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

Authors

  • E. Audain
  • A. Wilsdon
  • J. Breckpot
  • J.M. Izarzugaza
  • T.W. Fitzgerald
  • A.K. Kahlert
  • A. Sifrim
  • F. Wünnemann
  • Y. Perez-Riverol
  • H. Abdul-Khaliq
  • M. Bak
  • A.S. Bassett
  • W.D. Benson
  • F. Berger
  • I. Daehnert
  • K. Devriendt
  • S. Dittrich
  • P.E. Daubeney
  • V. Garg
  • K. Hackmann
  • K. Hoff
  • P. Hofmann
  • G. Dombrowsky
  • T. Pickardt
  • U. Bauer
  • B.D. Keavney
  • S. Klaassen
  • H.H. Kramer
  • C.R. Marshall
  • D.M. Milewicz
  • S. Lemaire
  • J.S. Coselli
  • M.E. Mitchell
  • A. Tomita-Mitchell
  • S.K. Prakash
  • K. Stamm
  • A.F.R. Stewart
  • C.K. Silversides
  • R. Siebert
  • B. Stiller
  • J.A. Rosenfeld
  • I. Vater
  • A.V. Postma
  • A. Caliebe
  • J.D. Brook
  • G. Andelfinger
  • M.E. Hurles
  • B. Thienpont
  • L.A. Larsen
  • M.P. Hitz

Journal

  • PLoS Genetics

Citation

  • PLoS Genet 17 (7): e1009679

Abstract

  • 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 parent-offspring 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.


DOI

doi:10.1371/journal.pgen.1009679