Clinical exome sequencing efficacy and phenotypic expansions involving anomalous pulmonary venous return

Abstract

Anomalous pulmonary venous return (APVR) frequently occurs with other congenital heart defects (CHDs) or extra-cardiac anomalies. While some genetic causes have been identified, the optimal approach to genetic testing in individuals with APVR remains uncertain, and the etiology of most cases of APVR is unclear. Here, we analyzed molecular data from 49 individuals to determine the diagnostic yield of clinical exome sequencing (ES) for non-isolated APVR. A definitive or probable diagnosis was made for 8 of those individuals yielding a diagnostic efficacy rate of 16.3%. We then analyzed molecular data from 62 individuals with APVR accrued from three databases to identify novel APVR genes. Based on data from this analysis, published case reports, mouse models, and/or similarity to known APVR genes as revealed by a machine learning algorithm, we identified 3 genes-EFTUD2, NAA15, and NKX2-1-for which there is sufficient evidence to support phenotypic expansion to include APVR. We also provide evidence that 3 recurrent copy number variants contribute to the development of APVR: proximal 1q21.1 microdeletions involving RBM8A and PDZK1, recurrent BP1-BP2 15q11.2 deletions, and central 22q11.2 deletions involving CRKL. Our results suggest that ES and chromosomal microarray analysis (or genome sequencing) should be considered for individuals with non-isolated APVR for whom a genetic etiology has not been identified, and that genetic testing to identify an independent genetic etiology of APVR is not warranted in individuals with EFTUD2-, NAA15-, and NKX2-1-related disorders.

Fig. 1. Machine learning allows all RefSeq genes to be ranked based on their similarity to genes known to cause APVR.

A The machine learning algorithm was trained using 35 genes known to cause APVR in humans and the human homologs of genes that cause APVR in mice. Receiver operating characteristic (ROC) style curves were generated based on a leave-one-out validation study analysis performed for each knowledge source: Gene Ontology (GO), Mouse Genome Database (MGI), Protein Interaction Network Analysis (PINA), GeneAtlas expression distribution (Exp), and transcription factor binding (TF) and epigenetic histone modifications data (Epi) from NIH Roadmap Epigenomics Mapping Consortium. The black curve represents an omnibus score whose positive deviation indicates that our algorithm can identify genes in the training set more effectively than chance (diagonal line). After validation, ARMs-specific pathogenicity scores were calculated for all RefSeq genes. B Box plot showing the algorithmically generated APVR-specific pathogenicity scores for APVR training genes.

Fig. 2. Study workflow.

A diagram showing the workflow by which phenotypic expansions involving APVR were identified.

Fig. 3. Copy number variants recurrently associated with APVR.

A S10 and S12 carried deletions affecting a region of chromosome 1q21.1. The recurrent deletions associated with TAR syndrome (MIM# 274000) occur between BP2 and BP3 low copy repeat (LCR) regions (shown). S10 has molecularly confirmed TAR syndrome caused by a pathogenic RBM8A sequence in trans with a 1q21.1 deletion of an unspecified size (not shown). S12 had TAPVR and heterotaxy and carried a 384.4 kb deletion. Liu et al. described an individual who had a complex CHD with laterality defects and heterotaxy who carried a deletion that included PDZK1 but not RBM8A [37]. The smallest region of overlap is shown by dashed vertical lines. B S31 had PAPVR and carried a 1.05 Mb central 22q11.21 deletion shown. A mother and her son were previously reported to both have TAPVR and central 22q11.21 deletions [40]. The smallest region of overlap includes CRKL and is shown by dashed vertical lines. C 13 had TAPVR and carried a 555.4 kb deletion of chromosome 2q31.3q32.1. Lalani et al. previously reported an individual with APVR and 625 kb deletion [20]. The smallest region of overlap is shown by dashed vertical lines. Currently there is insufficient evidence to support an association between this region and the development of APVR.