Hearing loss is a highly prevalent and debilitating neurosensory disorder associated with substantially reduced quality of life and overall health. It currently affects 430 million people worldwide; by 2050 this is expected to increase to nearly 2.5 billion and result 1 in 10 people requiring rehabilitation. About 50% of cases are predicted to have a genetic basis, however hearing loss can also be caused by other factors such as age, ototoxic drugs, noise, infection or injury. Low-cost next generation sequencing technologies have facilitated many genome-wide association studies (GWAS) and exome sequencing projects that have identified hundreds of variants and genes associated with hearing loss. There are currently more than 150 loci and over 100 genes associated with non- syndromic hearing loss, however few candidate genes have been identified for complex phenotypes such as age-related hearing loss (ARHL) or presbycusis, which is becoming increasingly common as the population ages. A GWAS conducted to identify candidate genes associated with ARHL identified 44 independent genomic loci associated with hearing loss. A nearest gene was mapped for each SNP identified in this study, yet how this SNP influences gene function in hearing loss has not been determined. Establishing a linkage between the target genes and the disease phenotype is a huge challenge that ultimately affects the correct diagnosis; generating similar phenotypes upon gene inactivation in animal models can establish a strong support for a candidate gene. We identified 39 orthologs of 44 GWAS candidate genes in zebrafish, and further selected 29 novel genes that will be tested functionally for their role in hearing loss by (1) generating a library of zebrafish mutants for 29 (and paralogs) candidate genes associated with ARHL (2) analyzing these mutants via a high-throughput phenotyping pipeline including morphological, cellular, and behavioral phenotypes. Identifying the functional consequences of the candidate genes in zebrafish will yield mechanistic insights in disease pathogenesis.