An investigation into the genetic risk of age-related hearing impairment

Abstract

Age-related hearing impairment (ARHI) is the most common sensory impairment in the ageing population. Disabling hearing loss affects a third of people aged 65 and is a major risk factor for dementia. Little is currently known about genetic risk factors and the underlying pathology of ARHI, making it a challenge to develop accurate diagnoses and treatment strategies. ARHI is a thought to be a polygenic, heterogeneous trait and so under the common trait common variant hypothesis, large studies are required to achieve the necessary statistical power to identify multiple genetic variants with small effect sizes. Previous studies have been limited by reduced sample sizes and the absence of a comprehensive, consistent definition of ARHI. In this thesis, the UK Biobank (UKBB) resource was used to perform two genome-wide association studies (GWAS) that were a magnitude larger than previous ARHI GWAS (n>250,000) and various methods were used to validate and investigate the subsequent associations. The results support the use of GWAS to uncover putative ARHI genetic risk variants. Forty-four independent genome-wide significant loci (p < 5E-08) were identified from the two GWAS studies, a 9-fold increase in the number of loci previously associated with common adult hearing impairment. A quarter of the identified loci contain genes that are implicated in other forms of hearing loss, while the remaining are novel gene candidates. The work demonstrates the viability of using self-report measures of adult hearing impairment for genetic discovery in large samples for the first time. Further, genetic correlation analysis revealed strong positive correlations with multiple personality and psychological traits for the first time. Multiple associations were validated via a replication meta-analysis, and tissue-specific expression was observed with immunohistochemistry for three candidate genes at significantly associated loci. All associated loci were evaluated for use in functional analysis, providing a framework for future studies.

Date of Award	1 Jan 2021
Original language	English
Awarding Institution	King's College London
Supervisor	Frances Williams (Supervisor)