AUTHOR=Lin Yingying , Lai Xiaofan , Huang Shaojie , Pu Lvya , Zeng Qihao , Wang Zhongxing , Huang Wenqi 

TITLE=Identification of diagnostic hub genes related to neutrophils and infiltrating immune cell alterations in idiopathic pulmonary fibrosis

JOURNAL=Frontiers in Immunology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2023.1078055

DOI=10.3389/fimmu.2023.1078055

ISSN=1664-3224

ABSTRACT=Background: There was still lacks of specific indicators to diagnose idiopathic pulmonary fibrosis (IPF). And the role of immune responses in IPF was elusive. In this study, we aimed to identify hub genes for diagnosing IPF and explore the immune microenvironment in IPF.

Methods: We identified the differentially expressed genes (DEGs) between IPF and control using the GEO database. Combined LASSO regression and SVM-RFE machine learning algorithms, we identified hub genes. Their differential expression was further validated in bleomycin-induced pulmonary fibrosis mice models and a meta-GEO cohort merged with five GEO datasets. Then we used hub genes to construct a diagnostic model. All GEO datasets met the inclusion criteria and verification methods, including ROC curve, calibration curve (CC), decision curve analysis (DCA) and clinical impact curve (CIC) were performed to validate the reliability of the model. Through the Cell Type Identification by Estimating Relative Subsets of RNA Transcripts algorithm, we analyzed the correlation between immune-infiltrating cells and hub genes and the changes of diverse immune-infiltrating cells in IPF.

Results:  A total of 412 DEGs were identified between IPF and healthy controls, of which, 283 were upregulated and 129 were downregulated. Through machine learning, three hub genes (ASPN, SFRP2, SLCO4A1) were screened. And we confirmed their differential expression using pulmonary fibrosis mice models by qPCR, western blotting and immunofluorescence staining and the meta-GEO cohort. There was intense correlation between three hub genes and neutrophils. Then we constructed a diagnostic model for identifying IPF. And the area under the curve were 1.000 and 0.962 respectively. Other external validation cohorts, CC, DCA and CIC also showed a good agreement. There was also significant correlation between IPF and immune-infiltrating cells. Most immune-infiltrating cells involved in activating adaptive immune responses were increased in IPF and a majority of innate immune cells were reduced. 

Conclusion: Our study demonstrated that three hub genes (ASPN, SFRP2, SLCO4A1) associated with neutrophils and the model constructed by them showed a good diagnostic value in IPF. And there was significant correlation between IPF and immune-infiltrating cells, indicating the potential role of immune regulation on the pathological process of IPF.