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Applying High-Resolution Variant Classification to Cardiac Arrhythmogenic Gene Testing in a Demographically Diverse Cohort of Sudden Unexplained Deaths

NCJ Number
253313
Date Published
Unknown
Annotation
This article reports on an evaluation of cardiac channelopathy and cardiomyopathy genes in a large, demographically diverse sudden unexplained death cohort that underwent thorough investigation in the United States' largest medical examiner's office, adapting a high-resolution variant interpretation framework, which considers disease prevalence, reduced penetrance, genetic heterogeneity, and allelic contribution to determine the maximum tolerated allele count in gnomAD.
Abstract
The cohort had 296 decedents: 147 Blacks, 64 Hispanics, 49 Whites, 22 Asians, and 14 mixed ethnicities; 142 infants (1 to 11 months), 39 children (1 to 17 years), 74 young adults (18 to 34 years), and 41 adults (35 to 55 years). Eighty-nine cardiac disease genes were evaluated. Using a high-resolution variant interpretation workflow, the study classified 17 variants as pathogenic or likely pathogenic (two of which were incidental findings and excluded in testing yield analysis), 46 novel variants of uncertain significance, and 130 variants of uncertain significance. Nine pathogenic or likely pathogenic variants in ClinVar were reclassified to likely benign and excluded in testing yield analysis. The yields of positive cases by ethnicity and age were 21.4 percent in mixed ethnicities, 10.2 percent Whites, 4.5 percent Asians, 3.1 percent Hispanics, and 2 percent Blacks; 7.7 percent children, 7.3 percent adults, 5.4 percent young adults, and 2.8 percent infants. The percentages of uncertain cases with variants of uncertain significance by ethnicity were 45.5 percent in Asians, 45.3 percent Hispanics, 44.20 percent Blacks, 36.7 percent Whites, and 14.3 percent in mixed ethnicities. The study concludes that high-resolution variant interpretation provides diagnostic accuracy and healthcare efficiency. Under-represented populations warrant greater inclusion in future studies. (publisher abstract modified)
Date Created: January 28, 2021