Background
Tooth movement speed in patients receiving conventional orthodontic treatment is normally 0.8 ~ 1.2 mm per month and the period of comprehensive orthodontic treatment is usually 12 ~ 36 months. Orthodontic treatment period is related to the type and severity of malocclusion, the selection of treatment design and technique, the experience of orthodontists and the compliance of patient. Shortening the orthodontic treatment is of great clinical significance [1].
Periodontally accelerated osteogenic orthodontics (PAOO) proposed by Wilcko in 2001 is a clinical procedure that combines selective alveolar corticotomy, particulate bone grafting, and orthodontic forces. PAOO could result in less cortical resistance during tooth movement, shorter treatment time, increased post-treatment stability, and decreased apical root resorption [2]. Clinical studies have confirmed that the PAOO efficiently accelerates orthodontic movement. However, the internal mechanism remains unclear and further studies are needed [3, 4]. In order to clarify the mechanism of accelerated tooth movement, many scholars have conducted a series of studies and proposed hypotheses. Wilcko et al. believed that PAOO is theoretically based on the bone healing pattern known as the Regional Acceleratory Phenomenon (RAP) that induces the healing of alveolar bone after local trauma [5, 6]. It is believed that corticotomy, an intentional surgical injury to the bone, started a cascade of physiologic events, stimulating osteoclast activity and leading to increased bone turnover with concomitant demineralization and new bone formation at the site of the bone injury [3]. The RAP comprises an acute inflammatory phase and intense osteoclastic and decreased osteoblastic bone formation, which manifests as transient local osteopenia. Lee et al. found the alveolar bone mineral density in the corticotomy site decreased in rats with Micro-CT detection, thus confirming the presence of RAP [7].
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Although previous studies have confirmed the uniqueness of bone metabolism in accelerated teeth movement, the specific cellular mechanism such as the signaling pathway of PAOO has not been elucidated. At present, most of the fundamental researches on PAOO concentrate on animal experiments or in vitro experiments, while there are few reports on the mechanism of PAOO in human [8, 9]. Therefore, this study aims to explore the internal mechanism of accelerated tooth movement via PAOO through label-free quantitative proteomic assay and bioinformatics analysis of gingival crevicular fluid, so as to investigate the inherent biological laws of accelerated tooth movement in the human body.
Materials and methods
This study is a prospective cohort study. PKUSSIRB-202,054,018 (09/03/2020) was reviewed and approved by the Biomedical Ethics Committee of Peking University Hospital of Stomatology. This study was registered in the Chinese Clinical Trial Registry (Clinical trial registration number: ChiCTR-ONRC-13,004,129) (26/04/2013). The study was conducted in full accordance with Declaration of Helsinki.
Participants
The inclusion criteria for all patients were as follows: (1) 18 to 40 years of age; (2) Class III relationships, ANB < − 4° or Wits < − 6 mm; (3) With combined surgical and orthodontic treatment; (4) Bilateral extraction of maxillary first premolars and erupted third molars; (5) Mild crowding in the maxillary arch (≤ 4 mm) and (6) Without severe or progressive periodontitis and with a probing depth of less than 4 mm.
The exclusion criteria were as follows: (1) Patients with active periodontal disease; (2) Patients with additional teeth loss except tooth extraction for orthodontic treatment; (3) Patients with congenital cleft lip and palate; (4) Patients with acute inflammation in the oral and maxillofacial region; (5) Patients with tumor or systemic severe diseases and (6) Pregnant and lactating patients.
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Gingival crevicular fluid (GCF) collection and processing
Ten adult orthodontic patients were selected in this study. After orthodontic alignment and leveling, the maxillary anterior teeth were treated with periodontally accelerated osteogenic orthodontics (PAOO), which is classified as the experimental area, while traditional orthodontic treatment performed for mandibular dentition, is classified as the control area.
The collection, storage, and processing of all samples were conducted according to a standardized protocol. EP tubes with 35# standard paper points were weighed by the electronic balance (Hundred thousandth). Absorbent paper points were used to collect GCF by inserting the paper points into the mesial and distal buccal gingival sulcus of maxillary anterior teeth (Stop for 30s when mild resistance was detected). The selected site of experimental group is from left upper canine to right upper one, while the selected site of the control group is from left lower canine to right lower one. EP tubes with 35# paper points were weighed again after collection of GCF and then stored at − 80℃ until the time of assay. Gingival crevicular fluid (GCF) was collected at six time points:
T1: the day before the PAOO; the day after orthodontic alignment and leveling.
T2: 1 week after the PAOO; the day postoperative review was scheduled.
T3: 2 weeks after the PAOO; the day of first application of orthodontic force after PAOO.
T4: 1 month after the PAOO; the day of second application of orthodontic force after PAOO.
T5: 2 months after the PAOO;
T6: 6 months after the PAOO.
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The protein differences in gingival crevicular fluid between PAOO and the control areas of the same patient were compared. The bone metabolism related proteins in gingival crevicular fluid in the PAOO accelerated tooth movement were selected.
Label-free quantitative proteomic screening
Extraction and enzymolysis of proteins
The microTOF-Q II mass spectrometry was used to evaluate the gingival crevicular fluid in PAOO area and the control area at time points T1, T2, and T4 in the 10 PAOO patients. Briefly, all test paper samples were transferred to a 1.5-mL screw capped tube and the 100 µL of lysis buffer (7 M urea, 2 M thiourea) were added into each sample and then ultrasonication was performed to extract total proteins. Proteins were precipitated with trichloroacetic acid (TCA) for 30 min on ice and centrifuged at 40,000×g for 30 min. Protein concentration was determined using the Qubit fluorescent protein quantification kit (Invitrogen) according to the manufacturer’s instructions.
Following the addition of 100 mmol/L DTT(DL-Dithiothreitol) to a final concentration of 10 mmol/L, the protein fractions were mixed at 56℃ for 60 min, and then diluted 10x with 250 mmol/L IAM(Iodoacetamide) and maintained in dark for 60 min. Finally, the samples were digested with trypsin (substrate to enzyme mass at a mass ratio of 50:1 at 37℃ for 12 h [10].
LC-MS/MS analysis
Peptides were acidified with formic acid (FA) (10%, v/v) and desalted byre-versed phase extraction using C18 ZipTip pipette tips and re-suspended in 0.1% FA for high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analysis. Pressure was applied to a fused silica capillary column packed with 3-µm dionex C18 material (RP; Phenomenex) to load digested peptide combinations. The RP sections with 100Å were each 15 cm long, and the column was washed with buffer A (water, 0.1% formic acid) and buffer B (Acetonitrile, 0.1% formic acid). After desalting, a 5-mm, 300-µm C18 capture tip was placed in line with an Agilent 1100 quaternary HPLC(High Performance Liquid Chromatography) and analyzed using a 12-step separation.
Firstly, a 45-min gradient to 40% buffer B was applied after a 5-min gradient from 0 to 2% buffer B. The buffer B then flowed by a gradient of 40–80% for 3 min and then 80% for 10 min. An approximately 100 µg tryptic peptide mixture was loaded onto the columns after a 2-min buffer B gradient from 80 to 2%, and it was separated using a linear gradient at a flow rate of 0.5 µL/min. After full scanning, 10 debris maps (MS2 scan, HCD) were collected. MS1 has a resolution of 70,000 at M/Z 200, while MS2 has a resolution of 17,500 at M/Z 200. Peptides were electrosprayed into a micrOTOF-Q II mass spectrometer (BRUKER Scientific) with the application of a distal 180 °C source temperature as they were eluted from the micro-capillary column. The mass spectrometer was operated in the MS/MS (auto) mode. Survey MS scans were acquired in the TOF-Q II with the resolution set to a value of 20,000. Each survey scan (50 ~ 2,500) was followed by five data-dependent tandem mass (MS/MS) scans at 2HZ normalized scan speed [11]. The following were the main parameters: 6 for the main search ppm, 2 for the missed cleavage, 20 for the MS/MS tolerance ppm, True set as de-isotopic, trypsin as digestion enzyme, carbamidomethyl as the fixed modification, Oxidation (M) and Acetyl (Protein N-term) as the variable modification.
Bioinformatics analysis
Tandem mass spectra were searched against mascot 2.1 (Local Host) human protein database(refseq_human_20140103.fasta). The search results were then filtered using a cutoff of 1% for peptide false identification rate. Peptides with Z score < 4 or Delta-Mass > 5 ppm were rejected. Furthermore, the minimum number of peptides to identify a protein was set to 1. Throughout the analysis, the default parameters for the Quantitative software Profile Analysis 2.0 software were applied.
Bioinformatics analysis was performed to categorize proteins based on biological processes, cellular component and molecular function using annotations in Protein Analysis Through Evolutionary Relationships (PANTHER) database v 6.1 (www.pantherdb.org), which is in compliance with gene ontology (GO) standards. Signaling pathway analysis were performed with the aid of tools on the Kyoto Encyclopedia of Genes and Genome (KEGG) database (http://www.genome.jp/kegg/pathway.html) independently [11‐14].
Validation by ELISA
ELISA was performed to confirm expression changes of the differentially expressed proteins. Five proteins selected by label-free quantitative proteomics were KLF10, SYT7, APOA1, FBN1 and NOTCH1. Human Krueppel-like factor 10 (KLF10) ELISA Kit (Jiangsu Jingmei Biotechnology Co., Ltd.; the detection limit was 10.0 pg/mL), Human Synaptotagmin 7(SYT7) ELISA Kit (Jiangsu Jingmei Biotechnology Co., Ltd. China; the detection limit was 10 pg/ml), Human apoprotein A1 (APOA1) ELISA Kit (Jiangsu Jingmei Biotechnology Co., Ltd. China; the detection limit was 0.1 µg/mL); Human Fibrillin-1 (FBN1) ELISA Kit (Jiangsu Jingmei Biotechnology Co., Ltd. China; the detection limit was 1.0 pg/mL) and Human NOTCH1 ELISA Kit (Jiangsu Jingmei Biotechnology Co., Ltd. China; the detection limit was 1.0 pg/mL) were used according to the manufacturers’ instructions to measure the concentrations of gingival crevicular fluid proteins in different groups.
Statistical analysis
Statistical analysis of omics data
Fold-change (FC) was calculated by the mean of each group. Selection criteria of different expressed proteins were set as follows: |log(FC)|>0.58.
The intensity data of these regions were used for GraphPad analysis. The biological process was analyzed with Gene Ontology database (http://geneontology.org/). Signaling pathway analysis was performed using the Kyoto Encyclopedia of Genes and Genome (KEGG) database (www.genome.jp/kegg/pathway.html).
Statistical analysis of ELISA
The ELISA results were statistically analyzed with RStudio. Paired sample Wilcoxon sign test was used to test these five factors (KLF10, SYT7, APOA1, FBN1, NOTCH1) in the maxillary PAOO area and mandibular control area at six time points. Wilcoxon sign test was used to analyze the trend of five factors related to bone metabolism in gingival crevicular fluid over time with pairwise comparative analysis performed at the same time.
Result
Label-free quantitative proteomic analysis
The microTOF-Q II mass spectrometry was used to detect the gingival crevicular fluid of PAOO area and the control area at T1, T2 and T4 in these 10 patients. The detected differential proteins are shown in Table 1.
Table 1
The number of differentially expressed proteins in the gingival crevicular fluid (GCF) of PAOO area and the control area at time points T1, T2 and T4
Group | Number of up-regulated differential proteins(>2) | Number of down-regulated differential proteins(≤ 0.5) | ||
|---|---|---|---|---|
PAOO area T1 vs. T2 vs. T4 | T1/T2 | T1/T4 | T1/T2 | T1/T4 |
76 | 45 | 80 | 71 | |
The control area T1 vs. T2 vs. T4 | T1/T2 | T1/T4 | T1/T2 | T1/T4 |
55 | 39 | 61 | 63 | |
Whole T1 vs. T2 vs. T4 | T1/T2 | T1/T4 | T1/T2 | T1/T4 |
127 | 70 | 120 | 104 | |
The total number of proteins identified were 2337. 134 proteins were selected by keywords (Osteoblast markers, Osteoclast markers, Osteoclastogenesis regulating genes and inflammatory marker). 33 of them were statistically different between groups, and 12 were related to bone metabolism (Table 2).
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Table 2
Twelve proteins related to bone metabolism
Gene | GI number | Protein | Median (T1up: T4up) | Median (T2up: T1up) | Median (T4down: T1down) | Median (T2down: T1down) | Median (T2:T1) | Median (T4:T1) |
|---|---|---|---|---|---|---|---|---|
APOA1 | 4,557,321 | apolipoprotein A-I preproprotein | 1.32 | 1.01 | 1.63 | 0.86 | 0.83 | 0.91 |
FBN1 | 281,485,550 | fibrillin-1 precursor | 0 | 0 | 0.87 | 0.57 | 0.43 | 0.41 |
FBN2 | 66,346,695 | fibrillin-2 precursor | 1.09 | 1.03 | 1.53 | 3.53 | 1.75 | 0.96 |
C3 | 115,298,678 | complement C3 precursor | 0 | 0 | 0 | 0 | 0.43 | 0.57 |
TRAF6 | 4,759,254 | TNF receptor-associated factor 6 | 0 | 0 | 0.51 | 0 | ||
NOTCH1 | 148,833,508 | neurogenic locus notch homolog protein 1 preproprotein | 2.27 | 0.88 | 0 | 0 | 0.72 | 0.57 |
ABCA3 | 116,734,710 | ATP-binding cassette sub-family A member 3 | 0.87 | 1.16 | 2.08 | 1 | ||
ERCC2 | 195,947,407 | TFIIH basal transcription factor complex helicase XPD subunit isoform 2 | 0 | 0 | 0.56 | 0.99 | ||
HDAC1 | 13,128,860 | histone deacetylase 1 | 0 | 0.38 | 0.69 | 1.02 | ||
KLF10 | 73,760,403 | Krueppel-like factor 10 isoform b | 0.33 | 4.55 | 1.19 | 1.08 | ||
SYT7 | 530,397,573 | PREDICTED: synaptotagmin-7 isoform X3 | 1.55 | 1.74 | 1.43 | 0 | ||
DCHS1 | 16,933,557 | protocadherin-16 precursor | 1.69 | 0 |
Statistical analysis of ELISA results
KLF10
KLF10 decreased after PAOO, hitting a trough at 1 month after PAOO (T4), and then leveled off. A statistically significant difference was found between preoperative (T1) results and postoperative (T2 ~ T6) results (P<0.05). Statistical differences between other groups are shown in Fig. 1a. The ELISA results showed that there was a significant difference in KLF10 between the Maxillary PAOO area and mandibular control area at 2 months after PAOO (T5) (P < 0.05), but no significant difference were found between the two areas at other time points (Table 3).
Fig. 1
Comparisons of five biomarkers in GCF from patients undergoing PAOO at six time points. The ELISA results were statistically analyzed with RStudio. Wilcoxon sign test was used to analyze the trend of five factors related to bone metabolism in gingival crevicular fluid over time with pairwise comparative analysis performed at the same time
×
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Table 3
Comparisons of five biomarkers at six time points in the PAOO and the control areas
T1 | T2 | T3 | T4 | T5 | T6 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Biomarkers | mean ± sd | p | mean ± sd | p | mean ± sd | p | mean ± sd | p | mean ± sd | p | mean ± sd | p | |
KLF10 | PAOO area | 679.7 ± 136.87 | 717.9 ± 110.26 | 599.2 ± 104.96 | 530.6 ± 130.78 | 523.8 ± 134.56 | 548.3 ± 175.78 | ||||||
Control area | 683.2 ± 132.56 | 0.786 | 711.4 ± 109.65 | 0.398 | 598.3 ± 109.88 | 0.734 | 530.6 ± 132.56 | 0.888 | 538.9 ± 133.11 | 0.028* | 553.0 ± 174.64 | 0.599 | |
SYT7 | PAOO area | 2233 ± 276.6 | 2556 ± 299.9 | 2904 ± 273.9 | 2932 ± 222.9 | 2962 ± 240.8 | 2964 ± 346.4 | ||||||
Control area | 2171 ± 247.8 | 0.068 | 2519 ± 284.9 | 0.345 | 2872 ± 357.4 | 0.446 | 2932 ± 233.9 | 1.000 | 2983 ± 275.6 | 0.248 | 2992 ± 370.8 | 0.461 | |
APOA1 | PAOO area | 4.916 ± 0.4684 | 5.693 ± 0.4203 | 6.173 ± 0.3096 | 6.380 ± 0.3315 | 6.404 ± 0.3766 | 6.381 ± 0.8202 | ||||||
Control area | 4.941 ± 0.4124 | 0.686 | 5.700 ± 0.4453 | 0.680 | 6.185 ± 0.3535 | 0.674 | 6.466 ± 0.3403 | 0.012* | 6.429 ± 0.3631 | 0.498 | 6.344 ± 0.8615 | 0.500 | |
FBN1 | PAOO area | 179.7 ± 22.81 | 202.4 ± 38.81 | 224.6 ± 29.13 | 242.1 ± 27.78 | 237.9 ± 31.30 | 231.8 ± 29.21 | ||||||
Control area | 180.0 ± 31.17 | 0.893 | 203.5 ± 41.59 | 0.612 | 220.6 ± 33.10 | 0.310 | 243.4 ± 29.18 | 0.779 | 232.9 ± 33.18 | 0.149 | 228.1 ± 31.10 | 0.249 | |
NOTCH1 | PAOO area | 294.6 ± 72.09 | 363.3 ± 50.12 | 359.4 ± 57.38 | 413.4 ± 41.21 | 424.6 ± 52.70 | 442.3 ± 54.24 | ||||||
Control area | 292.6 ± 67.77 | 1.000 | 275.1 ± 51.07 | 0.093 | 406.9 ± 49.88 | 0.249 | 400.4 ± 55.51 | 0.161 | 421.7 ± 61.75 | 0.753 | 441.1 ± 59.59 | 0.715 |
SYT7
SYT7 increased after PAOO, reaching a peak at 2 weeks after PAOO (T3), and then remained stable until 6 months after PAOO (T6). A statistically significant difference was found between preoperative (T1) results and postoperative (T2 ~ T6) results (P<0.05). Statistical differences between other groups are shown in Fig. 1b. The ELISA results showed that there were no significant difference in SYT7 between the Maxillary PAOO area and the mandibular control area (Table 3).
APOA1
The statistical analysis of macroscopic ELISA results was shown in Fig. 1. APOA1 ascended to a peak at 1 month (T4) after PAOO, and then stabilized until 6 months after PAOO (T6). A statistically significant difference was found between preoperative results (T1) and postoperative results (T2 ~ T6) (P<0.05). Statistical differences between other groups are shown in Fig. 1c. The ELISA results showed that there was a significant difference in APOA1 between the Maxillary PAOO area and the mandibular control area at one month after PAOO (T4), but no significant difference were found between the two areas at other time points (Table 3).
FBN1
FBN1 rose after PAOO, reaching a peak at 1 month after PAOO (T4), and then went down slowly. A statistically significant difference was found between preoperative results (T1) and postoperative (T2 ~ T6) results(P<0.01). Statistical differences between other groups are shown in Fig. 1d. The ELISA results showed that there was no significant difference in FBN1 between the Maxillary PAOO area and the mandibular control area (Table 3).
NOTCH1
NOTCH1 ascended rapidly in the first two weeks after PAOO and then continued its slow growth trend. A statistically significant difference was found between preoperative (T1) results and postoperative (T2 ~ T6) results (P<0.05). Statistical differences between other groups are shown in Fig. 1e. The ELISA results showed that there was no significant difference in NOTCH1 between the Maxillary PAOO area and the mandibular control area (Table 3).
Discussion
It has been documented that transient osteoporosis occurs in damaged bone tissue, and the content of calcium in bone will reduce, resulting in decreased bone mineral density in a certain area around the root. Thus, alveolar bone undergoes biological changes from osteoclastogenesis to osteogenesis, during which alveolar bone goes from mineralization to re-mineralization, providing a time window and theoretical feasibility for accelerating tooth movement [9]. Indeed, the underlying biological process of PAOO is similar to the healing of bone injury. After bone injury, macrophages and monocytes in the altered local microenvironment secrete some growth factors and cytokines. Impaired the lacunocanalicular network, including changed fluid flow, would activate intracellular molecular signaling pathways within osteocytes, actuating the secretion of mediators that could regulate bone remodeling, so as to contribute to the regional acceleration of bone remodeling (RAP). Kumar et al. analyzed ALP and AST in human saliva and crevicular fluid, and found that the enzyme activities of ALP and AST increased after corticotomy and reached a peak at the 6th week, and then decreased at the 3rd and 6th months [10]. Fernandes LSDMCP et al. have shown that GCF during the movement of canines were quantified in a multiplex immunoassay, and differences on biomarkers expression occurred at specific time points (p < 0.05), but a distinct pattern was not observed [11].
In this study, label-free quantitative proteomic assay was employed to detect changes in key proteins in gingival crevicular fluid of PAOO patients at six time points. 12 proteins related to bone metabolism with significant changes were selected. Among them, APOA1 and C3 were also reported in our previous research on the saliva of PAOO patients with the MALDI-TOF MS [15]. The peptides 3052.02 Da and 2775.33 Da detected with MALDI-TOF MS in the saliva of PAOO patients were identified as apolipoprotein A-I precursor (APOA1). APOA1 increased rapidly at one week after PAOO and then decreased. The peptides 1864.17 Da and 2027.72 Da were identified as complement 3 (C3). C3 decreased rapidly at 1 week after PAOO. Compared with our previous studies, this study detected gingival crevicular fluid in the PAOO area and the control area of the same patient separately, and mouth-split control partition was carried out. The label-free proteomics, in a certain range, is more accurate in protein analysis [16, 17].
Based on the results of mass spectrometry, ELISA was further used to verify the trend of bone metabolic factors over time. In this study, twelve bone metabolism-related proteins after PAOO were selected by label-free mass spectrometry, and then the changes of five bone metabolism-related proteins over time after PAOO were detected by ELISA.
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KLF10 is known to be vital in bone biology by regulating the expression and activity of Runx2 and Osterix (crucial osteogenic transcription factors) [18, 19]. Additionally, Jong Min Lee et al. found that primary ossification was critically delayed in KLF10 KO mice [20]. KLF10 decreased after PAOO, hitting a trough at 1 month after PAOO (T4), and then leveled off. The above results indicated that the reduction of KLF10 after PAOO weakened the osteogenesis of the PAOO area and reduced the alveolar bone mineral density in the operation area. Therefore, it reduced the resistance of orthodontic tooth movement, and accelerated tooth movement, which occurred within 1 month after PAOO. Haibo Zhao et al. [21] reported SYT7 plays a similar role in osteoblasts and osteoclasts. SYT7 performs a function in bone remodeling and homeostasis by regulating secretory pathways in osteoclasts and osteoblasts. SYT7 increased after PAOO, reaching a peak at 2 weeks after PAOO (T3), and then leveled off until 6 months after PAOO (T6). According to the above results, it could be concluded that SYT7 is a key to the balance between osteogenesis and osteoclastogenesis after PAOO.
In this study, APOA1 and FBN1 ascended, reaching a peak at 1 month after PAOO (T4), and then stabilized until 6 months after PAOO(T6). NOTCH1 increased rapidly in the first two weeks after PAOO(T3) and then continued its slow growth trend. Harry Blair et al. reported that APOA1 deficiency weakened the capacity of MSC to differentiate toward osteoblasts but promoted adipogenesis. The results confirmed that APOA1 was critical in regulating bone remodeling and maintaining bone quality [22]. Harikiran Nistala et al. reported that FBN1 could regulate bone formation by osteoblast differentiation through modulation of endogenous TGFβ and BMP signals. In vivo and in vitro experiments suggested that the fibrillin acted as a negative regulator in the bone resorption [23]. Sekine C. et al. reported that the activation of Notch1/Jag1 could inhibit osteoclast differentiation. NOTCH1 inhibits osteoclastogenesis through the RBPJ pathway and by enhancing OPG levels and Wnt signaling in osteoblasts and osteocytes [24]. It has been documented that transient osteoporosis occurs in damaged bone tissue, and the content of calcium in bone will decrease, resulting in decreased bone mineral density in a certain area around the root. Thus, the alveolar bone undergoes biological changes from osteoclastogenesis to osteogenesis, during which the alveolar bone goes from demineralization to re-mineralization, which could be viewed as a kind of reversible osteopenia, making the acceleration of tooth movement possible [3, 8]. In our study, it could be concluded that increased APOA1, FBN1 and NOTCH1 in PAOO could promote the balance between osteogenesis and osteoclastogenesis, favoring bone formation. These factors exert similar local effects on alveolar bone, which might prevent excessive decrease of alveolar bone mineral density and thus limit the decrease of bone mineral density around the tooth root to a certain range. Therefore, it is speculated that after PAOO, in addition to the increase of cytokines promoting osteoclastic effect, the antagonistic cytokines play roles. These factors negatively regulate the growth of osteoclasts to avoid excessive reduction of local alveolar bone mineral density and excessive loss of local bone tissue, which lays the foundation for the subsequent re-mineralization of alveolar bone. Baloul et al. established an orthodontic rat model of selective corticotomy and found that accelerated tooth movement occurred in the early stage after corticotomy [25]. This study also supports the findings of the previous in vivo studies that the changes of bone metabolic factors are most significant in the early postoperative period.
The ELISA results showed that no significant difference was found between the Maxillary PAOO area and the mandibular control area at time points T1-T6, except for a significant difference in APOA1 at 1 month after PAOO (T4) and in KLF10 at 2 months after PAOO (T5) (P < 0.05) between the two areas. According to a previous study, cytokine level in GCF is not differentiated by type of movement when force is applied to tooth, because GCF presents free circulation in the gingival sulcus [9, 26]. It is inferred that corticotomy affects the oral microenvironment and that gingival crevicular fluid circulates in the body; therefore, there is little difference in bone metabolic factors between surgical area and non-surgical area in the same patient at the same time.
Conclusions
In this study, protein changes in gingival crevicular fluid at different time points after PAOO were detected by proteomics method, and significant bone metabolization-related proteins were selected. It is speculated that APOA1, FBN1, NOTCH1, SYT7 and KLF10 play key roles in regulating bone metabolic balance and in reversible osteopenia after PAOO, which might be involved in the accelerated tooth movement. Intrinsic mechanism of related bone metabolic factors was further investigated, so as to summarize the changes of the effect of PAOO on alveolar bone with time, in hope of providing theoretical support for accelerating orthodontic tooth movement.
Acknowledgements
Not applicable.
Declarations
Ethics approval and consent to participate
This study is a prospective cohort study. PKUSSIRB-202054018 (09/03/2020) was reviewed and approved by the Biomedical Ethics Committee of Peking University Hospital of Stomatology. All participants were informed of the research procedure and signed the participation consent agreement. was conducted in full accordance with Declaration of Helsinki. Informed consent was obtained from all participants.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
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