Euan A. Ashley

Publication Details

  • A New Era in Clinical Genetic Testing for Hypertrophic Cardiomyopathy JOURNAL OF CARDIOVASCULAR TRANSLATIONAL RESEARCH Wheeler, M., Pavlovic, A., deGoma, E., Salisbury, H., Brown, C., Ashley, E. A. 2009; 2 (4): 381-391

    Abstract:

    Building on seminal studies of the last 20 years, genetic testing for hypertrophic cardiomyopathy (HCM) has become a clinical reality in the form of targeted exonic sequencing of known disease-causing genes. This has been driven primarily by the decreasing cost of sequencing, but the high profile of genome-wide association studies, the launch of direct-to-consumer genetic testing, and new legislative protection have also played important roles. In the clinical management of hypertrophic cardiomyopathy, genetic testing is primarily used for family screening. An increasing role is recognized, however, in diagnostic settings: in the differential diagnosis of HCM; in the differentiation of HCM from hypertensive or athlete's heart; and more rarely in preimplantation genetic diagnosis. Aside from diagnostic clarification and family screening, use of the genetic test for guiding therapy remains controversial, with data currently too limited to derive a reliable mutation risk prediction from within the phenotypic noise of different modifying genomes. Meanwhile, the power of genetic testing derives from the confidence with which a mutation can be called present or absent in a given individual. This confidence contrasts with our more limited ability to judge the significance of mutations for which co-segregation has not been demonstrated. These variants of "unknown" significance represent the greatest challenge to the wider adoption of genetic testing in HCM. Looking forward, next-generation sequencing technologies promise to revolutionize the current approach as whole genome sequencing will soon be available for the cost of today's targeted panel. In summary, our future will be characterized not by lack of genetic information but by our ability to effectively parse it.

    View details for DOI 10.1007/s12265-009-9139-0

    View details for Web of Science ID 000284691000005

    View details for PubMedID 20559996

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