Tuberculosis, one of the deadliest infectious diseases worldwide, is difficult to diagnose. As long noncoding RNAs (lncRNAs) were demonstrated to be promising biomarkers, we aimed to identify lncRNAs in plasma as potential biomarkers for tuberculosis.

We analyzed a GEO dataset (GSE94907) to identify the differential lncRNAs in serum exosomes between active tuberculosis (ATB) patients and healthy controls. To search for promising candidates that can be used for tuberculosis diagnosis, we excluded low-abundance lncRNAs using a cutoff value of FPKM >5. Four lncRNAs were selected for validation using real-time quantitative PCR in 69 ATB patients and 69 healthy individuals. A receiver operating characteristic (ROC) curve was constructed to evaluate the diagnostic value of these lncRNAs for ATB.

Integrated analysis of the GEO dataset and NONCODE database identified nine dysregulated lncRNAs in ATB patient serum exosomes. Compared with the heathy controls, NONHSAT101518.2, NONHSAT067134.2, NONHSAT148822.1 and NONHSAT078957.2 were significantly downregulated in ATB patient plasma. ROC curve analysis suggests that these four lncRNAs can discriminate ATB from healthy individuals with high specificity and sensitivity.

We identified four differentially expressed lncRNAs in ATB patient plasma that can be used as potential diagnostic biomarkers of ATB.