{Reference Type}: Journal Article
{Title}: Exomic and transcriptomic alterations of hereditary gingival fibromatosis.
{Author}: Han SK;Kong J;Kim S;Lee JH;Han DH;
{Journal}: Oral Dis
{Volume}: 25
{Issue}: 5
{Year}: Jul 2019
{Factor}: 4.068
{DOI}: 10.1111/odi.13093
{Abstract}: <B>OBJECTIVE: </B>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.<BR><B>METHODS: </B>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.<BR><B>RESULTS: </B>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.<BR><B>CONCLUSIONS: </B>The computational approach of connecting exomic and transcriptomic alterations through regulatory networks is applicable in the clinical interpretation of genetic variants in HGF patients.