Abstract

Dilated cardiomyopathy (DCM) is a leading cause of morbidity and mortality worldwide; yet how genetic variation and environmental factors impact DCM heritability remains unclear. Here, we report that compound genetic interactions between DNA sequence variants contribute to the complex heritability of DCM. By using genetic data from a large family with a history of DCM, we discovered that heterozygous sequence variants in the TROPOMYOSIN 1 (TPM1) and VINCULIN (VCL) genes cosegregate in individuals affected by DCM. In vitro studies of patient-derived and isogenic human-pluripotent-stem-cell-derived cardiomyocytes that were genome-edited via CRISPR to create an allelic series of TPM1 and VCL variants revealed that cardiomyocytes with both TPM1 and VCL variants display reduced contractility and sarcomeres that are less organized. Analyses of mice genetically engineered to harbour these human TPM1 and VCL variants show that stress on the heart may also influence the variable penetrance and expressivity of DCM-associated genetic variants in vivo. We conclude that compound genetic variants can interact combinatorially to induce DCM, particularly when influenced by other disease-provoking stressors.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Code availability

All custom code used in this study can be found at http://github.com/englea52/Englerlab or https://github.com/enfarah/digital_karyotype.

Data availability

The authors declare that all data supporting the findings of this study are available within the paper and its Supplementary Information. The materials and data of this study are available from the corresponding author on reasonable request, with the exception of patient DNA and tissue, which is limited and protected by local and federal privacy regulations. Microarray study and RNA-seq data are available via dbGaP with GEO accession numbers GSE121844 and GSE121559.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. 1.

    Hershberger, R. E., Hedges, D. J. & Morales, A. Dilated cardiomyopathy: the complexity of a diverse genetic architecture. Nat. Rev. Cardiol. 10, 531–547 (2013).

  2. 2.

    Benjamin, E. J. et al. Heart disease and stroke statistics—2017 update: a report from the American Heart Association. Circulation 135, e146–e603 (2017).

  3. 3.

    Stenson, P. D. et al. The Human Gene Mutation Database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies. Hum. Genet. 136, 665–677 (2017).

  4. 4.

    Villard, E. et al. A genome-wide association study identifies two loci associated with heart failure due to dilated cardiomyopathy. Eur. Heart J. 32, 1065–1076 (2011).

  5. 5.

    Meder, B. et al. A genome-wide association study identifies 6p21 as novel risk locus for dilated cardiomyopathy. Eur. Heart J. 35, 1069–1077 (2014).

  6. 6.

    Li, L., Bainbridge, M. N., Tan, Y., Willerson, J. T. & Marian, A. J. A potential oligogenic etiology of hypertrophic cardiomyopathy: a classic single gene disorder. Circ. Res. 126, 1084–1090 (2017).

  7. 7.

    Roncarati, R. et al. Doubly heterozygous LMNA and TTN mutations revealed by exome sequencing in a severe form of dilated cardiomyopathy. Eur. J. Hum. Genet. 21, 1105–1111 (2013).

  8. 8.

    Maron, B. J., Maron, M. S. & Semsarian, C. Double or compound sarcomere mutations in hypertrophic cardiomyopathy: a potential link to sudden death in the absence of conventional risk factors. Heart Rhythm 9, 57–63 (2012).

  9. 9.

    Petropoulou, E. et al. Digenic inheritance of mutations in the cardiac troponin (TNNT2) and cardiac beta myosin heavy chain (MYH7) as the cause of severe dilated cardiomyopathy. Eur. J. Med. Genet. 60, 485–488 (2017).

  10. 10.

    Haas, J. et al. Atlas of the clinical genetics of human dilated cardiomyopathy. Eur. Heart J. 36, 1123–1135 (2014).

  11. 11.

    Kimura, A. Molecular genetics and pathogenesis of cardiomyopathy. J. Hum. Genet. 61, 41–50 (2016).

  12. 12.

    Olson, T. M., Kishimoto, N. Y., Whitby, F. G. & Michels, V. V. Mutations that alter the surface charge of alpha-tropomyosin are associated with dilated cardiomyopathy. J. Mol. Cell. Cardiol. 33, 723–732 (2001).

  13. 13.

    Whitby, F. G. & Phillips, G. N. Crystal structure of tropomyosin at 7 Angstroms resolution. Proteins 38, 49–59 (2000).

  14. 14.

    Panopoulos, A. D. et al. iPSCORE: a resource of 222 iPSC lines enabling functional characterization of genetic variation across a variety of cell types. Stem Cell Rep. 8, 1086–1100 (2017).

  15. 15.

    Hsu, P. D. et al. DNA targeting specificity of RNA-guided Cas9 nucleases. Nat. Biotechnol. 31, 827–832 (2013).

  16. 16.

    Lian, X. et al. Directed cardiomyocyte differentiation from human pluripotent stem cells by modulating Wnt/β-catenin signaling under fully defined conditions. Nat. Protoc. 8, 162–175 (2013).

  17. 17.

    Tohyama, S. et al. Distinct metabolic flow enables large-scale purification of mouse and human pluripotent stem cell-derived cardiomyocytes. Cell Stem Cell 12, 127–137 (2012).

  18. 18.

    Dhalla, A. K., Hill, M. F. & Singal, P. K. Role of oxidative stress in transition of hypertrophy to heart failure. J. Am. Coll. Cardiol. 28, 506–514 (1996).

  19. 19.

    Rosenkranz, S. et al. Alterations of β-adrenergic signaling and cardiac hypertrophy in transgenic mice overexpressing TGF-β1. Am. J. Physiol. Heart Circ. Physiol. 283, H1253–H1262 (2002).

  20. 20.

    Razeghi, P. et al. Metabolic gene expression in fetal and failing human heart. Circulation 104, 2923–2931 (2001).

  21. 21.

    Bristow, M. R. et al. β1- and β2-adrenergic-receptor subpopulations in nonfailing and failing human ventricular myocardium: coupling of both receptor subtypes to muscle contraction and selective β1-receptor down-regulation in heart failure. Circ. Res. 59, 297–309 (1986).

  22. 22.

    Hinson, J. T. et al. HEART DISEASE. Titin mutations in iPS cells define sarcomere insufficiency as a cause of dilated cardiomyopathy. Science 349, 982–986 (2015).

  23. 23.

    Szklarczyk, D. et al. STRINGv10: protein–protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 43, D447–D452 (2015).

  24. 24.

    Xu, W., Baribault, H. & Adamson, E. D. Vinculin knockout results in heart and brain defects during embryonic development. Development 125, 327–337 (1998).

  25. 25.

    Rockman, H. A. et al. Segregation of atrial-specific and inducible expression of an atrial natriuretic factor transgene in an in vivo murine model of cardiac hypertrophy. Proc. Natl Acad. Sci. USA 88, 8277–8281 (1991).

  26. 26.

    Golbus, J. R. et al. Population-based variation in cardiomyopathy genes. Circ. Cardiovasc. Genet. 5, 391–399 (2012).

  27. 27.

    McNally, E. M. & Puckelwartz, M. J. Genetic variation in cardiomyopathy and cardiovascular disorders. Circ. J. 79, 1409–1415 (2015).

  28. 28.

    Lek, M. et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature 536, 285–291 (2016).

  29. 29.

    Happe, C. L. & Engler, A. J. Mechanical forces reshape differentiation cues that guide cardiomyogenesis. Circ. Res. 118, 296–310 (2016).

  30. 30.

    Khera, A. V. et al. Genetic risk, adherence to a healthy lifestyle, and coronary disease. N. Engl. J. Med. 375, 2349–2358 (2016).

  31. 31.

    Therneau, T. M. et al. kinship2: pedigree functions v.1.6.4. (CRAN, 2015); https://cran.r-project.org/package=kinship2

  32. 32.

    Marschner, I.C. & Donoghoe, M. W. glm2: fitting generalized linear models v.1.2.1. (CRAN, 2018); https://CRAN.R-project.org/package=glm2

  33. 33.

    Abecasis, G. R., Cherny, S. S., Cookson, W. O. & Cardon, L. R. Merlin—rapid analysis of dense genetic maps using sparse gene flow trees. Nat. Genet. 30, 97–101 (2002).

  34. 34.

    McGregor, T. L. et al. Consanguinity mapping of congenital heart disease in a South Indian population. PLoS ONE 5, e10286 (2010).

  35. 35.

    Purcell, S., Cherny, S. S. & Sham, P. C. Genetic Power Calculator: design of linkage and association genetic mapping studies of complex traits. Bioinformatics 19, 149–150 (2003).

  36. 36.

    Hashem, S. I. et al. Oxidative stress mediates cardiomyocyte apoptosis in a human model of Danon disease and heart failure. Stem Cells 33, 2343–2350 (2015).

  37. 37.

    Carter, M. S. et al. A regulatory mechanism that detects premature nonsense codons in T-cell receptor transcripts in vivo is reversed by protein synthesis inhibitors in vitro. J. Biol. Chem. 270, 28995–29003 (1995).

  38. 38.

    Byrne, S. M., Mali, P. & Church, G. M. in Methods in Enzymolology, Vol. 546 (eds Doudna, J.A. & Sontheimer, E.J.) 119–138 (Elsevier, Amsterdam, 2014).

  39. 39.

    Yang, L., Mali, P., Kim-Kiselak, C. & Church, G. CRISPR–Cas-mediated targeted genome editing in human cells. Methods Mol. Biol. 1114, 245–267 (2014).

  40. 40.

    Giacomelli, E. et al. Three-dimensional cardiac microtissues composed of cardiomyocytes and endothelial cells co-differentiated from human pluripotent stem cells. Development 144, 1008–1017 (2017).

  41. 41.

    Wu, H. et al. Epigenetic regulation of phosphodiesterases 2A and 3A underlies compromised β-adrenergic signaling in an iPSC model of dilated cardiomyopathy. Cell Stem Cell 17, 89–100 (2015).

  42. 42.

    Tse, J. R. & Engler, A. J. Preparation of hydrogel substrates with tunable mechanical properties. Curr. Protoc. Cell BioI. 47, 10.16.1–10.16.16 (2010).

  43. 43.

    del Alamo, J. C. et al. Three-dimensional quantification of cellular traction forces and mechanosensing of thin substrata by Fourier traction force microscopy. PLoS ONE 8, e69850 (2013).

  44. 44.

    Sayols, S., Scherzinger, D. & Klein, H. dupRadar: a Bioconductor package for the assessment of PCR artifacts in RNA-Seq data. BMC Bioinform. 17, 428 (2016).

  45. 45.

    Bray, N. L., Pimentel, H., Melsted, P. & Pachter, L. Near-optimal probabilistic RNA-seq quantification. Nat. Biotechnol. 34, 525–527 (2016).

  46. 46.

    Harrow, J. et al. GENCODE: the reference human genome annotation for the ENCODE Project. Genome Res. 22, 1760–1774 (2012).

  47. 47.

    Soneson, C., Love, M. I. & Robinson, M. D. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences. F1000Research 4, 1521 (2015).

  48. 48.

    Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

  49. 49.

    Tripathi, S. et al. Meta- and orthogonal integration of influenza “OMICs” data defines a role for UBR4 in virus budding. Cell Host Microbe 18, 723–735 (2015).

  50. 50.

    Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

  51. 51.

    Shen, S. et al. rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data. Proc. Natl Acad. Sci. USA 111, E5593–E5601 (2014).

  52. 52.

    Yang, H., Wang, H. & Jaenisch, R. Generating genetically modified mice using CRISPR/Cas-mediated genome engineering. Nat. Protoc. 9, 1956–1968 (2014).

  53. 53.

    Wang, H. et al. One-step generation of mice carrying mutations in multiple genes by CRISPR/Cas-mediated genome engineering. Cell 153, 910–918 (2013).

  54. 54.

    Li, R. et al. β1 integrin gene excision in the adult murine cardiac myocyte causes defective mechanical and signaling responses. Am. J. Pathol. 180, 952–962 (2012).

Download references

Acknowledgements

We thank the patients who participated in this study. K. DeMali (Univ. Iowa) provided the truncated Gallus gallus VCL peptide. Various experiments were conducted with the assistance, expertise and support of the following UCSD core facilities: Institute for Genomic Medicine Core, Mouse Transgenic Core, Histology and Immunohistochemistry Core, Seaweed Canyon Cardiovascular Physiology Laboratory, Microscopy Core and Human Embryonic Stem Cell Core facilities. We also thank P. Mali and H. Taylor-Weiner for assistance with hPSC culture, members of the Bruce Hamilton laboratory for helpful discussions and experimental design and members of the Chi lab for comments on the manuscript. This work was supported in part by grants from the NIH to N.C.C., J.C., R.S.R., E.D.A. and grant no. R01AG045428 to A.J.E. D.C.D. was supported by a CIRM pre-doctoral fellowship (grant no. TG2-01154) and an NIH pre-doctoral training grant (grant no. T32 GM008666). C.L.H. was supported by post-doctoral fellowships from the American Heart Association (grant no. 15POST25720070) and NIH (grant no. F32HL131424). J.C. is an American Heart Association Endowed Chair. E.N.F. was supported by a NIH pre-doctoral training grant (grant no. 4T32HL007444-34).

Author information

Author notes

  1. These authors contributed equally: Dekker C. Deacon, Cassandra L. Happe, Chao Chen.

Affiliations

  1. Division of Cardiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA

    • Dekker C. Deacon
    • , Chao Chen
    • , Neil Tedeschi
    • , Ana Maria Manso
    • , Ting Li
    • , Nancy D. Dalton
    • , Elie N. Farah
    • , Yusu Gu
    • , Ju Chen
    • , Kirk L. Peterson
    • , Eric D. Adler
    • , Robert S. Ross
    •  & Neil C. Chi
  2. Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA

    • Cassandra L. Happe
    • , Kevin P. Tenerelli
    • , Vivien D. Tran
    •  & Adam J. Engler
  3. Veterans Administration Healthcare San Diego, San Diego, CA, USA

    • Ana Maria Manso
    •  & Robert S. Ross
  4. Department of Neuroscience, The Scripps Research Institute, La Jolla, CA, USA

    • Qian Peng
  5. Department of Human Biology, J. Craig Venter Institute, La Jolla, CA, USA

    • Qian Peng
    •  & Nicholas J. Schork
  6. Sanford Consortium for Regenerative Medicine, La Jolla, CA, USA

    • Adam J. Engler
  7. Institute of Genomic Medicine, University of California, San Diego, La Jolla, CA, USA

    • Neil C. Chi

Authors

  1. Search for Dekker C. Deacon in:

  2. Search for Cassandra L. Happe in:

  3. Search for Chao Chen in:

  4. Search for Neil Tedeschi in:

  5. Search for Ana Maria Manso in:

  6. Search for Ting Li in:

  7. Search for Nancy D. Dalton in:

  8. Search for Qian Peng in:

  9. Search for Elie N. Farah in:

  10. Search for Yusu Gu in:

  11. Search for Kevin P. Tenerelli in:

  12. Search for Vivien D. Tran in:

  13. Search for Ju Chen in:

  14. Search for Kirk L. Peterson in:

  15. Search for Nicholas J. Schork in:

  16. Search for Eric D. Adler in:

  17. Search for Adam J. Engler in:

  18. Search for Robert S. Ross in:

  19. Search for Neil C. Chi in:

Contributions

D.C.D., C.L.H., C.C., A.J.E., R.S.R. and N.C.C. conceived the project. D.C.D., C.L.H., C.C., N.T., A.M.M., T.L., N.D.D., Q.P., E.N.F., Y.G., K.P.T., V.D.T., J.C. and K.L.P. planned the design of studies and conducted experiments. D.C.D. and E.D.A. recruited patients and generated human fibroblast lines. D.C.D. generated CRISPR-edited mouse lines and C.L.H. generated CRISPR-edited hESC lines. Q.P., J.C., K.L.P. and N.J.S. assisted in data interpretation and provided experimental advice. D.C.D., C.L.H., C.C., A.J.E., R.S.R. and N.C.C. prepared and wrote the manuscript.

Competing interests

The authors declare no competing interests.

Corresponding authors

Correspondence to Adam J. Engler or Robert S. Ross or Neil C. Chi.

Supplementary information

  1. Supplementary Information

    Supplementary figures, tables, references and video captions.

  2. Reporting summary

  3. Supplementary Video 1

    Representative parasternal short axis left ventricular views of mouse echocardiography pre-surgery for WT mice.

  4. Supplementary Video 2

    Representative parasternal short axis left ventricular views of mouse echocardiography post-TAC for WT mice.

  5. Supplementary Video 3

    Representative parasternal short axis left ventricular views of mouse echocardiography pre-surgery for VclVFS/+ mice.

  6. Supplementary Video 4

    Representative parasternal short axis left ventricular views of mouse echocardiography post-TAC for VclVFS/+ mice.

  7. Supplementary Video 5

    Representative parasternal short axis left ventricular views of mouse echocardiography pre-surgery for Tpm1TEK/+ mice.

  8. Supplementary Video 6

    Representative parasternal short axis left ventricular views of mouse echocardiography post-TAC for Tpm1TEK/+ mice.

  9. Supplementary Video 7

    Representative parasternal short axis left ventricular views of mouse echocardiography pre-surgery for TV-Dhet mice.

  10. Supplementary Video 8

    Representative parasternal short axis views of TV-Dhet mouse echocardiography reveals grossly decreased left ventricular function post-TAC.

  11. Supplementary Table 2

    Differentially expressed genes revealed by RNA-seq of TV-Dhet, and control hiPSC-cardiomyocytes.

  12. Supplementary Table 8

    Primers, guideRNA (gRNA), and single strand DNA oligonucleotide (ssDNA) sequences.

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/s41551-019-0348-9