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

IF 8.1 1区 生物学 Q1 GENETICS & HEREDITY
American journal of human genetics Pub Date : 2025-03-06 Epub Date: 2025-02-20 DOI:10.1016/j.ajhg.2025.01.024
Meltem Ece Kars, David Stein, Peter D Stenson, David N Cooper, Wendy K Chung, Peter J Gruber, Christine E Seidman, Yufeng Shen, Martin Tristani-Firouzi, Bruce D Gelb, Yuval Itan
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引用次数: 0

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.

利用三重奏外显子组测序数据破译先天性心脏病的基因结构。
先天性心脏病(CHD)是最常见的先天性异常,也是婴儿发病率和死亡率的主要原因。尽管在过去的几十年里对冠心病的单基因病因进行了广泛的探索,但仍有55%的病例缺乏分子诊断。利用高通量测序数据研究基因相互作用(寡基因相互作用的最简单形式)可以阐明导致该疾病的其他遗传因素。在这里,我们利用一个大型的冠心病三重奏外显子组测序队列,包括3,910个冠心病和3,644个对照三重奏,对冠心病的基因相互作用进行了全面分析。我们提取了在冠心病患者和未患病儿童中观察到的可能有害的罕见变异对,但没有在单亲中观察到。对这些变异对衍生的基因对进行负荷试验,发现29对名义上显著的基因对。这些基因对对已知冠心病基因(p -4)显著富集,与已知冠心病基因的平均生物距离比随机预期的要短(p = 3.0 × 10-4)。利用三种互补的生物学相关性方法,包括网络分析、生物距离计算和候选基因优先排序方法,我们确定了10对可能导致冠心病的最终基因对的优先级。大量rna测序数据分析显示,这些基因在发育中的胚胎心脏中高度表达(p -4)。总之,我们的发现提示了基因相互作用在冠心病发病机制中的潜在作用,并为尚未解决的分子诊断提供了见解。我们建议将遗传方法应用于其他疾病队列将显著提高遗传发现率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
14.70
自引率
4.10%
发文量
185
审稿时长
1 months
期刊介绍: The American Journal of Human Genetics (AJHG) is a monthly journal published by Cell Press, chosen by The American Society of Human Genetics (ASHG) as its premier publication starting from January 2008. AJHG represents Cell Press's first society-owned journal, and both ASHG and Cell Press anticipate significant synergies between AJHG content and that of other Cell Press titles.
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