Interferon characterization associates with asthma and is a potential biomarker of predictive diagnosis

Interferon (IFN) plays a role in immune and inflammation responses. However, the effect of IFN in asthma is still not fully clear. The present study was conducted to better understand the role of IFN signatures in asthma. Blood samples from case?control studies (study 1: 348 asthmas and 39 normal controls and validation study 2: 411 asthmas and 87 normal controls) were enrolled. The single-sample gene set enrichment analysis (ssGSEA) method was used to quantify the levels of 74 IFN signatures. Gene Ontology analysis and pathway function analysis were performed for functional analysis and a protein?protein interaction (PPI) network was constructed. The area under the curve (AUC) value was used to evaluate the diagnostic ability. In our work, IFN-? response-DN, negative regulation of IFN-? secretion, IFNG pathway, negative regulation of response to IFN-?, and type 1 IFN biosynthetic process showed higher levels in asthma. Functional analysis demonstrated that pathway and biological process involved in IFN signaling pathway, regulation of type 1 IFN production and response to IFN-?. Hub IFN-related genes were identified, and their combination as biomarker exhibited a good diagnostic capacity for asthma (AUC = 0.832). These findings offered more insight into the underlying mechanism of how IFN signatures affected asthma. The use of the easy-to-apply IFN-related genes might serve as a promising blood-based biomarker for early diagnosis of asthma. ABSTRACT Interferon (IFN) plays a role in immune and inflammation responses. However, the effect of IFN in asthma is still not fully clear. The present study was conducted to better understand the role of IFN signatures in asthma. Blood samples from case?control studies (study 1: 348 asthmas and 39 normal controls and validation study 2: 411 asthmas and 87 normal controls) were enrolled. The single-sample gene set enrichment analysis (ssGSEA) method was used to quantify the levels of 74 IFN signatures. Gene Ontology analysis and pathway function analysis were performed for functional analysis and a protein?protein interaction (PPI) network was constructed. The area under the curve (AUC) value was used to evaluate the diagnostic ability. In our work, IFN-? response-DN, negative regulation of IFN-? secretion, IFNG pathway, negative regulation of response to IFN-?, and type 1 IFN biosynthetic process showed higher levels in asthma. Functional analysis demonstrated that pathway and biological process involved in IFN signaling pathway, regulation of type 1 IFN production and response to IFN-?. Hub IFN-related genes were identified, and their combination as biomarker exhibited a good diagnostic capacity for asthma (AUC = 0.832). These findings offered more insight into the underlying mechanism of how IFN signatures affected asthma. The use of the easy-to-apply IFN-related genes might serve as a promising blood-based biomarker for early diagnosis of asthma.

Automated summary

The study found that levels of IFN-related genes were higher in asthma patients, suggesting their potential as biomarkers for early diagnosis.