Abstract This study aimed to evaluate the expression level of miRNA-155 and its association with chemokines CCL2 and CXCL8 in patients with localized and generalized gingivitis compared with healthy controls. A case–control study was conducted involving 90 participants divided equally into three groups (n = 30 each): healthy controls, localized gingivitis, and generalized gingivitis. GCF samples were collected using sterile paper strips. Relative expression of miRNA-155 was quantified using quantitative real-time PCR (qRT-PCR) via the 2^{- ΔΔCt} method. Chemokine concentrations of CCL2 and CXCL8 were assessed by ELISA. The expression of miRNA-155 was significantly lower in both the localized and generalized gingivitis groups compared with the healthy control group (P <0.05). On the other hand, the GCF level of CXCL8 increased significantly with severity of the disease and showing the highest value in the generalized gingivitis group (544.34 ± 199.24 pg/mL) compared with control group (311.90 ± 144.02 pg/mL; P = 0.0001). In contrast, there was non significant difference in GCF CCL2 levels between the study groups (P = 0.503). Even though CCL2 did not change between the groups, it showed a very strong positive correlation with CXCL8 in both localized gingivitis (r = 0.987, P = 0.0001) and generalized gingivitis (r = 0.992, P = 0.0001). Gingivitis is characterized by a significant suppression of miRNA-155 alongside a coordinated, synergistic chemokine network driven by CCL2 and CXCL8. This distinct molecular profile suggests an early epigenetic regulatory feedback mechanism attempting to control runaway inflammatory signaling while maintaining necessary innate immune cell recruitment within early inflamed gingival tissues.

Keywords: miRNA-155, Gingivitis, Chemokines, CCL2, CXCL8, Gingival crevicular fluid, Inflammation, qRT-PCR

Citation:  Abed, F.B., Talib, E.Q., and Mohammed, D.A. 2026. Molecular interplay between miRNA-155 and chemokines CCL2/CXCL8 in gingival crevicular fluid (GCF) in gingivitis. Natural and Life Sciences Communications. 25(4): e2026099.

Graphical Abstract:

INTRODUCTION

Periodontal disease develops as a result of the host immune and inflammatory response to bacterial infection around the teeth. If not treated, the disease can progress from mild gingival inflammation to destruction of the supporting periodontal tissues. Host protection against periodontal infections is mediated by both the innate and adaptive immune systems (Mohammed and Talib, 2026). In the early response of innate immunity oral epithelium combined with neutrophils and macrophages work against invading germs. Conversely, adaptive immunity is mostly B and T lymphocytes that identify distinct antigens and help destroy infected cells. These two immune responses cooperate to restrict bacterial infection and preserve the health of periodontal tissues (Luan et al., 2018).

Gingivitis is first stage of periodontal disease and is an inflammatory disorder of the gingival tissues around teeth that is reversible. It often arises as a reaction to the formation of dental biofilm and if left untreated, progresses to periodontitis (Ariyamuthu et al., 2013). The disease is characterized by gingival erythema and edema without loss of periodontal attachment. Since gingivitis is often painless and produces only mild clinical signs many people do not realize they have it (Trombelli et al., 2018; Geurs et al., 2023). In most cases, removing dental plaque is enough to reverse the inflammation. However, when plaque control is poor and inflammation persists, gingivitis may be become chronic and eventually progress to periodontitis in susceptible individuals. Evidence from long-term studies suggests that persistent gingival inflammation is associated with greater attachment loss emphasizing the importance of early plaque control (Knight et al., 2016; Geurs et al., 2023).

Pathogenic bacteria, especially Porphyromonas gingivalis, are the principal initiators of periodontal disease, although systemic diseases, environmental variables and genetic predisposition all contribute to its initiation and development. Bacterial components, notably lipopolysaccharide (LPS), activate toll-like receptors (TLRs) on epithelial cells, fibroblasts and immune cells. This activation leads to the host immune response and induces the secretion of pro-inflammatory cytokines such as tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6) (Calame, 2007; Ding et al., 2014; Prasad et al., 2016). These inflammatory mediators contribute to periodontal tissue destruction. Since the innate immune response has a key role in controlling inflammation, its activity must be tightly regulated by endogenous genes (Motedayyen et al., 2015).

During the last decade, microRNAs (miRNAs) have gained considerable attention because of their important role in regulating immune and inflammatory responses. These short non-coding RNAs are usually 19-24 nucleotides in length, and control gene expression at the post-transcriptional level by binding to the 3’-untranslated region (3’-UTR) of target messenger RNAs (mRNAs). This interaction prevents either the translation of the protein or the degradation of the target mRNA. miRNAs are not simple on/off switches but modulate protein expression and are involved in a broad spectrum of biological activities, including in the control of inflammation. They also regulate the synthesis of inflammatory mediators and have a role in the host immunological response to bacterial, viral, fungal and parasite infections (O’Connell et al., 2011; O’Neill et al., 2011; Diekwisch, 2016; Luan et al., 2017; Talib and Mohammed, 2026).

Alterations in miRNA expression have been associated with the initiation and development of periodontitis. MiRNAs are stable in a variety of bodily fluids such as blood, saliva, urine and gingival crevicular fluid (GCF) and hence have gained much attention as possible biomarkers for illness diagnosis and prognosis. Their excellent stability and non-invasive collection and detection by quantitative polymerase chain reaction (qPCR) make them interesting candidates for therapeutic applications (Luan et al., 2018; Micó-Martínez et al., 2021; Santonocito et al., 2021; Laberge et al., 2023). Among oral biofluids, gingival crevicular fluid (GCF) is particularly important because both its volume and composition change depending on the inflammatory status of periodontal tissues (Faulkner et al., 2022; Almiñana-Pastor et al., 2023).

Chemokines are tiny signaling proteins important in the regulation of immunological and inflammatory responses which guide the movement of leukocytes. They are categorized into four major groups based on the position of conserved cysteine residues near their N terminus, CC, CXC, CX3C and C. Humans contain around 50 chemokines and more than 20 chemokine receptors. Although many chemokines bind to more than one receptor, certain ligand-receptor pairings are very selective, e.g., “CX3CL1/CX3CR1 and CXCL16/CXCR6”. Most chemokines are secreted as soluble proteins while “CX3CL1 and CXCL16” are originally produced as membrane-bound molecules and are shed only after metalloprotease breakdown (Allen et al., 2007; Zlotnik and Yoshie, 2012; Bachelerie et al., 2014).

Chemokines can form homo- or heterodimers and also bind to glycosaminoglycans (GAGs), which helps create chemokine gradients and supports leukocyte recruitment to inflamed tissues (Allen et al., 2007). Functionally, they are classified into homeostatic chemokines, which maintain normal immune surveillance, and inflammatory chemokines, which are produced during infection or tissue injury to attract immune cells (Moser and Willimann, 2004). Their expression is regulated by transcription factors such as NF-κB and Krüppel-like factors (Hartmann et al., 2015). Chemokine receptors are differently expressed across leukocyte populations and are tightly controlled during inflammatory responses (Bachelerie et al., 2014).

Chemokines bind to G protein-coupled receptors to activate intracellular signaling pathways such as NF-κB and mitogen-activated protein kinase (MAPK) that initiate leukocyte adhesion, migration, and activation at sites of inflammation (Hartmann et al., 2015; Vollmer et al., 2022).

This study aimed to evaluate the expression level of miRNA-155 and its association with chemokines CCL2 and CXCL8 in patients with localized and generalized gingivitis compared with healthy controls.

MATERIALS AND METHODS

Study design and population

This case–control study was carried out between October 2024 and April 2025 at the College of Dentistry, Teaching Hospital, Al-Iraqia University. A total of 90 subject were enrolled, recruited, and examined during a single clinical visit in the College of Dentistry/Teaching Hospital/Al-Iraqia University and divided equally into three groups (n = 30 each):

• Healthy control group (n = 30): Individuals with clinically healthy gingiva, no bleeding on probing (BOP), and low plaque scores.
• Localized gingival inflammation group (n = 30):  Patients exhibiting bleeding on probing at limited sites with mild clinical signs of gingival inflammation.
• Generalized gingival inflammation group (n = 30):  Patients presenting with generalized bleeding on probing, gingival erythema, and clinically diagnosed plaque-induced gingivitis.

Ethical approval

This study was conducted in accordance with the ethical standards of the institutional research committee of Department of Clinical Sciences /College of Dentistry/Al-Iraqia University and with the principles of the Declaration of Helsinki (Projact No. HER-AIUCD/309, September, 2024).

Sample size calculation

Sample size was estimated using G*Power 3.1.9.7 (Franz Faul, Universität Kiel, Germany). With a power of 97%, two-sided alpha of 0.05, and an effect size of 0.80 for three groups, the estimated sample size was 82. An additional 10% was added to allow for possible errors or missing samples, making the final sample size 90 participants.

Inclusion criteria

• Participants were between 18-60 years of age.
• They had at least 20 natural functional teeth.
• Only individuals in good general health, with no history of chronic systemic diseases were included.

Exclusion criteria

• Receipt of professional periodontal therapy within the past 3 months. 
• Use of antibiotics, anti-inflammatory medications, or immunosuppressive drugs within the past 3 months. 
• Current smokers or individuals with a history of tobacco use. Pregnant or lactating women. 
• Systemic diseases such as autoimmune disease, immune patterns or inflammatory cascades, such as diabetes and lupus. 

Clinical examination

All clinical examinations were performed by a single calibrated examiner. The following periodontal parameters were recorded:

• Bleeding on Probing (BOP), recorded at six sites per tooth and expressed as a percentage
• Gingival condition assessment to confirm the absence of periodontitis

• Subjects were categorized into study groups based on predefined clinical criteria.

Gingival crevicular fluid (GCF) collection

GCF samples were collected using sterile absorbent paper strips. Selected locations were separated using cotton rollers and carefully air dried before sample collection to prevent saliva contamination. Paper strips were cautiously introduced into the gingival sulcus until minor resistance was felt and placed in the sulcus for 30 seconds. Strips with apparent blood contamination were also eliminated. The strips were collected and immediately put into RNase free Eppendorf tubes. Samples for miRNA analysis were put into tubes with lysis buffer and for ELISA samples were transferred into sterile tubes without lysis buffer. All samples were kept at −80°C until analysis (Mohammed and Talib, 2026).

Enzyme-linked immunosorbent assay (ELISA)

The levels of the biomarkers in the collected samples were quantified using commercially available ELISA kits according to the manufacturers' protocols.

CCL2 and CXCL8

The concentrations of CCL2 pg/mL (Cat: ELK5252/ ELK Biotechnology/USA) and CXCL8 pg/mL (Cat: ELK1159/ ELK Biotechnology/USA) in the GCF samples were determined using specific, commercially available ELISA kits.

RNA extraction and cDNA synthesis

Total RNA, including small non-coding RNA fractions, was extracted from the GCF-containing paper strips using the miRNeasy Micro Kit (Catalog No. 217084; Qiagen, Germany) according to the manufacturer’s instructions. The concentration and purity of the isolated RNA were then measured spectrophotometrically. After that, complementary DNA (cDNA) was synthesized using a miRNA-specific reverse transcription kit (TaqMan MicroRNA Reverse Transcription Kit; Catalog No. 10146854). The reaction mixture was incubated under the following thermal conditions 16°C for 30 min, 42°C for 30 min, and 85°C for 5 min to ensure specific synthesis of target miRNA fragments.

Quantitative real-time PCR (qRT-PCR)

The amplification and quantification of miRNA-155 were carried out on a real-time PCR platform using specific primer sets, with miRNA-16 serving as the endogenous internal reference gene for normalization. The primer configurations utilized in this study were as follows in Table 1.

Table 1. Primer detail.

RNA Extraction and miRNA-155 quantification

Total RNA, including small RNAs, was extracted from GCF samples using a commercial miRNA extraction kit according to the manufacturer’s instructions. Reverse transcription was performed using a miRNA-specific reverse transcription kit.

Quantitative real-time PCR (qRT-PCR) was used to measure miRNA-155 expression, with miRNA-16 as the internal control gene. All reactions were run in duplicate. Ct values were recorded and analyzed using the comparative Ct (ΔΔCt) method.

miRNA expression analysis

Relative miRNA-155 expression levels were calculated using the 2^⁻ΔΔCt method:

• ΔCt = Ct(miRNA-155) − Ct(miRNA-16)
• ΔΔCt = ΔCt (patient group) − ΔCt (control group)

The healthy control group was used as the calibrator and assigned a fold expression value of 1.0. Fold values <1 was considered downregulated, while values >1 were considered upregulated.

Statistical analysis

Statistical analysis was performed using SPSS software. Data distribution was assessed using the Shapiro–Wilk test. Continuous variables were expressed as mean ± standard deviation (SD). Group comparisons were conducted using one-way ANOVA, followed by post-hoc tests where appropriate. Correlations between inflammatory markers were analyzed using Pearson’s correlation coefficient. A P-value < 0.05 was considered statistically significant.

RESULTS

Distribution of sex show in Table 2, and revealed a statistically non-significant different between healthy control, localized gingival inflammation, and generalized gingival inflammation groups (P = 0.248).

Table 2. Distribution of sex among study groups.

The mean age between three study groups shown in Table 3 and the result observed non-significant difference between groups (P = 0.254).

But, BOP% showed a statistically significant difference between three groups (P = 0.0001). The highest mean BOP% was observed in the localized gingival inflammation group, followed by the generalized gingival inflammation group, while the lowest mean BOP% was recorded in the healthy control group.

Table 3. Descriptive statistics of age and bleeding on probing (BOP%) among study groups.

Table 4 illustrated the mean level of CCL2 between groups with statistical a non-significant different (P = 0.503), with comparable values observed across healthy and gingivitis groups.

While, CXCL8 levels show a significantly between the groups (P = 0.0001). The highest mean CXCL8 concentration was detected in the generalized gingival inflammation group, followed by the localized gingival inflammation group, while the low level was observed in the healthy control group.

Table 4. Descriptive statistics of GCF CCL2 and CXCL8 levels among study groups.

The comparisons of CCL2 between groups revealed that non- significant differences (P > 0.05). While the comparisons of CXCL8 level between healthy control vs. generalized gingival inflammation and localized vs. generalized gingival inflammation show a statistically significant, but comparisons between healthy control and localized gingival inflammation was not significant (P > 005). As demonstrated in Table 5.

Table 5. Pairwise comparisons of CCL2 and CXCL8 levels between study groups.

A significant positive correlation was shown between CCL2 and CXCL8 levels in both the localized gingival inflammation group and generalized gingival inflammation group (P < 0.05). As illustrated in Table 6.

Table 6. Correlation between CCL2 pg/mL and CXCL8 pg/mL levels in gingival inflammation groups.

Note: **Correlation is significant at the 0.01 level (2-tailed).

Table 7 presents the relative fold expression levels of miRNA-155 in patients with localized and generalized gingival inflammation compared with the healthy control group, calculated using the 2^⁻ΔΔCt method, with miRNA-16 used as the endogenous reference gene.

The results showed that miRNA-155 expression was downregulated in both gingival inflammation groups compared with the control group. In the localized gingival inflammation group, the Ct value of miRNA-155 was lower than that of the control group, which led to a clear change in the ΔCt value. The ΔΔCt analysis showed a very low relative expression (2^⁻ΔΔCt < 1), indicating marked downregulation of miRNA-155 in this group.

A similar pattern was observed in the generalized gingival inflammation group, where miRNA-155 expression was also reduced compared with controls. The 2^⁻ΔΔCt values were again very low, confirming consistent downregulation of miRNA-155 in generalized inflammation. The magnitude of reduction was comparable between localized and generalized forms, suggesting that gingival inflammation is associated with suppressed miRNA-155 expression regardless of disease extent.

Table 7. Comparison between patients and control groups regarding miRNA155 fold expression levels.

DISCUSSION

The study demonstrated balanced demographics across groups with no significant differences in age or sex distribution, no significant differences were observed in age (P = 0.254) or sex distribution (P = 0.248) between healthy controls, localized gingival inflammation, and generalized gingival inflammation groups. This balance minimizes confounding factors in biomarker assessments, as age and sex often influence inflammatory responses in periodontal tissues (Eke et al., 2018). Similar study by Gündogar et al. (2021) who found matching appears in most GCF chemokine studies to ensure comparability (Gündogar et al., 2021).

Bleeding on probing (BOP) in the present study was significant higher in both the localized and generalized gingival inflammation groups compared with control group. This may reflects plaque-induced neutrophil infiltration and increased vascular permeability. Bacterial lipopolysaccharides (LPS) can activate gingival epithelial cells through TLR4, leading to the release of CXCL8 and further recruitment of polymorphonuclear neutrophils (PMNs), which in turn amplifies BOP as an early marker of gingival inflammation. This finding is consistent with Tariq et al. (2022), who suggested that the higher localized BOP may be related to a more acute focal inflammatory response, while generalized inflammation may reflect a more adapted chronic state; similar patterns have also been observed in early periodontitis (Tariq et al., 2022).

Bleeding on probing (BOP) was significantly elevated in the localized (24.07 ± 6.09%) and generalized (19.37 ± 6.25%) groups compared with the control group (8.04 ± 6.03%; P = 0.0001), with localized peaking higher. This may be arises from plaque biofilm LPS triggering TLR4 on gingival epithelial cells, boosting vascular permeability and neutrophil diapedesis via early chemokine gradients. This result is consistent with Tariq et al. (2022), who linked higher BOP to focal neutrophil influx in early gingivitis. Similarly, Sreenivasan and Prasad, (2022) reported BOP as a reversible marker of plaque-induced inflammation. No major disagreement was observed across studies, although some reports have shown steeper increases in more aggressive cases of gingival inflammation (Sreenivasan and Prasad, 2022).

Regarding CCL2 level in this study, was show remained comparable between groups (healthy: 269.34 ± 86.28 mg/ml; localized: 236.83 ± 111.35 mg/ml; generalized: 256.24 ± 122.17 mg/ml; P = 0.503), non-significantly. In mild gingivitis, the production of CCL2 (MCP-1) by fibroblasts and endothelium levels off because of feedback from CCR2 This aligns with Alarcón-Sánchez et al. (2025), who reported that the stable level of MCP-1 GCF in plaque-induced gingivitis; similarly Pradeep et al. (2009) who confirm that in early-stage gingivitis no increased until attachment loss. In contrast, Kurtiş et al. (2005) who found that MCP-1 levels in GCF are significantly higher in periodontitis compared with healthy controls, suggesting the association between chemokine dysregulation and disease severity.

CXCL8 level in the present study showed significant elevation overall (P = 0.0001; healthy: 311.90 ± 144.02 ng/dl; localized: 368.79 ± 168.74 ng/dl; generalized: 544.34 ± 199.24 ng/dl), with healthy vs. generalized (P = 0.0001) and localized vs. generalized (P = 0.0001) significant, while healthy vs. localized was non significant. Actually, Bacterial LPS induces CXCL8 from keratinocytes/fibroblasts via TLR4/NF-κB, forming haptotactic gradients on GAGs to chemoattract neutrophils, explaining the dose-response with inflammation extent (Uckun et al., 2006). This agrees with Lagdive et al. (2013) who correlated GCF IL-8 increased to BOP in gingivitis (r >0.4).

Concerning the correlation result, a strong positive correlations linked CCL2 and CXCL8 in localized and generalized groups in this study.

The bacterial biofilms induce the NF-κB signaling pathway and promote the coordinated expression of inflammatory chemokines. CXCL8 is involved in the recruitment of neutrophils and CCL2 in the migration of monocytes therefore contributing to maintenance of the inflammatory response without irreparable tissue damage in the reversible stage of gingival inflammation. These results in agrement with result of Ramadan (2020) and Alarcón-Sánchez et al. (2024), who show that the coordinated action of chemokines is critical in the regulation of the innate immune response in periodontal disease.

This finding discovered that miR-155 was significantly downregulated in localized and generalized gingivitis groups compared with the control group. The reduction could serve as a regulatory mechanism to manage inflammation during the first phases of gingivitis. Inhibition of miR-155 perhaps by PU.1. Thus, interventions targeting 1-related transcriptional control or lncRNA sponging might dampen NF-κB and JAK/STAT signaling and promote inflammation resolution even in the presence of active chemokines. The downregulation of miR-155 expression may help to maintain the immune homeostasis as SHIP1 and SOCS1 are the targets of miR-155. Our results accord with those of O’Connell et al. (2010) who identified miR-155 control as a crucial role in the modulation of immune responses; similarly, gingival miR reviews note downregulation in mild cases (Baru et al., 2025). However, chronic periodontitis disagrees, with upregulation (up to 64-fold) from persistent LPS (Motedayyen et al., 2015; Baru et al., 2025).

Actually, in the healthy periodontium, baseline levels of epigenetic microprocessors maintain structural homeostasis. However, the accumulation of pathogenic dental biofilm leads to high concentrations of lipopolysaccharides (LPS) and other pathogen-associated molecular patterns (PAMPs) in the gingival sulcus. These microbial components actively ligate TLR4 expressed on resident gingival keratinocytes, fibroblasts, and sentinel macrophages.

Historically, miRNA-155 has been recognized as an inducible inflammatory miRNA; however, the findings in current study demonstrate a profound and uniform downregulation of miRNA-155 in both localized and generalized gingivitis. This dramatic suppression suggests a highly coordinated, early-stage negative feedback loop or the activation of upstream long non-coding RNA (lncRNA) "sponges" or transcriptional repressors “such as PU.1 or alternative anti-inflammatory cascades” specifically triggered during early, non-destructive tissue responses. Mechanistically, miRNA-155 directly targets and post-transcriptionally represses critical negative regulators of innate immunity, most notably SHIP1 (Src homology 2-containing inositol 5-phosphatase 1) and SOCS1 (Suppressor of Cytokine Signaling 1) (O’Connell et al., 2010).

However, under the conditions observed in this research, the severe downregulation of miRNA-155 effectively relieves the post-transcriptional inhibition on downstream inflammatory cascades. When miRNA-155 levels drop precipitously, the suppression of the MyD88-dependent TLR4 pathway is altered, facilitating unchecked phosphorylation and nuclear translocation of the NF-κB p65 subunit. Once active in the nucleus, NF-κB binds directly to the promoter regions of early response inflammatory genes, inducing a powerful, synergistic transcription of CCL2 (Monocyte Chemoattractant Protein-1) and CXCL8 (Interleukin-8) (O’Neill et al., 2011).

This molecular dependency may beautifully explain the exceptionally high positive correlation values (r = 0.987 and r = 0.992) observed between CCL2 and CXCL8 in our clinical samples. Rather than acting in isolation, these two chemokines function as a highly synchronized tandem network. CXCL8 is rapidly secreted to establish a haptotactic gradient bound to local glycosaminoglycans (GAGs), acting as the primary homing signal to initiate vascular permeability and direct the rapid transendothelial diapedesis of polymorphonuclear neutrophils (PMNs) to combat the initial biofilm invasion. Simultaneously, co-expressed CCL2 acts progressively to recruit circulating CCR2⁺ monocytes and macrophages. This division of labor allows the host to maximize defense cell infiltration without immediately triggering the catastrophic Matrix Metalloproteinase (MMP) tissue destruction typically seen in periodontitis, which matches our clinical classification of attachment-conserved gingivitis. Thus, the suppression of miRNA-155 serves as a master molecular switch that permits necessary, protective chemokine-mediated immune cell infiltration while attempting to preserve local tissue integrity (Proudfoot et al., 2003).

LIMITATIONS OF THE STUDY

First, because of the case–control design, the expression levels of the studied biomarkers were measured at only one point in time, making it difficult to determine causal relationships or evaluate changes during the progression of periodontal disease.

Second, although the sample size (n = 90) was sufficient based on the statistical power analysis, studies with a larger number of participants and a longitudinal design would help to confirm these findings in different populations.

Third, despite applying strict inclusion and exclusion criteria, some factors such as differences in daily plaque accumulation, dietary habits, oral hygiene practices, and individual anatomical variations could not be completely controlled.

Finally, this study focused on the association between miRNA-155 and the measured chemokines. Further functional studies, including cell culture and gene-silencing experiments, are needed to clarify the molecular mechanisms underlying the reduced expression of miR-155 and to identify its downstream target genes.

CONCLUSION

The present study showed that gingivitis is characterized by significant downregulation of miR-155 together with a strong positive correlation between the chemokines CCL2 and CXCL8. These findings indicate that chemokine-mediated inflammatory responses remain active during the early stage of gingival inflammation, whereas the reduced expression of miR-155 may represent a regulatory mechanism that helps control excessive immune activation. A better understanding of the relationship between miR-155 and inflammatory chemokines may improve our knowledge of the molecular events involved in periodontal inflammation and could contribute to the identification of novel biomarkers for the early detection and monitoring of periodontal disease.

ACKNOWLEDGEMENTS

The authors gratefully acknowledge the Higher Institute of Forensic Sciences, Al-Nahrain University, Jadriya, Baghdad, Iraq, for providing instrumental support. Special thanks are also extended to the Al-Iraqia University/College of Dental and Teaching Hospital for their valuable facilities and assistance in conducting the activity studies, as well as to all patients in this study.

AUTHOR CONTRIBUTIONS

Farah Badri Abed: Conceptualization (Lead), Data Curation (Lead), Software (Lead), Validation (Lead), Writing – Original Draft (Lead); Ehab Qasim Talib: Data Curation (Equal), Formal Analysis (Equal), Validation (Equal), Visualization (Equal), Writing – Review & Editing (Equal); Dunya Abdullah Mohammed: Data Curation (Equal), Formal Analysis (Equal), Software (Equal), Supervision (Equal), Validation (Equal), Visualization (Equal), Writing – Review & Editing (Equal).

CONFLICT OF INTEREST

The authors declare that they have no conflicts of interest.

REFERENCES

Alarcón-Sánchez, M.A., Guerrero-Velázquez, C., Becerra-Ruiz, J.S., Rodríguez-Montaño, R., Avetisyan, A., and Heboyan, A. 2024. IL-23/IL-17 axis levels in gingival crevicular fluid of subjects with periodontal disease: A systematic review. BMC Oral Health. 24(1): 302. https://doi.org/10.1186/s12903-024-04077-0

Alarcón-Sánchez, M.A., Rodríguez-Montaño, R., Lomelí-Martínez, S.M., and Heboyan, A. 2025. Relationship between MCP-1 levels in GCF and periodontitis: A systematic review with meta-analysis and analysis of molecular interactions. Journal of Cellular and Molecular Medicine. 29(9): e70545. https://doi.org/10.1111/jcmm.70545

Allen, S.J., Crown, S.E., and Handel, T.M. 2007. Chemokine: Receptor structure, interactions, and antagonism. Annual Review of Immunology. 25: 787-820. https://doi.org/10.1146/annurev.immunol.24.021605.090529

Almiñana-Pastor, P.J., Alpiste-Illueca, F.M., Micó-Martinez, P., García-Giménez, J.L., García-López, E., and López-Roldán, A. 2023. MicroRNAs in gingival crevicular fluid: An observational case-control study of differential expression in periodontitis. Non-Coding RNA. 9(6): 73. https://doi.org/10.3390/ncrna9060073

Ariyamuthu, V.K., Nolph, K.D., and Ringdahl, B.E. 2013. Periodontal disease in chronic kidney disease and end-stage renal disease patients: A review. Cardiorenal Medicine. 3(1): 71-78. https://doi.org/10.1159/000350046

Bachelerie, F., Ben-Baruch, A., Burkhardt, A.M., Combadiere, C., Farber, J.M., Graham, G.J., Horuk, R., Sparre-Ulrich, A.H., Locati, M., Luster, A.D., et al. 2014. International Union of Basic and Clinical Pharmacology. LXXXIX. Update on the extended family of chemokine receptors and introducing a new nomenclature for atypical chemokine receptors. Pharmacological Reviews. 66(1): 1-79. https://doi.org/10.1124/pr.113.007724

Baru, O., Pop, L., Raduly, L., Bica, C., Mehterov, N., Pirlog, R., Buduru, S., Braicu, C., Berindan-Neagoe, I., and Badea, M. 2025. The evaluation of a 5-miRNA panel in patients with periodontitis disease. JDR Clinical and Translational Research. 10(1): 34-43. https://doi.org/10.1177/23800844241252395

Calame, K. 2007. MicroRNA-155 function in B cells. Immunity. 27(6): 825-827. https://doi.org/10.1016/j.immuni.2007.11.010

Diekwisch, T.G.H. 2016. Novel approaches toward managing the micromanagers: 'Non-toxic' but effective. Gene Therapy. 23(10): 697-698. https://doi.org/10.1038/gt.2016.49

Ding, C., Ji, X., Chen, X., Xu, Y., and Zhong, L. 2014. TNF-α gene promoter polymorphisms contribute to periodontitis susceptibility: Evidence from 46 studies. Journal of Clinical Periodontology. 41(8): 748-759. https://doi.org/10.1111/jcpe.12279

Eke, P.I., Thornton-Evans, G.O., Wei, L., Borgnakke, W.S., Dye, B.A., and Genco, R.J. 2018. Periodontitis in US adults: National health and nutrition examination survey 2009-2014. Journal of the American Dental Association (1939). 149(7): 576-588.e6. https://doi.org/10.1016/j.adaj.2018.04.023

Faulkner, E., Mensah, A., Rodgers, A.M., McMullan, L.R., and Courtenay, A.J. 2022. The role of epigenetic and biological biomarkers in the diagnosis of periodontal disease: A systematic review approach. Diagnostics. 12(4): 919. https://doi.org/10.3390/diagnostics12040919

Geurs, N.C., Jeffcoat, M.K., Tanna, N., Geisinger, M.L., Parry, S., Biggio, J.R., Doyle, M.J., Grender, J.M., Gerlach, R.W., and Reddy, M.S. 2023. A randomized controlled clinical trial of prenatal oral hygiene education in pregnancy-associated gingivitis. Journal of Midwifery & Women's Health. 68(4): 507-516. https://doi.org/10.1111/jmwh.13486

Gündogar, H., Üstün, K., Ziya Şenyurt, S., Çetin Özdemir, E., Sezer, U., and Erciyas, K. 2021. Gingival crevicular fluid levels of cytokine, chemokine, and growth factors in patients with periodontitis or gingivitis and periodontally healthy subjects: A cross-sectional multiplex study. Central European Journal of Immunology. 46(4): 474-480. https://doi.org/10.5114/ceji.2021.110289

Hartmann, P., Schober, A., and Weber, C. 2015. Chemokines and microRNAs in atherosclerosis. Cellular and Molecular Life Sciences. 72(17): 3253-3266. https://doi.org/10.1007/s00018-015-1925-z

Knight, E.T., Liu, J., Seymour, G.J., Faggion, C.M., and Cullinan, M.P. 2016. Risk factors that may modify the innate and adaptive immune responses in periodontal diseases. Periodontology 2000. 71(1): 22-51. https://doi.org/10.1111/prd.12110

Kurtiş, B., Tüter, G., Serdar, M., Akdemir, P., Uygur, C., Firatli, E., and Bal, B. 2005. Gingival crevicular fluid levels of monocyte chemoattractant protein-1 and tumor necrosis factor-alpha in patients with chronic and aggressive periodontitis. Journal of Periodontology. 76(11): 1849-1855. https://doi.org/10.1902/jop.2005.76.11.1849

Laberge, S., Akoum, D., Wlodarczyk, P., Massé, J.D., Fournier, D., and Semlali, A. 2023. The potential role of epigenetic modifications on different facets in the periodontal pathogenesis. Genes. 14(6): 1202. https://doi.org/10.3390/genes14061202

Lagdive, S., Marawar, P., Byakod, G., and Lagdive, S. 2013. Evaluation and comparison of interleukin-8 (IL-8) level in gingival crevicular fluid in health and severity of periodontal disease: A clinico-biochemical study. Indian Journal of Dental Research. 24(2): 188-192. https://doi.org/10.4103/0970-9290.116675

Luan, X., Zhou, X., Naqvi, A., Francis, M., Foyle, D., Nares, S., and Diekwisch, T.G.H. 2018. MicroRNAs and immunity in periodontal health and disease. International Journal of Oral Science. 10(3): 24. https://doi.org/10.1038/s41368-018-0025-y

Luan, X., Zhou, X., Trombetta-eSilva, J., Francis, M., Gaharwar, A.K., Atsawasuwan, P., and Diekwisch, T.G.H. 2017. MicroRNAs and periodontal homeostasis. Journal of Dental Research. 96(5): 491-500. https://doi.org/10.1177/0022034516685711

Micó-Martínez, P., Almiñana-Pastor, P.J., Alpiste-Illueca, F., and López-Roldán, A. 2021. MicroRNAs and periodontal disease: A qualitative systematic review of human studies. Journal of Periodontal & Implant Science. 51(6): 386-397. https://doi.org/10.5051/jpis.2007540377

Mohammed, H.A. and Talib, E.Q.T. 2026. Assessment of serum CRP and gingival crevicular fluid OPG and neutrophil elastase as biomarkers for periodontal disease in type 2 diabetes mellitus. Natural and Life Sciences Communications. 25(3): e2026066. https://doi.org/10.12982/NLSC.2026.066

Moser, B. and Willimann, K. 2004. Chemokines: Role in inflammation and immune surveillance. Annals of the Rheumatic Diseases. 63 (Suppl 2): ii84–ii89. https://doi.org/10.1136/ard.2004.028316

Motedayyen, H., Ghotloo, S., Saffari, M., Sattari, M., and Amid, R. 2015. Evaluation of microRNA-146a and its targets in gingival tissues of patients with chronic periodontitis. Journal of Periodontology. 86(12): 1380-1385. https://doi.org/10.1902/jop.2015.150319

O'Connell, R.M., Kahn, D., Gibson, W.S.J., Round, J.L., Scholz, R.L., Chaudhuri, A.A., Kahn, M.E., Rao, D.S., and Baltimore, D. 2010. MicroRNA-155 promotes autoimmune inflammation by enhancing inflammatory T-cell development. Immunity. 33(4): 607-619. https://doi.org/10.1016/j.immuni.2010.09.009

O'Connell, R.M., Zhao, J.L., and Rao, D.S. 2011. MicroRNA function in myeloid biology. Blood. 118(11): 2960-2969. https://doi.org/10.1182/blood-2011-03-291971

O'Neill, L.A., Sheedy, F.J., and McCoy, C.E. 2011. MicroRNAs: The fine-tuners of Toll-like receptor signalling. Nature Reviews Immunology. 11(3): 163-175. https://doi.org/10.1038/nri2957

Pradeep, A.R., Daisy, H., and Hadge, P. 2009. Gingival crevicular fluid levels of monocyte chemoattractant protein-1 in periodontal health and disease. Archives of Oral Biology. 54(5): 503-509. https://doi.org/10.1016/j.archoralbio.2009.02.007

Prasad, S., Tyagi, A.K., and Aggarwal, B.B. 2016. Detection of inflammatory biomarkers in saliva and urine: Potential in diagnosis, prevention, and treatment for chronic diseases. Experimental Biology and Medicine. 241(8): 783-799. https://doi.org/10.1177/1535370216638770

Proudfoot, A.E.I., Handel, T.M., Johnson, Z., Lau, E.K., LiWang, P., Clark-Lewis, I., Borlat, F., Wells, T.N.C., and Kosco-Vilbois, M.H. 2003. Glycosaminoglycan binding and oligomerization are essential for the in vivo activity of certain chemokines. Proceedings of the National Academy of Sciences. 100(4): 1885-1890. https://doi.org/10.1073/pnas.0334864100

Ramadan, D.E., Hariyani, N., Indrawati, R., Ridwan, R.D., and Diyatri, I. 2020. Cytokines and chemokines in periodontitis. European Journal of Dentistry. 14(3): 483-495. https://doi.org/10.1055/s-0040-1712718

Santonocito, S., Polizzi, A., Palazzo, G., and Isola, G. 2021. The emerging role of microRNA in periodontitis: Pathophysiology, clinical potential and future molecular perspectives. International Journal of Molecular Sciences. 22(11): 5456. https://doi.org/10.3390/ijms22115456

Sreenivasan, P.K. and Prasad, K.V.V.K. 2022. Increase in the level of oral neutrophils with gingival inflammation – a population survey. The Saudi Dental Journal. 34(8): 795-801. https://doi.org/10.1016/j.sdentj.2022.11.004

Talib, E. and Mohammed, A. 2026. Interactions between T-cells and B-cells in the microbiological and histopathological mechanisms of peri-implantitis development. Microbes and Infectious Diseases. 7(1): 684-689. https://doi.org/10.21608/mid.2023.252495.1692

Tariq, M., Shahidan, W.N.S., and Awang, R.A. 2022. Interleukin-8 and interleukin-1α levels in the gingival crevicular fluid of periodontitis patients and their correlation with periodontal pocket depth and bleeding on probing. Khyber Medical University Journal. 14(2): 116-121. https://doi.org/10.35845/kmuj.2022.22432

Trombelli, L., Farina, R., Silva, C.O., and Tatakis, D.N. 2018. Plaque-induced gingivitis: Case definition and diagnostic considerations. Journal of Clinical Periodontology. 45(Suppl 20): S44-S67. https://doi.org/10.1111/jcpe.12939

Uckun, F.M., Morar, S., and Qazi, S. 2006. Vinorelbine-based salvage chemotherapy for therapy-refractory aggressive leukaemias. British Journal of Haematology. 135(4): 500-508. https://doi.org/10.1111/j.1365-2141.2006.06338.x

Vollmer, A., Vollmer, M., Lang, G., Straub, A., Shavlokhova, V., Kübler, A., Gubik, S., Brands, R., Hartmann, S., and Saravi, B. 2022. Associations between periodontitis and COPD: An artificial intelligence-based analysis of NHANES III. Journal of Clinical Medicine. 11(23): 7210. https://doi.org/10.3390/jcm11237210

Zlotnik, A. and Yoshie, O. 2012. The chemokine superfamily revisited. Immunity. 36(5): 705-716. https://doi.org/10.1016/j.immuni.2012.05.008        

OPEN access freely available online

Natural and Life Sciences Communications

Chiang Mai University, Thailand. https://cmuj.cmu.ac.th