A novel EDAR missense mutation identified by whole‐exome sequencing with non‐syndromic tooth agenesis in a Chinese family. Issue 6 (4th May 2021) - Zhang, Hongyu; Kong, Xuanting; Ren, Jiabao; Yuan, Shuo; Liu, Chunyan; Hou, Yan; Liu, Ye; Meng, Lingqiang; Zhang, Guozhong; Du, Qingqing; Shen, Wenjing
Abstract: Background: Causative variants in genes of the EDA/EDAR/NF‐κB pathway, such as EDA and EDARADD, have been widely identified in patients with non‐syndromic tooth agenesis (NSTA). However, few cases of NSTA are due to ectodysplasin‐A receptor ( EDAR ) variants. In this study, we investigated NSTA‐associated variants in Chinese families. Methods: Peripheral blood samples were collected from the family members of 24 individuals with NSTA for DNA extraction. The coding region of the EDA gene of the 24 probands was amplified by PCR and sequenced to investigate new variants. Whole‐exome sequencing and Sanger sequencing were then performed for probands without EDA variants detected by PCR. Results: A novel missense variant EDAR c.338G>A (p.(Cys113Tyr)) was identified in one family. In addition, three known EDA variants (c.865C>T, c.866G>A, and c.1013C>T) were identified in three families. Genotype–phenotype correlation analysis of EDAR gene mutation showed that NSTA patients were most likely to lose the maxillary lateral incisors and the maxillary central incisors were the least affected. The phenotype of mutations at codon 289 of EDA in NSTA affected patients was characterized by lateral incisors loss, rarely affecting the maxillary first molars. Conclusion: A novel EDAR missense variant c.338G>A (p.(Cys113Tyr)) was identified in a family with NSTA, extending the mutation spectrum of the EDAR gene. Genotype–phenotype correlation analyses of EDAR and EDA mutations could help to improve disease status prediction in NSTA families. Abstract : A novel EDAR missense mutation, c.338G>A (Cys113Tyr), was identified in a pedigree with NSTA, extending the mutation spectrum of the EDAR gene. Genotype–phenotype correlation analyses of EDAR and EDA mutation could help to improve disease status prediction in NSTA families.