitation,making asthma intractable and increasing the global disease burden.Currently,there is no treatment for airway remodeling.Early control of airway inflammation is an effective way to prevent airway remodeling.In addition to glucocorticoids,biologics targeting inflammatory factors have been effective in treating moderate to severe asthma.Omalizumab is the first biologic agent used in the treatment of moderate to severe allergic asthma.It is an anti-IgE monoclonal antibody,which mainly controls airway inflammation by reducing the level of free IgE.However,not all patients have improved or controlled with anti-IgE monoclonal antibody treatment,which may be related to the complex mechanism and heterogeneity of asthma.The search for biomarkers that predict response to anti-IgE monoclonal antibody therapy in asthma patients may help to identify populations of real clinical benefit,thereby optimizing treatment and reducing the disease burden.ObjectiveTo find potential biomarkers that can predict the clinical efficacy of anti-IgE monoclonal antibody through simple and feasible methods,so as to better guide the application of anti-IgE monoclonal antibody in asthma patients and promote the development of precision medicine.MethodsIn the first part of the study,differentially expressed genes(DEGs)between asthma patients responding to anti-IgE monoclonal antibody and those not responding to anti-IgE monoclonal antibody in the expression profiling dataset GSE134544 were analyzed by bioinformatics.The GO enrichment analysis and the KEGG pathway enrichment analysis were performed on DEGs to explore their potential biological functions.The core genes in DEGs of the two groups were screened by constructing a PPI network and functional modules,and the boxplot and ROC curve of the core genes were drawn to test their ability to predict the clinical efficacy of anti-IgE monoclonal antibody.Immunoinfiltration analysis was used to investigate the potential mechanism for the significant difference in core genes between the responder and non-responder groups.Finally,logistic regression analysis was used to construct a predictive model for the core gene.In the second part of the study,the clinical data of asthma patients treated with anti-IgE monoclonal antibody in our hospital and their serum sample before starting the treatment were collected.Patients were grouped according to treatment course and curative effect.The level of core gene expression products in the serum of patients was detected by enzyme-linked immunosorbent assay(ELISA),and its ability to predict the clinical efficacy of anti-IgE monoclonal antibody was analyzed by ROC curve.ResultsIn the first part of the study,131 DEGs were identified,which were mainly related to the interaction of cytokines and their receptors,cellular communication and other functions.Nine core genes,including HBD,HBAI,HBE1,SELP,CXCL5,CXCR3,CD248,SPARC and FSTL1,had significant and complex interactions at the protein level.At the transcription level,HBD,HBA1,HBE1,SELP,CXCL5,SPARC and FSTL1 in the non-responder group were higher than those in the responder group,while CXCR3 and CD248 in the non-responder group were lower than those in the responder group.The ROC curves show that core genes have some predictive efficacy.Immune cell infiltration analysis revealed significant correlations between FSTL1 and eosinophils,SELP and eosinophils,and CXCL5 and Th1 and Th2 cells.By constructing a predictive model,it was found that the model had a higher ability to distinguish between responders and non-responders to anti-IgE monoclonal antibody treatment when CXCL5,CXCR3,and HBA1 were included together.In the second part of the study,FSTL 1,SPARC,CXCL 5,and SELP were measured in patient serum.Two conditions were explored in asthma when anti-IgE treatment was over or not over 16 weeks.According to the overall level of asthma control,24 patients who were treated for more than 16 weeks were divided into a responder group(17 patients)and a nonresponder group(7 patients).There were no significant differences in baseline demographic and clinical characteristics between the two groups,and the changes in ACT scores before and after treatment were statistically different(P=0.005).The serum levels of FSTL1(P=0.003)and CXCL5(P=0.02)were significantly higher in the non-responder group than in the responder group,with ROC curves showing the area under the curve(AUC)of 0.887 and 0.807,respectively.The differences in serum levels of SPARC and SELP between the two groups were not statistically significant.The 16 patients who had not been treated for more than 16 weeks were divided into an effective group(10 patients)and an ineffective group(6 patients)according to their reasons for stopping treatment on their own.The mean age of the patients in the ineffective group was higher than that of the effective group(P=0.01),the mean eosinophil count was lower than that of the effective group(P=0.012),and there were no significant differences in other demographic and clinical characteristics.The serum levels of FSTL1(P=0.006)and CXCL5(P=0.03)were higher in the ineffective group than in the effective group,and the ROC curves showed AUC of 1.000 and 0.833,respectively.There was no statistical difference in serum SPARC and SELP between the two groups.ConclusionsAt the transcription level,high expression of CXCL5,HBA1 and low expression of CXCR3 in peripheral blood may be related to the non-response to anti-IgE monoclonal antibody therapy in asthmatic patients.At the protein level,serum levels of FSTL1 and CXCL5 at baseline may serve as biomarkers to predict the clinical efficacy of anti-IgE monoclonal antibody therapy in asthmatic patients.