Background. Type 2 diabetes mellitus (T2DM) and periodontitis (P) commonly occur as comorbidities, but the commonalities in the genetic makeup of affected individuals is largely unknown. Since dyslipidemia is a frequent condition in these individuals, we investigate the association of genomic variations in genes involved in lipid metabolism with periodontal, glycemic, lipid profiles, and the association with periodontitis and T2DM (as comorbidities). Methods. Based on clinical periodontal examination and biochemical evaluation, 893 subjects were divided into T2DM+P (T2DM subjects also affected by periodontitis, ), periodontitis ( ), and healthy ( ). Fourteen single-nucleotide polymorphisms (SNPs) were investigated: LDLR gene (rs5925 and rs688), APOB (rs676210, rs1042031, and rs693), ABCC8 (rs6544718 and 6544713), LPL (rs28524, rs3735964, and rs1370225), HNF1A (rs2650000), APOE (rs429358 and rs7412), and HNF4A (rs1800961). Multiple linear and logistic regressions (adjusted for covariates) were made for all populations and stratified by sex and smoking habits. Results. Individuals carrying APOB-rs1042031-CT (mainly women and never smokers) had a lower risk of developing periodontitis and T2DM (T2DM+P); altogether, this genotype was related with healthier glycemic, lipid, and periodontal parameters. Significant disease-phenotype associations with gene-sex interaction were also found for carriers of APOB-rs1676210-AG, HNF4A-rs1800961-CT, ABCC8-rs6544718-CT, LPL-rs13702-CC, and LPL-rs285-CT. Conclusions. Polymorphisms in lipid metabolism genes are associated with susceptibility to T2DM-periodontitis comorbidities, demonstrating gene-sex interaction. The APOB-rs1042031 was the most relevant gene marker related to glucose and lipid metabolism profiles, as well as with obesity and periodontitis.

This study aimed to develop and validate a dual murine model integrating a high-fat diet (HFD) and a single streptozotocin (STZ) dose to induce diabetes mellitus (DM), alongside periodontitis (Perio) induced by ligature placement and oral inoculation with Porphyromonas gingivalis (P. gingivalis). The goal was to mimic human pathological conditions, creating a physiologically relevant environment to study the interplay between DM and Perio. A total of 128 six-week-old male C57BL/6J mice were randomly divided into four groups: Control, DM, Perio, and DM-P. DM was induced by HFD and STZ injection, and Perio by ligature placement and P. gingivalis infection. Evaluations occurred at baseline and days 7, 14, and 21. Alveolar bone loss was assessed by micro-computed tomography, and inflammation was examined histologically. DM mice showed elevated glucose levels and insulin resistance. Perio and DM-P groups experienced significant bone loss compared with Control and DM groups. The morphometric analysis revealed abundant inflammatory cells and reduced collagen fibers in Perio and DM-P groups, especially at day 7. This dual murine model successfully replicated the key features of DM and Perio, maintaining overall health of the animals, and good tolerability by those subjects to the stress of both interventional procedures.

Aim: Peroxisome Proliferator-Activated Receptor Gamma (PPAR-γ) plays important anti-inflammatory roles, including in periodontitis. This systematic review with a meta-analysis compiles evidence on the transcriptional and translational levels of PPAR-γ in clinical and experimental periodontitis studies, alongside functional enrichment and PPAR-γ interaction network analyses. Method: Electronic searches were conducted in six databases for publications up to February 2024. For the meta-analysis of experimental studies of periodontitis, PPAR-γ levels in the periodontal tissues were assessed through gene expression (RT-qPCR) or protein expression (Western blotting). In the clinical periodontitis studies, PPAR-γ levels in the gingival tissues were evaluated through protein expression (immunohistochemistry). A risk of bias (RoB) assessment was performed using the Systematic Review Centre for Laboratory Animal Experimentation (SYRCLE) and Newcastle Ottawa Scale (NOS) tools for experimental and clinical studies, respectively. The enrichment analysis was performed using the g:Profiler tool, and gene interaction networks were analyzed using GeneMANIA. Results: The meta-analysis demonstrated significantly lower PPAR-γ protein levels in the periodontal tissues from animals with periodontitis. PPARG mRNA and PPAR-γ quantification through immunohistochemistry remained inconclusive. The bioinformatics analyses indicated direct or indirect PPAR-γ-associated molecules involved in the immune response to periodontitis. The PPAR-γ protein expression was higher in periodontal tissues from healthy animals compared to that from those with periodontitis. Conclusions: Given the inconclusive findings of RT-qPCR and immunohistochemistry, further PPARG mRNA and PPAR-γ protein evaluations are needed to clarify their levels in the periodontal tissues.