Genome-wide association analysis demonstrates the highly polygenic character of age-related hearing impairment

Abstract

We performed a genome-wide association study (GWAS) to identify the genes responsible for age-related hearing impairment (ARHI), the most common form of hearing impairment in the elderly. Analysis of common variants, with and without adjustment for stratification and environmental covariates, rare variants and interactions, as well as gene-set enrichment analysis, showed no variants with genome-wide significance. No evidence for replication of any previously reported genes was found. A study of the genetic architecture indicates for the first time that ARHI is highly polygenic in nature, with probably no major genes involved. The phenotype depends on the aggregated effect of a large number of SNPs, of which the individual effects are undetectable in a modestly powered GWAS. We estimated that 22% of the variance in our data set can be explained by the collective effect of all genotyped SNPs. A score analysis showed a modest enrichment in causative SNPs among the SNPs with a P-value below 0.01.

Figure 1

Schematic representation of the sample selection. Starting from a total sample size of 2161, the most informative samples were selected for genotyping based upon principle component analysis. Samples with an extreme value for either one of the first three PCs were included for genotyping. After various quality control steps, 1489 samples were included in the association analyses.

Figure 2

Manhattan plot for the common variant analysis. The figure shows the logarithm of the P-values for the association of the genotypes versus each of the three PC phenotypes. P-values above 0.01 are not shown. Red dots indicate the SNPs in the genes that show the strongest association in the current study. Blue dots highlight the genes with a previously reported association with ARHI by Girotto et al, plus the GRM7 gene reported by Friedman et al and the IQGAP2 gene reported by Van Laer et al.

Figure 3

Score analysis. Pearson correlation coefficients between the observed phenotype (PC1) and the predicted phenotype from the individuals in the validation set are shown in black. Correlation coefficients between these predicted phenotypes and an independent phenotype (PC2), which served as a negative control, are shown in red. Error bars denote the standard errors obtained by 10-fold cross-validation.