Within the limitations of this study, microgrooved implants may provide more favorable conditions for the attachment of hard and soft tissues and reduce the level of marginal bone resorption and soft tissue recession.
Complications associated with the use of bisphosphonate (BP) have risen over the years due to an increase in the prescription of BP. BP-related osteonecrosis of jaw (BRONJ), one of the complications linked to the consumption of BP, greatly affects patients with minor dental trauma, incurring a long healing period. While BRONJ afflicts only a minority of patients prescribed with BP, BRONJ is a multigenic disease affected both by environmental and genetic factors having a distinctive phenotype. This study aims to discover genetic biomarkers associated with BRONJ via whole exome sequencing (WES) followed by statistical analysis. Sixteen individuals who had been prescribed with bisphosphonate medication and diagnosed as BRONJ were chosen and each individual’s saliva sample was collected for WES. 126 randomized subsamples from the GSK project representing 109 male and 17 female Koreans were used as a control data set. Fisher’s exact test was carried out to assess the significance of genetic variants in BRONJ patients. Gene set enrichment analysis (GSEA) (DAVID Bioinformatics Resource 6.7) was used to perform a cluster analysis of variants found from Fisher‘s exact test. The results from this study suggest that BRONJ-inducing factors are genetically associated and BRONJ occurs due to the malfunctioning of post-translational modification in osteoclast leading to the impairment of cell morphology and adhesion.
Peri-implantitis is a frequently occurring gum disease linked to multi-factorial traits with various environmental and genetic causalities and no known concrete pathogenesis. The varying severity of peri-implantitis among patients with relatively similar environments suggests a genetic aspect which needs to be investigated to understand and regulate the pathogenesis of the disease. Six unrelated individuals with multiple clusterization implant failure due to severe peri-implantitis were chosen for this study. These six individuals had relatively healthy lifestyles, with minimal environmental causalities affecting peri-implantitis. Research was undertaken to investigate pathogenic genes in peri-implantitis albeit with a small number of subjects and incomplete elimination of environmental causalities. Whole-exome sequencing was performed on collected saliva samples via self DNA collection kit. Common variants with minor allele frequencies (MAF) > = 0.05 from all control datasets were eliminated and variants having high and moderate impact and loss of function were used for comparison. Gene set enrichment analysis was performed to reveal functional groups associated with the genetic variants. 2,022 genes were left after filtering against dbSNP, the 1000 Genomes East Asian population, and healthy Korean randomized subsample data (GSK project). 175 (p-value <0.05) out of 927 gene sets were obtained via GSEA (DAVID). The top 10 was chosen (p-value <0.05) from cluster enrichment showing significance of cytoskeleton, cell adhesion, and metal ion binding. Network analysis was applied to find relationships between functional clusters. Among the functional groups, ion metal binding was located in the center of all clusters, indicating dysfunction of regulation in metal ion concentration might affect cell morphology or cell adhesion, resulting in implant failure. This result may demonstrate the feasibility of and provide pilot data for a larger research project aimed at discovering biomarkers for early diagnosis of peri-implantitis.
Genetic analysis of HGF in this study implicated mutations in fibronectin and the immune system as triggering abnormal gingival fibromatosis.
Objective Hereditary gingival fibromatosis (HGF) is a rare oral disease characterized by either localized or generalized gradual, benign, non‐hemorrhagic enlargement of gingivae. Although several genetic causes of HGF are known, the genetic etiology of HGF as a non‐syndromic and idiopathic entity remains uncertain. Subjects and methods We performed exome and RNA‐seq of idiopathic HGF patients and controls, and then devised a computational framework that specifies exomic/transcriptomic alterations interconnected by a regulatory network to unravel genetic etiology of HGF. Moreover, given the lack of animal model or large‐scale cohort data of HGF, we developed a strategy to cross‐check their clinical relevance through in silico gene–phenotype mapping with biomedical literature mining and semantic analysis of disease phenotype similarities. Results Exomic variants and differentially expressed genes of HGF were connected by members of TGF‐β/SMAD signaling pathway and craniofacial development processes, accounting for the molecular mechanism of fibroblast overgrowth mimicking HGF. Our cross‐check supports that genes derived from the regulatory network analysis have pathogenic roles in fibromatosis‐related diseases. Conclusions The computational approach of connecting exomic and transcriptomic alterations through regulatory networks is applicable in the clinical interpretation of genetic variants in HGF patients.
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