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 ).

References

  1. [1] R.C. Lee, R.L. Feinbaum, V. Ambros; The C . elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14  ; Cell, 75 (1993), pp. 843–854
  2. [2] A.E. Pasquinelli, B.J. Reinhart, F. Slack, M.Q. Martindale, M.I. Kuroda, B. Maller, et al.; Conservation of the sequence and temporal expression of let-7 heterochronic regulatory RNA; Nature, 408 (2000), pp. 86–89
  3. [3] M. Weiland, X.H. Gao, L. Zhou, Q.S. Mi; Small RNAs have a large impact: circulating microRNAs as biomarkers for human diseases; RNA Biol., 9 (2012), pp. 850–859
  4. [4] D.P. Bartel; MicroRNAs: target recognition and regulatory functions; Cell, 136 (2009), pp. 215–233
  5. [5] M. Selbach, B. Schwanhausser, N. Thierfelder, Z. Fang, R. Khanin, N. Rajewsky; Widespread changes in protein synthesis induced by microRNAs; Nature, 455 (2008), pp. 58–63
  6. [6] D.W. Thomson, C.P. Bracken, G.J. Goodall; Experimental strategies for microRNA target identification; Nucleic Acids Res., 39 (2011), pp. 6845–6853
  7. [7] D. Baek, J. Villen, C. Shin, F.D. Camargo, S.P. Gygi, D.P. Bartel; The impact of microRNAs on protein output; Nature, 455 (2008), pp. 64–71
  8. [8] A. Kozomara, S. Griffiths-Jones; miRBase: annotating high confidence microRNAs using deep sequencing data; Nucleic Acids Res., 42 (2014), pp. D68–D73
  9. [9] R. Dai, S.A. Ahmed; MicroRNA, a new paradigm for understanding immunoregulation, inflammation, and autoimmune diseases; Trans. Res.: J. Lab. Clin. Med., 157 (2011), pp. 163–179
  10. [10] Y. Lee, C. Ahn, J. Han, H. Choi, J. Kim, J. Yim, et al.; The nuclear RNase III Drosha initiates microRNA processing; Nature, 425 (2003), pp. 415–419
  11. [11] H.K. Saini, A.J. Enright, S. Griffiths-Jones; Annotation of mammalian primary microRNAs; BMC Genom., 9 (2008), p. 564
  12. [12] E. Bernstein, A.A. Caudy, S.M. Hammond, G.J. Hannon; Role for a bidentate ribonuclease in the initiation step of RNA interference; Nature, 409 (2001), pp. 363–366
  13. [13] D.P. Bartel; MicroRNAs: genomics, biogenesis, mechanism, and function; Cell, 116 (2004), pp. 281–297
  14. [14] D.S. Schwarz, G. Hutvagner, B. Haley, P.D. Zamore; Evidence that siRNAs function as guides, not primers, in the Drosophila and human RNAi pathways; Mol. Cell, 10 (2002), pp. 537–548
  15. [15] X. Chen, Y. Ba, L. Ma, X. Cai, Y. Yin, K. Wang, et al.; Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases; Cell Res., 18 (2008), pp. 997–1006
  16. [16] P.S. Mitchell, R.K. Parkin, E.M. Kroh, B.R. Fritz, S.K. Wyman, E.L. Pogosova-Agadjanyan, et al.; Circulating microRNAs as stable blood-based markers for cancer detection; Proc. Natl. Acad. Sci. USA, 105 (2008), pp. 10513–10518
  17. [17] J.P. Duong Van Huyen, M. Tible, A. Gay, R. Guillemain, O. Aubert, S. Varnous, et al.; MicroRNAs as non-invasive biomarkers of heart transplant rejection; Eur. Heart J., 35 (45) (2014), pp. 3194–3202
  18. [18] C.H. Lawrie, S. Gal, H.M. Dunlop, B. Pushkaran, A.P. Liggins, K. Pulford, et al.; Detection of elevated levels of tumour-associated microRNAs in serum of patients with diffuse large B-cell lymphoma; Br. J. Haematol., 141 (2008), pp. 672–675
  19. [19] Y. Li, X. Zhou St, M.A. John, D.T. Wong; RNA profiling of cell-free saliva using microarray technology; J. Dent. Res., 83 (2004), pp. 199–203
  20. [20] N.J. Park, H. Zhou, D. Elashoff, B.S. Henson, D.A. Kastratovic, E. Abemayor, et al.; Salivary microRNA: discovery, characterization, and clinical utility for oral cancer detection; Clin. Cancer Res., 15 (2009), pp. 5473–5477
  21. [21] R.S. Patel, A. Jakymiw, B. Yao, B.A. Pauley, W.C. Carcamo, J. Katz, et al.; High resolution of microRNA signatures in human whole saliva; Arch. Oral Biol., 56 (2011), pp. 1506–1513
  22. [22] C.J. Liu, S.C. Lin, C.C. Yang, H.W. Cheng, K.W. Chang; Exploiting salivary miR-31 as a clinical biomarker of oral squamous cell carcinoma; Head Neck, 34 (2012), pp. 219–224
  23. [23] J.M. Yoshizawa, D.T. Wong; Salivary microRNAs and oral cancer detection; Methods Mol. Biol., 936 (2013), pp. 313–324
  24. [24] X. Lin, H.C. Lo, D.T. Wong, X. Xiao; Noncoding RNAs in human saliva as potential disease biomarkers; Front. Genet., 6 (2015), p. 175 http://dx.doi.org/10.3389/fgene.2015.00175
  25. [25] J.A. Webber, D.H. Baxter, S. Zhang, D.Y. Huang, K.H. Huang, M.J. Lee, et al.; The microRNA spectrum in 12 body fluids; Clin. Chem., 56 (2010), pp. 1733–1741
  26. [26] R.J. Genco; Salivary diagnostic tests; J. Am. Dent. Assoc., 143 (2012), pp. 3S–5S
  27. [27] W.V. Giannobile, D.T. Wong; Salivary diagnostics: oral health and beyond!; J. Dent. Res., 90 (2011), pp. 1153–1154
  28. [28] W.V. Giannobile, T. Beikler, J.S. Kinney, C.A. Ramseier, T. Morelli, D.T. Wong; Saliva as a diagnostic tool for periodontal disease: current state and future directions; Periodontology, 50 (2000), pp. 52–64 2009
  29. [29] S. Bonassi, M. Neri, R. Puntoni; Validation of biomarkers as early predictors of disease; Mutat. Res., 480–481 (2001), pp. 349–358
  30. [30] H. Fabryova, P. Celec; On the origin and diagnostic use of salivary RNA; Oral Dis., 20 (2014), pp. 146–152
  31. [31] N. Christodoulides, P.N. Floriano, C.S. Miller, J.L. Ebersole, S. Mohanty, P. Dharshan, et al.; Lab-on-a-chip methods for point-of-care measurements of salivary biomarkers of periodontitis; Ann. N. Y. Acad. Sci., 1098 (2007), pp. 411–428
  32. [32] D. Malamud; Salivary diagnostics: the future is now; J. Am. Dent. Assoc., 137 (284) (2006), p. 286
  33. [33] W.V. Giannobile, J.T. McDevitt, R.S. Niedbala, D. Malamud; Translational and clinical applications of salivary diagnostics; Adv. Dent. Res., 23 (2011), pp. 375–380
  34. [34] T.A. Farazi, J.I. Spitzer, P. Morozov, T. Tuschl; miRNAs in human cancer. The; J. Pathol., 223 (2011), pp. 102–115
  35. [35] J. Lu, G. Getz, E.A. Miska, E. Alvarez-Saavedra, J. Lamb, D. Peck, et al.; MicroRNA expression profiles classify human cancers; Nature, 435 (2005), pp. 834–838
  36. [36] G.A. Calin, C. Sevignani, C.D. Dumitru, T. Hyslop, E. Noch, S. Yendamuri, et al.; Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers; Proc. Natl. Acad. Sci. United States Am., 101 (2004), pp. 2999–3004
  37. [37] C.Z. Chen; MicroRNAs as oncogenes and tumor suppressorshe; N. Engl. J. Med., 353 (2005), pp. 1768–1771
  38. [38] F. Momen-Heravi, A.J. Trachtenberg, W.P. Kuo, Y.S. Cheng; Genomewide study of salivary microRNAs for detection of oral cancer; J. Dent. Res., 93 (2014), pp. 86S–93S
  39. [39] Y. Wang, Q. Wang, N. Zhang, H. Ma, Y. Gu, H. Tang, et al.; Identification of microRNAs as novel biomarkers for detecting esophageal squamous cell carcinoma in Asians: a meta-analysis; Tumour Biol., 35 (2014), pp. 11595–11604
  40. [40] N. Yanaihara, N. Caplen, E. Bowman, M. Seike, K. Kumamoto, M. Yi, et al.; Unique microRNA molecular profiles in lung cancer diagnosis and prognosis; Cancer Cell, 9 (2006), pp. 189–198
  41. [41] T.J. Chiu, Y.J. Chen, K.M. Rau, C.H. Chen, C.Y. Chien, S.H. Li, et al.; Midkine neurite growth-promoting factor 2 expression as a potential prognostic marker of adjuvant therapy in head and neck squamous cell carcinoma; Biomarkers, 18 (2013), pp. 687–698
  42. [42] A.K. Markopoulos; Current aspects on oral squamous cell carcinoma; Open Dent. J., 6 (2012), pp. 126–130
  43. [43] B.M. Brinkman, D.T. Wong; Disease mechanism and biomarkers of oral squamous cell carcinoma; Curr. Opin. Oncol., 18 (2006), pp. 228–233
  44. [44] G.F. Funk, L.H. Karnell, R.A. Robinson, W.K. Zhen, D.K. Trask, H.T. Hoffman; Presentation, treatment, and outcome of oral cavity cancer: a National Cancer Data Base report; Head Neck, 24 (2002), pp. 165–180
  45. [45] K.W. Chang, C.J. Liu, T.H. Chu, H.W. Cheng, P.S. Hung, W.Y. Hu, et al.; Association between high miR-211 microRNA expression and the poor prognosis of oral carcinoma; J. Dent. Res., 87 (2008), pp. 1063–1068
  46. [46] A.B. Hui, M. Lenarduzzi, T. Krushel, L. Waldron, M. Pintilie, W. Shi, et al.; Comprehensive MicroRNA profiling for head and neck squamous cell carcinomas; Clin. Cancer Res., 16 (2010), pp. 1129–1139
  47. [47] S.C. Lin, C.J. Liu, J.A. Lin, W.F. Chiang, P.S. Hung, K.W. Chang; miR-24 up-regulation in oral carcinoma: positive association from clinical and in vitro analysis; Oral Oncol., 46 (2010), pp. 204–208
  48. [48] Z. Chen, Y. Jin, D. Yu, A. Wang, I. Mahjabeen, C. Wang, et al.; Down-regulation of the microRNA-99 family members in head and neck squamous cell carcinoma; Oral Oncol., 48 (2012), pp. 686–691
  49. [49] C. Salazar, R. Nagadia, P. Pandit, J. Cooper-White, N. Banerjee, N. Dimitrova, et al.; A novel saliva-based microRNA biomarker panel to detect head and neck cancers; Cell. Oncol., 37 (2014), pp. 331–338
  50. [50] W. Ren, C. Qiang, L. Gao, S.M. Li, L.M. Zhang, X.L. Wang, et al.; Circulating microRNA-21 (MIR-21) and phosphatase and tensin homolog (PTEN) are promising novel biomarkers for detection of oral squamous cell carcinoma; Biomarkers, 19 (7) (2014), pp. 590–596
  51. [51] L.J. Shi, C.Y. Zhang, Z.T. Zhou, J.Y. Ma, Y. Liu, Z.X. Bao, et al.; MicroRNA-155 in oral squamous cell carcinoma: overexpression, localization, and prognostic potential; Head neck, 37 (2014), pp. 970–976
  52. [52] G.C. Armitage; Clinical evaluation of periodontal diseases; Periodontology, 7 (2000), pp. 39–53 1995
  53. [53] G.C. Armitage, P.B. Robertson; The biology, prevention, diagnosis and treatment of periodontal diseases: scientific advances in the United States; J. Am. Dent. Assoc., 140 (Suppl. 1) (2009), pp. 36S–43S
  54. [54] S.H. Kim, B.M. Seo, P.H. Choung, Y.M. Lee; Adult stem cell therapy for periodontal disease; Int. J. Stem Cells, 3 (2010), pp. 16–21
  55. [55] S. Offenbacher; Periodontal diseases: pathogenesis; Ann. Periodontol./Am. Acad. Periodontol., 1 (1996), pp. 821–878
  56. [56] D. Kinane, P. Bouchard, Group EoEWoP; Periodontal diseases and health: consensus report of the sixth European workshop on periodontology; J. Clin. Periodontol., 35 (2008), pp. 333–337
  57. [57] J.M. Goodson; Diagnosis of periodontitis by physical measurement: interpretation from episodic disease hypothesis; J. Periodontol., 63 (1992), pp. 373–382
  58. [58] Y.F. Xie, R. Shu, S.Y. Jiang, D.L. Liu, X.L. Zhang; Comparison of microRNA profiles of human periodontal diseased and healthy gingival tissues; Int. J. Oral Sci., 3 (2011), pp. 125–134
  59. [59] R. Perri, S. Nares, S. Zhang, S.P. Barros, S. Offenbacher; MicroRNA modulation in obesity and periodontitis; J. Dent. Res., 91 (2012), pp. 33–38
  60. [60] F. D׳Aiuto, J. Suvan; Obesity, inflammation, and oral infections: are microRNAs the missing link?; J. Dent. Res., 91 (2012), pp. 5–7
  61. [61] C. Stoecklin-Wasmer, P. Guarnieri, R. Celenti, R.T. Demmer, M. Kebschull, P.N. Papapanou; MicroRNAs and their target genes in gingival tissues; J. Dent. Res., 91 (2012), pp. 934–940
  62. [62] M.A. Nahid, M. Rivera, A. Lucas, E.K. Chan, L. Kesavalu; Polymicrobial infection with periodontal pathogens specifically enhances microRNA miR-146a in ApoE-/- mice during experimental periodontal disease; Infect. Immun., 79 (2011), pp. 1597–1605
  63. [63] Y. Liu, W. Liu, C. Hu, Z. Xue, G. Wang, B. Ding, et al.; MiR-17 modulates osteogenic differentiation through a coherent feed-forward loop in mesenchymal stem cells isolated from periodontal ligaments of patients with periodontitis; Stem Cells, 29 (2011), pp. 1804–1816
  64. [64] Y.H. Lee, H.S. Na, S.Y. Jeong, S.H. Jeong, H.R. Park, J. Chung; Comparison of inflammatory microRNA expression in healthy and periodontitis tissues; Biocell, 35 (2011), pp. 43–49
  65. [65] S.Y. Lee, K.A. Sohn, J.H. Kim; MicroRNA-centric measurement improves functional enrichment analysis of co-expressed and differentially expressed microRNA clusters; BMC Genom., 13 (Suppl 7) (2012), p. S17
  66. [66] E. Sonkoly, A. Pivarcsi; microRNAs in inflammation; Int. Rev. Immunol., 28 (2009), pp. 535–561
  67. [67] A. Tiwari, S. Shivananda, K.S. Gopinath, A. Kumar; microRNA-125a reduces proliferation and invasion of oral squamous cell carcinoma cells by targeting estrogen-related receptor alpha: implications for cancer therapeutics; J. Biol. Chem., 289 (2014), pp. 32276–32290
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