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A plasma 3-marker microRNA biosignature distinguishes spinal tuberculosis from other spinal destructive diseases and pulmonary tuberculosis
Accurate spinal tuberculosis (TB) diagnosis is of utmost importance for adequately treating and managing the disease. Given the need for additional diagnostic tools, this study aimed to investigate the utility of host serum miRNA biomarkers for diagnosing and distinguishing spinal tuberculosis (STB)...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10011472/ https://www.ncbi.nlm.nih.gov/pubmed/36926516 http://dx.doi.org/10.3389/fcimb.2023.1125946 |
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author | Liang, Qiang Jin, Weidong Huang, Zhigang Yin, Huquan Liu, Shengchun Liu, Liehua Song, Xiangwei Wang, Zili Fei, Jun |
author_facet | Liang, Qiang Jin, Weidong Huang, Zhigang Yin, Huquan Liu, Shengchun Liu, Liehua Song, Xiangwei Wang, Zili Fei, Jun |
author_sort | Liang, Qiang |
collection | PubMed |
description | Accurate spinal tuberculosis (TB) diagnosis is of utmost importance for adequately treating and managing the disease. Given the need for additional diagnostic tools, this study aimed to investigate the utility of host serum miRNA biomarkers for diagnosing and distinguishing spinal tuberculosis (STB) from pulmonary tuberculosis (PTB) and other spinal diseases of different origins (SDD). For a case-controlled investigation, a total of 423 subjects were voluntarily recruited, with 157 cases of STB, 83 cases of SDD, 30 cases of active PTB, and 153 cases of healthy controls (CONT) in 4 clinical centers. To discover the STB-specific miRNA biosignature, a high-throughput miRNA profiling study was performed in the pilot study with 12 cases of STB and 8 cases of CONT using the Exiqon miRNA PCR array platform. A bioinformatics study identified that the 3-plasma miRNA combination (hsa-miR-506-3p, hsa-miR-543, hsa-miR-195-5p) might serve as a candidate biomarker for STB. The subsequent training study developed the diagnostic model using multivariate logistic regression in training data sets, including CONT(n=100) and STB (n=100). Youden’s J index determined the optimal classification threshold. Receiver Operating Characteristic (ROC) curve analysis showed that 3-plasma miRNA biomarker signatures have an area under the curve (AUC) = 0.87, sensitivity = 80.5%, and specificity = 80.0%. To explore the possible potential to distinguish spinal TB from PDB and other SDD, the diagnostic model with the same classification threshold was applied to the analysis of the independent validation data set, including CONT(n=45), STB(n=45), brucellosis spondylitis (BS, n=30), PTB (n=30), spinal tumor (ST, n=30) and pyogenic spondylitis (PS, n=23). The results showed diagnostic model based on three miRNA signatures could discriminate the STB from other SDD groups with sensitivity=80%, specificity=96%, Positive Predictive Value (PPV)=84%, Negative Predictive Value (NPV)=94%, the total accuracy rate of 92%. These results indicate that this 3-plasma miRNA biomarker signature could effectively discriminate the STB from other spinal destructive diseases and pulmonary tuberculosis. The present study shows that the diagnostic model based on 3-plasma miRNA biomarker signature (hsa-miR-506-3p, hsa-miR-543, hsa-miR-195-5p) may be used for medical guidance to discriminate the STB from other spinal destructive disease and pulmonary tuberculosis. |
format | Online Article Text |
id | pubmed-10011472 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100114722023-03-15 A plasma 3-marker microRNA biosignature distinguishes spinal tuberculosis from other spinal destructive diseases and pulmonary tuberculosis Liang, Qiang Jin, Weidong Huang, Zhigang Yin, Huquan Liu, Shengchun Liu, Liehua Song, Xiangwei Wang, Zili Fei, Jun Front Cell Infect Microbiol Cellular and Infection Microbiology Accurate spinal tuberculosis (TB) diagnosis is of utmost importance for adequately treating and managing the disease. Given the need for additional diagnostic tools, this study aimed to investigate the utility of host serum miRNA biomarkers for diagnosing and distinguishing spinal tuberculosis (STB) from pulmonary tuberculosis (PTB) and other spinal diseases of different origins (SDD). For a case-controlled investigation, a total of 423 subjects were voluntarily recruited, with 157 cases of STB, 83 cases of SDD, 30 cases of active PTB, and 153 cases of healthy controls (CONT) in 4 clinical centers. To discover the STB-specific miRNA biosignature, a high-throughput miRNA profiling study was performed in the pilot study with 12 cases of STB and 8 cases of CONT using the Exiqon miRNA PCR array platform. A bioinformatics study identified that the 3-plasma miRNA combination (hsa-miR-506-3p, hsa-miR-543, hsa-miR-195-5p) might serve as a candidate biomarker for STB. The subsequent training study developed the diagnostic model using multivariate logistic regression in training data sets, including CONT(n=100) and STB (n=100). Youden’s J index determined the optimal classification threshold. Receiver Operating Characteristic (ROC) curve analysis showed that 3-plasma miRNA biomarker signatures have an area under the curve (AUC) = 0.87, sensitivity = 80.5%, and specificity = 80.0%. To explore the possible potential to distinguish spinal TB from PDB and other SDD, the diagnostic model with the same classification threshold was applied to the analysis of the independent validation data set, including CONT(n=45), STB(n=45), brucellosis spondylitis (BS, n=30), PTB (n=30), spinal tumor (ST, n=30) and pyogenic spondylitis (PS, n=23). The results showed diagnostic model based on three miRNA signatures could discriminate the STB from other SDD groups with sensitivity=80%, specificity=96%, Positive Predictive Value (PPV)=84%, Negative Predictive Value (NPV)=94%, the total accuracy rate of 92%. These results indicate that this 3-plasma miRNA biomarker signature could effectively discriminate the STB from other spinal destructive diseases and pulmonary tuberculosis. The present study shows that the diagnostic model based on 3-plasma miRNA biomarker signature (hsa-miR-506-3p, hsa-miR-543, hsa-miR-195-5p) may be used for medical guidance to discriminate the STB from other spinal destructive disease and pulmonary tuberculosis. Frontiers Media S.A. 2023-02-28 /pmc/articles/PMC10011472/ /pubmed/36926516 http://dx.doi.org/10.3389/fcimb.2023.1125946 Text en Copyright © 2023 Liang, Jin, Huang, Yin, Liu, Liu, Song, Wang and Fei https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cellular and Infection Microbiology Liang, Qiang Jin, Weidong Huang, Zhigang Yin, Huquan Liu, Shengchun Liu, Liehua Song, Xiangwei Wang, Zili Fei, Jun A plasma 3-marker microRNA biosignature distinguishes spinal tuberculosis from other spinal destructive diseases and pulmonary tuberculosis |
title | A plasma 3-marker microRNA biosignature distinguishes spinal tuberculosis from other spinal destructive diseases and pulmonary tuberculosis |
title_full | A plasma 3-marker microRNA biosignature distinguishes spinal tuberculosis from other spinal destructive diseases and pulmonary tuberculosis |
title_fullStr | A plasma 3-marker microRNA biosignature distinguishes spinal tuberculosis from other spinal destructive diseases and pulmonary tuberculosis |
title_full_unstemmed | A plasma 3-marker microRNA biosignature distinguishes spinal tuberculosis from other spinal destructive diseases and pulmonary tuberculosis |
title_short | A plasma 3-marker microRNA biosignature distinguishes spinal tuberculosis from other spinal destructive diseases and pulmonary tuberculosis |
title_sort | plasma 3-marker microrna biosignature distinguishes spinal tuberculosis from other spinal destructive diseases and pulmonary tuberculosis |
topic | Cellular and Infection Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10011472/ https://www.ncbi.nlm.nih.gov/pubmed/36926516 http://dx.doi.org/10.3389/fcimb.2023.1125946 |
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