Analyses of more than 60,000 exomes questions the role of numerous genes previously associated with dilated cardiomyopathy

Abstract

BackgroundHundreds of genetic variants have been described as disease causing in dilated cardiomyopathy (DCM). Some of these associations are now being questioned. We aimed to identify the prevalence of previously DCM associated variants in the Exome Aggregation Consortium (ExAC), in order to identify potentially false‐positive DCM variants.MethodsVariants listed as DCM disease‐causing variants in the Human Gene Mutation Database were extracted from ExAC. Pathogenicity predictions for these variants were mined from dbNSFP v 2.9 database.ResultsOf the 473 DCM variants listed in HGMD, 148 (31%) were found in ExAC. The expected number of individuals with DCM in ExAC is 25 based on the prevalence in the general population. Yet, 35 variants were found in more than 25 individuals. In 13 genes, we identified all variants previously associated with DCM; four genes contained variants above our estimated cut‐off. Prediction tools found ExAC variants to be significantly more tolerated when compared to variants not found in ExAC (P = 0.004).ConclusionIn ExAC, we identified a higher genotype prevalence of variants considered disease‐causing than expected. More importantly, we found 13 genes in which all variants previously associated with DCM were identified in ExAC, questioning the association of these genes with the monogenic form of DCM.

Genetics and genomics of dilated cardiomyopathy and systolic heart failure

“…The proportion of DCM cases with a familial basis is between 20 and 30%, although a level as high as 60% has been suggested [ 14 ]. In familial DCM, up to 40% of cases can have an identifiable genetic basis [ 5 ], although as a more critical evaluation of the genes linked to DCM continues and genes or variants are discounted, this percentage might fall [ 15 , 16 ]. Systolic heart failure is a catch-all phenotypic diagnosis and can be caused by a variety of insults ranging from myocardial ischemia to cardiomyopathy.…”

“…The ExAC data-set of over 60,000 exomes will help to address the pressing need for greater amounts of control data [ 13 ]. Several groups have shown how ExAC can be leveraged to aid the interpretation of rare variants in cardiomyopathies [ 15 , 16 ]. These population data should be placed, however, in the context of other available resources to aid clinicians and researchers in interpreting rare variants, such as disease variant databases (for example, Human Gene Mutation Database [ 21 ] and ClinVar [ 22 ]), computational data (such as in silico missense variant prediction tools, many of which are amalgamated in the dbNSFP [ 23 ]), functional data, and, crucially, segregation data.…”

Distinguishing pathogenic mutations from background genetic noise in cardiology: The use of large genome databases for genetic interpretation

“…Several research groups have estimated that at least 10% of the variants associated with LQTS may have been classified inaccurately . In addition, the pathogenicity of a large fraction of variants and even whole genes previously associated with dilated cardiomyopathy (DCM), Brugada syndrome (BrS), sudden infant death syndrome and catecholaminergic polymorphic ventricular tachycardia has been challenged . Thus, the issue of incidental genetic findings might be a larger problem than initially anticipated.…”

Genetics of paediatric cardiomyopathies

“…Interpretation of variants is a rapidly evolving as widespread sequencing efforts and public databases such as the Exome Aggregation Consortium (http://exac.broadinstitute.org), and the 1000 Genomes Project Exome Sequencing Project (http://evs.gs.washington.edu/EVS) lend insight into the frequency of rare variants in the population and allow comparison to cardiomyopathy cohorts. (11, 12, 33, 34) These studies have highlighted that rare genetic variation is, in aggregate, much more common than anticipated and is present to a substantial degree within healthy individuals. There has been a significant effort to reassess past interpretation of genetic variation in cardiomyopathy patients.…”