Identification of serum tRNA-derived small RNAs biosignature for diagnosis of tuberculosis.

Identification of serum tRNA-derived small RNAs biosignature for diagnosis of tuberculosis.

Publication date: Jan 24, 2025

ABSTRACTThe 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 (n = 289), test (n = 124), and prediction (n = 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.

Concepts Keywords
Biomarker Biomarker
Fast Diagnosis
Forest Tuberculosis
Tuberculosis

Semantics

Type Source Name
disease MESH tuberculosis
pathway KEGG Tuberculosis
disease MESH infection
disease MESH respiratory diseases
drug DRUGBANK Glycine
drug DRUGBANK L-Lysine
disease MESH lung injury
disease IDO algorithm

Original Article

Leave a Comment

Your email address will not be published. Required fields are marked *