Volume 43, Issue 8 pp. 1071-1081
REVIEW
Open Access

Phenotype-driven approaches to enhance variant prioritization and diagnosis of rare disease

Julius O. B. Jacobsen

Julius O. B. Jacobsen

William Harvey Research Institute, Charterhouse Square, Barts and the London School of Medicine and Dentistry Queen, Queen Mary University of London, London, UK

Search for more papers by this author
Catherine Kelly

Catherine Kelly

William Harvey Research Institute, Charterhouse Square, Barts and the London School of Medicine and Dentistry Queen, Queen Mary University of London, London, UK

Search for more papers by this author
Valentina Cipriani

Valentina Cipriani

William Harvey Research Institute, Charterhouse Square, Barts and the London School of Medicine and Dentistry Queen, Queen Mary University of London, London, UK

Search for more papers by this author
Genomics England Research Consortium

Genomics England Research Consortium

Genomics England, London, UK

Search for more papers by this author
Christopher J. Mungall

Christopher J. Mungall

Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, California, USA

Search for more papers by this author
Justin Reese

Justin Reese

Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, California, USA

Search for more papers by this author
Daniel Danis

Daniel Danis

The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, USA

Search for more papers by this author
Peter N. Robinson

Peter N. Robinson

The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, USA

Search for more papers by this author
Damian Smedley

Corresponding Author

Damian Smedley

William Harvey Research Institute, Charterhouse Square, Barts and the London School of Medicine and Dentistry Queen, Queen Mary University of London, London, UK

Correspondence Damian Smedley, William Harvey Research Institute, Charterhouse Sq, Barts and the London School of Medicine and Dentistry Queen, Queen Mary University of London, London EC1M 6BQ, UK.

Email: [email protected]

Search for more papers by this author
First published: 07 April 2022
Citations: 31

Abstract

Rare disease diagnostics and disease gene discovery have been revolutionized by whole-exome and genome sequencing but identifying the causative variant(s) from the millions in each individual remains challenging. The use of deep phenotyping of patients and reference genotype−phenotype knowledge, alongside variant data such as allele frequency, segregation, and predicted pathogenicity, has proved an effective strategy to tackle this issue. Here we review the numerous tools that have been developed to automate this approach and demonstrate the power of such an approach on several thousand diagnosed cases from the 100,000 Genomes Project. Finally, we discuss the challenges that need to be overcome if we are going to improve detection rates and help the majority of patients that still remain without a molecular diagnosis after state-of-the-art genomic interpretation.

CONFLICTS OF INTEREST

Julius Jacobsen and Damian Smedley declare they previously acted as part-time consultants for Congenica Ltd. The other authors declare no other potential conflicts of interest.

DATA AVAILABILITY STATEMENT

All data described in the paper are already provided in the paper except for access to the 100,000 Genomes Project samples which is by application to Genomics England.

The full text of this article hosted at iucr.org is unavailable due to technical difficulties.