Login / Signup

Novel WDR72 Mutations Causing Hypomaturation Amelogenesis Imperfecta.

Youn Jung KimHong ZhangYejin LeeFigen SeymenMine KoruyucuYelda KasimogluJames P SimmerJan C-C HuJung-Wook Kim
Published in: Journal of personalized medicine (2023)
Amelogenesis imperfecta (AI) is a heterogeneous collection of hereditary enamel defects. The affected enamel can be classified as hypoplastic, hypomaturation, or hypocalcified in form. A better understanding of normal amelogenesis and improvements in our ability to diagnose AI through genetic testing can be realized through more complete knowledge of the genes and disease-causing variants that cause AI. In this study, mutational analysis was performed with whole exome sequencing (WES) to identify genetic etiology underlying the hypomaturation AI condition in affected families. Mutational analyses identified biallelic WDR72 mutations in four hypomaturation AI families. Novel mutations include a homozygous deletion and insertion mutation (NM_182758.4: c.2680_2699delinsACTATAGTT, p.(Ser894Thrfs*15)), compound heterozygous mutations (paternal c.2332dupA, p.(Met778Asnfs*4)) and (maternal c.1287_1289del, p.(Ile430del)) and a homozygous 3694 bp deletion that includes exon 14 (NG_017034.2:g.96472_100165del). A homozygous recurrent mutation variant (c.1467_1468delAT, p.(Val491Aspfs*8)) was also identified. Current ideas on WDR72 structure and function are discussed. These cases expand the mutational spectrum of WDR72 mutations causing hypomaturation AI and improve the possibility of genetic testing to accurately diagnose AI caused by WDR72 defects.
Keyphrases
  • artificial intelligence
  • machine learning
  • deep learning
  • healthcare
  • genome wide
  • copy number
  • photodynamic therapy
  • autism spectrum disorder
  • pregnant women
  • dna methylation
  • intellectual disability
  • birth weight