ArticleBMC medical genomics2022
Identification of a novel CNV at the EYA4 gene in a Chinese family with autosomal dominant nonsyndromic hearing loss.
Article in BMC medical genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Two Novel Compound HeterozygousInternational journal of general medicine · 2026Article
- Identification of a novel EYA4 likely pathogenic variant in a Chinese family with postlingual non-syndromic hearing loss and analysis of molecular epidemiology of EYA4 variants.BMC medical genomics · 2024Article
- A novel splice-altering TNC variant (c.5247A > T, p.Gly1749Gly) in an Chinese family with autosomal dominant non-syndromic hearing loss.BMC medical genomics · 2024Article
- Autosomal Dominant Non-Syndromic Hearing Loss (DFNA): A Comprehensive Narrative Review.Biomedicines · 2023Review
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHereditary hearing loss is a heterogeneous class of disorders that exhibits various patterns of inheritance and involves many genes. Variants in the EYA4 gene in DFNA10 are known to lead to postlingual, progressive, autosomal dominant nonsyndromic hereditary hearing loss. PATIENTS AND
methodsWe collected a four-generation Chinese family with autosomal-dominant nonsyndromic hearing loss (ADNSHL). We applied targeted next-generation sequencing (TNGS) in three patients of this pedigree and whole-genome sequencing (WGS) in the proband. The intrafamilial cosegregation of the variant and the deafness phenotype were confirmed by PCR, gap-PCR and Sanger sequencing.
resultsA novel CNV deletion at 6q23 in exons 8-11 of the EYA4 gene with a 10 bp insertion was identified by TNGS and WGS and segregated with the ADNSHL phenotypes.
conclusionsOur results expanded the variant spectrum and genotype‒phenotype correlation of the EYA4 gene and autosomal dominant nonsyndromic hereditary hearing loss in Chinese Han individuals. WGS is an accurate and effective method for verifying the genomic features of CNVs.
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