Deciphering the digenic architecture of congenital heart disease using trio exome sequencing data

利用三重外显子组测序数据解读先天性心脏病的双基因结构

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Abstract

Congenital heart disease (CHD) is the most common congenital anomaly and a leading cause of infant morbidity and mortality. Despite extensive exploration of the monogenic causes of CHD over the last decades, ∼55% of cases still lack a molecular diagnosis. Investigating digenic interactions, the simplest form of oligogenic interactions, using high-throughput sequencing data can elucidate additional genetic factors contributing to the disease. Here, we conducted a comprehensive analysis of digenic interactions in CHD by utilizing a large CHD trio exome sequencing cohort, comprising 3,910 CHD and 3,644 control trios. We extracted pairs of presumably deleterious rare variants observed in CHD-affected and unaffected children but not in a single parent. Burden testing of gene pairs derived from these variant pairs revealed 29 nominally significant gene pairs. These gene pairs showed a significant enrichment for known CHD genes (p < 1.0 × 10(-4)) and exhibited a shorter average biological distance to known CHD genes than expected by chance (p = 3.0 × 10(-4)). Utilizing three complementary biological relatedness approaches including network analyses, biological distance calculations, and candidate gene prioritization methods, we prioritized 10 final gene pairs that are likely to underlie CHD. Analysis of bulk RNA-sequencing data showed that these genes are highly expressed in the developing embryonic heart (p < 1 × 10(-4)). In conclusion, our findings suggest the potential role of digenic interactions in CHD pathogenesis and provide insights into unresolved molecular diagnoses. We suggest that the application of the digenic approach to additional disease cohorts will significantly enhance genetic discovery rates.

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