Dilated cardiomyopathy of unknown cause (DCM), a major public health problem affecting more than a million people in the U.S., is usually diagnosed late in its course with overt heart failure or sudden death. Recent preliminary evidence indicates that most DCM has an underlying genetic basis; this hypothesis is being tested in the DCM Precision Medicine Study, the parent study of this ancillary application, which is conducting family based enrollment of 1300 DCM patients (probands) and 2600 of their relatives at 26 centers. In the parent study, the echocardiographic (echo) data currently collected on case report forms are only those necessary to confirm or detect left ventricular enlargement or systolic dysfunction. Genetic analysis is also conducted in probands to identify relevant variants (pathogenic, likely pathogenic, or uncertain significance) in DCM-related genes, but cascade testing in relatives is limited to pathogenic and likely pathogenic variants that would change clinical management. While these echocardiographic and genetic data are sufficient to achieve the aims of the parent study, collection of additional data exceeding the scope of the parent study is essential to test the central hypothesis of this ancillary study: that DCM-related abnormalities in cardiac mechanics are (1) present in individuals genetically at risk for DCM prior to development of left ventricular systolic dysfunction and dilation and (2) reflect the level of genetic risk. In particular, we propose centrally collecting digital echo data currently stored at sites and analyzing these data at an echo core lab using speckle-tracking echocardiography (STE), which is capable of detecting subtle abnormalities in cardiac mechanics. We also propose additional cascade testing for variants of uncertain significance (VUSs) in first-degree relatives (FDRs); VUSs have been found in 46% of probands with completed adjudications thus far, but their implications for genetic risk in FDRs are currently uncertain. Using these data, we will (1) examine how STE-derived strain measurements vary with the level of genetic risk using a two-fold approach. First, we will (a) compare these measurements between genetically at-risk FDRs with varying levels of measured genetic risk (i.e., severity and number of mutations in DCM-related genes identified via testing) and normal population controls. Second, we will (b) conduct a family- based analysis to determine the relative contributions of these measured and other unmeasured genetic factors to variation in these measurements. We will also (2) determine the effect of physiologic stress (exercise) on cardiac mechanics in 200 unaffected FDRs who have uncertain genetic risk (carriers of familial VUSs or FDRs of probands with negative genetic testing) compared to matched controls. This study, if successful, will lead to novel understanding of how varying levels of genetic risk, and especially VUSs, associate with abnormalities of cardiac mechanics, thereby improving our understanding of the genetic architecture and physiology of DCM. By gathering and aggregating all echo data, this ancillary study would also greatly enhance the opportunities for repeated echo-based analysis in the anticipated follow on parent study.
Dilated cardiomyopathy of unknown cause (DCM) has a mostly genetic basis, and identifying genetic risk and detecting very early clinical evidence of DCM in at-risk family members holds promise to prevent it. A major obstacle to fulfilling this promise is incomplete understanding of both the timing of DCM onset in individuals with established genetic risk as well as the implications of many genetic test results for DCM risk. In this ancillary study of a large clinical and genetic study of DCM families already underway, we propose collecting digital echocardiographic data, analyzing it using advanced techniques capable of detecting early disease, and integrating it with both new and existing genetic information in order to fill this knowledge gap and enhance our ability to prevent DCM.
