AIM2 and FCGR1A, two potential diagnostic biomarkers for distinguishing infection statuses of Mycobacterium tuberculosis

Abstract

Abstract Background Our study aims to identify novel diagnostic biomarkers for distinguishing different infection statuses of M. tuberculosis. Methods Differential genes (DEGs) of different infection statuses of M. tuberculosis from the GEO datasets were analyzed using GEO2R. The interactions between the proteins encoded by the DEGs were analyzed using STRING; the protein-protein interaction network was visualized using Cytoscape. The validation was performed by real-time PCR and ELISA, and ROC analysis of DEGs was performed using R package pROC. Results 80 DEGs were identified from the GSE19439, GSE83456, and GSE19444 datasets for ATB and healthy controls (HC). 14 DEGs with the largest values of betweenness were screened using Cytoscape. 55 DEGs for distinguishing active and latent TB were screened in the datasets GSE39941 and GSE19439, and 8 DEGs with the highest values of betweenness were screened using Cytoscape. Furthermore, the study also revealed increased expression levels of genes AIM2 and FCGR1A in HC, LTBI, and ATB. The expression levels of genes FCGR1A and AIM2 in ATB and HC were validated using real-time PCR, and the levels of serum FCGR1A protein in ATB and HC were validated using ELISA. Conclusion AIM2 and FCGR1A in HC, LTBI, and ATB showed an increasing trend and can be used as diagnostic biomarkers for distinguishing different infection statuses of M. tuberculosis.