Powerful use of automated prioritization of candidate variants in genetic hearing loss with extreme etiologic heterogeneity

So Young Kim,Doo Hyun Koh,Byung Yoon Choi,Seungmin Lee,Sohyun Hwang,Jin Hee Han,Namju Justin Kim,Bong Jik Kim,Doo Yi Oh,So Min Lee,Go Hun Seo,Bonggi Kim,Nayoung Yi,Moo Kyun Park,Changwon Keum

doi:10.1038/s41598-021-99007-3

Abstract

Variant prioritization of exome sequencing (ES) data for molecular diagnosis of sensorineural hearing loss (SNHL) with extreme etiologic heterogeneity poses a significant challenge. This study used an automated variant prioritization system (“EVIDENCE”) to analyze SNHL patient data and assess its diagnostic accuracy. We performed ES of 263 probands manifesting mild to moderate or higher degrees of SNHL. Candidate variants were classified according to the 2015 American College of Medical Genetics guidelines, and we compared the accuracy, call rates, and efficiency of variant prioritizations performed manually by humans or using EVIDENCE. In our in silico panel, 21 synthetic cases were successfully analyzed by EVIDENCE. In our cohort, the ES diagnostic yield for SNHL by manual analysis was 50.19% (132/263) and 50.95% (134/263) by EVIDENCE. EVIDENCE processed ES data 24-fold faster than humans, and the concordant call rate between humans and EVIDENCE was 97.72% (257/263). Additionally, EVIDENCE outperformed human accuracy, especially at discovering causative variants of rare syndromic deafness, whereas flexible interpretations that required predefined specific genotype–phenotype correlations were possible only by manual prioritization. The automated variant prioritization system remarkably facilitated the molecular diagnosis of hearing loss with high accuracy and efficiency, fostering the popularization of molecular genetic diagnosis of SNHL.

Highlights

Variant prioritization of exome sequencing (ES) data for molecular diagnosis of sensorineural hearing loss (SNHL) with extreme etiologic heterogeneity poses a significant challenge
We found that 50.19% (132/263) of SNHL probands carried candidate variants, with no candidate variants identified in the remaining 49.81% (131/263) from ES data analyzed by humans (Table 1)
EVIDENCE facilitated the exploration of candidate variants from ES, and its application saved significant time and effort during variant prioritization and improved the detection rate for pathogenic and likely pathogenic variants of hearing loss

Summary

Introduction

Variant prioritization of exome sequencing (ES) data for molecular diagnosis of sensorineural hearing loss (SNHL) with extreme etiologic heterogeneity poses a significant challenge. This study used an automated variant prioritization system (“EVIDENCE”) to analyze SNHL patient data and assess its diagnostic accuracy. Candidate variants were classified according to the 2015 American College of Medical Genetics guidelines, and we compared the accuracy, call rates, and efficiency of variant prioritizations performed manually by humans or using EVIDENCE. The automated variant prioritization system remarkably facilitated the molecular diagnosis of hearing loss with high accuracy and efficiency, fostering the popularization of molecular genetic diagnosis of SNHL. Benchmark data were developed to validate the performance of these automatic variant prioritization tools using a synthetic patient p opulation[17] or clinical cohorts with heterogeneous phenotypic e ntities[19,20]. Due to the heterogeneous disease entities of previous cohorts, it has not been possible to estimate the diagnostic yield for a single phenotypic disease that could be compared with previous published data

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Discussion

Conclusion