Specialist multidisciplinary input maximises rare disease diagnoses from whole genome sequencing
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, improv...
Gespeichert in:
Veröffentlicht in: | Nature communications 2022-11, Vol.13 (1), p.6324-9, Article 6324 |
---|---|
Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | 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. |
---|---|
ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/s41467-022-32908-7 |