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Amelogenesis imperfecta: A novel FAM83H mutation and characteristics of periodontal ligament cells
Author(s) -
Nowwarote Nunthawan,
Theerapa Thanakorn,
Osatha Thanaphum,
Pavasant Prasit,
Porntaveetus Thantrira,
Shotelersuk Vorasuk
Publication year - 2018
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.12926
Subject(s) - periodontal fiber , proband , nonsense mutation , mutation , exome sequencing , biology , medicine , chemistry , dentistry , genetics , gene , missense mutation
Objective To delineate orodental features, dental mineral density, genetic aetiology and cellular characteristics associated with amelogenesis imperfecta (AI). Materials and Methods Three affected patients in a family were recruited. Whole‐exome sequencing was used to identify mutations confirmed by Sanger sequencing. The proband's teeth were subjected for mineral density analysis by microcomputerised tomography and characterisation of periodontal ligament cells (PDLCs). Results The patients presented yellow‐brown, pitted and irregular enamel. A novel nonsense mutation, c.1261G>T, p.E421*, in exon 5 of the FAM83H was identified. The mineral density of the enamel was significantly decreased in the proband. The patient's PDLCs ( FAM83H cells) exhibited reduced ability of cell proliferation and colony‐forming unit compared with controls. The formation of stress fibres was remarkably present. Upon cultured in osteogenic induction medium, FAM83H cells, at day 7 compared to day 3, had a significant reduction of BSP , COL1 and OCN mRNA expression and no significant change in RUNX2 . The upregulation of ALP mRNA levels and mineral deposition were comparable between FAM83H and control cells. Conclusions We identified the novel mutation in FAM83H associated with autosomal dominant hypocalcified AI. The FAM83H cells showed reduced cell proliferation and expression of osteogenic markers, suggesting altered PDLCs in FAM83H ‐associated AI.