Genes and Pathways Implicated in Tetralogy of Fallot Revealed by Ultra-Rare Variant Burden Analysis in 231 Genome Sequences

Recent genome-wide studies of rare genetic variants have begun to implicate novel mechanisms for tetralogy of Fallot (TOF), a severe congenital heart defect (CHD). To provide statistical support for case-only data without parental genomes, we re-analyzed genome sequences of 231 individuals with TOF (n = 175) or related CHD. We adapted a burden test originally developed for de novo variants to assess ultra-rare variant burden in individual genes, and in gene-sets corresponding to functional pathways and mouse phenotypes, accounting for highly correlated gene-sets and for multiple testing. For truncating variants, the gene burden test confirmed significant burden in FLT4 (Bonferroni corrected p-value < 0.01). For missense variants, burden in NOTCH1 achieved genome-wide significance only when restricted to constrained genes (i.e., under negative selection, Bonferroni corrected p-value = 0.004), and showed enrichment for variants affecting the extracellular domain, especially those disrupting cysteine residues forming disulfide bonds (OR = 39.8 vs. gnomAD). Individuals with NOTCH1 ultra-rare missense variants, all with TOF, were enriched for positive family history of CHD. Other genes not previously implicated in CHD had more modest statistical support in gene burden tests. Gene-set burden tests for truncating variants identified a cluster of pathways corresponding to VEGF signaling (FDR = 0%), and of mouse phenotypes corresponding to abnormal vasculature (FDR = 0.8%); these suggested additional candidate genes not previously identified (e.g., WNT5A and ZFAND5). Results for the most promising genes were driven by the TOF subset of the cohort. The findings support the importance of ultra-rare variants disrupting genes involved in VEGF and NOTCH signaling in the genetic architecture of TOF, accounting for 11–14% of individuals in the TOF cohort. These proof-of-principle data indicate that this statistical methodology could assist in analyzing case-only sequencing data in which ultra-rare variants, whether de novo or inherited, contribute to the genetic etiopathogenesis of a complex disorder.