Association Of GATA3,GPX3 And TRIOBP Single Nucleotide Polymorphism And Noise-induced Hearing Loss

Objectives1 Establish a cross-sectional study to access the associations between noise exposure,shift working,health-related customs and the risk for hearing loss.2 To discuss about whether the Single Nucleotide Polymorphism of GATA3,GPX3and TRIOBP genes are related to the susceptibility of hearing loss in noise exposure workers.Methods1 Workers exposed to occupational noise were investigated by questionnaire,annual occupational health examination and the detection of the noise exposure levels.Individuals would be excluded who do not be consistent with the criteria.According to criterion formulated in some domestic studies and the judgement to noise-induced hearing loss,all individuals were divided into 2 groups:the hearing loss group and the normal hearing group.We compared the factors between 2 groups,including noise exposure,age,duration of occupational noise exposure,marital status,education background,tobacoo use,liquor consumption,weekly exercise,listen to the music by wearing earphones and life noise exposure.We aimed to find out the associations between noise exposure and the demographic index with the hearing loss.What’s more,the logistic regression model will be established to estimate the main effects and correct the confounding factors.2 By screening Gata3,GPX3 and TRIOBP gene SNP in Bioinformatics database and some studies,we predicted the SNPs that will probably be associated with noise-induced hearing loss in Chinese Han population.3 We selected the individuals to compose a new database（case:control=1:1）,and extracted DNA from whole blood samples.MASSARRAY technique will be used to recognize the SNPs of GATA3、GPX3 and TRIOBP genes in all samples for provide evidence confirming the association between all SNPs and noise-induced hearing loss.Results1 There are 276 individuals selected into the hearing loss group,while the normal hearing group has 1303 individuals.The distribution of Noise expose level,age,duration of occupational noise exposure were different in 2 groups,and the positive rate were different after divided individuals by various shift working types and the marital status（P<0.05）.However,we found no significant difference（P>0.05）in educational level,tobacco use,wine consumption,wearing ear plugs and the other occupational hazards exposure（high temperature,stive and organic solvent）.2 All the variables would be screened out and brought into the multiple logistic regression to control the confounding and estimate the main effects if P value<0.15 in single factor analysis.After adjusting confounding factors,it shows correlations between cumulative noise exposure,age,and shift working for hearing loss(P<0.05,OR_CNE95%CI 1.001-1.055,OR_agege 95%CI 1.022-1.098).The risk of hearing loss was higher in Two shifts workers group and three shifts workers group(P<0.05,OR_{two shifts}95%CI1.171-4.099,OR_{three shifts}95%CI为1.267-4.666).It shows that shift working is a risk factor of hearing loss.3 Individuals in the second part were selected from the first part study.According to the conclusions in first part,we paired the case group and the control group by 3 factors,including the same noise exposure position,age and duration of occupational noise exposure.Finally we collected 2 groups,the case group 155 individuals and the case group 155 individuals.There is no significant difference between noise exposure levels,age and duration of occupational noise exposure in 2 groups（P>0.05）.It shows 2 groups satisfied with a equilibrium condition in pairing.In the comparison of the other factors,we can’t see any covariants[BMI,educational level,marital status,tobacco use,wine consumption,wearing ear plugs,weekly exercise,listen to the music by wearing earphones and life noise exposure and the other occupational hazards exposure（high temperature,stive and organic solvent）]be different between 2 groups.4 We screened the bioinformatics database to select GATA3,GPX3 and TRIOBP gene SNPs.After adjust the target SNPs,we decided 14 SNPs,including GATA3（rs3802604,rs569421）;GPX3（rs3828599,rs8177429,rs3792795,rs11548,rs2070593,rs8177431,rs8177435）;TRIOBP（rs9619704,rs9610841,rs5756805,rs3788528,rs3788530）.The results showed all SNPs were satisfied with the hardy-weinberg equilibrium.5 The distribution of GATA3 gene SNPs genotype between case and control population:rs3802604 genotype:case group,GG genotype 20（12.9%）,GA genotype22（14.2%）,AA genotype 67（43.2%）.Control group:GG genotype 22（14.2%）,GA genotype 66（42.6%）,AA genotype 67（43.2%）;rs569421 genotype:case group,TT genotype 85（54.1%）,TC genotype 59（37.1%）,CC genotype 14（8.8%）.Control group,TT genotype 86（54.1%）,TC genotype 59（37.6%）,CC genotype 14（8.3%）;6 The distribution of GPX3 gene SNPs genotype between case and control population:rs3828599 genotype:case group,GG genotype 46（28.9%）,GA genotype 70（44.0%）,AA genotype 43（27.0%）.Control group,GG genotype 42（26.4%）,GA genotype74（46.5%）,AA genotype 43（27.0%）;rs8177429 genotype:case group,GG genotype 47（29.9%）,GC genotype 77（49.0%）,CC genotype 33（21.0%）.Control group,GG genotype 43（27.2%）,GC genotype75（47.5%）,CC genotype 40（25.3%）;rs3792795genotype:case group,CC genotype 51（32.1%）,CT genotype 75（47.2%）,TT gnotype 33（20.8%）.Control group,CC genotype 46（29.7%）,CT genotype 75（48.4%）,TT geenotype 34（21.9%）;rs11548genotype:case group,CC genotype 51（32.1%）,CT genotype 76（47.8%）,TT genotype 32（20.1%）.Control group,CC genotype 46（29.1%）,CT genotype 77（48.7%）,TT genotype 35（22.2%）;rs2070593genotype:case group,GG genotype 24（15.3%）,GA genotype 76（48.4%）,AA genotype 57（36.3%）.Control group,GG genotype 24（15.1%）,GA genotype69（43.4%）,AA genotype 66（41.5%）;rs8177431genotype:case group,GG genotype 24（15.3%）,GA genotype 76（48.4%）,AA genotype 57（36.3%）.Control group,GG genotype 42（26.4%）,GA genotype74（46.5%）,AA genotype 43（27.0%）;7 The distribution of TRIOBP gene SNPs genotype between case and control population:rs9619704 genotype:case group,AA genotype 56（35.4%）,AG genotype 72（45.6%）,GG genotype 30（19.0%）.Control group,AA genotype 55（34.8%）,AG genotype76（48.1%）,GG genotype 27（17.1%）;rs9610841genotype:case group,CC genotype 31（19.6%）,CA genotype 74（46.8%）,AA genotype 53（33.5%）.Control group,CC genotype 30（18.9%）,CA genotype76（47.8%）,AA genotype 53（33.3%）;rs5756805genotype:case group,CC genotype 28（17.9%）,CT genotype 72（46.2%）,TT genotype 56（35.9%）.Control group,CC genotype 28（17.7%）,CT genotype74（46.8%）,TT genotype 56（35.4%）;rs3788528genotype:case group,CC genotype 56（35.7%）,CT genotype 73（46.5%）,TT genotype 26（17.8%）.Control group,CC genotype 56（35.7%）,CT genotype 75（47.8%）,TT genotype 26（16.5%）;rs3788530 genotype:case group,AA genotype 57（35.4%）,AG genotype 72（45.6%）,GG genotype 30（19.0%）.Control group,AA genotype 57（35.8%）,AG genotype75（47.2%）,GG genotype 27（17.0%）;8 We analyzed the distribution of 14 SNPs between 2 groups,and evaluated the main effect of all SNPs with NIHL after controlling the confounding factors（BMI）by conditional logistic regression model.However,there’s no significant values whether in SNPs genetypes,alleles or dominance-recessiveness model（P>0.05）.Conclusions1 Cumulative noise exposure,age,and shift working（two shifts and three shifts）may be the risks of noise-induced hearing loss.2 Noise-induced hearing loss may not associate with the single nucleotide polymorphisms of GATA3 gene（rs3802604,rs569421）.3 Noise-induced hearing loss may not associate with the single nucleotide polymorphisms of GPX3 gene（rs3828599,rs8177429,rs3792795,rs11548,rs2070593,rs8177431,rs8177435）.4 Noise-induced hearing loss may not associate with the single nucleotide polymorphisms of TRIOBP gene（rs9619704,rs9610841,rs5756805,rs3788528,rs3788530）.