Integrative analysis of genomic variants reveals new associations of candidate haploinsufficient genes with congenital heart disease

Enrique Audain, Anna Wilsdon, Jeroen Breckpot, Jose M.G. Izarzugaza, Tomas W. Fitzgerald, Anne Karin Kahlert, Alejandro Sifrim, Florian Wünnemann, Yasset Perez-Riverol, Hashim Abdul-Khaliq, Mads Bak, Anne S. Bassett, Woodrow D. Benson, Felix Berger, Ingo Daehnert, Koenraad Devriendt, Sven Dittrich, Piers E.F. Daubeney, Vidu Garg, Karl HackmannKirstin Hoff, Philipp Hofmann, Gregor Dombrowsky, Thomas Pickardt, Ulrike Bauer, Bernard D. Keavney, Sabine Klaassen, Hans Heiner Kramer, Christian R. Marshall, Dianna M. Milewicz, Scott Lemaire, Joseph S. Coselli, Michael E. Mitchell, Aoy Tomita-Mitchell, Siddharth K. Prakash, Karl Stamm, Alexandre F.R. Stewart, Candice K. Silversides, Reiner Siebert, Brigitte Stiller, Jill A. Rosenfeld, Inga Vater, Alex V. Postma, Almuth Caliebe, J. David Brook, Gregor Andelfinger, Matthew E. Hurles, Bernard Thienpont, Lars Allan Larsen, Marc Phillip Hitz*

*Corresponding author for this work

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Numerous genetic studies have established a role for rare genomic variants in Congenital Heart Disease (CHD) at the copy number variation (CNV) and de novo variant (DNV) level. To identify novel haploinsufficient CHD disease genes, we performed an integrative analysis of CNVs and DNVs identified in probands with CHD including cases with sporadic thoracic aortic aneurysm. We assembled CNV data from 7,958 cases and 14,082 controls and performed a gene-wise analysis of the burden of rare genomic deletions in cases versus controls. In addition, we performed variation rate testing for DNVs identified in 2,489 parentoffspring trios. Our analysis revealed 21 genes which were significantly affected by rare CNVs and/or DNVs in probands. Fourteen of these genes have previously been associated with CHD while the remaining genes (FEZ1, MYO16, ARID1B, NALCN, WAC, KDM5B and WHSC1) have only been associated in small cases series or show new associations with CHD. In addition, a systems level analysis revealed affected protein-protein interaction networks involved in Notch signaling pathway, heart morphogenesis, DNA repair and cilia/centrosome function. Taken together, this approach highlights the importance of re-analyzing existing datasets to strengthen disease association and identify novel disease genes and pathways. This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Original languageEnglish
Article numbere1009679
JournalPLOS Genetics
Issue number7
Number of pages24
Publication statusPublished - 2021


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