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.

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Fig. 1: Machine learning allows all RefSeq genes to be ranked based on their similarity to genes known to cause APVR.
Fig. 2: Study workflow.
Fig. 3: Copy number variants recurrently associated with APVR.

Data availability

The data generated during this study can be found within the published article and its supplementary files. All previously unpublished variants from the BG clinical database and the CCVM database have been submitted to the ClinVar database (https://www.ncbi.nlm.nih.gov/clinvar/; SNVs = SCV003915701 – SCV003915719; CNVs = SCV003919100 – SCV003919143).

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Acknowledgements

This study makes use of data generated by the DECIPHER community. A full list of centers who contributed to the generation of the data is available from https://deciphergenomics.org/about/stats and via email from [email protected]. We note that those who carried out the original analysis and collection of the DECIPHER data bear no responsibility for the further analysis or interpretation of the data.

Funding

This work was supported, in part, by National Institutes of Health/Eunice Kennedy Shriver National Institute of Child Health and Human Development grant R01HD098458 to DAS. The CCVM Registry is supported in part by American Heart Association Transformational Award AHA 19TPA34850054 (SMW). Funding for the DECIPHER project was provided by Wellcome.

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Authors

Contributions

DAS conceived the study. EAH wrote the first draft of the manuscript. CAS and PNL were responsible for the machine learning. XZ and NO were responsible for providing updated SNV and CNV variant interpretations, respectively, based on ACMG criteria. IV, ILHD, SJ, JC-S, MJP, JJL, MG, JB, AK, ES, UK, TB, TYT, RA, KN, GBF, AB, WSK-F, JR, LRH, BJL, GCG, KLM, SMW, and SRL obtained and provided clinical and molecular data. EAH and DAS analyzed clinical and molecular data. All authors reviewed, edited, and approved the final draft.

Corresponding author

Correspondence to
Daryl A. Scott.

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Competing interests

The Department of Molecular & Human Genetics at Baylor College of Medicine receives revenue from clinical genetic testing completed at Baylor Genetics.

Ethical approval

This study was approved by the institutional review board of Baylor College of Medicine (protocol H-47546) and was conducted in accordance with the ethical standards of this institution’s committee on human research and international standards.

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Table S1

Table S2

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Huth, E.A., Zhao, X., Owen, N. et al. Clinical exome sequencing efficacy and phenotypic expansions involving anomalous pulmonary venous return.
Eur J Hum Genet (2023). https://doi.org/10.1038/s41431-023-01451-4

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  • Received: 27 April 2023

  • Revised: 08 August 2023

  • Accepted: 24 August 2023

  • Published: 07 September 2023

  • DOI: https://doi.org/10.1038/s41431-023-01451-4

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