MicroRNAs as biomarkers for dental diseases

Abstract

MicroRNAs (miRNAs) are short, noncoding RNAs that act as key regulators of diverse biological processes by mediating translational repression or mRNA degradation of target genes. Recent studies discovered miRNAs in saliva, and these miRNAs are promising candidates for use as biomarkers of dental diseases. In this review, the results of miRNA studies in the dental field are presented, and a brief overview of the current progress, limitations, and perspectives regarding miRNA biomarkers for dental diseases is given.

Keywords

microRNA ; Biomarker ; Saliva ; Periodontitis

MicroRNAs

MicroRNAs (miRNAs) are a class of small single-stranded noncoding RNAs that were first discovered in C. elegans and later shown to be evolutionarily conserved across many animal species, including humans [1] , [2]  and [3] . MicroRNAs, which are approximately 22 nucleotides in length, act as key regulators of diverse biological processes by mediating translational repression or mRNA degradation of their target genes [4]  and [5] . The mode of action of these regulators is through imperfect complementary binding to the 3′ untranslated region (3′ UTR) of target mRNAs [4]  and [6] . Typically, a single miRNA has the potential to simultaneously control the translation of hundreds of genes [5]  and [7] . To date, more than 2500 genes encoding miRNAs have been identified in the human genome [8]  and [9] .

The biogenesis of miRNAs begins with the production of mRNA-like polyadenylated primary transcripts (pri-miRNA) by RNA polymerase II. Subsequent miRNA maturation requires two RNase III proteins, Drosha and Dicer. These two proteins may collaborate in the stepwise processing of miRNAs, and also have key roles in the process of miRNA-mediated gene regulation. The mature single-stranded miRNAs are eventually incorporated into a ribonucleoprotein complex, the RNA-induced silencing complex (RISC). RISC acts to downregulate gene expression via mRNA cleavage or translation repression: the miRNA component acts as a guide [10] , [11] , [12] , [13]  and [14] .

Circulating microRNAs

Serum and plasma contain large amounts of stable miRNAs, and these therefore have potential to serve as biomarkers for specific physiological and pathological conditions such as cancer, transplant rejection, cardiac injury, infection, and others [3] , [15] , [16] , [17]  and [18] . The salivary transcriptome, which contains more than 3000 RNA species, including miRNAs, was recently released, and salivary miRNA biomarkers are emerging as tools for the detection of oral cancer and systemic diseases [19] , [20] , [21] , [22]  and [23] . The miRNAs in saliva have advantages for biomarkers compared with other salivary biomarkers like proteins, mRNAs, DNAs and bacterial products. Even aside from the distinctive function of miRNA as post-transcriptional regulator, miRNAs are stably present in saliva and the similarity between miRNA profiles of saliva and other body fluids provide high availability as biomarkers for various human diseases [21] , [24]  and [25] .

Saliva sampling is a non-invasive, cheap, easy-to-access alternative to traditional tissue and blood sampling [26]  and [27] . Saliva is an accurate indicator of bodily conditions, and salivary biomarkers may serve as early diagnostic tools. Saliva diagnostics is considered to be a highly promising alternative to classic environmental epidemiology [28]  and [29] . The ease of sampling and cost effectiveness of saliva-based tests provide advantages over traditional techniques for large scale population-based screening studies and also in situations where repeated sampling is required, such as for monitoring and managing disease progression [30] . Lab-on-a-chip (LOC) technologies are beginning to be used in clinical settings for point-of-care (POC) diagnostics [31] . Saliva samples have been used successfully for POC detection of multiple disease entities, including some that cause dental disease [32]  and [33] .

MicroRNAs as biomarkers for oral cancers

MicroRNAs are important in tumourigenesis due to their proximity to chromosomal breakpoints and their dysregulated expression levels in many malignancies [34] , [35]  and [36] . Overexpression of certain miRNAs might result in the downregulation of tumour suppressor genes, while underexpression of other miRNAs might cause oncogene upregulation [37]  and [38] . Consequently, several studies evaluated the potential of miRNAs as diagnostic and prognostic biomarkers for cancers [20] , [34] , [39]  and [40] .

Approximately 90% of head and neck cancers are oral squamous cell carcinomas (OSCC). OSCC is an aggressive and lethal malignancy that is a major worldwide problem due to its extremely high prevalence and very poor prognosis [41]  and [42] . The average 5-year survival rate for patients with diagnosed OSCC is approximately 50% [43]  and [44] . Therefore, an early detection method is needed for OSCC to improve treatment and long-term patient survival [20] . A number of studies have evaluated miRNAs as diagnostic biomarkers for OSCC. Differentially expressed miRNAs discovered by these studies are listed in Table 1 .

Table 1. Differential expression of miRNAs in oral cancers (Human model).

miRNA	Sample source	Disease	Expression	Reference
miR-211	Tissue	OSCC	Increased	Chang et al. [45]
miR-125a, miR-200a	Saliva	OSCC	Increased	Park et al. [20]
miR-21, miR-155, let-7i, miR142-3p, miR-423, miR-106b, miR-20a, miR-16	Tissue	HNSCC	Increased	Hui et al. [46]
miR-125b, miR-375, miR-10a			Decreased
miR-24	Plasma	OSCC	Increased	Lin et al. [47]
miR-31	Plasma	OSCC	Increased	Liu et al. [22]
miR-99a, miR-100	Tissue	HNSCC	Decreased	Chen et al. [48]
miR-9	Saliva	HNSCC	Increased	Salazar et al. [49]
miR-134, miR-191			Decreased
miR-21	Whole blood	OSCC	Increased	Ren et al. [50]
miR-155	Tissue	OSCC	Increased	Shi et al. [51]
miR-27b	Saliva	OSCC	Increased	Momen-Heravi et al. [38]

• Head and neck squamous cell carcinoma (HNSCC), oral squamous cell carcinoma (OSCC).

MicroRNAs as biomarkers for periodontitis

Periodontal disease is characterised by inflammation of tooth-supporting structures. Periodontitis, which is a typical manifestation of periodontal disease, involves progressive loss of the alveolar bone around the teeth. If left untreated, periodontitis can lead to tooth loosening and subsequent tooth loss [52] , [53] , [54]  and [55] . Associations between periodontal disease and other general health problems, such as diabetes, cardiovascular disease, rheumatoid arthritis and adverse pregnancy outcome, have been reported in recent years, indicating the importance of early detection and treatment of periodontal disease [56] . The development of diagnostic tools to detect the presence and activity of periodontal disease is therefore of high importance.

Periodontal disease severity has traditionally been assessed using clinical parameters like pocket probing depth, clinical attachment loss, bleeding on probing, and radiographic determination of alveolar bone loss. Most of these techniques were established more than five decades ago, and lack the capacity to identify highly susceptible patients at risk for disease progression [28]  and [57] . Periodontitis is a highly complex disease, which hampers the development of rapid, accurate, diagnostic and prognostic tests. Nevertheless, the development of innovative diagnostic tests for periodontal disease remains a high priority.

A small number of miRNA studies related to periodontal disease have been performed (Table 2 ). Xie et al. [58] used microarray analysis to examine miRNA expression, and transcript levels of selected inflammatory-related miRNAs were confirmed by quantitative reverse transcription polymerase chain reaction (qRT-PCR). The study used gingival tissues from ten healthy subjects and ten patients with periodontitis. Levels of some miRNAs were more than five-fold higher in tissues from periodontitis patients than in control tissues. In addition, the possible regulation of Toll-lik receptors (TLRs) in periodontal inflammation by miRNA pathways was also proposed.

Table 2. MicroRNA research related to periodontal disease.

Target diseases	Sample source	Methods	Results	Reference
Periodontitis	Healthy and diseased gingival tissues	miRNA PCR array	6 miRNAs up-regulated	Lee et al. [64]
Periodontitis	Healthy and diseased gingival tissues	miRNA Microarray	91 miRNAs up-regulated, 34 miRNAs down-regulated	Xie et al. [58]
Periodontitis and obesity	Gingival biopsy samples	miRNA PCR array	11 miRNAs up-regulated	Perri et al. [59]
Periodontitis	Healthy and diseased gingival tissues	miRNA Microarray	4 miRNAs up-regulated, 7 miRNAs down-regulated	Stoecklin-Wasmer et al. [61]

A pilot investigation was conducted to determine whether miRNA expression was altered by obesity or periodontal disease, and whether there were any potential interactions between obesity and periodontitis that could involve miRNA modulation [59] . In this study, gingival biopsy samples were obtained from 20 patients, ten of who were non-obese (BMI<30 kg/m² ) and ten of who were obese (BMI>30 kg/m² ). Each group of ten patients contained five patients with chronic periodontitis and five periodontally healthy patients. This was the first trial to assess the mechanisms underlying the pathogenesis of periodontitis and a common chronic condition (obesity), as well as the interaction between the two diseases [60] .

Stoecklin-Wasmer et al. [61] examined the occurrence of miRNAs in healthy and diseased gingival tissues and validated the in silico-predicted targets through mRNA profiling using whole-genome microarray analysis of the same specimens. Four miRNAs were significantly overexpressed, and seven significantly underexpressed, in gingival tissues compared to controls. Gene Set Enrichment Analysis (GSEA) identified 60 enriched miRNA gene sets with target genes involved in immune/inflammatory responses and tissue homeostasis. This was the first study to examine concurrent mRNA and miRNA expression in the same gingival tissues.

Only a handful of studies investigating miRNAs in gingival tissues have been reported to date. Studies of miRNAs and their relationships to periodontal disease will be improved in the near future by the use of diverse samples, including saliva, and this will allow the inter-relationships of periodontal disease with other systemic diseases to be ascertained. In addition, some studies using animal periodontitis models and dental stem cells have been conducted [62]  and [63] , and these will help determine the mechanisms underlying the modulation of specific candidate miRNAs.

Limitations of miRNAs as biomarkers

Although the exploitation of miRNAs as biomarkers for dental diseases is promising, some constraints should be considered.

First, differentially expressed candidate miRNAs identified through pilot studies need to be validated. Most previous studies using tissues were performed with samples from small numbers of individuals without matching for potential confounding factors known to influence periodontitis susceptibility such as age and gender. Further validation studies using large well-characterised cohorts are required [60] .

Second, although recent advances in molecular biology and high-throughput screening techniques have enabled researchers to characterise miRNA patterns in body fluids such as serum, plasma, and saliva on a large scale, this is limited by the lack of suitable endogenous controls for normalisation of salivary miRNAs. Recent research attempted to identify endogenous control miRNAs displaying minimal expression variability between samples [38] , but endogenous salivary miRNA controls are required for future exploitation of miRNA datasets. In addition, saliva samples collected from the same individual can display considerable heterogeneity according to the collection method used, and standardised methods for sample collection should therefore be considered.

Third, although biomarker development is paramount, the development of suitable treatment and prevention methods for patients testing positive for these biomarkers is also required. Effective, focused treatments are needed for highly susceptible patients in order to capitalise on early diagnosis, and without such treatments a clear cost-benefit advantage cannot be realised [28] .

Future directions

The availability of novel genetic testing technologies such as RNA sequencing will allow current technical limitations to be circumvented and will increase test accuracy when extremely small samples are used. Fundamental research into the mechanisms underlying control and activity of miRNAs will facilitate the identification of links between various diseases. In addition, more efficient computational prediction models and improved bioinformatic pipelines will allow optimal use of miRNA datasets [65] , [66]  and [67] .

The combination of new diagnostic tests with saliva sampling will provide easy, rapid, testing, and will enable large scale and follow-up studies to be conducted at lower costs than when using traditional blood or tissue samples. With the introduction of new and improved techniques, more individuals susceptible to periodontal disease and with poor prognosis for other conditions will be detected early, allowing patient-focused clinical treatments. This first step will lay the groundwork for the future development of personalised dentistry using genetic information.

Acknowledgements

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2013R1A1A2011974 ).

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