Phenotype‐driven approaches to enhance variant prioritization and diagnosis of rare disease. Issue 8 (27th April 2022)

• Record Type: Journal Article
• Authors: Jacobsen, Julius O. B.; Kelly, Catherine; Cipriani, Valentina; Research Consortium, Genomics England; Mungall, Christopher J.; Reese, Justin; Danis, Daniel; Robinson, Peter N.; Smedley, Damian
• Other Names: Laner Andreas guestEditor.; Maver Ales guestEditor.; den Dunnen Johan T. guestEditor.
• Is Part Of: Human mutation. Volume 43:Issue 8(2022)
• Page Start: 1071
• Page End: 1081
• Publication Date: 2022-04-27
• Subjects: diagnostics -- phenotypes -- rare disease -- variant prioritization; Human chromosome abnormalities -- Periodicals; Mutation (Biology) -- Periodicals; 616.04205
• DOI: 10.1002/humu.24380
• Languages: English
• ISSNs: 1059-7794

Abstract

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.