Genetic Landscape of Hearing Loss in Brazilian Patients Reveals Population-Specific Variants and Clinical...

Hearing loss (HL) is the most prevalent sensory disorder globally and a major public health challenge in Brazil, affecting over 1.5 million individuals. While over 150 HL-associated genes have been identified, the genetic architecture in underrepresented populations remains poorly defined, often limiting diagnostic yield and precision medicine. We assessed the diagnostic performance of a comprehensive 218-gene HL panel in 99 Brazilian probands (78 non-syndromic; 21 syndromic) who had previously tested negative for GJB2/GJB6 (DFNB1) and MT-RNR1 (m.1555A>G) and did not have ear malformations. Targeted next-generation sequencing was followed by variant interpretation according to ACMG/AMP guidelines, segregation analysis, and longitudinal phenotypic re-evaluation. Integration of Brazil-specific allele-frequency data was used to refine variant classification. A molecular diagnosis or a candidate variant was identified in 61 probands, yielding an overall diagnostic yield of 43%-62%, depending on classification stringency. We identified 19 novel variants across 15 genes, with MYO7A and MYO15A as the most frequently implicated. Notably, 10.4% of patients initially diagnosed with non-syndromic HL carried pathogenic or likely pathogenic variants in syndromic genes (PEX6, BSND, USH1C, and WFS1), necessitating clinical reclassification. Segregation analysis and phenotypic reassessment further enabled the reclassification of three variants of uncertain significance (VUS). In syndromic cases, a molecular diagnosis was established in 41% of cases, including Usher, Waardenburg, Branchio-oto-renal, and Bartter syndromes. This first large-scale clinical genetic evaluation of hearing loss in Brazil demonstrates that comprehensive gene panels incorporating population-specific data significantly improve diagnostic accuracy. Our findings broaden the mutational landscape of HL-associated genes, reinforce the value of integrated genetic approaches for underrepresented populations, and underscore their direct impact on patient care and clinical management.