Methodological challenges in utilizing miRNAs as circulating biomarkers

Abstract

MicroRNAs (miRNAs) have emerged as important regulators in the post-transcriptional control of gene expression. The discovery of their presence not only in tissues but also in extratissular fluids, including blood, urine and cerebro-spinal fluid, together with their changes in expression in various pathological conditions, has implicated these extracellular miRNAs as informative biomarkers of disease. However, exploiting miRNAs in this capacity requires methodological rigour. Here, we report several key procedural aspects of miRNA isolation from plasma and serum, as exemplified by research in cardiovascular and pulmonary diseases. We also highlight the advantages and disadvantages of various profiling methods to determine the expression levels of plasma- and serum-derived miRNAs. Attention to such methodological details is critical, as circulating miRNAs become diagnostic tools for various human diseases.

Keywords: biomarkers; circulating microRNAs; microRNA; plasma; profiling; real-time PCR; serum.

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.

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.