Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Long-Term Cochlear Implant Outcomes in Children with GJB2 and SLC26A4 Mutations

  • Che-Ming Wu ,

    bobwu506@hotmail.com (CMW); chenchiwu@ntuh.gov.tw (CCW)

    Affiliation Department of Otolaryngology—Head and Neck Surgery, Chang-Gung Memorial Hospital, Linkou Branch, College of Medicine, Chang-Gung University, Taoyuan, Taiwan

  • Hui-Chen Ko,

    Affiliation Department of Otolaryngology—Head and Neck Surgery, Chang-Gung Memorial Hospital, Linkou Branch, College of Medicine, Chang-Gung University, Taoyuan, Taiwan

  • Yung-Ting Tsou,

    Affiliation Department of Otolaryngology—Head and Neck Surgery, Chang-Gung Memorial Hospital, Linkou Branch, College of Medicine, Chang-Gung University, Taoyuan, Taiwan

  • Yin-Hung Lin,

    Affiliations Department of Otolaryngology, National Taiwan University Hospital, Taipei, Taiwan, Graduate Institute of Medical Genomics and Proteomics, National Taiwan University College of Medicine, Taipei, Taiwan

  • Ju-Li Lin,

    Affiliation Division of Genetics and Endocrinology, Department of Pediatrics, Chang-Gung Memorial Hospital, Linkou Branch, College of Medicine, Chang-Gung University, Taoyuan, Taiwan

  • Chin-Kuo Chen,

    Affiliation Department of Otolaryngology—Head and Neck Surgery, Chang-Gung Memorial Hospital, Linkou Branch, College of Medicine, Chang-Gung University, Taoyuan, Taiwan

  • Pei-Lung Chen,

    Affiliation Graduate Institute of Medical Genomics and Proteomics, National Taiwan University College of Medicine, Taipei, Taiwan

  • Chen-Chi Wu

    bobwu506@hotmail.com (CMW); chenchiwu@ntuh.gov.tw (CCW)

    Affiliations Department of Otolaryngology, National Taiwan University Hospital, Taipei, Taiwan, Department of Medical Genetics, National Taiwan University Hospital, Taipei, Taiwan

Long-Term Cochlear Implant Outcomes in Children with GJB2 and SLC26A4 Mutations

  • Che-Ming Wu, 
  • Hui-Chen Ko, 
  • Yung-Ting Tsou, 
  • Yin-Hung Lin, 
  • Ju-Li Lin, 
  • Chin-Kuo Chen, 
  • Pei-Lung Chen, 
  • Chen-Chi Wu
PLOS
x

Abstract

Objectives

To investigate speech and language outcomes in children with cochlear implants (CIs) who had mutations in common deafness genes and to compare their performances with those without mutations.

Study Design

Prospective study.

Methods

Patients who received CIs before 18 years of age and had used CIs for more than 3 years were enrolled in this study. All patients underwent mutation screening of three common deafness genes: GJB2, SLC26A4 and the mitochondrial 12S rRNA gene. The outcomes with CIs were assessed at post-implant years 3 and 5 using the Categories of Auditory Performance (CAP) scale, Speech Intelligibility Rating (SIR) scale, speech perception tests and language skill tests.

Results

Forty-eight patients were found to have confirmative mutations in GJB2 or SLC26A4, and 123 without detected mutations were ascertained for comparison. Among children who received CIs before 3.5 years of age, patients with GJB2 or SLC26A4 mutations showed significantly higher CAP/SIR scores than those without mutations at post-implant year 3 (p = 0.001 for CAP; p = 0.004 for SIR) and year 5 (p = 0.035 for CAP; p = 0.038 for SIR). By contrast, among children who received CIs after age 3.5, no significant differences were noted in post-implant outcomes between patients with and without mutations (all p > 0.05).

Conclusion

GJB2 and SLC26A4 mutations are associated with good post-implant outcomes. However, their effects on CI outcomes may be modulated by the age at implantation: the association between mutations and CI outcomes is observed in young recipients who received CIs before age 3.5 years but not in older recipients.

Introduction

Congenital sensorineural hearing loss (SNHL) has an incidence of approximately 0.1% in live births [1]. At least 50% of these cases are hereditary, and approximately 70–80% of cases of genetic deafness are non-syndromic, where deafness is not associated with any other clinical features [2,3]. Mutations in three genes, including GJB2 (or CX26, Gene ID: 2706) [4], SLC26A4 (or PDS, Gene ID: 5172) [5] and the mitochondrial 12S rRNA gene (MTRNR1) [6], have been reported to be highly prevalent in SNHL patients across different populations. It has been estimated that approximately 30–50% of idiopathic SNHL cases are attributable to mutations in these three genes [7,8].

With the restoration of hearing via a cochlear implant (CI), auditory and oral performances in children with severe-to-profound SNHL have been significantly improved [9]. However, their post-implant outcomes are highly variable. In addition to factors such as age at implantation and duration of implant use [9,10], different genetic etiologies might have an impact on CI outcomes as well (see Table 1). Implanted children with GJB2 mutations were reported to score higher than those without GJB2 mutations on measures of auditory performance and speech production [11,12], word and sentence perception [13], reading comprehension [14,15], and expressive language [16]. A study showed that children with SLC26A4 mutations demonstrated better results of speech perception and production than those with an unknown etiology, although statistical significance was not reached [11]. In our previous studies, children with mutations in any of the three common deafness genes displayed better auditory performance after 3 years of CI use [17,18].

thumbnail
Table 1. Review of studies on language/speech outcomes in cochlear implanted patients with mutations in GJB2, SLC26A4 or the mitochondrial 12S rRNA gene.

https://doi.org/10.1371/journal.pone.0138575.t001

By contrast, certain studies revealed that genetic factors might not be a reliable predictor of CI outcomes [13,1922]. The discrepancies among these studies may be because different tests were administered to evaluate patients with different lengths of CI use (Table 1). Some studies only addressed the outcomes for the first 2 years after implantation [11,12,15,20,22], while others preformed assessments until postoperative year 3 [13,14,18,19]. None of these studies, however, has reported long-term follow-up results in patients with different types of genetic deafness. To clarify the contribution of genetic factors to the CI outcomes, we investigated the long-term speech and language performance in CI children with mutations in common deafness genes and compared their outcomes to CI children without mutations.

Materials and Methods

Participants

A total of 222 patients who received cochlear implantation at a tertiary referral center (Chang-Gung Memorial Hospital) were enrolled in this study. None of them received CIs bilaterally. All subjects were ethnically Han Chinese and had Mandarin Chinese as their native language. After the exclusion of 39 patients who were implanted after the age of 18 years or used the CIs for less than 3 years, speech/language evaluations were administered on 183 patients. All of these patients were implanted with Nucleus CI24R(CS) or Nucleus CI24RE(CA) Freedom, went to mainstream schools and received auditory-verbal rehabilitation after implantation. The study protocol and written informed consent form were approved by the Chang-Gung Memorial Hospital Ethics Committee for Human Studies. All written informed consent forms signed by the participants or the guardians of the underage participants involved in our study were obtained before beginning the testing procedures.

Genetic examination

All subjects underwent mutation screening for the three common deafness genes, namely GJB2, SLC26A4 and MTRNR1, using direct sequencing [18]. Mutation screening included both exons of GJB2, all of the 21 exons of SLC26A4, and the entire mitochondrial 12S rRNA gene. For patients who carried only one mutant allele in GJB2 or SLC26A4, their DNA samples were further analyzed using two different massively parallel sequencing (MPS) panels to screen for copy number variants or large insertions/deletions in GJB2 or SLC26A4, as well as causative mutations in other deafness genes. Patients with mono-allelic GJB2 mutations were subjected to an MPS panel which targeted the entire length (i.e. both the coding and non-coding regions) of GJB2 and the coding regions of 128 known deafness genes, including five other gap junction genes: GJA1, GJB1, GJB3, GJB4, and GJB6 [2325]. Patients with mono-allelic SLC26A4 mutations were subjected to another MPS panel targeting 13 genes which had been related to enlarged vestibular aqueduct, and this panel specifically encompassed the entire length of SLC26A4, including exons, introns, and untranslated regions. Only patients with confirmative genotypes in the three common deafness genes, i.e. those with two mutant GJB2 or SLC26A4 alleles and those with definite MTRNR1 mutations, were included for further analyses.

Evaluation of post-implant auditory, speech and language performances

Auditory performance and speech intelligibility measures.

The Categories of Auditory Performance (CAP) scale and Speech Intelligibility Rating (SIR) scale were rated by speech therapists preoperatively and at post-implant years 3 and 5. The CAP is a nonlinear hierarchical scale that assesses the auditory performance of deaf patients and consists of 8 categories (from 0 to 7; S1 Appendix) [26]. The SIR classifies the intelligibility of patients’ spontaneous speech into 5 categories (from 1 to 5; S1 Appendix) [27]. Higher ratings indicate better performances. The reliability of both scales has been confirmed [26,27].

Speech perception measures.

Three open-set speech perception tests were administered at post-implant years 3 and 5: an easy sentence test, a difficult sentence test and a phonetically balanced (PB) monosyllabic word test. The two sentence tests were developed according to the Central Institute for the Deaf (CID) Everyday Sentence test [28]. The easy sentence test consists of 15 sentences that include 1–7 key words frequently used in daily conversations, e.g., "book" (S2 Appendix). The difficult sentence test has 20 sentences, each with 1–10 key words with lower familiarity, e.g., "examine" (S3 Appendix). The PB word test contains 25 monosyllabic words (S4 Appendix) [29]. The subjects needed to verbally repeat the word/sentence spoken by the test conductor, who spoke each word/sentence with the mouth covered to prevent lip-reading. The subjects were scored based on the number of (key) words correctly repeated, which was converted to percentages for further analysis.

Language skill measures.

At post-implant year 5, the Revised Primary School Language Assessment [30] was used to assess receptive and expressive language abilities (see Wu et al. [31] for details). The tests were given orally to the subjects. Raw scores were transformed into T scores based on the age-matched normal-hearing normative sample provided by the test developer (mean = 50 ± 10) [30].

Statistical analysis

Statistical analyses were conducted using SPSS software (version 17.0; SPSS; SPSS, Inc., Chicago, IL, USA). Descriptive statistical analyses were applied on genotypes and mutant alleles using frequency measurements. The Mann-Whitney U test was utilized to make between-group comparisons of test results. The Kruskal-Wallis test was conducted to compare the test results of more than two groups. A p value of less than 0.05 was considered significant. For post hoc Mann-Whitney U tests, the Bonferroni correction was used to adjust the p values of multiple comparisons.

Results

Of the 183 CI recipients, four had mono-allelic GJB2 mutations, three had mono-allelic SLC26A4 mutations, and five had the m.961delT variant. These patients (n = 12) were excluded because of non-confirmative genotypes, leaving 171 cases to be analyzed. Forty-eight (26.2%) were found to have confirmative mutations in the common deafness genes (hereafter called "the mutation group," see Tables 2 and 3), including 25 cases with 2 mutated alleles in GJB2 (52.1% of the 48 implantees), 23 with 2 mutated alleles in SLC26A4 (47.9%), and 0 with mutations in the mitochondrial 12S rRNA gene (see Table 4). No mutations were detected in the common deafness genes in the remaining 123 patients ("the no-mutation group").

thumbnail
Table 2. Genotypes of the 48 children with mutations in common deafness genes.

https://doi.org/10.1371/journal.pone.0138575.t002

thumbnail
Table 3. Demographic information of 171 subjects with and without mutations in GJB2, SLC26A4 and the mitochondrial 12S rRNA gene.

https://doi.org/10.1371/journal.pone.0138575.t003

thumbnail
Table 4. Number of subjects with mutations in GJB2, SLC26A4 and the mitochondrial 12S rRNA gene.

https://doi.org/10.1371/journal.pone.0138575.t004

The age of 3.5 years was used as the cutoff point for early-late implantation, which was determined based on the literature [32,33]. Of note, as many as 74 (43%) of the 171 cases were classified as late-implantation. The average ages at detection of HL and implantation in the 171 patients were 1.7 y and 4.2 y, respectively (Table 3). A possible explanation for the late detection and implantation is that the coverage rate of newborn hearing screening in Taiwan had not increased to 90% until 2012 [34], resulting in delayed diagnosis in certain hearing-impaired children.

A total of 109 patients (31 with mutations, 78 without mutations) had used the CIs for more than 5 years and thus received evaluations at post-implant year 5.

Comparison between CI recipients with and without genetic mutations

No significant difference was found between the mutation group and the no-mutation group regarding their age at implantation (4.4 ± 2.4 years vs. 4.1 ± 2.8 years, p > 0.05) and duration of implant use (7.6 ± 3.4 years vs. 7.5 ± 3.4 years, p > 0.05). Their CAP scores at the pre-implant visit (U = 1691.5, p < 0.001), post-implant year 3 (U = 2062.5, p = 0.002) and post-implant year 5 (U = 623.0, p = 0.027) were significantly different, and so were their SIR scores at the three test time points (respectively: U = 2225.0, p = 0.013; U = 2099.0, p = 0.004; U = 620.0, p = 0.022; see Table 5).

thumbnail
Table 5. CAP and SIR scores in all subjects, subjects implanted before the age of 3.5 years and subjects implanted after 3.5 years.

https://doi.org/10.1371/journal.pone.0138575.t005

Among patients who received implantation before age 3.5 years, the mutation group had significantly higher CAP and SIR scores than the no-mutation group at the pre-implant visit (U = 564.5, p = 0.017 for CAP; U = 636.0, p = 0.046 for SIR), post-implant year 3 (U = 471.0, p = 0.001 for CAP; U = 499.5, p = 0.004 for SIR) and post-implant year 5 (U = 159.5, p = 0.035 for CAP; U = 160.5, p = 0.038 for SIR; Table 5). On the contrary, among patients implanted after the age of 3.5 years, significant differences between the mutation and no-mutation groups were noted only in the pre-implant CAP scores (U = 388.5, p = 0.012; Table 5).

On the three speech perception tests (i.e., easy sentence, difficult sentence and PB word) and the receptive and expressive language tests, patients with and those without mutations obtained similar scores without significant differences at the two post-implant test time points, regardless of their age at implantation (all p > 0.05; Table 6).

thumbnail
Table 6. Speech perception and language skill measures in all subjects, subjects implanted before the age of 3.5 years and subjects implanted after 3.5.

https://doi.org/10.1371/journal.pone.0138575.t006

Comparison between different genotypes

The performances in children specifically with GJB2 (n = 25) or SLC26A4 mutations (n = 23) were further compared to those without mutations. There was no significant difference in age at detection of hearing loss between the three groups (p > 0.05; Table 4), but their ages at implantation differed significantly (p = 0.010), with the SLC26A4 group being significantly later implanted than the other two groups (p = 0.003 and p = 0.005 for post-hoc comparisons with the GJB2 group and the no-mutation group, respectively, where the significance was reached when p < α/3 = 0.017 for multiple comparisons). The later implantation in the SLC26A4 group probably could be explained by the progressive or fluctuating hearing loss associated with SLC26A4 mutations. In contrast to patients with GJB2 mutations who usually demonstrate congenital severe to profound SNHL, patients with SLC26A4 mutations often start with milder SNHL at the time of diagnosis which does not progress to profound SNHL necessitating cochlear implantation until a later age.

For children implanted before the age of 3.5 years, there was a significant difference between children with GJB2 or SLC26A4 mutations and those without mutations in CAP scores at the pre-implant visit (p = 0.038), post-implant year 3 (p = 0.005) and post-implant year 5 (p = 0.012), as well as in SIR scores (p = 0.012) and easy sentence scores (p = 0.048) at post-implant year 3. Post hoc tests showed that patients with GJB2 mutations had significantly higher CAP scores than those without mutations at post-implant year 3 (p = 0.010; Table 7). Patients with SLC26A4 mutations performed significantly better than the no-mutation group did on the easy sentence perception test at post-implant year 3 (p = 0.016) and on the CAP scale at post-implant year 5 (p = 0.004). No significant differences were found between patients with GJB2 mutations and those with SLC26A4 mutations, regardless of the test type or the test time point (all p > 0.017). Except for the easy-sentence test, none of the other measures of speech perception and language skills showed significant differences between the three groups (all p > 0.017).

thumbnail
Table 7. CAP and SIR scores in subjects broken down by age at implantation (before and after 3.5 years) and genotypes (GJB2, SLC26A4 and no mutations).

https://doi.org/10.1371/journal.pone.0138575.t007

Regarding children who received CIs after 3.5 years, significant differences were noted only in pre-implant CAP and SIR scores (p = 0.009 and p = 0.039, respectively) between children with GJB2 mutations, children with SLC26A4 mutations and those without mutations. No significant differences could be found at post-implant years 3 and 5 between the three groups. As post hoc tests showed (see Table 7), patients with SLC26A4 mutations obtained significantly better pre-implant CAP scores than the GJB2 group (p = 0.015) and the no-mutation group (p = 0.004). The SLC26A4 group also demonstrated significantly better pre-implant SIR scores than the GJB2 one (p = 0.007). The three groups did not perform differently on any of the speech perception and language skill tests (all p > 0.017).

Discussion

Our results revealed that for children who received CIs before the age of 3.5 years, patients with mutations in common deafness genes, including GJB2 and SLC26A4, demonstrated significantly better long-term auditory performance and speech intelligibility at post-implant year 3 and 5 than those without mutations. By contrast, for children who received CIs after 3.5 years, no differences were observed in post-implant outcomes between patients with and without mutations.

Early-implanted patients with mutations demonstrated better post-implant outcomes than those without mutations, most likely because the pathogenic consequences of GJB2 and SLC26A4 mutations are confined to the cochlea, sparing the neural integrity of the auditory system that is crucial for the function of CIs [17,35]. Despite the fact that both groups were implanted before 3.5 years of age, patients with GJB2 or SLC26A4 mutations, benefitting from the intact auditory pathway, have a better chance of developing satisfactory outcomes after implantation than those with unknown etiologies, where the causes of deafness are greatly heterogeneous.

This neural integrity, however, did not seem to play a significant role in the postoperative outcomes when patients were implanted after the age of 3.5 years. No significant differences could be noted in the post-implant outcomes between later-implanted patients with and those without mutations. The only difference between the two groups lies in their pre-implant auditory performance (median CAP score 2.5 vs. 1, p = 0.012; see Table 5), which is most likely because more than half (n = 17) of the later-implanted patients in the mutation group had SLC26A4 mutations. Recessive mutations in SLC26A4 are responsible for non-syndromic enlarged vestibular aqueduct (EVA) [36] and Pendred syndrome [37], which are often associated clinically with progressive or fluctuating hearing loss [38]. As a consequence, patients with SLC26A4 mutations might acquire more hearing experiences before implantation than those with congenital hearing loss. The larger amount of pre-implant hearing experiences thus led to higher pre-implant CAP scores in the SLC26A4 group than in GJB2 group and no-mutation group, which in turn resulted in higher pre-implant CAP scores in the mutation group than in the no-mutation group. However, the effect of previous hearing experiences became less visible with an increased length of implant use. After 3 years of use, all patients implanted after the age of 3.5 years produced similar outcomes.

As far as we know, only three studies have correlated the CI outcomes to the SLC26A4 genotypes in the literature [11,17,18]. Consistent with the current findings, our previous studies [17,18] showed better results in patients with SLC26A4 mutations than those without genetic etiologies, while Yan et al. [11] did not find significant differences between the two groups. The discrepancy between studies probably results from different durations of follow-up periods, as Yan et al. [11] focused on short-term outcomes at post-implant years 1 and 2.

A previous study of ours showed that SIR scores in patients implanted before the age of 5 years did not plateau until 5 years of implant use [39], indicating that children who receive CI early need 5 years to develop mature speech skills after implantation. By documenting the long-term outcomes in a large CI cohort, the present study further revealed that neither patients with GJB2 mutations nor patients with SLC26A4 mutations performed differently from those without mutations on the SIR scale after 5 years of use (Table 7). Their performances on speech perception and language skills tests were also similar to those without mutations. This is in line with our previous study on EVA that patients with and without EVA obtained comparable outcomes after using CIs for more than 5 years [40]. Taken together, although the outcomes with CIs could be influenced by the etiologies of deafness, it is likely that the effects of the etiologies are eventually diluted after 5 years of implant use. High levels of performance (i.e., median CAP = 6, median SIR = 5 and mean speech perception scores > 70%) were reached at post-implant year 5, regardless of the etiologies.

The decreased effect of genetic mutations on CI outcomes after several years of implant use may again be associated with neural integrity. On the one hand, common deafness-related genes such as GJB2 and SLC26A4 have minimal influence on the integrity of spiral ganglion neurons, leading to the speedy restoration of hearing after cochlear implantation. On the other hand, cases with unknown etiologies are more likely to have degenerated spiral ganglion neurons, which could result in slower post-implant development. However, considering that children with and without mutations both received aural-verbal rehabilitation after implantation, it is still possible for the no-mutation group to develop their skills steadily and catch up with the mutation group after using CIs for some years. The gap between the mutation group and the no-mutation group thus becomes smaller with the increased length of use.

It seems that the correlation between genetic diagnosis and CI outcomes is greatly influenced by other factors, including age at implantation, duration of implant use, and types of outcome measurements. This may account for the conflicting results among previous studies in the literature (Table 1), as their observations were made on the basis of different study designs and settings. Therefore, these factors should be taken into consideration to avoid potential biases in the interpretation when the relationship between genetic diagnosis and CI outcomes is explored. In the current study, it appears that the contribution of common genetic mutations is modulated by age at implantation and duration of CI use. Genetic mutations have an impact on post-implant outcomes only when the patients received CIs early (i.e., before the age of 3.5 years), and the impact becomes weaker after 5 years of implant use.

Recently, massively parallel sequencing (MPS) has been proven to be a powerful tool for genetic examination in hearing loss [41]. Theoretically, mutations in different deafness genes lead to different pathologies and might result in varied CI outcomes. Using the MPS technology, it has been demonstrated that mutations in the TMPRSS3 gene were associated with poor CI outcome [35], whereas mutations in the MYO15A, TECTA, and ACTG1 genes also showed relatively good auditory performance after implantation [42]. Our recent study [23] added that mutations in the PCDH15 and DFNB59 genes were associated with poor CI performance, but children with these mutations might demonstrate clinical features indistinguishable from those of other typical pediatric CI candidates before operation. Accordingly, the inclusion of a comprehensive genetic examination into the pre-CI evaluation battery could be anticipated in the near future, as it provides critical information for determining appropriate rehabilitation programs and setting the expectations of physicians, audiologists, schools, and families.

Conclusion

GJB2 and SLC26A4 mutations were associated with good post-implant outcomes. However, their effect on CI outcomes was modulated by the age at implantation and the duration of implant use. Patients with GJB2 or SLC26A4 mutations showed better post-implant auditory performance and speech intelligibility than those without mutations only when implanted before age 3.5 years. The effect of genetic mutations became weaker with the increase in the length of implant use and was not observed in those who received CIs after the age of 3.5 years. These results provide insight into the contribution of genetic factors to the outcomes of CIs, and might be useful in steering preoperative counseling and appropriate assessments in CI candidates.

Supporting Information

S1 Appendix. Criteria of Categorical Auditory Performance (CAP) and Speech Intelligibility Rating (SIR) scales.

https://doi.org/10.1371/journal.pone.0138575.s001

(DOC)

S2 Appendix. Easy sentence list for the speech perception test (English translation).

https://doi.org/10.1371/journal.pone.0138575.s002

(DOC)

S3 Appendix. Difficult sentence list for the speech perception test (English translation).

https://doi.org/10.1371/journal.pone.0138575.s003

(DOC)

S4 Appendix. Phonetically-balanced monosyllabic word list for the speech perception test.

https://doi.org/10.1371/journal.pone.0138575.s004

(DOC)

Acknowledgments

The authors would like to thank all of the children and their parents who participated in the study.

Author Contributions

Conceived and designed the experiments: CMW HCK CCW. Performed the experiments: YHL JLL CCW. Analyzed the data: YTT YHL. Contributed reagents/materials/analysis tools: CMW HCK CKC PLC. Wrote the paper: CMW YTT. Revised the manuscript: CCW HCK JLL.

References

  1. 1. Morton CC, Nance WE. Newborn hearing screening—a silent revolution. N Engl J Med. 2006; 354:2151–2164. pmid:16707752
  2. 2. Smith RJ, Bale JF Jr, White KR. Sensorineural hearing loss in children. Lancet. 2005; 365:879–890. pmid:15752533
  3. 3. Nance WE. The genetics of deafness. Ment Retard Dev Disabil Res Rev. 2003; 9: 109–119. pmid:12784229
  4. 4. Chan DK, Chang KW. GJB2-associated hearing loss: systematic review of worldwide prevalence, genotype, and auditory phenotype. Laryngoscope. 2014; 124:E34–53. pmid:23900770
  5. 5. Albert S, Blons H, Jonard L, Feldmann D, Chauvin P, Loundon N, et al. SLC26A4 gene is frequently involved in nonsyndromic hearing impairment with enlarged vestibular aqueduct in Caucasian populations. Eur J Hum Genet. 2006; 14:773–779. pmid:16570074
  6. 6. Ealy M, Lynch KA, Meyer NC, Smith RJ. The prevalence of mitochondrial mutations associated with aminoglycoside-induced sensorineural hearing loss in an NICU population. Laryngoscope. 2011; 121:1184–1186. pmid:21495045
  7. 7. Hutchin T, Coy NN, Conlon H, Telford E, Bromelow K, Blaydon D, et al. Assessment of the genetic causes of recessive childhood non-syndromic deafness in the UK—implications for genetic testing. Clin Genet. 2005; 68:506–512. pmid:16283880
  8. 8. Hilgert N, Smith RJ, Van Camp G. Forty-six genes causing nonsyndromic hearing impairment: which ones should be analyzed in DNA diagnostics? Mutat Res. 2009; 681:189–196. pmid:18804553
  9. 9. Niparko JK, Tobey EA, Thal DJ, Eisenberg LS, Wang NY, Quittner AL, et al. Spoken language development in children following cochlear implantation. JAMA. 2010; 303:1498–1506. pmid:20407059
  10. 10. Geers A, Brenner C, Davidson L. Factors associated with development of speech perception skills in children implanted by age five. Ear Hear. 2003; 24:24S–35S. pmid:12612478
  11. 11. Yan YJ, Li Y, Yang T, Huang Q, Wu H. The effect of GJB2 and SLC26A4 gene mutations on rehabilitative outcomes in pediatric cochlear implant patients. Eur Arch Otorhinolaryngol. 2013; 270:2865–2870. pmid:23296490
  12. 12. Matsushiro N, Doi K, Fuse Y, Nagai K, Yamamoto K, Iwaki T, et al. Successful cochlear implantation in prelingual profound deafness resulting from the common 233delC mutation of the GJB2 gene in the Japanese. Laryngoscope. 2002; 112:255–261. pmid:11889380
  13. 13. Sinnathuray AR, Raut V, Awa A, Magee A, Toner JG. A review of cochlear implantation in mitochondrial sensorineural hearing loss. Otol Neurotol. 2003; 24:418–426. pmid:12806294
  14. 14. Green GE, Scott DA, McDonald JM, Teagle HF, Tomblin BJ, Spencer LJ, et al. Performance of cochlear implant recipients with GJB2-related deafness. Am J Med Genet. 2002; 109:167–170. pmid:11977173
  15. 15. Bauer PW, Geers AE, Brenner C, Moog JS, Smith RJ. The effect of GJB2 allele variants on performance after cochlear implantation. Laryngoscope. 2003; 113:2135–2140. pmid:14660916
  16. 16. Angeli SI, Suarez H, Lopez A, Balkany TJ, Liu XZ. Influence of DFNB1 status on expressive language in deaf children with cochlear implants. Otol Neurotol. 2011; 32:1437–1443. pmid:21956600
  17. 17. Wu CC, Lee YC, Chen PJ, Hsu CJ. Predominance of genetic diagnosis and imaging results as predictors in determining the speech perception performance outcome after cochlear implantation in children. Arch Pediatr Adolesc Med. 2008; 162:269–276. pmid:18316665
  18. 18. Wu CC, Liu TC, Wang SH, Hsu CJ, Wu CM. Genetic characteristics in children with cochlear implants and the corresponding auditory performance. Laryngoscope. 2011; 121:1287–1293. pmid:21557232
  19. 19. Cullen RD, Buchman CA, Brown CJ, Copeland BJ, Zdanski C, Pillsbury HC 3rd, et al. Cochlear implantation for children with GJB2-related deafness. Laryngoscope. 2004; 114:1415–1419. pmid:15280719
  20. 20. Davcheva-Chakar M, Sukarova-Stefanovska E, Ivanovska V, Lazarevska V, Filipche I, Zafirovska B. Speech Perception Outcomes after Cochlear Implantation in Children with GJB2/DFNB1 associated Deafness. Balkan Med J. 2014; 31:60–63. pmid:25207169
  21. 21. Yoshida H, Takahashi H, Kanda Y, Usami S. Long term speech perception after cochlear implant in pediatric patients with GJB2 mutations. Auris Nasus Larynx. 2013; 40:435–439. pmid:23477838
  22. 22. Karamert R, Bayazit YA, Altinyay S, Yılmaz A, Menevse A, Gokdogan O, et al. Association of GJB2 gene mutation with cochlear implant performance in genetic nonsyndromic hearing loss. Int J Pediatr Otorhinolaryngol. 2011; 75:1572–1575. pmid:21996152
  23. 23. Wu CC, Lin YH, Liu TC, Lin KN, Yang WS, Hsu CJ, et al. Identifying children with poor cochlear implantation outcomes using massively parallel sequencing. Medicine. 2015; 94:e1073. pmid:26166082
  24. 24. Lin YH, Wu CC, Hsu TY, Chiu WY, Hsu CJ, Chen PL. Identification of a novel GATA3 mutation in a deaf Taiwanese family by massively parallel sequencing. Mutat Res. 2015; 771:1–5. pmid:25771973
  25. 25. Wu CC, Lin YH, Lu YC, Chen PJ, Yang WS, Hsu CJ, et al. Application of massively parallel sequencing to genetic diagnosis in multiplex families with idiopathic sensorineural hearing impairment. PLoS One. 2013; 8:e57369. pmid:23451214
  26. 26. Archbold S, Lutman ME, Nikolopoulos T. Categories of auditory performance: inter-user reliability. Br J Audiol. 1998; 32:7–12. pmid:9643302
  27. 27. Allen C, Nikolopoulos TP, Dyar D, O‘Donoghue GM. Reliability of a rating scale for measuring speech intelligibility after pediatric cochlear implantation. Otol Neurotol. 2001; 22:631–633. pmid:11568670
  28. 28. Silverman SR, Hirsh IJ. Problems related to the use of speech in clinical audiometry. Ann Otol Rhinol Laryngol. 1955; 64:1234–1244. pmid:13283495
  29. 29. Wang LT, Su FM. Zhong kuo yu yin jun hen zi huei biao zhi bian zhi yian jiou (Development of standardized phonetically balanced word lists). J Taiwan Otolaryngol Head Neck Surg. 1979; 14.
  30. 30. Lin BG, Chi PH. The Assessment of School Language Disorders. Taipei, Taiwan: National Taiwan Normal University Press; 2007.
  31. 31. Wu CM, Chen YA, Chan KC, Lee LA, Hsu KH, Lin BG, et al. Long-term language levels and reading skills in mandarin-speaking prelingually deaf children with cochlear implants. Audiol Neurootol. 2011; 16:359–380. pmid:21196727
  32. 32. Sharma A, Dorman MF, Spahr AJ. A sensitive period for the development of the central auditory system in children with cochlear implants: implications for age of implantation. Ear Hear. 2002; 23:532–539. pmid:12476090
  33. 33. Archbold S, Harris M, O'Donoghue G, Nikolopoulos T, White A, Richmond HL. Reading abilities after cochlear implantation: the effect of age at implantation on outcomes at 5 and 7 years after implantation. Int J Pediatr Otorhinolaryngol. 2008; 72:1471–1478. pmid:18703236
  34. 34. Huang CM, Yang IY, Ma YC, Lin GS, Yang CC, Tsai HT, et al. The effectiveness of the promotion of newborn hearing screening in Taiwan. Int. J. Pediatr. Otorhinolaryngol. 2014; 78:14–18. pmid:24300945
  35. 35. Eppsteiner RW, Shearer AE, Hildebrand MS, Deluca AP, Ji H, Dunn CC, et al. Prediction of cochlear implant performance by genetic mutation: the spiral ganglion hypothesis. Hear Res. 2012; 292:51–58. pmid:22975204
  36. 36. Li XC, Everett LA, Lalwani AK, Desmukh D, Friedman TB, Green ED, et al. A mutation in PDS causes non-syndromic recessive deafness. Nat Genet. 1998; 18:215–217. pmid:9500541
  37. 37. Everett LA, Glaser B, Beck JC, Idol JR, Buchs A, Heyman M, et al. Pendred syndrome is caused by mutations in a putative sulphate transporter gene (PDS). Nat Genet. 1997; 17:411–422. pmid:9398842
  38. 38. Wu CC, Chen YS, Chen PJ, Hsu CJ. Common clinical features of children with enlarged vestibular aqueduct and Mondini dysplasia. Laryngoscope. 2005; 115:132–137. pmid:15630381
  39. 39. Fang HY, Ko HC, Wang NM, Fang TJ, Chao WC, Tsou YT, et al. Auditory performance and speech intelligibility of Mandarin-speaking children implanted before age 5. Int J Pediatr Otorhinolaryngol. 2014; 78:799–803. pmid:24630030
  40. 40. Ko HC, Liu TC, Lee LA, Chao WC, Tsou YT, Ng SH, et al. Timing of surgical intervention with cochlear implant in patients with large vestibular aqueduct syndrome. PLoS One. 2013; 8:e81568. pmid:24282608
  41. 41. Shearer AE, Black-Ziegelbein EA, Hildebrand MS, Eppsteiner RW, Ravi H, Joshi S, et al. Advancing genetic testing for deafness with genomic technology. J. Med. Genet. 2013;50:627–634. pmid:23804846
  42. 42. Miyagawa M, Nishio SY, Ikeda T, Fukushima K, Usami S. Massively parallel DNA sequencing successfully identifies new causative mutations in deafness genes in patients with cochlear implantation and EAS. PLoS One. 2013;8:e75793. pmid:24130743