Genetic analysis of hereditary gingival fibromatosis using whole exome sequencing and bioinformatics

Abstract

ObjectivesOur study aims to identify genetic variants associated with hereditary gingival fibromatosis (HGF) by applying whole-exome sequencing (WES) and bioinformatics analyses such as gene set enrichment analysis (GSEA) and protein functional network study. Subjects and MethodsTwo affected siblings whose grandparents and parents have normal gingiva were chosen for our investigation. Saliva collected from the patients and their parents were used for WES. GSEA and protein functional network study were performed to find gene groups in a biological coordination which are associated with HGF. ResultsGenetic variants for homozygotes and compound heterozygotes were analyzed and translated into 845 genes. The result from protein functional network study showed that these genetic variants were mainly observed in genes affecting fibronectin as well as the immune and autoimmune system. Additionally, three mutated genes in our HGF patients,TMCO1,RIN2, andINSR, were found through human phenotype ontology (HPO) to have potential to contribute to gingival hyperplasia. ConclusionsGenetic analysis of HGF in this study implicated mutations in fibronectin and the immune system as triggering abnormal gingival fibromatosis.