Poster Presentation GENEMAPPERS 2026

Rare variant burden testing reveals new candidate genes for congenital heart disease (#104)

Yunkai Gao 1 2 , Debjani Das 1 , Gillian M Blue 3 4 , Eddie K K Ip 1 2 , Congenital Heart Disease Synergy Study Group 1 , David S Winlaw 3 5 6 , Sally L Dunwoodie 1 7 , Eleni Giannoulatou 1 7
  1. Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia
  2. School of Clinical Medicine, St Vincent's Healthcare Clinical Campus, Faculty of Medicine and Health, UNSW Sydney, Sydney, NSW, Australia
  3. Heart Centre for Children, Sydney Children's Hospital Network, Westmead, NSW, Australia
  4. Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW, Australia
  5. Sydney Medical Schoool, The University of Sydney, Sydney, NSW, Australia
  6. Cincinnati Children's Hospital Medical Center, Heart Institute, Cardiothoracic Surgery, Cincinnati, OH, US
  7. St Vincent's Clinical School, Faculty of Medicine, UNSW Sydney, Sydney, NSW, Australia

Congenital heart disease (CHD) is the structural and functional deficits that arise during cardiac embryogenesis and affects 10-12 per 1000 newborns worldwide. Phenotypes of CHD patients are highly heterogeneous, which is further complicated by the presence or absence of extra-cardiac anomalies. Genetics is the major cause of the disease and genetic diagnosis is important for the disease intervention, prognosis, and risk assessment for family members. Although many genes have already been found to be associated with CHD, the genetic diagnosis rate varies between 15% to 60%. Discovering new CHD genes can help increase the diagnostic rate. Burden test is a powerful way for whole-exome association analysis, but an ideal control cohort is difficult to obtain. Hence, we used CoCoRV, a rare-variant gene-based burden test that leverages gnomAD as a population control and stratifies analyses by ancestry. Our discovery cohort consists of 653 unrelated CHD samples with whole-exome sequencing, and our validation cohort consists of another 45 independent CHD samples with whole-genome sequencing. We observed an increased burden of rare damaging variants in four genes that showed consistent signals across both cohorts: HMCN1, TBPL2, VIPR1, and CLSTN1. Among these genes, HMCN1 was reported to be associated with pulmonary atresia. CLSTN1 was reported to affect cardiac systolic function possibly via PI3K/Akt pathway or via modulating calcium ions in the myocardium. Our findings can be used to validate future in silico analyses of independent cohorts. The functional roles of these genes in CHD can also be further explored with in vitro and in vivo studies.