Forty-six genes causing nonsyndromic hearing impairment: Which ones should be analyzed in DNA diagnostics?

Abstract

Hearing impairment is the most common sensory disorder, present in 1 of every 500 newborns. With 46 genes implicated in nonsyndromic hearing loss, it is also an extremely heterogeneous trait. Here, we categorize for the first time all mutations reported in nonsyndromic deafness genes, both worldwide and more specifically in Caucasians. The most frequent genes implicated in autosomal recessive nonsyndromic hearing loss are GJB2, which is responsible for more than half of cases, followed by SLC26A4, MYO15A, OTOF, CDH23 and TMC1. None of the genes associated with autosomal dominant nonsyndromic hearing loss accounts for a preponderance of cases. Mutations are somewhat more frequently reported in WFS1, KCNQ4, COCH and GJB2. Only a minority of these genes is currently included in genetic diagnostics, the selection criteria typically reflecting: 1) high frequency as a cause of deafness (i.e. GJB2); 2) association with another recognizable feature (i.e. SLC26A4 and enlarged vestibular aqueduct); or 3) a recognizable audioprofile (i.e. WFS1). New and powerful DNA sequencing technologies have been developed over the past few years, but have not yet found their way into DNA diagnostics. Implementing these technologies is likely to happen within the next 5 years, and will cause a breakthrough in terms of power and cost efficiency. It will become possible to analyze most -if not all -deafness genes, as opposed to one or a few genes currently. This ability will greatly improve DNA diagnostics, provide epidemiological data on genebased mutation frequencies, and reveal novel genotype-phenotype correlations.

Development of the stria vascularis and potassium regulation in the human fetal cochlea: Insights into hereditary sensorineural hearing loss

“…The most commonly affected gene causing nonsyndromic hearing loss (both in autosomal recessive DFNB1A [MIM 220290] and in autosomal dominant DFNA3A [MIM 601544]) is gap junction beta 2 ( GJB2 , [MIM 121011]), the gene encoding the connexin 26 protein (CX26) (Kelsell et al, 1997; Denoyelle et al, 1997). Depending on the studied population, 20–50% of all recessive nonsyndromic SNHL cases can be attributed to a mutation in GJB2 (Hilgert et al, 2009a; Linden Phillips et al, 2013). For a comprehensive overview of other affected genes, we refer to recent reviews (Hilgert et al, 2009b; Angeli et al, 2012; Shearer and Smith, 2012; Smith et al, 2014 2014; Stelma and Bhutta, 2014).…”

Comprehensive genetic testing for hereditary hearing loss using massively parallel sequencing

“…Because mutations in a single gene, GJB2 (DFNB1), account for up to 50% of ARNSHL in many world populations (6), this approach has changed the evaluation of patients with presumed ARNSHL. However, the mutation frequency in other genes in persons with NSHL in outbred populations is unknown, making sequential gene screening problematic (7). The extreme heterogeneity of NSHL also makes serial sequencing approaches unfavorable in terms of efficiency and cost.…”

A Low-Cost Exon Capture Method Suitable for Large-Scale Screening of Genetic Deafness by the Massively-Parallel Sequencing Approach

“…Detection of mutations in individual deafness genes (e.g., GJB2, GJB6 and SLC26A4) is now available from many medical centers (www.genetests.org). As a large-scale diagnostic screening or genetic epidemiological research tool, however, the value of these tests is limited, because the vast majority of deafness genes are not examined (Hilgert et al, 2009). Array-based semi high-throughput resequencing methods (Kothiyal et al, 2010;Rodriguez-Paris et al, 2010) only test known mutations and have a much smaller capacity compared with the approach presented here.…”

“…The technology validated here reduced overall per-sample cost significantly and enabled commercial offering of mutation screening in a targeted panel of deafness genes (www.otogenetics.com). As a genetic screening method, the approach described here will undoubtedly provide a more complete epidemiological survey of currently known deafness genes (Hilgert et al, 2009). One of the critical issues in data analysis is how to filter out large numbers of deafness-unrelated SNPs.…”