Abstract
Background:
The effect of non-surgical periodontal treatment on oral and systemic inflammatory mediators in subjects with periodontitis and hyperglycemia remains largely unknown. Therefore, the aim of this clinical study was to compare the short-term effect of non-surgical periodontal treatment on serum, saliva and GCF inflammatory markers levels in GP subjects with or without hyperglycemia.
Methods:
Sixty subjects divided into four groups of equal size were selected to participate: type 2 diabetics with generalized periodontitis (T2DM+GP), pre-diabetics with GP (PD+GP), normoglycemic subjects with GP (NG+GP), and healthy controls. GCF, serum, and saliva samples were obtained at baseline and 30 days after scaling and root planning (SRP) and the levels of interleukin-1β (IL-1 β), IL-8, IL-6, IL-2, IL-5, IL-4, IL-10, Interferon gamma (IFN-γ), Granulocyte macrophage colony-stimulating factor (GM-CSF) and Tumor necrosis factor-alpha (TNF-α) were determined by ultrasensitive multiplex assay. Clinical periodontal measurements were recorded.
Results:
SRP yielded significant improvement of all periodontal parameters for all GP groups (p<0.01). A significant reduction in GCF levels of several cytokines were observed; however, only IL-1B and IFN-γ were consistently reduced post-treatment across all GP groups. Salivary levels of IL-1β were significantly reduced in all GP groups following treatment. No significant differences were observed for serum levels after SRP.
Conclusions:
Periodontal treatment reduced local inflammatory markers, specifically IL-1B and IFN-γ, irrespective of the diabetes status. Periodontal treatment had no significant effect on serum levels of the inflammatory markers evaluated in this study.
Keywords: type 2 diabetes mellitus, pre-diabetes, periodontal disease, cytokines, gingival crevicular fluid, saliva, serum, inflammation
Introduction
Generalized periodontitis (GP) is an inflammatory disease caused by oral biofilms that leads to the destruction of the periodontium, and ultimately tooth loss. Long-term bacterial accumulation at the gingival margin results in a matured biofilm and enrichment of periodontal pathogens in subgingival areas causing an inflammatory response that develops as an imbalance between biofilm and the host defense mechanisms (Pihlstrom et al. 2005, Darveau 2010), leading to bone remodeling and connective tissue destruction (Slots 2013). This process produces inflammatory mediators and some of them can be detected at high levels in saliva and gingival crevicular fluid (GCF) (Javed et al. 2012, Stadler et al. 2016).
It is well established in the literature that non-surgical periodontal therapy is the gold standard for the management of GP (Sanz et al. 2012). This therapy is a cause related approach and consists of mechanical cleaning of the root surface to remove pathogenic biofilms, toxins, and calculus. The therapy has been associated with a reduction in local and systemic inflammatory markers (Sanz et al. 2012, Giannopoulou et al. 2012, D’Aiuto et al. 2013).
Over the past 20 years the association between type 2 diabetes mellitus (T2DM) and GP has received considerable attention due to the possible bidirectional relationship of these chronic diseases (Atieh et al. 2014, Purnamasari et al. 2019, Graves et al. 2019). Hyperglycemia affects several biological pathways, such as the advanced glycation end (AGE) pathway, which stimulate the release and activation of inflammatory cytokines. A decrease in collagen production and an increase in collagen degradation have been also observed in periodontal tissues of diabetics as a result of the accumulation of AGEs in the periodontium (Donath et al. 2011).Thus, poorly controlled T2DM and also impaired glucose tolerance (or prediabetes) has been associated with adverse outcomes in periodontal tissues (Preshaw et al. 2012, Javed et al. 2012). Several pro-inflammatory cytokines have been associated with the pathogenesis of both diabetes mellitus and periodontitis (Donath et al. 2011, Atieh et al. 2014).
The effect of periodontal treatment on oral and systemic inflammatory mediators in subjects with prediabetes and diabetes remains largely unknown (O’Connell et al. 2008, Kardeşler et al. 2010, Santos et al. 2010, Sun et al. 2011, Artese et al. 2015, Geisinger et al. 2016). Therefore, the aim of this clinical study was to compare the short-term effect of non-surgical periodontal treatment on serum, saliva and GCF inflammatory markers levels in GP subjects with or without hyperglycemia.
Material and Methods
This study was conducted between January 2014 and May 2015 in full accordance with the Helsinki Declaration of 1975, as revised in 2013. The study protocol and the informed consent form were reviewed and approved by the School of Dentistry Ethics Committee, University of São Paulo, Brazil (658.998/CEP). This study was registered at ClinicalTrials.gov under the identifier NCT02172716. Participants were recruited from the School of Dentistry, University of São Paulo. Each participant signed an informed consent form.
Study population
Participants were recruited from the School of Dentistry, University of Sao Paulo. Subjects 35 to 65 years old who were periodontally healthy or had been diagnosed with GP were eligible to participate. GP was defined as presence of ≥10 teeth with attachment loss ≥5mm; ≥10 teeth with probing depth ≥5mm; and ≥30% sites with bleeding on probing. Periodontally healthy controls had PPD ≤4mm and BOP in <30% sites. Exclusion criteria included: pregnancy, current smoking, body mass index > 40 Kg/m2, having received periodontal therapy or systemic antibiotics in the last 6 months, current use of NSAIDS or steroidal anti-inflammatory medications. Participants were then categorized with regards to their HbA1C levels according to the American Diabetes Association (ADA 2013): T2DM (HbA1C ≥6.5), pre-diabetes (PD; HbA1C ≥5.7 and ≤6.4), and normoglycemic (NG; HbA1C ≤5.6). All participants were under the supervision of an endocrinologist. Subjects were treated by dietary intervention and/or oral hypoglycemic agents. All subjects were authorized by their endocrinologist to participate in the study. Sixty subjects were distributed into four experimental groups as follows (Fig. 1): healthy controls (n=15), NG+GP (n=15), PD+GP (n= 15), and T2DM+GP (n=15).
Figure 1-.
Study Flow
Interview and periodontal assessment
Detailed medical and dental history was obtained from all subjects. A full-mouth, periodontal exam, involving probing at six sites per tooth, was carried out by two calibrated examiners (M.S.R. and A.M.F.). The following parameters were recorded: visible plaque index (VPI) (Ainamo & Bay 1975), gingival bleeding index (GBI) (Ainamo & Bay 1975), bleeding on probing (BOP), periodontal probing depth (PPD), and clinical attachment level (CAL). A manual periodontal probe was used during the exam (North Caroline, Hu-Friedy®, Chicago, IL, USA). Reproducibility during the study was assessed in 10% of the participants, and the intraclass correlation coefficients ranged from 0.91 to 0.94 for periodontal probing depth (PPD) and from 0.85 to 0.88 for clinical attachment level (CAL). Participants were examined at baseline and 1 month after non-surgical periodontal therapy (Fig. 1).
Periodontal Interventions
Two experienced periodontists (G.H.G, M.S.R) provided periodontal treatment. All subjects with GP (n=45) received full-mouth scaling and root planning (SRP) in one session of approximately 120 minutes. Hand instruments (Hu-Friedy®, Chicago, IL, USA) and ultra-sonic devices (PIEZON) were used for SRP under local analgesia (3% prilocaine with felypressin). Hopeless teeth were treated similarly and extracted after the study had been completed. Oral hygiene instructions were given as needed. Periodontally healthy subjects received supragingival scaling/polishing and oral hygiene instructions in one appointment. No other treatment interventions were carried out till the completion of the study.
Biological sampling
Saliva sampling
Unstimulated whole saliva was collected from participants at the baseline and 30 days after treatment. Subjects rinsed their mouth with water, and after they expectorated ≥ 4 ml whole saliva into sterile tubes. Samples were immediately placed on ice and transferred to the laboratory where they were centrifuged to remove particulate debris and mucosal cells (2800 rpm for 20 min at 4°C). Aliquots were prepared, and the supernatant were frozen at −80°C until analysis. Aliquots of 100μl of each saliva sample were used to run the assays.
Blood sample
Blood peripheral samples were collected by a nurse into appropriate tubes (Serum BD Vacutainer®; Plus Plastic Serum Tubes, BD, Franklin Lakes, NJ, USA) at the baseline and 30 days after SRP. Approximately 10 ml sample per subject was used to separate the serum by centrifugation and then stored in aliquots at −80°C for subsequent analysis. Aliquots of 100μl of each serum sample were used to run the assay.
GCF sampling
GCF samples were obtained from the four deepest sites at baseline and 30 days after treatment. After isolation of the area with cotton rolls, supragingival plaque was carefully removed using hand instruments. One paper strip (Periopaper, Oraflow Inc., Plainview, NY, USA) was gently inserted 1-2mm into the gingival sulcus or periodontal pocket until mild resistance was felt for 30 seconds. GCF volume was immediately determined using a chair-side instrument (Periotrom 8000, Oraflow Inc., Plainview, NY, USA), according to the manufacturer’s specification. The samples were pooled and immediately placed in polypropylene tubes and stored at −80°C. Paper strips visibly contaminated with blood were discarded. The actual volumes of the GCF samples were calculated in microliters by reference to the standard curve. Before the laboratory analysis GCF samples were eluted in 200μl PBS and shaken overnight in an orbital shaker. Aliquots of 100μl of each GCF sample were used to run the assay. The total concentrations of the GCF samples were estimated from the standard curve, which had 9 dilutions, expressed as picograms per milliliter (pg/mL) using the curve fitting software, considering sample dilution. The assay limit of the detection was lower than 0.5pg/mL for all analytes.
Quantification of biomarkers
Cytokine and chemokine concentrations were determined using a multiplex fluorescent bead-based immunoassay system (Bio-Plex MAGPIX Multiplex Reader, Bio-Rad, Hercules, CA, USA), with the proper software (Bio-Plex Manager MP Software, Bio-Rad, Hercules, CA, USA). Serum, saliva and GCF levels of 10 different cytokines and chemokines were measured using the Cytokine Human Ultrasensitive Magnetic 10-Plex Panel. The Ultrasensitive 10-Plex included the pro-inflammatory cytokines IL-1β, IL-2, IL-6, interferon gamma (IFN-γ), TNF-α, and granulocyte macrophage-colony stimulating factor (GM-CSF), the anti-inflammatory cytokines IL-4, IL-5 and IL-10, and the chemokine IL-8. The assays were performed in 96-well flat bottom plates following the instructions of the manufacturer. Approximately 5ml of blood was used for HbA1c analysis. HbA1c was assessed by high-performance liquid chromatography method (DisSTST hemoglobin A1c Analyzer System, BioRad® Laboratories, Hercules, CA, USA) at the Clinical Analysis Laboratory of USP, University Hospital.
Statistical analysis
Data were analyzed using the SPSS software (SPSS for Mac, version 20.0, SPSS Inc., Chicago, IL, USA). Delta values were calculated to show differences between baseline and follow-up for multiplex and clinical data. Multiplex data were not normally distributed and were analyzed using non-parametric statistical methods. Comparisons among groups were carried out using Kruskall-Wallis Test followed by Dunn test with Bonferroni correction for multiple comparisons. Medians and interquartile estimates and boxplots are reported. No major deviations from normality were observed for clinical data, and ANOVA and Bonferroni tests were used to compare among groups. Mean and standard deviation are reported. Statistical significance was set at 5%.
Results
All subjects completed the study (Table 1). Subjects in the PD+GP and T2DM+GP groups were significantly older than controls. No changes in medication or lifestyle were observed throughout the study. No adverse events or local/ systemic complications were observed. No significant differences in the periodontal parameters were observed among the GP groups, while the control group was periodontally healthy. As per study design, subjects with PD and T2DM had a greater HbA1c levels than normoglycemics subjects. No other differences were observed among the GP groups. Statistically significant improvements were observed for all periodontal parameters in all the GP groups after SRP, irrespective of glycemic status (Table 2).
Table 1-.
Demographic characteristics and clinical periodontal parameters for the experimental groups at baseline (n=60).
| Control Mean±SD |
NG+GP Mean±SD |
PD+GP Mean±SD |
T2DM+GP Mean±SD |
p-value* | |
|---|---|---|---|---|---|
| Age (years) | 45.3±7.9A | 50.4±8.1AB | 54.1±7.9B | 56.1±8.7B | <0.01 |
| Gender (% female) | 33.3 | 60 | 60 | 33.3 | 0.23 |
| T2DM duration | - | - | - | 10.3±7.5 | - |
| HbA1c (%) | 5.41±0.25 | 5.46±0.2 | 6.08±0.26 | 8.1±1.46 | <0.001 |
| BMI | 26.3±2.4 | 27.2±4.5 | 28.5±6.9 | 29.2±4.4 | 0.39 |
| PI (% sites) | 12,7±6,2 A | 75,7±16,2B | 73,7±8,1B | 81,8±14,7B | <0.01 |
| GI (% sites) | 4,1±5,0 A | 75,6±17,5B | 78,2±13,5B | 82,9±17,2B | <0.01 |
| BOP (% sites) | 5,4±5,2 A | 73,1±14,3B | 73,6±10,3B | 75,5±14,7B | <0.01 |
| PPD (mm) | 1,9±0,3 A | 3,3±0.5B | 3,4±0,7B | 3,6±0,7B | <0.01 |
| CAL (mm) | 1,3±0,5A | 3,9±0.9B | 4,2±1,3B | 4,9±1,3B | <0.01 |
Different letters denote statistically different groups (ANOVA followed by Bonferroni multiple-comparison test). SD: standard deviation; HbA1c, glycated hemoglobin; BMI, body mass index; DMT2, diabetes mellitus type 2. IP – plaque index; GI – gingival index; BOP – bleeding on probing; PPD – periodontal probing depth; CAL – clinical attachment loss.
Table 2 –
Clinical outcomes following non-surgical periodontal treatment.
| Control Mean±SD |
NG+GP Mean±SD |
PD+GP Mean±SD |
T2DM+GP Mean±SD |
p-value* | |
|---|---|---|---|---|---|
| All sites | |||||
| PI reduction (% sites) | 7,5±5,1 A | 62,6±14,5B | 60,8±8,8B | 65,7±10,2B | <0.01 |
| GI reduction (% sites) | 3,2±4,9 A | 69,9±16,0B | 70,1±15,3B | 69,9±13,7B | <0.01 |
| BOP reduction (% sites) | 4,3±4,8 A | 61,5±14,3B | 58,5±9,1B | 59,7±10,3B | <0.01 |
| PPD reduction (mm) | 0,1±0,1 A | 0,8±0,3B | 0,9±0,4B | 1,0±0,4B | <0.01 |
| CAL gain (mm) | 0,0±0,1A | 0,6±0,3B | 0,5±0,3B | 0,6±0,4B | <0.01 |
| Sites with probing depth 5+mm at baseline | |||||
| PI reduction (% sites) | - | 62,2±18,5A | 65,0±16,7A | 67,0±13,1A | 0,65 |
| GI reduction (% sites) | - | 72,2±14,8A | 76,7±16,7A | 73,2±16,3A | 0,62 |
| BOP reduction (% sites) | - | 70,8±12,9A | 67,8±15,8A | 67,5±11,0A | 0,80 |
| PPD reduction (mm) | - | 2,4±0,4A | 2,3±0,3A | 2,4±0,5A | 0,56 |
| CAL gain (mm) | - | 1,6±0,4A | 1,5±0,5A | 1,3±1,6A | 0,37 |
Different letters denote statistically different groups (ANOVA followed by Bonferroni multiple-comparison test). IP – plaque index; GI – gingival index; BOP – bleeding on probing; PPD – periodontal probing depth; CAL – clinical attachment loss; NG, normoglycemic; PD, pre-diabetes; T2DM, type 2 diabetes mellitus; GP, generalized periodontitis.
At baseline, GP groups had significantly higher GCF levels of IL-1β, IL-2, IL-6, IL-8, and TNF-α when compared to the control group, irrespective of the glycemic status (Table 3). NG+GP and T2DM+GP had significantly higher GCF levels of IL-10 when compared to the control group. Salivary levels of IL-1β and TNF-α were significantly higher in the GP groups when compared to the control group. (Table 4). No significant differences among groups were observed in serum levels for any of the cytokines evaluated (Table 5).
Table 3-.
GCF concentrations of selected cytokines at baseline.
| GCF pg/mL | Control Median (25%-75%) |
NG+GP Median (25%-75%) |
PD+GP Median (25%-75%) |
T2DM+GP Median (25%-75%) |
p-value* |
|---|---|---|---|---|---|
| IL-1β | 4369.9 (980.2; 8212) A | 12485.7 (6505.5; 48696.2) B | 10833.3 (6484.8; 20751.8) B | 15109.6 (4528.5; 20882.4) B | <0.01 |
| IL-2 | 76.4 (68.7; 104.2) A | 187.5 (135.3; 337.2) B | 199.6 (150.3; 281.3) B | 183.1 (131.8; 247.2) B | <0.01 |
| IL-6 | 32.5 (17.7; 57) A | 138.2 (97.9; 378.6) B | 195.2 (90.5; 293.4) B | 119.8 (81.7; 280) B | <0.01 |
| IL-8 | 20802.9 (6425.5; 54430.7) A | 41416.8 (25448.5; 267699.3) B | 105596.7 (42343.1; 414119.1) B | 67118.4 (47353.7; 118303.3) B | <0.0 |
| IL-5 | 5.9 (0.4; 10) A | 8.2 (5.1; 16.6) A | 7.2 (6.3; 10.6) A | 7.4 (3.8; 12.7) A | 0.12 |
| IL-4 | 130.02 (80.2; 139.7) A | 148.25 (122.7; 245.4) A | 145.8 (108.2; 189.4) A | 147.5 (111.6; 184) A | 0.18 |
| IL-10 | 19.7 (13.2; 41.5) A | 56.4 (20.8; 91) B | 42.8 (30.3; 50.6) AB | 46.6(32.2; 111.8) B | 0.02 |
| IFN-γ | 0.01 (0.01; 0.01) A | 16.1 (0.7; 30.5) B | 3.6 (0.01; 11.4) AB | 8.4 (0.01; 17.8) B | <0.01 |
| GM-CSF | 45.9 (28.5; 55.7) A | 68.7 (52.7; 184.6) A | 58 (44.9; 123) A | 112.1 (36.7; 158.7) A | 0.06 |
| TNF-α | 152.7 (108.8; 213.2) A | 301.9 (199.4; 507.8) B | 336.6 (244.5; 412.6) B | 315.8 (242; 408) B | <0.01 |
Different letters denote statistically different groups (Kruskall Wallis followed by Dunn test with Bonferroni correction).
NG, normoglycemic; PD, pre-diabetes; T2DM, type 2 diabetes mellitus; GP, generalized periodontitis.
Table 4-.
Saliva concentrations of selected cytokines at baseline.
| Saliva pg/mL | Control Median (25%-75%) |
NG+GP Median (25%-75%) |
PD+GP Median (25%-75%) |
T2DM+GP Median (25%-75%) |
p-value* |
|---|---|---|---|---|---|
| IL-1β | 23.08 (8.75; 38.5) A | 92.63 (46.12; 159) B | 125 (51.7; 209.2) B | 90.3 (48.7; 141.9) B | <0.01 |
| IL-2 | 6.8 (2.9; 8.4) A | 10.8 (6.36; 35.3) A | 11.9 (9.3; 17.9) A | 8.2 (4.3; 14.8) A | 0.19 |
| IL-6 | 8.15 (4; 16.07) A | 12.7 (8.8; 37.3) A | 14.8 (6.7; 28.8) A | 11.05 (6.05; 14.9) A | 0.26 |
| IL-8 | 1504.6 (455.5; 2217.2) A | 2092 (766.2; 3835.2) A | 3527.5 (1083.2; 10630.1) A | 3615.4 (1046.8; 13517.4) A | 0.15 |
| IL-5 | 0.7 (0.43; 1.38) A | 1.65 (0.55; 18.2) A | 1.92 (1.03; 2.4) A | 0.49 (0.3; 1.9) A | 0.03 |
| IL-4 | 3.27 (2.37; 4.53) A | 5.9 (4.5; 62.8) AB | 8.2 (6.3; 15.8) B | 6.8 (1.5; 12.06) AB | 0.02 |
| IL-10 | 1.34 (0.99; 3.88) A | 3.13 (1.83; 21.5) A | 4.15 (2.27; 6.78) A | 4.95 (0.8; 11) A | 0.28 |
| IFN-γ | 0.34 (0.01; 1.14) A | 0.3 (0.01; 6.9) A | 0.6 (0.3; 1.05) A | 0.11 (0.01; 0.75) A | 0.53 |
| GM-CSF | 3.46 (0.96; 7.26) A | 4.78 (2.9; 17) A | 6.26 (2.7; 12.8) A | 2.38 (1.44; 12) A | 0.62 |
| TNF-α | 6.6 (2.4; 8.3) A | 11.5 (7.3; 50) B | 14 (8.3; 23.1) B | 10.5 (3.9; 18.4) B | 0.01 |
Different letters denote statistically different groups (Kruskall Wallis followed by Dunn test with Bonferroni correction).
NG, normoglycemic; PD, pre-diabetes; T2DM, type 2 diabetes mellitus; GP, generalized periodontitis.
Table 5-.
Serum concentrations of selected cytokines at baseline.
| Serum pg/mL | Control Median (25%-75%) |
NG+GP Median (25%-75%) |
PD+GP Median (25%-75%) |
T2DM+GP Median (25%-75%) |
p-value* |
|---|---|---|---|---|---|
| IL-1β | 0.09 (0.01; 0.25) A | 0.13 (0.03; 0.28) A | 0.03 (0.02; 0.15) A | 0.09 (0.03; 0.14) A | 0.45 |
| IL-2 | 0.01 (0.01; 0.61) A | 0.51 (0.01; 5.6) A | 0.1 (0.01; 1.2) A | 0.1 (0.01; 1.55) A | 0.27 |
| IL-6 | 0.73 (0.44; 1.41) A | 2.27 (0.95; 12.53) A | 0.77 (0.39; 1.15) A | 0.82 (0.43; 3.36) A | 0.19 |
| IL-8 | 39.6 (12.9; 152.3) A | 162.8 (47.6; 854.6) A | 54.3 (24.6; 143.1) A | 55.8 (24.7; 174.8) A | 0.13 |
| IL-5 | 0.02 (0.01; 0.44) A | 0.32 (0.02; 2.49) A | 0.03 (0.01; 0.26) A | 0.18 (0.03; 1.16) A | 0.17 |
| IL-4 | 0.14 (0.01; 1.62) A | 0.99 (0.01; 5.46) A | 0.01 (0.01; 1.26) A | 0.4 (0.01; 2.78) A | 0.18 |
| IL-10 | 1.95 (0.06; 4.7) A | 1.48 (0.5; 3.4) A | 0.56 (0.34; 4.7) A | 1.41 (0.43; 5.2) A | 0.82 |
| IFN-γ | 0.03 (0.01; 0.26) A | 0.24 (0.06; 0.63) A | 0.01 (0.01; 0.14) A | 0.01 (0.01; 0.32) A | 0.02 |
| GM-CSF | 2.62 (0.25; 14.12) A | 2.33 (0.21; 17.8) A | 0.66 (0.14; 3.7) A | 2.93 (0.26; 18.1) A | 0.61 |
| TNF-α | 0.33 (0.01; 2.73) A | 1.35 (0.53; 4.84) A | 0.09 (0.01; 1.09) A | 0.31 (0.01; 1.01) A | 0.08 |
Different letters denote statistically different groups (Kruskall Wallis followed by Dunn test with Bonferroni correction).
NG, normoglycemic; PD, pre-diabetes; T2DM, type 2 diabetes mellitus; GP, generalized periodontitis.
Table 6 demonstrates the change in serum, saliva and GCF levels of cytokines following non-surgical periodontal treatment. A significant reduction following treatment in GCF and salivary levels of IL-1β and in GCF levels of IFN-γ was observed for all GP groups. No significant differences in serum cytokine levels were observed among groups after SRP. Regarding the comparisons between before and after treatment, IL-1β (GCF and saliva), IL-2 (GCF) and IFN-γ (GCF) changed significantly for the NG+GP group; IL-1β (GCF and saliva), IL-4 (GCF) and IFN-γ (GCF) changed significantly for the PD+GP group; IL-1β (GCF and saliva) and IL-8 (serum) changed significantly for the T2DM+GP group. Other comparisons were borderline significantly different: NG+GP group - IL-4 and IFN-γ (GCF); PD+GP group - IL-2, IL-6 and TNF-α (GCF); T2DM+ GP group - IL-6 (serum), IL-8 and TNF-α (saliva), IL-4 and IFN-γ (GCF).
Table 6-.
Change in serum, saliva and GCF concentrations of selected cytokines. Intra (before-after) and inter-group comparisons (Δ values).
| Control | NG+GP | PD+GP | T2DM+GP | p-value among groups** | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Median (25%-75%) | p-value* | Median (25%-75%) | p-value* | Median (25%-75%) | p-value* | Median (25%-75%) | p-value* | |||
| IL-1β | Serum | −0.01 (−0.14; 0.14) A | 0.48 | 0.01 (−0.09; 0.16) A | 0.63 | 0.01 (−0.02; 0.19) A | 0.26 | 0.01(−0.02; 0.35) A | 0.60 | 0.32 |
| Saliva | 1.46 (−16.27; 37.24) A | 0.69 | −43.27 (−93.47; −6.83) B | <0.01 | −83.76 (−103.23; −13.89) B | <0.01 | −51.40 (−72.75; −8.68) B | <0.01 | <0.01 | |
| GCF | −276.53 (−3533.53; 900.24) A | 0.39 | −8239.58 (−38693.97; −3061.17) B | <0.01 | −3957.10 (−13235.18; −2165.92) B | <0.01 | −9018.98 (−13495.31; −74.12) B | <0.01 | <0.01 | |
| IL-2 | Serum | 0.00 (−0.60; 0.00) A | 0.38 | −0.18 (−0.54; 0.35) A | 0.55 | 0.00 (−0.66; 0.15) A | 0.78 | 0.00 (−0.38; 0.05) A | 0.44 | 0.91 |
| Saliva | −0.21 (−0.69; 5.02) A | 0.42 | 0.40 (−7.74; 8.08) A | 0.82 | −2.97 (−8.48; 3.17) A | 0.23 | −0.88 (−3.3; 2.54) A | 0.39 | 0.29 | |
| GCF | 66.24 (−36.72; 270.41) A | 0.06 | 131.76 (43.48; 199.52) A | 0.02 | 96.50 (−59.47; 218.38) A | 0.06 | 12.18 (−33.39; 123.52) A | 0.21 | 0.49 | |
| IL-6 | Serum | −0.40 (−0.84; 0.54) A | 0.36 | 0.48 (−1.70; 8.95) A | 0.46 | −0.01 (−0.36; 8.92) A | 0.51 | 0.16 (−0.15; 3.98) A | 0.06 | 0.18 |
| Saliva | 0.14 (−6.47; 13.44) A | 0.73 | −0.92 (−21.71; 3.22) A | 0.30 | −3.06 (−17.32, 6.13) A | 0.28 | 0.12 (−2.18; 3.07) A | 0.86 | 0.58 | |
| GCF | 36.48 (−6.97; 96.11) A | 0.20 | −17.23 (−144.51; 23.88) A | 0.19 | −59.49 (−242.01; 41.20) A | 0.06 | −41.34 (−134.10; 96.95) A | 0.69 | 0.16 | |
| IL-8 | Serum | −25.85 (−102.64; 15.08) A | 0.15 | 206.57 (−99.06; 613.14) A | 0.14 | 24.32 (−59.11; 468.21) A | 0.21 | 19.86 (−1.34; 768.42) A | 0.03* | 0.07 |
| Saliva | −94.46 (−1327.85; 1901.91) A | 0.82 | −184.08 (−1221.92; 731.00) A | 0.65 | −278.25 (−2965.76; 9803.98) A | 0.92 | −1291.36 (−9631.41; 0.00) A | 0.07 | 0.37 | |
| GCF | 39119.20 (−11783.69; 133841.02) A | 0.10 | 480.61 (−94788.22; 121880.00) A | 0.92 | −7209.80 (−139724.09; 34608.14) A | 0.49 | 2553.40 (−26080.92; 81006.00) A | 0.47 | 0.51 | |
| IL-5 | Serum | 0.00 (−0.43; 0.02) A | 0.58 | −0.02 (−0.47, 0.12) A | 0.55 | 0.01 (−0.02; 0.17) A | 0.30 | 0.00 (−0.11; 0.07) A | 0.72 | 0.57 |
| Saliva | 0.30 (−0.78; 1.44) A | 0.36 | 0.56 (−0.40; 0.81) A | 0.39 | −0.40 (−1.99; 0.52) A | 0.69 | 0.19 (−0.72; 0.58) A | 0.69 | 0.64 | |
| GCF | 4.31 (−2.95; 14.22) A | 0.04 | 2.74 (−3.75; 3.10) A | 0.95 | 1.69 (−4.08; 6.79) A | 0.49 | 2.75 (−7.24; 8.94) A | 0.53 | 0.47 | |
| IL-4 | Serum | 0.00 (−1.50; 0.55) A | 0.53 | 0.00 (−1.28; 1.92) A | 0.82 | 0.00 (0.00; 0.58) A | 0.57 | 0.00 (−0.74; 0.55) A | 0.95 | 0.79 |
| Saliva | 1.24 (−1.33; 2.66) A | 0.28 | 0.40 (−3.88; 9.45) A | 0.69 | −2.24 (−8.24; 2.81) A | 0.33 | 0.26 (−7.28; 1.77) A | 0.60 | 0.51 | |
| GCF | 40.99 (−6.39; 116.89) A | <0.01 | 95.42 (23.83; 115.43) A | 0.06 | 50.39 (−24.52; 101.31) A | 0.03 | 38.11 (−25.91; 124.25) A | 0.06 | 0.78 | |
| IL-10 | Serum | 0.24 (−0.94; 1.72) A | 0.73 | 0.04 (−0.90; 1.11) A | 0.91 | −0.01 (−0.80; 0.52) A | 0.80 | 0.00 (−2.69; 1.74) A | 0.85 | 0.94 |
| Saliva | −0.39 (−2.30; 2.78) A | 0.97 | 0.07 (−6.17; 1.84) A | 0.60 | −0.11 (−2.02; 4.6) A | 0.65 | −0.26 (−4.86; 1.28) A | 0.57 | 0.83 | |
| GCF | 29.28(16.72; 70.69) A | 0.10 | 35.96 (23.95; 86.44) A | 0.17 | 28.60 (12.85; 61.23) A | 0.77 | 49.86 (16.12; 159.59) A | 0.12 | 0.08 | |
| IFN-γ | Serum | 0.00 (−0.17; 0.11) A | 0.72 | −0.06 (−0.23; 0.00) A | 0.15 | 0.00 (0.00; 0.06) A | 0.28 | 0.00 (−0.30; 0.03) A | 0.87 | 0.19 |
| Saliva | 0.00 (−0.34; 0.61) A | 0.59 | 0.00 (−0.38; 0.94) A | 0.92 | −0.15 (−0.83; 0.58) A | 0.39 | 0.12 (0.00; 0.70) A | 0.18 | 0.67 | |
| GCF | 0.00 (0.00; 0.00) A | 0.31 | −12.58 (−29.95; −0.69) B | <0.01 | −3.59 (−11.38; 0.00) AB | 0.01 | −0.78 (−9.00; 0.00) AB | 0.05 | <0.01 | |
| GM-CSF | Serum | −0.07 (−14.11; 3.00) A | 0.77 | 0.01 (−7.53; 1.76) A | 0.97 | 0.08 (−0.44; 0.69) A | 0.59 | 0.00 (−2.71; 2.75) A | 0.69 | 0.94 |
| Saliva | 0.36 (−6.03; 8.32) A | 0.86 | −0.35 (−8.72; 2.14) A | 0.65 | −0.26 (−6.27; 2.03) A | 0.42 | 0.34 (−0.66; 2.38) A | 0.57 | 0.95 | |
| GCF | 43.99 (−5.67; 208.70) A | 0.30 | 8.03 (−45.58; 27.94) A | 0.82 | −8.70 (−49.50; 44.74) A | 0.77 | −13.61 (−100.85; 27.07) A | 0.33 | 0.12 | |
| TNF-α | Serum | −0.12 (−2.02; 0.97) A | 0.43 | −0.14 (−2.42; 1.21) A | 0.86 | 0.03 (0.00; 1.21) A | 0.10 | 0.00 (−0.19; 0.68) A | 0.64 | 0.45 |
| Saliva | 0.65 (−3.51; 8.81) A | 0.65 | 1.26 (−9.44; 8.37) A | 0.69 | −5.33 (−8.78; 2.64) A | 0.15 | 0.24 (−9.21; 2.67) A | 0.07 | 0.43 | |
| GCF | −30.05 (−90.74; 20.60) A | 0.25 | −129.39 (−349.19; −73.84) A | 0.05 | −126.52 (−260.01; 62.55) A | 0.06 | −11.84 (−236.53; 25.00) A | 0.10 | 0.34 | |
NG, normoglycemic; PD, pre-diabetes; T2DM, type 2 diabetes mellitus; GP, generalized periodontitis;
Wilcoxon test, p-value for intra-group comparison between baseline and follow-up;
Kruskal-Wallis test followed by Dunn test with Bonferroni correction, p-value for comparison among groups, different capital letters denote statistically different groups
Discussion
The present study evaluated the short-term effect of non-surgical periodontal treatment on serum, saliva and GCF cytokine levels in GP subjects with and without hyperglycemia. Periodontal treatment significantly reduced pro-inflammatory cytokines levels in GCF (IL-1β and IFN-γ) and saliva (IL-1β), irrespective of the pre-diabetes/diabetes status; however, it had no significant effect on their serum levels. To the best of the authors’ knowledge, this is the first study to evaluate if the glycemic status modifies the effect of non-surgical periodontal treatment on oral and systemic cytokine levels in subjects diagnosed with GP.
The present non-surgical periodontal treatment was very effective in reducing clinical inflammation and no significant differences were observed among GP groups after one month. These findings are in agreement with previous reports showing no significant differences in periodontal parameters between normoglycemic and diabetic subjects over a short follow-up period (Christgau et al. 1998, Kara et al. 2015, Koçak et al. 2016).
GCF cytokines levels in periodontal health/disease and the effect of non-surgical periodontal treatment in GCF cytokines levels of periodontitis patients without diabetes have been explored in several studies. In a systematic review and meta-analysis, Stadler et al. (2016) concluded that IL-1β, IL-6, IFN-γ were significantly higher in subjects diagnosed with periodontitis when compared to controls. Inconsistent results due to limited data and a high degree of heterogeneity were observed for IL-8, IL-4, IL-10 and TNF-α. In the present study, all GP groups had significantly higher GCF levels of IL-1β, IL-2, IL-6, IL-8 and TNF-α than the control group at the baseline, irrespective of the glycemic status. These findings are in agreement with previous studies that reported similar GCF cytokine profiles in periodontitis patients with and without diabetes, which suggests that the expression of proinflammatory cytokines in the periodontal tissues is more related to local than systemic factors (Kurtis et al. 1999, Correa et al. 2008, Navarro-Sanchez et al. 2007). Stadler et al. (2016) also reported that IL-1β, IL-17 and IL-4 have large and significant changes after non-surgical treatment. The finding for IL-1β after periodontal treatment are in agreement with our findings in all GP groups. Few studies explored the effect of non-surgical periodontal treatment on the local levels of cytokines in subjects with and without diabetes. Navarro-Sanchez et al. (2007) reported a significant reduction in GCF levels of IL-1β and TNF-α after periodontal treatment in both groups with periodontitis, irrespective of the diabetes status. Reduction of GCF IL-1β level after non-surgical periodontal treatment in T2DM subjects was also reported in other studies (Correa et al. 2008, Kardeşler et al. 2011, Koçak et al. 2016). Our results showed a significant reduction in GCF levels of IL-1β in all GP groups, irrespective of the HbA1c levels. Interestingly, post-treatment changes of GCF levels of TNF-α were borderline significant for all the GP groups. These findings indicate that short-term periodontal healing after non-surgical periodontal treatment is similar between non-diabetics, pre-diabetic, and T2DM periodontal patients.
Salivary tests are very appealing noninvasive methods for the diagnosis of oral and systemic diseases (Teles et al. 2009, Miller et al. 2010, Giannobile 2012). However, few studies have correlated salivary biomarkers and periodontal status over time or explored the effect of periodontal treatment on salivary cytokine levels (Thomas et al. 2009, Kaushik et al. 2011, Kinney et al. 2011, Sexton et al. 2011). To the best of our knowledge, there are no studies exploring the effect of periodontal treatment on salivary cytokine levels of prediabetic or diabetic subjects. In the present study, salivary levels of IL-1β and TNF-α were significantly higher for subjects with periodontitis than controls at the baseline. Similarly, Sexton et al. (2011) found significant differences in the salivary levels of IL-1β between systemically healthy subjects with and without periodontitis. However, Teles et al. (2009) reported no significant differences between subjects with periodontitis and controls for IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IFN-γ, and TNF-α. Yoon et al (2012) found that periodontal disease, but not T2DM, was associated with the salivary levels of IL-1 β. Javed et al. (2014) observed that IL-6 and MMP-8 salivary levels were significantly increased in patients with periodontitis when compared to controls; no differences were observed in regards to prediabetes status. In contrast, no significant differences between healthy controls and the GP groups for IL-6 salivary levels were found in this study. Following periodontal treatment, a significant reduction on IL-1β salivary levels for all GP groups was observed, but glycemic levels did not affect this improvement. Whereas studies support our findings in regard to subjects with periodontitis (Kaushik et al. 2011, Kinney et al. 2011, Sexton et al. 2011), no studies have investigated the impact of hyperglycemia on IL-1β salivary levels after periodontal treatment. Overall, it appears that the glycemic status has limited impact on salivary levels of several inflammatory markers in subjects with periodontitis.
In a systematic review and meta-analysis, Artese et al. (2015) assessed the effect of periodontal therapy (surgical and non-surgical) on serum levels of inflammatory markers in subjects with T2DM. The results showed that periodontal therapy reduces serum levels of TNF-α and CRP in T2DM subjects. In the present study CRP was not analyzed and no differences were observed for TNF-α or any other markers after periodontal treatment. Geisinger et al. (2016) evaluated the effect of non-surgical periodontal treatment on serum biomarkers of 475 patients with T2DM and generalized periodontitis at the baseline and 6 months after treatment. No significant differences in serum inflammatory biomarkers were observed between treatment and control groups, despite a significant improvement in the periodontal parameters (Geisinger et al. 2016). Collectively, these findings suggest that T2DM may be the primary driver of systemic inflammation and that periodontal treatment has a limited effect on systemic inflammation. Caution should be exercised when comparing these studies owning to differences in patient characteristics, interventions, and follow-up time.
Among the strengths of this study are the comprehensive and simultaneous analysis of oral and systemic cytokines in subjects with different glycemic status, the study design, the consistent sampling methodology, standardization of the clinical and lab procedures, and the significant impact of the non-surgical treatment. Weaknesses of the study include the limited sample size, which likely led to some borderline p-values, and the fact that the present results are limited to ten cytokines. Therefore, clinical studies with larger sample sizes and a broader panel of biomarkers may help clarify the effect of periodontal treatment on oral and systemic inflammation and its relationship with hyperglycemia.
Conclusion
Periodontal treatment reduced local inflammatory markers, specifically IL-1B and IFN-γ, irrespective of the diabetes status. Periodontal treatment had no significant effect on serum levels of the inflammatory markers evaluated in this study.
Highlights.
Non-surgical periodontal treatment significantly reduced inflammatory markers in saliva and gingival crevicular fluid, irrespective of the diabetes status in subjects with periodontitis
Non-surgical periodontal treatment had no effect on systemic inflammatory markers in subjects with periodontitis
Gingival crevicular fluid and salivary levels of IL-1β are reduced by periodontal therapy, irrespective of the glycemic level
The severity of periodontal inflammation mainly governs the expression of proinflammatory cytokines in the gingival crevicular fluid
Acknowledgements
We would like to thank Dr. Marcia Pinto Alves Mayer for her collaboration during the preparation of the samples in the University of Sao Paulo, Brazil.
Conflict of interest and source of funding statement: the authors declare no conflicts of interest. This study was partially supported by NIH/NIDR RO1DE143288-11 and R21 DE020916-01 Grants and by São Paulo Research Foundation, FAPESP Grant 2011/06982-4.
Footnotes
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Declaration of interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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