CAP TODAY Pathology/Laboratory Medicine/Laboratory Management
Editors: Donna E. Hansel, MD, PhD, chief, Division of Anatomic Pathology, and professor, Department of Pathology, University of California, San Diego; John A. Thorson, MD, PhD, associate professor of pathology, director of the Clinical Genomics Laboratory, Center for Advanced Laboratory Medicine, UCSD; Sarah S. Murray, PhD, professor, Department of Pathology, and director of genomic technologies, Center for Advanced Laboratory Medicine, UCSD; and James Solomon, MD, PhD, resident, Department of Pathology, UCSD.
Misclassification of genetic variants associated with hypertrophic cardiomyopathy
Hypertrophic cardiomyopathy has a variable clinical presentation and may lead to sudden cardiac death. In many cases, it is associated with pathogenic genetic variants, enabling screening of relatives and, possibly, the ability to individualize treatment strategies through lifestyle modification or invasive procedures. However, the importance of accurately classifying such genetic variants cannot be understated, as misidentification could potentially cause inappropriate management, not only for patients but also for their relatives. Yet there is also a significant amount of background-normal genetic variation in the population. Therefore, the assignment of pathogenicity can be strongly influenced by observed variant frequencies in control populations. The authors hypothesized that some of the high-frequency variants classically associated with hypertrophic cardiomyopathy may be due to normal genetic variation in groups not traditionally represented in historical population-based sequencing. They predicted that many of these false-positives would occur in patients of African ancestry. The authors examined publicly available data from multiple sources, including exome data from 4,300 people of European ancestry (EA) and 2,203 people of African ancestry (AA), as well as whole genome data from 1,092 people from 14 ethnic populations, and SNP data for 938 people from 51 ethnic populations. They reviewed clinical data from patients who had been diagnosed with hypertrophic cardiomyopathy and included any patients with a genetic variant classified as pathogenic, presumed pathogenic, pathogenicity debated, or unknown significance. The patient population included 94 variants associated with hypertrophic cardiomyopathy, five of which were found to be high-frequency variants, defined as having a minor allele frequency of greater than one percent in the population. These five high-frequency variants—TNNT2 (p.K247R), OBSCN (p.R4344Q), TNNI3 (p.P82S), MYBPC3 (p.G278E), and JPH2 (p.G505S)—accounted for 75 percent of the genotypic prevalence of hypertrophic cardiomyopathy. In the publicly available data, all five of these high-frequency variants had significantly higher frequencies in the AA when compared to the EA groups, ranging from 1.5 to 14.9 percent in the AA group and 0.01 to 1.5 percent in the EA group, respectively. The remaining 89 variants associated with hypertrophic cardiomyopathy showed no significant frequency differences between the AA and EA ancestry groups. The study also found that even if these high-frequency variants were pathogenic, they would have very low penetrance, considering their prevalence in the general population. Multiple patients had positive genetic reports, which, in some cases, reported only these high-frequency variants that were later reclassified as benign. The authors found that for a few of the initial studies in the medical literature that first identified pathogenic variants associated with hypertrophic cardiomyopathy, the control sample sizes were too small and included no people of African ancestry. With statistical models, the authors demonstrated that even small studies can exclude pathogenicity of variants if small proportions of diverse populations are used. New resources, such as the Exome Aggregation Consortium database, include sufficiently diverse populations to provide enough power to rule out pathogenicity for rare variants. In addition, these large-scale efforts allow for the retrospective assessment of previously determined associations between genetic variants and disease. The authors concluded that the classification of variants should be a constantly evolving process as new information is obtained to guide interpretation.
Manrai AK, Funke BH, Rehm HL, et al. Genetic misdiagnoses and the potential for health disparities. N Engl J Med. 2016;375:655–665.
Correspondence: Dr. Isaac C. Kohane at isaac_kohane@harvard.edu