The Frequency of Common Deafness-Associated Variants Among 3,555,336 Newborns in China and 141,456 Individuals Across Seven Populations Worldwide : Ear and Hearing

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Research Article

The Frequency of Common Deafness-Associated Variants Among 3,555,336 Newborns in China and 141,456 Individuals Across Seven Populations Worldwide

Zhang, Jiao1,2,3; Wang, Hongyang1,2,3; Yan, Chengbin4; Guan, Jing1,2,3; Yin, Linwei5; Lan, Lan1,2,3; Li, Jin1,2,3; Zhao, Lijian5; Wang, Qiuju1,2,3

Author Information
Ear and Hearing 44(1):p 232-241, January/February 2023. | DOI: 10.1097/AUD.0000000000001274

Abstract

INTRODUCTION

Hearing loss (HL) is the most common sensory defect, affecting 1.33‰–1.86‰ of newborns worldwide, and more than 50% of cases have genetic etiologies, with lifelong impacts that may be ameliorated by early detection and intervention (Fortnum, Summerfield, Marshall, Davis, & Bamford 2001; Morton & Nance 2006). Newborn hearing screening has been widely performed worldwide and serves as a primary approach to detecting HL in newborns and triggering early intervention (Patel & Feldman 2011; Korver et al. 2017). However, hearing screening is unable to detect newborns with mild HL, delayed-onset, progressive hearing impairment, and drug-induced HL (Norris et al. 2006; Dedhia et al. 2013). Incorporating genetic screening can improve the effectiveness of newborn hearing screening programs (Q. J. Wang et al. 2007,2011; Q. Wang et al. 2019).

An important question in this field is what percentage of individuals in the general population carry a deafness-associated variant in common genes in different ethnic populations. This information is highly important for genetic screening and genetic counseling tailored to different ethnic backgrounds. However, few studies have been performed analyzing deafness-associated variants frequencies in general populations from different ethnic groups.

Here, we analyzed common deafness-associated variants frequencies in 3,555,336 newborns in the Chinese Newborn Concurrent Hearing and Genetic Screening cohort (CN cohort). The availability of public datasets has enabled us to identify variant frequencies across large populations, of which the Genome Aggregation Database (gnomAD; http://gnomad.broadinstitute.org) (Karczewski et al. 2021) is the most well known. Thus, we also analyzed the variant frequency in 141,456 individuals across seven populations worldwide based on gnomAD for the above variants. Comparison of this genetic information provided insights into the population-specific features of deafness-associated variants. These data can serve as a powerful resource for otolaryngologists and clinical geneticists to inform population-adjusted genetic screening programs.

MATERIALS AND METHODS

Study Design

This study used newborn concurrent hearing and genetic screening program in China. From January 2007 to September 2020, the population-based cohort study was conducted in 32 provinces nationwide in China. All of the recruited infants received both newborn hearing screening and genetic screening. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies. Parental informed consent was obtained for each infant to have the newborn hearing and genetic screening. The study was approved by the Research Ethics Committee of the Chinese PLA General Hospital and BGI.

CN Cohort Population Data

Newborn concurrent hearing and genetic screening has been practiced in China since 2007, and the CN cohort has been established since then. Now a total of 3,555,336 neonates in 32 provinces nationwide in China have undergone the screening of 20 common variants (c.35delG, c.167delT, c.l76_197dell6, c.235de1C, and c.299-300delAT of GJB2, c.28lC>T, c.589G>A, c.919-2A>G, c.l174A>T, c.l226G>A, c.1229C>T, c.1707 + 5G>A, c.1975G>C, c.2027T>A, c.2162C>T, and c.2l68A>G of SLC26A4, c.538C>T, and c.547G>A of GJB3, and m.1555A>G and m.1494C>T of MT-RNR1), which were the most common genetic causes of HL in the Chinese population as previously validated and reported(J. Zhang et al. 2013; Peng et al. 2016; Q. Wang et al. 2019; Guo et al. 2020). We analyzed the genetic screening data of 3,555,336 newborns in the CN cohort.

GnomAD Population Data

Genetic data of the earlier 20 variants were extracted from whole-exome and whole-genome sequencing data from the gnomAD. The gnomAD v2.1.1. contains genetic data variants from 141,456 individuals (125,748 exome sequences and 15,708 whole-genome sequences), including 12,487 African/African American (AFR), 17,720 Latino/Admixed American (AMR), 5185 Ashkenazi Jewish (ASJ), 9977 East Asian (EAS), 12,562 Finnish (FIN), 64,603 Non-Finnish European (NFE), 15,308 South Asian (SAS), and 3614 with unclear or other ethnicity.

Variant Frequency Analysis

We analyzed the following values for CN cohort and each subpopulation in gnomAD: allele count (representing the number of detected alleles in a given subpopulation), allele number (total number of genotyped alleles at the genomic position of the variant considered), heterozygote count (total number of heterozygous individuals for that specific allele), and homozygote count (total number of homozygous individuals for that specific allele). Based on these values, we calculated, the following parameters: allele frequency, carrier frequency, and compared the variant frequencies among different populations.

Statistical Analysis

Data were analyzed using GraphPad Prism (version 8.3.0, GraphPad Software) and R (version 3.6.3, R Foundation for Statistical Computing). Counts and percentages were calculated for categorical variables. The variant frequencies were compared across groups stratified by ethnic backgrounds using Chi-squared tests, with a Bonferroni correction or Fisher’s exact test when appropriate. A p value of less than 0.05 in two-tailed tests was regarded as statistically significant.

RESULTS

Frequency of Deafness-associated Variants in 3,555,336 Newborns in CN Cohort

Genetic screening data of the 20 deafness-associated variants in 3,555,336 Chinese neonates in CN cohort are shown in Table 1 and Figures 1–2. A total of 5.12% (181,962/3,555,336) of infants were identified with at least one of the screened variants. For the GJB2 gene, 2.53% (89,883/3,555,336) of newborns harbored at least one screened variant. The most frequent variant was GJB2 c.235delC, with an allele frequency of 0.99% (1,209/7,110,672). Another prevalent variant, c.299_300delAT, was the second most common variant in GJB2. A total of 2.05% (72,821/3,555,336) of infants harbored at least one screened variant in SLC26A4. The c.919-2A>G variant was most prevalent in SLC26A4, with an allele frequency of 0.67% (47,402/7,110,672).

TABLE 1. - Spectrum and frequencies of 20 common deafness-associated variants among 3,555,336 Chinese newborns.
Genes Nucleotide Change Protein Change Variant Type Het Hom Allele Count AF(%)
(Chinese) AF (%)
(East Asians) x2 value p
GJB2 c.35delG p.Gly12ValfsTer2 Frameshift 367 1 369 0.005 0.000 1.035 0.632
GJB2 c.167delT p.Leu56ArgfsTer26 Frameshift 4 0 4 0.000 0.000 0.011 1.000
GJB2 c.176_191del16 p.Gly59AlafsTer18 Frameshift 4009 6 4021 0.057 0.016 5.266 0.022
GJB2 c.235delC p.Leu79CysfsTer3 Frameshift 67,959 1209 70,377 0.990 0.651 23.253 0.000
GJB2 c.299_300del p.His100ArgfsTer14 Frameshift 17,047 68 17,183 0.242 0.090 18.956 0.000
GJB3 c.538C>T p.Arg180Ter Stop gained 9743 16 9775 0.137 0.110 1.074 0.300
GJB3 c.547G>A p.Glu183Lys Missense 3514 0 3514 0.049 0.050 0.002 0.964
SLC26A4 c.281C>T p.Thr94Ile Missense 903 1 905 0.013 0.005 0.767 0.736
SLC26A4 c.589G>A p.Gly197Arg Missense 1108 5 1118 0.016 0.005 1.237 0.382
SLC26A4 c.919-2A>G / Splice acceptor 46,114 644 47,402 0.667 0.506 7.720 0.005
SLC26A4 c.1174A>T p.Asn392Tyr Missense 2566 10 2586 0.036 0.005 4.837 0.028
SLC26A4 c.1226G>A p.Arg409His Missense 2302 2 2306 0.032 0.000 6.469 0.011
SLC26A4 c.1229C>T p.Thr410Arg Missense 4279 13 4305 0.061 0.000 11.138 0.001
SLC26A4 c.1707 + 5G>A / Splice region 1403 1 1405 0.020 0.011 0.723 0.596
SLC26A4 c.1975G>C p.Val659Leu Missense 3878 3 3884 0.055 0.020 4.360 0.037
SLC26A4 c.2027T>A p.Leu676Gln Missense 1730 1 1732 0.024 N/A N/A N/A
SLC26A4 c.2162C>T p.Thr721Met Missense 320 0 320 0.005 0.000 0.828 1.000
SLC26A4 c.2168A>G p.His723Arg Missense 8418 24 8466 0.119 0.160 2.854 0.091
MTRNR1 m.1494C>T / Non coding transcript exon 53 489 542 0.015 0.000 0.226 1.000
MTRNR1 m.1555A>G / Non coding transcript exon 1576 6928 8504 0.239 0.270 0.059 0.785
The RefSeq IDs of the above genes are NM_004004.5, NM_024009.2, NM_000441.1, and NC_012920.1, respectively.
AF indicates allele frequency; AF (Chinese), allele frequency in the Chinese newborn population; AF (East Asians), allele frequency in the East Asians from the gnomAD (https://gnomad.broadinstitute.org/); Het, heterozygote number for GJB2, GJB3 and SLC26A4, and heteroplasmic number for MTRNR1; Hom, homozygote number for GJB2, GJB3 and SLC26A4, and homoplasmic number for MTRNR1.

F1
Fig. 1.:
Distribution of the spectrum and carrier frequencies of the 20 common deafness-associated variants among 3,555,336 newborns. Genes are shown clockwise in order of decreasing carrier frequency. For the variants in the same gene, the color gradient from dark to light indicates decreasing carrier frequency. The red series denote the carrier frequencies of GJB2 variants, the blue series indicate the carrier frequencies of SLC26A4 variants, the green series denote the carrier frequencies of GJB3 variants, and the yellow series indicate the carrier frequencies of MTRNR1 variants.
F2
Fig. 2.:
Distribution of the spectrum and allele frequencies of the 20 common deafness-associated variants among 3,555,336 newborns. Genes are shown clockwise in order of decreasing allele frequency. For the variants in the same gene, the color gradient from dark to light indicates decreasing allele frequencies. The red series denote the allele frequencies of GJB2 variants, the blue series indicate the allele frequencies of SLC26A4 variants, the green series denote the allele frequencies of GJB3 variants, and the yellow series indicate the allele frequencies of MTRNR1 variants.

Frequency of Deafness-associated Variants in 141,456 Individuals in gnomAD

Frequency data of the common deafness-associated variants in 141,456 individuals in gnomAD are shown in Table 2. In regards to the general population, we analyzed the allele frequencies of all variants in this study and their allele frequencies in the seven assigned populations in gnomAD when data were available. Of the twenty deafness-associated variants, 19 were present in gnomAD (except SLC26A4 c.2027T>A), enabling evaluation of the allele frequencies of these variants in the general population (Figure 3) (Supplemental Digital Content 1, https://links.lww.com/EANDH/B51). The most prevalent variant was GJB2 c.35delC with an allele frequency of 0.62% in the whole gnomAD population. The variant of c.919-2A>G in SLC26A4 was also prevalent with allele frequency of 0.036%.

TABLE 2. - Comparison of allele frequency (%) of deafness-causing variants among countries in East Asia from gnomAD.
Variant Chinese (This Study) Japanese Korean x2 value p
GJB2 c.35delG 0.005 0 0 3.199 1.000
GJB2 c.167delT 0.000 0 0 11.841 1.000
GJB2 c.176_191del16 0.057 0 0.052 0.807 1.000
GJB2 c.235delC 0.990 0.658 0.602 6.014 0.049
GJB2 c.299_300delAT 0.242 0 0.052 6.806 0.030
GJB3 c.538C>T 0.137 0 0.079 0.786 0.600
GJB3 c.547G>A 0.049 0 0 2.204 0.334
SLC26A4 c.281C>T 0.013 0 0 2.003 1.000
SLC26A4 c.589G>A 0.016 0 0.026 2.849 0.464
SLC26A4 c.919-2A>G 0.667 0 0.184 14.435 0.001
SLC26A4 c.1174A>T 0.036 0 0 1.778 0.652
SLC26A4 c.1226G>A 0.032 0 0 1.694 0.662
SLC26A4 c.1229C>T 0.061 0 0 2.675 0.262
SLC26A4 c.1707 + 5G>A 0.020 0 0 1.678 1.000
SLC26A4 c.1975G>C 0.055 0 0 2.411 0.351
SLC26A4 c.2027T>A 0.024 N/A N/A N/A N/A
SLC26A4 c.2162C>T 0.005 0 0 3.431 1.000
SLC26A4 c.2168A>G 0.119 0.658 0.446 24.944 0.000
MTRNR1 m.1494C>T 0.015 N/A N/A N/A N/A
MTRNR1 m.1555A>G 0.239 N/A N/A N/A N/A
The gnomAD browser is available at: https://gnomad.broadinstitute.org/ (as accessed April 1, 2021).
The above populations are listed in alphabetically order.
N/A, not available.

F3
Fig. 3.:
Venn diagram of the distribution of 20 variants related to hearing loss in diverse populations. The diagrams show the population-specific variants found in East Asian, South Asian, Ashkenazi Jewish, European (non-Finish), and Latino/Admixed American populations, as well as the shared variants in two or more groups in the intersections of subsets. Variants are shown based on data from the Genome Aggregation Database (gnomAD) and the present study. The minimal allele frequency cutoff was 0.0001, as AF<0.0001 was defined as extremely rare. GJB2 variants are in red, SLC26A4 variants are in blue, GJB3 variants are in green, and MTRNR1 variants are in yellow.

Comparison of Allele Frequency in Different Populations

The most prevalent variant was GJB2 c.235delC with an allele frequency of 0.99% in the Chinese newborn population. Its frequency varied significantly among different populations, and the highest prevalence was found in East Asia (allele frequency, 0.65%), while it was extremely rare and carried only by a few individuals in other populations, with significant differences (x2 = 1622.766, p = 0.001). Hence, GJB2 c.235delC is referred to as an East-Asia-enriched variant. Furthermore, c.299_300delAT and c.176_191del16 were the second and third most prevalent variants of GJB2 in Chinese newborns (allele frequency, 0.24% and 0.06%, respectively), which were enriched in gnomAD among East Asians. Neither of the two variants were found among other populations in gnomAD (x2 = 81.821, p = 0.001 for c.299_300delAT and x2 = 13.654, p = 0.001 for c.176_191del16). Hence, they are referred to as East-Asia-enriched variants. GJB2 c.35delG is relatively rare in the Chinese population, with an allele frequency of only 0.01%. In contrast, it was observed to be more enriched in other ethnic groups. Most were found in NFEs (0.96%) but also in additional groups such as Finnish Europeans (0.84%), the Latino population (0.48%), Ashkenazi Jewish (0.34%), the African population (0.10%), and South Asians (0.08%), with significant differences (x2 = 660.703, p = 0.001). Thus, these can be referred to as European/American-enriched variants. It was noteworthy that GJB2 c.167delT was extremely rare in the Chinese population, while it was most common in the Ashkenazi Jewish group, with an allele frequency of 1.63%, followed by the Latino population (0.04%) and non-Finnish Europeans (0.03%). The statistical difference was significant (x2=3239.269, p = 0.001), so it can be referred to as Ashkenazi Jewish-enriched. Moreover, it has not been reported among other populations in gnomAD thus far (Tables 1 to 5 in Supplemental Digital Content 2, https://links.lww.com/EANDH/B52).

SLC26A4 c.919-2A>G was the second most common variant in the Chinese newborn group, with an allele frequency of 0.67%. It was found in East Asian and NFE populations with allele frequencies of 0.51% and 0.00%, respectively, while it was never reported in the other population groups in gnomAD with a significant difference among the seven groups (x2= 1264.089, p = 0.001). Thus, it can be referred to as East Asia-enriched. SLC26A4 c.1226G>A and c.2162C>T were also found in additional groups, but the difference in allele frequency for each variant was significant among groups. Thus, it can also be referred to as East Asia-enriched. Furthermore, c.2168A>G, c.1975G>C, and c.1707 + 5G>A in SLC26A4 were present uniquely in the East Asian population, and none of them were found in additional ethic groups in gnomAD, with significant differences (East Asia-enriched). The allele frequencies of SLC26A4 c.1229C>T, c.1174A>T, c.589G>A, and c.281C>T in the seven assigned populations were not significantly different (P > 0.05) (Tables 6–5 in Supplemental Digital Content, https://links.lww.com/EANDH/B52). Moreover, c.538C>T and c.547G>A in GJB3 were also present in several populations with significant differences (p = 0.001) in allele frequencies among diverse populations (Tables 16–17 in Supplemental Digital Content 2, https://links.lww.com/EANDH/B52). Notably, MT-RNR1 m.1555A>G and m.1494C>T were also found in additional groups, while the allele frequencies had no statistics difference (p > 0.05) among diverse populations (Tables 18–19 in Supplemental Digital Content, https://links.lww.com/EANDH/B52).

We also analyzed the variant allele frequencies in the subpopulations of the East Asia group, including the Japanese and Korean populations from gnomAD (Table 2) (Figure 1, Supplemental Digital Contents 1 https://links.lww.com/EANDH/B51), and then we compared them with our result from the Chinese newborn population. We finally found that the allele frequencies of most of the variants were not significantly different (P > 0.05) among the earlier three groups (Tables 20–36 in Supplemental Digital Content, https://links.lww.com/EANDH/B52).

DISCUSSION

In the present study, we analyzed the newborn genetic screening data for 3,555,336 newborns in CN cohort, which covering 94.12% (32/34) of provincial districts nationwide in China and identified that 5.12% of the infants harbored at least one of the screened variants. We provided a landscape of the variant frequency of the four most common deafness-associated genes in Chinese newborns, which was very distinct from other ethnic populations. Moreover, we demonstrated the population-specific features of deafness-associated variants in diverse populations and showed population-specific hotspot variants in certain ethnic groups: nine East Asia-enriched variants, one Ashkenazi Jewish-enriched variant, and one European/American-enriched variant.

The Chinese Newborn Concurrent Hearing and Genetic Screening cohort (CN cohort) was established since 2007, including genetic data of common deafness-associated variants from 3,555,336 newborns. These data can serve as a powerful resource for newborn genetic screening for HL, especially for Chinese. The Genome Aggregation Database (gnomAD) is the largest publicly-available human population dataset with 141,456 individuals, which spans six global and eight subcontinental populations, making population-level genetic data available for wider scientific research across diverse population groups.

The variant frequencies of the common deafness-associated variants in Chinese newborns were distinct. We found that mutations of GJB2 were the most common, with a total carrier rate of 2.53%. In addition, the most frequent variant was GJB2 c.235delC, and its frequency was extraordinarily high compared with those of other variants detected in this study, with an allele frequency of 0.99%. When compared with other Asian populations, this frequency was similar to those found among the general populations in the Korea (0.500%–0.744%) (Park et al. 2000,2003; Bae et al. 2008; Han et al. 2008; Sagong et al. 2013) and Japan (0.426%–0.786%) (Kudo et al. 2000; Tsukada et al. 2010; Taniguchi et al. 2015; Maeda et al. 2020) and previously studied Chinese populations (0.638%–1.229%) (Table 3) (Wu et al. 2011; Zhang et al. 2012; Chen et al. 2015; Peng et al. 2016; Wu et al. 2017; Hao et al. 2018; He et al. 2018; Dai et al. 2019; Zou et al. 2019; Cao et al. 2020,2022; Cai et al. 2021). GJB2 encodes the gap junction protein connexin 26 (Cx26), which is expressed in the nonsensory cells of the cochlea. The mutations in GJB2 presented in this study can cause early termination of translation and result in protein truncation, which ultimately impedes the flow of potassium from the hair cells in the cochlea. This results in a buildup of excess potassium in the organ of Corti, which in turn leads to sensorineural HL (Kelsell et al. 1997; Denoyelle et al. 1999; Snoeckx et al. 2005).

TABLE 3. - Overview of allele frequency (%) of deafness-causing variants in general populations among countries in East Asia in published literature.
Populations References Genes Screened (Spots Number) Cases AF (%) in GJB2 AF (%) in SLC26A4 and mt DNA
c.235delC c.299delAT c.176del16 c.919-2A>G c.2168A>G c.1229C>T m.1555A>G
Chinese-1 This study GJB2(5), SLC26A4(11), mtDNA(2), GJB3(2) 3,555,336 0.990 0.242 0.057 0.667 0.119 0.061 0.239
Chinese-2 Cao et al. (2022) GJB2(4), SLC26A4(8), mtDNA(2), GJB3(1) 2,174 1.058 0.138 0.046 0.437 0.115 0.000 0.184
Chinese-3 Cai et al. (2021) 22 genes (159 variants) 5,120 1.133 0.225 0.039 0.547 0.117 0.049 0.391
Chinese-4 Cao et al. (2020) GJB2(5), SLC26A4(3), mtDNA(4), GJB3(1) 47,538 0.711 0.093 0.024 0.377 0.058 0.080 0.187
Chinese-5 Zou et al. (2019) GJB2(6), SLC26A4(11), mtDNA(2), GJB3(1) 53,033 0.806 0.123 0.028 0.442 0.078 0.081 0.213
Chinese-6 Dai et al. (2019) GJB2(4), SLC26A4(2), mtDNA(2), GJB3(1) 180,469 / / / / / / 0.212
Chinese-7 Hao et al. (2018) GJB2(1), SLC26A4(1), mtDNA(2) 142,417 0.951 / / 0.492 / / 0.154
Chinese-8 He et al. (2018) GJB2(4), SLC26A4(2), mtDNA(2), GJB3(1) 2,500 0.760 0.240 0.040 0.580 0.140 / 0.200
Chinese-9 Wu et al. (2017) GJB2(2), SLC26A4(1), mtDNA(1) 5,173 0.638 / / 0.580 / / 0.077
Chinese-10 Peng et al. (2016) GJB2(5), SLC26A4(11), mtDNA(2), GJB3(2) 9,317 0.746 0.161 0.021 0.429 0.075 0.123 0.311
Chinese-11 Chen et al. (2015) GJB2(4), SLC26A4(2), mtDNA(2), GJB3(1) 5,800 0.940 0.147 0.095 0.845 0.172 0.009 0.138
Chinese-12 Zhang et al. (2012) GJB2(c), SLC26A4(1), mtDNA(2) 10,043 / / / 0.602 / / 0.149
Chinese-13 Wu et al. (2011) GJB2(2), SLC26A4(1), mtDNA(1) 1,017 1.229 / / 0.295 / / 0.098
Korean-1 Sagong et al. (2013) GJB2(1), SLC26A4(5), mtDNA(1) 336 0.744 / / 0.595 0.893 0.000 0.298
Korean-2 Han et al. (2008) GJB2(c) 2,072 0.627 0.072 0.024 / / / /
Korean-3 Bae et al. (2008) mtDNA(29) 217 / / / / / / 0.000
Korean-4 Park et al. (2003) SLC26A4(9) 120 / / / 0.000 0.833 0.000 /
Korean-5 Park et al. (2000) GJB2(c) 100 0.500 0.000 0.000 / / / /
Japanese-1 Maeda et al. (2020) mtDNA(2) 1,683 / / / / / / 0.060
Japanese-2 Taniguchi et al. (2015) GJB2(c) 509 0.786 / / / / / /
Japanese-3 Tsukada et al. (2010) GJB2(c) 252 0.400 / / / / / /
Japanese-4 Kudo et al. (2000) GJB2(c) 203 0.426 / 0.213 / / / /
AF indicates allele frequency; GJB2(c), the coding region of GJB2.

The SLC26A4 gene was the second most commonly mutated gene in Chinese newborns, with a total carrier rate of 2.05% (72,821/3,555,336). Variants in SLC26A4 have been found to be one of the most common genetic causes of autosomal recessive NSHL in several studies (Wu et al. 2011; Wu et al. 2017; Shearer et al. 2019). We identified c.919-2A>G as the most prevalent variant in the SLC26A4 gene, with an allele frequency of 0.66%. SLC26A4 encodes the transmembrane anion exchanger protein pendrin, which is expressed in nonsensory epithelial cells of the lateral wall of the cochlea, vestibular organs and endolymphatic sac. Mutations in SLC26A4 impair or eliminate the activity of pendrin, which upsets the balance of ions in the inner ear. These changes presumably affect the development of structures in the inner ear, including the cochlea and vestibular aqueduct, which in turn leads to sensorineural HL (Everett et al. 1999; Albert et al. 2006; Shearer et al. 2010).

We found 0.25% of newborns carrying MT-RNR1 variants in the general population. This means that one in 393 newborns is potentially highly sensitive to aminoglycosides, and even a small dose of such drugs may lead to aminoglycoside antibiotic-induced deafness. A meta-analysis showed that in newborns in China, the carrier frequency of MT-RNR1 variants (m.1555A>G and m.1449C>T) was 0.20% (Fu et al. 2019), while the prevalence of m.1555A>G was 0.19% in a European general population (Bitner-Glindzicz et al. 2009). Newborn genetic screening for HL helps to inform MT-RNR1 variant carriers with a risk of drug-induced HL to avoid aminoglycoside antibiotic exposure and therefore HL (Bitner-Glindzicz et al. 2009; Igumnova et al. 2019).

Newborn genetic screening of HL can provide an opportunity to identify individuals at increased risk for HL that may otherwise be missed by traditional hearing screening, and for which there are preventive measures or effective treatments. This reduces the risk of deafness by informing asymptomatic or presymptomatic individuals of their elevated genetic risk for HL and engaging them in personalized risk management, including identifying molecular etiology, discerning high-risk subgroups, triggering early diagnosis, and timely intervention (Wu et al. 2017; Dai et al. 2019; Q. Wang et al. 2019; Guo et al. 2020). Many studies have demonstrated the benefits of incorporating genetic screening into universal newborn hearing screening programs, especially for common deafness-associated variants (Kenna 2021; Zhu et al. 2021).

There is considerable genetic heterogeneity in HL among various ethnic and regional groups (Sloan-Heggen et al. 2016), so it is important to recognize hotspot variants for particular ethnic populations. Although genetic analysis of newborns from China, the United States, Italy, Hungary, Spain, Croatia, and Brazil (Niceta et al. 2007; Zaputovic et al. 2008; Nagy et al. 2010; Nivoloni et al. 2010; Streitenberger et al. 2011; Lim et al. 2013; Hao et al. 2018) has been reported, no large-scale study has compared the newborn variant frequencies of common deafness-associated genes among different geographical populations. Such a study would provide ethnic-specific variant information to improve the efficacy of newborn genetic screening.

To our knowledge, this is the first study regarding the comparison of variant frequencies of common deafness-associated variants in general individuals among diverse populations and provides insights into population-level allele frequencies in diverse ethnic groups. This study compares the frequencies of variants present in 3,555,336 newborns with information on published variants related to HL, and sequence variants obtained from 125,748 exome sequences and 15,708 whole-genome sequences of unrelated individuals from gnomAD. Thus, this study reveals interesting aspects of population-specific variants. Deafness-associated variants have different prevalence patterns in their hot spots and variant frequencies among different populations (Chan & Chang 2014; Tsukada et al. 2015).

We demonstrated the population-specific features of deafness-associated variants in diverse populations and reported population-specific hotspot mutations in certain ethnic groups. We found nine variants that were significantly enriched among East Asians (c.235delC, c.299_300delAT, and c.176_191del16 in GJB2 and c.919-2A>G, c.1226G>A, c.2162C>T c.2168A>G, c.1975G>C, and c.1707 + 5G>A in SLC26A4). One variant was considered Ashkenazi Jewish-enriched (GJB2 c.167delT), and one was considered European/American-enriched (GJB2 c.35delG). A potential explanation for this phenomenon is that these population-specific hotspot variants may be founder effects in particular populations from given geographic areas or ethnic groups. We also found that the allele frequencies of most of the variants in our cohort were similar to those in the Korean population and the Japanese population, which in turn further supported the population-specific features that we demonstrated.

These population-specific features of deafness-associated variants in diverse populations were of great importance, providing a reference to design an appropriate screening strategy tailored to different ethnic backgrounds, which is critical for optimizing the newborn genetic screening panel and further guiding carrier screening for HL in diverse populations. Furthermore, the screening strategy could be enhanced further with the use of better optimized panels of population-specific hotspot variants for HL without increasing the cost and turnaround time. For instance, we now observe that the GJB2 c.167delT variant is extremely rare in the Chinese population. Replacing this variant with other relatively common pathogenic variants is considered to improve the panel for our population. It is thus important to evaluate the content of gene panels used for the genetic screening of general newborns in different ethnic groups. An ethnic-specific screening panel could be designed to target the most common deafness-associated variants in a certain population. These findings enhance our knowledge about the perspective of population-specific features and hotspot variants for HL in diverse populations, and inform the broader implementation of newborn concurrent hearing and genetic screening tailored to particular populations to better serve different populations from various geographic locations and ethnic groups (Supplemental Digital Content 3, https://links.lww.com/EANDH/B53).

This study also has limitations. First, not all genetic causes of HL were assessed. Only commonly known deafness-associated variants were included in the screening panel, and the possibility remains that other untested genes and variants therein may contribute to the risk of deafness. This limitation, however, might be overcome by optimizing population-specific panels and increasing the number of variants, as increasing genetic knowledge of HL is discovered. Furthermore, this study was mainly conducted in a Chinese newborn population. Though gnomAD contains sequencing data from a variety of large-scale sequencing projects and is widely used to assess the frequency of a variant in a general population for different ethnic backgrounds, it only allows the evaluation of allele frequencies for each of the selected variants based on the aggregated manner with only 7 stratifications, thus making it impossible to access variations in some certain subpopulations, or individual populations that compose the larger population. It should be noted that the ethnical composition of gnomAD does not reflect the world population, and therefore, the data may not be yield worldwide generalizability. In addition, genetic data are still lacking for many geographic locations and ethnic groups in gnomAD, and the inclusion of certain ethnic populations in gnomAD is very limited or nonexistent. The allele frequency of these variants with a low number of observations may be biased. Hence, further investigations involving other ethnic groups are required to validate these findings.

In conclusion, we reported the distinct frequencies of common deafness-associated variants in a Chinese newborn population. Furthermore, we compared variant frequencies of deafness-associated genes in diverse general populations, demonstrating population-specific features and hotspot variants, which is critical to optimize genetic screening strategies that are tailored to different ethnic backgrounds. Future studies are required to assess the clinical implications of these findings.

ACKNOWLEDGMENTS

This work was supported by the grants of the National Natural Science Foundation of China (Major Project No. 81830028 & 81530032; Youths Program 81900951 & 81900950); Beijing Municipal Natural Science Foundation Youth Projects (7204312); Medical Technology Incubation Project for Youth (19QNP058); National Key Research and Development Project (No. 2020YFC2005201 & 2020YFC2005200). The funding organization had no role in the design and conduct of the study; in the collection, analysis, and interpretation of the data; or in the decision to submit the article for publication; or in the preparation, review, or approval of the article. There are no conflicts of interest, financial, or otherwise.

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Keywords:

Concurrent hearing and genetic screening; Genetic screening; Hearing loss; Newborns; Population-specific

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