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Systematic Expression Profiling Analysis Identifies Specific MicroRNA-Gene Interactions that May Differentiate between Active and Latent Tuberculosis Infection
Tuberculosis (TB) is the second most common cause of death from infectious diseases. About 90% of those infected are asymptomatic—the so-called latent TB infections (LTBI), with a 10% lifetime chance of progressing to active TB. To further understand the molecular pathogenesis of TB, several molecul...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4167957/ https://www.ncbi.nlm.nih.gov/pubmed/25276827 http://dx.doi.org/10.1155/2014/895179 |
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author | Wu, Lawrence Shih-Hsin Lee, Shih-Wei Huang, Kai-Yao Lee, Tzong-Yi Hsu, Paul Wei-Che Weng, Julia Tzu-Ya |
author_facet | Wu, Lawrence Shih-Hsin Lee, Shih-Wei Huang, Kai-Yao Lee, Tzong-Yi Hsu, Paul Wei-Che Weng, Julia Tzu-Ya |
author_sort | Wu, Lawrence Shih-Hsin |
collection | PubMed |
description | Tuberculosis (TB) is the second most common cause of death from infectious diseases. About 90% of those infected are asymptomatic—the so-called latent TB infections (LTBI), with a 10% lifetime chance of progressing to active TB. To further understand the molecular pathogenesis of TB, several molecular studies have attempted to compare the expression profiles between healthy controls and active TB or LTBI patients. However, the results vary due to diverse genetic backgrounds and study designs and the inherent complexity of the disease process. Thus, developing a sensitive and efficient method for the detection of LTBI is both crucial and challenging. For the present study, we performed a systematic analysis of the gene and microRNA profiles of healthy individuals versus those affected with TB or LTBI. Combined with a series of in silico analysis utilizing publicly available microRNA knowledge bases and published literature data, we have uncovered several microRNA-gene interactions that specifically target both the blood and lungs. Some of these molecular interactions are novel and may serve as potential biomarkers of TB and LTBI, facilitating the development for a more sensitive, efficient, and cost-effective diagnostic assay for TB and LTBI for the Taiwanese population. |
format | Online Article Text |
id | pubmed-4167957 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-41679572014-09-28 Systematic Expression Profiling Analysis Identifies Specific MicroRNA-Gene Interactions that May Differentiate between Active and Latent Tuberculosis Infection Wu, Lawrence Shih-Hsin Lee, Shih-Wei Huang, Kai-Yao Lee, Tzong-Yi Hsu, Paul Wei-Che Weng, Julia Tzu-Ya Biomed Res Int Research Article Tuberculosis (TB) is the second most common cause of death from infectious diseases. About 90% of those infected are asymptomatic—the so-called latent TB infections (LTBI), with a 10% lifetime chance of progressing to active TB. To further understand the molecular pathogenesis of TB, several molecular studies have attempted to compare the expression profiles between healthy controls and active TB or LTBI patients. However, the results vary due to diverse genetic backgrounds and study designs and the inherent complexity of the disease process. Thus, developing a sensitive and efficient method for the detection of LTBI is both crucial and challenging. For the present study, we performed a systematic analysis of the gene and microRNA profiles of healthy individuals versus those affected with TB or LTBI. Combined with a series of in silico analysis utilizing publicly available microRNA knowledge bases and published literature data, we have uncovered several microRNA-gene interactions that specifically target both the blood and lungs. Some of these molecular interactions are novel and may serve as potential biomarkers of TB and LTBI, facilitating the development for a more sensitive, efficient, and cost-effective diagnostic assay for TB and LTBI for the Taiwanese population. Hindawi Publishing Corporation 2014 2014-09-04 /pmc/articles/PMC4167957/ /pubmed/25276827 http://dx.doi.org/10.1155/2014/895179 Text en Copyright © 2014 Lawrence Shih-Hsin Wu et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Wu, Lawrence Shih-Hsin Lee, Shih-Wei Huang, Kai-Yao Lee, Tzong-Yi Hsu, Paul Wei-Che Weng, Julia Tzu-Ya Systematic Expression Profiling Analysis Identifies Specific MicroRNA-Gene Interactions that May Differentiate between Active and Latent Tuberculosis Infection |
title | Systematic Expression Profiling Analysis Identifies Specific MicroRNA-Gene Interactions that May Differentiate between Active and Latent Tuberculosis Infection |
title_full | Systematic Expression Profiling Analysis Identifies Specific MicroRNA-Gene Interactions that May Differentiate between Active and Latent Tuberculosis Infection |
title_fullStr | Systematic Expression Profiling Analysis Identifies Specific MicroRNA-Gene Interactions that May Differentiate between Active and Latent Tuberculosis Infection |
title_full_unstemmed | Systematic Expression Profiling Analysis Identifies Specific MicroRNA-Gene Interactions that May Differentiate between Active and Latent Tuberculosis Infection |
title_short | Systematic Expression Profiling Analysis Identifies Specific MicroRNA-Gene Interactions that May Differentiate between Active and Latent Tuberculosis Infection |
title_sort | systematic expression profiling analysis identifies specific microrna-gene interactions that may differentiate between active and latent tuberculosis infection |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4167957/ https://www.ncbi.nlm.nih.gov/pubmed/25276827 http://dx.doi.org/10.1155/2014/895179 |
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