Distinguishing hypertrophic cardiomyopathy-associated mutations from background genetic noise.
Repository Usage Stats
Despite the significant progress that has been made in identifying disease-associated mutations, the utility of the hypertrophic cardiomyopathy (HCM) genetic test is limited by a lack of understanding of the background genetic variation inherent to these sarcomeric genes in seemingly healthy subjects. This study represents the first comprehensive analysis of genetic variation in 427 ostensibly healthy individuals for the HCM genetic test using the "gold standard" Sanger sequencing method validating the background rate identified in the publically available exomes. While mutations are clearly overrepresented in disease, a background rate as high as ∼5 % among healthy individuals prevents diagnostic certainty. To this end, we have identified a number of estimated predictive value-based associations including gene-specific, topology, and conservation methods generating an algorithm aiding in the probabilistic interpretation of an HCM genetic test.
Published Version (Please cite this version)
Kapplinger, JD, AP Landstrom, JM Bos, BA Salisbury, TE Callis and MJ Ackerman (2014). Distinguishing hypertrophic cardiomyopathy-associated mutations from background genetic noise. Journal of cardiovascular translational research, 7(3). pp. 347–361. 10.1007/s12265-014-9542-z Retrieved from https://hdl.handle.net/10161/20316.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.