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 [h2] = 11.78%; SE = 2.84%). ICD-based GWAS identified no significant loci (h2 = 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.