EyeG2P: an automated variant filtering approach improves efficiency of diagnostic genomic testing for inherited ophthalmic disorders

Abstract

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.

Keywords: Eye Diseases; Genetic Variation; Genomics.

Figure 1

Molecular findings for 1228 individuals with a confirmed molecular diagnosis for inherited ophthalmic disorders. (A) Eye gene2phenotype (EyeG2P) is a plugin for the Ensembl variant effector enabling automated variant filtering and selection of variants in a disease-causing state (vcf, Variant Call Format). The specific requirements of variants to be retained can be set by the user and, through developments in the G2P software for the work described in this manuscript, can now include predefined lists of genomic variants, including pathogenic variants in ClinVar, variants predicted to impact splicing and complex alleles that comprised variants above the defined variant frequency threshold. (B) The predicted molecular consequences of 1267 variants identified as a cause of disease in 1228 individuals demonstrating the wide range of variant consequences that can be prioritised by EyeG2P (UTR, untranslated region). (C) The number of variants identified as a cause of disease in 166 genes by their proven zygosity. Hemizygous variants are included in the Homozygous display.

Figure 2

Direct comparison between EyeG2P and routine testing approaches identifies increased precision and efficiency of EyeG2P as a first-tier analysis approach. (A) The number of variants requiring analysis by clinical scientists for 83 individuals receiving genetic testing for inherited ophthalmic disorders (VUS, variant of uncertain significance). (B) Summary of the molecular consequences of pathogenic variants identified to underpin confirmed molecular diagnoses in 31 individuals. (C) The precision (PPV) of different testing approaches for 31 individuals receiving a diagnosis through both approaches. PPV, positive predictive value.

Figure 3

EyeG2P effectively prioritises pathogenic variation from whole genome sequencing data sets. The median and range of genomic variants identified across 10 individuals with whole genome sequencing analysis are shown at each stage of the filtering process. The complete list of clinically reported pathogenic and likely pathogenic variants prioritised by EyeG2P as a cause of inherited ophthalmic disorders is shown (genomic coordinates refer to the GRCh38 genome build). gnomAD, Genome Aggregation Database; indels, small insertion and deletion events; SNVs, single nucleotide variant; SVs, structural variants.