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. 2015 Feb 10;10(2):e0118084.
doi: 10.1371/journal.pone.0118084. eCollection 2015.

Genetic investigation of bisphosphonate-related osteonecrosis of jaw (BRONJ) via whole exome sequencing and bioinformatics

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Genetic investigation of bisphosphonate-related osteonecrosis of jaw (BRONJ) via whole exome sequencing and bioinformatics

Jee-Hwan Kim et al. PLoS One. .

Abstract

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.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. An outline of variant selection for data analysis.
Fig 2
Fig 2. Analysis of gene function enrichment and construction of functional network.
Each cluster is represented as a yellow circle, in which nodes show all terms included in the cluster. A representative term was selected to describe each cluster. Node size shows the number of genes mapped in the network. Nodes were color-coded according to their characteristics: genes related to cell morphology (pink), cell adhesion and binding (green), Ubiquitin-like proteins and isopeptide bond (red), and proteases (yellow). If different terms share two or more genes, a link was given. Links express the number of genes shared among distinct terms.

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