Systematic Expression Profiling Analysis Identifies Specific MicroRNA-Gene Interactions that May Differentiate between Active and Latent Tuberculosis Infection. (3rd September 2014)
- Record Type:
- Journal Article
- Title:
- Systematic Expression Profiling Analysis Identifies Specific MicroRNA-Gene Interactions that May Differentiate between Active and Latent Tuberculosis Infection. (3rd September 2014)
- Main Title:
- Systematic Expression Profiling Analysis Identifies Specific MicroRNA-Gene Interactions that May Differentiate between Active and Latent Tuberculosis Infection
- Authors:
- Wu, Lawrence Shih-Hsin
Lee, Shih-Wei
Huang, Kai-Yao
Lee, Tzong-Yi
Hsu, Paul Wei-Che
Weng, Julia Tzu-Ya - Other Names:
- Chang Tzu-Hao Academic Editor.
- Abstract:
- Abstract : 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.
- Is Part Of:
- BioMed research international. Volume 2014(2014)
- Journal:
- BioMed research international
- Issue:
- Volume 2014(2014)
- Issue Display:
- Volume 2014, Issue 2014 (2014)
- Year:
- 2014
- Volume:
- 2014
- Issue:
- 2014
- Issue Sort Value:
- 2014-2014-2014-0000
- Page Start:
- Page End:
- Publication Date:
- 2014-09-03
- Subjects:
- Medicine -- Periodicals
Biology -- Periodicals
Biotechnology -- Periodicals
Life sciences -- Periodicals
610.5 - Journal URLs:
- https://www.hindawi.com/journals/bmri/ ↗
- DOI:
- 10.1155/2014/895179 ↗
- Languages:
- English
- ISSNs:
- 2314-6133
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 23396.xml