Histological analysis of periodontal tissues in patients with autoimmune diseases: a comparative cross-sectional study of inflammatory cell infiltration and epithelial barrier function

Abstract

Background

Periodontal disease exhibits bidirectional associations with autoimmune diseases; however, comprehensive histological, radiographic, and correlational differences in periodontal tissues between patients with varying immune statuses remain poorly characterized.

Objective

To compare inflammatory cell infiltration patterns, junctional epithelium characteristics, radiographic findings, and clinical-histological correlations in periodontal tissues between patients with periodontitis and concurrent autoimmune diseases versus those with periodontitis alone.

Methods

A cross-sectional study was conducted on 40 participants: 20 with periodontitis and autoimmune diseases (rheumatoid arthritis, type 1 diabetes, systemic lupus erythematosus, asthma) and 20 with periodontitis without autoimmune diseases. Periodontal tissue biopsies were analyzed for inflammatory cell infiltration and junctional epithelium characteristics. radiographic parameters were quantified using standardized protocols. A correlation analysis was performed between clinical and histological parameters.

Results

The autoimmune group showed significantly higher inflammatory cell infiltration (36% higher total cell density, p = 0.001), reduced junctional epithelium thickness (185.4 ± 28.7 vs. 242.8 ± 31.2 μm, p = 0.001), and 32% more alveolar bone loss (p = 0.019). Strong correlations between clinical and histological parameters were observed in autoimmune patients (r = 0.65–0.78, p < 0.05) but not in controls.

Conclusions

Patients with autoimmune diseases exhibit enhanced inflammatory cell infiltration, compromised integrity of the junctional epithelium, increased radiographic bone destruction, and altered clinical-histological relationships in periodontal tissues, suggesting a distinct clinical entity requiring specialized management.

Introduction

Periodontitis represents one of the most prevalent chronic inflammatory diseases affecting human populations worldwide, characterized by progressive destruction of the periodontal supporting structures, including the gingiva, periodontal ligament, cementum, and alveolar bone [1]. This multifactorial disease affects approximately 42% of adults aged 30 years and older in the United States alone, with severe forms affecting 7.8% of the adult population, making it a significant public health concern with substantial socioeconomic implications [2]. The pathogenesis of periodontitis involves a complex interplay between pathogenic bacterial biofilms and the host immune response, where the latter often determines the extent and severity of tissue destruction [3].

The traditional understanding of periodontal disease etiology has evolved significantly from the early concepts of specific bacterial pathogens to the current recognition of dysbiotic microbial communities that trigger disproportionate host inflammatory responses [4]. Recent evidence demonstrates that while bacterial dysbiosis serves as the initiating factor, it is the subsequent recruitment of immune cells and the release of inflammatory mediators that ultimately determine the progression and severity of periodontitis [5].

The link between periodontitis and systemic conditions, particularly autoimmune diseases, is increasingly recognized due to shared inflammatory pathways [6, 7]. Autoimmune diseases, affecting 5–8% of the population, involve the immune system attacking the body’s own tissues [8].

The connection between periodontal and autoimmune diseases is complex, involving mechanisms like molecular mimicry, where bacterial antigens resemble host proteins, triggering cross-reactive immune responses [9]. This is well-documented in the association between Porphyromonas gingivalis and rheumatoid arthritis [10]. Periodontitis is associated with an increased risk for several autoimmune conditions, including rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes [11, 12], with shared genetic factors contributing to this link [13].

The inflammatory cascade in periodontitis involves both innate and adaptive immunity [14]. Neutrophils, the first line of defense, can have altered function in autoimmune diseases, leading to impaired bacterial clearance and increased tissue damage [15, 16].

Macrophages play equally crucial roles in periodontal pathogenesis, exhibiting remarkable plasticity in their activation states in response to the local microenvironment [17]. The balance between pro-inflammatory M1 macrophages and anti-inflammatory M2 macrophages has been shown to influence disease progression, with an increased M1/M2 ratio associated with more severe periodontal destruction [18, 19].

The adaptive immune response in periodontitis involves the activation of T-helper cells, with Th1 and Th17 responses predominating in destructive lesions [20]. Th17 cells, in particular, have been implicated in both periodontal disease and various autoimmune conditions, producing interleukin-17, which promotes neutrophil recruitment and osteoclast activation [21]. The presence of regulatory T cells (Tregs) provides a counterbalancing mechanism, but their function may be compromised in autoimmune diseases, leading to uncontrolled inflammatory responses [22].

Histological analysis of periodontal tissues provides crucial insights into disease pathogenesis [23]. In autoimmune diseases, this analysis can reveal distinct patterns of immune cell infiltration and tissue damage [24].

The junctional epithelium represents a critical component of the periodontal defense mechanism, serving as a physical and immunological barrier between the oral environment and the underlying periodontal tissues [25, 26]. In periodontal disease, the junctional epithelium undergoes significant changes, including apical migration, increased permeability, and altered cellular composition, which contribute to disease progression [27].

Recent research highlights the role of inflammasomes in mediating the inflammatory response [28]. These protein complexes serve as sensors of danger signals and mediate the maturation and release of pro-inflammatory cytokines such as interleukin-1β and interleukin-18 [29]. Excessive activation of inflammasomes has been associated with inflammatory dysregulation and tissue damage, with patients exhibiting elevated inflammasome levels that are proportional to disease severity [30]. In autoimmune diseases, inflammasome activation may be further enhanced, contributing to the observed increased susceptibility to periodontal disease [31].

Given the bidirectional relationship between periodontal and autoimmune diseases, managing one can positively impact the other [32, 33]. However, there is a knowledge gap regarding the specific histological differences in periodontitis in patients with autoimmune diseases [34]. This study aims to address this gap by comparing inflammatory cell infiltration and junctional epithelium characteristics in patients with periodontitis with and without concurrent autoimmune diseases. We hypothesize that patients with autoimmune diseases will exhibit enhanced inflammatory infiltration and compromised epithelial barrier function.

Materials and methods

Study design and ethical considerations

This cross-sectional comparative study was conducted at the College of Dentistry, University of Kufa, Iraq, between January 2024 and December 2024. The study protocol was approved by the Institutional Review Board (IRB) of the University of Kufa (approval number: IRB-2024-001), and all procedures were conducted by the Declaration of Helsinki and its subsequent amendments. Written informed consent was obtained from all participants before enrollment, following a comprehensive explanation of the study’s objectives, procedures, potential risks, and benefits.

Sample size calculation

A sample size calculation was performed using G*Power software version 3.1.9.7, based on pilot data showing a mean difference of 36 cells per high-power field in total inflammatory cell count between groups. With an effect size of 1.8, α = 0.05, power = 0.80, and a 1:1 allocation ratio, a minimum of 12 participants per group was required. The sample size was increased to 20 participants per group (n = 40 total) to account for potential dropouts (20%) and enhance power for secondary analyses, providing more than 95% power for the primary outcome and more than 80% power for correlation analyses.

Study population and participant selection

A total of 40 participants were recruited for this study through convenience sampling from patients attending the periodontal clinic at the College of Dentistry. Participants were divided into two groups based on their systemic health status: Group A consisted of 20 individuals with periodontitis and concurrent autoimmune diseases, while Group B comprised 20 individuals with periodontitis but without autoimmune diseases, serving as the control group.

Inclusion criteria for Group A included: (1) confirmed diagnosis of periodontitis based on the 2017 World Workshop classification criteria [35], (2) documented diagnosis of at least one autoimmune disease including rheumatoid arthritis, systemic lupus erythematosus, type 1 diabetes mellitus, or asthma (see Table 1 for distribution), (3) For the autoimmune group (Group A), participants were required to be on a stable medication regimen (including corticosteroids, immunosuppressants, or biologics) for at least three months prior to enrollment to ensure that the observed periodontal status reflected a managed, chronic disease state rather than an acute flare or recent treatment change (4) age between 25 and 65 years, (5) presence of at least 20 natural teeth, and (6) willingness to participate in the study. The inclusion criteria for Group B were identical, except for the absence of any diagnosed autoimmune diseases.

Table 1.

Distribution of autoimmune diseases and immunosuppressive medications in group A(n = 20 per group)

Autoimmune Disease	Number of Patients	Immunosuppressive Medications
Rheumatoid Arthritis	6	Methotrexate, Biologics
Type 1 Diabetes	6	Insulin Therapy
Systemic Lupus Erythematosus	4	Corticosteroids, Hydroxychloroquine
Asthma	2	Inhaled Corticosteroids
RA + T1DM (Concurrent)	2	Methotrexate, Biologics for R.A

Abbreviations: RA Rheumatoid Arthritis, T1DM Type 1 Diabetes

Exclusion criteria for Group B (controls) included: (1) pregnancy or lactation, (2) current use of immunosuppressive medications or corticosteroids, (3) history of periodontal therapy within the previous six months, (4) current smoking or tobacco use within the past year, (5) presence of acute periodontal abscess or necrotizing periodontal diseases, (6) systemic conditions that could affect periodontal status, or use of other medications known to affect periodontal status (e.g., calcium channel blockers, anticonvulsants), (7) use of antibiotics within the past three months, and (8) inability to provide informed consent. For Group A (autoimmune), the same exclusion criteria applied except for immunosuppressive medications, as patients on stable immunomodulatory therapy for at least three months were included.

Clinical examination protocol

All clinical examinations were performed by a single, calibrated examiner (inter-examiner reliability, κ > 0.85), using standardized protocols and instruments. Before examination, participants underwent professional supragingival plaque removal to ensure accurate assessment of periodontal parameters. Clinical measurements were recorded at six sites per tooth (mesiobuccal, buccal, distobuccal, mesiolingual, lingual, and distolingual) using a calibrated periodontal probe (UNC-15, Hu-Friedy, Chicago, IL, USA).

The following clinical parameters were assessed and recorded: (1) Probing depth (PD), measured as the distance from the gingival margin to the base of the periodontal pocket, (2) Clinical attachment level (CAL), calculated as the distance from the cemento-enamel junction to the base of the periodontal pocket, (3) Bleeding on probing (BOP), recorded as present or absent within 30 s of gentle probing, (4) Plaque index (PI), assessed using the Silness and Löe index on a scale of 0–3, and (5) Calculus index (CI), evaluated using the simplified oral hygiene index on a scale of 0–3.

Tissue collection and biopsy procedure

Periodontal tissue biopsies were obtained from sites exhibiting clinical signs of periodontitis, specifically areas with probing depths of ≥ 5 mm and clinical attachment loss of ≥ 3 mm. All biopsies were taken from the buccal aspect of single-rooted teeth with the most severe periodontal destruction to ensure homogeneity.

Before biopsy collection, the surgical site was thoroughly anesthetized using 2% lidocaine with 1:100,000 epinephrine (Septodont, Saint-Maur-des-Fossés, France) administered via local infiltration. The area was then isolated using rubber dam isolation when possible, and the surgical site was disinfected with 0.12% chlorhexidine gluconate solution.

Tissue biopsies were obtained using a standardized surgical technique employing a #15 scalpel blade (Swann-Morton, Sheffield, UK) to create precise incisions. The biopsy specimens measured approximately 3 × 2 × 2 mm and included both epithelial and connective tissue components to ensure comprehensive histological analysis. Care was taken to minimize trauma to surrounding tissues and to obtain specimens that were representative of the diseased periodontal tissues.

Immediately following collection, tissue specimens were placed in 10% neutral buffered formalin solution (pH 7.4) for fixation. The fixation process was maintained for 24–48 h at room temperature to ensure adequate tissue preservation while preventing over-fixation that could compromise subsequent histological analysis.

Instrument sterilization and infection control

All surgical instruments were sterilized using standard autoclave protocols (121 °C for 15 min at 15 psi) before use. Single-use disposable items were used whenever possible to minimize the risk of cross-contamination. The surgical area was prepared using standard aseptic techniques, and all personnel involved in the procedure wore appropriate personal protective equipment, including sterile gloves, masks, and protective eyewear.

Histological processing and staining

Following fixation, tissue specimens underwent standard histological processing using an automated tissue processor (Leica TP1020, Leica Biosystems, Wetzlar, Germany). The processing protocol included sequential dehydration through graded alcohol solutions (70%, 80%, 95%, and 100% ethanol), clearing with xylene, and infiltration with paraffin wax at 60 °C [36].

Tissue specimens were then embedded in paraffin blocks using a tissue embedding station (Leica EG1150H, Leica Biosystems), ensuring proper orientation to obtain representative cross-sections of the periodontal tissues. Serial sections of 4–5 μm thickness were cut using a rotary microtome (Leica RM2125RTS, Leica Biosystems) and mounted on positively charged glass slides.

Hematoxylin and eosin (H&E) staining was performed using a standardized protocol. Briefly, sections were deparaffinized in xylene, rehydrated through graded alcohols, and stained with Harris hematoxylin for 5 min, followed by differentiation in acid alcohol. After washing in running water and bluing in ammonia water, the sections were counterstained with eosin for 2 min, dehydrated through a graded series of alcohols, cleared in xylene, and mounted with DPX mounting medium [36].

Histological analysis and quantification

Histological analysis was performed using a light microscope (Olympus BX53, Olympus Corporation, Tokyo, Japan) equipped with a digital camera system (Olympus DP73, Olympus Corporation). All analyses were conducted by a single examiner blinded to the group assignment to ensure objectivity and minimize bias.

Inflammatory cell infiltration was graded on a 4-point scale adapted from Smith et al. (2015) [37]: 0 = no inflammation; 1 = mild, scattered inflammation; 2 = moderate, diffuse inflammation; 3 = severe, dense inflammation with lymphoid aggregates. The epithelial organization score was defined as: 0 = intact, well-organized basal layer; 1 = mild disorganization with some loss of polarity; 2 = moderate disorganization with significant loss of polarity and intercellular edema; 3 = severe disorganization with complete loss of structure and evidence of epithelial breakdown [37].

Inflammatory cell infiltration was assessed using a standardized point counting method at 400× magnification. Five representative fields per section were analyzed, and inflammatory cells were identified and counted based on their morphological characteristics. Neutrophils were identified by their multilobed nuclei and granular cytoplasm, lymphocytes by their small, round, darkly staining nuclei with minimal cytoplasm, plasma cells by their eccentric nuclei and basophilic cytoplasm, and macrophages by their large, oval nuclei and abundant cytoplasm.

Junctional epithelium thickness was measured using calibrated image analysis software (ImageJ, National Institutes of Health, Bethesda, MD, USA). Measurements were taken at five standardized locations along the junctional epithelium, and the mean thickness was calculated for each specimen. The junctional epithelium was identified based on its characteristic morphology and location adjacent to the tooth surface.

Radiographic analysis

Standardized periapical radiographs were obtained for all participants using a digital radiographic system (Kodak RVG 6100, Carestream Health, Rochester, NY, USA) with standardized exposure parameters (70 kVp, 8 mA, 0.08 s). Radiographs were taken using the paralleling technique with XCP positioning devices to ensure reproducible geometry and minimize distortion.

Radiographic analysis was performed by two calibrated examiners (inter-examiner reliability κ = 0.89) using digital imaging software (ImageJ, National Institutes of Health, Bethesda, MD, USA). The following parameters were assessed:

• Alveolar Bone Loss Assessment: Bone loss percentage was calculated as the distance from the cemento-enamel junction (CEJ) to the alveolar bone crest divided by the total root length, multiplied by 100. Measurements were taken at the mesial and distal aspects of each tooth and averaged.

• Periodontal Ligament Space Analysis: Periodontal ligament space widening was assessed qualitatively and classified as: (1) normal - uniform thin radiolucent line, (2) mild widening - slight increase in radiolucency, (3) moderate widening - obvious increase in space width, or (4) severe widening - marked increase with loss of lamina dura continuity.

• Lamina Dura Evaluation: The integrity of the lamina dura was assessed and classified as intact, partially disrupted, or completely absent. All measurements were performed under standardized viewing conditions with consistent brightness and contrast settings.

Statistical analysis

Statistical analysis was performed using SPSS software version 28.0 (IBM Corporation, Armonk, NY, USA). Descriptive statistics were calculated for all variables, including means, standard deviations, and ranges for continuous variables, as well as frequencies and percentages for categorical variables. The normality of data distribution was assessed using the Shapiro-Wilk test.

For comparison between groups, independent samples t-tests were used for normally distributed continuous variables, while the Mann-Whitney U test was employed for non-normally distributed data. Chi-square tests or Fisher’s exact tests were used for categorical variables as appropriate. Correlation analyses were performed using Pearson or Spearman correlation coefficients, depending on data distribution. A Bonferroni correction was applied to the p-values to account for multiple comparisons, thereby reducing the risk of false positives.

A p-value of < 0.05 was considered statistically significant for all analyses. Effect sizes were calculated using Cohen’s d for continuous variables to assess the clinical significance of observed differences. All statistical tests were two-tailed, and confidence intervals were set at a 95% confidence level.

Data management and quality control

All data were collected using standardized case report forms and entered into a secure electronic database with built-in range and consistency checks. Double data entry was performed for 20% of cases to ensure data accuracy, with discrepancies resolved through review of source documents.

Regular calibration exercises were conducted throughout the study period to maintain consistency in clinical measurements and histological assessments. Inter-examiner and intra-examiner reliability were assessed using intraclass correlation coefficients, with values > 0.80 considered acceptable for all measurements.

Results

Participant characteristics and demographics

A total of 40 participants were enrolled and divided into two groups of 20: an autoimmune group (Group A) and a control group (Group B). The groups were well-matched, with no statistically significant differences in age (p = 0.512) or gender distribution (p = 0.685) (Table 2). The specific autoimmune diseases represented in Group A are detailed in Fig. 1.

Table 2.

Demographic and clinical characteristics of study participants ( n = 20 per group

Parameter	Group A (n = 20)	Group B (n = 20)	p-value	Effect Size (Cohen’s d)
Age (years) ± SD	42.3 ± 8.7	39.8 ± 9.2	0.512	0.28
Gender (Female/Male)	6/4	5/5	0.685	-
Probing Depth (mm) ± SD	6.8 ± 1.2	5.4 ± 0.9	0.008*	1.32
Clinical Attachment Level (mm) ± SD	7.2 ± 1.5	5.8 ± 1.1	0.021*	1.07
Bleeding on Probing (%) ± SD	78.5 ± 12.3	65.2 ± 10.8	0.015*	1.15
Plaque Index ± SD	2.1 ± 0.4	1.8 ± 0.3	0.045*	0.85
Calculus Index ± SD	1.9 ± 0.5	1.6 ± 0.4	0.142	1.11

Abbreviations: SD standard deviation; (%) percentage, mm millimeter

*Statistically significant difference (p < 0.05)

Effect sizes: small (0.2), medium (0.5), large (0.8)

Fig. 1.

Autoimmune Disease Distribution

Clinical parameter analysis

Analysis of clinical parameters, presented in Table 2, confirmed that patients with autoimmune disease had a significantly more severe periodontal presentation. Group A showed deeper probing depths compared to Group B (6.8 ± 1.2 mm vs. 5.4 ± 0.9 mm, p = 0.008) and had sustained greater clinical attachment loss (7.2 ± 1.5 mm vs. 5.8 ± 1.1 mm, p = 0.021). Furthermore, these patients demonstrated more widespread inflammation, evidenced by a significantly higher percentage of sites with bleeding on probing (78.5 ± 12.3% vs. 65.2 ± 10.8%, p = 0.015). Plaque accumulation was also significantly higher in the autoimmune group (2.1 ± 0.4 vs. 1.8 ± 0.3, p = 0.045), although the difference in calculus index did not reach statistical significance (1.9 ± 0.5 vs. 1.6 ± 0.4, p = 0.142).

Histological analysis of inflammatory cell infiltration

Comprehensive histological analysis revealed significant differences in inflammatory cell infiltration patterns between the two groups (Fig. 2). The quantitative assessment of inflammatory cells demonstrated consistently higher cell counts across all inflammatory cell types in Group A compared to Group B, as detailed in Table 3 and illustrated in Fig. 4.

Fig. 2.

Comprehensive histological analysis comparing gingival tissues from patients with autoimmune and healthy individuals (H&E stain). The top row focuses on the inflammatory cell infiltrate in the lamina propria, while the bottom row illustrates alterations in the squamous epithelium. A Gingival mucosa from a patient with rheumatoid arthritis, demonstrating a rich and diffuse chronic inflammatory cell infiltrate (arrows) and ectatic blood vessels (BV) in the lamina propria. The dense accumulation of inflammatory cells indicates active inflammation. (×40 magnification). B Gingival mucosa from a patient with asthma, showing a diffuse infiltrate of chronic inflammatory cells (IC) and ectatic blood vessels (BV). The infiltrate is predominantly composed of lymphocytes and plasma cells. (×40 magnification). C Gingival mucosa from a patient with type 1 diabetes mellitus, revealing organized collections of chronic inflammatory cells (IC) infiltrating the lamina propria, associated with tissue destruction. (×40 magnification). D Gingival mucosa from a patient with both rheumatoid arthritis and type 1 diabetes mellitus, exhibiting squamous epithelium parakeratosis and acanthosis as a response to chronic inflammation. (×40 magnification). E Gingival mucosa from a patient with systemic lupus erythematosus, illustrating squamous epithelium parakeratosis and acanthosis with epithelial disorganization characteristic of autoimmune-associated periodontal disease. (×40 magnification). F Gingival mucosa from a healthy patient with periodontitis, showing a less dense, diffuse infiltrate of chronic inflammatory cells (IC) alongside fibroblast cells (arrows) and collagen fibers. The tissue architecture appears more organized compared to the autoimmune samples. (×40 magnification)

Table 3.

Inflammatory cell counts in periodontal tissues (cells per high-power field) ( n = 20 per group)

Cell Type	Group A (n = 20)	Group B (n = 20)	p-value	Effect Size (Cohen’s d)
Neutrophils	45.2 ± 8.7	32.1 ± 6.3	0.002*	1.69
Lymphocytes	38.6 ± 7.2	28.4 ± 5.8	0.004*	1.56
Plasma Cells	28.9 ± 5.4	21.7 ± 4.2	0.006*	1.48
Macrophages	22.3 ± 4.8	16.8 ± 3.9	0.012*	1.26
Total Inflammatory Cells	135.0 ± 18.3	99.0 ± 14.2	0.001*	2.18
Inflammatory infiltration score	2.8 ± 0.4	1.2 ± 0.3	0.001*	4.73

*Statistically significant difference (p < 0.05) ;Scoring criteria: 0 = no inflammation; 1 = mild, scattered inflammation; 2 = moderate, diffuse inflammation; 3 = severe

Fig. 4.

Relationships between Clinical Periodontal Parameters and Inflammatory Cell Counts, and Comparison of Correlation Strengths between Autoimmune and Control Groups. A Probing depth versus total inflammatory cell count showing strong positive correlation in the autoimmune group (Group A) compared to weak correlation in controls (Group B). B Clinical attachment level versus neutrophil count demonstrating enhanced neutrophil infiltration in autoimmune patients. C Probing depth versus junctional epithelium (JE) thickness showing significant negative correlation in autoimmune patients, indicating reduced epithelial thickness with increased periodontal severity. D Bleeding on probing versus total inflammatory cell count illustrating the association between clinical bleeding and inflammatory cell infiltration. E Correlation strength comparison bar chart contrasting the strength of correlations between clinical parameters and histological findings in autoimmune (Group A, red bars) versus control (Group B, blue bars) groups, demonstrating significantly stronger clinical-histological relationships in autoimmune patients. The abbreviations box provides definitions for all parameters used in the analysis

Representative histological images from autoimmune patients showed dense inflammatory cell infiltration with prominent vascular changes (Fig. 2A-E). In contrast, control patients demonstrated more organized tissue architecture with less intense inflammatory responses (Fig. 2F).

The total inflammatory cell count was 36% higher in Group A compared to Group B (135.0 ± 18.3 vs. 99.0 ± 14.2 cells/field, p = 0.001). The infiltration of all major inflammatory cell types—neutrophils, lymphocytes, plasma cells, and macrophages—was significantly elevated in Group A, as shown in Table 3; Fig. 2.

Qualitative assessment of Inflammatory infiltration using a standardized scoring system revealed significantly highly infiltration score in Group A (score 2.8 ± 0.4 ) compared to Group B (score 1.2 ± 0.3, p = 0.001) (Table 3).

Junctional epithelium analysis

Detailed morphometric analysis of the junctional epithelium revealed significant structural differences between the two groups, as presented in Table 4 and illustrated in Fig. 3. Representative measurements using ImageJ software demonstrated apparent differences in epithelial thickness and organization between groups (Fig. 3A-B).

Table 4.

Junctional epithelium characteristics (n = 20 per group)

Parameter	Group A (n = 20)	Group B (n = 20)	p-value	Effect Size (Cohen’s d)	Range (min-max)	Reduction (%)
Mean Thickness (µm)	185.4 ± 28.7	242.8 ± 31.2	0.001*	1.94	150.2–210.6	24%
Minimum Thickness (µm)	142.3 ± 22.1	198.6 ± 26.4	0.001*	2.31	110.5–170.1	28%
Maximum Thickness (µm)	228.7 ± 35.2	287.1 ± 38.9	0.003*	1.58	180.9–260.3	20%
Epithelial Organization Score	2.6 ± 0.5	0.8 ± 0.4	0.001*	4.05

Abbreviations: (%) percentage, µm micrometer

*Statistically significant difference (p < 0.05); Epithelial Organization Score: 0 = intact, well-organized basal layer; 1 = mild disorganization with some loss of polarity; 2 = moderate disorganization with significant loss of polarity and intercellular edema; 3 = severe disorganization with complete loss of structure and evidence of epithelial breakdown

Fig. 3.

Junctional Epithelium Thickness Measurements. A Representative measurement of junctional epithelium thickness using ImageJ software in a patient with autoimmune disease, showing reduced thickness (185.4 μm average) and poor epithelial organization. The measurement demonstrates the compromised epithelial barrier function characteristic of autoimmune patients. B Representative measurement of junctional epithelium thickness in a control patient without autoimmune disease, showing greater thickness (242.8 μm average) and better epithelial organization. The image illustrates the maintained epithelial integrity in patients without systemic immune dysfunction

The structural integrity of the junctional epithelium was significantly compromised in the autoimmune group. Morphometric analysis showed that the mean thickness of the junctional epithelium was reduced by 24% in Group A compared to Group B (p = 0.001), with significant reductions also observed in minimum and maximum thickness measurements (Table 4). Qualitative assessment of epithelial organization using a standardized scoring system revealed significantly poorer organization in Group A (score 2.6 ± 0.5 ) compared to Group B (score 0.8 ± 0.4, p = 0.001) (Table 4).

Correlation analysis

Correlation analysis revealed several significant associations between clinical parameters and histological findings, as illustrated in Fig. 4 and summarized in Table 5. A strong relationship between clinical severity and histological findings was evident only in the autoimmune group (Table 5). In Group A, greater probing depth and clinical attachment loss were strongly correlated with higher total inflammatory cell counts (r = 0.78 for both, p < 0.05) and reduced junctional epithelium thickness (r ≈ -0.72, p < 0.05). In contrast, no significant correlations between these key clinical and histological parameters were found in the Group B (Fig. 4).

Table 5.

Correlation analysis between clinical parameters and histological findings (n = 20 per group)

Clinical Parameter	Histological Parameter	Group A (Autoimmune)		Group B (Control)
		r	p-value	r	p-value
Probing Depth	Total Inflammatory Cell Count	0.78	0.008*	0.34	0.334
	Mean JE Thickness	-0.72	0.018*	-0.28	0.431
	Neutrophil Count	0.74	0.014*	0.31	0.385
	Lymphocyte Count	0.68	0.030*	0.25	0.486
Clinical Attachment Level	Total Inflammatory Cell Count	0.78	0.008*	0.29	0.416
	Neutrophil Count	0.69	0.027*	0.33	0.351
	Epithelial Organization Score	-0.65	0.041*	-0.22	0.541
	Mean JE Thickness	-0.71	0.021*	-0.26	0.467
Bleeding on Probing	Lymphocyte Count	0.71	0.021*	0.34	0.334
	Plasma Cell Count	0.66	0.037*	0.28	0.431
	Total Inflammatory Cell Count	0.73	0.016*	0.31	0.385
Plaque Index	Neutrophil Count	0.62	0.056	0.19	0.598
	Total Inflammatory Cell Count	0.58	0.078	0.23	0.520

Abbreviations: JE Junctional Epithelium, r correlation coefficient

*Statistically significant correlation (p < 0.05)

Radiographic analysis

Radiographic assessment complemented the histological findings, showing more severe alveolar bone loss in Group A compared to Group B. The comprehensive radiographic analysis is presented in Table 6, demonstrating significant differences between groups across multiple radiographic parameters.

Table 6.

Radiographic analysis results (n = 20 per group)

Parameter	Group A (n = 20)	Group B (n = 20)	p-value	Effect Size (Cohen’s d)
Alveolar Bone Loss (%)	34.7 ± 8.2	26.3 ± 6.8	0.019*	1.13
Mesial Bone Loss (%)	36.2 ± 9.1	27.8 ± 7.2	0.025*	1.02
Distal Bone Loss (%)	33.1 ± 8.8	24.9 ± 6.9	0.021*	1.05
PDL Space Widening Score	2.8 ± 0.9	1.9 ± 0.7	0.015*	1.12
Lamina Dura Disruption Score	2.4 ± 0.8	1.6 ± 0.6	0.012*	1.15
Categorical Analysis (n, %)
PDL Space Widening	Group A	Group B	p-value
Normal	2 (10%)	10 (50%)	0.070
Mild	4 (20%)	6 (30%)
Moderate	8 (40%)	4 (20%)
Severe	6 (30%)	0 (0%)
Lamina Dura Integrity	Group A	Group B	p-value
Intact	4 (20%)	12 (60%)	0.045*
Partially Disrupted	10 (50%)	8 (40%)
Completely Absent	6 (30%)	0 (0%)

Abbreviations: PDL Periodontal Ligament, (%) percentage

*Statistically significant difference (p < 0.05)

Radiographic findings corroborated the clinical and histological results, demonstrating significantly greater periodontal tissue destruction in the autoimmune group (Table 6). Patients in Group A had 32% more mean alveolar bone loss compared to Group B (p = 0.019). They also exhibited significantly more pronounced periodontal ligament space widening and greater disruption of the lamina dura (p < 0.05 for both).

Subgroup analysis by autoimmune disease type

Subgroup analysis, suggested a hierarchy of periodontal disease severity among the different autoimmune conditions (Fig. 5). Patients with concurrent rheumatoid arthritis and type 1 diabetes mellitus exhibited the most severe periodontal pathology. Overall severity from most to least severe was: simultaneous RA + T1DM > RA > T1DM > SLE > asthma > controls.This trend was consistent across clinical, histological, and radiographic parameters, as visualized in the heatmap (Fig. 5E).

Fig. 5.

Periodontal Disease Characteristics Across Different Autoimmune Subgroups. A Total inflammatory cell infiltration by disease type, showing highest infiltration in patients with concurrent rheumatoid arthritis and type 1 diabetes mellitus (RA+T1DM), followed by rheumatoid arthritis (RA) alone, type 1 diabetes (T1DM), systemic lupus erythematosus (SLE), asthma, and controls. B Epithelial barrier function (junctional epithelium thickness) by disease type, demonstrating the most compromised epithelial barrier in RA+T1DM patients and progressively better epithelial integrity in other groups. C Clinical severity parameters by disease type, displaying both probing depth (red bars) and clinical attachment level (blue bars) across all autoimmune subgroups and controls. D Radiographic bone destruction by disease type, showing the percentage of alveolar bone loss for each disease category, with RA+T1DM exhibiting the most severe bone destruction. E Comprehensive disease severity heatmap (red = more severe, white = less severe) integrating inflammatory cell count, epithelial barrier function, clinical parameters, and radiographic findings across all disease types and controls, providing a visual summary of disease severity hierarchy: RA+T1DM > RA > T1DM > SLE > asthma > controls

Discussion

Our findings demonstrate that individuals with autoimmune diseases exhibit markedly enhanced inflammatory cell infiltration and compromised junctional epithelium integrity, suggesting fundamental alterations in the periodontal immune response and tissue architecture.

The findings of this study confirm and extend existing knowledge regarding the interplay between systemic autoimmune diseases and periodontal health. Our results confirm previous clinical observations that patients with autoimmune conditions present with more severe periodontitis [38], while providing detailed histological evidence quantifying the cellular and structural changes underlying these clinical signs [39]. The 36% greater inflammatory cell infiltration provides an accurate measure of this effect. Strong correlations between clinical and histological parameters in the autoimmune group but not in controls suggest a specific pathophysiological process where systemic immune dysfunction directly drives tissue breakdown, supporting the concept that periodontitis in autoimmune patients represents a separate clinical entity [40, 41]. The enhanced inflammatory cell infiltration in our autoimmune cohort aligns with current understanding of periodontal pathogenesis. The 41% increase in neutrophil density reflects dysregulated neutrophil function leading to impaired bacterial clearance and increased tissue damage [42–44], consistent with findings showing bacterial dysbiosis induces exaggerated inflammatory responses [28]. The elevated lymphocyte (36%) and plasma cell (33%) counts reflect chronic inflammation and heightened adaptive and humoral immune responses, potentially involving molecular mimicry [45–49]. The 33% increase in macrophage infiltration suggests a skew toward a pro-inflammatory M1 phenotype [50, 51].

The compromised junctional epithelium, evidenced by a 24% reduction in mean thickness and poorer organization, suggests a weakened epithelial barrier that could facilitate bacterial penetration and perpetuate inflammation [52]. These changes may stem from systemic effects of autoimmune diseases on wound healing and epithelial cell dynamics, supported by the strong negative correlation between epithelial thickness and inflammatory cell infiltration [53, 54]. These findings suggest that patients with autoimmune diseases may require more intensive periodontal monitoring and treatment [55].

Our subgroup analysis provides insights into the differential effects of various autoimmune diseases on periodontal tissues. Rheumatoid arthritis patients showed the most severe histological changes, consistent with the well-established bidirectional relationship and shared inflammatory pathways including citrullinated proteins and anti-citrullinated protein antibodies [56, 57]. Type 1 diabetes patients showed intermediate changes, aligning with the known effects of hyperglycemia on immune function and wound healing [58]. The relatively milder changes in systemic lupus erythematosus patients may reflect the episodic nature of this condition and potential protective effects of immunosuppressive treatments [59].

While asthma is classically considered an immunoinflammatory condition rather than a classical autoimmune disease, we included patients with severe, non-allergic asthma phenotypes based on emerging evidence that these phenotypes share features with autoimmune disorders. Recent studies have identified an autoimmune endotype of severe asthma characterized by the presence of sputum autoantibodies against eosinophil peroxidase and autologous cellular components [60]. Specifically, severe asthma phenotypes have been associated with the presence of autoantibodies, including anti-epithelial antibodies and anti-nuclear antibodies, as well as a Th1/Th17-dominant inflammatory profile similar to other autoimmune conditions [61]. Airway autoantibodies directed against macrophage scavenger receptors have been shown to be determinants of asthma severity and are associated with exacerbations and steroid dependence [62]. Furthermore, these patients exhibit systemic inflammation and immune dysregulation that parallel the pathophysiological mechanisms observed in established autoimmune diseases [63]. Patients with asthma enrolled in our study were thoroughly phenotyped according to the clinical criteria for severe, nonatopic asthma namely poor response to treatment, evidence of systemic inflammation and no allergic sensitization [64, 65].

These observations are supported by radiographs showing increased bone loss and widening of periodontal ligament, indicative of the downstream effects of an enhanced inflammatory response [66].

Mechanistically, this may be due to NLRP3 inflammasome hyperactivity, observed in both periodontal [67] and autoimmune disease pathogenesis [68], and NeTs formation that enhance tissue destruction and provide an abundant source of autoantigens [69]. These studies support an association between the presence of rheumatologic and non-rheumatologic diseases and severe periodontitis suggesting a need for non-surgical treatment accompanied by anti-inflammatory adjuncts, in addition to essential integrated health care between medicine and dentistry [70–72].

Of course all type 1 diabetic patients in our study were treated with insulin. Insulin, despite being non-immunosuppressive agent, metabolically and immunologically may affect the immune response of the periodontal tissues. Insulin’s role in inflammation is complex, and there are anti-inflammatory effects via inhibition of NF-κB signaling pathway, but insulin is proinflammatory in the setting of insulin resistance [73, 74]. Another aspect that is directly related to insulin therapy and of critical importance in defining the health status of periodontal tissues is glycemic control. High blood glucose levels are also linked with more severe periodontal inflammation, delayed wound healing and altered immune cell function [75, 76], while poor glycemic control is a potential risk factor for acute necrotizing ulcerative gingivitis [77]. Diabetes and periodontitis have a reciprocal relationship, whereby periodontal inflammation may induce insulin resistance in the host, but also hyperglycemia will enhance destruction of the periodontium [77]. The intermediate histological findings in our type 1 diabetes subgroup appear to be indicative of the interplay between both the underlying autoimmune process, hyperglycemia-induced metabolic effects and modulatory impact of insulin therapy on inflammation [78].

The study has several limitations. The sample size might not be sensitive enough to observe smaller differences. The cross-sectional nature does not allow establishment of causality. There was a possibility that the heterogeneity of autoimmune diseases might have confounded factors. These limitations could be answered by future large, homogeneous cohort studies with a long-term follow-up visit.

Furthermore, in our histological analysis of tissues, we exclusively used H&E sections. The immunohistochemical markers (e.g., CD3, CD68, IL-17, occludin/ZO-1) would give more precise characterization of immune cell subgroups and share intrinsic principles with the molecular changes that should be applied in the further studies.

The lack of multicenter nature and limited one type of population are the disadvantages. Ethnicity, genetic background and living conditions may modulate the association between various autoimmune diseases and periodontal disease, greater evidence of which could be obtained through multicenter trials including a variety of populations.

The possible confounder of medications taken by group-A subjects also should be considered. Corticosteroids, immunosuppressive agents (including methotrexate), and biologic drugs modify immune responses and may also act directly on the parameters measured. Adverse effects of corticosteroids Corticosteroids induce anti-inflammatory effects; however, prolonged use might have negative impact on tissue healing and bone metabolism [79, 80]. Some biologics directed to specific inflammatory cytokines may alleviate some types of periodontal destruction [81, 82]. Due to the heterogeneity of regimens and numbers, no formal analysis could be done with respect to medication effect. To disentangle these complex relations, further studies with larger and better distributed cohorts are necessary [83].

Despite these limitations, our study provides valuable insights into the histological characteristics of periodontal disease in patients with autoimmune diseases. The consistent patterns across multiple inflammatory cell types and significant alterations in epithelial structure provide strong evidence for fundamental differences in periodontal pathophysiology in this population, contributing to the growing body of evidence supporting the bidirectional relationship between periodontal disease and systemic health.

Longitudinal studies to examine progression of disease, as well as further understanding of specific molecular pathways and testing therapies directed toward these pathways are needed. Clinical investigations of separate autoimmune diseases and their treatment influences on oral periodontal tissues would be useful. Biomarkers of periodontal disease severity in autoimmune patients would have tremendous clinical utility.

Our findings have implications beyond periodontal medicine. The elevated inflammatory cell infiltration and impaired epithelial barrier function may also be present in other tissues targeted by autoimmune diseases, indicating that the periodontal tissue might serve as an accessible model to investigate immune dysfunction in autoimmune diseases.

Conclusions

This comparative cross-sectional study demonstrates significant histological differences in periodontal tissues between patients with autoimmune diseases and controls. Autoimmune patients exhibited 36% greater inflammatory cell infiltration across all immune cell types and 24% reduction in junctional epithelium thickness, indicating compromised epithelial barrier function and enhanced inflammatory responses. Strong correlations between clinical parameters and histological findings in autoimmune patients (r = 0.65–0.78) versus weak correlations in controls suggest that systemic immune dysfunction may be associated with altered periodontal disease pathophysiology, though the cross-sectional nature of this study precludes causal inference. Our findings suggest that autoimmune diseases may influence inflammatory responses and structural characteristics of periodontal tissues. Further longitudinal studies are required to clarify the causal relationships. These findings support the concept that periodontal disease in autoimmune patients represents a distinct clinical entity requiring specialized management approaches, including more frequent monitoring and potentially modified treatment protocols incorporating anti-inflammatory strategies. Longitudinal studies investigating disease progression patterns and targeted therapeutic interventions for this vulnerable population are warranted to optimize clinical outcomes and advance our understanding of the periodontal-systemic health relationship.

Authors’ contributions

Conceptualization: S.M.I., A.M.K.; Methodology: S.M.I., A.M.K.; Formal Analysis: S.M.I., M.A.A.H.; Investigation: S.M.I., A.M.K.; Resources: S.M.I., A.M.K.; Data Curation: S.M.I., A.M.K.; Writing—Original Draft: S.M.I.; Writing—Review & Editing: S.M.I., A.M.K.; Visualization: S.M.I.; Supervision: A.M.K., M.A.A.H; Project Administration: S.M.I.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data availability

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request, subject to appropriate ethical and legal considerations and institutional review board approval.

Declarations

Ethics approval and consent to participate

The study protocol was approved by the Institutional Review Board (IRB) of the University of Kufa (approval number: IRB-2024-001. The study was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants before their inclusion in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.