RT Journal Article
SR Electronic
T1 EyeG2P: an automated variant filtering approach improves efficiency of diagnostic genomic testing for inherited ophthalmic disorders
JF Journal of Medical Genetics
JO J Med Genet
FD BMJ Publishing Group Ltd
SP jmedgenet-2022-108618
DO 10.1136/jmg-2022-108618
A1 Eva Lenassi
A1 Ana Carvalho
A1 Anja Thormann
A1 Liam Abrahams
A1 Gavin Arno
A1 Tracy Fletcher
A1 Claire Hardcastle
A1 Javier Lopez
A1 Sarah E Hunt
A1 Patrick Short
A1 Panagiotis I Sergouniotis
A1 Michel Michaelides
A1 Andrew Webster
A1 Fiona Cunningham
A1 Simon C Ramsden
A1 Dalia Kasperaviciute
A1 David R Fitzpatrick
A1 Genomics England Research Consortium
A1 Graeme C Black
A1 Jamie M Ellingford
YR 2023
UL http://jmg.bmj.com/content/early/2023/01/19/jmg-2022-108618.abstract
AB Background Genomic variant prioritisation is one of the most significant bottlenecks to mainstream genomic testing in healthcare. Tools to improve precision while ensuring high recall are critical to successful mainstream clinical genomic testing, in particular for whole genome sequencing where millions of variants must be considered for each patient.Methods We developed EyeG2P, a publicly available database and web application using the Ensembl Variant Effect Predictor. EyeG2P is tailored for efficient variant prioritisation for individuals with inherited ophthalmic conditions. We assessed the sensitivity of EyeG2P in 1234 individuals with a broad range of eye conditions who had previously received a confirmed molecular diagnosis through routine genomic diagnostic approaches. For a prospective cohort of 83 individuals, we assessed the precision of EyeG2P in comparison with routine diagnostic approaches. For 10 additional individuals, we assessed the utility of EyeG2P for whole genome analysis.Results EyeG2P had 99.5% sensitivity for genomic variants previously identified as clinically relevant through routine diagnostic analysis (n=1234 individuals). Prospectively, EyeG2P enabled a significant increase in precision (35% on average) in comparison with routine testing strategies (p<0.001). We demonstrate that incorporation of EyeG2P into whole genome sequencing analysis strategies can reduce the number of variants for analysis to six variants, on average, while maintaining high diagnostic yield.Conclusion Automated filtering of genomic variants through EyeG2P can increase the efficiency of diagnostic testing for individuals with a broad range of inherited ophthalmic disorders.Shareable data is freely available through public resources, as specified in relevant sections of the manuscript, and is included in this manuscript.