What is normal? Next generation sequencing-driven analysis of the human circulating miRNAOme
© Tonge and Gant. 2016
Received: 6 November 2015
Accepted: 1 February 2016
Published: 9 February 2016
MicroRNAs (miRNAs) are short non-protein-coding RNA species that have a regulatory function in modulating protein translation and degradation of specific mRNAs. MicroRNAs are estimated to target approximately 60 % of all human mRNAs and are associated with the regulation of all physiological processes. Similar to many messenger RNAs (mRNA), miRNAs exhibit marked tissue specificity, and appear to be dysregulated in response to specific pathological conditions. Perhaps, one of the most significant findings is that miRNAs are detectable in various biological fluids and are stable during routine clinical processing, paving the way for their use as novel biomarkers. Despite an increasing number of publications reporting individual miRNAs or miRNA signatures to be diagnostic of disease or indicative of response to therapy, there is still a paucity of baseline data necessary for their validation. To this end, we utilised state of the art sequencing technologies to determine the global expression of all circulating miRNAs within the plasma of 18 disease-free human subjects.
In excess of 500 miRNAs were detected in our study population with expression levels across several orders of magnitude. Ten highly expressed miRNAs accounted for 90 % of the total reads that mapped showing that despite the range of miRNAs present, the total miRNA load of the plasma was predominated by just these few species (50 % of which are blood cell associated). Ranges of expression were determined for all miRNA detected (>500) and a set of highly stable miRNAs identified. Finally, the effects of gender, smoking status and body mass index on miRNA expression were determined.
The data contained within will be of particular use to researchers performing miRNA-based biomarker screening in plasma and allow shortlisting of candidates a priori to expedite discovery or reduce costs as required.
KeywordsPlasma sequencing miRNA Small RNA NGS Biomarker Baseline
MicroRNAs (miRNAs) are short non-protein-coding RNA species that have a regulatory function in modulating protein translation from specific mRNAs . MicroRNAs are estimated to target approximately 60 % of all human mRNAs  and are associated with the regulation of all physiological processes. Similar to many messenger RNAs (mRNA), miRNAs exhibit marked tissue specificity [9, 12], and appear to be dysregulated in response to specific pathological conditions . Perhaps most significant is the finding that miRNAs are detectable in various biological fluids  and are stable during routine clinical processing , paving the way for their use as novel biomarkers. Whilst the presence of extra-cellular miRNAs in a range of biological fluids has been consistently described within the recent literature, the precise mechanisms via which they leave their “host cell” and enter the circulation are still under investigation. Nevertheless, it is now accepted that miRNAs are not simply shed from necrotic or apoptotic cells but rather, are subject to selective export from specific cells and function as extra-cellular signalling molecules, retaining their biological activity in recipient cells .
In considering the use of miRNAs as novel biomarkers, it is essential to generate baseline data that describes which miRNA species are present in a given biological fluid, where they likely originate from, and what is considered normal in terms of their patterns of expression. Indeed, we take such data for granted when we consider other routine clinical analyses such as the measurement of plasma/serum aspartate aminotransferase and alanine aminotransferase for the determination of liver function. Despite an increasing number of publications (5897 articles indexed by PubMed at the time of publication) reporting individual miRNAs or miRNA signatures as biomarkers of various conditions, there is still a paucity of baseline data necessary for their validation. To date, there are no comprehensive assessments of plasma miRNA expression conducted using unbiased methodology (i.e. where the miRNA targets are not required a priori) in a representative set of healthy human subjects reported. To this end, we utilised state of the art sequencing and bioinformatic techniques to determine the global expression of all circulating miRNAs within the plasma of 18 disease-free human subjects with high resolution. We report data to support the key questions outlined above including (1) a comprehensive list of all miRNAs found within human plasma, (2) the expected range of expression in a disease-free cohort and (3) the likely tissue of origin for a selection of the most highly expressed miRNAs. Furthermore, we report the effects of sex, smoking status and differing body mass index (BMI) on these parameters.
Results and discussion
Details of the donor population
Total RNA concentration derived from 5 mL of human plasma
Total mass RNA (µg)
Details of miRNAs detected in all plasma samples analysed (18 out of 18 individuals)
Our realisation that a number of the most highly expressed miRNAs were of blood cell origin led us to consider the potential implications that this may have for biomarker development (for a comprehensive review of the challenges associated with miRNA biomarker development, please refer to . The routine clinical sampling of blood involves venapuncture, delivery to a suitable storage vessel with or without anticoagulant and delivery to the analytical laboratory. The preparation of plasma or serum involves a further step during which blood cells are removed by centrifugation to leave a “cell free” supernatant. At each point, there is potential to influence the number of blood cell associated miRNAs present in the remaining sample either through haemolysis following venapuncture or during transportation, or via variation in the time and or intensity of centrifugation. In support of this, Pritchard and colleagues have previously demonstrated significant increases in erythrocyte-associated miRNAs (miRs-451, 16, 92a, 486) in haemolysis, and explained miR-150 and 223 expression as a function of lymphocyte and neutrophil count respectively . Thus, small variations in blood sample preparation may lead to individual samples being enriched or depleted in certain blood cell types and thus have significant impacts upon the expression of specific miRNAs. Of concern is the fact that all of the blood cell associated miRNAs identified herein have been identified in biomarker screens and or proposed as novel biomarkers for various conditions (miR-486-5p—gastric adenocarcinoma, miR-92a-3p—colorectal cancer, miR-181-5p—endometrial carcinoma, miR-151a-3p—paracetamol toxicity, let-7f-5p—Alzheimer’s disease) and may thus be subject to the aforementioned issues.
Comparison of the most stable miRNAs (90th percentile for stability) identified in this study with plasma and serum data from 
Wang et al. (top 10 % stable plasma miRNAs)
Wang et al. (top 10 % stable serum miRNAs)
Tonge et al. (top 10 % stable plasma miRNAs)
hsa - miR - 126 - 3p
hsa - miR - 126 - 5 p
hsa - miR - 191 - 5p
hsa - miR - 451a
The potential of miRNAs to serve as novel biomarkers is under intense investigation. To date, numerous studies have attempted to correlate miRNA expression with a range of endpoints. Despite the number of studies reporting such miRNA biomarkers, there is still a relative paucity of baseline data reporting the miRNA species expressed in a given biological fluid, what is considered normal in terms of their patterns of expression, and further, how this expression is altered by gender, obesity and smoking status. In this study we utilised state of the art sequencing technology to provide data to support the above key questions. In excess of 500 miRNAs were detected in our study population with expression across several orders of magnitude. However, only 53 of those miRNAs were detected in all participants with some miRNAs being detected in just a single individual. In considering relative expression between miRNAs, the top 10 most highly expressed candidates accounted for 90 % of the total reads that mapped to all miRNAs suggesting that despite the range of miRNAs present, the total miRNA load of the plasma was predominated by just 10 different species. Furthermore, many of the most abundant miRNAs have been shown to be highly expressed in cells of the blood and thus, perhaps with the exception of haematological biomarkers, their use as biomarkers should be approached with caution. Ranges of expression were determined for all miRNA detected (> 500) and a set of highly stable miRNAs identified. Finally, the effects of gender, smoking status and BMI on miRNA expression were determined. These data provide researchers with the ability to (1) determine the presence or absence of individual miRNAs within the plasma of a disease-free population, (2) consider the penetrance of each individual miRNA, (3) gain insight into the relative expression levels and “normal range” of individual miRNAs, ensuring that only suitabily highly expressed and stable candidates are taken forward, and (4) to have an indication of whether individual miRNAs are regulated by gender, smoking or obesity. Perhaps most striking and of most relevance here is the finding that of the large pool of miRNA detected in disease-free plasma, only a very small proportion of this may house suitable biomarker candidates (considering that, with the exception of the 10 most highly expressed miRNAs, only 10 % of the total miRNA pool is left and once miRNAs with low penetrance, those associated with cells of the blood, and those with high levels of inter-individual variation are discounted). Thus, the information contained within will assist researchers in designing more targeted miRNA biomarker studies.
Ethical approval and consent to participate
Sample collection was undertaken by Sera Lab ltd. who obtained ethical approval by an Institutional Review Board (Schulman Associates IRB #201209850). Written informed consent to participate was obtained from each study participant prior to sample collection.
Consent for publication
The supplying company (Sera Lab ltd) obtained written consent to produce reports or articles about the study from each participant, subject to their names being omitted from any such publications.
Samples, RNA isolation and sequencing
This study utilised human control material purchased from SeraLab ltd. All data were analysed anonymously; donor details are included in Table 1. Whole blood was drawn into EDTA containing tubes and stored on ice prior to centrifugation at 1000×g to obtain the plasma component. Plasma samples were frozen at −20 °C immediately after production. RNA was extracted from 5 mL of each plasma sample using the QiaAmp Circulating Nucleic Acid extraction kit in accordance with the manufacturer’s standard instructions. The quantity and quality of all RNA extracts was determined using the QuBit fluorimeter (Invitrogen) and Agilent BioAnalyzer (with Small RNA chip) respectively. Small RNA sequencing libraries were preparing using the TruSeq Small RNA kit according to the manufacturer’s standard directions. Sequencing was conducted on the Illumina HiSeq 2000 platform with the aim of obtaining >5,000,000 reads per sample.
All sequencing data underwent stringent quality control measures prior to analysis. Briefly, reads were quality clipped to only retain reads with a median quality of ≥Q30, sequencing adapters removed, and read length distributions assessed to ensure these met the expectations of a miRNA sequencing run. An extract and count routine was utilised to condense the millions of sequencing reads into sequence tab count format to increase computational efficiency. Reads shorter than 15 nucleotides and longer than 35 nucleotides were filtered given that these were unlikely to map to miRNAs. Following parsing to remove superfluous data columns, the resulting tally tables comprising the miRNA sequence and count were processed by miRanalyzer V0.2 . Reads were mapped to the human genome (hg18) and to miRBase version 20.0 permitting one mismatch between the sequencing reads and each index. Reads mapping to known miRNAs were counted and a relative expression value determined by dividing the number of reads mapping to each particular miRNA by the total number of reads mapped to all miRNAs. MicroRNAs evidenced by less than 10 sequencing reads or present in less than three study individuals were excluded prior to further analysis. Differential expression analysis and P value estimation were performed using QluCore Omics Explorer. The significance of differences between the various factors (BMI, smoking status and gender) was determined using a two-tailed t-test. In each case, contributions from other factors were eliminated using QluCore Omics explorer.
DPT and TWG conceived and designed the study; DPT performed the laboratory work and prepared the manuscript. Both authors read and approved the final manuscript.
Funding for this study was provided from the development fund of Public Health England and the University of Keele.
The authors declare that they have no competing interests.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Boon RA, Vickers KC. Intercellular transport of microRNAs. Arterioscler Thromb Vasc Biol. 2013;33(2):186–92.PubMed CentralView ArticlePubMedGoogle Scholar
- Boyerinas B, Park S, Hau A, Murmann AE, Peter ME. The role of let-7 in cell differentiation and cancer. Endocr Relat Cancer. 2010;17(1):F19–36.View ArticlePubMedGoogle Scholar
- Cortez MA, Bueso-Ramos C, Ferdin J, Lopez-Berestein G, Sood AK, Calin GA. MicroRNAs in body fluids—the mix of hormones and biomarkers. Nat Rev Clin Oncol. 2011;8(8):467–77.PubMed CentralView ArticlePubMedGoogle Scholar
- Dong Y, Zhao J, Wu C, Zhang L, Liu X, Kang W, Leung W, Zhang N, Chan FK, Sung JJ. Tumor suppressor functions of miR-133a in colorectal cancer. Mol Cancer Res. 2013;11(9):1051–60.View ArticlePubMedGoogle Scholar
- Graff JW, Powers LS, Dickson AM, Kim J, Reisetter AC, Hassan IH, Kremens K, Gross TJ, Wilson ME, Monick MM. Cigarette smoking decreases global microRNA expression in human alveolar macrophages. PloS one. 2012;7(8):e44066.PubMed CentralView ArticlePubMedGoogle Scholar
- Hackenberg M, Rodriguez-Ezpeleta N, Aransay AM. miRanalyzer: an update on the detection and analysis of microRNAs in high-throughput sequencing experiments. Nucleic Acids Res. 2011;39(Web Server issue):W132–8.PubMed CentralView ArticlePubMedGoogle Scholar
- Hogg DR, Harries LW. Human genetic variation and its effect on miRNA biogenesis, activity and function. Biochem Soc Trans. 2014;42(part 4):1184–9.View ArticlePubMedGoogle Scholar
- Izzotti A, Calin GA, Arrigo P, Steele VE, Croce CM, de Flora S. Downregulation of microRNA expression in the lungs of rats exposed to cigarette smoke. FASEB J. 2009;23(3):806–12.PubMed CentralView ArticlePubMedGoogle Scholar
- Laterza OF, Lim L, Garrett-Engele PW, Vlasakova K, Muniappa N, Tanaka WK, Johnson JM, Sina JF, Fare TL, Sistare FD, Glaab WE. Plasma microRNAs as sensitive and specific biomarkers of tissue injury. Clin Chem. 2009;55(11):1977–83.View ArticlePubMedGoogle Scholar
- Lee K, Lin F, Hsu T, Lin J, Guo J, Tsai C, Lee Y, Lee Y, Chen C, Hsiao M. MicroRNA-296-5p (miR-296-5p) functions as a tumor suppressor in prostate cancer by directly targeting Pin1. Biochim Biophys Acta (BBA)-Mol Cell Res. 2014;1843(9):2055–66.View ArticleGoogle Scholar
- Leidinger P, Backes C, Meder B, Meese E and Keller A. The human miRNA repertoire of different blood compounds. BMC Genom. 2014;15:474-2164-15-474.Google Scholar
- Mestdagh P, Lefever S, Pattyn F, Ridzon D, Fredlund E, Fieuw A, Ongenaert M, Vermeulen J, de Paepe A, Wong L, Speleman F, Chen C, Vandesompele J. The microRNA body map: dissecting microRNA function through integrative genomics. Nucleic Acids Res. 2011;39(20):e136.PubMed CentralView ArticlePubMedGoogle Scholar
- Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL, Peterson A, Noteboom J, O’Briant KC, Allen A, Lin DW, Urban N, Drescher CW, Knudsen BS, Stirewalt DL, Gentleman R, Vessella RL, Nelson PS, Martin DB, Tewari M. Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci USA. 2008;105(30):10513–8.PubMed CentralView ArticlePubMedGoogle Scholar
- Powers L, Dickson A, Gerke A, Hansdottir S, Wilson M, Gross T, Monick M, Sears R. Smoking disrupts the Erk/dicer/trbp/microrna pathway resulting in global down-regulation of microrna expression. Am J Respir Crit Care Med. 2011;183:A1048.Google Scholar
- Pritchard CC, Kroh E, Wood B, Arroyo JD, Dougherty KJ, Miyaji MM, Tait JF, Tewari M. Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies. Cancer Prev Res Philadelphia PA. 2012;5(3):492–7.View ArticleGoogle Scholar
- Tiberio P, Callari M, Angeloni V, Daidone MG and Appierto V. Challenges in using circulating miRNAs as cancer biomarkers. BioMed Res Int. 2015;2015:731479.PubMed CentralView ArticlePubMedGoogle Scholar
- Uesugi A, Kozaki K, Tsuruta T, Furuta M, Morita K, Imoto I, Omura K and Inazawa J. The tumor suppressive microRNA miR-218 targets the mTOR component Rictor and inhibits AKT phosphorylation in oral cancer. Cancer Res. 2011;canres.0368.2011.Google Scholar
- Wang K, Yuan Y, Cho J, McClarty S, Baxter D, Galas DJ. Comparing the MicroRNA spectrum between serum and plasma. PLoS ONE. 2012;7(7):e41561.PubMed CentralView ArticlePubMedGoogle Scholar
- Weber JA, Baxter DH, Zhang S, Huang DY, Huang KH, Lee MJ, Galas DJ, Wang K. The microRNA spectrum in 12 body fluids. Clin Chem. 2010;56(11):1733–41.View ArticlePubMedGoogle Scholar
- Wu Y, Crawford M, Mao Y, Lee RJ, Davis IC, Elton TS, Lee LJ, Nana-Sinkam SP. Therapeutic delivery of microRNA-29b by cationic lipoplexes for lung cancer. Mol Ther Nucleic Acids. 2013;2(4):84.View ArticleGoogle Scholar
- Yungang W, Xiaoyu L, Pang T, Wenming L, Pan X. miR-370 targeted FoxM1 functions as a tumor suppressor in laryngeal squamous cell carcinoma (LSCC). Biomed Pharmacother. 2014;68(2):149–54.View ArticlePubMedGoogle Scholar
- Zheng B, Liang L, Wang C, Huang S, Cao X, Zha R, Liu L, Jia D, Tian Q, Wu J. MicroRNA-148a suppresses tumor cell invasion and metastasis by downregulating ROCK1 in gastric cancer. Clin Cancer Res. 2011;17(24):7574–83.View ArticlePubMedGoogle Scholar