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. 2024 May 31;10(1):34–43. doi: 10.1177/23800844241252395

The Evaluation of a 5-miRNA Panel in Patients with Periodontitis Disease

O Baru 1,2,3, L Pop 1, L Raduly 1, C Bica 1, N Mehterov 4,5, R Pirlog 1, S Buduru 3,6, C Braicu 1,*, I Berindan-Neagoe 1, M Badea 7
PMCID: PMC11653349  PMID: 38819194

Abstract

Introduction:

Side by side with tooth decay, periodontitis remains one of the most common oral diseases and is increasingly recognized as a serious public health concern worldwide.

Objectives:

The present study aims at comparing the levels of 5 specific miRNAs (miR-29b-3p, miR-34a-5p, miR-155-5p, miR-181a-5p, and miR-192-5p) in patients with periodontal disease and healthy controls.

Methods:

The pathogenic mechanism is related to the activation of immune response and significant alteration of coding and noncoding genes, including miRNA. The study includes 50 subjects (17 with periodontal disease and 33 healthy controls) with a mean age of 45.3 y. In both periodontitis patients and healthy controls, a panel of 5 miRNAs (miR-29b-3p, miR-34a-5p, miR-155-5p, miR-181a-5p, and miR-192-5p) is examined by determining their expression levels with quantitative reverse transcription polymerase chain reaction.

Results:

The periodontitis patients express high levels of all the investigated miRNAs. Receiver operating characteristic curve analysis shows an area under the curve (AUC) of 0.69 to 0.74 for individual transcripts with the highest AUC value observed for miR-192, followed by miR-181a.

Conclusions:

The study indicates that the 5-miRNA panel can be used as biomarker for periodontitis. In this way, all implantology procedures and treatment options for patients diagnosed with periodontitis can be improved for better long-term results, predictability, and follow-up frequency.

Knowledge Transfer Statement:

The discovery of a miRNA panel as a potential biomarker for periodontitis offers major opportunities for practical application. Our study can improve diagnostic accuracy; researchers can develop new theories on molecular mechanisms and biomarker discovery.

Keywords: oral health, periodontitis disease, microRNAs, qRT-PCR, biomarkers, diagnostic tools

Introduction

Periodontitis is a complex inflammatory disease, currently ranked sixth among the broad class of chronic inflammatory diseases, and many theories of its etiology have been suggested over the years. Hypotheses on its pathogenic mechanisms have shifted from an initial theory stating that periodontitis is an inherent consequence of gingivitis, whose severity is directly connected to plaque levels (Preshaw et al. 2004), to a recent assumption drawing attention to the presence of biofilm, host immune response, microbiome, and the dysbiosis phenomenon (Meyle and Chapple 2015; Aravindraja et al. 2022; Aravindraja et al. 2023). Page and Kornman (1997) were the first to determine a pathogenetic pattern of periodontitis in 1997. Since then, there has been a consensus that bacteria population is different in patients with periodontal disease and in healthy subjects (Darveau et al. 1997). Based on the fact that there is no certainty on how bacteria affect the response of the host, Roberts and Darveau (2015) focus on the oral microbiome, suggesting that it may play a key role in the onset and evolution of periodontitis. Periodontitis has more recently been considered a dysbiosis disease (Aravindraja et al. 2023). The notion refers to the disruption of balance between commensal bacteria and pathogens and the altering of host response, and it is related to some specific miRomics (Aravindraja et al. 2023).

Early diagnosis is essential to initiate timely intervention and prevent further disease progression. By discovering reliable and specific biomarkers, clinicians can identify individuals at risk of developing periodontitis before clinical signs become apparent (Baru et al. 2023).

Although the bacteria involved in the onset and progression of the disease have been extensively studied and much has been published on the respective topic, less is known about the immune response and hereditary components. Among them, the inflammatory response, the activation of Toll-like receptors, the excessive activity of matrix metalloproteinases, the production of reactive species of oxygen, and the interaction between receptor activator of nuclear factor κB ligand (RANKL) and its receptor RANK play a crucial role in bone remodeling during periodontitis.

Several molecular mechanisms are involved in the development and progression of periodontitis. The mechanism of local inflammation and systemic injury in periodontitis is complex yet limited in its molecular profiling characteristics. It involves the alteration of coding and noncoding genes, including well-known microRNAs (miRNAs), but also other species of noncoding RNAs like long noncoding RNAs (lncRNAs).

Noncoding RNAs have been extensively studied, emerging as regulators of gene expression levels and being known for their potential involvement in the biological and pathological processes of periodontitis (Amaral et al. 2019; Liu et al. 2020; Aravindraja et al. 2022). miRNAs are small noncoding RNAs (ncRNAs) that bind to messenger RNA (mRNA) molecules, preventing translation or promoting degradation. miRNAs are highly conserved short sequences (19–24 nucleotides in length) that interact with the 3′ untranslated regions (3′ UTR) of target mRNA, leading to mRNA degradation, translational inhibition, or interfering with the posttranscriptional expression of essential genes related to critical biological processes, including regulation of the immune response. The miR-29 family includes members overexpressed in gingiva during periodontitis and positively regulates osteoblast differentiation (Kagiya 2016). miR-29b is a critical element of inflammation and regulation of the extracellular matrix proteins (Durrani-Kolarik et al. 2017). Another study presents miR-29b as a transcript that alters macrophage function. An in vitro study reveals that macrophages exposed to lipopolysaccharide cause downregulation of miR-29b (Naqvi et al. 2014). miR-34 family members are involved in inflammatory processes. miR-34a is related to periodontitis as a critical regulatory element of TLR/NF-κB signaling pathway (Pan et al. 2022). miR-155 is a deeply investigated transcript; it has been demonstrated to participate in various biological processes, including cell proliferation and inflammation. Recent studies have revealed an altered expression level of miR-155 as an essential element of the pathological mechanism of periodontal diseases (Al-Rawi et al. 2020; Jankauskas et al. 2021; Wu et al. 2021). miR-192-5 has been observed to be downregulated in periodontal disease, as revealed in our recent microarray study.

miRNAs can serve as informative markers for dental procedures in periodontitis. Evidence suggests that altered miRNA expression levels in gingival tissues can be causally connected to periodontitis and regarded as potential biomarker candidates. There is less evidence on the expressions of miR-29b-3p, miR-34a-5p, miR-155-5p, miR-181a-5p, and miR-192-5p in the gingival tissue of patients with periodontal diseases versus a healthy control group. While several studies show data on the aforementioned miRNAs at a single level, our study proposes the investigation of their expression level in a 5-miRNA panel.

Materials and Methods

Patients

The study included a cohort of 50 patients, 33 healthy controls and 17 with periodontitis (Table). Thorough dental and periodontal examinations were performed, and all clinical data were collected and stored in a computer database. Periodontal examination was based on Tonetti’s staging and grading of periodontitis (Tonetti et al. 2018). Gingival index less than 1, periodontal probing depth less than 3 mm, clinical attachment loss less than 1 mm, and a percentage less than 10% of bleeding on probing indicated a healthy subject. The periodontitis group consisted of patients who underwent periodontal treatment (staging I–IV) according to the latest guidelines (Sanz et al. 2020; Herrera et al. 2022), whose gingival inflammation site was stable from a periodontal point of view at the moment of gingival sampling. Smokers and patients with uncontrolled diabetes, severe cardiovascular diseases, bisphosphonates treatment, and chemotherapy or head and neck radiotherapy were excluded from the study. Periodontal patients included in the study were patients who needed implant therapy, tooth extraction, bone regeneration, and alveolar crest reconstruction, whose treatment justified sampling of 2 × 2 × 1 keratinized gingival tissue without any surgical risk for individual healing or affecting the outcome of the procedure. Before surgery, patients were informed that a sample of their gingival tissue would be studied according to a specific informed protocol developed at the Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca.

Periodontitis and healthy control samples consisted of fresh-frozen gingival tissue. All the patients signed informed consents, and the study was approved by the Ethical Committee of the Iuliu Hatieganu University of Medicine and Pharmacy no 81/11 March 2019.

RNA Extraction

Fresh-frozen gingival tissue from patients with periodontitis and healthy controls was used to extract RNA with the standard phenol-chloroform method. The tissue was mechanically homogenized in an 800-µL TripleXtractor (Grisp), and the samples were then used for RNA extraction. The first step of the protocol was adding chloroform (160 µL), gentle vortexing, and incubating for 5 min at room temperature (RT), followed by centrifugation for 20 min at 13,000 rpm and 4°C. Subsequently, the aqueous fraction was transferred to a new tube, precipitated using isopropanol (a volume of approximately 500 µL), gently mixed, and transferred to a new 1.5-mL tube. RNA was precipitated with 500 µL isopropanol, mixed by tube inversion, and incubated for 15 min at RT, then centrifuged at 13,000 rpm and 4°C for 15 min. The washing step consisted of adding 1 mL of 75% ethanol. The ethanol was removed, the pellet was dried, and 20 µL of nuclease-free water was added for solubilization. The total RNA was quantified using a NanoDrop spectrophotometer (Thermo Fisher).

Evaluation of miRNA Using a TaqMan Quantitative Reverse Transcription Polymerase Chain Reaction Protocol

The expressions of miR-29b-3p, miR-34a-5p, miR-155-5p, and miR-192 were assessed by using 50 ng total RNA, reverse transcribed with a TaqMan MicroRNA Transcription kit (Applied Biosystems), and primers for selected transcripts and normalization to RNU6 and RNU48 as internal controls. Appendix Table 1 presents the TaqMan assay ID of the primers used for evaluation. In the complementary DNA (cDNA) synthesis step, the samples were incubated at 16°C for 30 min, 42°C for 30 min, and 85°C for 5 min and then held at 4°C. All the samples were diluted 5 times in nuclease-free water for amplification.

The amplification reaction mixture comprised 5 µL TaqMan Fast Advanced Master Mix (Applied Biosystems), 0.4 µL TaqMan microRNA primer for each analyzed miRNA, and 5.2 µL cDNA. A mixture of 5 µL in duplicate was used for quantitative reverse transcription polymerase chain reaction (qRT-PCR), performed according to the manufacturer’s standard program in FastMode (1 cycle: 2 min at 50°C, 1 cycle: 20 s at 95°C, and 40 cycles at 95°C for 1 s and 60°C for 20 s). The data were analyzed and the CT values extracted. Then the data were analyzed using the standard ΔΔCT method developed by Vandesompele et al. (2002). The results were normalized to the level of RNU6 and RNU44 expression. The results of relative miRNA expression levels were reported as the mean ± standard error. P values <0.05 based on a Student’s t test were considered significant.

Discrimination Power Analysis

The diagnostic potential of miR-29b-3p, miR-34a-5p, miR-155-5p, and miR-192 in periodontitis was evaluated by the receiver operating characteristic (ROC) curve. The combiROC online tool (www.combiroc.eu) was used to design ROC curves by comparing the expression levels of the aforementioned miRNAs in normal and periodontal gingival tissues. Additionally, assessing the sensitivity, specificity, area under the curve (AUC), and P value at various expression thresholds could help identify an optimal cutoff point for diagnostic purposes, balancing sensitivity and specificity to achieve the most accurate diagnostic performance.

Results

miRNA Expression Levels

Statistically significant relative expression levels for all the tested miRNAs were found in periodontitis patients as compared to healthy controls. Statistical analysis of each tested miRNA showed that all of them were upregulated, with a P value <0.05 (Fig. 1).

Figure 1.

Figure 1.

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The relative expression levels were determined by quantitative reverse transcription polymerase chain reaction for selected microRNA (miRNA) in gingival tissue in periodontitis (n = 17) versus the healthy control group (n = 33) and receiver operating characteristic (ROC) curve analysis. Relative expression levels of (A) miR-29b-3p, (B) miR-34a-5p, (C) miR-155-5p, (D) miR-192-5p, and (E) miR-181a-5p. ROC curve analysis of (F) miR-29b-3p, (G) miR-34a-5p, (H) miR-155-5p, (I) miR-192-5p, and (J) miR-181a-5p. Student’s t test was used to calculate P values (*P < 0.05, **P < 0.01, ***P < 0.001).

ROC curve analysis of the selected miRNAs revealed that all tested miRNAs had an AUC more significant than 6 (Fig. 1F–J). The results of ROC curves used to diagnose periodontitis showed an AUC of 0.69 to 0.74 for individual transcripts. The highest AUC value was observed for the miR-192-5p, followed by miR-181a-5p.

Multiple ROC analyses are presented in Figure 2, showing the highest AUC value (0.818) for the combination miR-192-5p + miR-181a-5p, which had a higher AUC value than the individual transcripts. The lowest AUC values were obtained for miR-34a-5p + miR-29b (AUC = 0.676); interestingly enough, when evaluated in combination with miR-181a-5p (miR-34a-5p + miR-29b + miR-181a-5p), the AUC was 0.724. Multiple ROC curves for the analyzed miR-155-5p could not be generated using the CombiROC online tool.

Figure 2.

Figure 2.

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Multiple receiver operating characteristic curves showing relative expression levels of miR-29b-3p, miR-34a-5p, miR-155-5p, miR-192-5p, miR-181a-5p, and the best combination, with the highest area under the curve value used to differentiate between periodontitis patients and periodontally healthy individuals.

Correlation and Principal Component Analysis

The correlation coefficients between the investigated miRNAs were determined by using GraphPad Prism version 9 (GraphPad Software). The results of the correlation analysis showed that in chronic periodontitis, miR-155-5p expression level was significantly positively correlated with miR-192-5p, miR-34a-5p was positively correlated with miR-29b-3p and miR-181a-5p, and miR-29b was positively correlated with miR-181a-5p. Pearson correlation analyses of the selected and P values are presented in Appendix Table 2 and Figure 3.

Figure 3.

Figure 3.

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Pearson correlation and principal component analysis (PCA) for altered microRNAs (miRNAs) in periodontitis. (A) Heatmap of Pearson correlations of the miRNA expression levels among the periodontitis samples. (B) PCA analysis for evaluated miRNAs in periodontitis.

Principal component analysis (PCA) was performed to determine the top 3 principal components and the resulting discriminating miRNA variables on the hierarchical clustering heatmaps. PCA of periodontitis gingival tissue showed that 3 miRNAs, miR-34a-5p, miR-29b-3p, and miR-1815p, respectively miR-192-5p and miR-155-5p, were grouped.

Kyoto Encyclopedia of Genes and Genomes Targeted Pathways and Clusters/Heatmap Analysis

DIANA Mirpath used reverse search to identify miRNAs involved in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways using the DIANA-TarBase v7.0 method and searching clusters/heatmap results for KEGG-targeted pathways (Tastsoglou et al. 2023). The investigated transcripts (miR-29b-3p, miR-34a-5p, miR-155-5p, miR-192-5p, miR-181a-5p) are shown in Figure 4. Results were visualized as KEGG pathway unions and the P value threshold was set at 0.05, revealing a wide range of biological pathways involved.

Figure 4.

Figure 4.

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Heatmap showing Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway intersection with all the investigated transcripts; it selected targeted KEGG pathways, with statistically significant results for all the investigated microRNAs according to Tarbase.

Discussion

In the present study, our examination of a panel of 5 miRNAs—miR-29b-3p, miR-34a-5p, miR-155-5p, miR-181a-5p, and miR-192-5p—revealed interesting insights about their potential role as biomarkers for periodontitis. The combination of multiple miRNAs would improve accuracy of diagnosis, potentially leading to earlier detection and intervention. Our assumptions were supported by a recent bioinformatic study that presented the importance of miRNA in orthodontic pathologies (Kapoor et al. 2021). miR-34 and miR-29 families were indicated as key biomarkers for tooth movement. A profiling study revealed upregulation of miR-15a, miR-29b, miR-125a, miR-146a, miR-148/148a, and miR-223 and downregulation of miR-92 in periodontal disease in both human and mouse models (Luan et al. 2018). Also, miR-29b was proved to be part of an altered miRNA signature of obese periodontitis cases (Naqvi et al. 2019). Upregulation of miR-29b activated osteoclast differentiation in tumor necrosis factor α/RANKL-treated cells, which could promote periodontal bone loss (Kagiya and Nakamura 2013). Through regulating many extracellular matrix (ECM) genes, miRNAs had been proven to play an important role in tissue remodeling. Chen et al. (2015) showed that, in human periodontal ligament cells (PDLCs), cyclic stretch led to overexpression of major ECM genes, such as COL1A1, COL3A1, and COL5A1. In contrast, the compression force had the opposite effect on their expression. Moreover, direct interaction between miR-29 and COL1A1, COL3A1, and COL5A1 was proven in both in vitro and in vivo studies (Chen et al. 2015). The selected miRNAs were significantly increased in the periodontitis group as compared to the gingivitis group (Öngöz Dede et al. 2023). In addition, miR-29b, alongside miR-203, miR-142-3p, miR-146a, miR-146b, and miR-155, was demonstrated to be induced in the saliva of patients with periodontal disease as compared to healthy smokers and nonsmokers.

All our selected miRNAs had an AUC significantly higher than 0.6, showing that they could effectively enable to distinguish patients with periodontitis. The highest value was observed for miR-181a and miR-192, which suggested that they could be used as potential early-diagnosis biomarkers. Analyzing the effect of combined miRNA panels for their AUC values in distinguishing patients with periodontitis versus healthy controls, we obtained the highest value for the grouping of miR-192-5p with miR-181a-5p. Using PCA analysis, we identified 2 groups of miRNAs that clustered together: one group represented by miR-34a-5p, miR-29b-3p, and miR-1815p and the second group composed of miR-192-5p and miR-155-5p. The elevated miR-192 expression in the gum tissue of patients with chronic periodontitis and its positive correlation with the severity of periodontal inflammation indicated its potential relevance in regulating the inflammatory response in this condition (Ogata 2017). Its target genes were involved in the TGFβ1 pathway, suggesting that it could also be involved in tissue fibrosis and remodeling in periodontal tissues (Ogata 2017). Patients with periodontitis displayed increased miR-34a levels (Pan et al. 2022). A part of the miR-34 family, miR-34a, miR-34b, and miR-34c, was involved in several biological processes, including cell death, cell cycle, and cellular senescence (Ghandadi and Sahebkar 2016). They were associated with bone development and regulating the function of osteoblasts. Aberrant expression of miR-34a was correlated with dysregulation of bone synthesis and loss in periodontitis. Among the miR-34 family, miR-34a was more extensively studied in dental medicine in connection to periodontal disease (Taheri et al. 2022). Consequently, miR-34a showed highly increased levels in the gingival crevicular fluid (GCF) of patients with chronic periodontal disease. Also, the study by Meng et al. (2022) presented data on miR-34a as a repressor of cyclic stretch-induced osteogenic differentiation. A study on miRNA expression in healthy and periodontitis tissues revealed a 4-fold increase of miR-34c (Lee et al. 2011). miR-34a was a tumor suppressor miRNA investigated in multiple malignancies and presented as a therapeutic target (Li et al. 2021). The respective transcript was noticed to be associated with the activation of inflammatory pathways (Taheri et al. 2022). In periodontitis, miR-34a was upregulated in both affected gingival tissue and circulating inflammatory lymphocytes (Luan et al. 2018). It was also associated with several processes involved in bone remodeling, such as osteoblast proliferation, differentiation, mineralization, and osteoclast activity in bone remodeling (Luan et al. 2018). Therefore, periodontitis could activate inflammation and trigger bone remodeling processes that altered tooth roots and integrity. miRNA-155 was the most reliable predictor of periodontitis among nondiabetics, revealing a high accuracy as a salivary biomarker considering its AUC value of 0.82 (Al-Rawi et al. 2020). One study revealed a high specificity and sensitivity of miR-155 in diagnosing periodontitis (AUC = 0.887) (Wu et al. 2021). Another study revealed miR-155 to be overexpressed in patients with chronic periodontitis versus healthy control, regulating the expression of proinflammatory cytokines in periodontal tissues (Mogharehabed et al. 2022). miR-155 was proved to play a fundamental part in apical periodontitis progression by directly inhibiting semaphorin-3A, a key angiogenic gene (Yue et al. 2016). Increased expression of miR-155 was observed in periodontitis patients. The respective miRNA had a role in immune responses and inflammation by targeting genes involved in proinflammatory pathways, including the NF-κB pathway. Dysregulation of miR-155 may have contributed to the excessive production of inflammatory mediators in periodontitis.

The study of the interactions and regulatory networks involving the investigated miRNAs in periodontitis could provide deeper understanding of the underlying molecular mechanisms of the disease and potential therapeutic targets. According to the heatmap analysis performed in our study (Fig. 4), both miR-192-5p and miR-181a-5p were overexpressed in the lysine degradation pathway, shown to be a promoter of periodontitis (Yongqing et al. 2011). Additionally, we found miR-181a-5p upregulated in protein processing in the endoplasmic reticulum pathway. Overactivation of endoplasmic reticulum processing was a known factor associated with chronic inflammation in the progression of periodontal disease (Jiang et al. 2022).

As they were shown to be predictive of bone resorption, the study of miRNAs in patients with a history of periodontitis could become an essential tool in fields like implantology as well; they could turn out to be biomarkers found in the peri-implant crevicular fluid (Delucchi et al. 2023; Menini et al. 2021) for early diagnosis of peri-implant diseases (Asa’ad et al. 2020; Kebschull et al. 2023).

The main limitation of our study was the involvement of a relatively small sample of 50 subjects (17 with periodontal disease and 33 healthy controls). A more extensive and diverse sample could provide a more comprehensive understanding of miRNA expression patterns in different populations. Therefore, further research would be necessary to unravel the precise mechanisms of action of the respective miRNAs and explore their potential as therapeutic targets in periodontal disease management.

Conclusions

miRNAs have been intensively studied in the past decade for their role as critical regulators of the primary cellular metabolic processes and their wide tissue distribution and stability, which have made them attractive biomarker candidates. Our study evaluated a panel of 5 miRNAs with roles in inflammation regulation that showed a difference in expression between normal and periodontitis tissue. Our current research demonstrated that miR-29b-3p, miR-34a-5p, miR-155-5p, miR-181a-5p, and miR-192 were upregulated in periodontitis patients as compared to healthy controls, suggesting their involvement in the pathogenesis of the disease. The panel could serve as a potential biomarker for the early detection and monitoring of periodontitis, enabling timely interventions and improved treatment outcomes.

In general, the present study contributed to the growing body of evidence supporting the role of miRNAs as potential biomarkers for periodontal disease and highlighted the importance of molecular profiling in improving our understanding and management of this common oral health condition.

Table.

Patients Included in the Study.

Patient Identification Number Gingival Tissue Sample (GTS) Gender Female/Male (F/M) Age Interval, y Site Collection Sample Control Group Periodontitis Disease
1. GTS 1 F 41–50 Mandible Yes
2. GTS 2 M 31–40 Maxilla Yes
3. GTS 4 M 20–30 Maxilla Yes
4. GTS 5 F 31–40 Mandible Yes
5. GTS 6 F 41–50 Maxilla Yes
6. GTS 8 M 31–40 Maxilla Yes
7. GTS 9 M 61–70 Maxilla Yes
8. GTS 10 F 31–40 Maxilla Yes
9. GTS 11 F 31–40 Maxilla Yes
10. GTS 12 M 41–50 Maxilla Yes
11. GTS 14 M 31–40 Mandible Yes
14. GTS 18 M 51–60 Mandible Yes
15. GTS 21 F 31–40 Mandible Yes
17. GTS 25 M 31–40 Maxilla Yes
18. GTS 26 M 31–40 Maxilla Yes
19. GTS 27 M 51–60 Maxilla Yes
20. GTS 28 M 31–40 Maxilla Yes
21. GTS 29 F 20–30 Maxilla Yes
23. GTS 31 F 71–80 Mandible Yes
24. GTS 34 F 41–50 Maxilla Yes
25. GTS 32 F 31–40 Maxilla Yes
26. GTS 33 F 41–50 Maxilla Yes
27. GTS 35 F 41–50 Maxilla Yes
28. GTS 37 M 51–60 Maxilla Yes
29. GTS 38 F 51–60 Mandible Yes
30. GTS 40 M 61–70 Maxilla Yes
31. GTS 41 F 61–70 Maxilla Yes
32. GTS 42 M 61–70 Maxilla Yes
33. GTS 43 F 41–50 Maxilla Yes
36. GTS 46 F 61–70 Maxilla Yes
37. GTS 47 F 31–40 Mandible Yes
39. GTS 49 F 51–60 Maxilla Yes
40. GTS 50 F 41–50 Maxilla Yes
41. GTS 51/GTS 52 M 31–40 Maxilla Yes
42. GTS 53 F 51–60 Maxilla Yes
43. GTS 54/GTS 55 M 31–40 Mandible Yes
44. GTS 56 M 31–40 Maxilla Yes
45. GTS 57 M 51–60 Maxilla Yes
47. GTS 59 M 31–40 Mandible Yes
48. GTS 60/GTS 61 M 31–40 Mandible Yes
49. GTS 62 M 31–40 Maxilla Yes
50. GTS 63 F 51–60 Mandible Yes
51. GTS 64 F 51–60 Mandible Yes
52. GTS 65 M 41–50 Mandible Yes
53. GTS 66 F 51–60 Maxilla Yes
54. GTS 67 M 41–50 Mandible Yes
55. GTS 68/GTS 69 F 41–50 Mandible Yes
56. GTS 70 F 41–50 Maxilla Yes
57. GTS 71/GTS 72 F 31–40 Mandible Yes
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Author Contributions

O. Baru, conception and study design, data interpretation, drafted the manuscript; L. Pop, conception and study design, experimental analysis, drafted the manuscript; L. Raduly, C. Bica, experimental analysis, drafted the manuscript; N. Mehterov, data interpretation, drafted the manuscript; R. Pirlog, S. Buduru, data interpretation, critically revised the manuscript; C. Braicu, I. Berindan-Neagoe, M. Badea, conception and study design, data interpretation, critically revised the manuscript. All authors have their final approval and agree to be accountable for all aspects of work.

Supplemental Material

sj-docx-1-jct-10.1177_23800844241252395 – Supplemental material for The Evaluation of a 5-miRNA Panel in Patients with Periodontitis Disease
sj-docx-1-jct-10.1177_23800844241252395.docx (16KB, docx)

Supplemental material, sj-docx-1-jct-10.1177_23800844241252395 for The Evaluation of a 5-miRNA Panel in Patients with Periodontitis Disease by O. Baru, L. Pop, L. Raduly, C. Bica, N. Mehterov, R. Pirlog, S. Buduru, C. Braicu, I. Berindan-Neagoe and M. Badea in JDR Clinical & Translational Research

Footnotes

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: O. Baru has received an internal grant from the host institution.

A supplemental appendix to this article is available online.

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Supplementary Materials

sj-docx-1-jct-10.1177_23800844241252395 – Supplemental material for The Evaluation of a 5-miRNA Panel in Patients with Periodontitis Disease
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Supplemental material, sj-docx-1-jct-10.1177_23800844241252395 for The Evaluation of a 5-miRNA Panel in Patients with Periodontitis Disease by O. Baru, L. Pop, L. Raduly, C. Bica, N. Mehterov, R. Pirlog, S. Buduru, C. Braicu, I. Berindan-Neagoe and M. Badea in JDR Clinical & Translational Research

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