Update on the Role of Cytokines as Oral Biomarkers in the Diagnosis of Periodontitis

Blanco-Pintos, Triana; Regueira-Iglesias, Alba; Balsa-Castro, Carlos; Tomás, Inmaculada

doi:10.1007/978-3-030-96881-6_15

Cited by 12 publications

(8 citation statements)

References 84 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These are well known pro-inflammatory cytokines and their association with periodontal inflammation is not surprising. In fact, numerous studies investigating the levels of these cytokines in association with periodontal disease found positive results [ 33 ] although there are also contradictory reports [ 34 ]. The reasons for discordant results could be multiple including the nature of the population, the measures of periodontal disease, the methodology assessing the cytokines, the nature of the saliva (whole, stimulated vs. unstimulated).…”

Section: Discussionmentioning

confidence: 99%

Periodontal Inflamed Surface Area (PISA) associates with composites of salivary cytokines

et al. 2023

View full text Add to dashboard Cite

Background Periodontal disease (PerioD) is a chronic, complex inflammatory condition resulting from the interaction between subgingival dysbiotic bacteria and the host immune response leading to local inflammation. Since periodontal inflammation is characterized by multiple cytokines effects we investigated whether Periodontal Inflamed Surface Area (PISA), a continuous measure of clinical periodontal inflammation is a predictor of composite indexes of salivary cytokines. Methods and findings In a cross-sectional study of 67 healthy, well-educated individuals, we evaluated PISA and several cytokines expressed in whole stimulated saliva. Two salivary cytokine indexes were constructed using weighted and unweighted approaches based on a Principal Component Analysis [named Cytokine Component Index (CCI)] or averaging the (standardized) level of all cytokines [named Composite Inflammatory Index (CII)]. In regression analysis we found that PISA scores were significantly associated with both salivary cytokine constructs, (CCI: part R = 0.51, p<0.001; CII: part R = 0.40, p = 0.001) independent of age, gender and BMI showing that single scores summarizing salivary cytokines correlated with severity of clinical periodontal inflammation. Conclusions Clinical periodontal inflammation may be reflected by a single score encompassing several salivary cytokines. These results are consistent with the complexity of interactions characterizing periodontal disease. In addition, Type I error is likely to be avoided.

show abstract

Section: Discussionmentioning

confidence: 99%

Periodontal Inflamed Surface Area (PISA) associates with composites of salivary cytokines

et al. 2023

View full text Add to dashboard Cite

show abstract

“…Our results show the most signi cant correlation between key genes and immune cells, especially dendritic cells and T cells, which play a synergistic role in the development of periodontitis [30,31]. Furthermore, multiple immune factors, including chemokines, immunosuppressors, immunostimulators, MHCs, and receptors, were closely correlated with the expression of those key genes [29,32,33]. These analyses suggested that key genes were tightly linked to the immune cell in ltration level and played essential roles in the immune microenvironment.…”

Section: Discussionmentioning

confidence: 56%

Identification of immune cells and key genes related to periodontitis

Sun,

Wang

2023

Preprint

View full text Add to dashboard Cite

Background The aim of this study was to identify the immune cellular and molecular mechanisms of periodontitis and the important role of key genes in the pathogenesis of periodontitis. Methods GSE16134, GSE10334, and GSE23586 were obtained from the Gene Expression Omnibus (GEO) database, and CIBERSORT was applied to examine the constitution of 22 kinds of immune cells in all samples. Weighted gene coexpression network analysis (WGCNA) was employed to identify candidate module genes associated with periodontitis. The least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM) algorithms were constructed to screen key genes. The key genes-related signaling pathways were explored through gene set variation analysis (GSVA). Moreover, the R package "RcisTarget" was adopted to predict transcription elements, and Cytoscape software was used to visualize the miRNA network. Constructing a nomogram model on the basis of the key genes expression level for the diagnosis of periodontitis. Results There were 427 periodontitis samples and 136 healthy samples. Periodontitis samples’ CD4 memory resting T cells were significantly higher, and WGCNA demonstrated that genes in the black module had the highest correlation with CD4 memory resting T cells. Seven genes, including AHNAK2, ALOX12B, CBR3, FAM57A, KLK8, KRT3, and TGM5, were associated with T cells in periodontitis. The identified key genes showed a strong correlation between immune cell infiltration levels and immune factors, primarily participating in multiple signaling pathways, including but not limited to the ESTROGEN RESPONSE EARLY, MYC TARGETS V2, G2M CHECKPOINT, and PI3K AKT MTOR signaling pathways. 73 miRNAs and 163 mRNA‒miRNA relationship pairs were identified, which were subsequently visualized. We constructed a nomogram model on the basis of the expression levels of the seven genes for diagnostic value, and the area under the AUC curve of the nomogram model was 0.937. Conclusions Periodontitis-related immune cells and key genes were identified, and the important role of key genes in the pathogenesis of periodontitis was explored through a series of bioinformatics analyses.

show abstract

“…Furthermore, these pro‐inflammatory cytokines with the anti‐inflammatory cytokine IL‐2 as a ratio showed excellent ability to detect periodontitis in non‐smokers and smokers, with smokers showing higher sensitivity (>95%) but lower specificity values (Arias‐Bujanda et al, 2018). Therefore, tobacco's immunosuppressive effect directly affects cytokines' ability to diagnose periodontitis (Blanco‐Pintos et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

Accuracy of periodontitis diagnosis obtained using multiple molecular biomarkers in oral fluids: A systematic review and meta‐analysis

Blanco‐Pintos,

Regueira‐Iglesias,

Seijo‐Porto

et al. 2023

J Clinic Periodontology

View full text Add to dashboard Cite

AimTo determine the accuracy of biomarker combinations in gingival crevicular fluid (GCF) and saliva through meta‐analysis to diagnose periodontitis in systemically healthy subjects.MethodsStudies on combining two or more biomarkers providing a binary classification table, sensitivity/specificity values or group sizes in subjects diagnosed with periodontitis were included. The search was performed in August 2022 through PUBMED, EMBASE, Cochrane, LILACS, SCOPUS and Web of Science. The methodological quality of the articles selected was evaluated using the QUADAS‐2 checklist. Hierarchical summary receiver operating characteristic modelling was employed to perform the meta‐analyses (CRD42020175021).ResultsTwenty‐one combinations in GCF and 47 in saliva were evaluated. Meta‐analyses were possible for six salivary combinations (median sensitivity/specificity values): IL‐6 with MMP‐8 (86.2%/80.5%); IL‐1β with IL‐6 (83.0%/83.7%); IL‐1β with MMP‐8 (82.7%/80.8%); MIP‐1α with MMP‐8 (71.0%/75.6%); IL‐1β, IL‐6 and MMP‐8 (81.8%/84.3%); and IL‐1β, IL‐6, MIP‐1α and MMP‐8 (76.6%/79.7%).ConclusionsTwo‐biomarker combinations in oral fluids show high diagnostic accuracy for periodontitis, which is not substantially improved by incorporating more biomarkers. In saliva, the dual combinations of IL‐1β, IL‐6 and MMP‐8 have an excellent ability to detect periodontitis and a good capacity to detect non‐periodontitis. Because of the limited number of biomarker combinations evaluated, further research is required to corroborate these observations.

show abstract

Update on the Role of Cytokines as Oral Biomarkers in the Diagnosis of Periodontitis

Cited by 12 publications

References 84 publications

Periodontal Inflamed Surface Area (PISA) associates with composites of salivary cytokines

Periodontal Inflamed Surface Area (PISA) associates with composites of salivary cytokines

Identification of immune cells and key genes related to periodontitis

Accuracy of periodontitis diagnosis obtained using multiple molecular biomarkers in oral fluids: A systematic review and meta‐analysis

Contact Info

Product

Resources

About