Salivary and Serum Inflammatory Biomarkers in Diabetic Nephropathy by Periodontal Status

Diabetic Nephropathy Type 2, Type 2 Diabetes, Periodontitis, Gingivitis, Periodontal Health

diabetic nephropathy, periodontitis, NGAL, cytokine, saliva

Chronic inflammation underlies the bidirectional relationship between diabetes and periodontitis, a process that may be further exacerbated in the presence of diabetic nephropathy. While the roles of inflammatory cytokines such as TNF-α and IL-10 in both periodontal tissue destruction and diabetes-related microvascular complications remain unclear, NGAL is recognized as a biomarker for diabetic nephropathy but its association with periodontal disease is not well established. This study aimed to comparatively evaluate salivary and serum levels of NGAL, TNF-α, and IL-10 according to different periodontal conditions in individuals with newly diagnosed diabetes and those with diabetic nephropathy.

The newly diagnosed diabetes mellitus group consisted of patients attending the Department of Endocrinology who had been diagnosed with type 2 diabetes mellitus for less than 5 years and had no evidence of diabetic vascular complications. The diabetic nephropathy group comprised patients followed in the Department of Endocrinology for nephropathy, defined as a urinary albumin-to-creatinine ratio \>30 mg/g. At baseline, height, body weight, and waist circumference were measured, and body mass index (BMI) was calculated. The body mass index (BMI) was calculated by taking the weight, in kilograms divided by the height in meters squared. A complete physical examination was also performed. In patients evaluated for diabetes mellitus, routinely requested laboratory parameters, including fasting plasma glucose, insulin, HOMA-IR, glycated haemoglobin (HbA1c), complete blood count, liver and renal function tests, erythrocyte sedimentation rate, C-reactive protein (CRP), estimated glomerular filtration rate (eGFR), triglycerides, total cholesterol, HDL, LDL, TSH, and urinary albumin-to-creatinine ratio, were retrieved from the hospital information management system and recorded. Subsequently, all patients were referred to the Faculty of Dentistry, Pamukkale University for further periodontal evaluation. Following periodontal examination, participants were diagnosed as periodontally healthy, gingivitis, or periodontitis, and were allocated to the corresponding study groups according to their periodontal status. The periodontal status of patients was determined based on the Classification of Periodontal and Peri-Implant Diseases and Conditions stated in 2017 World Workshop. Periodontally health was considered if the volunteers have clinically healthy gingiva on an intact periodontium who had BOP \< 10% and PD ≤ 3 mm, no sites with attachment loss, no radiographic sign of alveolar bone destruction and no history of periodontitis. Gingivitis was characterized by the absence of clinical attachment loss and radiographic bone loss, with a BOP score ≥10% (gingivitis on an intact periodontium). Patients with periodontitis were defined as individuals presenting with periodontal disease characterized by PD ≥6 mm, interdental clinical attachment loss (CAL) ≥5 mm, and radiographic bone loss extending to the middle third of the root or beyond in ≥30% of teeth. In these patients, the number of teeth lost due to periodontitis was ≤4. In Endocrinology clinic, peripheral venous blood samples were collected from all included participants via the antecubital vein. A total of 10 mL of venous blood was obtained using separator vacutainer tubes and centrifuged at room temperature. Unstimulated whole saliva was collected by passive drooling into a sterile test tube over a 10-minute period in Periodontology clinic. The collected serum and saliva samples were transferred into Eppendorf tubes and stored at -80°C until the day of analysis. The concentrations of NGAL, TNF-α, and IL-10 in serum and saliva samples were measured using the enzyme-linked immunosorbent assay (ELISA) method at the Department of Histology and Embryology. The power analyse of the study was performed for sample size calculation. Sample size was calculated using the G\*Power software program (G\*Power; Universitat, Dusseldorf, Germany) for α = 0.05 and f = 0.4. The analyses revealed that 19 subjects per group achieved a power of 80 % with 95% confidence. The data were analysed with the SPSS 25 program (SPSS Inc., Chicago, IL). Continuous variables were presented as mean ± standard deviation and categorical variables as numbers and percentages. Shapiro-Wilk test was used to detect data's normality. For the comparison of the parameters of the study groups, One-way ANOVA test was used for normally distributed data while Kruskal-Wallis test was performed as non-parametric test. For pairwise group comparisons, Student's t-test or the Mann-Whitney U test was applied. Chi-square test was used for the comparison of the categorical variables. Statistical significance value was considered as p \< 0.05.

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