Unraveling the complex genetic landscape of OTOF-related hearing loss: a deep dive into cryptic variants and
Pei-Hsuan Lin1,2, Cheng-Yu Tsai2,3, Yu-Ting Chiang2,3
1Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, 100229, Taiwan.
Background:
Pathogenic variants in OTOF are a major cause of auditory synaptopathy. However, challenges remain in interpreting OTOF variants, including difficulties in confirming haplotype phasing using traditional short-read sequencing (SRS) due to the large gene size, the potential incomplete penetrance of certain variants, and difficulties in assessing variants at non-canonical splice sites. This study aims to revisit the genetic landscape of OTOF variants in a Taiwanese non-syndromic auditory neuropathy spectrum disorder (ANSD) cohort using a combination of sequencing technologies, predictive tools, and experimental validations.
Methods:
We performed SRS to analyze OTOF variants in 65 unrelated Taiwanese patients diagnosed with non-syndromic ANSD, complemented by long-read sequencing (LRS) for haplotype phasing. A prediction-to-validation pipeline was implemented to assess the pathogenicity of cryptic variants using SpliceAI software and minigene assays.
Results:
Biallelic pathogenic OTOF variants were identified in 33 patients (50.8%), while monoallelic variants were found in five patients. Three novel variants, c.3864G > A (p.Ala1288 =), c.4501G > A (p.Ala1501Thr), and c.5813 + 2T > C, were detected. The pathogenicity of two non-canonical mis-splicing variants, c.3894 + 5G > C and c.3864G > A (p.Ala1288 =), was confirmed by minigene assays. LRS-based haplotype phasing revealed that the common missense variant c.5098G > C (p.Glu1700Gln) and the novel variant c.5975A > G (p.Lys1992Arg) are in cis and form a founder pathogenic allele in the Taiwanese population.
Conclusions:
Our study highlights the genetic heterogeneity of DFNB9 and emphasizes the importance of population-specific variant interpretation. The integration of advanced sequencing technologies, predictive algorithms, and functional validation assays will improve the accuracy of molecular diagnosis and inform personalized treatment strategies for individuals with DFNB9.
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