A rare case of Waardenburg syndrome with unilateral hearing loss caused by nonsense variant c.772C>T (p.Arg259*) in the MITF gene in Yakut patient from the Eastern Siberia (Sakha Republic, Russia).
Nikolay A BarashkovGeorgii P RomanovUigulaana P BorisovaAisen V SolovyevVera G PshennikovaFedor M TeryutinAlexander A BondarIgor V MorozovElza K KhusnutdinovaOlga L PosukhTatiana E BurtsevaJon Øyvind OdlandSardana A FedorovaPublished in: International journal of circumpolar health (2020)
Waardenburg syndrome (WS) is an orphan genetic disease with autosomal dominant pattern of inheritance characterised by varying degrees of hearing loss accompanied by skin, hair and iris pigmentation abnormalities. Four types of WS differing in phenotypic characteristics are now described. We performed a Sanger sequencing of coding regions of genes PAX3, MITF, SOX10 and SNAI2 in the patient with WS from a Yakut family living in the Sakha Republic. No changes were found in the PAX3, SOX10 and SNAI2 coding regions while a previously reported heterozygous transition c.772C>T (p.Arg259*) in exon 8 of the MITF gene was found in this patient. This patient presents rare phenotype of WS type 2: congenital unilateral hearing loss, unilateral heterochromia of irises, and absence of skin/hair depigmentation and dystopia canthorum. Audiological variability in WS type 2, caused by the c.772C>T (p.Arg259*) variant in the MITF gene, outlines the importance of molecular analysis and careful genotype-phenotype comparisons in order to optimally inform patients about the risk of hearing loss. The results of this study confirm the association of pathogenic variants in the MITF gene with WS type 2 and expanded data on the variability of audiological features of the WS.
Keyphrases
- south africa
- hearing loss
- case report
- copy number
- genome wide
- genome wide identification
- mitochondrial dna
- rare case
- end stage renal disease
- transcription factor
- dna methylation
- ejection fraction
- newly diagnosed
- chronic kidney disease
- soft tissue
- electronic health record
- deep learning
- peritoneal dialysis
- machine learning