Genetic Diagnostic Yield and Novel Causal Genes of Congenital Heart Disease

Abstract

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.

Keywords: CHD-related genes; congenital heart disease; diagnostic yield; genetic etiology; whole-exome sequencing; whole-genome sequencing.

FIGURE 1

Methodological workflows of genetic etiological diagnosis and CHD-related gene prediction. Each case had conducted low-coverage WGS and WES. The unique reads mean depth of whole-genome by low-coverage WGS was 0.37X. A total of 204 CNVs were identified in 95 samples, and the ACMG classifications of these 204 CNVs were demonstrated in a stacked bar chart. Six aneuploidy variants, seven LP|P CNVs, and eight candidates CHD pathogenic VUS CNVs were proposed as CHD causative CNVs. These 21 causative CNVs all explained 30 samples and some of the causative CNVs were diagnosed repeatedly in multiple samples (Table 3). The mean depth in the capture region of WES was 171.04X. Total 724 P|LP variants were identified in 268 genes involving 100 samples and their functional effect was shown in a stacked bar chart. Among these 724 P|LP variants there were 94 variants belonging to 33 definitive CHD genes and 8 variants belonging to candidate CHD-related genes. Combined with low-coverage WGS and WES, there were 42 samples identified with genetic etiology with a 34.71% diagnostic yield. We also explored the potential CHD association genes by KGGSeq software based on WES data. A total of 1,133 variants on 886 genes were predicted as rare disease-causing. 36 of the 886 were definitive CHD-related genes. The left 850 genes were further narrowed down based on interactions with curated CHD genes. Finally, 86 genes were proposed as CHD-related genes. Abbreviations: UR, unique reads; LP|P, likely pathogenic or pathogenic; CR, capture region.

FIGURE 2

Landscape of distribution of genetic etiology and clinical features (N = 121). The heatmap on the left demonstrated the distribution of genetic etiologies detected in each sample. Each row represents a sample and the columns are five categories of genetic etiology. The correspondence colors of genetic etiology were summarized in the right legend. Four clinical characteristics including sample types, gender, latest ultrasonic testing, and clinical features of each sample were demonstrated in the right heatmaps separately. At the same time, we also displayed the distribution statistics of clinical characteristics on the top of the heatmap.

FIGURE 3

Protein interactions and Genetic causes of CHD identified by WES. (A–C): protein interactions of gene FN1, IRS1, and CCT5. (D–E): Enriched biological processes of 886 genes (D) set and 86 genes (E) set.