PT - JOURNAL ARTICLE AU - Leslie Patricia Molina-Ramírez AU - Claire Kyle AU - Jamie M Ellingford AU - Ronnie Wright AU - Algy Taylor AU - Sanjeev S Bhaskar AU - Christopher Campbell AU - Harriet Jackson AU - Adele Fairclough AU - Abigail Rousseau AU - George J Burghel AU - Laura Dutton AU - Siddharth Banka AU - Tracy A Briggs AU - Jill Clayton-Smith AU - Sofia Douzgou AU - Elizabeth A Jones AU - Helen M Kingston AU - Bronwyn Kerr AU - John Ealing AU - Suresh Somarathi AU - Kate E Chandler AU - Helen M Stuart AU - Emma MM Burkitt-Wright AU - William G Newman AU - Iain A Bruce AU - Graeme C Black AU - David Gokhale TI - Personalised virtual gene panels reduce interpretation workload and maintain diagnostic rates of proband-only clinical exome sequencing for rare disorders AID - 10.1136/jmedgenet-2020-107303 DP - 2021 Apr 19 TA - Journal of Medical Genetics PG - jmedgenet-2020-107303 4099 - http://jmg.bmj.com/content/early/2021/04/20/jmedgenet-2020-107303.short 4100 - http://jmg.bmj.com/content/early/2021/04/20/jmedgenet-2020-107303.full AB - Purpose The increased adoption of genomic strategies in the clinic makes it imperative for diagnostic laboratories to improve the efficiency of variant interpretation. Clinical exome sequencing (CES) is becoming a valuable diagnostic tool, capable of meeting the diagnostic demand imposed by the vast array of different rare monogenic disorders. We have assessed a clinician-led and phenotype-based approach for virtual gene panel generation for analysis of targeted CES in patients with rare disease in a single institution.Methods Retrospective survey of 400 consecutive cases presumed by clinicians to have rare monogenic disorders, referred on singleton basis for targeted CES. We evaluated diagnostic yield and variant workload to characterise the usefulness of a clinician-led approach for generation of virtual gene panels that can incorporate up to three different phenotype-driven gene selection methods.Results Abnormalities of the nervous system (54.5%), including intellectual disability, head and neck (19%), skeletal system (16%), ear (15%) and eye (15%) were the most common clinical features reported in referrals. Combined phenotype-driven strategies for virtual gene panel generation were used in 57% of cases. On average, 7.3 variants (median=5) per case were retained for clinical interpretation. The overall diagnostic rate of proband-only CES using personalised phenotype-driven virtual gene panels was 24%.Conclusions Our results show that personalised virtual gene panels are a cost-effective approach for variant analysis of CES, maintaining diagnostic yield and optimising the use of resources for clinical genomic sequencing in the clinic.All data relevant to the study are included in the article or uploaded as supplementary information.