Combining bioinformatics and biological detection to identify novel biomarkers for diagnosis and prognosis of pulmonary tuberculosis.

ABSTRACT:

Objectives

To identify the novel and promising indicators for pulmonary tuberculosis (PTB) patients.

Methods

The study was carried out between June 2016 and June 2019. Three RNA sequencing or microarray datasets of TB infection were used to identify the potential genes showing a common expression trend. The expression level of screened targets was determined by reverse transcription polymerase chain reaction and ELISA using samples of whole blood and peripheral blood mononuclear cells (PBMCs) isolated from 69 PTB patients and 69 healthy volunteers. The potential of the identified targets to predict the treatment outcomes was further studied.

Results

Bioinformatics analysis demonstrated that a total of 91 genes were up-regulated in all the 3 datasets; among them, the e

SUBMITTER: Zhao G 

PROVIDER: S-EPMC7841615 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature