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Abstract：
BACKGROUND: This study aimed to screen and validate noise-induced hearing loss (NIHL) associated single nucleotide polymorphisms (SNPs), construct genetic risk prediction models, and evaluate higher-order gene-gene, gene-environment interactions for NIHL in Chinese population.
METHODS: First, 83 cases and 83 controls were recruited and 60 candidate SNPs were genotyped. Then SNPs with promising results were validated in another case-control study (153 cases and 252 controls). NIHL-associated SNPs were identified by logistic regression analysis, and a genetic risk model was constructed based on the genetic risk score (GRS), and classification and regression tree (CART) analysis was used to evaluate interactions among gene-gene and gene-environment.
RESULTS: Six SNPs in five genes were significantly associated with NIHL risk (p < 0.05). A positive dose-response relationship was found between GRS values and NIHL risk. CART analysis indicated that strongest interaction was among subjects with age ≥ 45 years and cumulative noise exposure ≥ 95 [dB(A)·years], without personal protective equipment, and carried GJB2 rs3751385 (AA/AB) and FAS rs1468063 (AA/AB) (OR = 10.038, 95% CI = 2.770, 47.792), compared with the referent group. CDH23, FAS, GJB2, PTPRN2 and SIK3 may be NIHL susceptibility genes.
CONCLUSIONS: GRS values may be utilized in the evaluation of the cumulative effect of genetic risk for NIHL based on NIHL-associated SNPs. Gene-gene, gene-environment interaction patterns play an important role in the incidence of NIHL.
METHODS: First, 83 cases and 83 controls were recruited and 60 candidate SNPs were genotyped. Then SNPs with promising results were validated in another case-control study (153 cases and 252 controls). NIHL-associated SNPs were identified by logistic regression analysis, and a genetic risk model was constructed based on the genetic risk score (GRS), and classification and regression tree (CART) analysis was used to evaluate interactions among gene-gene and gene-environment.
RESULTS: Six SNPs in five genes were significantly associated with NIHL risk (p < 0.05). A positive dose-response relationship was found between GRS values and NIHL risk. CART analysis indicated that strongest interaction was among subjects with age ≥ 45 years and cumulative noise exposure ≥ 95 [dB(A)·years], without personal protective equipment, and carried GJB2 rs3751385 (AA/AB) and FAS rs1468063 (AA/AB) (OR = 10.038, 95% CI = 2.770, 47.792), compared with the referent group. CDH23, FAS, GJB2, PTPRN2 and SIK3 may be NIHL susceptibility genes.
CONCLUSIONS: GRS values may be utilized in the evaluation of the cumulative effect of genetic risk for NIHL based on NIHL-associated SNPs. Gene-gene, gene-environment interaction patterns play an important role in the incidence of NIHL.
摘要：
背景：这项研究旨在筛选和验证噪声诱发的听力损失（NIHL）相关的单核苷酸多态性（SNP），构建遗传风险预测模型，并评估高阶基因-基因，中国人群NIHL的基因-环境相互作用。
方法：首先，招募83例病例和83例对照，并对60个候选SNP进行基因分型。然后在另一项病例对照研究（153例和252例对照）中验证了具有良好结果的SNP。NIHL相关SNP通过logistic回归分析进行鉴定，基于遗传风险评分(GRS)构建遗传风险模型,分类和回归树（CART）分析用于评估基因-基因和基因-环境之间的相互作用。
结果：5个基因中的6个SNP与NIHL风险显著相关(p<0.05)。GRS值与NIHL风险之间存在正的剂量反应关系。CART分析表明，年龄≥45岁和累积噪声暴露≥95[dB（A）·年]的受试者之间的相互作用最强，没有个人防护装备，并携带GJB2rs3751385（AA/AB）和FASrs1468063（AA/AB）（OR=10.038，95％CI=2.770，47.792），与参考组进行比较。CDH23,FAS,GJB2、PTPRN2和SIK3可能是NIHL易感基因。
结论：GRS值可用于基于NIHL相关SNP评估NIHL遗传风险的累积效应。基因-基因,基因-环境相互作用模式在NIHL的发病中起着重要作用。
方法：首先，招募83例病例和83例对照，并对60个候选SNP进行基因分型。然后在另一项病例对照研究（153例和252例对照）中验证了具有良好结果的SNP。NIHL相关SNP通过logistic回归分析进行鉴定，基于遗传风险评分(GRS)构建遗传风险模型,分类和回归树（CART）分析用于评估基因-基因和基因-环境之间的相互作用。
结果：5个基因中的6个SNP与NIHL风险显著相关(p<0.05)。GRS值与NIHL风险之间存在正的剂量反应关系。CART分析表明，年龄≥45岁和累积噪声暴露≥95[dB（A）·年]的受试者之间的相互作用最强，没有个人防护装备，并携带GJB2rs3751385（AA/AB）和FASrs1468063（AA/AB）（OR=10.038，95％CI=2.770，47.792），与参考组进行比较。CDH23,FAS,GJB2、PTPRN2和SIK3可能是NIHL易感基因。
结论：GRS值可用于基于NIHL相关SNP评估NIHL遗传风险的累积效应。基因-基因,基因-环境相互作用模式在NIHL的发病中起着重要作用。
