本論文已被瀏覽 127 次， [ ] 31 次，[ ] [ ]
Background: Expression patterns of microRNAs in body fluids show potential to be used as noninvasive rapid and accurate biomarkers for various diseases.The study aimed to (i) identify patterns of microRNA signatures for diagnosis of tuberculosis (TB) and (ii) assess significance of a patient’s genetic background on signature composition and diagnostic performance.
Patients and Methods: The study enrolled consented participants from Europe and Africa. Circulating miRNAs were measured and compared between patients belonging to the following categories; (i) active pulmonary tuberculosis (PTB), (ii) healthy individuals (H), (iii) active pulmonary TB co-infected with HIV (PTB/HIV), (iv) latent TB infection (LTBI) and (v) other pulmonary infection (OPI). As a first step, pooled sera of 10 participants from each category and region of enrolment were measured by TaqMan low-density arrays. Secondly, the identified significant miRNA signatures were applied to 56 individual sera aiming to discriminate between H and PTB patients. Next, the identified miRNA signatures were analysed for their diagnostic performances using multivariate logistic analysis, and Relevance Vector Machine (RVM). The diagnostic performance of both models was evaluated by a leave-one-out-cross-validation (LOOCV).
Results: Significant miRNA signatures that discriminated patient categories were selected from the pooled samples. After validation of these in 56 individual participants (36 from the European cohort and 20 from the African population); a signature of 15 miRNAs was observed to be significantly differently expressed between categories, and able to differentiate healthy individuals and from individuals with PTB with a diagnostic accuracy of 82% (CI 70.2-90.0) in the RVM and 77% (CI 64.2-85.9) in the logistic classification model. The analysis based on genetic background identified a signature of 10 miRNAs that was specific for the European cohort with a diagnostic accuracy of 83% (CI 68.1-92.1) in RVM, and 81% (65.0-90.3) in the logistic model. Whereas a signature of 12 miRNAs was specific to the African cohort and the diagnostic accuracy increased up to 95% (CI 76.4-99.1) and 100% (83.9-100.0) in RVM and logistic model, respectively.
Conclusion: This proof-of-concept study showed that miRNA levels were significantly higher in patient with TB than in those without TB. miRNAs are a promising diagnostic candidate for TB, therefore further prospective evaluation of this diagnostic seems warranted.