Rare diseases, particularly those with great phenotypic and genetic heterogeneity, remain a diagnostic challenge. Broadening the investigative approach through whole genome sequencing (WGS) is anticipated to improve diagnostic yield. Despite this, substantial numbers of patients remain undiagnosed through current 100,000 Genomes Project pipelines. In these cases, the causative mutation may not be prioritised due to lack of evidence associating the gene with a specific phenotype, or as a result of being inadvertently filtered out.
A systematic approach to additional data analysis utilising both inheritance model filtering and ranking algorithm tools has been piloted in cases with no primary findings (NPF). Examples of diagnoses secured include a de novo TAB2mutation, causing a connective tissue phenotype with congenital heart disease and a paternally inherited COL7A1mutation, causing a variable penetrance skin blistering disorder, epidermolysis bullosa dystrophica.
Identification of causative variants in WGS data remains challenging. Data led approaches to optimising additional review of cases with NPF have the prospect of improving both sensitivity and cost efficiency and may provide earlier diagnosis for individuals with rare disease, ending their diagnostic odyssey. Establishing a standardised approach to reanalysis will be particularly important as we approach the introduction of an NHS clinical sequencing service.
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