MMP-2 salivary activity in type 2 diabetes mellitus patients

Relationship Between Diabetes Mellitus and Periodontal/Peri-Implant Disease: A Contemporaneous Review

The prevalence of diabetes mellitus (DM), a major chronic disease and a leading cause of death and disability around the world, is rising. According to the latest data, the global prevalence of DM has increased to 463 million (9.3% of adults) in 2019 and is estimated to reach 700 million by 2045. Periodontal disease, result of periodontium inflammation, is a common, chronic disease and has long been considered one of the complications of DM. Moreover, literature reflects a spectrum of conflicting viewpoints on the effect of diabetic conditions on the implant treatment strategies. The current review aims to update the recent epidemiologic evidence regarding the relationship between DM and periodontal/peri-implant disease, emphasising the effects of glycaemic control on the severity of these diseases and describing the pathobiological mechanisms underlying this association. This review's findings indicate a bidirectional relationship between DM and periodontal/peri-implant disease and that this relationship seems causal, implying that controlling these two diseases might help prevent each other's incidence. Additionally, the severity of periodontal/peri-implant disease is directly related to metabolic control. Although patients with diabetes can obtain implant success similar to those in systemically healthy individuals, an increased risk of peri-implantitis has been reported in DM patients. Therefore, the importance of glycaemic control and maintaining proper oral hygiene cannot be overstated.

Fibro-inflammatory recovery and type 2 diabetes remission following a low calorie diet but not exercise training: A secondary analysis of the DIASTOLIC randomised controlled trial

AIMS

To investigate the relationship between fibro-inflammatory biomarkers and cardiovascular structure/function in people with Type 2 Diabetes (T2D) compared to healthy controls and the effect of two lifestyle interventions in T2D.

METHODS

Data were derived from the DIASTOLIC randomised controlled trial (RCT) and includes a comparison between those with T2D and the matched healthy volunteers recruited at baseline. Adults with T2D without cardiovascular disease (CVD) were randomized to a 12-week intervention either: (1) exercise training, (2) a low-energy (∼810 kcal/day) meal-replacement plan (MRP) or (3) standard care. Principal Component and Fisher's linear discriminant analysis were used to investigate the relationships between MRI acquired cardiovascular outcomes and fibro-inflammatory biomarkers in cases versus controls and pre- and post-intervention in T2D.

RESULTS

At baseline, 83 people with T2D (mean age 50.5 ± 6.4; 58% male) and 36 healthy controls (mean age 48.6 ± 6.2; 53% male) were compared and 76 people with T2D completed the RCT for pre- post-analysis. Compared to healthy controls, subjects with T2D had adverse cardiovascular remodelling and a fibro-inflammatory profile (20 differentially expressed biomarkers). The 3D data visualisations showed almost complete separation between healthy controls and those with T2D, and a marked shift towards healthy controls following the MRP (15 biomarkers significantly changed) but not exercise training.

CONCLUSIONS

Fibro-inflammatory pathways and cardiovascular structure/function are adversely altered before the onset of symptomatic CVD in middle-aged adults with T2D. The MRP improved the fibro-inflammatory profile of people with T2D towards a more healthy status. Long-term studies are required to assess whether these changes lead to continued reverse cardiac remodelling and prevent CVD.

Identification of Type 2 Diabetes Based on a Ten-Gene Biomarker Prediction Model Constructed Using a Support Vector Machine Algorithm

Background

Type 2 diabetes is a major health concern worldwide. The present study is aimed at discovering effective biomarkers for an efficient diagnosis of type 2 diabetes.

Methods

Differentially expressed genes (DEGs) between type 2 diabetes patients and normal controls were identified by analyses of integrated microarray data obtained from the Gene Expression Omnibus database using the Limma package. Functional analysis of genes was performed using the R software package clusterProfiler. Analyses of protein-protein interaction (PPI) performed using Cytoscape with the CytoHubba plugin were used to determine the most sensitive diagnostic gene biomarkers for type 2 diabetes in our study. The support vector machine (SVM) classification model was used to validate the gene biomarkers used for the diagnosis of type 2 diabetes.

Results

GSE164416 dataset analysis revealed 499 genes that were differentially expressed between type 2 diabetes patients and normal controls, and these DEGs were found to be enriched in the regulation of the immune effector pathway, type 1 diabetes mellitus, and fatty acid degradation. PPI analysis data showed that five MCODE clusters could be considered as clinically significant modules and that 10 genes (IL1B, ITGB2, ITGAX, COL1A1, CSF1, CXCL12, SPP1, FN1, C3, and MMP2) were identified as “real” hub genes in the PPI network using algorithms such as Degree, MNC, and Closeness. The sensitivity and specificity of the SVM model for identifying patients with type 2 diabetes were 100%, with an area under the curve of 1 in the training as well as the validation dataset.

Conclusion

Our results indicate that the SVM-based model developed by us can facilitate accurate diagnosis of type 2 diabetes.

Impact of the Glycemic Level on the Salivary Proteome of Middle-Aged and Elderly People With Type 2 Diabetes Mellitus: An Observational Study

Type 2 diabetes mellitus (T2DM) is an increasing global public health concern, but its impact on the salivary proteome is still unclear. To evaluate the effect of glycemic levels in middle-aged and elderly individuals with T2DM on salivary proteomics, we compared the differences by liquid chromatography tandem mass spectrometry (LC–MS/MS). Unstimulated whole saliva samples from 8 T2DM patients with good glycemic control (G group, HbA1c <6.5%) and 16 patients with poor control (P group, HbA1c ≥6.5%) were analyzed by LC–MS/MS in the data-independent acquisition mode (Clinical register number: ChiCTR1900023582.). After functional annotation, cluster analysis and receiver operating characteristic (ROC) curve analysis were carried out to screen and evaluate candidate proteins. A total of 5,721 proteins were quantified, while 40 proteins differed significantly. In the P group, proteins involved in oxidative stress-related processes were upregulated, whereas proteins related to salivary secretion were downregulated. The combination of thioredoxin domain-containing protein 17, zymogen granule protein 16B, and FAM3 metabolism regulating signaling molecule D yielded an area under the curve of 0.917 which showed a robust ability to distinguish the P and G groups. In conclusion, poorly controlled hyperglycemia may affect salivary proteins through various pathways, including oxidative stress and glandular secretion. Furthermore, the differentially expressed proteins, especially the three proteins with the best differentiation, might serve as an anchor point for the further study of hyperglycemia and oral diseases.

Should We Be Concerned about the Association of Diabetes Mellitus and Periodontal Disease in the Risk of Infection by SARS-CoV-2? A Systematic Review and Hypothesis

The objective of this article was to conduct a systematic review of the literature to contrast the existing evidence regarding the relationship between periodontal disease (PD) and diabetes mellitus (DM) with the possibly increased risk of SARS-CoV-2 infection, as well as to establish a hypothesis that explains the ways in which this interaction could take place. A literature search up from 1 January 2020 to 21 March 2021 was conducted in three electronic databases, namely, PubMed, Web of Science, and Scopus, in order to identify studies on periodontal disease alone or in conjunction with diabetes mellitus, reporting any relation with SARS-CoV-2 infection as a primary outcome. Only articles published in the English language were included. Due to the lack of studies, we decided to collect all the theoretical and clinical evidence suggesting a possible biological pathway evidencing the relationship among PD, DM, and SARS-CoV-2 infection. From a total of 29 articles, 12 were included for final review studies (five reviews, two hypotheses, one Special Issue, one perspective, one commentary, one case–control study, and one case report). In addition, this systematic review article hypothesizes the correlation between PD and type 2 diabetes mellitus (T2DM) by expression of angiotensin-converting enzyme 2 (ACE2) in periodontal tissue and the risk of SARS-CoV-2 infection. T2DM is a metabolic disorder characterized by high blood glucose levels resulting from altered insulin secretion or action. Likewise, periodontitis and T2DM are inflammatory disorders with a bidirectional association, and both diseases have a similar immunomodulatory cascade and cytokine profile. ACE2 is a crucial component of the renin–angiotensin system (RAS) and the key factor of entry in the cells by the new SARS-CoV-2. ACE2 is widely distributed in the lung and kidneys, and interestingly has a great distribution in the oral cavity, principally in the tongue and periodontal tissue. ACE2 in periodontal tissue plays a crucial role between health and disease. Moreover, the ACE2/Ang-(1-7)/MasR axis is downregulated in the dysbiotic and inflammatory periodontal environment. Nevertheless, the balance of ACE2 activity is modified in the context of concurrent diabetes, increasing the expression of ACE2 by the uncontrolled glycemia chronic in T2DM. Therefore, the uncontrolled hyperglycemia possibly increases the risk of developing periodontitis and triggering overexpression of ACE2 in periodontal tissue of T2DM patients, with these events potentially being essential to SARS-CoV-2 infection and the development of mild-to-severe form of COVID-19. In this sense, we would like to point out that the need for randomized controlled trials is imperative to support this association.

PTGER3 and MMP-2 play potential roles in diabetic nephropathy via competing endogenous RNA mechanisms

BACKGROUND

Diabetic nephropathy (DN) is a primary complication of diabetes mellitus (DM). The pathology of DN is still vague, and diagnostic accuracy is not enough. This study was performed to identify miRNAs and genes that have possibilities of being used as therapeutic targets for DN in type 2 DM.

METHODS

Human miRNA data GSE51674 and gene data GSE111154 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and miRNAs (DEmiRNAs) in the kidney between control and DN patients were screened out. The competing endogenous RNA (ceRNA) network was constructed, and key lncRNA-miRNA-mRNA pairs were selected accordingly. Potential drugs targeting DEGs were screened out and validated using PCR analysis.

RESULTS

Totally, 83 DEmiRNAs and 293 DEGs were identified in GSE51674 and GSE111154, respectively. Thirteen of the top 20 DEmiRNAs (10 up and 10 down) targeted to 47 DEGs. In the ceRNA network, RP11-363E7.4/TTN-AS1/HOTAIRM1-hsa-miR-106b-5p-PTGER3 and LINC00960-hsa-miR-1237-3p-MMP-2 interaction pairs were identified as the key ceRNA network. Interestingly, PTGER3 and hsa-miR-1237-3p were downregulated, and MMP-2 and hsa-miR-106b-5p were upregulated in the kidney of patients with DN compared with normal controls, respectively. PTGER3 and MMP-2 were targeted by drugs including iloprost, treprostinil, or captopril, and the deregulation of the two genes was confirmed in the plasma samples from patients with DN as compared with controls.

CONCLUSIONS

We speculated that the RP11-363E7.4/TTN-AS1/HOTAIRM1-hsa-miR-106b-5p-PTGER3 and LINC00960-hsa-miR-1237-3p-MMP-2 networks were associated with diabetic renal injury.

Salivary biomarkers for discriminating periodontitis in the presence of diabetes

AIM

Salivary biomarkers can help in assessment of periodontitis; however, concentrations may be altered in the presence of diabetes. Hence, the ability of salivary biomarkers to discriminate periodontally healthy type II diabetics (T2DM) from T2DM who have periodontitis was examined.

METHODS

Ninety-two participants (29 with T2DM with chronic periodontitis, DWP; 32 T2DM without chronic periodontitis, DWoP; and 31 Not Periodontitis, NP) provided saliva and clinical parameters of periodontal health were recorded. Salivary concentrations of interleukin (IL)-1β, IL-6, matrix metalloproteinase-8 (MMP-8), macrophage inflammatory protein-1α (MIP-1α), adiponectin and resistin were measured by immunoassay.

RESULTS

Salivary analyte concentrations for IL-1β, MMP-8 and resistin correlated with clinical parameters of periodontitis, with MMP-8 demonstrating the strongest positive correlation with PD ≥5 mm (p < 0.0001). Periodontal health was reflected in salivary analyte concentrations by group, with concentrations of IL-1β and MMP-8 showing significant associations with periodontitis (p ≤ 0.04) that increased in concentration from health to DWoP to DWP. Odds ratio (OR) analyses showed that MMP-8 discriminated periodontitis from NP (OR of 8.12; 95% CI: 1.01-65.33; p = 0.03) and in the presence of T2DM (DWP vs DWoP, OR = 5.09; 95% CI: 1.24-20.92; p = 0.03).

CONCLUSION

Salivary MMP-8 and IL-1β discriminate periodontitis in T2DM.

Metalloproteinases and Their Inhibitors: Potential for the Development of New Therapeutics

The metalloproteinase (MP) family of zinc-dependent proteases, including matrix metalloproteinases (MMPs), a disintegrin and metalloproteases (ADAMs), and a disintegrin and metalloproteinase with thrombospondin motifs (ADAMTSs) plays a crucial role in the extracellular matrix (ECM) remodeling and degradation activities. A wide range of substrates of the MP family includes ECM components, chemokines, cell receptors, and growth factors. Metalloproteinases activities are tightly regulated by proteolytic activation and inhibition via their natural inhibitors, tissue inhibitors of metalloproteinases (TIMPs), and the imbalance of the activation and inhibition is responsible in progression or inhibition of several diseases, e.g., cancer, neurological disorders, and cardiovascular diseases. We provide an overview of the structure, function, and the multifaceted role of MMPs, ADAMs, and TIMPs in several diseases via their cellular functions such as proteolysis of other cell signaling factors, degradation and remodeling of the ECM, and other essential protease-independent interactions in the ECM. The significance of MP inhibitors targeting specific MMP or ADAMs with high selectivity is also discussed. Recent advances and techniques used in developing novel MP inhibitors and MP responsive drug delivery tools are also reviewed.