14-Center Study Finds Key Genes Linked to Different Forms of Pediatric Cardiomyopathy

Published February 2022 | American Journal of Human Genetics

While both children and adults can develop cardiomyopathy, until now, most knowledge about risk genes causing the condition have been derived from adult studies. That landscape has changed since the Pediatric Cardiomyopathy Registry Study Group conducted a 14-center exome sequencing project involving 528 children suffering from distinct forms of cardiomyopathy and at high risk of needing a heart transplant. Data analyses were led by Surbhi Bhatnagar, PhD student, as a co-first author, and by Lisa Martin, PhD, Division of Human Genetics, and Bruce Aronow, PhD, co-director, Computational Medicine Center, as co-senior authors. When comparing affected genes among these children to an existing list of known genes linked to cardiomyopathy, only 32% of the cohort displayed risk variants. However, comparing the children to a wider set of candidate genes—compiled using a gene, protein, cell, and multi-population human gene variation network analysis approach—revealed that 56% of the cohort carried potentially causal genes and damaging variants.

“These results suggest that while current clinical genetic testing is warranted, more research on the genes of cardiomyopathy is needed. Future studies should include wider diversity. Further, larger sample sizes will enable us to evaluate the impact of harboring multiple damaging variants,” says Martin. The yield of risk genes detected varied by ancestry, type of cardiomyopathy, and age. For example, patients with European ancestry and hypertrophic cardiomyopathy showed higher yields. The most commonly found variants involved the genes MYH7 and MYBPC3. However, no MYBPC3 variants were found in children of African descent. Other Cincinnati Children’s co-authors included Erin Miller, MS, CGC, Phillip Dexheimer, PhD student, and Jeffrey Towbin, MD (now with Le Bonheur Children’s Hospital). All exome sequencing was performed at Cincinnati Children’s. The team also used the ToppGene suite, developed at Cincinnati Children’s, to analyze candidate genes.