Gingival Crevicular Fluid Uric Acid and Albumin Levels in Diabetic and Non-Diabetic Patients Across Periodontitis Stages and Grades

Gingival Crevicular Fluid Uric Acid and Albumin Levels in Diabetic and Non-Diabetic Patients Across Periodontitis Stages and Grades | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Gingival Crevicular Fluid Uric Acid and Albumin Levels in Diabetic and Non-Diabetic Patients Across Periodontitis Stages and Grades Malaz Diaeldin Mohamed, Ibrahim Ahmed Ghandour, Nada Tawfig Hashim, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8133337/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Periodontitis and type 2 diabetes mellitus (T2DM) are chronic inflammatory conditions with a well-established bidirectional relationship, partially mediated by oxidative stress. Gingival crevicular fluid (GCF) biomarkers such as uric acid (UA) and albumin (ALB) may reflect local redox status and periodontal disease severity. Objective: This facility-based analytical cross-sectional study aimed to assess the levels of UA and ALB in the GCF of diabetic and non-diabetic patients across different stages and grades of periodontitis based on the 2017 classification system. Methods: A total of 120 participants were enrolled and divided equally into three groups (n = 40): periodontally healthy individuals, non-diabetic patients with Stage II Grade A periodontitis, and diabetic patients with Stage III Grade B & C periodontitis. Clinical periodontal parameters were recorded. GCF samples were collected using standardized paper strips and analyzed for UA and ALB concentrations using enzyme-linked immunosorbent assay (ELISA). Data were analyzed using one-way ANOVA and Spearman’s correlation tests. Results: Significantly lower levels of UA and ALB were observed in periodontitis patients compared to healthy controls (p = 0.001), with the lowest levels found in diabetic individuals with advanced periodontitis. A moderate to strong inverse correlation was found between both biomarkers and clinical parameters, including probing depth and clinical attachment loss (p < 0.05). Conclusion: GCF levels of uric acid and albumin decline with increasing periodontal severity, especially in patients with T2DM. These findings support the potential utility of UA and ALB as adjunctive biomarkers for monitoring periodontal disease progression and tailoring patient-specific periodontal care, particularly in systemically compromised individuals. Gingival Crevicular Fluid Uric Acid Albumin Periodontitis Type 2 Diabetes Mellitus Oxidative Stress Staging Grading Figures Figure 1 Introduction Periodontal disease is a chronic inflammatory condition characterized by the destruction of tooth-supporting structures and is among the most prevalent infectious diseases globally. It is initiated by a dysbiotic subgingival biofilm and exacerbated by a dysregulated host immune response, leading to clinical manifestations such as gingival inflammation, attachment loss, and alveolar bone resorption. Periodontitis affects an estimated 750 million people and significantly impacts quality of life, chewing ability, and nutritional status [ 1 – 5 ]. Diabetes mellitus (DM), particularly type 2, is a global health concern characterized by chronic hyperglycemia due to insulin deficiency or resistance. A bidirectional relationship between DM and periodontitis is well established: diabetes increases susceptibility to periodontal breakdown, and periodontal therapy has been shown to improve glycemic control [ 6 – 9 ]. One of the key mechanisms underlying this bidirectional link is oxidative stress (OS)—a condition in which excessive production of reactive oxygen species (ROS) overwhelms antioxidant defenses. In diabetes, chronic hyperglycemia triggers oxidative stress via multiple metabolic pathways, while in periodontitis, elevated ROS levels promote inflammatory cytokine release and osteoclastogenesis, contributing to tissue destruction [ 10 – 15 ]. Hyperglycemia may further aggravate periodontitis through the AGE/RAGE pathway and systemic inflammatory dysregulation [ 16 – 18 ]. Among the local antioxidant defenses, uric acid (UA) and albumin (ALB) are of interest. UA is a potent hydrophilic radical scavenger, while albumin, a negative acute-phase reactant, plays a role in redox regulation. Alterations in serum and salivary levels of these molecules have been associated with both diabetes and periodontitis [ 19 – 25 ]. Although previous studies have examined salivary or serum UA and ALB levels in systemic and oral diseases, limited research has explored their concentrations in gingival crevicular fluid (GCF)—the most immediate extracellular environment of the periodontium. Moreover, data remain scarce on how these biomarkers vary across different stages and grades of periodontitis, especially when stratified by diabetic status under the new 2017 periodontal classification system. Therefore, this study aimed to evaluate and compare the levels of the antioxidants uric acid (UA) and albumin (ALB) in the gingival crevicular fluid (GCF) among three groups: periodontally healthy individuals, non-diabetic patients with Stage II Grade A periodontitis, and type 2 diabetic patients with Stage III Grade B & C periodontitis. Furthermore, the study examined the association between these biomarker levels and clinical periodontal parameters, including probing pocket depth (PPD) and clinical attachment loss (CAL). Specifically, the research sought to address the following questions: Are there significant differences in the GCF levels of UA and ALB across the three study groups? Do UA and ALB levels show statistically significant correlations with clinical periodontal parameters (PPD and CAL)? Methods Study design: This was an analytical, cross-sectional, facility-based study designed to investigate gingival crevicular fluid (GCF) uric acid and albumin levels in diabetic and non-diabetic patients with varying stages and grades of periodontitis. The study was conducted from February to September 2019. Study setting and population: The study took place at Jabir Abu-Aliz Diabetic Center (JAIDC), located in Khartoum State, Sudan. The center is a specialized facility for diabetes care and serves a large catchment population within the region. A total of 120 participants were enrolled using a convenience sampling method based on their availability and eligibility during the study period. A convenience sampling technique was used to recruit participants attending JAIDC during the study period. Individuals were screened and selected based on the predefined inclusion and exclusion criteria. Eligible participants were approached consecutively, and those who provided written informed consent were enrolled into the study. Each participant was then allocated to one of three groups—periodontally healthy, Stage II Grade A periodontitis (non-diabetic), or Stage III Grade B & C periodontitis (with type 2 diabetes mellitus)—according to their clinical periodontal and systemic status. While this approach facilitated recruitment, we acknowledge that it may introduce selection bias and limit the external validity of the findings. Participants were matched for age and gender across three groups (n = 40 per group): Group 1: Periodontally and systemically healthy individuals (BOP <10%, PPD <3 mm). Group 2: Non-diabetic patients with generalized periodontitis, diagnosed based on the presence of interdental clinical attachment loss (CAL) at two or more non-adjacent teeth or buccal/oral CAL ≥3 mm with pocketing >3 mm at ≥2 teeth, and clinical signs of instability (PD ≥4 mm with BOP or PD >5 mm) [26]. Group 3: Diabetic patients with generalized periodontitis, using the same criteria as above. Inclusion and exclusion criteria: Inclusion required the ability to provide informed consent and meet the criteria for one of the above groups. Exclusion criteria included: presence of systemic disease other than diabetes, pregnancy, recent antibiotic therapy, smoking, periodontal treatment within the previous three months, unwillingness to participate, and diabetic complications. Clinical periodontal examination: Periodontal parameters were recorded using a William’s periodontal probe by a calibrated examiner. Measurements included: Plaque Index (PLI) as per Silness and Löe [27]. Bleeding on Probing (BOP): assessed by gentle probing into the gingival sulcus or pocket, recording bleeding within 15–30 seconds as present [28]. Probing Pocket Depth (PPD): distance from the gingival margin to the bottom of the pocket. Clinical Attachment Level (CAL): distance from the cementoenamel junction (CEJ) to the base of the pocket. Calibration was performed by repeated measurements on three volunteers until an intra-examiner reliability of >0.85 was achieved. Radiographic assessment of alveolar bone loss (ABL): Panoramic radiographs (orthopantomograms) were taken for all participants using the same digital radiographic unit with a fixed magnification factor. To minimize potential bias from magnification differences, relative measurements were used: the distance from the cementoenamel junction (CEJ) to the alveolar crest was expressed as a percentage of the total root length (CEJ to apex) [29,30]. Measurements were taken at mesial and distal sites of each tooth (excluding third molars, implants, and supernumerary teeth). Disease progression was estimated by dividing percentage bone loss by age. Periodontal staging was classified as: Stage I: ABL <25% Stage II: ABL 25% to <35% Stage III & IV: ABL ≥35% Grading was determined by glycemic status: Grade A: normoglycemic individuals Grade B: diabetics with HbA1c <7% Grade C: diabetics with HbA1c ≥7% Gingival crevicular fluid (GCF) sampling and biomarker analysis: GCF sampling was performed at the same visit as the clinical examination. For periodontitis patients, samples were collected from the deepest periodontal pockets (≥4 mm), confirmed both clinically and radiographically. For healthy controls, samples were taken from sites with 1–3 mm sulcus depth and no CAL or BOP. Supragingival plaque was carefully removed using sterile curettes. Sample sites were isolated and dried. Sterile paper points (size 30) were inserted into the sulcus or pocket for 1 minute and then transferred into cryogenic vials, immediately stored at −80°C at the Institute of Endemic Diseases. Uric acid and albumin levels were quantified using enzyme-linked immunosorbent assay (ELISA) kits (Biosystem™): Uric acid: Uricase/peroxidase-based assay Albumin: Bromocresol Green-based assay Absorbance was measured using a spectrophotometric plate reader (HumaReader HS, Germany) at 450 nm. Statistical analysis: Data were analyzed using SPSS version [insert version] (IBM Corp., Armonk, NY, USA). Descriptive statistics were computed for all variables. Differences in clinical and biochemical parameters among the three groups were assessed using one-way analysis of variance (ANOVA), followed by Bonferroni post hoc pairwise comparisons for multiple group comparisons. Correlation between gingival crevicular fluid (GCF) uric acid and albumin levels and periodontal parameters (probing pocket depth [PPD], clinical attachment loss [CAL]) was evaluated using Spearman’s rank correlation coefficient. A p-value of < 0.05 was considered statistically significant. Ethical considerations: The study received ethical approval from the Research Ethics Board of the Faculty of Dentistry, University of Khartoum (Approval No. FOD/UoK/PG/2020/13), and from the Khartoum State Ministry of Health. All procedures were conducted in accordance with the ethical principles of the Declaration of Helsinki (1975, revised 2002). Written informed consent was obtained from all participants prior to their inclusion in the study. Results Demographic and clinical characteristics of participants: A total of 120 participants were enrolled in the study and equally categorized into three groups: periodontally healthy individuals (n = 40; mean age: 30.1 ± 3.9 years), non-diabetic patients with Stage II Grade A periodontitis (n = 40; mean age: 43.4 ± 9.4 years), and diabetic patients with Stage III Grade B & C periodontitis (n = 40; mean age: 49.3 ± 10.4 years) (Table 1). Clinical periodontal parameters demonstrated a progressive worsening pattern across the groups. The highest mean probing pocket depth (PPD) and clinical attachment loss (CAL) were reported among diabetic participants with Stage III periodontitis (PPD: 5.1 ± 0.3 mm; CAL: 6.0 ± 1.3 mm), followed by Stage II Grade A patients (PPD: 4.6 ± 0.4 mm; CAL: 4.9 ± 0.9 mm). The periodontally healthy group showed minimal or no loss of periodontal support. (Table 2). GCF uric acid and albumin levels: The concentration ranges of gingival crevicular fluid (GCF) uric acid and albumin decreased consistently with disease severity. Uric acid ranged from 3.0–6.0 mg/dL in healthy individuals, 2.4–4.4 mg/dL in Stage II patients, and 2.1–3.8 mg/dL in diabetic Stage III participants. Albumin ranged from 7–28 mg/dL in healthy controls, 7.5–14 mg/dL in Stage II, and 4.5–9 mg/dL in Stage III patients (Table 3). Mean uric acid levels were 4.5 ± 0.7 mg/dL in the healthy group, significantly higher than those recorded in Stage II (3.3 ± 0.5 mg/dL) and Stage III (2.8 ± 0.5 mg/dL). Similarly, albumin levels were highest in healthy individuals (21.4 ± 4.1 mg/dL), followed by Stage II (10.5 ± 1.7 mg/dL), and lowest in Stage III patients (6.0 ± 1.0 mg/dL). (Table 4). Post hoc comparison and correlation analysis: Tukey’s HSD post hoc analysis confirmed statistically significant pairwise differences in both uric acid and albumin levels across the three groups (Table 5). Spearman’s correlation analysis demonstrated significant negative correlations between biomarker concentrations and periodontal parameters. Uric acid showed an inverse relationship with PPD (r = –0.32, p = 0.0038) and CAL (r = –0.29, p = 0.0088), while albumin exhibited stronger negative correlations with PPD (r = –0.44, p < 0.001) and CAL (r = –0.39, p = 0.0003) (Table 6). Graphical interpretation: Figure 1 illustrates the inverse relationships between GCF uric acid and albumin levels with PPD and CAL. The results show that both biomarkers decline with increasing clinical measures of periodontal destruction, further supporting their potential role as oxidative stress-related indicators of disease severity. Discussion Periodontitis is a chronic inflammatory disease resulting from a dysregulated host–microbial interaction, and it is closely linked to systemic conditions such as type II diabetes mellitus [ 31 , 32 ]. Diabetes mellitus exacerbates periodontal breakdown by impairing immune and metabolic functions, both of which influence the severity and progression of periodontitis [ 31 , 32 ]. The 2017 classification of periodontal diseases incorporates systemic modifiers like HbA1c levels into the grading system, recognizing diabetes as a factor accelerating tissue destruction [ 26 ]. To the best of our knowledge, this is the first study to assess uric acid (UA) and albumin (ALB) levels in the gingival crevicular fluid (GCF) of diabetic and non-diabetic individuals with moderate and advanced periodontitis using the updated staging and grading system. It is also the first study of its kind conducted in a Sudanese population using GCF samples, whereas earlier studies primarily relied on saliva or serum. Our results showed that diabetics with Stage III Grade B & C periodontitis had significantly higher probing depths and attachment loss compared to non-diabetics with Stage II Grade A periodontitis and healthy individuals, consistent with earlier studies showing increased periodontitis prevalence and severity in T2DM patients [ 33 ]. This may be attributed to hyperglycemia-mediated inflammation via the AGE–RAGE pathway, which alters immune cell function, enhances cytokine production, and promotes osteoclastogenesis and bone resorption [ 34 ]. Uric acid and albumin levels were significantly lower in diabetic patients with periodontitis compared to both non-diabetic periodontitis patients and healthy controls. These findings align with previous studies reporting elevated total oxidative stress (TOS) and diminished antioxidant capacity in periodontitis [ 35 , 36 ]. Panjamurthy et al. linked oxidative stress in periodontitis to lipid peroxidation at inflammation sites [ 37 ], while Wei et al. and Brock et al. also reported lower antioxidant capacity in periodontitis patients [ 38 , 39 ]. Akalin et al. confirmed these findings across hormonal subgroups [ 40 ]. The reduced levels of UA and ALB observed in this study likely reflect antioxidant depletion due to oxidative challenge in the inflamed periodontium of diabetic individuals [ 41 ]. One explanation is increased UA consumption due to ROS-mediated oxidation or microbial utilization, while another possibility is decreased production linked to suppression of xanthine oxidoreductase activity, as previously discussed [ 42 – 46 ]. However, contradictory findings exist. Rizal et al. reported higher UA levels in periodontitis compared to gingivitis, possibly due to disease-stage variations [ 36 ]. Al-Rawi found increased antioxidants in diabetic saliva, possibly as an adaptive response to systemic oxidative stress [ 47 ]. Discrepancies may also be due to differences in fluid analyzed (saliva vs. GCF), type of diabetes, or metabolic control. Albumin showed a similar trend of reduction in severe periodontitis, consistent with studies by Ben-Arch and Dodd [ 48 , 49 ], but at odds with results from Belazi et al. and Fisher et al., who examined salivary albumin in type 1 diabetes [ 50 , 51 ]. Levent et al. found significant albumin reductions after periodontal therapy, especially in diabetics [ 52 ], supporting its inflammatory responsiveness. Our study also found significant inverse correlations between GCF levels of UA and ALB with probing depth (PPD) and attachment loss (CAL), suggesting that depletion of these antioxidants tracks with disease severity. These results align other studies that demonstrated similar inverse trends with disease extent [ 53 , 54 ]. Together, these findings suggest that declining levels of uric acid and albumin are reflective of disease severity, and may serve as adjunctive biomarkers for periodontal tissue breakdown. The moderate-to-strong inverse correlations observed in this study support the notion that local antioxidant depletion parallels clinical worsening, particularly in the context of diabetes-induced oxidative stress. This study has several limitations. First, its cross-sectional design limits inference of causality and temporal changes in antioxidant levels. Second, the use of convenience sampling may reduce generalizability due to potential selection bias. Third, serum levels of uric acid and albumin were not evaluated, which precludes comparison between systemic and local oxidative states. Factors such as diet, medications, and systemic antioxidant status, which may influence GCF composition, were not controlled for. Future Directions: Longitudinal studies are needed to assess how GCF biomarkers like uric acid and albumin respond to periodontal therapy over time, especially in diabetic populations. Future research should also compare local (GCF) and systemic (serum) antioxidant profiles to understand compartmental oxidative dynamics. Integrating these biomarkers with microbiological and clinical data may enhance risk assessment and allow for personalized therapeutic strategies Conclusion The current study found that diabetic individuals with Stage III Grade B & C periodontitis had lower uric acid and albumin levels in the gingival crevicular fluid than non-diabetic patients with periodontitis and periodontally healthy individuals. This finding supports the hypothesis that antioxidant levels are inversely related to the degree of periodontal inflammation, as well as evidence from the literature indicating that oxidative stress may be a contributing factor in the pathogenesis of both diabetes and periodontal disease. Furthermore, significant inverse correlations between uric acid and albumin levels and clinical parameters such as probing pocket depth and attachment loss underscore their potential role as local biomarkers of periodontal destruction. These results highlight the clinical relevance of assessing oxidative stress markers for monitoring disease progression and individualizing periodontal treatment strategies. What is known about this topic Periodontitis and type 2 diabetes mellitus are chronic diseases that exhibit a well-established bidirectional relationship. Oxidative stress plays a critical role in the pathogenesis of both conditions, leading to increased periodontal destruction and metabolic dysregulation. Uric acid and albumin are key antioxidant biomarkers known to be altered in systemic and oral inflammatory conditions, including periodontitis. What this study adds We found that uric acid and albumin levels in gingival crevicular fluid (GCF) are significantly reduced in patients with periodontitis, particularly in those with type 2 diabetes mellitus and advanced periodontal destruction. This study demonstrates that lower levels of local antioxidants in GCF are moderately and significantly associated with worsening periodontal parameters, such as increased probing depth and attachment loss. By establishing these biomarkers' inverse correlation with disease severity, this study supports the potential clinical application of GCF uric acid and albumin as non-invasive indicators for monitoring periodontal disease progression in both diabetic and non-diabetic patients. Our findings contribute novel biochemical evidence to the understanding of oxidative stress as a key mechanistic link between diabetes and periodontitis, based on the 2018 periodontal classification system. Declarations Competing interests The authors declare no competing interest Authors' contributions All authors contributed equally to the conception, design, literature search, data extraction, analysis, and writing of the manuscript. All authors have read and approved the final version of the manuscript. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. References Pendyala G, Thomas B, Joshi SR. 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Kardes L. Gingival crevicular fluid IL-6, tPA, PAI-2, albumin levels following initial periodontal treatment in chronic periodontitis patients with or without type 2 diabetes. Inflamm Res. 2011;60:143–51. Lalkota, H.; Alluri, L.; Paes Batista da Silva, A.; Gummalla, S.; Krishna Mohana Reddy, K. Estimation and Correlation of Serum Albumin and Serum Alkaline Phosphatase Levels between Smokers and Non-Smokers with Generalized Chronic Periodontitis. Cureus 2021, 13, e17474. Ogawa, H., Yoshihara, A., Amarasena, N., Hirotomi, T., & Miyazaki, H. (2006). Association between serum albumin and periodontal disease in community-dwelling elderly. Journal of Clinical Periodontology, 33(5), 312-316. Tables Table 1. Demographic Distribution and Mean Age of Study Participants Across Clinical Groups (N = 120) . This table presents the frequency and age distribution of individuals categorized into three clinical groups: periodontally healthy individuals, non-diabetic patients with Stage II Grade A periodontitis, and diabetic patients with Stage III Grade B & C periodontitis. Group Frequency (%) Age (Mean ± SD) Healthy 40 (33.3) 30.1 ± 3.9 Stage II Grade A Periodontitis 40 (33.3) 43.4 ± 9.4 Stage III Grade B & C Periodontitis 40 (33.3) 49.3 ± 10.4 Total 120 – Table 2. Comparison of Clinical Periodontal Parameters Across Study Groups (N = 120) . This table summarizes the mean ± standard deviation of key periodontal parameters—Plaque Index (PI), Bleeding on Probing (BoP), Probing Pocket Depth (PPD), and Clinical Attachment Loss (CAL)—among periodontally healthy individuals, non-diabetic patients with Stage II Grade A periodontitis, and diabetic patients with Stage III Grade B & C periodontitis. Statistical significance was determined using one-way ANOVA. Parameter Healthy Stage II Grade A Periodontitis Stage III Grade B & C Periodontitis P-value PI 1.2 ± 0.3 1.7 ± 0.3 1.6 ± 0.3 0.001** BoP (%) 15.1 ± 8.1 51.4 ± 12.1 51.3 ± 10.4 0.001** PPD 0.0 4.6 ± 0.4 5.1 ± 0.3 0.001** CAL 0.0 4.9 ± 0.9 6.0 ± 1.3 0.001** PI: Plaque Index, BoP: Bleeding on Probing, PPD: Probing Pocket Depth, CAL: Clinical Attachment Loss. Table 3. Minimum and Maximum Levels of Uric Acid and Albumin in Gingival Crevicular Fluid Across Clinical Groups (N = 120) . This table presents the range (minimum to maximum) of uric acid and albumin concentrations in the gingival crevicular fluid (GCF) of participants categorized into three clinical groups: periodontally healthy individuals, non-diabetic patients with Stage II Grade A periodontitis, and diabetic patients with Stage III Grade B & C periodontitis. These measurements were obtained using ELISA and reflect the oxidative stress profiles associated with each group. Group Uric Acid (mg/dL) Albumin (mg/dL) Minimum Maximum Minimum Maximum Healthy 3.0 6.0 7.0 28.0 Stage II Grade A Periodontitis 2.4 4.4 7.5 14.0 Stage III Grade B & C Periodontitis 2.1 3.8 4.5 9.0 Table 4. Mean Gingival Crevicular Fluid Levels of Uric Acid and Albumin Among Study Groups (N = 120) . This table displays the mean ± standard deviation concentrations of uric acid and albumin in the gingival crevicular fluid (GCF) of periodontally healthy individuals, patients with Stage II Grade A periodontitis, and diabetic patients with Stage III Grade B & C periodontitis. Statistically significant differences were identified using one-way ANOVA (p < 0.001), indicating a progressive decline in antioxidant levels with increasing disease severity. Biomarker Healthy Stage II Grade A Periodontitis Stage III Grade B & C Periodontitis P-value Uric Acid (mg/dL) 4.5 ± 0.7 3.3 ± 0.5 2.8 ± 0.5 0.001** Albumin (mg/dL) 21.4 ± 4.1 10.5 ± 1.7 6.0 ± 1.0 0.001** Table 5. Post hoc pairwise comparisons of mean uric acid and albumin levels in gingival crevicular fluid (GCF) among diabetic and non-diabetic patients with different stages and grades of periodontitis using Tukey’s HSD test (n = 120). This table summarizes the differences in GCF biomarker levels (uric acid and albumin) between three patient groups: healthy individuals, patients with Stage II Grade A periodontitis, and patients with Stage III Grade B & C periodontitis with type 2 diabetes. Reported values include the mean differences, 95% confidence intervals (CI), p-values, and whether the differences were statistically significant. All comparisons show a significant decline in biomarker levels with increasing disease severity. Biomarker Comparison Mean Difference 95% CI (Lower–Upper) P-value Significant Uric Acid Healthy vs. Stage II -1.043 -1.32 to -0.77 < 0.001 Yes Healthy vs. Stage III -1.633 -1.91 to -1.36 < 0.001 Yes Stage II vs. Stage III -0.590 -0.87 to -0.31 < 0.001 Yes Albumin Healthy vs. Stage II -10.97 -12.32 to -9.61 < 0.001 Yes Healthy vs. Stage III -15.97 -17.33 to -14.61 < 0.001 Yes Stage II vs. Stage III -5.01 -6.37 to -3.65 < 0.001 Yes Table 6. Correlation analysis between gingival crevicular fluid (GCF) biomarker levels (uric acid and albumin) and clinical periodontal parameters (probing pocket depth [PPD] and clinical attachment loss [CAL]) among study participants (n = 120). This table presents the Pearson correlation coefficients (r) and corresponding p-values for the relationships between antioxidant biomarkers and periodontal disease severity. Significant moderate inverse correlations were observed, indicating that as PPD and CAL increased, uric acid and albumin levels decreased, supporting their potential role as indicators of periodontal tissue destruction. Marker Parameter Correlation (r) P-value Interpretation Uric Acid PPD -0.32 0.0038** Moderate inverse correlation (significant) Albumin PPD -0.44 < 0.001** Moderate-to-strong inverse correlation Uric Acid CAL -0.29 0.0088** Weak-to-moderate inverse correlation Albumin CAL -0.39 0.0003** Moderate inverse correlation Significance level: p < 0.05 ( ), p < 0.01 (**)* Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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09:28:00","extension":"html","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":126141,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8133337/v1/04274adfef9dc5e221dcdd11.html"},{"id":98780515,"identity":"8c9095f3-3e9c-41bd-9bd0-c47adf738860","added_by":"auto","created_at":"2025-12-22 12:31:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":75479,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePearson correlation coefficients between gingival crevicular fluid (GCF) antioxidant biomarkers (uric acid and albumin) and clinical periodontal parameters (probing pocket depth [PPD] and clinical attachment loss [CAL]) among study participants (n = 120).\u003c/em\u003eThis figure illustrates the negative correlations observed, with both uric acid and albumin showing a decline in levels as periodontal disease severity increased. The inverse relationship was stronger for albumin compared to uric acid, particularly with respect to PPD.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8133337/v1/6a6860547eacb30dc656ae81.png"},{"id":101408608,"identity":"d8bd6326-23de-4ec2-af7f-c0ebf39340e8","added_by":"auto","created_at":"2026-01-29 11:12:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1165051,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8133337/v1/32714fd4-d10a-43d0-ba7a-548b43a08ee7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Gingival Crevicular Fluid Uric Acid and Albumin Levels in Diabetic and Non-Diabetic Patients Across Periodontitis Stages and Grades","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePeriodontal disease is a chronic inflammatory condition characterized by the destruction of tooth-supporting structures and is among the most prevalent infectious diseases globally. It is initiated by a dysbiotic subgingival biofilm and exacerbated by a dysregulated host immune response, leading to clinical manifestations such as gingival inflammation, attachment loss, and alveolar bone resorption. Periodontitis affects an estimated 750\u0026nbsp;million people and significantly impacts quality of life, chewing ability, and nutritional status [\u003cspan additionalcitationids=\"CR2 CR3 CR4\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDiabetes mellitus (DM), particularly type 2, is a global health concern characterized by chronic hyperglycemia due to insulin deficiency or resistance. A bidirectional relationship between DM and periodontitis is well established: diabetes increases susceptibility to periodontal breakdown, and periodontal therapy has been shown to improve glycemic control [\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOne of the key mechanisms underlying this bidirectional link is oxidative stress (OS)\u0026mdash;a condition in which excessive production of reactive oxygen species (ROS) overwhelms antioxidant defenses. In diabetes, chronic hyperglycemia triggers oxidative stress via multiple metabolic pathways, while in periodontitis, elevated ROS levels promote inflammatory cytokine release and osteoclastogenesis, contributing to tissue destruction [\u003cspan additionalcitationids=\"CR11 CR12 CR13 CR14\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Hyperglycemia may further aggravate periodontitis through the AGE/RAGE pathway and systemic inflammatory dysregulation [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmong the local antioxidant defenses, uric acid (UA) and albumin (ALB) are of interest. UA is a potent hydrophilic radical scavenger, while albumin, a negative acute-phase reactant, plays a role in redox regulation. Alterations in serum and salivary levels of these molecules have been associated with both diabetes and periodontitis [\u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23 CR24\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e Although previous studies have examined salivary or serum UA and ALB levels in systemic and oral diseases, limited research has explored their concentrations in gingival crevicular fluid (GCF)\u0026mdash;the most immediate extracellular environment of the periodontium. Moreover, data remain scarce on how these biomarkers vary across different stages and grades of periodontitis, especially when stratified by diabetic status under the new 2017 periodontal classification system.\u003c/p\u003e \u003cp\u003eTherefore, this study aimed to evaluate and compare the levels of the antioxidants uric acid (UA) and albumin (ALB) in the gingival crevicular fluid (GCF) among three groups: periodontally healthy individuals, non-diabetic patients with Stage II Grade A periodontitis, and type 2 diabetic patients with Stage III Grade B \u0026amp; C periodontitis. Furthermore, the study examined the association between these biomarker levels and clinical periodontal parameters, including probing pocket depth (PPD) and clinical attachment loss (CAL). Specifically, the research sought to address the following questions:\u003c/p\u003e \u003cp\u003eAre there significant differences in the GCF levels of UA and ALB across the three study groups?\u003c/p\u003e \u003cp\u003eDo UA and ALB levels show statistically significant correlations with clinical periodontal parameters (PPD and CAL)?\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy design:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;This was an analytical, cross-sectional, facility-based study designed to investigate gingival crevicular fluid (GCF) uric acid and albumin levels in diabetic and non-diabetic patients with varying stages and grades of periodontitis. The study was conducted from February to September 2019.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy setting and population:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The study took place at Jabir Abu-Aliz Diabetic Center (JAIDC), located in Khartoum State, Sudan. The center is a specialized facility for diabetes care and serves a large catchment population within the region.\u003c/p\u003e\n\u003cp\u003eA total of 120 participants were enrolled using a convenience sampling method based on their availability and eligibility during the study period. A convenience sampling technique was used to recruit participants attending JAIDC during the study period. Individuals were screened and selected based on the predefined inclusion and exclusion criteria. Eligible participants were approached consecutively, and those who provided written informed consent were enrolled into the study. Each participant was then allocated to one of three groups—periodontally healthy, Stage II Grade A periodontitis (non-diabetic), or Stage III Grade B \u0026amp; C periodontitis (with type 2 diabetes mellitus)—according to their clinical periodontal and systemic status.\u003c/p\u003e\n\u003cp\u003eWhile this approach facilitated recruitment, we acknowledge that it may introduce selection bias and limit the external validity of the findings.\u003c/p\u003e\n\u003cp\u003eParticipants were matched for age and gender across three groups (n = 40 per group):\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eGroup 1:\u003c/strong\u003e Periodontally and systemically healthy individuals (BOP \u0026lt;10%, PPD \u0026lt;3 mm).\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eGroup 2:\u003c/strong\u003e Non-diabetic patients with generalized periodontitis, diagnosed based on the presence of interdental clinical attachment loss (CAL) at two or more non-adjacent teeth or buccal/oral CAL ≥3 mm with pocketing \u0026gt;3 mm at ≥2 teeth, and clinical signs of instability (PD ≥4 mm with BOP or PD \u0026gt;5 mm) [26].\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eGroup 3:\u003c/strong\u003e Diabetic patients with generalized periodontitis, using the same criteria as above.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion and exclusion criteria:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Inclusion required the ability to provide informed consent and meet the criteria for one of the above groups. Exclusion criteria included: presence of systemic disease other than diabetes, pregnancy, recent antibiotic therapy, smoking, periodontal treatment within the previous three months, unwillingness to participate, and diabetic complications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical periodontal examination:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Periodontal parameters were recorded using a William’s periodontal probe by a calibrated examiner. Measurements included:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003ePlaque Index (PLI)\u003c/strong\u003e as per Silness and Löe [27].\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eBleeding on Probing (BOP):\u003c/strong\u003e assessed by gentle probing into the gingival sulcus or pocket, recording bleeding within 15–30 seconds as present [28].\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eProbing Pocket Depth (PPD):\u003c/strong\u003e distance from the gingival margin to the bottom of the pocket.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eClinical Attachment Level (CAL):\u003c/strong\u003e distance from the cementoenamel junction (CEJ) to the base of the pocket.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eCalibration was performed by repeated measurements on three volunteers until an intra-examiner reliability of \u0026gt;0.85 was achieved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRadiographic assessment of alveolar bone loss (ABL):\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePanoramic radiographs (orthopantomograms) were taken for all participants using the same digital radiographic unit with a fixed magnification factor. To minimize potential bias from magnification differences, relative measurements were used: the distance from the cementoenamel junction (CEJ) to the alveolar crest was expressed as a percentage of the total root length (CEJ to apex) [29,30]. Measurements were taken at mesial and distal sites of each tooth (excluding third molars, implants, and supernumerary teeth). Disease progression was estimated by dividing percentage bone loss by age. Periodontal staging was classified as:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eStage I: ABL \u0026lt;25%\u003c/li\u003e\n \u003cli\u003eStage II: ABL 25% to \u0026lt;35%\u003c/li\u003e\n \u003cli\u003eStage III \u0026amp; IV: ABL ≥35%\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eGrading was determined by glycemic status:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eGrade A: normoglycemic individuals\u003c/li\u003e\n \u003cli\u003eGrade B: diabetics with HbA1c \u0026lt;7%\u003c/li\u003e\n \u003cli\u003eGrade C: diabetics with HbA1c ≥7%\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eGingival crevicular fluid (GCF) sampling and biomarker analysis:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;GCF sampling was performed at the same visit as the clinical examination.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eFor periodontitis patients, samples were collected from the deepest periodontal pockets (≥4 mm), confirmed both clinically and radiographically.\u003c/li\u003e\n \u003cli\u003eFor healthy controls, samples were taken from sites with 1–3 mm sulcus depth and no CAL or BOP.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eSupragingival plaque was carefully removed using sterile curettes. Sample sites were isolated and dried. Sterile paper points (size 30) were inserted into the sulcus or pocket for 1 minute and then transferred into cryogenic vials, immediately stored at −80°C at the Institute of Endemic Diseases.\u003c/p\u003e\n\u003cp\u003eUric acid and albumin levels were quantified using enzyme-linked immunosorbent assay (ELISA) kits (Biosystem™):\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eUric acid:\u003c/strong\u003e Uricase/peroxidase-based assay\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAlbumin:\u003c/strong\u003e Bromocresol Green-based assay\u003cbr\u003e\u0026nbsp;Absorbance was measured using a spectrophotometric plate reader (HumaReader HS, Germany) at 450 nm.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Data were analyzed using SPSS version [insert version] (IBM Corp., Armonk, NY, USA). Descriptive statistics were computed for all variables. Differences in clinical and biochemical parameters among the three groups were assessed using one-way analysis of variance (ANOVA), followed by Bonferroni post hoc pairwise comparisons for multiple group comparisons. Correlation between gingival crevicular fluid (GCF) uric acid and albumin levels and periodontal parameters (probing pocket depth [PPD], clinical attachment loss [CAL]) was evaluated using Spearman’s rank correlation coefficient. A p-value of \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical considerations:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The study received ethical approval from the Research Ethics Board of the Faculty of Dentistry, University of Khartoum (Approval No. FOD/UoK/PG/2020/13), and from the Khartoum State Ministry of Health. All procedures were conducted in accordance with the ethical principles of the Declaration of Helsinki (1975, revised 2002). Written informed consent was obtained from all participants prior to their inclusion in the study.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eDemographic and clinical characteristics of participants:\u003c/strong\u003e A total of 120 participants were enrolled in the study and equally categorized into three groups: periodontally healthy individuals (n = 40; mean age: 30.1 ± 3.9 years), non-diabetic patients with Stage II Grade A periodontitis (n = 40; mean age: 43.4 ± 9.4 years), and diabetic patients with Stage III Grade B \u0026amp; C periodontitis (n = 40; mean age: 49.3 ± 10.4 years) (Table 1). Clinical periodontal parameters demonstrated a progressive worsening pattern across the groups. The highest mean probing pocket depth (PPD) and clinical attachment loss (CAL) were reported among diabetic participants with Stage III periodontitis (PPD: 5.1 ± 0.3 mm; CAL: 6.0 ± 1.3 mm), followed by Stage II Grade A patients (PPD: 4.6 ± 0.4 mm; CAL: 4.9 ± 0.9 mm). The periodontally healthy group showed minimal or no loss of periodontal support. (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGCF uric acid and albumin levels:\u003c/strong\u003e The concentration ranges of gingival crevicular fluid (GCF) uric acid and albumin decreased consistently with disease severity. Uric acid ranged from 3.0–6.0 mg/dL in healthy individuals, 2.4–4.4 mg/dL in Stage II patients, and 2.1–3.8 mg/dL in diabetic Stage III participants. Albumin ranged from 7–28 mg/dL in healthy controls, 7.5–14 mg/dL in Stage II, and 4.5–9 mg/dL in Stage III patients (Table 3). Mean uric acid levels were 4.5 ± 0.7 mg/dL in the healthy group, significantly higher than those recorded in Stage II (3.3 ± 0.5 mg/dL) and Stage III (2.8 ± 0.5 mg/dL). Similarly, albumin levels were highest in healthy individuals (21.4 ± 4.1 mg/dL), followed by Stage II (10.5 ± 1.7 mg/dL), and lowest in Stage III patients (6.0 ± 1.0 mg/dL). (Table 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePost hoc comparison and correlation analysis:\u003c/strong\u003e Tukey’s HSD post hoc analysis confirmed statistically significant pairwise differences in both uric acid and albumin levels across the three groups (Table 5). Spearman’s correlation analysis demonstrated significant negative correlations between biomarker concentrations and periodontal parameters. Uric acid showed an inverse relationship with PPD (r = –0.32, p = 0.0038) and CAL (r = –0.29, p = 0.0088), while albumin exhibited stronger negative correlations with PPD (r = –0.44, p \u0026lt; 0.001) and CAL (r = –0.39, p = 0.0003) (Table 6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGraphical interpretation:\u003c/strong\u003e Figure 1 illustrates the inverse relationships between GCF uric acid and albumin levels with PPD and CAL. The results show that both biomarkers decline with increasing clinical measures of periodontal destruction, further supporting their potential role as oxidative stress-related indicators of disease severity.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePeriodontitis is a chronic inflammatory disease resulting from a dysregulated host\u0026ndash;microbial interaction, and it is closely linked to systemic conditions such as type II diabetes mellitus [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Diabetes mellitus exacerbates periodontal breakdown by impairing immune and metabolic functions, both of which influence the severity and progression of periodontitis [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The 2017 classification of periodontal diseases incorporates systemic modifiers like HbA1c levels into the grading system, recognizing diabetes as a factor accelerating tissue destruction [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, this is the first study to assess uric acid (UA) and albumin (ALB) levels in the gingival crevicular fluid (GCF) of diabetic and non-diabetic individuals with moderate and advanced periodontitis using the updated staging and grading system. It is also the first study of its kind conducted in a Sudanese population using GCF samples, whereas earlier studies primarily relied on saliva or serum.\u003c/p\u003e \u003cp\u003eOur results showed that diabetics with Stage III Grade B \u0026amp; C periodontitis had significantly higher probing depths and attachment loss compared to non-diabetics with Stage II Grade A periodontitis and healthy individuals, consistent with earlier studies showing increased periodontitis prevalence and severity in T2DM patients [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. This may be attributed to hyperglycemia-mediated inflammation via the AGE\u0026ndash;RAGE pathway, which alters immune cell function, enhances cytokine production, and promotes osteoclastogenesis and bone resorption [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUric acid and albumin levels were significantly lower in diabetic patients with periodontitis compared to both non-diabetic periodontitis patients and healthy controls. These findings align with previous studies reporting elevated total oxidative stress (TOS) and diminished antioxidant capacity in periodontitis [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Panjamurthy et al. linked oxidative stress in periodontitis to lipid peroxidation at inflammation sites [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], while Wei et al. and Brock et al. also reported lower antioxidant capacity in periodontitis patients [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Akalin et al. confirmed these findings across hormonal subgroups [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe reduced levels of UA and ALB observed in this study likely reflect antioxidant depletion due to oxidative challenge in the inflamed periodontium of diabetic individuals [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. One explanation is increased UA consumption due to ROS-mediated oxidation or microbial utilization, while another possibility is decreased production linked to suppression of xanthine oxidoreductase activity, as previously discussed [\u003cspan additionalcitationids=\"CR43 CR44 CR45\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, contradictory findings exist. Rizal et al. reported higher UA levels in periodontitis compared to gingivitis, possibly due to disease-stage variations [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Al-Rawi found increased antioxidants in diabetic saliva, possibly as an adaptive response to systemic oxidative stress [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Discrepancies may also be due to differences in fluid analyzed (saliva vs. GCF), type of diabetes, or metabolic control.\u003c/p\u003e \u003cp\u003eAlbumin showed a similar trend of reduction in severe periodontitis, consistent with studies by Ben-Arch and Dodd [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], but at odds with results from Belazi et al. and Fisher et al., who examined salivary albumin in type 1 diabetes [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Levent et al. found significant albumin reductions after periodontal therapy, especially in diabetics [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], supporting its inflammatory responsiveness.\u003c/p\u003e \u003cp\u003eOur study also found significant inverse correlations between GCF levels of UA and ALB with probing depth (PPD) and attachment loss (CAL), suggesting that depletion of these antioxidants tracks with disease severity. These results align other studies that demonstrated similar inverse trends with disease extent [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTogether, these findings suggest that declining levels of uric acid and albumin are reflective of disease severity, and may serve as adjunctive biomarkers for periodontal tissue breakdown. The moderate-to-strong inverse correlations observed in this study support the notion that local antioxidant depletion parallels clinical worsening, particularly in the context of diabetes-induced oxidative stress.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, its cross-sectional design limits inference of causality and temporal changes in antioxidant levels. Second, the use of convenience sampling may reduce generalizability due to potential selection bias. Third, serum levels of uric acid and albumin were not evaluated, which precludes comparison between systemic and local oxidative states. Factors such as diet, medications, and systemic antioxidant status, which may influence GCF composition, were not controlled for.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eFuture Directions:\u003c/h2\u003e \u003cp\u003eLongitudinal studies are needed to assess how GCF biomarkers like uric acid and albumin respond to periodontal therapy over time, especially in diabetic populations. Future research should also compare local (GCF) and systemic (serum) antioxidant profiles to understand compartmental oxidative dynamics. Integrating these biomarkers with microbiological and clinical data may enhance risk assessment and allow for personalized therapeutic strategies\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe current study found that diabetic individuals with Stage III Grade B \u0026amp; C periodontitis had lower uric acid and albumin levels in the gingival crevicular fluid than non-diabetic patients with periodontitis and periodontally healthy individuals. This finding supports the hypothesis that antioxidant levels are inversely related to the degree of periodontal inflammation, as well as evidence from the literature indicating that oxidative stress may be a contributing factor in the pathogenesis of both diabetes and periodontal disease. Furthermore, significant inverse correlations between uric acid and albumin levels and clinical parameters such as probing pocket depth and attachment loss underscore their potential role as local biomarkers of periodontal destruction. These results highlight the clinical relevance of assessing oxidative stress markers for monitoring disease progression and individualizing periodontal treatment strategies.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eWhat is known about this topic\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePeriodontitis and type 2 diabetes mellitus are chronic diseases that exhibit a well-established bidirectional relationship.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eOxidative stress plays a critical role in the pathogenesis of both conditions, leading to increased periodontal destruction and metabolic dysregulation.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eUric acid and albumin are key antioxidant biomarkers known to be altered in systemic and oral inflammatory conditions, including periodontitis.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eWhat this study adds\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eWe found that uric acid and albumin levels in gingival crevicular fluid (GCF) are significantly reduced in patients with periodontitis, particularly in those with type 2 diabetes mellitus and advanced periodontal destruction.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThis study demonstrates that lower levels of local antioxidants in GCF are moderately and significantly associated with worsening periodontal parameters, such as increased probing depth and attachment loss.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eBy establishing these biomarkers' inverse correlation with disease severity, this study supports the potential clinical application of GCF uric acid and albumin as non-invasive indicators for monitoring periodontal disease progression in both diabetic and non-diabetic patients.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eOur findings contribute novel biochemical evidence to the understanding of oxidative stress as a key mechanistic link between diabetes and periodontitis, based on the 2018 periodontal classification system.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interest\u003c/p\u003e\n\u003ch3\u003eAuthors' contributions\u003c/h3\u003e\n\u003cp\u003eAll authors contributed equally to the conception, design, literature search, data extraction, analysis, and writing of the manuscript. All authors have read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003ePendyala G, Thomas B, Joshi SR. Evaluation of Total Antioxidant Capacity of Saliva in Type 2 Diabetic Patients with and without Periodontal Disease: A Case Control Study. N Am J Med Sci. 2013;5(1):1\u0026ndash;8.\u003c/li\u003e\n \u003cli\u003eFaisal R, Jabber W. Salivary profile and periodontal condition in patients with heart disease under warfarin treatment. J Int Dent Med Res. 2018;11:449\u0026ndash;53.\u003c/li\u003e\n \u003cli\u003eGrover HS, Luthra S. Molecular mechanisms involved in the bidirectional relationship between diabetes mellitus and periodontal disease. 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Diabetes Vasc Dis Res. 2011;8:22\u0026ndash;8.\u003c/li\u003e\n \u003cli\u003eBen-Aryeh H, Serouya R, Kanter Y, Szargel R, Laufer D. Oral health and salivary composition in diabetic patients. J Diabetes Complications. 1993;7(1):57\u0026ndash;62.\u003c/li\u003e\n \u003cli\u003eDodd MJ, Yeh CK, Johnson DA. Salivary alterations in type 2 (non-insulin dependent) diabetes mellitus and hypertension. Community Dent Oral Epidemiol. 2000;28:373\u0026ndash;81.\u003c/li\u003e\n \u003cli\u003eBelazi MA, Galli-Tsinopoulou A, Drakoulakos D, Fleva A, Papanayiotou PH. Salivary alterations in insulin-dependent diabetes mellitus. Int J Paediatr Dent. 1998;8:29\u0026ndash;33.\u003c/li\u003e\n \u003cli\u003eFisher BM, Lamey PJ, Sweeney D, Beely JA, Spooner RJ, Frier BM. Salivary secretion of albumin in type 1 (insulin-dependent) diabetes. Diabetes Res Clin Pract. 1991;11(2):117\u0026ndash;9.\u003c/li\u003e\n \u003cli\u003eKardes L. Gingival crevicular fluid IL-6, tPA, PAI-2, albumin levels following initial periodontal treatment in chronic periodontitis patients with or without type 2 diabetes. Inflamm Res. 2011;60:143\u0026ndash;51.\u003c/li\u003e\n \u003cli\u003eLalkota, H.; Alluri, L.; Paes Batista da Silva, A.; Gummalla, S.; Krishna Mohana Reddy, K. Estimation and Correlation of Serum Albumin and Serum Alkaline Phosphatase Levels between Smokers and Non-Smokers with Generalized Chronic Periodontitis. Cureus 2021, 13, e17474.\u003c/li\u003e\n \u003cli\u003eOgawa, H., Yoshihara, A., Amarasena, N., Hirotomi, T., \u0026amp; Miyazaki, H. (2006). Association between serum albumin and periodontal disease in community-dwelling elderly. Journal of Clinical Periodontology, 33(5), 312-316.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. \u003cstrong\u003eDemographic Distribution and Mean Age of Study Participants Across Clinical Groups (N = 120)\u003c/strong\u003e\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e This table presents the frequency and age distribution of individuals categorized into three clinical groups: periodontally healthy individuals, non-diabetic patients with Stage II Grade A periodontitis, and diabetic patients with Stage III Grade B \u0026amp; C periodontitis.\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (Mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHealthy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30.1 \u0026plusmn; 3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage II Grade A Periodontitis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43.4 \u0026plusmn; 9.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage III Grade B \u0026amp; C Periodontitis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49.3 \u0026plusmn; 10.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e120\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ndash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. \u003cstrong\u003eComparison of Clinical Periodontal Parameters Across Study Groups (N = 120)\u003c/strong\u003e\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eThis table summarizes the mean \u0026plusmn; standard deviation of key periodontal parameters\u0026mdash;Plaque Index (PI), Bleeding on Probing (BoP), Probing Pocket Depth (PPD), and Clinical Attachment Loss (CAL)\u0026mdash;among periodontally healthy individuals, non-diabetic patients with Stage II Grade A periodontitis, and diabetic patients with Stage III Grade B \u0026amp; C periodontitis. Statistical significance was determined using one-way ANOVA.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStage II Grade A Periodontitis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStage III Grade B \u0026amp; C Periodontitis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.2 \u0026plusmn; 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.7 \u0026plusmn; 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.6 \u0026plusmn; 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBoP (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.1 \u0026plusmn; 8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51.4 \u0026plusmn; 12.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51.3 \u0026plusmn; 10.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.6 \u0026plusmn; 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.1 \u0026plusmn; 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.9 \u0026plusmn; 0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.0 \u0026plusmn; 1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003ePI: Plaque Index, BoP: Bleeding on Probing, PPD: Probing Pocket Depth, CAL: Clinical Attachment Loss.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. \u003cstrong\u003eMinimum and Maximum Levels of Uric Acid and Albumin in Gingival Crevicular Fluid Across Clinical Groups (N = 120)\u003c/strong\u003e\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003eThis table presents the range (minimum to maximum) of uric acid and albumin concentrations in the gingival crevicular fluid (GCF) of participants categorized into three clinical groups: periodontally healthy individuals, non-diabetic patients with Stage II Grade A periodontitis, and diabetic patients with Stage III Grade B \u0026amp; C periodontitis. These measurements were obtained using ELISA and reflect the oxidative stress profiles associated with each group.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUric Acid (mg/dL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlbumin (mg/dL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMinimum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMaximum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMinimum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMaximum\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHealthy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage II Grade A Periodontitis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage III Grade B \u0026amp; C Periodontitis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. \u003cstrong\u003eMean Gingival Crevicular Fluid Levels of Uric Acid and Albumin Among Study Groups (N = 120)\u003c/strong\u003e\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e This table displays the mean \u0026plusmn; standard deviation concentrations of uric acid and albumin in the gingival crevicular fluid (GCF) of periodontally healthy individuals, patients with Stage II Grade A periodontitis, and diabetic patients with Stage III Grade B \u0026amp; C periodontitis. Statistically significant differences were identified using one-way ANOVA (p \u0026lt; 0.001), indicating a progressive decline in antioxidant levels with increasing disease severity.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiomarker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStage II Grade A Periodontitis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStage III Grade B \u0026amp; C Periodontitis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUric Acid (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.5 \u0026plusmn; 0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.3 \u0026plusmn; 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.8 \u0026plusmn; 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAlbumin (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21.4 \u0026plusmn; 4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.5 \u0026plusmn; 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.0 \u0026plusmn; 1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 5.\u0026nbsp;\u003c/strong\u003e\u003cem\u003ePost hoc pairwise comparisons of mean uric acid and albumin levels in gingival crevicular fluid (GCF) among diabetic and non-diabetic patients with different stages and grades of periodontitis using Tukey\u0026rsquo;s HSD test (n = 120).\u003c/em\u003e This table summarizes the differences in GCF biomarker levels (uric acid and albumin) between three patient groups: healthy individuals, patients with Stage II Grade A periodontitis, and patients with Stage III Grade B \u0026amp; C periodontitis with type 2 diabetes. Reported values include the mean differences, 95% confidence intervals (CI), p-values, and whether the differences were statistically significant. All comparisons show a significant decline in biomarker levels with increasing disease severity.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiomarker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eComparison\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean Difference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI (Lower\u0026ndash;Upper)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSignificant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUric Acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHealthy vs. Stage II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-1.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-1.32 to -0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHealthy vs. Stage III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-1.633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-1.91 to -1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage II vs. Stage III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.87 to -0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAlbumin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHealthy vs. Stage II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-10.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-12.32 to -9.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHealthy vs. Stage III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-15.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-17.33 to -14.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage II vs. Stage III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-5.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-6.37 to -3.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6.\u0026nbsp;\u003c/strong\u003e\u003cem\u003eCorrelation analysis between gingival crevicular fluid (GCF) biomarker levels (uric acid and albumin) and clinical periodontal parameters (probing pocket depth [PPD] and clinical attachment loss [CAL]) among study participants (n = 120).\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eThis table presents the Pearson correlation coefficients (r) and corresponding p-values for the relationships between antioxidant biomarkers and periodontal disease severity. Significant moderate inverse correlations were observed, indicating that as PPD and CAL increased, uric acid and albumin levels decreased, supporting their potential role as indicators of periodontal tissue destruction.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCorrelation (r)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eInterpretation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUric Acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0038**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eModerate inverse correlation (significant)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAlbumin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eModerate-to-strong inverse correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUric Acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0088**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWeak-to-moderate inverse correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAlbumin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0003**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eModerate inverse correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eSignificance level: p \u0026lt; 0.05 (\u003c/em\u003e), \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01 (**)*\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Gingival Crevicular Fluid, Uric Acid, Albumin, Periodontitis, Type 2 Diabetes Mellitus, Oxidative Stress, Staging, Grading","lastPublishedDoi":"10.21203/rs.3.rs-8133337/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8133337/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003cbr\u003e\nPeriodontitis and type 2 diabetes mellitus (T2DM) are chronic inflammatory conditions with a well-established bidirectional relationship, partially mediated by oxidative stress. Gingival crevicular fluid (GCF) biomarkers such as uric acid (UA) and albumin (ALB) may reflect local redox status and periodontal disease severity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e\u003cbr\u003e\nThis facility-based analytical cross-sectional study aimed to assess the levels of UA and ALB in the GCF of diabetic and non-diabetic patients across different stages and grades of periodontitis based on the 2017 classification system.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003cbr\u003e\nA total of 120 participants were enrolled and divided equally into three groups (n = 40): periodontally healthy individuals, non-diabetic patients with Stage II Grade A periodontitis, and diabetic patients with Stage III Grade B \u0026amp; C periodontitis. Clinical periodontal parameters were recorded. GCF samples were collected using standardized paper strips and analyzed for UA and ALB concentrations using enzyme-linked immunosorbent assay (ELISA). Data were analyzed using one-way ANOVA and Spearman’s correlation tests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003cbr\u003e\nSignificantly lower levels of UA and ALB were observed in periodontitis patients compared to healthy controls (p = 0.001), with the lowest levels found in diabetic individuals with advanced periodontitis. A moderate to strong inverse correlation was found between both biomarkers and clinical parameters, including probing depth and clinical attachment loss (p \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003cbr\u003e\nGCF levels of uric acid and albumin decline with increasing periodontal severity, especially in patients with T2DM. These findings support the potential utility of UA and ALB as adjunctive biomarkers for monitoring periodontal disease progression and tailoring patient-specific periodontal care, particularly in systemically compromised individuals.\u003c/p\u003e","manuscriptTitle":"Gingival Crevicular Fluid Uric Acid and Albumin Levels in Diabetic and Non-Diabetic Patients Across Periodontitis Stages and Grades","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-22 09:27:56","doi":"10.21203/rs.3.rs-8133337/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"80c05d92-4dd4-4165-8ead-520fd3f7ec07","owner":[],"postedDate":"December 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-29T11:10:48+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-22 09:27:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8133337","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8133337","identity":"rs-8133337","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}