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Title: Refining the genetic architecture of inherited cardiomyopathies through case-control analyses
Author: Thomson, Kate
ISNI:       0000 0004 7653 7904
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2018
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Inherited cardiomyopathies comprise a clinically and genetically heterogeneous group of heart muscle disorders, which are a major cause of heart disease and cardiac morbidity. Genetic testing for these conditions has been available for over a decade, and the number of genes incorporated into clinical test panels has increased significantly in recent years. However, rather than an increase in genetic diagnoses, this has resulted in a higher proportion of inconclusive results. In this study, large-scale case-control analyses were employed to compare rare variation in 7855 cardiomyopathy cases and 60,706 reference controls, with the aim of identifying significant excess of rare variation in cases. These analyses highlighted the genes and classes of variant that show the strongest evidence of causality, as well as those that cannot be interpreted reliably. This methodology was used to reassess genes in current clinical test panels and to explore the contribution of more recently implicated genes. Analyses were also undertaken to explore the prevalence of pathogenic variants in the wider population. These analyses provide critical insight into the genetic architecture of inherited cardiomyopathies, confirming the main causal genes and classes of variant. One novel finding was identified (an excess of rare truncating variants in the ALKP3 gene in sarcomere-negative HCM cases compared to controls), but in most recently implicated genes, the gene-disease relationship could not be validated and lack of evidence precluded variant interpretation. Collectively, these findings inform evidence-based selection of genes for clinical test panels, reduce uncertainty in interpretation, and increase the clinical utility of testing in these medically important disorders. More broadly, this study demonstrates how the methods described can be used to enhance understanding of rare variation in dominant Mendelian disease genes.
Supervisor: Watkins, Hugh ; Farrall, Martin Sponsor: National Institute for Health Research
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available