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Recent Highlights

The Prevalence and Association of Exercise Test Abnormalities with Sudden Cardiac Death and Transplant-Free Survival in Childhood Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy (HCM) can be associated with an abnormal exercise response. In an international cohort study the goal was to determine if an abnormal exercise response is associated with adverse outcomes in pediatric HCM patient by looking at phenotype-positive children with primary HCM from 20 centers. Using Kaplan-Meier survival, competing outcomes, and Cox regression analyses the association of an abnormal exercise test with transplant and SCD event-free survival were analyzed. Finding, an abnormal exercise test was independently associated with lower transplant-free survival especially in those with an ischemic or abnormal blood pressure response with exercise. Exercise-induced ischemia was also independently associated with SCD events. These findings argue for routine exercise testing in childhood HCM as part of ongoing risk assessment.

Whole genome sequencing delineates regulatory, copy number, and cryptic splice variants in early onset cardiomyopathy

Cardiomyopathy (CMP) is the leading cause of heart failure and sudden cardiac death in childhood with an estimated 20 million people worldwide living with the disease with thousands of new cases are diagnosed annually in North America. Despite the inclusion of over 100 CMP disease genes in clinical testing panels, a majority of cases remain gene-elusive. Standard panels do not evaluate the non-coding genome that harbors DNA regulatory sequences including core and proximal promoters and enhancers, as well as distal regulatory elements.

This study used WGS to characterize all classes of genetic variation in a well-phenotyped discovery cohort of childhood-onset CMP. WGS identified copy number variants (CNVs), cryptic splicing variants, and high-risk regulatory variants associated with known CMP genes, and loss-of-function (LoF) variants in additional candidate genes that would not have been detected on clinical genetic testing.

Finding that high confidence variants identified using in silico prediction models have functional consequences validates bioinformatics approach to WGS-based variant discovery and makes a strong case for exploring cryptic splice variants, CNVs, variants in new candidate genes, and variants in recurrently altered regulatory elements of CMP genes in order to identify the missing genomic etiology of CMP.

Common Genetic Variants Contribute to Risk of Transposition of the Great Arteries

Tetralogy of Fallot (TOF) and Transposition of the great arteries (TGA) are the leading causes of cyanotic congenital heart disease i.e. “blue” babies. Through an international collaboration in patients with TGA, it was identified that several common variants near the gene, WNT5A, may explain up to 25% of the risk of inheriting this heart condition. This work suggests that TGA can be the result of several gene variants rather than a single gene variant.

Rare variants in KDR, encoding VEGF Receptor 2, are associated with tetralogy of Fallot

Rare genetic variants in KDR, encoding the vascular endothelial growth factor receptor 2 (VEGFR2), have been reported in patients with tetralogy of Fallot (TOF). Exome sequencing, large-scale genetic studies, and cell-based assays were conducted to explore the role of KDR genetic variation in the etiology of TOF. A 46-fold enrichment of protein-truncating variants (PTVs) in TOF cases compared to controls was identified. The findings in this study shed light on the role of VEGF signaling in TOF and justify consideration of KDR screening in TOF patients in a clinical diagnostic setting.

PRecIsion Medicine in CardiomyopathY (PRIMaCY)

Hypertrophic cardiomyopathy is the leading cause of sudden cardiac death in adolescents and young adults. Despite the availability of implantable cardioverter-defibrillators (ICD) as a life-saving intervention, the lack of precision in predicting sudden death risk hampers timely ICDs in at-risk patients resulting in deaths that could have been prevented.

PRIMaCY has developed an eHealth clinical decision support tool that generates an individualized 5-year risk prediction for sudden cardiac death (SCD) for each patient. The primary goal is to implement the PRIMaCY tool in hospital information systems for use by physicians as a point of care tool, to evaluate the effectiveness of the tool in adherence to clinical practice guidelines, and to evaluate how it influences patient/family counseling. Click the link below to explore the PRIMaCY SCD risk calculator website.

Machine Learning Identifies Clinical and Genetic Factors Associated With Anthracycline Cardiotoxicity in Pediatric Cancer Survivors

Medical advances have helped children with cancer survive into adulthood and live healthy lives. However some children can suffer from cardiac side-effects of chemotherapy, in particular, to a class of drugs called anthracyclines which are used to treat almost 50% of cancers. This can manifest as reduced heart function, or even heart failure, years to decades after exposure. Unfortunately our ability to predict who is at risk for developing cardiac side-effects has been limited.

We performed exome sequencing in close to 300 pediatric cancer survivors enrolled in a multi-center international study. We identified rare variants in several genes that influenced which children develop cardiotoxicity. Manipulating these genes experimentally with drugs or compounds was able to protect heart cells from cardiotoxicity. Additionally, using machine learning, we developed an integrated clinical and genetic model that was superior to a clinical only model in predicting who is at risk for cardiotoxicity. In the future, this knowledge could be used by physicians to decide which child should or should not be exposed to anthracyclines, which child should be closely monitored for cardiac side-effects, and which child should get cardio-protective drugs that target their unique genetic factors. This will bring precision medicine one step closer to helping childhood cancer survivors.

A Validated Model for Sudden Cardiac Death Risk Prediction in Pediatric Hypertrophic Cardiomyopathy