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A Panel-Agnostic Strategy 'HiPPo' Improves Diagnostic Efficiency in the UK Genomic Medicine Service.

Authors :
Seaby, Eleanor G.
Thomas, N. Simon
Hunt, David
Baralle, Diana
Rehm, Heidi L.
O'Donnell-Luria, Anne
Ennis, Sarah
Source :
Healthcare (2227-9032); Dec2023, Vol. 11 Issue 24, p3179, 21p
Publication Year :
2023

Abstract

Genome sequencing is available as a clinical test in the UK through the Genomic Medicine Service (GMS). The GMS analytical strategy predominantly filters genome data on preselected gene panels. Whilst this reduces variants requiring assessment by reporting laboratories, pathogenic variants outside applied panels may be missed, and variants in genes without established disease–gene relationships are largely ignored. This study compares the analysis of a research exome to a GMS clinical genome for the same patients. For the research exome, we applied a panel-agnostic approach filtering for variants with High Pathogenic Potential (HiPPo) using ClinVar, allele frequency, and in silico prediction tools. We then restricted HiPPo variants to Gene Curation Coalition (GenCC) disease genes. These results were compared with the GMS genome panel-based approach. Twenty-four participants from eight families underwent parallel research exome and GMS genome sequencing. Exome HiPPo analysis identified a similar number of variants as the GMS panel-based approach. GMS genome analysis returned two pathogenic variants and one de novo variant. Exome HiPPo analysis returned the same variants plus an additional pathogenic variant and three further de novo variants in novel genes, where case series are underway. When HiPPo was restricted to GenCC disease genes, statistically fewer variants required assessment to identify more pathogenic variants than reported by the GMS, giving a diagnostic rate per variant assessed of 20% for HiPPo versus 3% for the GMS. With UK plans to sequence 5 million genomes, strategies are needed to optimise genome analysis beyond gene panels whilst minimising the burden of variants requiring clinical assessment. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22279032
Volume :
11
Issue :
24
Database :
Complementary Index
Journal :
Healthcare (2227-9032)
Publication Type :
Academic Journal
Accession number :
174438034
Full Text :
https://doi.org/10.3390/healthcare11243179