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Noise-induced hearing loss (NIHL) is a major occupational health risk in industrialized countries worldwide that affects people of all ages, sex, and races. About 22-30 million US workers are exposed to hazardous noise levels at work and an estimated US $242 million is spent annually on compensation for disability associated with hearing loss[1-2]. Data from the Centers for Disease Control and Prevention (China) showed that NIHL is the third most serious occupational disease in China[3]. NIHL not only affects workers' health, but also causes social isolation, impaired communication, and decreased productivity.
NIHL is a complex form of hearing loss induced by interactions between genetic and environmental factors. Noise is the most studied environmental factor associated with hearing loss; it is harmful over 85 dB and causes both mechanical and metabolic damage. However, not all workers develop NIHL after exposure to identical noise levels. Thus, genetic factors might also influence the susceptibility to NIHL.
PCDH15 is a member of the cadherin superfamily of calcium-dependent cell-cell adhesion molecules[4], which is localized in the inner ear hair cell stereocilia and retinal photoreceptors. Mutations in PCDH15 have been associated with both non-syndromic (DFNB23) and syndromic hearing loss (Usher syndrome type1F, USH1F)[5-6]. In 2009, research in Swedish and Polish populations first reported that single nucleotide polymorphisms (SNPs) in PCDH15 were associated with NIHL risk[7]. Even though the reported variation is relatively common in certain European populations, racial differences need to be considered. Zhang et al. were the first to conduct research on this topic in China, reporting that the rs11004085 genetic variation in PCDH15 was associated with NIHL[8]. However, the findings in this study were restricted to men living in South China; thus, more studies in other independent samples are necessary to confirm these findings. Therefore, this study investigated whether susceptibility to NIHL was associated with PCDH15 genetic variations in a northern Chinese population.
This study included 6, 309 workers exposed to continuous and steady occupational noise in a steel factory in Henan province, China. A detailed description of the inclusion and exclusion criteria can be found elsewhere[9-10]. The case group was defined as those individuals with an average high-frequency (3, 4, and 6 kHz) binaural hearing level (HL)≥40 dB. The individually matched control group was defined as binaural HL of any frequency (0.5, 1, 2, 3, 4, and 6 kHz) < 25 dB. Finally, 344 matched pairs of participants were recruited from the steel factory cohort from September to December in 2013 and September to November in 2014. The study was approved by the Ethics Committee of the Henan Institute of Occupational Medicine.
All the subjects answered a structured questionnaire and underwent physical examinations by trained physicians. Noise exposure levels were assessed during their working time, which was evaluated with equivalent continuous dB (A)-weighted sound pressure levels (LAeq, 8h). Cumulative noise exposure (CNE) was calculated to determine the actual noise exposure for each subject[9-10].
A total of 12 candidate SNPs were selected based on the inclusion criteria[9-10], including rs10825112, rs10825113, rs1900443, rs12258253, rs2135720, rs11004085, rs11004142, rs996320, rs7081730, rs978842, rs11004439, and rs7922254. The genotypes were determined using the commercial SNPscanTM multiplex SNP genotyping kit (Genesky Biopharm Technology Co., Ltd, Shanghai, China).
Hardy-Weinberg equilibrium (HWE) was checked for each SNP in the control subjects using χ2-tests. Paired samples t-tests were used to compare demographic information for continuous variables, while χ2-tests were used for categorical variables. Adjusted ORs with 95% CIs were computed by conditional logistic regression analysis to test for associations between NIHL risk and the genotypes. Bonferroni correction was performed to control for multiple testing, which resulted in a corrected significance level of 0.004 (P=0.05/12=0.004). Haploview was used to estimate the haplotypes and investigate the linkage disequilibrium (LD) between the SNPs. All statistical analyses were two-sided and performed using IBM SPSS Statistics for Windows, Version 20.0, with a significance level of 0.05.
The basic characteristics of the subjects are shown in Table S1 (www.besjournal.com). The average binaural HL of high frequency noise exposure in the case group was significantly higher than that of the control subjects (P=0.024). The percentage of smokers was also higher in the case group (P < 0.001). The two groups appeared to be well matched by age, gender, body mass index (BMI), hypertension, drinking status, exposure time, the use of earplug, noise exposure level, and CNE (P > 0.05).
Variables Case (n=344) Control (n=344) P Age (y), mean±SD 40.7±8.4 40.1±8.4 0.998 Tenure (y), mean±SD 19.1±9.2 18.6±9.0 0.747 HLa, mean±SD 51.1±8.9 10.2±8.6 0.024 BMIb, mean±SD 25.5±3.4 25.3±3.4 0.964 Gender, n (%) male 327 (95.1) 327 (95.1) 1.000 female 17 (4.9) 17 (4.9) Hypertension, n (%) yes 140 (40.7) 142 (41.3) 0.877 no 204 (59.3) 202 (58.7) Smoking, n (%) yes 217 (63.1) 172 (50.0) < 0.001 no 127 (36.9) 172 (50.0) Drinking (Alcohol), n (%) yes 233 (71.6) 228 (69.0) 0.685 no 111 (28.4) 116 (31.0) Protector (Earplug), n (%) yes 140 (40.7) 148 (43.0) 0.536 no 204 (59.3) 196 (57.0) Noise exposure level, dB (A) 85.7±3.9 85.7±3.7 0.152 CNEc, dB (A) 97.9±4.6 97.9±4.4 0.152 Note. aHL: hearing level in high frequency; bBMI (Body Mass Index) was calculated as body weight (kg)/height (m)2; cCNE: cumulative noise exposure. Table Table S1. Basic Characteris cs of Case and Control Subjects
The distributions of the PCDH15 genotypes and alleles in the case and control subjects are shown in Table 1. Of the 12 SNPs, only one significant association of genotype rs11004085 was observed between the two groups (P=0.039). As shown in Table S2 (www.besjournal.com), for rs11004085, after adjusting for BMI, smoking, drinking, and CNE, the frequencies of the CT compared with the TT genotype in the case group was significantly higher than that in the control group (adjusted OR=3.03; 95% CI: 1.26-7.33, P=0.014). Compared with subjects carrying the TT genotype, subjects with CT/CC genotypes were at increased risk of NIHL (adjusted OR=2.64; 95% CI: 1.14-6.11, P=0.024). Thus, this SNP genotype (CT/CC on rs11004085) was identified as a risk factor associated with NIHL. These findings were in agreement with two previously published studies of Polish and Swedish populations and a southern Chinese population[7-8]. Mutations on rs11004085 might decrease calcium binding capacity, weaken its interaction with other genes such as CDH23, and affect its adhesion function, which increase the stereocilia bundle susceptibility to noise injury[4-6]. However, no significant differences between two groups in terms of the distribution of genotypes or alleles of the other 11 SNPs were found in our study, as shown in Table S3 (www.besjournal.com). Similarly, no significant differences were detected when Zhang and colleagues compared allele and genotype frequencies for the SNPs on rs12258253[8]. This SNP did not seem to play an important role in NIHL in the Chinese population, although more studies are needed to confirm these findings.
SNPs Minor/major
Allele (A1/A2)Loca on Minor Allele Frequency P (H-W)a A1A1/A1A2/A2A2 Pb HapMap-CHB Case Control Case Control rs10825112 C/A 3'UTR 0.057 0.071 0.078 0.693 0/49/295 3/48/293 0.537 rs10825113 A/G intron32 0.146 0.214 0.201 0.116 17/113/212 19/100/225 0.593 rs1900443 T/C intron27 0.306 0.259 0.230 1.000 22/134/185 18/122/204 0.251 rs12258253 C/T intron25 0.278 0.243 0.219 0.509 22/123/197 14/123/204 0.479 rs2135720 G/A exon20 0.427 0.507 0.480 0.792 89/171/82 78/174/89 0.335 rs11004085 C/T intron16 0.023 0.061 0.030 0.129 0/21/323 1/8/333 0.039 rs11004142 C/A intron9 0.159 0.156 0.153 0.504 9/89/246 10/85/249 0.957 rs996320 A/G intron9 0.159 0.177 0.154 0.328 14/94/236 11/84/247 0.364 rs7081730 T/C intron8 0.232 0.195 0.170 0.085 18/98/228 15/87/242 0.312 rs978842 C/T intron7 0.222 0.193 0.235 0.550 15/103/225 18/126/200 0.118 Note. aHWE test was performed using χ2 test for each SNP among control subjects; bAdjusted for BMI, drinking, smoking, and CNE. Table 1. Distri ons of PCDH15 Alleles and Genotypes in the Case and Control Subjects
Genotypes Case Control OR (95% CI)a Pa N % N % rs11004085 TT 323 94.2 333 97.7 1.00 CT 21 5.8 8 2.0 3.03 (1.26-7.33) 0.014 CC 0 0.0 1 0.3 - 0.978 CC/CT 21 5.8 8 2.3 2.64 (1.14-6.11) 0.024 T Allele 667 96.9 674 98.0 1.00 C Allele 21 3.1 10 1.5 - 0.978 Note. aAdjusted for BMI, drinking, smoking and CNE. Table Table S2. Single SNP Analysis of Association of rs11004085 with the Risk of NIHL
SNPs Genotypes Case Control OR (95% CI)* P* N % N % rs10825112 AA 295 85.8 293 85.2 1.00 CA 49 14.2 48 14.0 0.10 (0.63-1.56) 0.985 CC 0 0.0 3 0.9 ‐ 0.975 CA/CC 49 14.2 51 14.8 0.93 (0.60-1.45) 0.741 A allele 639 92.9 634 92.2 1.00 C allele 49 7.1 54 7.8 0.92 (0.59-1.43) 0.715 rs10825113 GG 212 61.6 225 65.4 1.00 GA 113 32.8 100 29.1 1.19 (0.85-1.67) 0.307 AA 17 4.9 19 5.5 0.93 (0.48-1.83) 0.840 GA/AA 130 37.8 119 34.6 1.15 (0.83-1.58) 0.398 GG/GA 325 94.5 325 94.5 1.00 AA 17 4.9 19 5.5 0.88 (0.45-1.71) 0.706 G allele 537 78.1 550 79.9 1.00 A allele 147 21.4 138 20.1 0.88 (0.45-1.71) 0.703 rs1900443 CC 185 53.8 204 59.3 1.00 TC 134 39.0 122 35.5 1.19 (0.86-1.63) 0.293 TT 22 6.4 18 5.2 1.26 (0.66-2.40) 0.485 TC/TT 156 45.3 140 40.7 1.19 (0.88-1.60) 0.268 CC/TC 319 92.7 326 94.8 1.00 TT 22 6.4 18 5.2 1.19 (0.63-2.24) 0.599 C allele 504 73.3 530 77.0 1.00 T allele 178 25.9 158 23.0 1.20 (0.89-1.61) 0.243 rs12258253 TT 197 57.3 204 59.3 1.00 TC 123 35.8 123 35.8 0.99 (0.72-1.37) 0.955 CC 22 6.4 14 4.1 1.50 (0.76-2.99) 0.245 TC/CC 145 42.2 137 39.8 1.06 (0.78-1.44) 0.710 TT/TC 320 93.0 327 95.1 1.00 CC 22 6.4 14 4.1 1.51 (0.76-2.98) 0.238 T allele 517 75.1 531 77.2 1.00 C allele 167 24.3 151 21.9 1.50 (0.76-2.96) 0.243 rs2135720 CC 82 23.8 89 25.9 1.00 TC 171 49.7 174 50.6 0.85 (0.59-1.22) 0.380 TT 89 25.9 78 22.7 0.81 (0.52-1.27) 0.353 TC/TT 260 75.6 252 73.3 0.84 (0.60-1.18) 0.319 CC/TC 253 73.5 263 76.5 1.00 TT 89 25.9 78 22.7 0.90 (0.62-1.31) 0.592 C allele 335 48.7 352 51.2 1.00 T allele 349 50.7 330 48.0 1.20 (0.85-1.70) 0.297 rs11004142 AA 246 71.5 249 72.4 1.00 CA 89 25.9 85 24.7 1.01 (0.70-1.45) 0.953 CC 9 2.6 10 2.9 0.92 (0.34-2.44) 0.861 CA/CC 98 28.5 95 27.6 1.00 (0.71-1.41) 1.000 AA/CA 335 97.4 334 97.1 1.00 CC 9 2.6 10 2.9 0.92 (0.34-2.44) 0.859 A allele 581 84.4 583 84.7 1.00 C allele 107 15.6 105 15.3 1.01 (0.71-1.42) 0.977 rs996320 GG 236 68.6 247 71.8 1.00 GA 94 27.3 84 24.4 1.11 (0.78-1.58) 0.558 AA 14 4.1 11 3.2 1.41 (0.60-3.31) 0.426 GA/AA 108 31.4 95 27.6 1.14 (0.82-1.60) 0.436 GG/GA 330 95.9 331 96.2 1.00 AA 14 4.1 11 3.2 1.37 (0.59-3.20) 0.461 G allele 566 82.3 578 84.0 1.00 A allele 122 17.7 106 15.4 1.41 (0.61-3.30) 0.423 rs7081730 CC 228 66.3 242 70.3 1.00 TC 98 28.5 87 25.3 1.14 (0.81-1.60) 0.467 TT 18 5.2 15 4.4 1.37 (0.65-2.86) 0.406 TC/TT 116 33.7 102 29.7 1.16 (0.84-1.61) 0.369 CC/TC 326 94.8 329 95.6 1.00 TT 18 5.2 15 4.4 1.30 (0.63-2.69) 0.476 C allele 554 80.5 571 83.0 1.00 T allele 134 19.5 117 17.0 1.15 (0.83-1.60) 0.391 rs978842 TT 225 65.4 200 58.1 1.00 TC 103 29.9 126 36.6 1.25 (0.90-1.72) 0.184 CC 15 4.4 18 5.2 1.47 (0.70-3.09) 0.305 TC/CC 118 34.3 144 41.9 1.29 (0.94-1.76) 0.113 TT/TC 328 95.3 326 94.8 1.00 CC 15 4.4 18 5.2 1.37 (0.66-2.83) 0.403 T allele 553 80.4 526 76.5 1.00 C allele 133 19.3 162 23.5 1.34 (0.65-2.77) 0.427 rs11004439 AA 243 70.6 241 70.1 1.00 CA 89 25.9 98 28.5 0.94 (0.66-1.34) 0.736 CC 12 3.5 5 1.5 2.43 (0.83-7.12) 0.105 CA/CC 101 29.4 103 29.9 1.01 (0.72-1.43) 0.946 AA/CA 332 96.5 339 98.5 1.00 CC 12 3.5 5 1.5 2.49 (0.86-7.23) 0.094 A allele 575 83.6 580 84.3 1.00 C allele 113 16.4 108 15.7 1.01 (0.72-1.42) 0.953 rs7922254 AA 204 59.3 189 54.9 1.00 TA 117 34.0 139 40.4 0.90 (0.57-1.12) 0.187 TT 23 6.7 16 4.7 1.41 (0.72-2.76) 0.323 TA/TT 140 40.7 155 45.1 0.86 (0.63-1.19) 0.359 AA/TA 321 93.3 328 95.3 1.00 TT 23 6.7 16 4.7 1.55 (0.81-3.00) 0.189 A allele 525 76.3 517 75.1 1.00 T allele 163 23.7 171 24.9 0.86 (0.63-1.18) 0.353 Note. *Adjusted for BMI, smoking, drinking, and CNE. Table Table S3. Associations of Candidate SNPs with the Risk of NIHL
As noise is the most common cause of NIHL, stratified analysis by noise exposure level or CNE was conducted, the results of which are shown in Table 2. For rs11004085, compared with the TT genotype, CT/TT genotypes resulted in an increased risk of NIHL for noise exposure levels > 85 dB (A) (adjusted OR=4.61; 95% CI: 1.25-17.04, P=0.022); for CNE > 95 dB (A), the CT/TT genotypes were also at increased risk (P=0.011), with adjusted OR of 5.26 and 95% CI of 1.47-18.79. For rs978842, no overall significant associations with NIHL were observed before stratification. Compared to those with TT genotypes, noise exposure levels > 85 dB (A) were associated with an increased risk for NIHL among subjects carrying TC/CC genotypes (adjusted OR=1.58; 95% CI: 1.03-2.42, P=0.035). Therefore, this study iden fied significant SNP-environment interac ons between two SNPs, rs11004085 and rs978842, and noise exposure, a finding concordant with that of previous research[8]. It is not surprising that NIHL is posi vely correlated with noise exposure, as workers are more susce ble to NIHL when exposed to greater noise exposure levels. Taken together, these data suggest that the interac ons between PCDH15 polymorphisms and noise exposure might play important roles in the incidence of NIHL.
Variables SNPs Case Control OR (95% CI)a Pa Genetype N (%) Genetype N (%) Noise exposure level [dB (A)] ≤85 rs11004085 TT 151 (93.8) TT 144 (96.6) 1.00 0.212 CT/CC 10 (6.2) CT/CC 5 (3.4) 2.03 (0.67-6.19) > 85 TT 172 (94.0) TT 190 (98.4) 1.00 0.022 CT/CC 11 (6.0) CT/CC 3 (1.6) 4.61 (1.25-17.04) ≤85 rs978842 TT 94 (58.4) TT 94 (63.1) 1.00 0.457 TC/CC 67 (41.6) TC/CC 55 (36.9) 1.19 (0.75-1.91) > 85 TT 106 (57.9) TT 131 (68.2) 1.00 0.035 TC/CC 77 (42.1) TC/CC 61 (31.8) 1.58 (1.03-2.42) CNE [dB (A)] ≤95 rs11004085 TT 85 (92.4) TT 85 (93.4) 1.00 0.523 CT/CC 7 (66.6) CT/CC 6 (6.6) 1.47 (0.45-4.73) > 95 TT 238 (94.4) TT 250 (98.8) 1.00 0.011 CT/CC 14 (5.6) CT/CC 3 (1.2) 5.26 (1.47-18.79) Note. aAdjusted for BMI, drinking, smoking, and CNE. Table 2. Strafied Analysis of PCDH15 by Noise Exposure Level or CNE
In order to ide fy true associa ons that might be missed because of the incomplete informa on provided by the individual SNP, we primarily applied a haplotype-centric approach, taking into account different levels of noise exposure, to test for interac ons. The pairwise LD between the 12 SNPs is shown in Table S4 (www.besjournal.com). From Table 3, no significant P-values were obtained before stra fica on (P > 0.05). When noise exposure level > 85 dB (A) were compared with haplotype TAGCT, the frequencies of haplotype TAGCC was significantly higher in the case group (adjusted OR=1.84; 95% CI=1.01-3.33, P < 0.05); for CNE > 95 dB (A), subjects with haplotype TAGCC were more susceptible to NIHL (adjusted OR=1.79; 95% CI=1.08-2.95, P < 0.05), indicating it to be a risk haplotype. Our finding was concordant with that of a previous study[8], suggesting that multiple genetic variations in PCDH15 modify NIHL risk and that higher noise exposure might increase risk.
SNPs rs10825112 rs10825113 rs1900443 rs12258253 rs2135720 rs11004085 rs11004142 rs996320 rs7081730 rs978842 rs11004439 rs7922254 rs10825112 ‐ 0.728 0.046 0.013 0.704 0.443 0.134 0.182 0.207 0 0 0 rs10825113 0.124 ‐ 0.593 0.472 0.601 0.174 0.06 0.071 0.047 0.062 0 0 rs1900443 0.001 0.283 ‐ 0.919 0.289 0.47 0.126 0.146 0.109 0.073 0 0 rs12258253 0 0.191 0.795 ‐ 0.211 0.495 0.121 0.148 0.121 0.095 0 0 rs2135720 0.041 0.095 0.027 0.014 ‐ 0.616 0.021 0.003 0.028 0.017 0 0 rs11004085 0.056 0.003 0.016 0.019 0.009 ‐ 0.431 0.729 0.953 0.899 0 0 rs11004142 0.008 0.003 0.009 0.009 0 0.023 ‐ 0.925 0.843 0.541 0.275 0 rs996320 0.013 0.004 0.013 0.015 0 0.062 0.784 ‐ 0.923 0.644 0.094 0 rs7081730 0.015 0.002 0.008 0.011 0 0.094 0.58 0.758 ‐ 0.689 0.235 0 rs978842 0 0.004 0.005 0.008 0 0.068 0.195 0.302 0.388 ‐ 0.176 0.23 rs11004439 0 0 0 0 0 0 0.003 0 0 0.002 ‐ 0.907 rs7922254 0 0 0 0 0 0 0 0 0 0.002 0.492 ‐ Note. The upper triangle was D' value and the lower triangle was r2 value. Table Table S4. Linkage Disequilibrium test of PCDH15 Gene
Haplotypea, b Case
(n, %)Control
(n, %)Adjusted OR (95% CI)c Total Noise Exposure
Level≤85 dB (A)Noise Exposure
Level > 85 dB (A)CNE≤95 dB (A) CNE > 95 dB (A) TAGCT 479 (69.6) 516 (75.0) 1.00 1.00 1.00 1.00 1.00 TCATC 59 (8.6) 61 (8.9) 1.03 (0.70-1.51) 1.27 (0.72-2.24) 0.87 (0.51-1.47) 1.08 (0.53-2.18) 1.03 (0.65-1.63) TAGCC 59 (8.6) 42 (6.1) 1.51 (1.00-2.30) 1.32 (0.72-2.41) 1.84 (1.01-3.33)d 1.13 (0.52-2.46) 1.79 (1.08-2.95)d TCATT 23 (3.3) 25 (3.5) 0.94 (0.52-1.69) 1.48 (0.58-3.79) 0.68 (0.32-1.47) 3.55 (0.72-17.58) 0.72 (0.37-1.34) Note. aHaplotype analysis was restricted to the SNPs that were in one block (D' > 0.4); bHaplotypes of PCDH15 were deduced for the following SNPs: rs11004085, rs11004142, rs996320, rs7081730, and rs978842; cAdjusted for BMI, smoking and drinking; only haplotype with frequency > 3% was shown in this table; dBold signifies P < 0.05. Table 3. Assessment of the Associations between Haplotypes and NIHL
However, after applying Bonferroni correction, the associations were no longer statistically significant.
These findings are of value for the prevention of NIHL. People with the CT/CC rs11004085 genotype or the TAGCC PCDH15 risk haplotype should take care to avoid high levels of noise exposure in their workplaces.
The limitations of this study should be acknowledged when interpreting the results. Firstly, although some workers might be exposed to community noise, such as sleeping with the television on and listening to music with headphones, these factors were too complicated to consider in the current study. Secondly, while this study identified TAGCT as a potential risk haplotype, the molecular mechanism are not clear and further functional studies are warranted.
In conclusion, our findings indicated that genetic variations in PCDH15 may play an important role in genetic susceptibility to NIHL. The effect of gene-environment interactions and multiple loci on the development of NIHL were detected. However, after Bonferroni correction, these differences were not found to be significant. Further studies involving a larger number of individuals and independent populations are required to assess these findings.
The Effect of PCDH15 Gene Variations on the Risk of Noise-induced Hearing Loss in a Chinese Population
doi: 10.3967/bes2017.019
Funds:
the National Natural Science Foundation of China 81372940
research funds from the National Science and Technology Infrastructure Program of the People's Republic of China 2014BAI12B03
- Received Date: 2016-09-22
- Accepted Date: 2017-01-01
Abstract: Noise-induced hearing loss (NIHL) is a complex disease caused by interactions between environmental and genetic factors. This study investigated whether genetic variability in protocadherin related 15 (PCDH15) underlies an increased susceptibility to the development of NIHL in a Chinese population. The results showed that compared with the TT genotype of rs11004085, CT/CC genotypes were associated with an increased risk of NIHL [adjusted odds ratio (OR)=2.64; 95% confidence interval (CI): 1.14-6.11, P=0.024]. Additionally, significant interactions between the rs11004085 and rs978842 genetic variations and noise exposure were observed in the high-level exposure groups (P < 0.05). Furthermore, the risk haplotype TAGCC was observed when combined with higher levels of noise exposure (P < 0.05). Thus, our study confirms that genetic variations in PCDH15 modify the susceptibility to NIHL development in humans.
| Citation: | XU Xiang Rong, WANG Jing Jing, YANG Qiu Yue, JIAO Jie, HE Li Hua, YU Shan Fa, GU Gui Zhen, CHEN Guo Shun, ZHOU Wen Hui, WU Hui, LI Yan Hong, ZHANG Huan Ling, ZHANG Zeng Rui, JIN Xian Ning. The Effect of PCDH15 Gene Variations on the Risk of Noise-induced Hearing Loss in a Chinese Population[J]. Biomedical and Environmental Sciences, 2017, 30(2): 143-146. doi: 10.3967/bes2017.019
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