Study links precise phenotyping to better hearing loss prediction

A 16,000-participant analysis conducted by Vanderbilt University Medical Center investigators has confirmed that precise clinical phenotyping yields superior genetic predictions for sensorineural hearing loss compared to standard diagnostic codes. The study, reviewed on October 8, 2026, highlights how granular audiometric data enhances the identification of genetic variants associated with the condition.

Limitations of traditional diagnostic codes

The research team, comprising experts in clinical audiology, ear surgery, and general otolaryngology, was led by co-first author Andie DeFreese, AuD, a clinical audiologist and PhD candidate in the Department of Hearing and Speech Sciences at Vanderbilt Health. DeFreese explained that while physiological measurements exist, understanding the subjective experience of hearing loss remains complex. Traditional medical diagnostic codes, primarily designed for billing, often fail to capture the nuance of individual cases.

"Diagnostic codes are very common because that's the data that's available in large genetic biobanks that facilitate this research," DeFreese stated. She noted that relying on these codes creates a "gray area" where accurately defining who has hearing loss becomes difficult. To address this, the researchers de-identified information from their clinical audiometric database and integrated it with BioVU, Vanderbilt Health’s biobank of anonymous genetic samples. This pairing allowed access to genetic data from consenting participants while utilizing a more precise phenotype for hearing loss.

Polygenic risk scores show improved accuracy

By applying polygenic risk scores developed from these precise phenotypes to a new population's genetic data, the team found that these scores predicted individuals with hearing loss more effectively than those derived from diagnostic codes. DeFreese emphasized that this enhanced predictive power underscores the value of precision phenotyping not only for hearing loss but across all medical disciplines employing risk prediction approaches.

"With a sample size of 16,000, we were able to better discover genetic variants that are associated with hearing loss," DeFreese said. The findings suggest that building biobanks capable of supporting precision phenotyping is crucial for discovery. For hearing loss specifically, this approach improves risk prediction, potentially enabling the development of tools integrated into electronic health records or consumer-based genetic tests to identify patients at varying levels of risk.

Clinical integration and future applications

Taha Jan, MD, Assistant Professor of Otolaryngology-Head and Neck Surgery and corresponding author, highlighted the significance of this collaborative work as opportunities for advancements in hearing health expand. He pointed to recent regulatory developments, noting that the Food and Drug Administration has approved its first gene therapy for genetic hearing loss. "Genetics is becoming increasingly relevant for precision therapy," Jan said. "This work is an example of how our world-class clinicians and scientists at Vanderbilt Health are pushing the boundaries of precision medicine."

DeFreese indicated that further research aims to build systems that determine not just the presence of hearing loss, but also the specific configuration or affected frequencies. She argued that institutions like Vanderbilt Health, with strong intersections between research and clinical care, are well-positioned to evaluate methodologies such as precise phenotyping that complement standard practices. Additional authors included Tanguy Rubat du Mérac, MSc; Quanhu Sheng, PhD, Associate Professor of Biostatistics; and Srishti Nayak, PhD, Assistant Professor of Otolaryngology-Head and Neck Surgery.

The study received funding from 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 (grants R03DC021550, R21DC021276, R21DC023019).