Audioprofile-directed screening identifies novel mutations in KCNQ4 causing hearing loss at the DFNA2 locus

Abstract

Purpose: Gene identification in small families segregating autosomal dominant sensorineural hearing loss presents a significant challenge. To address this challenge, we have developed a machine learning-based software tool, AudioGene v2.0, to prioritize candidate genes for mutation screening based on audioprofiling.

Methods: We analyzed audiometric data from a cohort of American families with high-frequency autosomal dominant sensorineural hearing loss. Those families predicted to have a DFNA2 audioprofile by AudioGene v2.0 were screened for mutations in the KCNQ4 gene.

Results: Two novel missense mutations and a stop mutation were detected in three American families predicted to have DFNA2-related deafness for a positive predictive value of 6.3%. The false negative rate was 0%. The missense mutations were located in the channel pore region and the stop mutation was in transmembrane domain S5. The latter is the first DFNA2-causing stop mutation reported in KCNQ4.

Conclusions: Our data suggest that the N-terminal end of the P-loop is crucial in maintaining the integrity of the KCNQ4 channel pore and AudioGene audioprofile analysis can effectively prioritize genes for mutation screening in small families segregating high-frequency autosomal dominant sensorineural hearing loss. AudioGene software will be made freely available to clinicians and researchers once it has been fully validated.

Figure 1

Genetic screening strategy for small families segregating ADSNHL. AudioGene is used to rank order all known genes that cause ADSNHL (letters in black boxes), placing genes that have similar audioprofiles into clusters (red boxes). Haplotyping is used to determine whether any candidate gene within a given cluster can be eliminated; mutation screening is completed on candidate genes that cannot be eliminated. If families are too small to make haplotyping useful, all genes within a cluster will be screened, beginning with the highest ranking cluster.

Figure 2

Graphic depiction of the classification (and misclassification) of 2,400 audiograms from 360 patients for six genes. Each node in the graph represents a gene and each arc represents the number of individuals classified as having the audioprofile for that gene by Audiogene v2.0. The number of individuals indicated between the nodes are those misclassified by the program.

Figure 3

Left: Web interface of a tool to allow human experts to classify audiograms to the likely causal gene. Right: Results of human classification of 50 audiograms for DFNA2 and DFNA5 (in the same cluster) by 27 experts versus machine classification of the same set of audiograms.

Figure 4

Graphical representation of the gene prediction for each of 160 individuals from 77 ADSNHL families by AudioGene v2.0 audioprofiling

Figure 5

Point mutations in KCNQ4 exon 5. A–B Sequence chromatograms of the patient with the p.E260K mutation and a normal CEPH control. The mutation results in a G/A nucleotide substitution. C–D Sequence chromatograms of the patient with the p.D262V mutation and a normal CEPH control. The mutation results in an A/T nucleotide substitution.

Figure 6

Audiograms of individuals from American families 3 and 4 with hearing loss due to missense mutations in KCNQ4. A Audiogram of the individual carrying the p.E260K mutation measured at five years of age. B Audiogram of the individual carrying the p.D262V mutation measured at twelve years of age.

Figure 7

Pedigree of American family 5 with non-syndromic DFNA2 hearing loss due to a stop mutation in KCNQ4. Genotypes for nuceotide c.807 in the KCNQ4 gene and age (years) are shown for those individuals included in the genetic analysis. Open symbols unaffected; filled black symbols affected; diagonal line deceased.

Figure 8

Audiograms of representative affected family member III:2 at 23 and 30 years of age respectively from American family 5. High frequency hearing is more severely affected at both ages, although thresholds are significantly higher at the later age reflecting the progressive nature of the condition.

Figure 9

The novel causative stop mutation in the KCNQ4 gene in American family 5. The mutation is a G-to-A nucleotide alteration in exon 5 (c.807G→A) that results in introduction of a stop codon (p.W241X).

Figure 10

Analysis of the missense mutations in KCNQ4. A Multi-sequence alignment of KCNQ4 sequence that contributes to the 5^th transmembrane and P-loop domains. The glutamate and aspartate residues affected by the p.E260K and p.D262V mutations respectively are highly conserved (purple boxes). B Conseq analysis of the residues affected by the mutations showing that they are both predicted to be exposed and functionally important.