Role of Targeted Next Generation Sequencing in the Etiological Work-Up of Congenitally Deaf Children.
Otol Neurotol. 2018 Jul;39(6):732-738
Authors: Boudewyns A, van den Ende J, Sommen M, Wuyts W, Peeters N, Van de Heyning P, Van Camp G
OBJECTIVES: The purpose of this study is to report the results of a comprehensive etiological work-up for congenitally deaf children including targeted next generation sequencing.
STUDY DESIGN: Retrospective case review.
SETTING: Tertiary referral center.
PATIENTS: Fifty children with congenital, bilateral profound hearing loss (HL) (>90 dBnHL).
INTERVENTIONS: Etiological work-up included testing for pathogenic variants in GJB2, a phenotype driven genetic analysis, screening for congenital infections and imaging. When no etiology could be found, comprehensive genetic testing was performed using a HL gene panel including 45 syndromic and 96 non-syndromic HL genes.
RESULTS: Eleven patients carried bi-allelic pathogenic variants in GJB2. Phenotype driven genetic analysis identified two homozygous KCNQ1 patients (Jervell and Lange Nielsen syndrome) and one heterozygous CHD7 patient (CHARGE syndrome). One patient was diagnosed with achondroplasia and one had a clinical diagnosis of Waardenburg syndrome. A deafness gene panel evaluated 16 patients. In 12 out of 16, we identified a pathogenic (n = 12) or likely pathogenic (n = 2) variant and one variant of unknown significance (VUS). A definite diagnosis of non-syndromic or syndromic HL was made in 18 and seven patients, respectively. Non-genetic causes were congenital cytomegalovirus infection (n = 11), anatomic abnormalities (n = 2), neurological/metabolic/polymalformative conditions (n = 3), meningitis (n = 1), and auditory neuropathy (n = 1).
CONCLUSIONS: A definite genetic cause was found in 25 (50%) of congenital, bilaterally deaf children. Our data show that implementation of a gene panel improves the diagnostic yield for etiological work-up of congenital profound HL to 86%. Identification of the etiology of congenital HL may contribute to predicting outcomes of cochlear implantation.
PMID: 29889784 [PubMed – in process]