title: Systematic expression profiling analysis identifies specific microRNA-gene interactions that may differentiate between active and latent tuberculosis infection.
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.
authors.affiliation: Institute of Medical Sciences, Tzu Chi University, Hualien 97004, Taiwan.
authors.forename: Lawrence Shih-Hsin
authors.initials: LS
authors.lastname: Wu
authors.affiliation: Taoyuan General Hospital, Ministry of Health and Welfare, Taoyuan 33004, Taiwan ; Department of Life Sciences, National Central University, Taoyuan 32001, Taiwan.
authors.forename: Shih-Wei
authors.identifier: 0000-0002-8367-8647
authors.initials: SW
authors.lastname: Lee
authors.affiliation: Department of Computer Science and Engineering, Yuan Ze University, Taoyuan 32003, Taiwan.
authors.forename: Kai-Yao
authors.initials: KY
authors.lastname: Huang
authors.affiliation: Department of Computer Science and Engineering, Yuan Ze University, Taoyuan 32003, Taiwan ; Innovation Center for Big Data and Digital Convergence, Yuan Ze University, Taoyuan 32003, Taiwan.
authors.forename: Tzong-Yi
authors.initials: TY
authors.lastname: Lee
authors.affiliation: Bioinformatics Core Laboratory, Institute of Molecular Biology, Academia Sinica, Taipei 11529, Taiwan.
authors.forename: Paul Wei-Che
authors.initials: PW
authors.lastname: Hsu
authors.affiliation: Department of Computer Science and Engineering, Yuan Ze University, Taoyuan 32003, Taiwan ; Innovation Center for Big Data and Digital Convergence, Yuan Ze University, Taoyuan 32003, Taiwan.
authors.forename: Julia Tzu-Ya
authors.identifier: 0000-0003-0127-0945
authors.initials: JT
authors.lastname: Weng
mesh_terms: D016022:Case-Control Studies; D003937:Diagnosis, Differential; D015536:Down-Regulation / Q000235:genetics; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D006801:Humans; D055985:Latent Tuberculosis / Q000097:blood / Q000175:diagnosis* / Q000235:genetics*; D035683:MicroRNAs / Q000097:blood / Q000235:genetics*; D015203:Reproducibility of Results; D015854:Up-Regulation / Q000235:genetics
chemical_list: D035683:MicroRNAs