Introduction

Periodontitis represents a multifaceted immune-inflammatory pathology caused by bacterial biofilm [1]. The supporting apparatus of the dentition is adversely influenced by the accumulation of biofilm, particularly affecting the alveolar bone and periodontal ligament [1]. Periodontal disease demonstrates a significant association with a spectrum of systemic conditions, including disorders of the cardiovascular, renal, autoimmune, pulmonary, endocrine, and neurological systems [2, 3].

At its core, diabetes mellitus (DM) arises from disruptions in normal insulin physiology, either through cellular resistance to insulin or a deficit in its production. The resulting hyperglycaemia is the primary clinical feature, and landmark studies such as the UK Prospective Diabetes Study have firmly established a direct relationship between elevated blood glucose levels and the deve­lopment of devastating long-term complications, leading to increased mortality and reduced lifespan [4, 5].

There are several DM-related systemic complications, such as micro- and macrovascular pathology, delayed wound healing, as well as DM-associated reti­nopathy and nephropathy [4, 6]. Among the well-documented complications of DM, periodontitis is now classified as the sixth [6, 7].

Periodontitis and DM exhibit a two-way, mutually influential relationship. Several studies observed that diabetic individuals had elevated risk of periodontitis than healthy ones. Consequently, periodontitis exerts a detrimental impact on glycaemic regulation and the progression of DM [1, 7-9].

Conventional clinical parameters, including probing depth and clinical attachment level, have limitations in accurately predicting the progression of the disease and often fail to capture the underlying biological disease activity, which can be driven by shifts in the subgingival microbiota that are not immediately reflected in the clinical examination [10-12]. Therefore, assessing biomarkers that correlate with clinical parameters offers a promising approach for more precise assessment of disease severity and progression, potentially enhancing diagnostic accuracy and treatment planning. Given the strong correlation between periodontitis and DM, both characterised by pronounced inflammatory responses, studies have increasingly focused on pro-inflammatory mediators as potential biomarkers to better understand and link these two conditions [4, 9].

Research has shown that hyperglycaemia can directly enhance the inflammatory response within the infected periodontium. As a result, diabetic individuals with periodontal disease tend to demonstrate elevated levels of proinflammatory cytokines in their saliva and gingival tissues compared to non-diabetic patients [4, 13].

Shared inflammatory pathways link periodontitis and DM, characterised notably by elevated concentrations of cytokines such as interleukin (IL)-1β, tumor necrosis factor alpha (TNF-α), and IL-17A. [14]. Ramseier et al. [15] demonstrated that salivary biomarkers and perio­dontopathic bacteria have a diagnostic relevance in identifying periodontal disease severity. Kinney et al. [16] conducted a longitudinal study on a consistent patient cohort, demonstrating that salivary biomarkers and
periodontal bacteria can effectively predict the progression of periodontal disease.

Despite growing interest in salivary inflammatory biomarkers, there remains limited evidence regarding the simultaneous evaluation of IL-17A, IL-18, and IL-1β levels in patients with periodontitis, particularly in the presence of controlled type 2 diabetes mellitus (T2DM). Furthermore, while prior research has explored links between individual cytokines and periodontal disease severity, few studies have examined their relationship with the 2017 American Academy of Periodontology (AAP)/European Federation of Periodontology (EFP) staging system, and none has evaluated their association with periodontal disease grading.

This knowledge gap limits understanding of the potential diagnostic and stratification value of these biomarkers across different disease profiles. Consequently, this investigation was designed to assess salivary profiles of IL-17A, IL-18, and IL-1β in periodontitis patients with and without T2DM and to explore their associations with periodontal stage and grade according to the 2017 AAP/EFP classification.

Objectives

To evaluate the levels of salivary IL-18, IL-17A, and IL-1β in periodontitis patients with and without T2DM.

Material and methods

Study design

This cross-sectional study was conducted following STROBE guidelines [17] to compare salivary inflammatory biomarker levels (IL-17A, IL-18, and IL-1β) in perio­dontitis patients with and without T2DM. The research protocol was approval by the Research Ethics Committee, Faculty of Dentistry, Alexandria University (IRB No. 1033-IORG0008839) in accordance with Declaration of Helsinki and other ethical guidelines adopted by the Research Ethics Committee of the Faculty of Dentistry, Alexandria University. The purpose and nature of the study was explained, and, prior to any procedure, informed consent was obtained from patients who agreed to participate in this study.

A total sample of 80 patients diagnosed with perio­dontitis were recruited from the outpatient clinic of the Department of Periodontology and Oral Medicine, Faculty of Dentistry, Alexandria University. Patients were categorised into two groups: Group I (T2DM-P) – 40 patients with mild to moderate or severe periodontitis who were also diagnosed with T2DM; and Group II (HP) – 40 systemically healthy patients with periodontitis.

Inclusion criteria included T2DM patients (diagnosed for at least the past 3 years), both genders, with ages ranging from 40 to 60 years, diagnosed clinically with periodontal disease [18]. Only patients with controlled T2DM (glycated haemoglobin [HbA_1c] ≤ 7%) [19] were included to minimise metabolic variability and reduce the confounding influence of uncontrolled hyperglycaemia on inflammatory biomarker expression.

Exclusion criteria included smokers, patients with uncontrolled metabolic disease (HbA_1c > 7%), immuno-compromised patients, and pregnant or lactating women.

The required sample size was determined based on similar methodologies reported in prior research [20, 21], using a power of 80% and a confidence interval of 95% to detect differences in inflammatory biomarker levels. This calculation yielded a minimum required sample size of 26 participants per study group. To enhance the robustness of the study and to account for potential laboratory or data attrition errors, the final sample size was set at 40 participants per group, resulting in a total of 80 participants (40 diabetic and 40 non-diabetic patients with periodontitis). This adjustment ensures sufficient statistical power and reliability of the results across all measured outcomes [22]. The biochemical assessment of the level of inflammatory mediators and statistical ana­lysis of the results were carried out by a blinded operator. Effect size assumptions for the current sample size calculation were derived from biomarker differences reported in prior studies evaluating salivary IL-17A, IL-18, and IL-1β in periodontitis and diabetic populations. In the study by Özçaka et al. [20], significant differences were observed in salivary IL-17 (p = 0.025) and IL-18 (p = 0.009) between chronic periodontitis patients and healthy controls, with between-group mean differences indicating moderate-to-large effects. Similarly, Liu et al. [21] reported that the IL-17A salivary profile differed significantly between periodontitis and non-perio­dontitis subjects within the control group (p = 0.031), and that IL-18 levels demonstrated significant associa­tions with metabolic parameters (β = 0.270-0.293). Based on these reported magnitudes of difference and regression effect sizes, a conservative moderate expected effect size (Cohen’s d ≈ 0.65-0.80) was used for calculating the required sample size. Using 80% power and a 95% confidence level, this indicated a minimum of 26 participants per group. To enhance robustness and accommodate potential laboratory variability, this number was increased to 40 participants per group.

Assessment of periodontal clinical parameters

All participants underwent a full-mouth clinical examination, excluding third molars. The following parameters were assessed at six sites per tooth: mesiobuccal, midbuccal, distobuccal, mesiolingual, midlingual, and distolingual, gingival index (GI) [23], bleeding upon probing (BoP), periodontal probing depth (PPD), and clinical attachment loss (CAL). A pre-calibrated examiner did all periodontal assessments (intraclass correlation coefficient > 0.92) using a periodontal probe (UNC-15; Hu-Friedy, Chicago, IL, USA).

Employing a comprehensive clinical and radiographic evaluation, two calibrated periodontists independently categorised participants into either a mild-to-moderate (Stage I-II) or a severe (Stage III-IV) perio­dontitis group, following the 2017 AAP/EFP classification criteria [18]. Recorded clinical parameters included probing depth (PD), CAL, BOP, and radiographic bone loss (expressed as a percentage of root length). Inter-examiner agreement was evaluated using Cohen’s kappa statistic (κ = 0.9), demonstrating “almost perfect” consensus. Discrepancies (< 5% of cases) were resolved through discussion with a third senior periodontist. This standardised approach ensured consistent stratification of disease severity for comparative analyses.

Glycaemic control evaluation

HbA_1c and body mass index (BMI) [24] were assessed for all participants at the beginning of the study. BMI was computed by dividing each participant’s weight (kg) by their height squared (m²).

Analysis of salivary biomarkers

Participants, after fasting overnight, attended a morning session for saliva collection between 9:00 AM and 12:00 PM. Whole saliva samples were obtained via the passive drooling (spitting) technique [25, 26], allowing the collection of both stimulated and unstimulated saliva. Parti­cipants were instructed to expectorate approximately 5 ml of saliva into a sterile tube kept on ice. Immediately after collection, for protein stabilisation, a protease inhibitor cocktail (Roche Diagnostics GmbH, Mannheim, Germany) was incorporated into the samples. Samples were centrifuged at 10,000 g for 10 minutes at 4°C. The clarified supernatant was then aliquoted and cryopreserved at −80°C for subsequent biomarker quantification.

To minimise the influence of pre-analytical variability on salivary cytokine levels, a one-hour pre-collection fast was required, prohibiting all intake (except water), smoking, and oral hygiene practices. Parti­cipants were also advised to maintain normal hydration status the evening before sampling and perform a gentle oral rinse with water 10 minutes prior to collection to remove debris without stimulating salivary flow. These standardised instructions helped ensure consistent sampling conditions across participants.

Quantification of salivary cytokines

Salivary concentrations of IL-17A, IL-18, and IL-1β were quantified using commercially available human-specific ELISA kits (MOLEQULE-ON, Auckland, New Zealand). The assay was performed in 96-well plates (Nunc Maxisorp) according to the manufacturer’s protocol, with absorbance measured using an xMark microplate spectrophotometer (BIO-RAD, USA). All samples were analysed in triplicate.

All measurements were conducted in triplicate in strict adherence to the manufacturer’s protocols. All target cytokines were quantified using a sandwich ELISA format, as provided in the respective commercial kits. Saliva samples were allowed to liquefy at room temperature and were then processed as per the provided protocols. For the ELISA assays, 100 µl of each saliva sample was diluted at a ratio of 1 : 2.

Following the addition of 100 µl of diluted sample per well, plates were incubated under cytokine-specific conditions: 120 minutes at 25°C for IL-17A, and 90 minutes at 37°C for IL-18 and IL-1β. Following the initial incubation, wells were washed, and 100 µl of biotin-conjugated anti-human IL-17A antibody was added and incubated for 1 hour at 25°C for IL-17A, and at a lower temperature (specified by the manufacturer) for IL-18 and IL-1β.

Following a wash step to remove unbound antibody, 100 µl of streptavidin-horseradish peroxidase (HRP) conjugate was added to every well and incubated for 30 minutes at 25°C for IL-17A and at 37°C for IL-18 and IL-1β. Subsequently, 100 µl of substrate solution was added and incubated for 15 minutes in the dark at 25°C for IL-17A, and at 37°C for IL-18 and IL-1β.

Final cytokine levels (IL-17A, IL-18, and IL-1β) were interpolated from respective standard curves, and they are reported in picograms per millilitre (pg/ml). The lower limits of detection were as follows: IL-17A: 8.17 pg/ml; IL-18: 2.8 pg/ml; and IL-1β: 1 pg/ml.

Statistical analysis

All statistical analyses were performed using IBM SPSS Statistics, Version 20.0 (IBM Corp., Armonk, NY, USA). Categorical data are summarised as frequencies and percentages. Associations among categorical variables were evaluated using the c² test. For contingency tables where more than 20% of expected cell counts were less than 5, the Monte Carlo simulation method was employed as a correction.

The normality of continuous variables was evaluated with the Kolmogorov-Smirnov test. Data following normal distribution are presented as mean ± standard deviation (SD), along with the range (minimum and maximum), and compared between two groups using Student’s t-test. Non-normally distributed quantitative data were presented as medians and interquartile ranges (IQR), and comparisons between two groups were performed using the Mann-Whitney U test. For comparisons involving more than two groups with non-normally distributed data, the Kruskal-Wallis test was employed. In all analyses, statistical significance was defined as a p-value < 0.05.

Multivariable adjustment was not planned at the design stage because the study was exploratory in nature, employed a cross-sectional design, and included a rela­tively modest sample size. The primary objective was to identify unadjusted associations between salivary inflammatory biomarkers and periodontal staging and grading rather than to develop adjusted predictive mo­dels, which would require larger samples and longitudinal data.

Results

Baseline characteristics revealed no statistically signi­ficant variation in gender distribution between the study groups (p = 0.251; Cramér’s V = 0.13), while the BMI and age showed significant differences. The T2DM-P group had a higher mean age (56.70 ± 14.11 years) than the non-diabetic group (40.13 ± 12.16 years), showing a large effect size (Cohen’s d = 1.28). All participants in the T2DM-P group met the WHO criteria for overweight (BMI ≥ 25 kg/m²), with 42.5% classified as obese, whereas 77.5% of non-diabetic participants were within the normal BMI range, reflecting a strong association between group status and BMI category (Cramér’s V = 0.71). Age and BMI may act as potential confounders. However, multivariable adjustment was not performed due to sample size constraints.

A higher proportion of severe periodontitis was found in the diabetic (40%) in comparison to the non-diabetic group (20%). Differences in periodontal stage showed a small-to-moderate association (Cramér’s V = 0.22) but did not show significant difference (p = 0.051) and were interpreted cautiously. In contrast, grade classification differed significantly between groups (c² = 19.501, p < 0.001), with diabetic patients predominantly classified as Grade B and non-diabetic patients as Grade A, corresponding to a large effect size (Cramér’s V = 0.49).

No significant inter-group differences were detected for GI, bleeding on probing (BOP), or salivary IL-17A levels (all p > 0.05; small effect sizes). Although IL-18 and IL-1β levels were greater in the diabetic group, no significant differences were found with small-to-mode­rate effect sizes (Table 1).

Among diabetic patients, IL-17A, IL-18, and IL-1β levels showed no statistical significance across periodontal stages (all p > 0.05; Table 2). When biomarkers were compared across periodontal grades within the diabetic group, IL-1β levels differed significantly (p = 0.046), with Grade C exhibiting lower mean concentrations than Grades A and B, corresponding to a moderate effect size (η² = 0.11). IL-17A and IL-18 levels did not vary significantly across grades (Table 3).

In the non-diabetic group, no significant differences in IL-17A, IL-18, or IL-1β levels were identified across periodontal stages or grades, and effect sizes were consistently small (all p > 0.05; Table 4 and 5).

Discussion

Biological mediators present in oral fluids, including saliva and gingival crevicular fluid (GCF), have emerged as valuable indicators in diagnosing and observing various oral diseases. While GCF offers site-specific information [27], saliva as a non-invasive, easily collected sample can provide a reflection on the overall periodontal status [21]. In this study, salivary IL-18, IL-17A, and IL-1β levels were evaluated in 80 periodontitis patients with and without T2DM to investigate their potential as biomarkers of disease severity and systemic interaction. In this study, restricting the diabetic group to individualswith stable glycaemic control ensured that observed differences in salivary cytokine levels could be attributed to diabetes status and periodontal condition rather than fluctuations in blood glucose regulation. This approach improves internal validity and enhances the interpretability of biomarker comparisons between groups.

Although BMI and age showed significant difference across the diabetic and non-diabetic groups, subsequent comparisons of inflammatory biomarkers were conducted without adjustment for these potential confounders. Therefore, biomarker differences should be interpreted with caution because age and BMI may partially influence cytokine expression.

IL-17A and IL-18 did not show significant differences across grades in the diabetic group (p = 0.064 and p = 0.184, respectively). Although IL-17A approached borderline significance (p = 0.064), this value does not indicate a reliable difference and should be interpreted with caution. IL-1β was the only marker demonstrating a significant difference between grades (p = 0.046), with Grade C exhibiting the lowest levels.

In this study the saliva was collected using the spitting method, this technique was selected due to its ability to collect both the unstimulated and stimulated saliva, which provide a comprehensive view of oral health status. Moreover, this technique is known for its strength in assessing both salivary content and flow rate [28, 29]. Moreover, a previous study showed that stimulated saliva showed decreased essential immune and inflammatory proteins content than unstimulated salivary samples [30].

Our findings revealed that salivary IL-1β and IL-18 levels were greater in diabetic than in non-diabetic individuals with periodontitis, whereas IL-17A levels were slightly higher in non-diabetics. Despite the observed trends, statistical significance was not attained, except for IL-1β when analysed across different periodontitis grades within the diabetic group. Specifically, a signi­ficant difference in IL-1β levels was found among diabetic individuals with different grades of periodontitis (p = 0.046), with Grade C surprisingly showing the lowest levels compared to Grades A and B. This observation could be due to the small sample size in this subgroup.

Salivary IL-18 and IL-17A levels did not vary significantly between the diabetic and non-diabetic groups or across stages and grades in the non-diabetic group, so this finding should be considered preliminary and requires validation in larger studies. Diabetic patients exhibited slightly higher median levels of IL-18, aligning with previous studies that reported elevated IL-18 in T2DM and metabolic syndrome [31-33]. The absence of statistical significance in our results may be due to the small sample size, the variation in glycaemic control, or the influence of local factors affecting cytokine secretion.

The present investigation observed no significant variation in salivary IL-18 concentrations among perio­dontitis individuals either with or without T2DM. This finding agrees with previous research conducted by Correa et al. [34], which assessed IL-18 levels in the GCF of T2DM against healthy individuals, both with chronic periodontitis. No significant differences were found in GCF IL-18 levels between the two cohorts at baseline and 3 months following non-surgical perio­dontal intervention. Furthermore, the periodontitis group showed no significant differences after treatment compared to before. Although the present findings are consistent with those of Correa et al. [34], it is noteworthy that the analysis was conducted on GCF, which reflects the localised inflammatory state of the periodontal pocket, whereas the current study assessed salivary IL-18, which provides a broader, pooled measure of the oral inflammatory burden.

Previous studies have observed that elevated serum IL-18 was associated with HbA_1c levels, but not with periodontitis. Moreover, it is hypothesised to be involved in the development of microvascular complications associated with T2DM [35-37].

The investigation by Esfahrood et al. [38] demonstrated no statistically significant differences in both salivary and GCF IL-18 levels between subjects with and without periodontitis. Conversely, Ozcaka et al. [29] found a significant reduction in salivary IL-17A levels coupled with an increase in salivary IL-18 levels in subjects diagnosed with periodontitis compared to healthy ones. Consequently, the relationship between periodontal inflammation and the elevation of IL-18 and IL-17A levels within the oral environment remains unresolved. In addition to the potential involvement of IL-17A and IL-18 in local periodontal pathology, the systemic function of these cytokines and their interactions with DM have also been acknowledged. In rodent models, DM has been shown to amplify mRNA expression and protein concentrations of IL-17 in various tissues [39, 40]. Supporting a local oral effect, a study by Al-Saady et al. [41] found significantly elevated salivary IL-17 levels in T2DM periodontitis subjects compared to non-diabetic periodontitis subjects. Moreover, elevated IL-18 concentrations were observed in the serum of indivi­duals with T2DM [35, 42].

The absence of correlation between the glycaemic status and salivary IL-17A levels may be elucidated through several considerations. While it is widely reco­gnised that glycaemic control influences inflammation within periodontal tissues, this relationship does not necessarily manifest as an elevation in salivary IL-17A concentrations. The current results correlate with those of Gursoy et al. [43], who evaluated salivary IL-17 concentrations in diabetic individuals categorised by glycaemic control (HbA_1c < 7 and HbA_1c > 7) and observed no difference in salivary IL-17 levels across the two groups. Therefore, effective blood sugar management may result in negligible alterations in cytokine secretion among these patients, suggesting that IL-17A may not be central to the inflammatory processes in T2DM, as it is in periodontal inflammation.

An alternative, speculative explanation is that loca­lised inflammation associated with periodontitis may exert a stronger influence on salivary cytokine levels than systemic metabolic conditions such as T2DM. Such localised inflammatory activity could therefore obscure potential differences in IL-17A levels attributable to glycaemic status in this cohort. It is also important to note that significant differences in age and BMI between groups may have contributed to the observed cytokine profiles, because both factors are known to influence inflammatory responses, and they were not adjusted for in the present analysis.

The observed reduction in IL-1β levels in more advanced periodontal grades among diabetic patients may reflect, speculatively, a state of immune exhaustion or altered inflammatory signalling in the context of chronic disease. Prolonged systemic inflammation associated with long-standing diabetes could lead to compensatory downregulation of certain pro-inflammatory cytokines, a phenomenon reported in other chronic inflammatory conditions [44, 45]. Such immune dysregulation might result in weaker correlations between inflammatory markers and clinical disease severity, as suggested in previous studies [46]. These interpretations should be considered hypothesis-generating and warrant confirmation in longitudinal studies with appropriate adjustment for potential confounders.

Previous studies have reported significantly elevated levels of IL-1β in individuals with T2DM compared to healthy controls [47, 48]. Similarly, Zhou et al. [49] found increased IL-1β levels in both T2DM and impaired glucose tolerance (IGT) groups relative to controls. Elevated IL-1β in T2DM has been shown to stimulate the expression of other pro-inflammatory cytokines such as IL-6, IL-8, and IL-18, thereby amplifying the systemic inflammatory response [50, 51]. This heightened inflammatory activity may also lead to a transient increase in insulin secretion, potentially exerting adverse effects on metabolic regulation [52]. Furthermore, Banerjee et al. [53] observed significantly higher IL-1β levels in younger T2DM patients (aged 31-40 years) compared to age-matched controls, while no significant differences were detected in older age groups.

The observed variations in salivary cytokine levels, particularly IL-1β, support the value of saliva as a promising diagnostic fluid. Its ease of collection, minimal invasiveness, and ability to reflect both local and systemic changes make it an attractive alternative to GCF and serum in periodontal research [21]. The current findings are in agreement with previous literature [21, 43] suggesting that salivary IL-17A may be more closely linked to local periodontal status, while IL-18 and IL-1β could reflect systemic influences such as glycaemic control. The significant age difference between the two groups (diabetics being older on average) raises the possibility of age as a confounding factor. Ageing is independently associated with increased baseline inflammatory activity and may affect periodontal disease progression and cytokine profiles. Although IL-17A, IL-18, and IL-1β levels did not differ significantly between diabetic and non-diabetic periodontitis groups, these results must be interpreted with caution given the baseline differences in age and BMI. Both variables are known to influence systemic and local inflammatory responses, and the diabetic group in this study was significantly older and had substantially higher BMI. These factors may partially decrease or mask the underlying relationship between glycaemic status and inflammatory biomarkers. The absence of multivariable adjustment limits the ability to separate the effect of diabetes from age- or obesity-related inflammatory changes.

This study demonstrates a significant association between IL-1β levels and periodontitis grade in diabetic patients, emphasising a potential immune modulation in advanced disease stages.

Although other cytokines did not demonstrate statistically significant differences in this study, the observed trends and their potential biological relevance suggest further exploration.

This study has several limitations. First, the relatively small sample size and the cross-sectional design limit the ability to establish causal relationships between inflammatory markers and clinical parameters. Second, although the diabetic and non-diabetic groups were comparable in periodontal status, they differed significantly in age and BMI, both of which are potential confounders that may influence salivary inflammatory biomarker levels. Because multivariable adjustment was not performed, residual confounding cannot be excluded.

Third, only controlled diabetic patients (HbA_1c ≤ 7%) were included, which may restrict the generalisability of the findings to uncontrolled diabetes patients. Fourth, the absence of a periodontally healthy control group limits the external validity of the biomarker findings, because it precludes comparison with physiological baseline cytokine levels. Consequently, the observed biomarker patterns can only be interpreted within po­pulations affected by periodontitis and do not allow conclusions regarding the diagnostic specificity or screening potential of these salivary markers in distinguishing health from disease.

Additionally, salivary biomarker levels are susceptible to pre-analytical variables such as hydration, circa­dian rhythm, and recent oral hygiene practices, which may contribute to biological variability despite standardisation efforts.

Future prospective cohort, matched case-control studies using larger samples to minimise confounding effects of diabetes and periodontitis on salivary cytokine profiles are needed.

Baseline differences in age and BMI should also be addressed through appropriate multivariable adjustment in future analyses.

Conclusions

The present study suggests that salivary IL-17A may be more closely associated with periodontal inflammatory burden, whereas IL-1β and IL-18 may be influenced by the presence of T2DM. The observation of reduced IL-1β levels in advanced periodontal grades among diabetic patients may reflect altered inflammatory regulation; however, this finding should be interpreted cautiously and considered hypothesis-generating.

The observed cytokine patterns and their potential biological relevance warrant further investigation but should be viewed considering the study’s limitations, including the absence of a periodontally healthy control group and the potential confounding effects of age and BMI. Given the cross-sectional and exploratory nature of the study, no conclusions regarding biomarker specificity, diagnostic performance, or clinical utility can be drawn at this stage.

While these preliminary findings contribute to the growing body of literature on salivary inflammatory profiles in diabetic periodontitis, confirmation through larger, well-controlled longitudinal studies is required before any translational or clinical implications can be considered.

Disclosures

Author contributions: Conceptualization: M.K., G.I.; Methodology: M.K., G.I.; Investigation and data collection: M.K., G.I.; Formal analysis: M.K., G.I.; Data curation: M.K., G.I.; Writing of original draft: M.K., G.I.; Writing – review and editing: M.K., G.I.; Supervision: M.K. All authors have read and agreed to the published version of the manuscript.

Funding: This research received no external funding.

Institutional Review Board statement: This study was approved by the Research Ethics Committee of Faculty of Dentistry, Alexandria University, on 21/1/2025, approval number: IRB No. 1033-IORG0008839.

Informed consent statement: The purpose and nature of the study was explained, and an informed consent was obtained from patients who agreed to participate in this study prior to any procedure.

Data availability statement: All the data generated or analyzed in this study are included in this manuscript. The data generated in this study may be requested from the corresponding author.

Acknowledgments: None.

Conflicts of interest: The authors declare no conflicts of interest.

AI use statement: Not applicable.

References