Abstract
Objective: This case–control study aimed to investigate the diagnostic accuracy of salivary interleukin (IL)-1β, IL-10, and IL-1β/IL-10 ratio to discriminate periodontitis from periodontal health and stable from unstable periodontitis.
Methods: Saliva samples were collected from 135 (healthy on an intact periodontium = 45 [as healthy control], stable periodontitis = 39, and unstable periodontitis = 51) participants, and then clinical periodontal parameters were recorded. An enzyme-linked immunosorbent assay was used to determine salivary levels of IL-1β and IL-10. Area under the curves (AUCs), sensitivity, and specificity of IL-1β, IL-10, and IL-1β/IL-10 were estimated to discriminate between groups.
Result: The level of salivary IL-1β was significantly higher in unstable periodontitis than in stable periodontitis and healthy control groups (426 ± 59, 247 ± 55, and 204 ± 36 pg/ml [picograms per milliliter], respectively). While the level of salivary IL-10 was significantly higher in the control group (360.7 ± 80.5 pg/ml) than unstable periodontitis group (146.92 ± 1.8 pg/ml), no significant difference was found between the control and stable periodontitis (317.04 ± 59.8 pg/ml) groups. IL-1β, IL-10, and IL-1β/IL-10 had significant diagnostic accuracy for differentiating healthy control from unstable periodontitis (AUCs = 0.99, 0.96, and 1; sensitivity = 0.98,1, and 1; specificity = 0.95, 0.95, and 1, respectively). Similarly, they showed significant diagnostic accuracy in distinguishing unstable from stable periodontitis (AUCs = 0.98, 0.99, and 1; sensitivity = 0.94, 1, and 1; specificity = 0.94, 0.97, and 1, respectively).
Conclusion: Salivary IL-1β, IL-10, and IL-1β/IL-10 have a high potential to discriminate healthy control from periodontitis and stable from unstable periodontitis.
Trial Registration: ClinicalTrials.gov identifier: NCT05722613
1. Introduction
Periodontitis is a common chronic multifactorial inflammatory disease [1]. Globally, 796 million individuals are suffering from periodontitis; the prevalence of severe periodontitis is 9.8%. With increases in age, these numbers are expected to rise [2]. Periodontitis has a negative impact on the quality of life associated with oral health [3]. Moreover, periodontitis has been reported to be associated with several systemic disorders, such as dementia [4], diabetes, and cardiovascular diseases [5]. Accordingly, early and precise diagnosis of periodontitis is crucial since the loss of soft tissue and bone could have esthetic, functional, and systemic consequences [6].
The main cause of periodontitis is the shifting in the ecological balance between virulent periodontal pathogens and the host immune response [7]. The inflammatory changes in periodontal tissue are initiated by dental biofilm (harboring many periodontal pathogens) accumulated on teeth surfaces [8]. Host inflammatory cells response to virulent pathogens and release both pro-inflammatory and anti-inflammatory cytokines [9]. Interleukin (IL)-1β is a pro-inflammatory cytokine associated with tissue degradation in periodontitis [10]. Elevation in its levels could be detected shortly in the gingival crevicular fluid after the initiation of gingival inflammation [11]. It is released from macrophages, monocytes, lymphocytes, epithelial cells, fibroblasts, and osteoblasts in response to periodontal pathogens. IL-1β has been reported to be elevated in serum, saliva, and gingival crevicular fluid of periodontitis patients [12, 13]. After nonsurgical periodontal therapy, salivary levels of IL-1β are significantly reduced [14]. On the other hand, regulatory T cells release IL-10 in the affected tissue. IL-10, known as an anti-inflammatory cytokine, plays a complex role in the pathogenesis of periodontitis. IL-10 declines alveolar bone loss by downregulation of osteoclastogenesis mediated by T-helper 1 [15]. Simultaneously, IL-10 suppresses the innate response [16]. Thus, the role of IL-10 is to control the immune response and hinder the production of pro-inflammatory cytokines. For instance, IL-10 has the ability to restrict and inhibit the action of IL-1β [17]. Thus, it has a protective role in reducing inflammatory-driven alveolar bone resorption and tissue damage [18]. Consequently, the overall pro- and anti-inflammatory balance could be able to identify whether the lesions are stable or progressing [19].
In fact, accurate diagnosis of periodontal diseases is essential for appropriate treatment planning as well as prognosis [20]. No doubt, the precision of the diagnosis of periodontal diseases not only impacts clinical practice but also boosts the validity and reliability of research aimed to enhance periodontal care strategies [21].
Currently, clinical parameters such as bleeding on probing (BOP), clinical attachment loss (CAL), probing pocket depth (PPD), and radiographs are still the standard approaches for diagnosing periodontal diseases. By these parameters, clinicians could assess the present extent and severity of periodontitis as well as illustrate the past tissue destruction of periodontal tissue [22]. However, the above-mentioned parameters have several considerable limitations. They are deficient in providing data about the current biological activity or future progression of the disease [22]. Additionally, the accuracy of measuring these parameters is more dependent on clinician skills. Therefore, there are marginal errors in recording these parameters among different clinicians [23]. This might have an impact on the precision of diagnosing periodontal diseases. For instance, the current status of periodontitis, according to the recent classification, is detected after recording BOP and PPD [20]. In light of these limitations, the recent classification of periodontal diseases has brought attention to the possible use of biomarkers to enhance the early and accurate diagnosis of periodontitis [20].
The nature of periodontitis is intricate, and it is inadequate to rely on a solitary biomarker to encompass all dimensions of the disease [24]. Identifying a prospective panel consisting of combined salivary biomarkers exhibits an enhanced efficacy in differentiating patients with varying stages and statuses of periodontitis from healthy peers. Therefore, this study aimed to determine the diagnostic accuracy of salivary levels of tissue destruction-associated biomarkers (IL-1β and IL-10) for differentiating periodontal health from periodontitis and stable from unstable periodontitis.
2.1. Study Design and Population
This observational case–control study was conducted at the Department of Periodontics/College of Dentistry/University of Baghdad and Al-Noor Specialized Dental Center from May 2022 to March 2023. This study followed the ethical guidelines of the Declaration of Helsinki and its revisions for human research. The protocol has been approved by the ethics committee of the College of Dentistry/University of Baghdad (Reference number: 527, Project number: 527622 on April 17th, 2022).
During screening, only subjects who fit the inclusion and exclusion criteria were invited to participate in this study. Signed informed consent forms were collected by the examiner from all participants.
The inclusion criteria included those who were systemically healthy with body mass index (BMI) ≤25, not under any medications in the last 3 months and had a minimum of 20 teeth with facial and lingual scorable surfaces. Smoker subjects or subjects having diabetes were excluded from this study. Additionally, exclusion criteria included any previous periodontal therapy within the last 3 months or currently under active periodontal treatment. Accordingly, the participants were diagnosed and categorized into three groups: healthy on an intact periodontium as a healthy control, unstable periodontitis, and stable periodontitis. In the control group, the participants were diagnosed as having healthy periodontium characterized by BOP <10%, PPD ≤3 mm, and intact periodontium with no probing attachment loss [25]. On the other hand, participants having periodontitis were diagnosed as they were having interdental CAL detected at ≥2 nonadjacent teeth or/and facial or oral surfaces with CAL ≥3 mm as well as PPD >3 mm detected at ≥2 teeth [26]. In unstable periodontitis group, the participants were diagnosed as generalized (>30% of teeth having CAL) unstable periodontitis having at least one site with PPD ≥5 mm or PPD ≥4 mm with BOP. While stable periodontitis group included participants having generalized stable periodontitis with BOP <10%, PPD ≤4 mm, and no BOP at 4 mm PPD sites [26]. Both stable and unstable periodontitis groups had a history of active periodontal treatment and were currently in the maintenance phase.
A pilot study was conducted to optimize the techniques and compute the required sample size. After estimating the concentration of IL-1β concentration (primary outcome) in 20 saliva samples by enzyme-linked immunosorbent assay (ELISA), the sample size was calculated according to the following equation:r was cases/controls ratio ( = 1); SD was the standard deviation (65.7); Zβ was the desired power of 90% ( = 1.28); Zα/2 was 5% type 1 error ( = 1.96); d was the expected mean difference between case and control ( = 53.4). Accordingly, a sample of 37 participants in each group was estimated. To boost the power of the study, a higher sample size was considered (45 for the healthy control group, 51 for the unstable periodontitis group, and 39 for the stable periodontitis group).
2.2. Clinical Parameters
After participants selection, all clinical periodontal parameters, including the plaque index (PI) [27], BOP [28], PPD, and CAL, were recorded using a Michigan O periodontal probe (MEDESY, Maniago, Italy) by the same calibrated examiner. Plaque-disclosing pellets (Guided Biofilm Therapy, biofilm discloser, Zwingenberg, Germany) were used to aid in the detection of the dental biofilm. BOP, PPD, and CAL were recorded at six sites/tooth, while the PI was recorded at four sites/tooth.
Prior to starting the study, the examiner was calibrated for diagnosis and recording of clinical parameters with 2-h intervals between two readings. The calibration sessions were repeated on different days until reaching an accepted level of agreement between readings; >0.75 kappa values for PI and BOP as well as >0.9 intraclass correlation coefficient values for PPD and CAL.
2.3. Salivary Sample Collection and Biochemical Analysis
Before recording the clinical parameters, unstimulated saliva samples were collected from participants, as previously reported [29]. From 9 AM to 12 PM, participants were asked to refrain from drinking, eating, and brushing their teeth 1 h before sample collection. Then, each participant was asked to rinse his/her mouth with tap water to remove any food residue, and a saliva sample was collected 10 min later. The participants were asked to sit comfortably in an upright position with their heads tilted slightly downwards. The participants were instructed to allow saliva to pool on the floor of their mouths before gently expectorating into a graduated sterile tube for 5 min to obtain 1 ml of unstimulated saliva. Then, the tube was centrifuged for 20 min at room temperature at 1000 x g (800 electrical centrifuge—China). A total of 500 μl of the supernatant was transferred into an Eppendorf tube (DNase/Nase free, BIOFL) to estimate the concentrations of IL-1β and IL-10. All samples were saved at −80°C in a deep freezer (Angelantoni Life Science, UK).
At the time of sample analysis, frozen saliva samples were allowed to thaw at room temperature. The concentrations of IL-1β and IL-10 in the samples were determined using ELISA kits (Cloud-Clone Corp, USA; IL-1β: SEA563Hu; IL-10: SEA056Hu) according to manufactural instructions. Standard curves were plotted, and regression equations were derived to convert the optical density values of IL-1β and IL-10 in the samples to their respective quantities in picograms per milliliter (pg/ml).
2.4. Statistical Analysis
The distribution of continuous variables was checked using the Shapiro–Wilk test. Mean ± SD was used to describe the continuous data, while the frequency and percentage were used for describing categorical variables. Kruskal–Wallis test was used to compare among groups with Bonferroni post hoc analysis for pairwise comparisons. While the Mann–Whitney U-test was used for comparing two groups. Categorical variables were analyzed using Chi-square test (X2). The Correlations between clinical parameters and biochemical variables were performed using Spearman's coefficient correlation test. Binary logistic regression analysis was applied to explore the association of IL-1β and IL-10 as independent variables to the study groups, which was adjusted by age. The receiver operating characteristic curve (ROC) and area under the curve (AUC) were used to explore the sensitivity, specificity, and cutoff values for each biomarker, as well as the ratio between the biomarkers for discriminating between groups. The Youden index was used to determine the optimal cutoff value for each tested biomarker [30]. The latter statistical test was accomplished after dichotomizing the concentration of each biomarker as “0” for health and “1” for periodontal disease. All the statistical analyses of the data were performed and processed with GraphPad Prism software (version 9.0). Statistical difference was considered significant when p < 0.05.
3. Result
A total of 135 participants were recruited for this study who were distributed into healthy control (n = 45), stable periodontitis (n = 39) and unstable periodontitis (n = 51) groups. The participants in the healthy control group were younger than participants in the other groups. The distribution of sex and mean BMI were not significantly different among the groups. The basic characteristics of the study sample are shown in Table 1. Furthermore, PI and BOP were significantly higher in unstable periodontitis than in other groups. However, no significant difference was detected between the healthy control group and the stable periodontitis group. Deeper pockets were observed in the unstable periodontitis group compared to the stable periodontist group (p < 0.05). On the other hand, no significant difference was found between periodontitis groups regarding CAL measurements (Table 1).
A significantly higher salivary level of IL-1β was detected in the unstable periodontitis group (426 ± 59 pg/ml) than in the stable periodontitis group (247 ± 55 pg/ml; p < 0.001) and healthy control group (204 ± 36 pg/ml; p < 0.001) (Figure 1A); moreover, the level was significantly higher in the stable periodontitis group than healthy control group (p < 0.05). In contrast, the lowest salivary level of IL-10 was detected in the unstable group (164 ± 21.8 pg/ml) compared to the other groups. No significant difference (p > 0.05) in the salivary level of IL-10 was found between the stable periodontitis group (317.04 ± 59.8 pg/ml) and healthy control group (360.7 ± 80.5 pg/ml), as shown in Figure 1B. The ratio between the above-mentioned biomarkers was found to be significantly different among the groups (p < 0.001); higher in unstable periodontitis group followed by stable periodontitis and healthy control groups (Figure 1C).
After adjusting the effect of age, an increased salivary level of IL-1β was found to be associated with an increased probability to have periodontitis (odd ratio = 1.033; p = 0.004). Obviously, an increase by one unit of this marker was associated with the likelihood of the incidence of unstable (odd ratio = 1.979) and stable (odd ratio = 1.989) periodontitis from health, respectively. Similarly, an elevated level of IL-1β was also detected to be significantly associated (β coefficient = 0.079; p = 0.004) with the incidence of unstable from stable periodontitis. Such relations were found not significant for IL-10 (Table 2). However, both IL-1β and IL-10 were found to be positively and negatively (respectively) associated with the clinical periodontal parameters. While the correlation between the levels of salivary IL-1β and IL-10 was negative and significant, as illustrated in Table 3.
Table 4 and Figure 2 illustrate the ROC curve, AUC, sensitivity, specificity, and cutoff values of salivary biomarkers and their ratio to differentiate periodontal health from periodontitis and discriminate the current status of periodontitis. Both IL-1β and IL-10 biomarkers, as well as their ratio, showed high sensitivity and specificity and excellent potential to discriminate periodontal heath from unstable periodontitis (AUC = 0.99, 0.96, and 1.00) and stable periodontitis from unstable periodontitis (AUC 0.98, 0.99, and 1.00), respectively. Similarly, they exhibited the same pattern in discriminating periodontal heath from periodontitis (stable and unstable) (AUC = 0.91, 0.85, and 0.90, respectively). These salivary biomarkers and their ratio showed an accepted potential to discriminate between periodontal health and stable periodontitis.
Interestingly, the IL-1β/IL-10 ratio showed an improved diagnostic potential (AUC of 1, p < 0.0001) to discriminate between periodontal health from unstable periodontitis (cutoff value >1.35) and stable periodontitis from unstable periodontitis (cutoff value >1.55) (Table 4).
4. Discussion
In the current study, analysis of the data showed that salivary IL-1β, IL-10, and IL-1β/IL-10 ratio had high accuracy in differentiating periodontal health from periodontitis. Also, they demonstrated high sensitivity and specificity to discriminate unstable periodontitis from stable periodontitis and periodontal health. This case–control study aims to assess the potential accuracy of the aforementioned salivary proteins and their ratio as diagnostic biomarkers.
In the recent classification of periodontal diseases, a new entity called stable periodontitis was introduced, which defines a periodontium that has restored healthy status after successful periodontal therapy. It could be differentiated from unstable periodontitis either by the presence of PPD >4 mm or PPD equal to 4 mm, which shows bleeding during examination [20]. Using manual probing to measure periodontal parameters is not a sensitive procedure. For instance, forceful probing could induce bleeding or incorrectly record a deeper pocket depth. Such issues are not uncommon during probing [31]. A lack of accuracy in identifying stable from unstable periodontium leads to drastically changing treatment plans from supportive periodontal therapy to active periodontal therapy. Therefore, a precise diagnosis is essential for customizing the treatment approach appropriately [32]. In the past several decades, using biomarkers found in oral fluid to distinguish between periodontal health and disease has shown promising findings [21].
In this study, saliva has been chosen as a biomarker source due to the ease of collection and handling as well as obtaining adequate volumes of samples. Additionally, salivary biomarkers reflect all local and systemic conditions and are suited for screening purposes [33–35]. Recently, point-of-care (POC) mouth rinse tests, such as the active MMP-8 POC test, have been incorporated into the new classification system for periodontitis [36]. Although they are rapid, sensitive, specific, and robust, they are costly to use in routine clinical practice compared to traditional diagnostic methods [32]. This study exclusively used biomarkers with clear evidence of correlation with the pathogenesis of periodontal disease.
In this study, IL-1β was chosen as a robust diagnostic biomarker to discriminate healthy from diseased periodontal tissue. It is strongly linked to the severity and progression of periodontal diseases, tooth loss, and tissue response to periodontal therapy [37, 38]. IL-1β has been observed to upregulate the expression of many cytokines involved in the degradation of tissues and bone resorption, such as collagenases and prostaglandins [37, 38]. Furthermore, IL-1β increases the expression of adhesion molecules, which in turn exacerbates inflammatory reactions and increases the extent of tissue degradation by promoting the recruitment of inflammatory cells [39]. It is not surprising that salivary levels of IL-1β were increased in the periodontitis groups in this study, as previously reported [40–43]. Accordingly, salivary IL-1β has been reported to exhibit a potential to distinguish periodontitis from periodontal health with varying sensitivity (54%–88%) and specificity (52%–100%) [41, 44–46]. These previous reports agree with the current study findings. Moreover, this explanation might also interpret the significantly higher level of IL-1β in unstable periodontitis than in stable periodontitis and its accuracy in discriminating these two periodontitis statuses.
IL-10 is a potent anti-inflammatory mediator that suppresses both immunoproliferative and inflammatory reactions. IL−10 inhibits the production of cytokines, such as IL-1, IL-6, and TNF-α, by T-helper1 cells and suppresses the production of collagenase, gelatinase, and nitric oxide [18, 47]. In this study, the level of IL-10 was lower in periodontitis patients than in peers with healthy periodontium; this finding is in accordance with what has been reported in the literature [48–50]. Scarel-Caminaga et al. proposed that individuals who produce a lot of IL-10 might be more resistant to periodontitis due to its anti-inflammatory effect [51]. Moreover, IL-10 levels have been reported to be elevated 2 weeks [52], 6 weeks [53], and 2 months [54] after nonsurgical periodontal therapy. Therefore, a higher salivary level of IL-10 was expected in subjects with healthy periodontium or periodontitis patients who had completed periodontal therapy, i.e., stable periodontitis. However, contrary findings have also been reported: periodontitis patients have higher levels of IL-10 than healthy controls [18, 55–57]. This controversy encourages the authors to investigate the salivary level of this biomarker in this study.
In this study, the IL-1β/IL-10 ratio exhibited high sensitivity and specificity for potentially discriminating periodontitis from healthy groups as well as for distinguishing unstable from stable periodontitis groups. No doubt, tissue affected by periodontitis is associated with an imbalance between pro and anti-inflammatory cytokines (IL-17, IL-23, IL-6, IL-8, TNF-α, and interferon-γ) in favor of pro-inflammatory burden [48, 49, 58]. These findings indicate that the combination of biomarkers not only enhances the accuracy of diagnosis compared with a single biomarker but also attains sufficient reliability for diagnosing periodontitis.
The concentration of salivary IL-1β was found to be positively associated with clinical periodontal parameters (PL, BOP, PPD, and CAL), as previously reported [18, 41, 59, 60]. This significant correlation highlights the essential function of IL-1β in the host immune response related to periodontitis, particularly in patients with identified IL-1β gene variants [61, 62]. Interestingly, the means of BOP and PPD were significantly different between stable and unstable periodontitis patients. One can conclude that IL-1β is more related to the BOP and PPD parameters, which could discriminate among periodontitis statuses. Furthermore, salivary IL-10 was found to be negatively related to BOP, PPD, and CAL. This finding is not surprising as IL-10 is a potent anti-inflammatory cytokine [18, 47] and is expected to be elevated when clinical periodontal parameters are improved, as previously reported [10, 18, 63].
As a limitation, smokers and patients having systemic diseases were excluded in this study. This fact impacts the external validity of this study, as its findings cannot be generalized to the population. However, excluding such individuals was necessary to eliminate biases and confounding factors. Larger-scale studies involving participants without exclusion are highly suggested. Another limitation is that this study only assessed host-derived salivary biomarkers while integrating bacterial and host-derived salivary biomarkers might provide a better realizable diagnostic approach.
5. Conclusion
Despite the limitations of this study, salivary IL-1β and IL-10 potentially possess a high diagnostic power for discriminating periodontal health from periodontitis as well as for distinguishing stable from unstable periodontitis. This diagnostic power is further increased when IL-1β/IL-10 is employed.
6.1. Scientific Rationale for the Study
The conventional periodontitis diagnostic approach is based on clinical parameters that are inaccurate in detecting early periodontitis, and they could potentially mirror the previous tissue damage. Salivary biomarkers have been found to have the potential to enhance screening, diagnosis, and monitoring of periodontitis.
6.2. Principle Findings
IL-1β and IL-10 have great diagnostic capabilities when used separately or in combination for the diagnosis of periodontitis.
6.3. Practical Implications
The IL-1β/IL-10 ratio in saliva exhibits a valuable potential for diagnosing periodontitis and in discriminating periodontitis stability.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Conflicts of Interest
The authors declare no conflicts of interest.
Author Contributions
Conception and design were done by Hayder Raad Abdulbaqi. Data collection was done by Zainab J. Raheem. Analysis and interpretation of data were done by both authors. Drafting the manuscript was done by Zainab J. Raheem. Revising the manuscript was done by Hayder Raad Abdulbaqi. Both authors read and approved the final version of the manuscript.
Funding
This research was self-funded.
Acknowledgments
This research was self-funded.
References
1 KassebaumN. J. BernabéE. DahiyaM. BhandariB. MurrayC. J. L. MarcenesW. Global Burden of Severe Periodontitis in 1990–2010: A Systematic Review and Meta-Regression Journal of Dental Research 201493111045105310.1177/00220345145524912-s2.0-8491004922525261053PMC4293771
2 BernabeE. MarcenesW. HernandezC. R. Global, Regional, and National Levels and Trends in Burden of Oral Conditions from 1990 to 2017: A Systematic Analysis for the Global Burden of Disease 2017 Study Journal of Dental Research 202099436237310.1177/002203452090853332122215PMC7088322
3 GrazianiF. TsakosG. Patient-Based Outcomes and Quality of Life Periodontology 2000 202083127729410.1111/prd.1230532385874
4 AsherS. StephenR. MäntyläP. SuominenA. L. SolomonA. Periodontal Health, Cognitive Decline, and Dementia: A Systematic Review and Meta-Analysis of Longitudinal Studies Journal of the American Geriatrics Society 20227092695270910.1111/jgs.1797836073186PMC9826143
5 RaheemZ. J. AhmedM. A. Assessment of Serum Levels of MMP- 8 and hs CRP in Chronic Periodontitis Patients in Relation to Atherosclerotic Cardiovascular Disease Journal of Baghdad College of Dentistry 201426414114610.12816/0015154
6 PapapanouP. N. SanzM. BuduneliN. Periodontitis: Consensus Report of Workgroup 2 of the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions Journal of Periodontology 201889S173S1822992695110.1002/JPER.17-0721
7 SaliemS. S. BedeS. Y. CooperP. R. AbdulkareemA. A. MilwardM. R. AbdullahB. H. Pathogenesis of Periodontitis—A Potential Role for Epithelial-Mesenchymal Transition Japanese Dental Science Review 20225826827810.1016/j.jdsr.2022.09.00136159185PMC9489739
8 SlotsJ. Periodontitis: Facts, Fallacies and the Future Periodontology 2000 201775172310.1111/prd.122212-s2.0-8502667584528758294
9 EbersoleJ. L. DawsonD. Emecen-HujaP. The Periodontal War: Microbes and Immunity Periodontology 2000 20177515211510.1111/prd.122222-s2.0-8502666125628758303
10 PanW. WangQ. ChenQ. The Cytokine Network Involved in the Host Immune Response to Periodontitis International Journal of Oral Science 201911310.1038/s41368-019-0064-z30PMC682866331685798
11 SalahR. AbdulbaqiH. R. Short-Term (4 Day) Effects of Oral Rinsing With Miswak and Green Tea on Gingival Crevicular Fluid Flow and IL-1β Levels: A Pilot Study Healthcare 202311210.3390/healthcare11020226226PMC985913236673594
12 ZhuH. LinX. ZhengP. ChenH. Inflammatory Cytokine Levels in Patients With Periodontitis and/or Coronary Heart Disease International Journal of Clinical and Experimental Pathology 2015822214222025973132PMC4396332
13 RangbullaV. NirolaA. GuptaM. BatraP. GuptaM. Interleukin-1β and MMP-8 as Salivary Biomarkers in Chronic Periodontitis Patients The Chinese Journal of Dental Research 2017201435110.3290/j.cjdr.a377412-s2.0-8502214314828232966
14 KimJ.-Y. KimH.-N. Changes in Inflammatory Cytokines in Saliva After Non-Surgical Periodontal Therapy: A Systematic Review and Meta-Analysis International Journal of Environmental Research and Public Health 202118110.3390/ijerph18010194194PMC779573833383828
15 ZhangX. TengY.-T. A. Interleukin-10 Inhibits Gram-Negative-Microbe-Specific Human Receptor Activator of NF-κB Ligand-Positive CD4+-Th1-Cell- Associated Alveolar Bone Loss In Vivo Infection and Immunity 20067484927493110.1128/IAI.00491-062-s2.0-3374663639516861684PMC1539589
16 MegeJ.-L. MeghariS. HonstettreA. CapoC. RaoultD. The Two Faces of Interleukin 10 in Human Infectious Diseases The Lancet Infectious Diseases 20066955756910.1016/S1473-3099(06)70577-12-s2.0-3374762209616931407
17 MohammedH. A. AbdulkareemA. ZardawiF. GulS. Determination of the Accuracy of Salivary Biomarkers for Periodontal Diagnosis Diagnostics 2022121010.3390/diagnostics121024852485PMC960093136292174
18 TanA. GürbüzN. C. ÖzbalciF. KoşkanÖ. C. Yetkin AyZ. Increase in Serum and Salivary Neutrophil Gelatinase-Associated Lipocalin Levels With Increased Periodontal Inflammation Journal of Applied Oral Science 20202810.1590/1678-7757-2020-0276PMC752141932997091
19 CafferataE. A. JerezA. VernalR. MonasterioG. PandisN. FaggionC. M.Jr. The Therapeutic Potential of Regulatory T Lymphocytes in Periodontitis: A Systematic Review Journal of Periodontal Research 201954320721710.1111/jre.126292-s2.0-8505713843830474205
20 TonettiM. S. GreenwellH. KornmanK. S. Staging and Grading of Periodontitis: Framework and Proposal of a New Classification and Case Definition Journal of Periodontology 201889 Suppl 1S1S159S17210.1002/JPER.18-00062-s2.0-8505205859729926952
21 RakicM. PejcicN. PerunovicN. VojvodicD. A Roadmap Towards Precision Periodontics Medicina 202157310.3390/medicina57030233233PMC799912833802358
22 TsuchidaS. Proteome Analysis of Molecular Events in Oral Pathogenesis and Virus: A Review With a Particular Focus on Periodontitis International Journal of Molecular Sciences 2020211510.3390/ijms211551845184PMC743269332707841
23 PreianòM. SavinoR. VillellaC. PelaiaC. TerraccianoR. Gingival Crevicular Fluid Peptidome Profiling in Healthy and in Periodontal Diseases International Journal of Molecular Sciences 2020211510.3390/ijms211552705270PMC743212832722327
24 XiangX. SowaM. G. IacopinoA. M. An Update on Novel Non-Invasive Approaches for Periodontal Diagnosis Journal of Periodontology 201081218619810.1902/jop.2009.0904192-s2.0-7764920621820151796
25 ChappleI. L. MealeyB. L. Van DykeT. E. Periodontal Health and Gingival Diseases and Conditions on an Intact and a Reduced Periodontium: Consensus Report of Workgroup 1 of the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions Journal of Periodontology 201889S74S842992694410.1002/JPER.17-0719
26 DietrichT. OwerP. TankM. Periodontal Diagnosis in the Context of the 2017 Classification System of Periodontal Diseases and Conditions—Implementation in Clinical Practice British Dental Journal 20192261162210.1038/sj.bdj.2019.32-s2.0-8505982874230631188
27 O’LearyT. J. DrakeR. B. NaylorJ. E. The Plaque Control Record Journal of Periodontology 197243110.1902/jop.1972.43.1.382-s2.0-0015265378384500182
28 AinamoJ. BayI. Problems and Proposals for Recording Gingivitis and Plaque International Dental Journal 19752542292351058834
29 HensonB. S. WongD. T. Collection, Storage, and Processing of Saliva Samples for Downstream Molecular Applications Methods in Molecular Biology 2010666213010.1007/978-1-60761-820-1_220717775
30 SchistermanE. F. PerkinsN. J. LiuA. BondellH. Optimal Cut-Point and Its Corresponding Youden Index to Discriminate Individuals Using Pooled Blood Samples Epidemiology 2005161738110.1097/01.ede.0000147512.81966.ba2-s2.0-1374425154315613948
31 LaugischO. AuschillT. M. HeumannC. SculeanA. ArweilerN. B. Clinical Evaluation of a New Electronic Periodontal Probe: A Randomized Controlled Clinical Trial Diagnostics 202212110.3390/diagnostics1201004242PMC877492435054209
32 GulS. S. AbdulkareemA. A. ShaA. M. RawlinsonA. Diagnostic Accuracy of Oral Fluids Biomarker Profile to Determine the Current and Future Status of Periodontal and Peri-Implant Diseases Diagnostics 2020101010.3390/diagnostics10100838838PMC760312933081038
33 de LimaC. L. AcevedoA. C. GrisiD. C. TabaM.Jr GuerraE. De Luca CantoG. Host-Derived Salivary Biomarkers in Diagnosing Periodontal Disease: Systematic Review and Meta-Analysis Journal of Clinical Periodontology 201643649250210.1111/jcpe.125382-s2.0-8496972214326926312
34 WeiF. WongD. T. W. Point-of-Care Platforms for Salivary Diagnostics The Chinese Journal of Dental Research 201215171522866276
35 MahmoodA. ShukriM. Assessment of Salivary Elements (Zinc, Copper and Magnesium) Among Groups of Patients With Rheumatoid Arthritis and Chronic Periodontitis and Its Correlation to Periodontal Health Status Journal of Baghdad College of Dentistry 2012243
36 SorsaT. AlassiriS. GrigoriadisA. Active MMP-8 (aMMP-8) as a Grading and Staging Biomarker in the Periodontitis Classification Diagnostics 202010210.3390/diagnostics1002006161PMC716892431979091
37 AralK. BerdeliE. CooperP. R. Differential Expression of Inflammasome Regulatory Transcripts in Periodontal Disease Journal of Periodontology 202091560661610.1002/JPER.19-022231557327
38 ArroyoE. Oliveira-AlvesM. G. Chamorro-PetronacciC. M. Protein-Based Salivary Biomarkers for the Diagnosis of Periodontal Diseases: Systematic Review and Meta-Analysis Journal of Taibah University Medical Sciences 202318473774710.1016/j.jtumed.2022.12.00436852252PMC9957757
39 PreshawP. M. TaylorJ. J. How Has Research Into Cytokine Interactions and Their Role in Driving Immune Responses Impacted Our Understanding of Periodontitis? Journal of Clinical Periodontology 20113860842132370510.1111/j.1600-051X.2010.01671.x
40 ReddahiS. BouzianeA. RidaS. TliguiH. EnnibiO. Salivary Biomarkers in Periodontitis Patients: A Pilot Study International Journal of Dentistry 20222022910.1155/2022/36645163664516PMC897094935368315
41 AbdullameerM. A. AbdulkareemA. A. Salivary Interleukin-1β as a Biomarker to Differentiate Between Periodontal Health, Gingivitis, and Periodontitis Minerva Dental and Oral Science 202372522122910.23736/S2724-6329.23.04778-237162330
42 KimJ. Y. KimK. R. KimH. N. The Potential Impact of Salivary IL-1 on the Diagnosis of Periodontal Disease: A Pilot Study Healthcare 20219610.3390/healthcare9060729729PMC823186734199256
43 KaushikR. YeltiwarR. K. PushpanshuK. Salivary Interleukin-1β Levels in Patients With Chronic Periodontitis Before and After Periodontal Phase I Therapy and Healthy Controls: A Case-Control Study Journal of Periodontology 20118291353135910.1902/jop.2011.1004722-s2.0-8005302095521235331
44 EbersoleJ. L. NagarajanR. AkersD. MillerC. S. Targeted Salivary Biomarkers for Discrimination of Periodontal Health and Disease(s) Frontiers in Cellular and Infection Microbiology 2015510.3389/fcimb.2015.000622-s2.0-8500621393562PMC454132626347856
45 EbersoleJ. L. SchusterJ. L. StevensJ. Patterns of Salivary Analytes Provide Diagnostic Capacity for Distinguishing Chronic Adult Periodontitis From Health Journal of Clinical Immunology 201333127127910.1007/s10875-012-9771-32-s2.0-8487644151722926406PMC3788639
46 WuY. C. NingL. TuY. K. Salivary Biomarker Combination Prediction Model for the Diagnosis of Periodontitis in a Taiwanese Population Journal of the Formosan Medical Association 2018117984184810.1016/j.jfma.2017.10.0042-s2.0-8503337391429129647
47 ZhangQ. ChenB. YanF. Interleukin-10 Inhibits Bone Resorption: A Potential Therapeutic Strategy in Periodontitis and Other Bone Loss Diseases BioMed Research International 20142014510.1155/2014/2848362-s2.0-84896132694284836PMC394766424696846
48 AcharyaA. B. ThakurS. MuddapurM. V. KulkarniR. D. Cytokine Ratios in Chronic Periodontitis and Type 2 Diabetes Mellitus Diabetes & Metabolic Syndrome: Clinical Research & Reviews 201711427727810.1016/j.dsx.2016.12.0072-s2.0-8500838511927989515
49 MirandaT. S. HeluyS. L. CruzD. F. The Ratios of Pro-Inflammatory to Anti-Inflammatory Cytokines in the Serum of Chronic Periodontitis Patients With and Without Type 2 Diabetes and/or Smoking Habit Clinical Oral Investigations 201923264165010.1007/s00784-018-2471-52-s2.0-8504662091729737428
50 PassojaA. PuijolaI. KnuuttilaM. Serum Levels of Interleukin-10 and Tumour Necrosis Factor-α in Chronic Periodontitis Journal of Clinical Periodontology 2010371088188710.1111/j.1600-051X.2010.01602.x2-s2.0-7795655589320718895
51 Scarel-CaminagaR. M. TrevilattoP. C. SouzaA. P. BritoR. B. CamargoL. E. A. LineS. R. P. Interleukin 10 Gene Promoter Polymorphisms Are Associated With Chronic Periodontitis Journal of Clinical Periodontology 200431644344810.1111/j.1600-051X.2004.00500.x2-s2.0-294263531215142213
52 GümüşP. NizamN. LappinD. F. BuduneliN. Saliva and Serum Levels of B-Cell Activating Factors and Tumor Necrosis Factor-α in Patients With Periodontitis Journal of Periodontology 201485227028010.1902/jop.2013.1301172-s2.0-8488596722723701482
53 PrakasamS. SrinivasanM. Evaluation of Salivary Biomarker Profiles Following Non-Surgical Management of Chronic Periodontitis Oral Diseases 201420217117710.1111/odi.120852-s2.0-8489381545623496245
54 Öngöz DedeF. BalliU. Bozkurt DoğanŞ. GüvenB. Interleukin-32 Levels in Gingival Crevicular Fluid and Saliva of Patients With Chronic Periodontitis After Periodontal Treatment Journal of Periodontal Research 201752339740710.1111/jre.124042-s2.0-8499468354627501514
55 VarmaS. R. ThomasB. RameshA. Estimation of Sialic Acid and IL10 Levels in Stage 1 and 2 Periodontitis Patients International Journal of Dentistry 20192019510.1155/2019/29171242917124PMC690688331871458
56 TâlvanE. MohorC. ChisnoiuD. CristeaV. CâmpianR. Expression of Interleukin (IL)-1β, IL-8, IL-10 and IL-13 in Chronic Adult Periodontitis Progression Archives of Medical Science 201793418
57 MohammedM. A. AbbasR. F. AkramH. M. Salivary IL-17 and IL-10 as Potential Diagnostic Biomarkers of Different Stages of Periodontitis in Smoker and Nonsmoker Patients European Journal of Dentistry 202418125326410.1055/s-0043-176815437172945PMC10959607
58 Al-GhurabiB. ShakerZ. Al-HassanA. Clinical Relevance of IL1B\IL-10 and TNF-Alpha\IL-10 Ratio in Chronic Periodontitis Patients2018
59 Tobón-ArroyaveS. Jaramillo-GonzálezP. Isaza-GuzmanD. Correlation Between Salivary IL-1β Levels and Periodontal Clinical Status Archives of Oral Biology 200853434635210.1016/j.archoralbio.2007.11.0052-s2.0-3974919020518155182
60 SánchezG. A. MiozzaV. A. DelgadoA. BuschL. Salivary IL-1β and PGE 2 as Biomarkers of Periodontal Status, Before and After Periodontal Treatment Journal of Clinical Periodontology 201340121112111710.1111/jcpe.121642-s2.0-8488731868324118119
61 RibeiroM. S. M. PachecoR. B. A. FischerR. G.ães MacedoJ. M. B. Interaction of IL1B and IL1RN Polymorphisms, Smoking Habit, Gender, and Ethnicity With Aggressive and Chronic Periodontitis Susceptibility Contemporary Clinical Dentistry 20167334935610.4103/0976-237X.1885602-s2.0-8498465018727630500PMC5004549
62 AmirisettyR. PatelR. P. DasS. SarafJ. JyothyA. MunshiA. Interleukin 1β (+3954, -511 and -31) Polymorphism in Chronic Periodontitis Patients From North India Acta Odontologica Scandinavica 201573534334710.3109/00016357.2014.9619582-s2.0-8492932319225252591
63 SyrjäläinenS. GursoyU. K. GursoyM. Salivary Cytokine Biomarker Concentrations in Relation to Obesity and Periodontitis Journal of Clinical Medicine 201981210.3390/jcm8122152PMC694734031817464