World-wide, hearing loss and traumatic brain injury (TBI) are the top two risk factors for dementia in mid- life. Together the two disorders account for approximately 11% of the potentially modifiable attributable risk fraction for dementia. Chronic auditory sensory disorders including hearing damage and difficulties understanding speech in noise complicate recovery even from mild TBI. In addition, comorbidities of hearing difficulties include loss of employability, depression, difficulties with cognition, and suicide. The use of hearing aids is associated with the delay of the onset of age-related dementia, and significant genetic overlap exists between Alzheimer’s disease and hearing loss. A critical gap in our understanding consists of genetic vulnerabilities to hearing loss related to TBI. Using the largest global genomic dataset with audiogram and TBI data, our overarching objective is to identify genetic variants associated with hearing loss with and without the environmental incidence of TBI. The difference in TBI- induced hearing loss and hearing difficulties secondary to aging and noise is indicated by anatomic studies that demonstrate a central neurologic component with TBI in addition to peripheral cochlear damage. We propose to perform the first large genomic studies with objective audiologic data, using over 1.2 million audiograms in 373,744 Veteran participants, in the largest study to date of a specific etiology for hearing impairment. The study will include audiogram thresholds, speech psychometrics, and a measure of speech intelligibility in noise to identify genetic variants, genes, and pathways associated with hearing difficulties secondary to TBI. We will then assess a polygenic risk score (PRS) to predict those Veterans most at risk for dementia who might benefit from early combined treatment, such as hearing augmentation and neurocognitive therapy. The first specific aim will establish criteria on multiple phenotypes for hearing loss. We have aggregated audiogram data from the VA and DoD medical record to calculate pure-tone averages, principal components, and a measure of individual deviation from a predicted speech intelligibility index. We will then characterize TBI, mild cognitive impairment, and dementia according to self-report on MVP questionnaires and diagnoses in the electronic health record. In the second aim, we will conduct separate GWAS in individuals of diverse ancestries represented in the US military using multiple phenotypes, subsequently adding TBI as a Gene x Environment variable. Analysis of variants and genes identified will consist of functional annotation, including correlations with other disorders and traits, categorizing relevant molecular pathways, and incorporating transcription information from the cochlea and brain to focus our results to genes relevant to hearing impairment. An exploratory aim will formulate and test a polygenic risk score for hearing loss following TBI. A predictive model fo...