Quantitative gingival crevicular fluid proteome in type 2 diabetes mellitus and chronic periodontitis

S100A9 as a promising therapeutic target for diabetic foot ulcers

BACKGROUND

Diabetic foot is a complex condition with high incidence, recurrence, mortality, and disability rates. Current treatments for diabetic foot ulcers are often insufficient. This study was conducted to identify potential therapeutic targets for diabetic foot.

METHODS

Datasets related to diabetic foot and diabetic skin were retrieved from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using R software. Enrichment analysis was conducted to screen for critical gene functions and pathways. A protein interaction network was constructed to identify node genes corresponding to key proteins. The DEGs and node genes were overlapped to pinpoint target genes. Plasma and chronic ulcer samples from diabetic and non-diabetic individuals were collected. Western blotting, immunohistochemistry, and enzyme-linked immunosorbent assays were performed to verify the S100 calcium binding protein A9 (S100A9), inflammatory cytokine, and related pathway protein levels. Hematoxylin and eosin staining was used to measure epidermal layer thickness.

RESULTS

In total, 283 common DEGs and 42 node genes in diabetic foot ulcers were identified. Forty-three genes were differentially expressed in the skin of diabetic and non-diabetic individuals. The overlapping of the most significant DEGs and node genes led to the identification of S100A9 as a target gene. The S100A9 level was significantly higher in diabetic than in non-diabetic plasma (178.40 ± 44.65 ng/mL vs. 40.84 ± 18.86 ng/mL) and in chronic ulcers, and the wound healing time correlated positively with the plasma S100A9 level. The levels of inflammatory cytokines (tumor necrosis factor-α, interleukin [IL]-1, and IL-6) and related pathway proteins (phospho-extracellular signal regulated kinase [ERK], phospho-p38, phospho-p65, and p-protein kinase B [Akt]) were also elevated. The epidermal layer was notably thinner in chronic diabetic ulcers than in non-diabetic skin (24.17 ± 25.60 μm vs. 412.00 ± 181.60 μm).

CONCLUSIONS

S100A9 was significantly upregulated in diabetic foot and was associated with prolonged wound healing. S100A9 may impair diabetic wound healing by disrupting local inflammatory responses and skin re-epithelialization.

Salivary proteomic analysis in patients with type 2 diabetes mellitus and periodontitis

OBJECTIVE

This study aimed to compare the salivary protein profile in individuals with Type 2 Diabetes Mellitus (DM2) and periodontitis and their respective controls.

METHODS

Eighty participants were included in the study. The four groups were formed by individuals with DM2 and periodontitis (DM2 + P, n = 20), DM2 without periodontitis (DM2, n = 20), periodontitis without DM2 (P, n = 20) and individuals without periodontitis and without DM2 (H, n = 20). Periodontal clinical examinations were performed and unstimulated saliva was collected. Proteomic analysis was performed by shotgun mass spectrometry. The results were obtained by searching the Homo sapiens database of the UniProt catalog.

RESULTS

A total of 220 proteins were identified in saliva samples. In the comparison between DM2 + P and DM2 groups, 27 proteins were up-regulated [e.g. S100-A8 was 6 times up-regulated (humoral immune response pathway)]. The DM2 + P and P groups had 26 up-regulated proteins [e.g. Immunoglobulin lambda constant 7 more than 2 times up-regulated (complement activation pathway)]. The non-DM2 groups (P and H) presented 22 up-regulated proteins [e.g. Glyceraldehyde-3-phosphate dehydrogenase more than 2 times up-regulated (Peptidyl-cysteine S-nitrosylation pathway)]. The groups without periodontitis (DM2 and H) showed 23 were up-regulated proteins [e.g. Hemoglobin subunit alpha that was more than 10 times up-regulated (cellular oxidant detoxification pathway)].

CONCLUSION

The presence of DM2 and periodontitis significantly impacts the salivary proteome. Our proteomic analysis demonstrated that changes in the S100 family proteins (S100A8 and S100 A9) are highly related to the presence of DM2 and periodontitis.

CLINICAL RELEVANCE

Diabetes Mellitus (DM) and periodontitis are highly prevalent chronic diseases that present a wide variety of signs and symptoms. They present a bidirectional relationship, where patients with DM have a higher prevalence and severity of periodontitis, and patients with periodontitis have a higher prevalence of DM, worse glycemic control, and more diabetic complications. Diagnosing periodontitis requires specific clinical examinations, which require a highly trained operator. In this study, we used high throughput proteomics in order to evaluate non-invasive biomarkers for periodontitis in type 2 DM subjects. The results can contribute to earlier, more accurate, and less costly diagnosis of periodontitis in diabetic subjects, enabling better diabetes control.

Progression from healthy periodontium to gingivitis and periodontitis: Insights from bioinformatics-driven proteomics - A systematic review with meta-analysis

AIM

The current study aimed to: (1) systematically review the published literature regarding the proteomics analyses of saliva and gingival crevicular fluid (GCF) in healthy humans and gingivitis and/or periodontitis patients; and (2) to identify the differentially expressed proteins (DEPs) based on the systematic review, and comprehensively conduct meta-analyses and bioinformatics analyses.

METHODS

An online search of Web of Science, Scopus, and PubMed was performed without any restriction on the year and language of publication. After the identification of the DEPs reported by the included human primary studies, gene ontology (GO), the Kyoto encyclopedia of genes and genomes pathway (KEGG), protein-protein interaction (PPI), and meta-analyses were conducted. The risk of bias among the included studies was evaluated using the modified Newcastle-Ottawa quality assessment scale.

RESULTS

The review identified significant differences in protein expression between healthy individuals and those with gingivitis and periodontitis. In GCF, 247 proteins were upregulated and 128 downregulated in periodontal diseases. Saliva analysis revealed 79 upregulated and 70 downregulated proteins. There were distinct protein profiles between gingivitis and periodontitis, with 159 and 31 unique upregulated proteins in GCF, respectively. Meta-analyses confirmed significant upregulation of various proteins in periodontitis, including ALB and MMP9, while CSTB and GSTP1 were downregulated. AMY1A and SERPINA1 were upregulated in periodontitis saliva. HBD was upregulated in gingivitis GCF, while DEFA3 was downregulated. PPI analysis revealed complex networks of interactions among DEPs. GO and KEGG pathway analyses provided insights into biological processes and pathways associated with periodontal diseases.

CONCLUSION

The ongoing MS-based proteomics studies emphasize the need for a highly sensitive and specific diagnostic tool for periodontal diseases. Clinician acceptance of the eventual diagnostic method relies on its ability to provide superior or complementary information to current clinical assessment procedures. Future research should prioritize the multiplex measurement of multiple biomarkers simultaneously to enhance diagnostic accuracy and large study cohorts are necessary to ensure the validity and reliability of research findings.

Proteomic profile of human gingival crevicular fluid reveals specific biological and molecular processes during clinical progression of periodontitis

BACKGROUND AND OBJECTIVE

There is no clear understanding of molecular events occurring in the periodontal microenvironment during clinical disease progression. Our aim was to explore qualitative and quantitative differences in gingival crevicular fluid (GCF) protein profiles from patients diagnosed with periodontitis between non-progressive and progressive periodontal sites.

METHODS

Five systemically healthy patients diagnosed with periodontitis were monitored weekly in their progression of the disease and GCF samples from 10 candidate sites were obtained. Two groups of five sites, matched from an equal number of teeth, were selected from the five patients: Progression (PG) and Non-Progression (NP). Global protein identification was performed with high-throughput proteomic approaches and label-free analysis determined their relative abundances. Proteins were identified by Proteome Discoverer v2.4 and searched against human SwissProt protein databases. Enrichment bioinformatic analyses were performed in STRING-DB and ShinyGO environment.

RESULTS

1504 and 1500 proteins were identified in NP and PG respectively. Forty-eight proteins were exclusively identified in PG, while 52 were identified in NP. Moreover, 35 proteins were more abundant in PG and 29 proteins in NP (twofold change, p < .05). The NP group was mainly represented by proteins from "response to biotic stimuli and other organisms," "processes of cell death regulation," "peptidase regulation," "protein ubiquitination," and "ribosomal activity" GO categories. The most represented GO categories of the PG group were "assembly of multiprotein complexes," "catabolic processes," "lipid metabolism," and "binding to hemoglobin and haptoglobin."

CONCLUSIONS

There are quantitative and qualitative differences in the proteome of GCF from periodontal sites according to the status of clinical progression of periodontitis. Progressive periodontitis sites are characterized by a protein profile associated with catabolic processes, immune response, and response to cellular stress, while stable periodontitis sites show a protein profile mainly related to wound repair and healing processes, cell death regulation, and chaperone-mediated autophagy. Understanding the etiopathogenic role of these profiles in progressive periodontitis may help to develop new diagnostic and therapeutic approaches.

Impact of peri-implantitis on the proteome biology of crevicular fluid: A pilot study

BACKGROUND

The proteome of the peri-implant crevicular fluid (PICF) has not been systematically investigated. The aim of the present study was to reveal the proteome biology of dental implants affected with peri-implantitis.

METHODS

Patients with at least one diseased implant were included (probing depth ≥6 mm, ≥3 mm peri-implant radiological bone loss). Using sterile paper strips, samples were collected from healthy implants (I), healthy teeth (T) and peri-implantitis affected implants (P). Proteome analysis was performed using liquid chromatography - tandem mass spectrometry (LC-MS/MS) and data independent acquisition, allowing the identification and quantification of human and bacterial proteins as well as semi-specific peptides.

RESULTS

A total of 38 samples from 14 patients were included in the study; 2332 different human proteins were identified across all samples. No differentially expressed proteins between T and I were found. Comparing P to I, 59 proteins were found upregulated and 31 downregulated in P with significance. Upregulated proteins included proinflammatory proteins such as immunoglobulins, dysferlin, and S100P, as well as antimicrobial proteins, for example, myeloperoxidase or azurocidin. Gene ontology analysis further revealed higher activity of immunological pathways. Proteolytic patterns indicated the activity of inflammatory proteins such as cathepsin G. A total of 334 bacterial proteins were identified and quantified. Peri-implantitis showed elevated proteolytic activity.

CONCLUSION

I and T share similarities in their proteome, while diseased implants deviate strongly from healthy conditions. The PICF proteome of peri-implantitis affected sites exhibits an inflammatory fingerprint, dominated by neutrophil activity when compared with healthy implants.

Proteomic analysis of infected root canals with apical periodontitis in patients with type 2 diabetes mellitus: A cross-sectional study

AIM

This study aimed to quantitatively and qualitatively determine the proteomic profile of apical periodontitis (AP) in type 2 diabetes mellitus (T2DM) patients in comparison with systemically noncompromised patients and to correlate the protein expression of both groups with their biological functions.

METHODOLOGY

The sample consisted of 18 patients with asymptomatic AP divided into two groups according to the presence of T2DM: diabetic group-patients with T2DM (n = 9) and control group-systemically healthy patients (n = 9). After sample collection, the root canal samples were prepared for proteomic analysis using reverse-phase liquid chromatography-mass spectrometry. Label-free quantitative proteomic analysis was performed by Protein Lynx Global Service software. Differences in protein expression between groups were calculated using t-test (p < .05). Biological functions were analysed using the Homo sapiens UniProt database.

RESULTS

A total of 727 human proteins were identified in all samples. Among them, 124 proteins common to both groups were quantified, out of which 65 proteins from the diabetic group showed significant differences compared with the control: 43 upregulated (p < .05) and 22 downregulated (p < .05) proteins. No significant differences in protein expression were seen for the remaining 59 proteins (p > .05). Most proteins with differences in expression were related to immune/inflammatory response. Neutrophil gelatinase-associated lipocalin, Plastin-2, Lactotransferrin and 13 isoforms of immunoglobulins were upregulated. In contrast, Protein S100-A8, Protein S100-A9, Histone H2B, Neutrophil defensin 1, Neutrophil defensin 3 and Prolactin-inducible protein were downregulated.

CONCLUSIONS

Quantitative differences were demonstrated in the expression of proteins common to diabetic and control groups, mainly related to immune response, oxidative stress, apoptosis and proteolysis. These findings revealed biological pathways that provide the basis to support clinical findings on the relationship between AP and T2DM.

Systems Biology in Periodontitis

Systems biology is a promising scientific discipline that allows an integrated investigation of host factors, microbial composition, biomarkers, immune response and inflammatory mediators in many conditions such as chronic diseases, cancer, neurological disorders, and periodontitis. This concept utilizes genetic decoding, bioinformatic, flux-balance analysis in a comprehensive approach. The aim of this review is to better understand the current literature on systems biology and identify a clear applicability of it to periodontitis. We will mostly focus on the association between this condition and topics such as genomics, transcriptomics, proteomics, metabolomics, as well as contextualize delivery systems for periodontitis treatment, biomarker detection in oral fluids and associated systemic conditions.

Host Defence Peptides in Diabetes Mellitus Type 2 Patients with Periodontal Disease. A Systematic Review

The aim of the study was to critically assess and review the latest evidence relating the associations between host defence peptides (HDPs), periodontal diseases (PD) and diabetes mellitus type 2 (DM2). To explore studies on HDPs, periodontal disease, and DM2, researchers utilised specific key phrases to search the electronic databases PubMed (National Library of Medicine), Embase (Ovid), Medline (EBSCO), and Dentistry and Oral Sciences (EBSCO). Quality assessment was conducted by means of the Newcastle Ottawa scale and the Systematic Review Centre for Laboratory Animal Experimentation (SYRCLE) tool. Following a thorough screening process, a total of 12 papers (4 case-control, 6 cross-sectional, 1 animal, and 1 in vitro) fulfilled the selection criteria and were included. The majority of research found that HDPs were upregulated in DM2 patients with PD. Three investigations, however, found that HDPs were downregulated in DM2 patients with PD. HDPs play a part in the pathophysiology of PD and DM2. Nonetheless, more human, animal and laboratory investigations are needed to fully understand validation of the link, as the evidence is limited. Understanding HDPs as common moderators is critical, aimed at unlocking their potential as therapeutic and diagnostic agents.

Association between periodontitis and glycosylated haemoglobin before diabetes onset: a cross-sectional study

OBJECTIVES

The aim of the present cross-sectional study was to investigate the association between serum glycosylated haemoglobin (HbA1c) levels and periodontal status in patients with periodontitis (CP) and periodontally healthy controls. Furthermore, the objectives were to determine if the periodontitis influenced the serum HbA1c levels.

MATERIALS AND METHODS

A total of 93 patients with CP and 95 periodontally healthy subjects were enrolled in the present study using a cross-sectional design. At baseline, patients were examined and characterized on a regular basis for blood serum parameters and non-fasting blood samples levels. In all patients, a full periodontal examination was performed and clinical attachment loss (CAL) was the primary outcome variable chosen. The spearman correlation, a stepwise multivariable linear regression, and Jonckheere-Terpstra tests were applied in order to assess the relationship between HbA1c levels and periodontitis.

RESULTS

Patients in the CP group presented a significantly higher median serum level of HbA1c [40.9 (31.2; 45.6) mmol/mol)] compared to patients in the healthy control group [35.3 (29.6; 38.6) mmol/mol)] (p < 0.001). HbA1c levels were negatively correlated with the number of teeth and positively correlated with C-reactive protein levels and all periodontal parameters (p < 0.001). Moreover, there was a significant decrease in the number of teeth when HbA1c levels increased (P-trend < 0.001), while there was a significant increase in periodontal parameters (CAL, p = 0.002); PD, p = 0.008; BOP, p < 0.001) when levels of HbA1c increased.

CONCLUSIONS

Patients with CP and undiagnosed diabetes presented significantly higher serum levels of HbA1c compared to periodontally healthy controls. Moreover, the presence of periodontitis was positively correlated with serum HbA1c levels before diabetes onset.

CLINICAL RELEVANCE

HbA1c levels were positively correlated with the severity of periodontitis before diabetes onset.

Relationship between Blood and Standard Biochemistry Levels with Periodontitis in Parkinson's Disease Patients: Data from the NHANES 2011-2012

People with Parkinson's Disease (PD) are associated with the presence of periodontitis. We aimed to compare blood and standard biochemical surrogates of PD patients diagnosed with periodontitis with PD individuals without periodontitis. This retrospective cohort study used a sample from the National Health and Nutrition Examination Survey (NHANES) 2011-2012 that underwent periodontal diagnosis (n = 3669). PD participants were identified through specific PD reported medications. Periodontitis was defined according to the 2012 case definition, using periodontal examination data provided. Then, we compared blood levels and standard chemical laboratory profiles of PD patients according to the presence of periodontitis. Multivariable regression was used to explore this dataset and identify relevant variables towards the presence of periodontitis. According to the medication report, 37 participants were eligible, 29 were secure and 8 were unsecure PD medications regimens. Overall, PD cases with periodontitis presented increased levels of White Blood Cells (WBC) (p = 0.002), Basophils (p = 0.045) and Segmented neutrophils (p = 0.009), and also, lower levels of Total Bilirubin (p = 0.018). In the PD secure medication group, a significant difference was found for WBC (p = 0.002) and Segmented neutrophils (p = 0.002) for the periodontitis group. Further, WBC might be a discriminating factor towards periodontitis in the global sample. In the secure PD medication, we found gender, segmented neutrophils and Vitamin D2 to be potential discriminative variables towards periodontitis. Thus, periodontitis showed association with leukocyte levels alterations in PD patients, and therefore with potential systemic changes and predictive value. Furthermore, Vitamin D2 and gender showed to be associated with periodontitis in with secure medication for PD. Future studies should assess in more detail the potential systemic repercussion of the presence of periodontitis in PD patients.

Gingival Crevicular Fluid Peptidome Profiling in Healthy and in Periodontal Diseases

Given its intrinsic nature, gingival crevicular fluid (GCF) is an attractive source for the discovery of novel biomarkers of periodontal diseases. GCF contains antimicrobial peptides and small proteins which could play a role in specific immune-inflammatory responses to guarantee healthy gingival status and to prevent periodontal diseases. Presently, several proteomics studies have been performed leading to increased coverage of the GCF proteome, however fewer efforts have been done to explore its natural peptides. To fill such gap, this review provides an overview of the mass spectrometric platforms and experimental designs aimed at GCF peptidome profiling, including our own data and experiences gathered from over several years of matrix-assisted laser desorption ionization/time of flight mass spectrometry (MALDI-TOF MS) based approach in this field. These tools might be useful for capturing snapshots containing diagnostic clinical information on an individual and population scale, which may be used as a specific code not only for the diagnosis of the nature or the stage of the inflammatory process in periodontal disease, but more importantly, for its prognosis, which is still an unmet medical need. As a matter of fact, current peptidomics investigations suffer from a lack of standardized procedures, posing a serious problem for data interpretation. Descriptions of the efforts to address such concerns will be highlighted.

Proteomics approach for biomarkers and diagnosis of periodontitis: systematic review

Quantitative proteomic workflow based on mass spectrometry (MS) is recently developed by the researchers to screen for biomarkers in periodontal diseases comprising periodontitis. Periodontitis is known for chronic inflammatory disease characterized by progressive destruction of the tooth-supporting apparatus, yet has a lack of clear pathobiology based on a discrepancy between specified categories and diagnostic vagueness. The objective of this review was to outlined the accessible information related to proteomics studies on periodontitis. The Preferred Reporting Items for Systematical Reviews and Meta-Analysis (PRISMA) statement guides to acquaint proteomic analysis on periodontal diseases was applied. Three databases were used in this study, such as Pubmed, ScienceDirect and Biomed Central from 2009 up to November 2019. Proteomics analysis platforms that used in the studies were outlined. Upregulated and downregulated proteins findings data were found, in which could be suitable as candidate biomarkers for this disease.

Host-microbe interactions: Profiles in the transcriptome, the proteome, and the metabolome

Periodontal studies using transcriptomics, proteomics, and metabolomics encompass the collection of mRNA transcripts, proteins, and small-molecule chemicals in the context of periodontal health and disease. The number of studies using these approaches has significantly increased in the last decade and they have provided new insight into the pathogenesis and host-microbe interactions that define periodontal diseases. This review provides an overview of current molecular findings using -omic approaches that underlie periodontal disease, including modulation of the host immune response, tissue homeostasis, and complex metabolic processes of the host and the oral microbiome. Integration of these -omic approaches will broaden our perspective of the molecular mechanisms involved in periodontal disease, advancing and improving the diagnosis and treatment of various stages and forms of periodontal disease.

miR-9-1 gene methylation and DNMT3B (rs2424913) polymorphism may contribute to periodontitis

BACKGROUND

Genetic and epigenetic changes have been associated with periodontitis in various genes; however, little is known about genes involved in epigenetic mechanisms and in oxidative stress.

OBJECTIVE

This study aims to investigate the association of polymorphisms C677T in MTHFR (rs1801133) and -149C→T in DNMT3B (rs2424913), as well as the methylation profiles of MTHFR, miR-9-1, miR-9-3, SOD1, and CAT with periodontitis. The association between polymorphisms and DNA methylation profiles was also analyzed.

METHODOLOGY

The population studied was composed of 100 nonsmokers of both sexes, divided into healthy and periodontitis groups. Genomic DNA was extracted from the epithelial buccal cells, which were collected through a mouthwash. Polymorphism analysis was performed through polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), while methylation-specific PCR (MSP) or combined bisulfite restriction analysis techniques were applied for methylation analysis.

RESULTS

For DNMT3B, the T allele and the TT genotype were detected more frequently in the periodontitis group, as well as the methylated profile on the miR-9-1 promoter region. There was also a tendency towards promoter region methylation on the CAT sequence of individuals with periodontal disease.

CONCLUSION

The polymorphism -149C→T in DNMT3B (rs2424913) and the methylated profile of the miR-9-1 promoter region are associated with periodontitis.