Identification of miR‐93 as a suitable miR for normalizing miRNA in plasma of tuberculosis patients

Abstract

Tuberculosis (TB) remains a major public health issue. New tests to aid diagnoses and monitor the response to therapy are urgently required. There is growing interest in the use of microRNA (miRNA) profiles as diagnostic, prognostic or predictive markers in a range of clinical and infectious diseases, including Mycobacterium tuberculosis infection, however, challenges exist to accurately normalise miRNA levels in cohorts. This study examined the appropriateness of 12 miRs and RNU6B to normalise circulating plasma miRNA levels in individuals with active TB from 2 different geographical and ethnic regions. Twelve miRs (let-7, miR-16, miR-22, miR-26, miR-93, miR-103, miR-191, miR-192, miR-221, miR-423, miR-425 and miR-451) and RNU6B were selected based on their reported production by lung cells, expression in blood and previous use as a reference miRNA. Expression levels were analysed in the plasma of newly diagnosed TB patients from Australia and China compared with individuals with latent TB infection and healthy volunteers. Analysis with both geNorm and NormFinder software identified miR-93 as the most suitable reference miR in both cohorts, either when analysed separately or collectively. Interestingly, there were large variations in the expression levels of some miRs, in particular miR-192 and let-7, between the two cohorts, independent of disease status. These data identify miR-93 is a suitable reference miR for normalizing miRNA levels in TB patients, and highlight how environmental, and possibly ethnic, factors influence miRNA expression levels, demonstrating the necessity of assessing the suitability of reference miRs within the study population.

Translating RNA sequencing into clinical diagnostics: opportunities and challenges

“…Host microRNA-gene interactions during the infection response are also proving to be a fruitful source of potential diagnostic biomarkers for specific infections, as well as distinguishing between active and latent infections; for example, the use of such markers to discriminate between latent infection and active disease with M. tuberculosis 88 . As with the other diagnostic uses of small RNA biomarkers described in this Review, a number of hurdles exist for the development and validation of infection assays, including sensitivity, specificity and, perhaps more difficult to overcome, the normalization of small RNA in clinical samples, which will vary between conditions, tissues and individual hosts and is an active area of study 89 . However, the application of RNA-seq provides a useful orthogonal approach to genomics-based diagnostics for clinical microbiology.…”

MicroRNA in innate immunity and autophagy during mycobacterial infection

“…Additionally, there are still many challenges in the accurate normalization of miRNA levels among different cohorts. Recent trials that normalized miRNA levels between cohorts from Australia and China identified only miR‐93 as the most suitable reference miRNA in both cohorts, with large variations in several miRNAs between the cohorts (Barry et al, ). Currently, several miRNAs, including miR‐223, miR‐144*, and miR‐29, may be associated with host responses against TB, but the value of these miRNAs as biomarkers for diagnostics has not been demonstrated.…”

“…Additionally, there are still many challenges in the accurate normalization of miRNA levels among different cohorts. Recent trials that normalized miRNA levels between cohorts from Australia and China identified only miR-93 as the most suitable reference miRNA in both cohorts, with large variations in several miRNAs between the cohorts (Barry et al, 2015).…”

Identification of suitable reference gene and biomarkers of serum miRNAs for osteoporosis

“…Most of the results obtained by qPCR used different reference genes for normalization, such as miR-16, miR-93-5p in skeletal disease10121314. Although miR-93 had been defined as a plasma miRNA reference gene for tuberculosis17, it was also connected with osteoblast differentiation and bone mineralization18. External reference couldn’t correct for the other causes of variability such as the total concentration of miRNA fraction.…”