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Genetic analysis of hereditary gingival fibromatosis using whole exome sequencing and bioinformatics
Author(s) -
Hwang J,
Kim YL,
Kang S,
Kim S,
Kim SO,
Lee JH,
Han DH
Publication year - 2017
Publication title -
oral diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.953
H-Index - 87
eISSN - 1601-0825
pISSN - 1354-523X
DOI - 10.1111/odi.12583
Subject(s) - exome sequencing , gene , fibromatosis , phenotype , biology , genetics , genetic analysis , bioinformatics , medicine , pathology
Objectives Our 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 Methods Two 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 . Results Genetic 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, TMCO 1 , RIN 2 , and INSR , were found through human phenotype ontology ( HPO ) to have potential to contribute to gingival hyperplasia. Conclusions Genetic analysis of HGF in this study implicated mutations in fibronectin and the immune system as triggering abnormal gingival fibromatosis.