| Literature DB >> 30886653 |
Shamila D Alipoor1,2, Payam Tabarsi3, Mohammad Varahram4, Mehrnaz Movassaghi3, Mehdi Kazempour Dizaji3, Gert Folkerts5, Johan Garssen5,6, Ian M Adcock7,8, Esmaeil Mortaz3,5.
Abstract
INTRODUCTION: Tuberculosis (TB) remains a major threat to human health. Due to the limited accuracy of the current TB diagnostic tests, it is critical to determine novel biomarkers for this disease. Circulating exosomes have been used as diagnostic biomarkers in various diseases. OBJECTIVE OF THE STUDY: In this pilot study, we examined the expression of miRNAs as biomarker candidates for the diagnosis of TB infection.Entities:
Mesh:
Substances:
Year: 2019 PMID: 30886653 PMCID: PMC6388314 DOI: 10.1155/2019/1907426
Source DB: PubMed Journal: Dis Markers ISSN: 0278-0240 Impact factor: 3.434
Clinical characteristics of the patients with active TB (n = 25).
| Characteristic | Value |
|---|---|
|
| 41 (15–65) |
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| 12, 13 |
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| |
| Diabetes mellitus | 0 |
| Others (malignancy, HIV, or other infectious diseases) | 0 |
|
| |
| Cough/sputum | 20 |
| Fever | 5 |
| Hemoptysis | 0 |
|
| |
| Culture, AFB, and PCR | 25 |
AFB: acid-fast bacillus; DM: diabetes mellitus; PCR: polymerase chain reaction.
Figure 1Characterization of the serum exosomes. (a) Transmission electron microscopy showing that serum exosomes are spherical particles with an average size of 70 nm. The bar represents 100 nm. (b) Detection of exosomal CD81 surface markers using flow cytometry. MFI (mean fluorescence intensity) represents the expression of CD81 on the surface of exosomes. The results are representative of three independent experiments. (c) Exosomal RNA analysis by Agilent Bioanalyzer indicated a population of 18–28 nt without prominent ribosomal RNA peaks. Results are representative of three independent experiments.
Figure 2The relative expression of exosomal miR-484, miR-425, and miR-96-3-p in TB patients compared to that in control subjects. Real-time PCR of exosomal miR-484, miR-425, and miR-96 indicated upregulation in TB patients compared to control subjects (∗p < 0.05 and ∗∗p < 0.01 significantly different compared to control). Data represent mean ± SEM of data from 25 patients in each group. Each sample was analyzed twice in triplicate to give a single value for each subject. The relative value in control subjects is defined by the dotted blue line.
Figure 3Correlation between the exosomal level of miRNAs and the grade of smear positivity. Real-time PCR showed increased exosomal miRNA expression with increasing infection rates in comparison with healthy controls. Data represent mean ± SEM from 25 patients of 2 independent analyses each repeated in triplicate for each subject. ∗p < 0.05 and ∗∗p < 0.01 significantly different compared to control. The relative value in control subjects is defined by the dotted blue line.
Figure 4Diagnostic power of exosomal miR-484 (a), miR-425 (b), and miR-96 (c) determined by ROC curve analysis. The results show the area under the ROC curve (AUC) for the sensitivity and specificity of each miRNA. The improved AUC (95% CI) for the combination of all miRNAs is shown in (d).
Predictive values from AUC data from ROC curves for serum exosomal miR-484, miR-425, and miR-96 individually and in combination in TB.
| miRNA | AUC |
|---|---|
| miR-484 | 0.72 |
| miR-425 | 0.66 |
| miR-96 | 0.62 |
| miR-484, miR-425 | 0.71 |
| miR-425, miR-96 | 0.64 |
| miR-484, miR-96 | 0.68 |
| miR-484, miR-425, and miR-96 | 0.78 |
Target genes and pathways of miR-484, miR-425, and miR-96.
| Cluster | Node ID in cluster | Pathways | |
|---|---|---|---|
| Pathway name and function | Mechanism | ||
| 1 | VEGFD, VEGFB, VEGFA, PDGFB, PDGFA, CUL7, CUL5, CUL4B, CUL4A, CUL3, CUL2, CUL1, CACUL1 | Endocytosis | Mycobacterium can exploit the formation of new blood vessels to facilitate its dissemination via VEGF-related signaling pathways [ |
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| 2 | TGFBR1, TCF7, TCF4, PRKG1, MAN1A2, GNAI1, EDEM1, CTNNB1 | TGF- | Regulation of the immune system |
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| 3 | SOS1, PANK3, IQGAP1, PRKCA, INPP4B, PIKFYVE, MAN2A1 | N-Glycan biosynthesis | Metabolism and catabolism |
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| 4 | UBE2W, SMURF2, RYR2, PTEN, PLCZ1, MAN1A1, GRM1, GNAQ | Ubiquitination & proteasome degradation | Adaptive immune system |
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| 5 | VEGFC, ST6GAL1, PRKCB, PLN, PIK3CD, PDGFD, ORAI3, OCRL, MAN2C1, MAN2B1, MAN2A2, LEF1, HERC3, EDEM2 | Calcium signaling pathway | Metabolism and catabolism |
VEGF: vascular endothelial growth factor; CUL: cullin; TGFBR1: transforming growth factor beta receptor I; TCF7: transcription factor 7; TCF4: transcription factor 4; PRKG1: protein kinase cGMP-dependent 1; MAN1A2: mannosidase alpha class 1A member 2; GNAI1: guanine nucleotide-binding protein G(i); EDEM1: ER degradation enhancing alpha-mannosidase-like protein 1; CTNNB1: catenin beta1.