Genetic Screening of a Chinese Cohort of Children with Hearing Loss using a Next-Generation Sequencing Panel

doi:10.21203/rs.3.rs-2095399/v1

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Research Article

Genetic Screening of a Chinese Cohort of Children with Hearing Loss using a Next-Generation Sequencing Panel

https://doi.org/10.21203/rs.3.rs-2095399/v1

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published 04 Jan, 2023

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Background At present, the hereditary hearing loss homepage, (https://hereditaryhearingloss.org/), includes 250 deafness genes and more than 500 genes that have been reported to cause deafness. With few exceptions, the region-specific distributions are unclear for many of the identified variants and genes.

Methods Here, we used a custom capture panel to perform targeted sequencing of 518 genes in a cohort of 879 deaf Chinese probands who lived in Yunnan. mutation sites of the parents were performed by high-throughput sequencing and validated by Sanger sequencing.

Results The ratio of male to female patients was close to 1:1 (441:438) and the age of onset was mainly under six. Most patients (68.9%) were diagnosed with moderate to severe deafness. Four hundred and twenty-nine patients had variants in a deafness gene, with a detection rate of 48.8%. Pathogenic variants were detected in 98 genes and a number of these were recurrent within the cohort. However, many of the variants were rarely observed in the cohort. In accordance with the American College of Medical Genetics and Genomics, pathogenic, likely pathogenic and variants of uncertain significance accounted for 34.3%, 19.3% and 46.4% of all detected variants, respectively. The most common genes included GJB2, SLC26A4, MYO15A, MYO7A, TMC1, CDH23, USH2A and WFS1, which contained variants in more than ten cases. The two genes with the highest mutation frequency were GJB2 and SLC26A4, which accounted for 28.5% (122/429) of positive patients. We showed that more than 60.3% of coding variants were rare and novel. Of the variants that we detected, 80.0% were in coding regions, 17.9% were in introns and 2.1% were copy number variants.

Conclusion The common mutation genes and loci detected in this study were different from those detected in other regions or ethnic groups, which suggested that genetic screening or testing programs for deafness should be formulated in accordance with the genetic characteristics of the region.

Hearing loss

Molecular diagnostics

Next-generation sequencing

Gene panels

Hereditary hearing loss (HL) is one of the most common sensory disorders, with an incidence of 1–2 cases per 1000 newborns [1]. In 2021, the World Health Organization reported that more than 1.5 billion people experience some decline in their hearing capacity during their life course and at least 430 million will require care [2]. Hereditary hearing loss is nonsyndromic in 70% of newborns. The remaining 30% present with the syndromic form and exhibit additional abnormalities [3]. Deafness is a disease with high genetic and clinical heterogeneity. Clinical diagnosis can determine the degree of deafness but cannot clarify the cause of the disease. The molecular etiology of most patients can be identified by a combination of genetic testing and clinical diagnosis [3; 4]. The introduction of next-generation sequencing (NGS) has resulted in great progress in the diagnostics of HL [5; 6]. As of July 2022, mutations in 258 different genes have been reported to cause HL (http://hereditaryhearingloss.org). Genetic factors account for more than 50% of cases, in which the majority exhibit autosomal recessive inheritance (75–80%). Twenty to twenty-five percent show autosomal dominant inheritance and 1.0%-1.5% show X-linked or mitochondrial inheritance [7].

To date, the genes involved and the spectrum of mutations are largely unknown in early HL patients from Yunnan. In this study, we presented the results of an NGS analysis of a large cohort of 879 patients with deafness. Using this large number of patients, we expected to reveal the genes and variants that cause HL in the Yunnan region.

Subjects

This study was approved by the Ethics Committee of Kunming Children's Hospital (Kunming, China). Informed consent was obtained from the parents of the patients, prior to sampling. The diagnosis of HL was established via standard audiometry, in a soundproofed room, in accordance with the current clinical standards. Hearing loss was classed as either congenital onset or prelingual onset and the severity was established as mild (between 25 and 40 dB), moderate (between 40 and 70 dB) or severe/profound (> 70 dB). Clinical evaluation included a thorough physical examination and otoscopy, in all cases. Additional evaluations, which included a high-resolution, thin-section computed tomography (CT) and magnetic resonance imaging (MRI) of the temporal bone, were performed when possible. We extracted DNA from peripheral blood leukocytes of the probands, in accordance with standard procedures.

Sequencing And Data Analysis

Genomic DNA was extracted from whole blood (3 ml) from the proband and parents. Samples were analyzed using a 518 gene panel, on the Illumina Next Generation Sequencing platform. The 518 gene panel was a probe capture panel that was comprised of non-syndromic deafness genes (such as GJB2 and GJB3), syndromic deafness genes (such as SLC26A4, FOXI1 and EDN3) and mitochondrial deafness genes (such as MT-TS1, MT-RNR1, MT-TL1, MT-TK and MT-TE). The library of sample DNA was loaded onto the NovaSeq 6000 (Illumina, CA, United States). Sequencing quality was controlled by the following parameters: the average coverage was ≥ 100, ≥ 20× target region was ≥ 98% and Q20 was ≥ 95%. Sequencing data was filtered and the quality was checked by Fastp software. Sequence alignment and splicing were performed by BWA, with hg19 as the reference genome. Variants were identified using GATK4 and annotated with ANNOVAR/ClinVar/HGMD/OMIM. The target variants were curated in accordance with the American College of Medical Genetics and Genomics (ACMG) Standards and Guidelines, using the following evidence: 1) The frequency in the normal population (gnomAD database); 2) computational prediction: mutations were predicted using Pubvar (https://www.pubvar.com/), with several prediction software packages, such as Polyphen, SIFT and MutationTaster; 3) literature reports: target variants were searched in HGMD, ClinVar and Pubmed. The target variants were validated by Sanger sequencing. The variants were interpreted in accordance with the ACMG guidelines [8] and patient phenotype.

Patients

We sequentially accrued 879 HL patients during the study period. There were no exclusion criteria. As shown in Table 1, the demographics of the patients were binned into five categories: Sex, onset, severity, family history and physical exam. There were 72 patients who did not provide clinical information. The ratio of male to female patients was close to 1:1 (441:438) and the largest group for the age of onset data was ‘under the age of six’. The most common characteristics included: young age (86.2% were < 18 years of age) and severe-to-profound HL (44.5%). Most patients had a normal physical exam (81.8%) and approximately half had no family history of HL (37.3%).

Table 1

Phenotypic characteristics of patients evaluated in this study
Characteristic	Number	%
Sex
Male	441	50.2
Female	438	49.8
Age when onset (years)
Age ༜ 6	406	46.2
Age 6–18	387	44.0
Age ༞ 18	86	9.8
Family history
Autosomal recessive	261	29.7
Autosomal dominant	160	18.2
X-linked	10	1.1
Ambiguous	5	0.6
No family history	328	37.3
Not provided	113	12.9
Severity
Mild-moderate	22	2.5
Severe-profound	391	44.5
Not provided	464	52.8
Physical exam
Normal	719	81.8
Any abnormality	73	8.3
Not provided	87	9.9

Table 2

The deafness gene detected in this cohort
NO.	Gene	Number of case	NO.	Gene	Number of case	NO.	Gene	Number of case
1	GJB2	71	34	TRRAP	3	67	GAB1	1
2	SLC26A4	51	35	ADGRV1	3	68	CREBBP	1
3	MYO15A	22	36	FGFR3	2	69	FOXC1	1
4	MYO7A	21	37	MT-RNR1	2	70	CLDN14	1
5	TMC1	13	38	GATA3	2	71	COL1A1	1
6	CDH23	14	39	SALL4	2	72	COL9A1	1
7	MITF	13	40	POU3F4	2	73	TRPV4	1
8	USH2A	13	41	CHD7	2	74	FLNB	1
9	WFS1	11	42	TSHZ1	2	75	COL2A1	1
10	COL11A2	10	43	MYO6	2	76	ER2	1
11	OTOF	10	44	COL4A6	2	77	LARS2	1
12	SOX10	10	45	USH1G	2	78	DSPP	1
13	PTPN11	8	46	DIAPH3	2	79	CLRN1	1
14	OTOG	6	47	EYA4	2	80	SH3TC2	1
15	TNC	6	48	DIAPH1	2	81	MARVELD2	1
16	EYA1	5	49	EDNRB	1	82	P2RX2	1
17	BDP1	5	50	PRPS1	1	83	SIX5	1
18	GJB3	5	51	ESRRB	1	84	CEACAM16	1
19	TECTA	5	52	ACTG1	1	85	TBL1Y	1
20	USH1C	4	53	GRXCR1	1	86	YAP1	1
21	PTPRQ	4	54	ACTB	1	87	CABP2	1
22	TRIOBP	4	55	TWIST1	1	88	CD164	1
23	MYO1A	4	56	PDE1C	1	89	GSDME	1
24	PCDH15	4	57	TMIE	1	90	MYH14	1
25	WHRN	4	58	ANKRD11	1	91	TCOF1	1
26	DMXL2	3	59	AIFM1	1	92	POLG	1
27	MYH9	3	60	TPRN	1	93	NLRP3	1
28	LHFPL5	3	61	PDZD7	1	94	REST	1
29	MCM2	3	62	FLNA	1	95	PAX3	1
30	TBC1D24	3	63	BCOR	1	96	KCNQ4	1
31	COL11A1	3	64	TNFRSF11A	1	97	COL4A5	1
32	LOXHD1	3	65	LRP2	1	98	CCDC50	1
33	SLC17A8	3	66	ERCC6	1

Molecular Findings Among Probands

As shown in Fig. 1, 429 out of the 879 (48.8%) patients had mutations (Supplemental table1) in known HL genes, which were classified as pathogenic (P), likely pathogenic (LP) or variants of uncertain significance (VUS), in accordance with ACMG. The basic and diagnostic information for each sample were shown in Fig. 2. The GJB2 and SLC26A4 genes were the most common deafness susceptibility genes and their mutations accounted for 28.5% (GJB2: 16.6% (71/429), SLC26A4: 11.9% (51/429) of mutation positive patients in our study. Three hundred and seven patients (81.8%) had others known deafness gene variants. The molecular etiology of the remaining 350 patients was not identified.

Using the pedigree analysis and NGS results, we observed autosomal dominant inheritance for 158 of the 429 deafness gene variants (158/429, 36.8%) and autosomal recessive inheritance for 259 variants (259/429, 56.4%). We observed X-linked inheritance in 10 cases (10/429, 2.3%) and mitochondrial gene mutation in two cases (2/429, 0.47%). In this cohort, sequence variants were identified in a total of 98 genes (Table 1). The genes that were identified in at least five patients included GJB2 (16.6%; 71/429), SLC26A4 (11.9%; 51/429), MYO15A (5.1%; 22/429), MYO7A (4.9%; 21/429), TMC1 (3.7%9%; 16/429), CDH23 (3.3%; 14/429), MITF (3.0%; 13/429), USH2A (3.0%; 13/429), WFS1 (2.6%; 11/429), COL11A2 (2.3%; 10/429), OTOF (2.3%; 10/429), SOX10 (2.3%; 10/429), PTPN11 (1.9%; 8/429), OTOG (1.4%; 6/429), TNC (1.4% 6/429), EYA1 (1.2%; 5/429), BDP1 (1.2%; 5/429), GJB3 (1.2%; 5/429) and TECTA (1.2%; 5/429).

Analysis of NGS data indicated that 429 patients had variants that could be classified as P, LP or VUS, based on ACMG guidelines. These accounted for 34.3%, 19.3% and 46.4% of variants, respectively. Of the 429 variants, 42.3% had previously been reported in the literature, whilst 57.7% were novel. Variants that led to protein truncation, such as frameshift mutations and nonsense mutations, were found at a higher rate and were usually classed as P or LP (Fig. 3). In addition, missense mutations or splice mutations were also detect in large numbers and rated as P or LP. It was noted that a small number of copy number variations (CNVs) were detected among the pathogenic variants. However, the proportion of mutation types in the VUS class was quite different from that of the P and LP classes. Missense mutations were the most common mutation type in the VUS class and most had not been included in the database or previously reported in the literature.

Using the mutation types found in more than five probands in this deafness cohort, it was observed that the proportion of missense mutations was the highest, followed by frameshift mutations and splicing mutations (Fig. 4). We also noted a wide variation across genes in the fractional contribution of missense versus loss of function (LOF) variants (frameshift and nonsense) (Fig. 4). Some genes had exclusively missense mutations (WFS1 and TECTA, Fig. 4).

The proportion of CNVs was 2.1% (Fig. 4). Six compound heterozygous CNVs were identified in SLC26A4 and two heterozygous CNVs were identified in EYA1 and MITF. One CNV was also detect in the BDP1 gene in one patient. One novel, homozygous CNV, which was a deletion that spanned exons 37–50 of the CDH23 gene, was identified in this cohort. Deleted exons did not amplify in confirmatory PCR reactions from proband samples.

The development of the Human Genome Project has promoted the combination of genetics and clinical medicine for diagnostics. The emergence of genetic screening and diagnosis for deafness is of great significance for the clarification of the cause of deafness and to prevent its occurrence [9; 10; 11]. Since the 1980s, with the development of technology, great progress has been made in the study of the genetic etiology of deafness. To date, more than 250 deafness genes have been cloned or identified (https://hereditaryhearingloss.org/) and it has been reported that more than 500 genes may contribute to the deafness phenotype. However, the diagnosis of hereditary deafness is extremely challenging for the following reasons: Firstly, hereditary deafness is a disease with very high genetic, clinical and ethnic heterogeneity. Secondly, hereditary deafness genes may have different categories of genetic variants, such as single nucleotide variations (SNVs), insertions and deletions (INDELs) and CNVs. Thirdly, most deafness gene variants do not occur repeatedly.

The introduction of NGS into the field of medical genetics has opened up new horizons for clinical diagnosis and scientific research and it has become a powerful auxiliary technology. Over the past decade, studies have attempted to enrich the known HL genes using capture-based or PCR-based targeted enrichment methods, followed by NGS, to screen for variants [12]. It can be concluded that the sensitivity and specificity of NGS for HL genetic detection is comparable to conventional Sanger sequencing, based on previous studies. Recently, Gema García-García et al [13] detected the variants responsible for the disease in 47 out of 118 families (40%), with a custom panel that included 59 genes associated with non-syndromic or syndromic HL. Seco et al [14] published a study that evaluated the diagnostic utility of NGS targeting using a gene panel of 120 HL-related genes. Using this strategy, they were able to identify a causative variant of HL in 67 out of 200 patients (33.5%). In this study, 518 deafness-related genes were identified in 879 patients. Deafness gene variants were detected in 429 children and the detection rate was 48.8%, which was slightly higher than the detection rates observed when using the smaller gene panels that contain the common deafnessrelated variants. Our study showed that the more deafness-related genes that are included, the higher the detection rate, which indicates that some populations have rare variants. These results are significant for the molecular diagnosis of deafness and further research.

Deafness is a disease with high genetic heterogeneity and one of the manifestations is that the high-frequency mutation genes are different in different populations. The GJB2 and MYO6 genes are the most commonly mutated HL genes in the global population. In Czech patients, the common HL genes are GJB2 and STRC [15; 16]. However, in the Chinese population, the common HL genes are GJB2 and SLC26A4 [9]. These studies show that molecular diagnostic analyses are highly population dependent, as the mutation spectrum for HL can differ greatly between populations. In this study, variants were detected in ten genes (GJB2, SLC26A4, MYO15A, MYO7A, TMC1, CDH23, MITF, USH2A, WFS1 and SOX10), which explained 55.7% of patients with deafness variants. With the exception of mutations in two relatively common genes, GJB2 (16.6%) and SLC26A4 (11.9%), most reported mutations were present in only a single or a small number of families. After excluding GJB2 and SLC26A4 mutations, we detected P, LP or VUS mutations in the known HL genes in 34.9% of the probands.

Our results demonstrated that NGS screening is a powerful technology for the identification of mutations in HL genes. From an epidemiological perspective, GJB2 and SLC26A4 mutations were involved in 28.44% of cases of deafness with a gene variant, while the remaining cases arose from rare gene mutations. For instance, CDH23, PCDH15 and MYO7A are large genes and it appears that these genes are more prone to mutations [17; 18]. The mutations in some genes did not appear repeatedly. For example, none of the mutations in the SOX10 and MITF genes were recurrent in our cohort. This may indicate that SOX10 and MITF are relatively more prone to de novo mutations or that they are highly conserved genes in which variation is rarely tolerated. Some genes, such as TNIE and TPRN, had less than 20 loci reported in the HGMD database. In these two genes, only one case of a rare gene mutation was detected in our cohort. In contrast, five patients in our study had BDP1 gene mutations, despite this gene having less than 20 mutation sites in the HGMG database. It is worth noting that, among these five individuals, four had the same mutation, which has not been reported in the literature. This suggested that this locus may be a hotspot in this population and patients with negative test results are likely to carry undetected mutations.

Mutations in introns may be relatively common in deafness patients. Among the 98 deafness-related genes detected in this study, SLC26A4 (62.7%, 32/51), MYO15A (63.6%, 14/22), OTOF (40.0%, 4/10) and PTPRQ (75%.0, 3/4) contained intronic variants. In previous studies, it has been confirmed that the intron of SLC26A4 is prone to mutations, especially at the c.919-2A > G site, which is one of the mutation hotspots in the Asian population [19; 20]. Our research also confirmed this. The variants detected in this study included common intronic mutations and also some rare or novel variants. This suggested that there are some unknown variant sites that require comprehensive testing, in order to find more genetic variants.

Copy number variants are a major contributor to hereditary HL, which shows the importance of the inclusion of CNV detection in a molecular diagnostic analysis for HL [21; 22]. Although there have been studies that show the importance of CNV analysis of NGS data, in the etiology of deafness, this analysis method is still being optimized for clinical use. The study by Shearer et al [23] used targeted enrichment and NGS with integrated CNV detection for HL in 686 patients. At least one CNV within a known deafness gene was observed in 15.2% (104) of patients. In our cohort, we used NGS to identify CNVs in four different genes (SLC26A4, MITF, EYA1 and CDH23), in nine patients (2.1%, 9/429). Several studies have shown that STRC is one of the deafness genes that is more prone to CNVs [23; 24; 25]. These results demonstrated that NGS can detect CNVs but more medical records and studies are needed to confirm whether all CNVs can be detected [26].

This study was not able to fully identify and explain the molecular etiology of all patients. Deafness-related gene variants were not detected in 20.8% of the 879 patients. These patients were likely to have undetected variants but more research is needed to confirm this speculation. It was noted that 43.2% of the unsolved patients had a pathogenic variant in a known HL gene. These patients may have had another mutation that had not been detected, or they may have been carriers who had developed deafness [27; 28]. Deafness can also occur through an oligogenic pattern of inheritance, were two or more pathogenic variants in different genes are detected in individuals with unsolved HL. Combinations of some variants have been reported to be the cause of oligogenesis, such as variants in SLC26A4 and KCNJ10, or SLC26A4 and FOXI1 [29]. However, we did not find any patients with the previously reported combinations of variants.

In this study, we applied NGS technology to (1) identify the molecular epidemiological etiology of HL in Chinese children and (2) discover novel mutations in causative genes. The results of the study provide a reference for the development of genetic screening or diagnosis of deafness, which is suitable for this region. In our analysis, we only considered coding regions, which is a limitation of this study. Pathogenic variants in noncoding regions or transcripts may also cause HL. In addition, due to the lack of family history, it was not clear whether the deafness gene variants carried by some patients contributed to the development of the disease.

Our data indicated that many rare variants are responsible for HL in this cohort and these mutations can be detected using NGS, which is approximately comparable in accuracy to Sanger sequencing. It is likely that there are undetected, rare variants that are specific to the Chinese population. Therefore, the main challenge for the future will be the establishment of population specific mutation-spectra, to achieve accurate, personalized, comprehensive molecular testing for HL.

Hereditary hearing loss

NGS

next-generation sequencing

MRI

magnetic resonance imaging

ACMG

American College of Medical Genetics and Genomics

Pathogenic

Likely pathogenic

VUS

Variants of uncertain significance

CNVs

Copy number variations

LOF

loss of function

SNVs

Nucleotide variations

INDELs

Insertions and deletions

Ethics approval and consent to participate

The presented study was performed in accordance with the Declaration of Helsinki and approved by The Ethics Committee of Kunming Children’s Hospital (Kunming, China, grant no. 2020-01-009-H01). Written informed consent was obtained from all participants.

Consent for publication

Not applicable

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Authors’ contributions

JM, XLM and KL designed the study, analyzed data and wrote the manuscript. RH, XYB, CM and LL designed the study, collected data and wrote the manuscript. XYB, LPZ and QDC performed the literature review and revised the manuscript. XL, GL and LPZ confirm the authenticity of all the raw data. TY, YQG and TSZ conceived the study, participated in its design and coordination. All authors have read and approved the final version of the manuscript.

Funding

This study was supported by grants from the National Natural Science Fund of China (grant no. 82060192), Reserve Talents for Young and Middle‐aged Academic and Technical Leaders in Yunnan Province (grant no. 2019HB102), Academician (Expert) Workstation in Yunnan Province (grant no. 202105AF150056), Yunnan Applied Basic Research-Joint Special Project of Kunming Medical University (grant no. 202001AY070001-170)

Acknowledgements

Not applicable

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Genetic Screening of a Chinese Cohort of Children with Hearing Loss using a Next-Generation Sequencing Panel

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