Abstract

Introduction

MicroRNAs (miRNAs) are small non-coding RNA sequences of about 22 nucleotides that are important post-transcriptional regulators of gene expression. They impact many if not most developmental [1] and homeostatic processes such as the immune response and metabolism [2, 3] and epigenetic processes as well [1, 4].

A plethora of studies in humans, complemented by animal models, demonstrate the importance of tissue miRNAs during developmental processes [5–11] and various disease pathologies [12–17]. Thus, significant changes of tissue miRNA ‘signatures' occur in various diseases, such as cancers [18, 19], cardiovascular disease (CVD)[21–26], diseases of the lung [27–31], kidney [16] and nervous system [32, 33]. However, routine biopsies from any organ for miRNA profiling are not a practical option; therefore, investigators are turning towards less invasive procedures, involving circulating miRNA biomarkers (for a review of practical issues, see [34]).

The presence of miRNA molecules in human plasma was concomitantly reported by several groups [35–38]. Once it became clear that some miRNAs were released from their cells of origin and could be captured in various extracellular fluids, numerous studies began investigating whether tissue-and disease-specific miRNA signatures were also reflected in fluids such as blood, urine, spinal fluid or saliva [39]. Extracellular miRNAs are remarkably stable in the circulation [35–37, 40]. As a result of cellular damage/tissue injury, such as in acute myocardial infarction (MI) [41, 42], atherosclerosis [44], non-small cell lung cancer [45], neurodegenerative diseases [46–49], skin fibrosis [50] and osteoarthritis [51] (Table 1), miRNA expression can change in the blood. Notably, this list is increasingly expanding. Furthermore, miRNA expression can change not only in the blood but in other body fluids as well (Table 1). Thus, circulating miRNAs are attractive candidates for disease monitoring to serve as valuable prognostic indicators of disease progression or resolution. It is predicted that changes in miRNA expression in body fluids occur earlier than conventional biomarkers. For instance, the markers of inflammation and repair in the cardiovascular and lung systems include troponin, C-reactive protein, chemokines and cytokines [52, 53]. However, by the time these proteins are detectable in the circulation, much of the tissue damage has already occurred, which makes it crucial that better biomarkers be uncovered for the early detection of diseases.

Table 1

Examples of circulating miRNAs detected in various human pathologies

MiRNAs differentially expressed	Condition	Sample type	Anticoagulant	Volume (ml)	Isolation method*	Spike-in/endogenous controls	Detection method	No. of miRNAs tested	Refs.
miRs-21,-155,-210	Diffuse large B-cell lymphoma	Serum	N/A	2	Trizol	miR-16	qRT-PCR†	3	[71]‡
N/A	Healthy donors	Plasma	Unknown	40	Trizol	None	qRT-PCR pre-amp	420	[36]§
let-7a, miRs-16,-92a,-122,-142-3p,-150	Healthy donors	Plasma (p), EV, Serum (s)	EDTA	30 (p) 10 (s)	miRNeasy; 5 vol Qiazol	cel-miRs	Microarray¶ qRT-PCR	375	[68]**
miRs-15b,-16	Prostate cancer	Plasma Serum	EDTA	10	mirVana PARIS	cel-miRs	qRT-PCR pre-amp	368	[37]††
miRs-16,-21,-24,-34b	Healthy donors	Plasma	EDTA	0.4	Tri-Reagent LS miRNeasy	cel-miR-39	qRT-PCR pre-amp	667	[72]‡‡
miRs-15b,-16,-24,-122	Healthy donors	Plasma Serum	EDTA	0.4	mirVana PARIS	cel-miRs	qRT-PCR	3	[73]§§
let-7b, miR-223	NSCLC	Plasma Serum	Heparin	0.1	Total RNA purification kit	cel-miRs	qRT-PCR	30	[74]§§
N/A	N/A	Plasma Serum	U	0.4	miRNeasy; 10 vol Qiazol	cel-miRs	qRT-PCR	N/A	[75]¶¶
miR-499	ACS; CHF	Plasma	EDTA	0.5	mirVana PARIS	Novel Synthetic miR	qRT-PCR	1	[41]
miRs-1,-133a,-133b,-208a,-208b,-499	ACS	Plasma	U	0.05	Master Pure RNA Purification Kit	cel-miR-54	qRT-PCR	6	[43]
miRs-1,-133	AMI	Plasma	Citrate	1	miRNeasy	U6 snRNA	qRT-PCR	2	[42]
miR-1	AMI‡‡	Serum	N/A	0.2	miRNAs Isolation Kit	None (absolute quantification)	qRT-PCR	1	[76]
miRs-1,-16, 133a,-208a,-499	AMI‡‡	Plasma	EDTA	0.1	TRI Reagent BD TR126	cel-miR-39	Microarray qRT-PCR	5	[77]
miRs-1,-122, 133a,-133b,-375,-499-5p	AMI‡‡	Plasma Serum	EDTA; thrombin	2.4	mirVana PARIS	miR-17-5p; median normalization	qRT-PCR	667	[52]
miRs-208b,-499	AMI, VM, DD; AHF	Plasma	Citrate; EDTA	0.1	mirVana PARIS	cel-miRs	qRT-PCR	6–12	[78]
miRs-1,-133a	AMI‡‡	Serum	N/A	0.35	Trizol LS	N/A	qRT-PCR	3	[79]
miRs-133,-328	AMI	Plasma	EDTA	0.5-1	Trizol LS	U6 snRNA	qRT-PCR	3	[80]
miRs-17,-92a,-126,-145,-155,-199a	CAD	Plasma Serum	EDTA	0.25	TRI Reagent BD miRNAeasy	cel-miR-39	Microarray qRT-PCR	>1000	[81]
miRs-126,-133a,-499	CAD	Plasma	EDTA	U	TRI Reagent BD	cel-miR-39	qRT-PCR	7	[82]
miR-423-5p	HF	Plasma	Citrate	0.5–4.4	mirVana PARIS	miR-1249	Sequencing***; qRT-PCR	>1000	[83]
miRs-122,-126,-499	CHF	Plasma	EDTA	0.5	mirVana PARIS	Novel Synthetic miR	qRT-PCR pre-amp	3	[84]
hcmv-miR-UL112, let-7e, miR-296–5p	HT	Plasma	EDTA	0.25	TRI Reagent BD	Median normalization; U6 snRNA	Microarray qRT-PCR	>1000	[67]
miRs-27b,-130a,-210	ASO	Serum	N/A	U	QIAamp Circulating Nucleic Acid Kit	U6 snRNA	qRT-PCR	13	[85]
miR-21	AS	Plasma	EDTA	U	TRIzol	cel-miR-39	qRT-PCR	1	[86]
miRs-105,-106a,-223	FH†††	Plasma (HDL, EV)	U	U	miRNeasy	RNU6; Array Specific	Microarray qRT-PCR pre-amp	>1000	[69]‡‡‡
miRs-20a,-21,-133a, 146a,-221,-222,-210,-328	Exercise –ind. Cardiovasc. Adaptation	Plasma	EDTA	0.1	MicroRNA Extraction Kit	miR-422b	qRT-PCR	8	[87]
miRs-122,-370	HL	Plasma	EDTA	0.4	mirVana PARIS	cel-miR-39	qRT-PCR	4	[88]
miRs-1,-21,-29a,-133a,-208	MI	Plasma	U	0.4	mirVana PARIS	U6 snRNA	qRT-PCR	5	[89]
miRs-208b,-499,	MI	Plasma	Citrate	U	mirVana PARIS	cel-miRs	qRT-PCR	2	[90]
miR-133a	MI	Serum	N/A	0.1	miRNeasy	cel-miR-39	qRT-PCR	1	[91]
miRs-126,-197,-223	MI	Plasma	U	U	miRNeasy	U6 snRNA	qRT-PCR	19	[92]
miRs-15b,-27b	NSCLC	Serum	N/A	0.5	mirVana PARIS§§§	ΔCt matrix	qRT-PCR	181	[93]
miRs-1,-30d,-486,-499	NSCLC	Serum	N/A	50	TRIzol¶¶¶	Normalization to total RNA	qRT-PCR; sequencing	11 by qRT-PCR	[94]
let7f, miRs-20b,-30e-3p	NSCLC	Plama EV	U	3	Dynabeads + mirVana PARIS††	miR-142-3p and miR-30b	qRT-PCR	365	[95]
let7b, miRs-20b,-33a, 199b, 200a,-518b,-635,-662,-935	COPD, lung cancer	Whole blood	PAXgene	5	miRNeasy	Quantile normalization	Microarray; qRT-PCR	863	[96]
miRs-1, 7,-21,-30a,-126,-200b,-210,-219,-324,-451,-486	Lung cancer	Plasma	EDTA	0.2	mirVana PARIS	RNU-6B	Microarray; qRT-PCR	>200	[61]
miR-150	PAH	Plasma	Citrate	U	miRNeasy	cel-miR-39	Microarray; qRT-PCR	1223	[59]
miRs-21,-210, 486-5p	SPN	Plasma	EDTA	U	mirVana PARIS	miR-16	qRT-PCR	5	[97]
miR-483-5p	HCC	Plasma	U	0.25	miRNeasy	U6 snRNA; cel-miR-39	qRT-PCR TLDA cards A & B	5	[98]
let-7d-5p, let-7 g-5p, miRs-15b-5p,-142-3p,-191-5p,-301a-3p,-545	Alzheimer	Plasma	U	1	mirVana PARIS modified	Ath-159a; NegA	nCounter****	˜800	[99]
miR-210	AKI	Plasma	U	U	MasterPure RNA Purification Kit	cel-miR-54	Microarray	>1000; 3 by qRT-PCR	[100]

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^*Reagents and supplier information: Master Pure RNA Purification Kit (Epicentre Biotechnologies, Madison, WI, USA); MicroRNA Extraction Kit (BenevBio, Mission Viejo, CA, USA); miRNA Isolation Kit (RNA Bioscience, Salt Lake City, UT, USA); miRNeasy, Qiazol, QIAamp Circulating Nucleic Acid Kit (Qiagen, Valencia, CA, USA); mirVana PARIS, Trizol and Trizol LS [Ambion/Invitrogen/Applied Biosytems Inc. (ABI), Life Technologies, Carlsbad, CA, USA]; TRI Reagent BD and Tri-Reagent LS (Sigma-Aldrich, St. Louis MO, USA); Total RNA Purification Kit (Norgen Biotek Corp, Thorold, Canada).

^†Quantitative real-time-PCR (qRT-PCR) technologies include TaqMan, TLDA Cards and SYBR Green methodologies using a wide range of products from ABI, Qiagen, Exiqon (Woburn, MA, USA), Roche (Indianapolis, IN, USA) and Promega (Madison, WI, USA).

^‡First study to show miRNA presence in plasma.

^§First study to analyse miRNA in plasma microvesicles in healthy individuals.

^¶Various array technologies are from Affymetrix (Santa Clara, CA, USA), Agilent (Santa Clara, CA, USA), Exiqon miRCURY LNA Array (Woburn, MA, USA), Genom Biochip MPEA (Febit biomed GmbH, Heidelberg, Germany), Fluidigm (San Francisco, CA, USA).

^**Reports that some circulating miRNA species may be associated with Argonaute2.

^††Describes the use of Caenorhabditis elegans miRNAs spike-ins as exogenous controls for the efficiency of extraction procedure.

^‡‡Useful methods paper.

^§§Useful methods paper; compares plasma and serum.

^¶¶Comprehensive methods review paper.

^***Sequencing-based profiling from Illumnia (San Diego, CA, USA).

^†††In addition to humans, study included rodent models.

^‡‡‡Report that circulating miRNAs are associated with HDL.

^§§§Reported yield 300–500 ng/ml of serum.

^¶¶¶Reported yield 5–10 μg/50 ml of serum.

^****nCounter miRNA expression assay v1 (Nanostring Technology, Seattle, WA, USA).

ACS: acute coronary syndrome; AHF: acute heart failure; AKI: acute kidney injury; AMI: acute myocardial infarction; AS: atherosclerosis; ASO: atherosclerosis obliterans; CAD: coronary artery disease; cc: cell culture; cel-miRs: C. elegans synthetic miR-39, miR-54 and/or miR-238; CHF: congestive heart failure; COPD: congestive obstructive pulmonary disease; DD: diastolic dysfunction; EDTA: ethylenediaminetetraacetic acid; EV: extracellular vesicles (including exosomes); FH: familial hypercholesterolaemia; H: human; HCC: hepatocellular carcinoma; HF: heart failure; HL: hyperlipidaemia; HT: hypertension; pre-amp.: pre-amplification; MI: myocardial infarction; NSCLC: non-small cell lung carcinoma; PAH: pulmonary artery hypertension; SPN: solitary pulmonary nodules; U: unknown (not mentioned in paper); VM: viral myocarditis.

However, miRNA fingerprinting as a novel and valid diagnostic, prognostic and disease surveillance tool is still in the descriptive stages. Currently, information is being gathered and compared in various disease states. The necessity of more thorough studies, based on much larger patient cohorts, is required for their utility. This is underscored by several studies using conventional biomarkers to assess tissue damage from organs that would also require invasive biopsies. For instance, comparison of circulating miRNA profile with at least one protein marker of acute coronary syndromes, namely troponin, led to conflicting results [55, 56]. At the same time, there are only few studies that analyse miRNA expression outside lung tissue in chronic obstructive pulmonary disease [57, 58], pulmonary artery hypertension [59], idiopathic pulmonary fibrosis [60] or lung cancer [61]. Several studies have begun to examine the potential of miRNAs to predict liver damage as well [62, 63].

Another level of complexity is added by the fact that, although many circulating extracellular miRNA species are repeatedly found having differential expression, such as miRs-1,-122,-126 and-223 in MI (Table 1; for comprehensive recent reviews, see Refs. [43, 64]), some of these are also associated with leukaemias and cancers [12, 66], further complicating identification of a disease-specific profile. In addition, extracellular miRNAs derived from viruses such as human cytomegalovirus can be found in patients with CVD. For example, hcmv-miR-UL112 is elevated in the circulation in hypertension [67] (Table 1). Although the role of viral miRNAs in infection is just beginning to be elucidated, little is known about their involvement in the pathogenesis of other human diseases.

Sources of variability in miRNA assessment from body fluids involve both the extraction methodology and the analysis platform employed, which may lead to inconsistent or even contradictory results. A comprehensive literature survey revealed that many methodological details are often overlooked, thus making it difficult to directly compare the specific efficiency and accuracy of various methods. The matter is further complicated by the fact that in the blood, miRNAs are either associated with proteins, such as argonaute [68], lipoproteins [69], or contained within cellular fragments designated as exosomes, microparticles, microvesicles or extracellular vesicles (EVs) [36, 37]. Extraction and analysis of miRNA from any or all of these components may pose specific challenges and yield different results.

Initial studies [36, 37] utilized a large volume of blood to isolate and profile >450 miRNAs. In contrast, advances in the approaches now allow the interrogation of <1 ml of blood to examine the expression of extracellular miRNAs (Table 1). However, in-depth analyses of the miRNA profiles often require more starting biological fluid, which may be a limiting factor. This is especially true when the patients are children, elderly or seriously ill. In addition, the RNA quantity can dictate the platform used for miRNA analysis. As shown in Table 1, current methods vary among laboratories both for miRNA isolation from plasma or serum and for obtaining miRNA profiles from these isolates.

In this review, we will highlight important considerations, such as blood collection methods or the choice of a profiling platform, when embarking on studies to profile circulating miRNAs. Throughout the review, we will refer to circulating extracellular miRNAs, as those found in the serum or plasma and not blood cells, unless otherwise stated. We focus on studies using limited sample volumes, as would be practical for disease profiling in clinical settings, and highlight optimal miRNA isolation protocols for small sample sizes. In this review, we also discuss analytic methods to identify circulating miRNAs, as well as other critical factors when designing these studies.

Current methodologies for extracting miRNAs from plasma and serum

The purposes of detecting extracellular miRNAs are to use them as disease biomarkers, as well as to understand disease pathogenesis. Therefore, much of the effort so far involves profiling miRNA species in various body fluids to uncover differential expression patterns and to correlate them with physiological status or disease progression. The composition of these fluids is quite dissimilar, which implies that isolation methods cannot be directly transposed from one tissue/fluid to another. To date, most RNA and miRNA extraction methods use a phenol:chloroform-based extraction technique, often facilitated by adding guanidinium thiocyanate, whereas newer methods, faster and some automated, include a selective solid phase (silica) adsorption of RNA from the phenol:chloroform extraction onto mini-columns, followed by elution in water or a buffer [101]. MiRNA molecules behave physically and chemically different from the larger RNA molecules, and their quantitative recovery requires optimization of existing total RNA isolation procedures. Various manufacturers have employed different strategies for this purpose.

MiRNA profiling is a multi-step process that includes: (i ) blood collection; (ii ) RNA purification; (iii ) RNA quantification and quality control; and (iv ) RNA profiling (Fig. 1). We will further discuss each of these steps, highlighting methodological aspects that may impact the outcome, as well as possible pitfalls. In addition to limited sample volumes, these involve: (i ) the lack of standard protocols; (ii ) interference of anticoagulants in PCR-based profiling [101]; (iii ) low recovery of miRNAs [64, 81]; and (iv ) the lack of known invariant miRNA species to be used as endogenous controls.

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Figure 1

Summary of the workflow in designing miRNA profiling from plasma or serum. One needs to first decide if plasma or serum will be analysed. If plasma is selected, then the anticoagulant should be carefully chosen, because of interference with downstream applications. Consistency in the time of collection, as well as other phlebotomy parameters, is necessary, concomitant with a similar time frame of miRNA extraction. For the extraction method selection, other factors have to be considered, such as the available initial fluid volume and the expected yield. Finally, quality control is a necessary step for successful downstream applications.

Lastly, we should stress the fact that it is not possible to unequivocally assign the origin of detected miRNAs. While circulating miRNAs are associated with EVs [36, 70], plasma lipoproteins [69] and proteins [68], the levels of each of these components, combined with efficiency of the extraction method used, further contribute to bias in interpreting miRNA expression levels. The sections below discuss newer methods for isolating all circulating extracellular miRNAs, regardless of plasma or serum components with which they may be associated.

MiRNAs profiling methods

To date, there are several methods to examine miRNA expression profiling including (i ) qRT-PCR, (ii ) microarrays, (iii ) sequence-specific hybridization in solution followed by miRNA molecules counting based on reporter probes and (iv) direct sequencing (Table 1). Each method has advantages and limitations (Fig. 2). In addition, miRNA assessment is also confronted with (i ) the inability to distinguish between precursor and mature forms of miRNAs on some profiling platforms and (ii ) the difficulty to validate and correlate individual miRNA expression between different profiling platforms [18, 103]. In addition, considerations for endogenous controls are dependent on the platform used. Although there are inconsistencies across profiling platforms, qRT-PCR platforms seem to have better sensitivity than array technologies for miRNA profiling from body fluids [141]. These issues and methods are briefly described below.

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Figure 2

Comparison of the common miRNA profiling methods. Workflow: indicates main steps after miRNA isolation for getting the raw expression data. Sensitivity, Specificity, Throughput, Absolute quantification/accuracy and Flexibility are classified as follows: +++ (very high); ++ (moderate); +/++ (moderate to low); + (low); and +/-(low or not applicable). Flexibility: refers to ease of customization. The only technology that allows absolute quantification is qRT-PCR, whereas NextGen sequencing is the only platform that can identify novel miRNAs. Data analysis is classified as: E (relatively easy); M (moderate) with various software applications available; and D (difficult) requiring advanced computational infrastructure. Other: Considerations and challenges for the respective technologies.

Using a qRT-PCR approach is limited in the species as well as the number of detectable miRNA species compared with microarrays. However, medium-and large-scale, high-throughput platforms are commercially available using a qRT-PCR approach, such as microfluidic cards or plates. These are customizable. However, for profiling a large number of miRNA species, the microfluidic cards are at the same time more flexible, but more limited in the number of miRNAs that can be examined compared with microarrays. To date, Qiagen PCR arrays cover human, mouse and rat, with primer assays extending to Rhesus, hamster, chicken, several viruses, etc., whereas Life Technologies assays cover ˜200 species. The design of PCR arrays can accommodate as few or as many miRNA species desired, but the higher their number, the more labour-intensive the study becomes, and less price-efficient compared with microarray methodology.

Discussion

The search for useful diagnostic and prognostic biomarkers obtained from minimally invasive techniques is at the forefront of many disease-oriented studies. From these studies, circulating extracellular miRNAs from the blood are emerging as ideal candidates. As highlighted throughout this review, using extracellular miRNAs from body fluids as biomarkers is in its infancy. While an abundance of studies report miRNAs differential expression, important procedural information is lacking and needs to be standardized and disseminated to the research community. Importantly, attention to the fasting status of the patient and blood collection procedures, such as anticoagulants and needle size, should be considered when profiling extracellular miRNA from blood. Furthermore, extraction methods vary among reports, while information on the starting fluid volume and especially the efficiency of extraction is often missing. The availability of this information will enable investigators to standardize procedures and perhaps compare profiles across various patient cohorts.

As discussed, there are currently no known endogenous controls for serum or plasma miRNAs [36, 37]. While the miRNA profile of plasma and serum are comparable in general terms [35, 37], subtle changes in expression patterns may be present. Finally, optimization of RNA extraction methodologies from fluid samples should enable the analysis of a few miRNA species up to several hundred miRNAs. Ultimately, the RNA quantity and quality may dictate the platform used to obtain the extracellular miRNA profile.

Conclusions

There is sufficient evidence to support circulating extracellular miRNAs, retrieved either from plasma or serum, as important players and/or promising biomarkers for a variety of diseases. Current studies are improving the ability to retrieve sufficient RNA for analysis and profile numerous miRNAs. However, the field still lacks consistency and standardization, and thus effort is needed to establish common practices. Furthermore, several important considerations are needed before designing studies to analyse circulating miRNAs. As this field evolves, circulating miRNA profiles from plasma or serum are still susceptible to significant technological advancement. The potential to obtain extracellular miRNA signature from body fluids collected by non-invasive means exists. In fact, the knowledge of isolating extracellular RNAs from plasma or serum can be extrapolated to other body fluids, such as saliva or urine [68, 165]. Certainly, this information will lead to the development of diagnostic tests from easily assessable biofluids. Thus, as future experimental and clinical investigations start filling the gaps of our knowledge, the power of using not only extracellular miRNAs but perhaps other RNA species will greatly expand our understanding of diseases and may lead to new exciting therapies.

Key Points

• Introduction

• Current methodologies for extracting miRNAs from plasma and serum

  • – Considerations for the collection of plasma and serum

  • – Extraction methods

  • – Global quantity and quality assessment of miRNAs

• MiRNA Profiling Methods

  • – Real-time PCR

  • – Microarray-based detection of miRNA expression

  • – Exiqon miRCURY LNATM microRNA arrays

  • – NanoString Technologies nCounterc miRNA Expression Assay

  • – Next-generation sequencing

• Discussion

• Conclusions

Acknowledgments

References