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121 Re-evaluating the genetic contribution of monogenic dilated cardiomyopathy
  1. Francesco Mazzarotto1,
  2. Paz Tayal2,
  3. Rachel Buchan2,
  4. William Midwinter2,
  5. Alicja Wilk2,
  6. Nicola Whiffin2,
  7. Risha Govind3,
  8. Erica Mazaika2,
  9. Antonio De Marvao2,
  10. Leanne Felkin2,
  11. Timothy Dawes2,
  12. Mian Ahmad2,
  13. Elizabeth Edwards4,
  14. Alexander Ing5,
  15. Kate Thomson6,
  16. Laura Chan7,
  17. David Sim7,
  18. John Baksi2,
  19. Antonis Pantazis8,
  20. Angharad Roberts2,
  21. Hugh Watkins9,
  22. Birgit Funke10,
  23. Declan O’Regan2,
  24. Iacopo Olivotto11,
  25. Paul Barton2,
  26. Sanjay Prasad2,
  27. Stuart Cook7,
  28. James Ware2,
  29. Roddy Walsh12
  1. 1University of Florence - Imperial College London
  2. 2Imperial College London
  3. 3Kings College London
  4. 4Genomics UK
  5. 5Lurie Children’s Hospital Chicago
  6. 6Oxford University Hospitals
  7. 7National Heart Centre Singapore
  8. 8Royal Brompton and Harefield NHS Trust
  9. 9University of Oxford
  10. 10Harvard Medical School
  11. 11University of Florence
  12. 12Academic Medical Center - Amsterdam


Introduction Dilated cardiomyopathy (DCM) is genetically heterogeneous, with >100 purported disease genes tested in clinical laboratories. However, many genes were originally identified based on candidate-gene studies that did not adequately account for background population variation. Here we define the frequency of rare variation in 2538 DCM patients across protein-coding regions of 56 commonly tested genes and compare this to both 912 confirmed healthy controls and a reference population of 60,706 individuals in order to identify clinically interpretable genes robustly associated with dominant monogenic DCM.

Methods We used the TruSight Cardio sequencing panel to evaluate the burden of rare variants in 56 putative DCM genes in 1040 DCM patients and 912 healthy volunteers processed with identical sequencing and bioinformatics pipelines. We further aggregated data from 1498 DCM patients sequenced in diagnostic laboratories and the ExAC database for replication and meta-analysis.

Results Specific variant classes in TTN, DSP, MYH7 and LMNA were associated with DCM in all comparisons. Variants in BAG3, TNNT2, TPM1, NEXN and VCL were significantly enriched specific patient subsets, with the last 3 genes likely contributing primarily to early-onset forms of DCM. Overall, rare variants in these 9 genes potentially explained 19–26% of cases. Whilst the absence of a significant excess in other genes cannot preclude a role in disease, such genes have limited diagnostic value since novel variants will be uninterpretable and therefore non-actionable, and their diagnostic yield is minimal.

Conclusion In the largest sequenced DCM cohort yet described, we observe robust disease association with 9 genes, highlighting their importance in DCM and translating into high interpretability in diagnostic testing. The other genes evaluated have limited value in diagnostic testing in DCM. This data will contribute to community gene curation efforts, and will reduce erroneous and inconclusive findings in diagnostic testing.

Conflict of Interest None

  • Dilated Cardiomyopathy
  • Genetics
  • Exome Aggregation Consortium

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