Type

Journal Article

Authors

David C Henshall
Eva M Jimenez-Mateos
Amaya Sanz-Rodriguez
Hany El-Naggar
Rana Raoof
Catherine Mooney

Subjects

Veterinary

Topics
gene expression real time pcr disease control plasma biomarker stability high throughput microrna biomarkers body fluids diurnal variation mirna profiling small rna

High Throughput qPCR Expression Profiling of Circulating MicroRNAs Reveals Minimal Sex- and Sample Timing-Related Variation in Plasma of Healthy Volunteers. (2015)

Abstract MicroRNAs are a class of small non-coding RNA that regulate gene expression at a post-transcriptional level. MicroRNAs have been identified in various body fluids under normal conditions and their stability as well as their dysregulation in disease opens up a new field for biomarker study. However, diurnal and day-to-day variation in plasma microRNA levels, and differential regulation between males and females, may affect biomarker stability. A QuantStudio 12K Flex Real-Time PCR System was used to profile plasma microRNA levels using OpenArray in male and female healthy volunteers, in the morning and afternoon, and at four time points over a one month period. Using this system we were able to run four OpenArray plates in a single run, the equivalent of 32 traditional 384-well qPCR plates or 12,000 data points. Up to 754 microRNAs can be identified in a single plasma sample in under two hours. 108 individual microRNAs were identified in at least 80% of all our samples which compares favourably with other reports of microRNA profiles in serum or plasma in healthy adults. Many of these microRNAs, including miR-16-5p, miR-17-5p, miR-19a-3p, miR-24-3p, miR-30c-5p, miR-191-5p, miR-223-3p and miR-451a are highly expressed and consistent with previous studies using other platforms. Overall, microRNA levels were very consistent between individuals, males and females, and time points and we did not detect significant differences in levels of microRNAs. These results suggest the suitability of this platform for microRNA profiling and biomarker discovery and suggest minimal confounding influence of sex or sample timing. However, the platform has not been subjected to rigorous validation which must be demonstrated in future biomarker studies where large differences may exist between disease and control samples.
Collections Ireland -> Royal College of Surgeons in Ireland -> PubMed
Ireland -> University College Dublin -> College of Science
Ireland -> University College Dublin -> Computer Science Research Collection
Ireland -> University College Dublin -> School of Computer Science

Full list of authors on original publication

David C Henshall, Eva M Jimenez-Mateos, Amaya Sanz-Rodriguez, Hany El-Naggar, Rana Raoof, Catherine Mooney

Experts in our system

1
David C Henshall
Royal College of Surgeons in Ireland
Total Publications: 127
 
2
Eva M Jimenez-Mateos
Royal College of Surgeons in Ireland
Total Publications: 55
 
3
Amaya Sanz-Rodriguez
Royal College of Surgeons in Ireland
Total Publications: 18
 
4
Rana Raoof
University College Dublin
Total Publications: 7
 
5
Catherine Mooney
University College Dublin
Total Publications: 63