Introduction
In recent times, noncoding RNAs have received increasing interest for their potential role in the molecular pathways of orthodontic tooth movement. This study was designed to evaluate microRNA (miRNA)181a, 181b, 181c, and 181d as potential biomarkers by measuring their expression in gingival crevicular fluid (GCF) during different phases of tooth movement.
Methods
GCF was collected from patients undergoing fixed appliance treatment at 4 time points: T0: Baseline (pretreatment), T1: 24 hours after force application (initial phase), T2: 7-14 days after force application (lag phase), and T3: 14-21 days after force application (log phase). Total RNA was isolated using the Qiagen miRNeasy kit (Qiagen, Hilden, Germany), quantified using NanoDrop (NanoDrop, Wilmington, Del), and converted to complementary DNA using the miScript Reverse Transcription kit (Qiagen). Quantitative real-time polymerase chain reaction was performed to assess the expression of miRNA-181a, 181b, 181c, and 181d. Statistical analyses included the Shapiro-Wilk test, the Friedman test, and Dunn’s multiple comparison test.
Results
All 4 miRNA-181 subtypes were expressed at baseline (T0) in GCF. After orthodontic force application, their expression progressively increased in subsequent phases. MiRNA-181b showed a significant rise at T1 ( P = 0.013), and miRNA-181a showed a significant increase at T2 ( P = 0.035). By T3, all 4 subtypes showed significantly increased expression compared with T0 ( P <0.0001).
Conclusions
All 4 miRNAs were expressed throughout the study period from T0-T3 with progressive increase in expression from T0-T3. However, at each given time point (T0, T1, T2, and T3), there was no statistically significant difference among the subtypes. This study provides evidence that miRNA-181 subtypes function as potential biomarkers of orthodontic tooth movement.
Highlights
-
•
This is the first prospective cohort study to evaluate microRNA (miRNA)-181a, 181b, 181c, and 181d expression in GCF during orthodontic tooth movement.
-
•
All 4 miRNA-181 subtypes were detected at baseline and showed progressive increase in different phases of tooth movement (T0-T3), indicating their potential as biomarkers for bone remodelling.
-
•
No significant difference in expression was observed among the 4 miRNA subtypes at individual timepoints.
-
•
These findings support the role of miRNA-181 family in osteogenic and osteoclastic activity during orthodontic force application.
Orthodontic tooth movement (OTM) is the process where mechanical forces are exerted on the teeth, resulting in alterations to the surrounding periodontal ligament and alveolar bone. This transformation is crucial for the repositioning of teeth, but its success is heavily dependent on the biological processes that lead to bone remodeling. Bone remodeling, in turn, is regulated by a complex interaction between bone formation and resorption. The balance between these processes is essential not only for proper tooth alignment but also for minimizing complications, enhancing treatment predictability, and reducing the time required for orthodontic treatment. ,
When mechanical forces are applied to teeth, they trigger a cascade of molecular signaling events, and these forces create distinct biological responses on the pressure and tension sides of the tooth through various pathways and cell types. , Key signaling molecules are activated and contribute to bone remodeling. Tooth movement occurs in biologically distinct phases—initial, lag, and postlag—each characterized by specific remodeling events in the periodontal ligament and alveolar bone. Receptor activator of nuclear factor kappa-B ligand, expressed by osteoblasts and periodontal ligament cells, promotes osteoclast differentiation and activation, leading to bone resorption on the pressure side. Osteoprotegerin acts as a receptor for receptor activator of nuclear factor kappa-B ligand, inhibiting osteoclastogenesis and favoring bone formation. In addition, mechanical stress activates intracellular pathways such as mitogen-activated protein kinase, Wnt/β-catenin, and transforming growth factor—beta (TGF-β)/Smad, which regulate gene expression involved in osteoblast proliferation and differentiation on the tension side. These interconnected signaling networks ensure coordinated bone resorption and formation, allowing controlled tooth movement while maintaining tissue integrity. , In recent times, noncoding RNAs (ncRNAs) have received increasing interest for their potential role in the molecular pathways. MicroRNAs (miRNAs) are small, ncRNA molecules that function as posttranscriptional regulators of gene expression, making them key players in various biological functions, including inflammation, immune response, cellular stress, and tissue repair. , Over the past decade, several studies have examined the role of miRNAs in regulating OTM, with particular focus on their influence on bone remodeling, inflammation, and cellular processes differentiation.
Key miRNAs, such as 21, 29 family (a, b, and c), 101, 146 a and b, 214, have been widely explored for their dynamic expression patterns in response to orthodontic forces. These miRNAs have been detected in gingival crevicular fluid (GCF) and are shown to modulate critical pathways involved in osteoclastogenesis, osteoblastogenesis, and the inflammatory response. For instance, miRNA-21 has been implicated in promoting osteoclast differentiation, whereas miRNA-29 is known to regulate extracellular matrix remodeling and osteoblast activity. ,
miRNA-181 subtypes have gained considerable attention because of their involvement in multiple biological processes in bone remodeling. , These are believed to influence TGF-β signaling, a pathway that regulates osteoblast differentiation and bone formation and suppresses TGF-βI (TGF-β-induced) and TGF-βRI (TGF–receptor induced), negative regulators of osteoblast differentiation, thereby promoting bone formation during tooth movement. , Although studies in other fields have suggested their involvement in bone metabolism ,, and immune regulation, their specific role in orthodontic-induced bone remodeling has not been studied. This study seeks to address that gap by focusing on the expression and potential regulatory functions of miRNA-181 subtypes during OTM, aiming to contribute novel insights that could refine biological understanding and therapeutic strategies in orthodontics.
Secretory miRNAs can be found in body fluids, including oral fluids, such as saliva and GCF. , They are typically detected in exosomes, which are small vesicles that carry nucleic acids and proteins. GCF and saliva are considered convenient sources for identifying miRNA biomarkers in orthodontic treatment. Together, these miRNAs form a complex network that controls the cellular processes necessary for efficient tooth movement. ,, The potential applications of miRNA-based research in orthodontics are vast, with several significant implications for improving treatment outcomes. ,, By understanding the molecular mechanisms underlying bone remodeling during orthodontic treatment, orthodontists could predict tooth movement with greater accuracy. This could lead to better treatment planning and more efficient orthodontic care, with reduced treatment durations and fewer complications.
Hence, the aim of this study was to evaluate and compare the levels of miRNA-181a, 181b, 181c, and 181d in GCF at baseline (pretreatment), 24 hours, 7-14 days, and 14-21 days after orthodontic force application.
Material and methods
This study was conducted as a prospective cohort study, and ethical approval was secured to ensure compliance with confidentiality standards. The inclusion criteria is as described: (1) adolescent patients with permanent dentition who were to undergo fixed orthodontic treatment with the Mclaughlin Bennett Trevisi appliance, and (2) no history of recent periodontal disease or oral infections. The exclusion criteria is as described: (1) use of medications that could interfere with bone metabolism (eg, bisphosphonates and steroids), and (2) any history of previous orthodontic treatment.
The determination of sample size followed the methodology outlined by Chen et al (2016). Statistical parameters included a 95% confidence interval, 80% power, and a confidence width of 0.0992. With an assumed standard deviation of 0.25 and a desired precision width of 0.8000, the final required sample size for meaningful statistical analysis was found to be 22. Thus, 22 patients who were to receive fixed orthodontic treatment were recruited for this study. Patients who received nonextraction treatment were included in this study.
MINI DIAMOND (Ormco, Orange, Calif) 0.022-in slot and ORMCO brackets were bonded with lacebacks in all quadrants. Active force was applied using lacebacks to canine teeth, and the initial arch wire placed was 0.014-in nickel-titanium wire. Force was measured and standardized using a dontrix gauge.
GCF was collected using a micropipette at the following time points: T0: Before appliance placement, T1: Within 24 hours of appliance placement, T2: Between 7-14 days, and T3: After 14-21 days. Samples were stored in phosphate-buffered solution, free of RNAase and DNAase, at–80°C until analysis. miRNA analysis was done using the following reagents, chemicals, and kits: miRNeasy kit (Qiagen, Hilden, Germany), 2X SYBR green master mix (Thermofisher Scientific), and polymerase chain reaction (PCR) grade water (Qiagen, Germany). Total RNA, including all miRNA species, was extracted from each GCF sample using the miRNeasy Kit following the protocol. This ensured the preservation of RNA molecules essential for downstream quantitative analysis.
The quality and concentration of the extracted RNA was evaluated using the NanoDrop 2000; Spectrophotometer (NanoDrop, Wilmington, Del). The concentration was determined by measuring absorbance at 260 nm (A260). Purity was assessed (A260:A280 ratio), with optimal values around 2.0, indicating that the RNA is suitable for molecular biology.
High-quality RNA samples were reverse-transcribed into complementary DNA using the miScript Reverse Transcription kit (Qiagen). This step is essential for detecting mature miRNA expression through real-time PCR (RT-PCR).
RT-PCR assays were employed to detect the expression levels of miRNA-181a, 181b, 181c, and 181d in the given sample. The PCR reaction mixture was created by combining the necessary components in a PCR tube ( Table I ).
Table I
Real-time PCR temperature and time settings
| Setup | Temperature | Time |
|---|---|---|
| Initial denaturation | 95°C | 3 min |
| Denaturation | 95°C | 15 s |
| Annealing | 60°C | 30 s |
| Extension | 72°C | 15 s |
min , minutes; s , seconds.
Reagents, including 2X SYBR green master mix, contained thermostable polymerase, buffers, dNTPs, and miRNA-specific primers, and were dispensed into PCR tubes. Next, nucleic acid was added to the respective PCR tubes, which were then tightly capped and transferred to the RT-PCR instrument for amplification.
In each round of thermal cycling, the amplification products were separated into single strands at elevated temperatures, which facilitated primer binding and extension as the temperature decreased. The use of SYBR green dye allowed for clear observation of the amplification process because it attached to double-stranded DNA, producing fluorescence. Exponential amplification of the product occurred through repeated cycles of high and low temperatures, leading to an amplification of target sequences by a billion-fold or more. The amplification of all targets (miRNA-181a, 181b, 181c, 181d, and U6) occurred simultaneously in distinct reactions.
During the read cycles of RT-PCR, the miRNA-181a, 181b, 181c, 181d, and internal control primers bound to their target sequences. When these target sequences were absent, fluorescence amplification was not observed. The use of 2X SYBR green master mix may lead to the formation of primer dimers, resulting in low cycle threshold values. However, in the presence of miRNA-181 subtypes or internal control target sequences, primer binding to complementary sequences enabled fluorescent emission and subsequent detection. The emitted fluorescence was captured and converted into a cycle threshold value, allowing for quantitative analysis of the target sequences.
Statistical analysis
All analyses were performed using SPSS (version 23; IBM, Armonk, NY) and R (version 4.2.2; R Foundation for Statistical Computing, Vienna, Austria). Data normality was assessed using the Shapiro-Wilk test, which indicated that most variables were not normally distributed. Therefore, nonparametric methods were used. The Friedman test was applied to evaluate differences in miRNA expression across 4 timepoints (T0, T1, T2, and T3). Dunn’s multiple comparison test was used for post-hoc pairwise test comparisons. Continuous variables are presented as mean ± standard deviation or median (interquartile range), as appropriate. A P -value of <0.05 was considered statistically significant.
Results
Assessment of expression levels of miRNAs (miRNA-181a, 181b, 181c, 181d) across different time points (T0, T1, T2, and T3) demonstrated normal distribution as evident by Shapiro-Wilk test ( Table II ).
Table II
Tests of normality
| Timepoints | miRNA | Kolmogorov-Smirnov | Shapiro-Wilk test | ||||
|---|---|---|---|---|---|---|---|
| Statistic | df | Sig | Statistic | df | Sig | ||
| T0 | miRNA-181b_T0 | 0.211 | 22 | 0.01 | 0.85 | 22 | 0.004 |
| miRNA-181c_T0 | 0.188 | 22 | 0.041 | 0.86 | 22 | 0.006 | |
| miRNA-181d_T0 | 0.151 | 22 | 0.200 ∗ | 0.95 | 22 | 0.385 | |
| T1 | miRNA-181a_T1 | 0.171 | 22 | 0.095 | 0.90 | 22 | 0.032 |
| miRNA-181b_T1 | 0.184 | 22 | 0.051 | 0.87 | 22 | 0.011 | |
| miRNA-181c_T1 | 0.189 | 22 | 0.040 | 0.88 | 22 | 0.011 | |
| miRNA-181d_T1 | 0.189 | 22 | 0.039 | 0.92 | 22 | 0.065 | |
| T2 | miRNA-181a_T2 | 0.210 | 22 | 0.013 | 0.76 | 22 | 0.000 |
| miRNA-181b_T2 | 0.223 | 22 | 0.006 | 0.74 | 22 | 0.000 | |
| miRNA-181c_T2 | 0.181 | 22 | 0.060 | 0.89 | 22 | 0.022 | |
| miRNA-181d_T2 | 0.102 | 22 | 0.200 ∗ | 0.97 | 22 | 0.612 | |
| T3 | miRNA-181a_T3 | 0.357 | 22 | 0.000 | 0.55 | 22 | 0.000 |
| miRNA-181b_T3 | 0.240 | 22 | 0.002 | 0.76 | 22 | 0.000 | |
| miRNA-181c_T3 | 0.231 | 22 | 0.004 | 0.85 | 22 | 0.004 | |
| miRNA-181d_T3 | 0.101 | 22 | 0.200∗ | 0.95 | 22 | 0.301 | |
Note. miRNA-181a_T0 is constant, and therefore has been omitted.
df , degree of freedom.
Therefore, nonparametric statistical method Friedman test was considered for further analysis.
The value of miRNA-181a at T0 was fixed at 1.00, and all other time points were measured relative to this baseline ( Table III ). Although the overall increase of miRNA-181a between T0-T3 was highly significant ( P <0.0001), there was no significant change between the other time intervals except between T1-T2 ( P = 0.035) ( Fig 1 ; Table IV ).
Table III
Descriptive statistics
| miRNA | Timepoint | N | Mean | SD | Minimum | Maximum |
|---|---|---|---|---|---|---|
| miRNA-181a | T0 | 22 | 1.00 | 0.00 | 1.00 | 1.00 |
| T1 | 22 | 0.91 | 0.46 | 0.15 | 2.33 | |
| T2 | 22 | 0.90 | 0.55 | 0.25 | 2.95 | |
| T3 | 22 | 1.09 | 1.08 | 0.21 | 5.50 | |
| miRNA-181b | T0 | 22 | 2.20 | 1.73 | 0.46 | 7.31 |
| T1 | 22 | 2.46 | 1.69 | 0.41 | 6.73 | |
| T2 | 22 | 2.18 | 1.90 | 0.36 | 8.00 | |
| T3 | 22 | 2.25 | 2.05 | 0.32 | 8.06 | |
| miRNA-181c | T0 | 22 | 3.91 | 2.41 | 1.29 | 10.37 |
| T1 | 22 | 4.25 | 2.54 | 1.23 | 10.93 | |
| T2 | 22 | 4.01 | 2.50 | 1.05 | 9.92 | |
| T3 | 22 | 3.78 | 2.47 | 1.10 | 9.78 | |
| miRNA-181d | T0 | 22 | 6.74 | 2.34 | 3.04 | 11.08 |
| T1 | 22 | 7.07 | 3.58 | 2.35 | 16.56 | |
| T2 | 22 | 6.58 | 2.91 | 1.57 | 13.00 | |
| T3 | 22 | 7.39 | 3.52 | 2.38 | 14.50 |
Stay updated, free articles. Join our Telegram channel
Full access? Get Clinical Tree
