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- Title
Specialist multidisciplinary input maximises rare disease diagnoses from whole genome sequencing.
- Authors
Macken, William L.; Falabella, Micol; McKittrick, Caroline; Pizzamiglio, Chiara; Ellmers, Rebecca; Eggleton, Kelly; Woodward, Cathy E.; Patel, Yogen; Labrum, Robyn; Genomics England Research Consortium; Ambrose, J. C.; Arumugam, P.; Bevers, R.; Bleda, M.; Boardman-Pretty, F.; Boustred, C. R.; Brittain, H.; Brown, M. A.; Caulfield, M. J.; Chan, G. C.
- Abstract
Diagnostic whole genome sequencing (WGS) is increasingly used in rare diseases. However, standard, semi-automated WGS analysis may overlook diagnoses in complex disorders. Here, we show that specialist multidisciplinary analysis of WGS, following an initial 'no primary findings' (NPF) report, improves diagnostic rates and alters management. We undertook WGS in 102 adults with diagnostically challenging primary mitochondrial disease phenotypes. NPF cases were reviewed by a genomic medicine team, thus enabling bespoke informatic approaches, co-ordinated phenotypic validation, and functional work. We enhanced the diagnostic rate from 16.7% to 31.4%, with management implications for all new diagnoses, and detected strong candidate disease-causing variants in a further 3.9% of patients. This approach presents a standardised model of care that supports mainstream clinicians and enhances diagnostic equity for complex disorders, thereby facilitating access to the potential benefits of genomic healthcare. This research was made possible through access to the data and findings generated by the 100,000 Genomes Project: http://www.genomicsengland.co.uk. Whole genome sequencing is emerging as a first-line test for rare genetic diseases. In this study, authors maximise diagnoses by supplementing existing semiautomated analyses with clinically driven reevaluation of genomic data by a specialist multidisciplinary team.
- Subjects
WHOLE genome sequencing; DIAGNOSIS; RARE diseases; GENETIC disorders; GENETIC testing; PHENOTYPES
- Publication
Nature Communications, 2022, Vol 13, Issue 1, p1
- ISSN
2041-1723
- Publication type
Article
- DOI
10.1038/s41467-022-32908-7