MARATTO

article · Frontiers in Tropical Diseases

TNF and HNRNPL Related Immunoregulatory Long non-coding RNA (THRIL) and long intergenic noncoding RNA-p21 (lincRNA-p21) as potential useful biomarkers for the diagnosis of tuberculosis

20223 citationsOpen accessUniversity of Douala

Abstract

Early diagnosis is crucial in controlling tuberculosis globally and in developing countries with the emergence of drug-resistant Mycobacterium tuberculosis strains. Long non-coding RNAs (lncRNAs) are promising tuberculosis diagnostic biomarkers. Two lncRNA diagnostic markers, lncRNA THRIL and lincRNA-p21, were studied as tuberculosis diagnostic biomarkers. This cross-sectional study was conducted at the Center of Respiratory Diseases of LAQUINTINIE hospital and the National Veterinary Laboratory of Douala from December 2020 to August 2021. The ability of lncRNAs to distinguish between 19 healthy controls, 15 latent tuberculosis, and 21 active tuberculosis was estimated using quantitative polymerase chain reaction and Receiver Operating Characteristic curve analysis. Our analysis showed that lncRNA THRIL and lincRNA-p21 were significantly upregulated (P <0.05) in active and latent tuberculosis compared with healthy controls. LincRNA-p21 expression was significantly increased (P <0.05) in active tuberculosis compared with latent tuberculosis, whereas lncRNA THRIL was not significantly affected (P ≥0.05). Both lncRNA THRIL and lincRNA-p21 showed excellent performance in classifying latent tuberculosis and healthy controls (AUC = 92.86%). Furthermore, lncRNA THRIL was good at discriminating active tuberculosis from healthy controls (AUC = 89.79%), while lincRNA-p21 showed excellent discriminating performance (AUC = 100%). LncRNA THRIL was identified as a poor discriminator of latent tuberculosis from active tuberculosis (AUC = 64.28%), while lincRNA-p21 showed excellent diagnostic performance in this distinction (AUC = 92.86%). Our cross-sectional study suggests that lncRNA THRIL and lincRNA-p21 are promising tuberculosis diagnostic biomarkers that can differentiate between latent and active infection.

Research topics

  • Mycobacterium research and diagnosis
  • Cancer-related molecular mechanisms research
  • Tuberculosis Research and Epidemiology

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.3389/fitd.2022.969307

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.