Identification of Serum TRNA-derived Small RNAs Biosignature for Diagnosis of Tuberculosis

Overview

Journal Emerg Microbes Infect

Date 2025 Jan 24

PMID 39851057

Authors

Zikun Huang

Qing Luo

Cuifen Xiong

Haiyan Zhu

Chao Yu

Jianqing Xu

Yiping Peng

Junming Li

Aiping Le

Affiliations

Soon will be listed here.

Abstract

The tRNA-derived small RNAs (tsRNAs) are a new class of non coding RNAs, which are stable in body fluids and can be used as potential biomarkers for disease diagnosis. However, the exact value of tsRNAs in the diagnosis of tuberculosis (TB) is still unclear. The objective of the present study was to evaluate the performance of the serum tsRNAs biosignature to distinguish between active TB, healthy controls, latent TB infection, and other respiratory diseases. The differential expression profiles of tsRNAs in serum from active TB patients and healthy controls were analyzed by high-throughput sequencing. A total of 905 subjects were prospectively recruited for our study from three different cohorts. Levels of tsRNA-Gly-CCC-2, tsRNA-Gly-GCC-1, and tsRNA-Lys-CTT-2-M2 were significantly elevated in the serum of TB patients compared to non-TB individuals, showing a correlation with lung injury severity and acid-fast bacilli grades in TB patients. The accuracy of the three-tsRNA biosignature for TB diagnosis was evaluated in the training ( = 289), test ( = 124), and prediction ( = 292) groups. By utilizing cross-validation with a random forest algorithm approach, the training cohort achieved a sensitivity of 100% and specificity of 100%. The test cohort exhibited a sensitivity of 75.8% and a specificity of 91.2%. Within the prediction group, the sensitivity and specificity were 73.1% and 92.5%, respectively. The three-tsRNA biosignature generally decreased within 3 months of treatment and then remained stable. In conclusion, the three-tsRNA biosignature might serve as biomarker to diagnose TB and to monitor the effectiveness of treatment in a high-burden TB clinical setting.

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