Introduction:
Hereditary hearing loss (HL) is one of the most common birth defects, with an approximate incidence of 3 per 1,000 newborns presenting bilateral sensorineural HL at the time of newborn hearing screening. So every year, about 400,000 deaf children are born (1). In developed countries, HL stems from both environmental and genetic etiological factors, with the genetic contribution comprising 50–60% of cases (2-3). In Vietnam, in 2014 the Hanoi Obstetrics and Gynecology Hospital screened 3.8331 newborns with hearing impairments in 688 (1.5%). This rate may actually be higher as there are more cases of hearing loss in adulthood. Vietnam has about 1 million children born each year with only 1.5%, more than 15,000 children will be deaf each year (4). Identifying the genetic basis of deafness provides important information for diagnosis, intervention and treatment of the disease. Non-syndromic hearing loss (NSHL) is extremely heterogeneous. To date, more than 200 genes and 300 genetic loci have been implicated in NSHL (4). The marked heterogeneity of genetic hearing loss can be explained by the complexity of the auditory system, which requires coordination of multiple processes involving the inner ear and nervous system. A defect in any part of this complex chain of events can lead to hearing impairment. For many decades, linkage analysis has been the most powerful and widely used strategy to identify the gene defects responsible for inherited disorders. However, this approach is time consuming and requires the availability of cohorts of homogeneous and informative large families, and a large proportion of NSHL remain genetically unexplained. These limitations, however, may be overcome by the next-generation sequencing (NGS) technologies.
NGS offers an unprecedented ability to identify rare variants and new causative genes. Several next generation sequencing platforms allow for a DNA-to-diagnosis protocol to identify the molecular basis of inherited non-syndromic hearing loss, including whole genome sequencing (WGS), whole exome sequencing (WES) and targeted deafness gene capture (4).
Materials and Methods
Upon diagnosis of HL, patients routinely undergo kidney and thyroid sonography, urinalysis, electrocardiogram, neurological examination, blood profile analysis, and serological examination for infectious disease, as well as ophthalmological examination and magnetic resonance imaging of the brain, inner ear, and temporal bones for the assessment of HL in conjunction with a syndrome. Clinical test results, age of onset, and age of enrollment are summarized in Supplementary (Table 1). Pure-tone audiometry and auditory brainstem response were used to assess degree and progression of HL. The following guideline was used to determine severity of HL: 0–15 dB: normal; 16-25: very mild; 26–40 dB: mild; 41–70 dB: moderate; 70–90 dB: severe; and >90 dB: profound (5).
A total of 80 hearing-impaired children from 76 Viet Nam families were recruited from the Otorhinolaryngology faculty and Biomedical and Genetics Department of the Hanoi Medical Hospital at the Hanoi Medical University, Hanoi, Viet Nam. All affected members in these groups were diagnosed as having hereditary NSHL by a complete hearing evaluation, general examination and medical history collection.
Deafness Gene Mutation Detection Microarray
Peripheral blood samples were obtained from available members of these families, and genomic DNA was extracted using a blood genomic DNA extraction kit (Qiagen, America) according to the manufacturer’s protocol. In the study group each 60 subjects (children and those parents) of the 20 families were pre-tested for nine hotspot mutations of 4 deafness genes with a Nine Deafness Gene Mutation Detection Microarray Kit (Capital Bio Corporation, Beijing, China), as previously described (6). The mutations included c.512insAACG, c.176-191del16, c.235delC and c.299-300delAT in the GJB2 gene; c.538C>T in the GJB3 gene; c.IVS7-2A>G and c.2168A>G in the SLC26A4 gene; and m.1555A>G and m.1494C>T in the MT-RNR1 gene.
Samples were divided in two and transferred into two 200 µl centrifuge tubes (tubes A and B). Primers A1 and B1 were naturally thawed at room temperature, and the amplification reagents A2 and B2 were shaken evenly. A1 (12.5 µl)+A2 (4.5 µl)+DNA (3 µl) was added into Tube A and B1 (12.5 µl)+B2 (4.5 µl)+DNA (3 µl) was added into Tube B1 (total volume=20 µl). One negative reference group was prepared using the same method. The reaction condition was as follows: 37°C for 10 min, 95°C for 15 min, 96°C for 1 min, 94°C for 30 s, 55°C for 30 s, 70°C for 45 s (32 cycles) and 60°C for 10 min. PCR products were left on ice for 3 min for hybridization. The hybridization instrument, kit and hybridization solution were preheated to 50°C. Samples were added into 200 µl centrifuge tube and 15 µl of hybridization solution was added. 10 µl into the tube and 2.5 µl into the amplification system A and B. 14.5 µl of solution were transferred to the chip and sealed. It was placed in the hybridization instrument for 60 min under 50°C and 5 r/min. Then, it was washed, dried and scanned. Deaf Test software was used to set up the QC (quality control probe), PC (positive probe), BC (blank control probe), NC (negative control probe) and W (wild type) and M (mutant type) probes for 9 detection sites. The specification of chip: (76.20 ± 0.50) mm × (25.40 ± 0.25) mm ×(1.00 ± 0.10) mm, scanning area: 22 mm × 72 mm, detection sensitivity: = 0.1 fluorescent molecules/µm2.
Next generation sequencing
To further search for the causative genes in these families, we performed targeted genomic capture and MPS. For cases in which novel variants were detected, segregation analysis was performed to assess 80 deafness children. A total of 100 ethnicity matched children were selected as controls to confirm the candidate mutations. This study was approved by the Ethical Committee of Hanoi Medical University for Human Studies. Targeted genomic capture and next-generation sequencing whole-exon regions of 18 deafness genes, namely GJB2, GJB3, SLC26A4, MT-RNR1, MT-CO1, MT-TL1, MT-TS1, MT-TH, DSPP, GPR98, DFNA5, TMC1, MYO7A, TECTA, DIABLO, COCH, MYO15A and PRPS1 (Table 1) were target-enriched using a Target Enrichment Kit (My Genostics Inc., Beijing, China) as previously described (7). A minimum of 3µg of DNA was used to generate indexed Illumina libraries according to the manufacturer’s protocol. The final library size was 300 to 400 bp, including the adapter sequences. The enrichment libraries were sequenced on an Illumina HiSeq 2000 sequencer to generate 100 bp paired-endreads. High-quality reads were identified by filtering out low-quality reads and adaptor sequences using Solexa QA package and Cutadapt program respectively. Variants were first selected if they appeared in the 1000 Genomes Project database with an MAF of >0.05, and then they were selected if they appeared in the 300 local Asian Genome database. The remaining variants were further processed according to the db SNP database. SNPs and indels were identified using SOAPsnp and GATK programs. Subsequently, the reads were realigned to the reference genome (NCBI37/hg19) using BWA software. Non-synonymous variants were evaluated by four algorithms, including PolyPhen, and Pmut, to determine pathogenicity (7).
Statistical analysis
The statistical analysis was performed using SPSS 17.0 (SPSS Inc., Chicago, USA). The intergroup difference infrequency was compared using the two-tailed chi-square test or Fisher’s exact probability test. A P-value less than 0.05 was considered statistically significant.
Results
HL and clinical summaries
A total of 80 subjects with severe hearing loss in Viet Nam were studied. Males accounted for 45%. The average age was 3,4 years. The degree of hearing loss was divided into 3 groups (=<70 (16.7%); 71–90 (28.5%); >90 (54.8%) (Fig.1) and the data – PTA ( pure tone average) was calculated as the mean of the plus thresholds at three frequencies of 500 Hz, 1000 Hz, and 2000 Hz.
 |
Fig.1: The rate children with different degrees of hearing loss in Viet Nam (dB: decibel) |
Table 1: 100 mutations on 18 genes in this study |
N |
Gene |
Mutation |
1 |
GJB2 |
c.235delC |
2 |
c.299-300delAT |
3 |
c.35delG |
4 |
c.176-191del16 |
5 |
c.167delT |
6 |
c.512insAACG |
7 |
c.456C>A |
8 |
c.456C>G |
9 |
c.427C>T |
10 |
c.416G>A |
11 |
c.257C>G |
12 |
c.253T>C |
13 |
c.109G>A |
14 |
c.99delT |
15 |
c.94C>T |
16 |
SCL26A4 |
IVS7-2A>G |
17 |
c.2168A>G |
18 |
c.1229C>T |
19 |
c.1147A>T |
20 |
c.1975G>C |
21 |
c.2027T>A |
22 |
c.2162C>T |
23 |
c.589G>A |
24 |
c.1226G>A |
25 |
c.281C>T |
26 |
IVS15+5G>A |
27 |
c.2086C>T |
28 |
c.745T>C |
29 |
c.1079C>T |
30 |
c.259G>T |
31 |
c.1343C>T |
32 |
c.1540C>T |
33 |
c.1919G>T |
34 |
c.2000T>C |
35 |
c.679G>C |
36 |
IVS14-2A>G |
37 |
c.919-18T>G |
38 |
c.920C>T |
39 |
c.109G>T |
40 |
c.1160C>T |
41 |
ct.1181_1183
delTCT |
42 |
SCL26A4 |
c.1318A>T |
43 |
c.1336C>T |
44 |
c.1555_1556 delAA |
45 |
c.1586T>G |
46 |
c.1594A>C |
47 |
c.1634T>C |
48 |
c.1673A>T |
49 |
c.1717G>T |
50 |
c.1746delG |
51 |
c.2054G>G |
52 |
c.2082delA |
53 |
c.2107C>G |
54 |
c.227C>T |
55 |
c.230A>T |
56 |
c.269C>T |
57 |
c.589G>A |
58 |
c.349delC |
59 |
c.387delC |
60 |
c.404A>G |
61 |
c.439A>G |
62 |
GJB3 |
c.697G>C |
63 |
c.812A>G |
64 |
IVS10-12T>A |
65 |
IVS13+9C>G |
66 |
IVS14+1G>A |
67 |
IVS14-1G>A |
68 |
IVS16-6G>A |
69 |
GJB3 |
c.538C>T |
70 |
c.574G>A |
71 |
c.423delATT |
72 |
c.497A>G |
73 |
c.421A>G |
74 |
MT-RNR1 |
m.1555A>G |
75 |
m.1494C>T |
76 |
m.827A>G |
77 |
m.961delTinsC |
78 |
MT-CO1 |
m.7444G>A |
79 |
MT-TL1 |
m.3243A>G |
80 |
MT-TS1 |
m.7445A>G |
81 |
m.7505T>C |
82 |
m.7511T>C |
83 |
MT-TH |
m.12201T>C |
84 |
DSPP |
c.52G>T |
85 |
GPR98 |
c.10088_10091 delTAAG |
86 |
DFNA5 |
IVS8+4A>G |
87 |
TMC1 |
c.150delT |
88 |
IVS15+5G>A |
89 |
MYO7A |
c.625G>A |
90 |
c.731G>C |
91 |
TECTA |
c.4525T>G |
92 |
DIABLO |
c.377C>T |
93 |
COCH |
c.1535T>C |
94 |
c.1625G>A |
95 |
MYO15A |
c.8183G>A |
96 |
c.8767C>T |
97 |
PRPS1 |
c.193G>A |
98 |
c.259A>G |
99 |
c.869T>C |
100 |
c.916G>A |
The carrier and mutation rates of deafness genes
In the study group each 60 proband of the 15 families were pre-tested for nine hotspot mutations of deafness genes with a Nine Deafness Gene Mutation Detection Microarray Kit. The analysis revealed that identify 6 cases with deafness mutations (account for 10%). As shown in Table 3, the carrier rate of the c.299-300delAT and c.235delC mutation in the GJB2 gene was 5.0%. Moreover, 2 children had pathogenic mutations of the SLC26A4 gene, or 3.3% of all 60 subjects. In addition, the carrier rate of the m.1555A>G mutation in the MT-RNR1 gene was 1.6% (Table 2).
Table 2: Mutation detection by microarray method |
| Sample |
2D |
7D, 10D |
34D |
21D, 58D |
Result |
|
|
|
|
Mutation |
GJB2 (299_300delC)
Heterozygous. |
GJB2 (235delC)
Heterozygous |
SLC26A4 (IVS7-2A>G)
Heterozygous |
MT-RNR1 (1555A>G)
Homozygous |
Among 80 children with hearing loss, 4 carriers of homozygous and 14 carriers of heterozygous mutation of deafness gene were detected by NGS method, and the detection rate was 22.5%. As for gene GJB2,10 cases of c.235delC (2 heterozygous), c.512insAACG (2 homozygous and 1 heterozygous) and c.299-300delAT (5 heterozygous) were detected. About gene SLC26A4, 1 case of IVS7-2A>G and 2 cases of c.2168A>G were detected. 2 cases of MT-RNR1 (m.827 A>G and m.961delTinsC); 1 case of MT-TH (m.12201T>C); 1 case of MT-TL1 (m.3243A>G), 1 case of TMC1 (c.1334G>A were detected - Table 3). No mutations were identified in the control group.
Table 3: The carrier rate of deafness genes in 80 children |
Gene |
Nucleotide chance |
Carrier number |
Carrier Rate(%) |
Homozygous |
Heterozygous |
GJB2 |
c.299-300delAT |
0 |
5 |
27,78 |
c.235delC |
0 |
2 |
11,11 |
c.512insAACG |
2 |
0 |
16,67 |
c.512insAACG |
0 |
1 |
5,56 |
SLC26A4 |
c.2168A>G |
0 |
2 |
11,11 |
IVS7-2A>G |
0 |
1 |
5,56 |
MT - RNR1 |
m.1555A > G |
2 |
0 |
11,11 |
TMC1 |
c.1334G>A |
0 |
1 |
5,56 |
MT-TL1 |
m.3243A>G |
0 |
1 |
5,56 |
MT-TH |
m.12201T>C |
0 |
1 |
5,56 |
Total |
18 |
100% |
Discussion
We ought to analyze mutation in pediatric population with severe hearing loss. For inclusion in the present study, subjects were limited to the criteria discussed above, including audiometry demonstrating > 70 dB hearing loss. In fact, the proportion of enrolled subjects with profound hearing loss (>90 dB) was 54.8%. In addition, the average age was only 3.4 years.
Our new findings revealed that the frequency the mutations in six from eighteen common deafness genes was 22.5% among the total subjects, which is in accordance with the frequencies in previous reports (8-10).
It is well known that mutations of the GJB2 gene, encoding the protein connexin 26, may affect potassium recycling in the inner ear, and mutations of the MT-RNR1 can cause a range of phenotypes from mild to profound sensorineural hearing loss (SNHL) (10). In addition, the SLC26A4 gene, encoding the pendredprotein, can cause prelingual or postlingual onset of sensorineural or mixed, fluctuating or progressive hearing loss (8-10). Therefore, the general level of the mutant frequency in the children with severe or profound SNHL could be interpreted by unfixed phenotypes of hearing loss in mutations of three genes.
Among these 100 sites in 18 genes, mutation frequencies vary across ethnicities. Furthermore, in a worldwide review, the most frequent causative genes in order of frequency are GJB2, SLC26A4, MYO15A, and OTOF; in Caucasians, the most common mutation is 35delG GJB2 (11). In our study of Viet Nam population, the carrier rates of GJB2, SLC26A4, MT-RNR1, TMC1, MT-TL1 and MT-TH gene mutations were 55.56%, 16.67%; 11.11%; 5.56%; 5.56% and 5.56%, respectively. Our study results for the children population of Viet Nam were different, likely because of the different genetic trends in the different. Sample size may also have affected these outcomes.
GJB2 gene mutations are the most common deafness susceptibility genes which already have been mapped and cloned. At present, more than 100 types of mutations have been found in the GJB2 gene (14). However, different populations differ in their variations in the GJB2 gene (12). In a children group in Viet Nam, 22.5% of those with deafness-related mutations had the c.512insAACG mutation of gene GJB2, compared to 3.75% in our study. The difference with other studies maybe due to the different genetic populations and the differences in sample size.
Our study was consistent with previous reports suggesting that SLC26A4 mutations account for 16.67% of inherited deafness cases (8,11-13). As expected, c.2168A>G was the most common SLC26A4 gene mutation. The detection rate of two mutations, c.IVS7-2A>G and c.2168A>G, in the subjects with the hearing loss was 5.56%, and 11.11%.
In this study was found that the MT-RNR1 m.1555A>G mutation accounted for 11.11% of all pathogenic mutations. Drug ototoxicity is an important factor in pre-lingual HL, in particular for those carrying the MT-RNR1 gene mutation at 1555A>G, which can increase the sensitivity of the cochlea to amino glucoside drugs. In the US, 10% of ototoxic-drug-related HL patients have the MT-RNR1 m. 1555A>G mutation, and the incidence of prelingual HL is ˜ 1/20 000–1/40 000 of patients with this mutation. In Spain, the MT-RNR1 1555A>G mutation is related to 15–20% of familial NSHL, with many of the older family members also having gene-related HL, even without the use of amino glucoside drugs (14). In Viet Nam, the incidence of drug-induced deafness is unknown.
The predicted structure of TMC1 is similar to that of the a-subunit of voltage-dependent K+ channels, which has six a-helical TM segments and intracellular N and C termini. It was predicted that TMC1 might be an ion channel or transporter which mediated K+ homeostasis in the inner ear. The first four TM domains of the K+ channel a-subunit act as voltage sensors for activation gating, whereas the intervening segment between TM5 and TM6 appears to confer channel selectivity. One novel conserved TMC1 sequence variant in this study c.1334G>A (p.Arg445His) lies within the central portion of hydrophobic TM segments (15).
The m.3243A>G mutation has been shown to lead to reduced levels of the tRNA Leu (UUR), decrease in aminoacylation, and absence of the normal modification with 5-taurinomethyl group at the wobble base (16,17). Mitochondrial disease caused by this mutation may result from the reduction of mtDNA-encoded proteins and oxidative phosphorylation activity in mitochondrial translation. The m.3243A>G mutation is usually present as heteroplasmic state.Its phenotype is highly variable, ranging from asymptomatic to mild or severe phenotype. Several clinical syndromes including hearing loss, MELAS, myoclonic epilepsy with ragged-red fibers, chronic progressive external ophthalmoplegia, and Leigh's syndrome may associate with m.3243A>G mutation. Patients with m.3243A>G mutation but without clinical symptoms are not uncommon (18). In our study, patient with the m.3243A>G mutation presented with a mean PTA = 106.67 dB HL. Patients with pathological mtDNA mutations often have a mixture of mutated and wild-type mtDNA molecules (heteroplasmy).
In affected members of a large 5-generation Han Chinese family with maternally inherited nonsyndromic adult-onset hearing loss identified a heteroplasmic 12201T-C transition in the MTTH gene, affecting the acceptor stem of tRNA-His (19). In this study, no mutation was found in 100 Viet Nam controls.
Application of targeted NGS in routine diagnostics
The great heterogeneity comprising NSHL undoubtedly contributes to molecular diagnostic challenges. In the pre-NGS era, the identification of damaging mutations was dependent on labor- and cost-intensive Sanger sequencing. Routine screening is typically initiated with GJB2 analysis because 30–40% of NSHL probands with European ancestry have mutations in this gene.(1) Unless additional clinical symptoms hint at specific genes (i.e., goiter suggesting SLC26A4 or auditory neuropathy suggesting OTOF), the vast majority of GJB2 mutation–negative probands remain without genetic diagnoses (20). In our study of Viet Nam population was found GJB2, SLC26A4, MTRNR1, TMC1, MT-TL1 and MT-TH gene mutations. This is the first study to use NGS in the diagnosis of hearing loss in Vietnam.
Massively parallel sequencing is a revolutionary technology that enables us to obtain large amounts of genomic sequence information in a rapid and low-cost manner (4). With targeted gene capture, the proportion of DNA fragments containing or near targeted regions is greatly increased. Because of its ability to enrich deafness genes, NGS can be used to identify causative mutations of hereditary hearing loss. The use of NGS has frequently resulted in the identification of disease genes within a limited number of patient samples (21,22).
The development and optimization of NGS gene panels expand the spectrum of disease-relevant genes simultaneously screened in affected individuals with the potential to translate into better case outcomes and support when rare pathogenic mutations are liable.
Conclusion
Although a major limitation of our study was the small sample size, we used conservative statistics to avoid overstating our findings. Recent studies have only begun discovering genetic complexities unknown before the advent of NGS technologies in Viet Nam. It is noteworthy that all 80 children diagnosed with a monogenic form of deafness exhibited additional pathogenic variants in other HL genes. It is tempting to speculate that these additional variants have a modifying phenotypic effect, explaining variability in age of onset and progression.
Using targeted genomic capture and MPS, we have successfully identified causative gene mutations in 80 hearing-impaired and 100 normal children from Viet Nam. The incidence of deafness mutations in hearing-loss group is 22.5%. Mutations of GJB2 cover the largest proportion (12.5%) among 18 genes investigated.
NGS can be a powerful tool in the detection of new deafness – causing mutations, both in previously known genes, as well as in genes not previously implied in HL. This technology helps overcome the serious drawbacks of linkage analysis, the most widely used method to search for genetic disease mutations in the genomic era. Indeed, since this technology entered the market, its use to identify causative genes and mutations in deaf individuals has grown tremendously. Targeted capture and MPS appears to be the ideal tool for this task as it limits the analysis to a manageable subset of the whole genome, thus reducing the cost, time and bioinformatics infrastructure necessary for the analysis of large - scale data.
Acknowledgements
The study was performed in the framework of the basic part of the Ministry of education and science of the Russian Federation state task on the theme: «The study of the genetic polymorphisms and microRNAs functional role in the genomes of humans and animals», project No. 6.6762.2017/BT.
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