Rare copy number variants in patients with congenital conotruncal heart defects

Abstract

Background: Previous studies using different cardiac phenotypes, technologies and designs suggest a burden of large, rare or de novo copy number variants (CNVs) in subjects with congenital heart defects. We sought to identify disease-related CNVs, candidate genes, and functional pathways in a large number of cases with conotruncal and related defects that carried no known genetic syndrome.

Methods: Cases and control samples were divided into two cohorts and genotyped to assess each subject's CNV content. Analyses were performed to ascertain differences in overall CNV prevalence and to identify enrichment of specific genes and functional pathways in conotruncal cases relative to healthy controls.

Results: Only findings present in both cohorts are presented. From 973 total conotruncal cases, a burden of rare CNVs was detected in both cohorts. Candidate genes from rare CNVs found in both cohorts were identified based on their association with cardiac development or disease, and/or their reported disruption in published studies. Functional and pathway analyses revealed significant enrichment of terms involved in either heart or early embryonic development.

Conclusion: Our study tested one of the largest cohorts specifically with cardiac conotruncal and related defects. These results confirm and extend previous findings that CNVs contribute to disease risk for congenital heart defects in general and conotruncal defects in particular. As disease heterogeneity renders identification of single recurrent genes or loci difficult, functional pathway and gene regulation network analyses appear to be more informative. Birth Defects Research 109:271-295, 2017. © 2017 Wiley Periodicals, Inc.

Keywords: CNVs; congenital heart defects; conotruncal defects; copy number variants; functional analysis; pathway analysis.

FIGURE 1. Flow chart outlining process of data analysis

For CNV detection workflow refer to White et al. (2014).

FIGURE 2. Flow chart depicting the distribution of CNVs in each cohort

The total count of CNVs and in parenthesis, the subset of CNVs containing genes, are presented. Row I reports all CNVs; Row II describes inheritance status for Cohort 1; Rows III and IV report the number of rare and very rare CNVs as defined in Methods, respectively.

FIGURE 3. Gene interaction network clustering using ReactomeFIViz

Top function within each cluster is highlighted on top of each cluster. a The figure is constructed using genes from rare CNVs from Cohort 1. b The figure is constructed using genes from rare CNVs from Cohort 2. Each circle represents one unique Refseq gene with different shades representing different interaction network clusters identified from those genes. To simplify figure presentation, we annotated each module using its top enriched function or more abundant functional categories to illustrate each module’s functional characterization. Different connecting lines represent different biological events as illustrated in the legend in the figure.