TY - JOUR T1 - Uncovering the burden of hidden ciliopathies in the 100 000 Genomes Project: a reverse phenotyping approach JF - Journal of Medical Genetics JO - J Med Genet SP - 1151 LP - 1164 DO - 10.1136/jmedgenet-2022-108476 VL - 59 IS - 12 AU - Sunayna Best AU - Jing Yu AU - Jenny Lord AU - Matthew Roche AU - Christopher Mark Watson AU - Roel P J Bevers AU - Alex Stuckey AU - Savita Madhusudhan AU - Rosalyn Jewell AU - Sanjay M Sisodiya AU - Siying Lin AU - Stephen Turner AU - Hannah Robinson AU - Joseph S Leslie AU - Emma Baple AU - Genomics England Research Consortium AU - Carmel Toomes AU - Chris Inglehearn AU - Gabrielle Wheway AU - Colin A Johnson Y1 - 2022/12/01 UR - http://jmg.bmj.com/content/59/12/1151.abstract N2 - Background The 100 000 Genomes Project (100K) recruited National Health Service patients with eligible rare diseases and cancer between 2016 and 2018. PanelApp virtual gene panels were applied to whole genome sequencing data according to Human Phenotyping Ontology (HPO) terms entered by recruiting clinicians to guide focused analysis.Methods We developed a reverse phenotyping strategy to identify 100K participants with pathogenic variants in nine prioritised disease genes (BBS1, BBS10, ALMS1, OFD1, DYNC2H1, WDR34, NPHP1, TMEM67, CEP290), representative of the full phenotypic spectrum of multisystemic primary ciliopathies. We mapped genotype data ‘backwards’ onto available clinical data to assess potential matches against phenotypes. Participants with novel molecular diagnoses and key clinical features compatible with the identified disease gene were reported to recruiting clinicians.Results We identified 62 reportable molecular diagnoses with variants in these nine ciliopathy genes. Forty-four have been reported by 100K, 5 were previously unreported and 13 are new diagnoses. We identified 11 participants with unreportable, novel molecular diagnoses, who lacked key clinical features to justify reporting to recruiting clinicians. Two participants had likely pathogenic structural variants and one a deep intronic predicted splice variant. These variants would not be prioritised for review by standard 100K diagnostic pipelines.Conclusion Reverse phenotyping improves the rate of successful molecular diagnosis for unsolved 100K participants with primary ciliopathies. Previous analyses likely missed these diagnoses because incomplete HPO term entry led to incorrect gene panel choice, meaning that pathogenic variants were not prioritised. Better phenotyping data are therefore essential for accurate variant interpretation and improved patient benefit.Data are available in a public, open access repository. Data are available on reasonable request.Full data are available in the Genomic England Secure Research Environment. All datasets are available in the re_gecip shared folder of the GEL research environment for approved researchers. Access to our folder containing variant data (re_gecip/shared_allGeCIPs/GW_SB) can be requested from the GEL Helpdesk. ER -