Journal
FRONTIERS IN GENETICS
Volume 13, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2022.941364
Keywords
congenital heart disease; genetic etiology; whole-genome sequencing; whole-exome sequencing; diagnostic yield; CHD-related genes
Categories
Funding
- Education and Research Collaborative Innovation of Fujian Province [2021YZ034011]
- Key Project on Science and Technology Program of Fujian Health Commission [2021ZD01002]
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Congenital heart disease (CHD) is a common malformation in fetuses and neonates, and a leading cause of mortality. Genetic mechanisms behind CHD remain poorly understood and many patients lack a genetic diagnosis. In this study, a strategy combining low-coverage whole-genome sequencing and whole-exome sequencing was used to identify genetic causes of CHD. By analyzing a patient-only cohort, 34.71% of CHD patients were diagnosed with genetic causes, with chromosomal abnormalities and damaging variants of CHD-related genes being common findings. Eight candidate CHD-causing genes were identified, along with 86 potential CHD-related genes. Our study provides new insights into the research strategies and underlying mechanisms of CHD.
Congenital heart disease (CHD) is the most common congenital malformation in fetuses and neonates, which also represents a leading cause of mortality. Although significant progress has been made by emerging advanced technologies in genetic etiology diagnosis, the causative genetic mechanisms behind CHD remain poorly understood and more than half of CHD patients lack a genetic diagnosis. Unlike carefully designed large case-control cohorts by multicenter trials, we designed a reliable strategy to analyze case-only cohorts to utilize clinical samples sufficiently. Combined low-coverage whole-genome sequencing (WGS) and whole-exome sequencing (WES) were simultaneously conducted in a patient-only cohort for identifying genetic etiologies and exploring candidate, or potential causative CHD-related genes. A total of 121 sporadic CHD patients were recruited and 34.71% (95% CI, 26.80 to 43.56) was diagnosed with genetic etiologies by low-coverage WGS and WES. Chromosomal abnormalities and damaging variants of CHD-related genes could explain 24.79% (95% CI, 17.92 to 33.22) and 18.18% (95% CI, 12.26 to 26.06) of CHD patients, separately, and 8.26% (95% CI, 4.39 to 14.70) of them have simultaneously detected two types of variants. Deletion of chromosome 22q11.2 and pathogenic variants of the COL3A1 gene were the most common recurrent variants of chromosomal abnormalities and gene variants, respectively. By in-depth manual interpretation, we identified eight candidate CHD-causing genes. Based on rare disease-causing variants prediction and interaction analysis with definitive CHD association genes, we proposed 86 genes as potential CHD-related genes. Gene Ontology (GO) enrichment analysis of the 86 genes revealed regulation-related processes were significantly enriched and processes response to regulation of muscle adaptation might be one of the underlying molecular mechanisms of CHD. Our findings and results provide new insights into research strategies and underlying mechanisms of CHD.
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