TY - JOUR 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 DO - 10.1136/jmg-2022-108618 SP - jmedgenet-2022-108618 AU - Eva Lenassi AU - Ana Carvalho AU - Anja Thormann AU - Liam Abrahams AU - Gavin Arno AU - Tracy Fletcher AU - Claire Hardcastle AU - Javier Lopez AU - Sarah E Hunt AU - Patrick Short AU - Panagiotis I Sergouniotis AU - Michel Michaelides AU - Andrew Webster AU - Fiona Cunningham AU - Simon C Ramsden AU - Dalia Kasperaviciute AU - David R Fitzpatrick AU - Genomics England Research Consortium AU - Graeme C Black AU - Jamie M Ellingford Y1 - 2023/01/20 UR - http://jmg.bmj.com/content/early/2023/01/19/jmg-2022-108618.abstract N2 - 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. ER -