Researchers at Vanderbilt Health have developed precise polygenic risk scores for sensorineural hearing loss by pairing clinical audiometric testing data with the BioVU biobank, overcoming limitations of traditional medical billing codes.
Precision Phenotyping Improves Genetic Risk Models for Hearing Loss
- Precision Phenotyping: Researchers used detailed hearing threshold measurements instead of generic medical billing codes to classify hearing loss, yielding much sharper genetic data.
- Polygenic Risk Scores: These refined phenotypes allowed scientists to build stronger predictive genetic models, tested successfully in an independent validation cohort.
- Future Screening: The methodology paves the way for electronic health record tools or consumer genetic tests that can estimate an individual’s risk before hearing loss begins.
Transitioning From Billing Codes to Clinical Audiometry in Genetic Biobanks
Large-scale genomic studies investigating sensorineural hearing loss relied heavily on diagnostic codes extracted from electronic health record systems. While these alphanumeric codes efficiently serve hospital administrative tasks and medical billing, they fail to capture the nuanced realities of auditory function. According to Andie DeFreese, AuD, a clinical audiologist, PhD candidate in the Department of Hearing and Speech Sciences at Vanderbilt Health, and co-first author of the study, diagnostic codes introduce a troublesome gray area. Because two patients can share an identical billing code while experiencing vastly different degrees, patterns, or frequency thresholds of hearing impairment, genetic associations derived from those codes are frequently blunted by data noise.
To resolve this translational barrier, the Vanderbilt research team de-identified and cross-referenced complete clinical audiometric records—encompassing comprehensive hearing threshold measurements across multiple frequencies—with the genomic data of 16,000 consenting participants stored within BioVU, Vanderbilt Health’s anonymous biobank. This integration of high-resolution audiometric metrics with genomic repositories produced higher heritability estimates, identified genome-wide significant loci, and established much stronger polygenic risk estimation.
Validating Audiometric Polygenic Risk Scores Across Independent Populations
Armed with a more granular quantitative trait representation of hearing sensitivity, the research team constructed polygenic risk scores designed to map the complex genetic architecture underlying sensorineural hearing loss. When these models were applied to an independent validation cohort’s genetic data, they demonstrated significantly superior predictive power compared to risk scores modeled strictly on standard diagnostic codes. The findings confirm that quantitative hearing measures capture underlying genetic architecture far more accurately than categorical administrative labels.
Taha Jan, MD, Assistant Professor of Otolaryngology-Head and Neck Surgery and corresponding author of the study, emphasized the clinical timeliness of the work. Genetics is becoming increasingly relevant for precision therapy, especially now that the Food and Drug Administration has approved its first gene therapy for genetic hearing loss,
Jan stated. This work is an example of how our world-class clinicians and scientists at Vanderbilt Health are pushing the boundaries of precision medicine.
The research team comprised DeFreese and Jan alongside Tanguy Rubat du Mérac, MSc; Quanhu Sheng, PhD, Associate Professor of Biostatistics; and Srishti Nayak, PhD, Assistant Professor of Otolaryngology-Head and Neck Surgery.
| Methodology Metric | Diagnostic Code Approach | Precision Phenotyping Approach |
|---|---|---|
| Data Source Primary | Medical billing codes | Quantitative audiometric test records |
| Sample Population Size | Large biobank administrative datasets | 16,000 consenting BioVU participants |
| Predictive Accuracy | Blunted by broad categorical noise | Superior risk score stratification |
Vanderbilt Researchers Develop Tools to Predict Auditory Deterioration
The implications of this methodology extend well beyond academic discovery. By demonstrating that precision phenotyping significantly improves risk prediction, the Vanderbilt investigators have laid a foundation for future clinical tools. DeFreese noted that subsequent research phases will seek to build systems capable of predicting not just the presence or absence of hearing loss, but also the specific auditory configurations and frequencies likely to deteriorate over time.
Funding for the study was provided by a Vanderbilt Lacy-Fischer Interdisciplinary Grant, an American Otological Society Fellowship Grant, and the National Institute on Deafness and Other Communication Disorders, part of the National Institutes of Health under grants R03DC021550, R21DC021276, R21DC023019, K08DC019683, and R21DC022058. The research was published on October 1, 2026, in JAMA Otolaryngology–Head & Neck Surgery.
References
- DeFreese, A. J., et al. (2026). Precision Phenotyping With Audiometric Data and Gene Discovery for Sensorineural Hearing Loss. JAMA Otolaryngology–Head & Neck Surgery. DOI: 10.1001/jamaoto.2026.3089.
