Precision Phenotyping With Audiometric Data and Gene Discovery for Sensorineural Hearing Loss

Importance The genetic architecture underlying hearing sensitivity as a quantitative trait is critical for advancing precision medicine in hearing health. Despite extensive genome-wide association study (GWAS) efforts, few strong genetic drivers have been identified. Objective To compare the sensitivity for detecting genetic variants associated with sensorineural hearing loss (SNHL) using precision phenotyping with pure-tone averages (PTAs) with common phenotyping using diagnostic coding approaches. Design, Setting, and Participants In this genetic association study, 2 separate GWASs were conducted using different phenotyping approaches for SNHL: (1) diagnostic code control and (2) precision phenotyping with PTA data. Whole-genome sequencing data from a population with European genetic ancestry collected at a single tertiary center biobank was used. For the control GWAS based on diagnostic codes, case and control participants were defined using primarily International Classification of Diseases, Ninth Revision ( ICD-9 ) and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision ( ICD-10 ) diagnosis and procedure codes related to SNHL hearing loss. For the precision phenotyping GWAS, hearing status was defined as a continuous variable, using the standard 3-frequency PTA of the better hearing ear from the audiogram. Data analysis was conducted from August 2025 to April 2026. Main Outcomes and Measures GWAS summary statistics were used to calculate estimates of single-nucleotide variant (SNV)–based heritability for PTA and ICD phenotypes; to map the genetic risk loci to candidate genes using functional annotation; to evaluate genetic correlations with existing GWASs; and to calculate polygenic risk scores for testing in an independent cohort from the National Institutes of Health’s All of Us Research Program. Results Overall, 10 164 case participants (mean [SD] age, 63.9 [21.3] years; 5118 [50.4%] female) and 51 305 control participants (mean [SD] age, 51.1 [21.0] years; 28 784 [56.1%] female) were included in the first GWAS; 16 057 participants with PTA (mean [SD] age, 55.5 [21.8] years; 9147 [57.0%] female) were included in the second GWAS. PTA-based GWAS identified 3 genome-wide significant loci mapped to 4 genes: EML6 , SPTBN1 , ARHGEF28 , and EYA4 (SNV-based heritability estimate [ h 2 ] = 11.78%; SE = 2.84%). ICD -based GWAS identified no significant loci ( h 2 = 2.90%; SE = 0.77%). Genome-wide correlations between the PTA-based GWAS and 3 hearing-related ability traits were found (eg, PTA-based GWAS and hearing aid use: r = 0.985; SE = 0.163; P = 1.56 × 10 −9 ). In the All of Us cohort, PTA-derived polygenic risk scores were significantly associated with self-reported deafness (odds ratio [OR], 1.09; 95% CI, 1.07-1.12), whereas ICD -derived scores were not (OR, 1.00; 95% CI, 0.97-1.02). Conclusions and Relevance In this genetic association study, precision phenotyping using audiometric PTAs improved genetic discovery for SNHL compared with diagnostic code–based approaches. Higher heritability estimates, identification of genome-wide significant loci, and stronger polygenic risk estimation indicate that quantitative hearing measures better capture genetic architecture, supporting precision medicine in hearing health.