Abstracts/Presentation Description
Nicola Whiffin1
1University of Oxford
Rare disorders collectively impact around one in every seventeen individuals. In excess of 80% of rare disorders are estimated to have a genetic cause, and identifying that cause is of incredible value: enabling familial and prenatal screening, recurrence risk counselling, prognostic prediction, and personalised treatment. Increasingly, genome sequencing is used as a first-tier diagnostic test, enabling identification of variants across the entire genome. Despite this, in the vast majority of settings analysis is limited to variants found in regions of the genome that directly encode proteins. This strategy focuses on a small portion of the genome, around 1.5%, where variants may have a large and predictable effect, however, it results in a diagnosis for fewer than half of all patients with rare disorders. This protein-focussed approach is in large part due to the difficulties of annotating, interpreting, and clinically classifying variants in non-coding regions for a role in rare disease. I will discuss ongoing research on identifying variants in non-coding regions that cause rare disease using large-scale genome sequencing datasets such as the Genomics England 100,000 Genomes Project. I will discuss the successes, but also the challenges that remain to routine identification and classification of non-coding variants in clinical settings.
1University of Oxford
Rare disorders collectively impact around one in every seventeen individuals. In excess of 80% of rare disorders are estimated to have a genetic cause, and identifying that cause is of incredible value: enabling familial and prenatal screening, recurrence risk counselling, prognostic prediction, and personalised treatment. Increasingly, genome sequencing is used as a first-tier diagnostic test, enabling identification of variants across the entire genome. Despite this, in the vast majority of settings analysis is limited to variants found in regions of the genome that directly encode proteins. This strategy focuses on a small portion of the genome, around 1.5%, where variants may have a large and predictable effect, however, it results in a diagnosis for fewer than half of all patients with rare disorders. This protein-focussed approach is in large part due to the difficulties of annotating, interpreting, and clinically classifying variants in non-coding regions for a role in rare disease. I will discuss ongoing research on identifying variants in non-coding regions that cause rare disease using large-scale genome sequencing datasets such as the Genomics England 100,000 Genomes Project. I will discuss the successes, but also the challenges that remain to routine identification and classification of non-coding variants in clinical settings.