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Genetic association analyses highlight biological pathways underlying mitral valve prolapse

Nature Genetics volume 47, pages 1206–1211 (2015)Cite this article

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Abstract

Nonsyndromic mitral valve prolapse (MVP) is a common degenerative cardiac valvulopathy of unknown etiology that predisposes to mitral regurgitation, heart failure and sudden death1. Previous family and pathophysiological studies suggest a complex pattern of inheritance2,3,4,5. We performed a meta-analysis of 2 genome-wide association studies in 1,412 MVP cases and 2,439 controls. We identified 6 loci, which we replicated in 1,422 cases and 6,779 controls, and provide functional evidence for candidate genes. We highlight LMCD1 (LIM and cysteine-rich domains 1), which encodes a transcription factor6 and for which morpholino knockdown of the ortholog in zebrafish resulted in atrioventricular valve regurgitation. A similar zebrafish phenotype was obtained with knockdown of the ortholog of TNS1, which encodes tensin 1, a focal adhesion protein involved in cytoskeleton organization. We also showed expression of tensin 1 during valve morphogenesis and describe enlarged posterior mitral leaflets in Tns1−/− mice. This study identifies the first risk loci for MVP and suggests new mechanisms involved in mitral valve regurgitation, the most common indication for mitral valve repair7.

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Figure 1: Plots representing the association of 4.8 million SNPs in the GWAS meta-analysis.
Figure 2: Cardiac regurgitation in zebrafish embryos with morpholino-mediated knockdown of orthologs to the candidate genes at 2q35 in human.
Figure 3: Tensin 1 expression in developing mouse valves and the knockout phenotype at 9 months.
Figure 4: Cardiac regurgitation in zebrafish embryos with morpholino-mediated knockdown of the ortholog of LMCD1 at 3p13 in human.

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References

  1. Freed, L.A. et al. Mitral valve prolapse in the general population: the benign nature of echocardiographic features in the Framingham Heart Study. J. Am. Coll. Cardiol. 40, 1298–1304 (2002).

    Article  Google Scholar 

  2. Disse, S. et al. Mapping of a first locus for autosomal dominant myxomatous mitral valve prolapse to chromosome 16p11.2-p12.1. Am. J. Hum. Genet. 65, 1242–1251 (1999).

    Article  CAS  Google Scholar 

  3. Freed, L.A. et al. A locus for autosomal dominant mitral valve prolapse on chromosome 11p15.4. Am. J. Hum. Genet. 72, 1551–1559 (2003).

    Article  CAS  Google Scholar 

  4. Kyndt, F. et al. Mapping of X-linked myxomatous valvular dystrophy to chromosome Xq28. Am. J. Hum. Genet. 62, 627–632 (1998).

    Article  CAS  Google Scholar 

  5. Nesta, F. et al. New locus for autosomal dominant mitral valve prolapse on chromosome 13: clinical insights from genetic studies. Circulation 112, 2022–2030 (2005).

    Article  Google Scholar 

  6. Rath, N., Wang, Z., Lu, M.M. & Morrisey, E.E. LMCD1/Dyxin is a novel transcriptional cofactor that restricts GATA6 function by inhibiting DNA binding. Mol. Cell. Biol. 25, 8864–8873 (2005).

    Article  CAS  Google Scholar 

  7. Avierinos, J.F. et al. Natural history of asymptomatic mitral valve prolapse in the community. Circulation 106, 1355–1361 (2002).

    Article  Google Scholar 

  8. Freed, L.A. et al. Prevalence and clinical outcome of mitral valve prolapse. N. Engl. J. Med. 341, 1–7 (1999).

    Article  CAS  Google Scholar 

  9. Devereux, R.B., Brown, W.T., Kramer-Fox, R. & Sachs, I. Inheritance of mitral valve prolapse: effect of age and sex on gene expression. Ann. Intern. Med. 97, 826–832 (1982).

    Article  CAS  Google Scholar 

  10. Delling, F.N. et al. Mild expression of mitral valve prolapse in the Framingham offspring: expanding the phenotypic spectrum. J. Am. Soc. Echocardiogr. 27, 17–23 (2014).

    Article  Google Scholar 

  11. Glesby, M.J. & Pyeritz, R.E. Association of mitral valve prolapse and systemic abnormalities of connective tissue. A phenotypic continuum. J. Am. Med. Assoc. 262, 523–528 (1989).

    Article  CAS  Google Scholar 

  12. Hagège, A.A. et al. The mitral valve in hypertrophic cardiomyopathy: old versus new concepts. J. Cardiovasc. Transl. Res. 4, 757–766 (2011).

    Article  Google Scholar 

  13. Kyndt, F. et al. Mutations in the gene encoding filamin A as a cause for familial cardiac valvular dystrophy. Circulation 115, 40–49 (2007).

    Article  CAS  Google Scholar 

  14. Hall, E.H., Daugherty, A.E., Choi, C.K., Horwitz, A.F. & Brautigan, D.L. Tensin1 requires protein phosphatase-1α in addition to RhoGAP DLC-1 to control cell polarization, migration and invasion. J. Biol. Chem. 284, 34713–34722 (2009).

    Article  CAS  Google Scholar 

  15. Sureshbabu, A. et al. IGFBP5 induces cell adhesion, increases cell survival and inhibits cell migration in MCF-7 human breast cancer cells. J. Cell Sci. 125, 1693–1705 (2012).

    Article  CAS  Google Scholar 

  16. Chang, C.Y., Lin, S.C., Su, W.H., Ho, C.M. & Jou, Y.S. Somatic LMCD1 mutations promoted cell migration and tumor metastasis in hepatocellular carcinoma. Oncogene 31, 2640–2652 (2012).

    Article  CAS  Google Scholar 

  17. Bian, Z.Y. et al. LIM and cysteine-rich domains 1 regulates cardiac hypertrophy by targeting calcineurin–nuclear factor of activated T cells signaling. Hypertension 55, 257–263 (2010).

    Article  CAS  Google Scholar 

  18. Beis, D. et al. Genetic and cellular analyses of zebrafish atrioventricular cushion and valve development. Development 132, 4193–4204 (2005).

    Article  CAS  Google Scholar 

  19. Schunkert, H. et al. Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nat. Genet. 43, 333–338 (2011).

    Article  CAS  Google Scholar 

  20. Lockhart, M.M. et al. Mef2c regulates transcription of the extracellular matrix protein cartilage link protein 1 in the developing murine heart. PLoS ONE 8, e57073 (2013).

    Article  CAS  Google Scholar 

  21. Vasan, R.S. et al. Genetic variants associated with cardiac structure and function: a meta-analysis and replication of genome-wide association data. J. Am. Med. Assoc. 302, 168–178 (2009).

    Article  CAS  Google Scholar 

  22. Pyeritz, R.E. & Wappel, M.A. Mitral valve dysfunction in the Marfan syndrome. Clinical and echocardiographic study of prevalence and natural history. Am. J. Med. 74, 797–807 (1983).

    Article  CAS  Google Scholar 

  23. Ng, C.M. et al. TGF-β–dependent pathogenesis of mitral valve prolapse in a mouse model of Marfan syndrome. J. Clin. Invest. 114, 1586–1592 (2004).

    Article  CAS  Google Scholar 

  24. Rabkin, E. et al. Activated interstitial myofibroblasts express catabolic enzymes and mediate matrix remodeling in myxomatous heart valves. Circulation 104, 2525–2532 (2001).

    Article  CAS  Google Scholar 

  25. Lee, A.P. et al. Quantitative analysis of mitral valve morphology in mitral valve prolapse with real-time 3-dimensional echocardiography: importance of annular saddle shape in the pathogenesis of mitral regurgitation. Circulation 127, 832–841 (2013).

    Article  Google Scholar 

  26. Jensen, M.O., Hagege, A.A., Otsuji, Y., Levine, R.A. & Leducq Transatlantic MITRAL Network The unsaddled annulus: biomechanical culprit in mitral valve prolapse? Circulation 127, 766–768 (2013).

    Article  Google Scholar 

  27. Sauls, K. et al. Developmental basis for filamin-A–associated myxomatous mitral valve disease. Cardiovasc. Res. 96, 109–119 (2012).

    Article  CAS  Google Scholar 

  28. Levine, R.A. et al. Three-dimensional echocardiographic reconstruction of the mitral valve, with implications for the diagnosis of mitral valve prolapse. Circulation 80, 589–598 (1989).

    Article  CAS  Google Scholar 

  29. Levine, R.A., Stathogiannis, E., Newell, J.B., Harrigan, P. & Weyman, A.E. Reconsideration of echocardiographic standards for mitral valve prolapse: lack of association between leaflet displacement isolated to the apical four-chamber view and independent echocardiographic evidence of abnormality. J. Am. Coll. Cardiol. 11, 1010–1019 (1988).

    Article  CAS  Google Scholar 

  30. Delaneau, O., Marchini, J. & Zagury, J.F. A linear complexity phasing method for thousands of genomes. Nat. Methods 9, 179–181 (2012).

    Article  CAS  Google Scholar 

  31. Marchini, J., Howie, B., Myers, S., McVean, G. & Donnelly, P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat. Genet. 39, 906–913 (2007).

    Article  CAS  Google Scholar 

  32. Li, Y., Willer, C.J., Ding, J., Scheet, P. & Abecasis, G.R. MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genet. Epidemiol. 34, 816–834 (2010).

    Article  Google Scholar 

  33. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

    Article  CAS  Google Scholar 

  34. Stouffer, S.A., Suchman, E.A., Devinney, L.C., Star, S.A. & Williams, R.M. The American Soldier: Adjustment During Army Life (Princeton University Press, Princeton, New Jersey, USA, 1949).

  35. Willer, C.J., Li, Y. & Abecasis, G.R. METAL: fast and efficient meta-analysis of genome-wide association scans. Bioinformatics 26, 2190–2191 (2010).

    Article  CAS  Google Scholar 

  36. Pruim, R.J. et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics 26, 2336–2337 (2010).

    Article  CAS  Google Scholar 

  37. Norris, R.A. et al. Expression of the familial cardiac valvular dystrophy gene, filamin-A, during heart morphogenesis. Dev. Dyn. 239, 2118–2127 (2010).

    Article  CAS  Google Scholar 

  38. Milan, D.J., Giokas, A.C., Serluca, F.C., Peterson, R.T. & MacRae, C.A. Notch1b and neuregulin are required for specification of central cardiac conduction tissue. Development 133, 1125–1132 (2006).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We acknowledge the major contribution of the Leducq Foundation, Paris for supporting a transatlantic consortium investigating the physiopathology of mitral valve disease, for which this genome-wide association study was a major project (coordinators: R.A.L. and A.A.H.). We thank J. Leyton-Mange, X.-X. Nguyen and M. McLellan for help with the zebrafish experiments and P. Mathieu as one of the main investigators of the PROGRAM (Determinants of the Progression and Outcomes of Organic Mitral Regurgitation) study, from which was ascertained the Canadian MVP case control study. C.D., T.L.T. and J.-J.S. acknowledge a translational research grant on genetics of mitral valve funded by the Nantes Hospital (CHU Nantes). R.A.L. acknowledges grant support from the US National Institutes of Health (NIH; grants K24 HL67434, R01 HL72265 and HL109506). N.B.-N. is recipient of a French young investigator fund (ANR-13-ISV1-0006-0). D.J.M. acknowledges the support of the Hassenfeld Scholar Program and a gift from Michael Zak. P.T.E. is supported by grants from the NIH (HL092577, HL104156, K24HL105780, HL065962), an Established Investigator Award from the American Heart Association (13EIA14220013) and support from the Fondation Leducq (14CVD01). P.P. holds the Canada Research Chair in Valvular Heart Diseases and is supported by grants from the Canadian Institutes of Health Research (CIHR; grants MOP-102737, MOP-114997 and MOP-126072). Y.B. is the recipient of a Junior 2 Research Scholar award from the Fonds de recherche Québec–Santé (FRQS) and is supported by the CIHR (MOP-102481 and MOP-137058). L.F.-F. and J.S. received financial support from the Spanish Society of Cardiology. R.D. was supported by fellowships from the fund for medical discovery of the Massachusetts General Hospital and by a Marie Curie reintegration award from the European Commission R.R.M. and R.A.N. performed their work in a facility constructed with support from the US National Institutes of Health, grant C06 RR018823, from the Extramural Research Facilities Program of the Heart, Lung, and Blood Institute: R01-HL33756 (R.R.M.), COBRE 1P30 GM103342 (R.R.M. and R.A.N.), 8P20 GM103444-07 (R.R.M. and R.A.N.), R01-HL127692 (D.J.M., S.A.S. and R.A.N.) and American Heart Association 15GRNT25080052 (R.A.N.). A.A.H., N.B.-N. and X.J. acknowledge funds from INSERM and the French Society of Cardiology.

Author information

Author notes

  1. Christian Dina, Nabila Bouatia-Naji, Nathan Tucker and Xavier Jeunemaitre: These authors contributed equally to this work.

  2. Russell A Norris, David J Milan, Susan A Slaugenhaupt, Robert A Levine, Jean-Jacques Schott, Albert A Hagege and Xavier Jeunemaitre: These authors jointly supervised this work.

Authors and Affiliations

  1. INSERM Unité Mixte de Recherche (UMR) 1087, Centre National de la Recherche Scientifique (CNRS) UMR 6291, Institut du Thorax, Nantes, France

    Christian Dina, Thierry Le Tourneau, Vincent Probst, Floriane Simonet, Simon Lecointe, Florence Kyndt, Richard Redon, Hervé Le Marec & Jean-Jacques Schott

  2. Centre Hospitalier Universitaire (CHU) Nantes, Université de Nantes, Nantes, France

    Christian Dina, Thierry Le Tourneau, Vincent Probst, Simon Lecointe, Florence Kyndt, Richard Redon, Hervé Le Marec & Jean-Jacques Schott

  3. INSERM UMR 970, Paris Cardiovascular Research Center, Paris, France

    Nabila Bouatia-Naji, Maelle Perrocheau, Patrick Bruneval, Albert A Hagege & Xavier Jeunemaitre

  4. Paris Descartes University, Paris Sorbonne Cité, Paris, France

    Nabila Bouatia-Naji, Maelle Perrocheau, Serge Hercberg, Patrick Bruneval & Xavier Jeunemaitre

  5. Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, Massachusetts, USA

    Nathan Tucker, Elena Dolmatova, Patrick T Ellinor & David J Milan

  6. Division of Intramural Research, Framingham Heart Study, Population Sciences Branch, National Heart, Lung, and Blood Institute, US National Institutes of Health, Framingham, Massachusetts, USA

    Francesca N Delling, Ming-Huei Chen, Emelia J Benjamin & Ramachandran S Vasan

  7. Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA

    Francesca N Delling & Emelia J Benjamin

  8. Department of Regenerative Medicine and Cell Biology, Cardiovascular Developmental Biology Center, Children's Research Institute, Medical University of South Carolina, Charleston, South Carolina, USA

    Katelynn Toomer, Roger R Markwald & Russell A Norris

  9. Department of Cardiology, Hadassah Hebrew University Medical Center, Jerusalem, Israel

    Ronen Durst

  10. Hospital Universitario Montepríncipe, Universidad Centro de Estudios Universitarios (CEU) San Pablo, Madrid, Spain

    Leticia Fernandez-Friera & Jorge Solis

  11. Centro Nacional de Investigaciones Cardiovasculares, Carlos III (CNIC), Madrid, Spain

    Leticia Fernandez-Friera & Jorge Solis

  12. Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, USA

    Ming-Huei Chen

  13. Institut Universitaire de Cardiologie et de Pneumologie de Québec, Laval University, Quebec City, Quebec, Canada

    Yohan Bosse & Philippe Pibarot

  14. Centre National de Génotypage, Evry, France

    Diana Zelenika & Mark Lathrop

  15. Génome Québec, Montreal, Quebec, Canada

    Mark Lathrop

  16. Paris 13 University, Sorbonne Paris Cité, Bobigny, France

    Serge Hercberg

  17. INSERM U1153, Institut National de Recherche en Agronomie (INRA) U1125, Nutritional Epidemiology Research Unit, Epidemiology and Biostatistics Center, Bobigny, France

    Serge Hercberg

  18. Department of Public Health, Assistance Publique–Hôpitaux de Paris (AP-HP), Avicenne Hospital, Bobigny, France

    Serge Hercberg

  19. Paris Diderot University, Paris, France

    Serge Hercberg & Ronan Roussel

  20. INSERM UMRS 1138, Centre de Recherche des Cordeliers, Paris, France

    Ronan Roussel

  21. Department of Endocrinology, Respiratory and Renal Diseases (FIRE) Department Hospital University, AP-HP, Diabetes and Nutrition, Fibrosis, Inflammation, Remodeling in Cardiovascular, Bichat Hospital, Paris, France

    Ronan Roussel

  22. INSERM, Clinical Investigation Centre (CIC) 0203, University Hospital of Pontchaillou, Rennes, France

    Fabrice Bonnet

  23. Department of Endocrinology, University Hospital, Rennes, France

    Fabrice Bonnet

  24. Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, Davis, California, USA

    Su Hao Lo

  25. CNRS UMR 8199, Lille Pasteur Institute, Lille 2 University, European Genomic Institute for Diabetes (EGID), Lille, France

    Philippe Froguel

  26. Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, UK

    Philippe Froguel

  27. Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA

    Patrick T Ellinor

  28. Department of Pathology, AP-HP, Hôpital Européen Georges Pompidou, Paris, France

    Patrick Bruneval

  29. Center for Human Genetic Research, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA

    Susan A Slaugenhaupt

  30. Cardiac Ultrasound Laboratory, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA

    Robert A Levine

  31. Department of Cardiology, AP-HP, Hôpital Européen Georges Pompidou, Paris, France

    Albert A Hagege

  32. Department of Genetics, AP-HP, Hôpital Européen Georges Pompidou, Paris, France

    Xavier Jeunemaitre

Authors
  1. Christian Dina
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  2. Nabila Bouatia-Naji
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  3. Nathan Tucker
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  4. Francesca N Delling
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  5. Katelynn Toomer
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  12. Vincent Probst
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  14. Philippe Pibarot
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  15. Diana Zelenika
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Contributions

C.D., N.B.-N. and X.J. organized and designed the genome-wide association study and the manuscript preparation. A.A.H., R.A.L., S.A.S., H.L.M., P.P., J.S. and L.F.-F. organized and coordinated the network efforts and recruitment of patients. R.D., V.P., T.L.T., F.K., P.P. and Y.B. participated in the recruitment of patients and the interpretation of the echocardiographs. J.-J.S. and X.J. coordinated the collection of patient samples. M.P. and S.L. managed the collection of patient samples and performed DNA extraction and genotyping. C.D. and N.B.-N. conceptualized the statistical analyses. C.D. supervised the statistical analyses. C.D., M.-H.C. and F.S. performed the statistical analyses. D.J.M. conceptualized and supervised the zebrafish experiments. N.T. performed zebrafish experiments, interpreted the data and wrote parts of the manuscript. P.T.E. and E.D. participated in zebrafish experiments and interpretation of data. R.R.M. and R.A.N. conceptualized and supervised the mouse studies and interpreted the data. K.T. performed immunohistochemistry staining of mouse organs. S.H.L. generated the mice. F.N.D., E.J.B., D.Z., M.L., S.H., R. Roussel, F.B., R. Redon, P.F. and R.S.V. conducted the epidemiological studies in control cohorts and/or contributed samples to the GWAS and/or follow-up genotyping. P.B. supervised valve tissues DNA extraction. S.A.S. contributed patient samples and organized follow-up genotyping and interpreted the GWAS and follow-up data. C.D., N.B.-N. and X.J. wrote the manuscript. F.N.D., R.A.N., D.J.M. S.A.S., R.A.L., J.-J.S. and A.A.H. edited the manuscript, and all authors approved its content.

Corresponding authors

Correspondence to Christian Dina, Nabila Bouatia-Naji or Xavier Jeunemaitre.

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The authors declare no competing financial interests.

Additional information

A full list of members is provided in the Supplementary Note.

A full list of members is provided in the Supplementary Note.

Integrated supplementary information

Supplementary Figure 1 Study design with cohorts in discovery and follow-up and filtration strategy of SNPs.

Supplementary Figure 2 Igfbp5 expression in mouse developing heart.

Cardiac expression of Igfbp5 (red) was analyzed at embryonic (E13.5), fetal (E17.5) and adult time points. At the time points investigated, very little Igfbp5 protein was detected in the valves. Expression was observed in the myocardium of the left and right atria and the primary atrial septum (PAS) at E13.5 and E17.5 (arrows) as well as the coronary endothelium in the adult (arrow heads). AL, PL, IVS, LV = anterior and posterior mitral leaflets, interventricular septum, and left ventricle, respectively. Green = MF20 (sarcomeric myosin-myocytes), Blue = Hoescht (nuclei).

Supplementary Figure 3 In vivo assessment of mitral valve phenotypes in Tns1 total knockout mice using echocardiographs.

Tensin1+/+, wildtype; Tensin1-/-, Tns1 knockout mice. Images were obtained in a four-chamber view of the heart.

Supplementary Figure 4 In situ hybridizations of tns1 and lmcd1 mRNA distribution in zebrafish embryos.

Top panel shows tns1 expression pattern at 96 hours post fertilization. Expression is found throughout the myocardium, with highest levels in the outflow tract (right). Lower panel shows lmcd1 expression at 72 hours post fertilization (hpf). Expression is found in the entire myocardium, with enhanced expression in the ventricular chamber.

Supplementary Figure 5 In situ hybridizations for developmental markers of valvulogenesis in lmcd1 and tns1 knockdown embryos.

Top panel shows anti-notch1b probe labeling the developing valve in 72-hpf embryos. Lower panel shows anti-bmp4 probe labeling the valve and surrounding myocardium in control (CN) and lmcd1 knockdown embryos. Arrows in both panels point to the approximate location of the AV valve.

Supplementary Figure 6 Pitpnb expression in mouse developing heart.

Cardiac expression of Pitpnb (red) was analyzed at embryonic (E13.5), fetal (E17.5) and adult time points. Pitpnb was detected in valve endothelial and interstitial cells within the mitral leaflets at each of the time points investigated. Expression was also observed in the epicardium (arrow head) and coronary endothelium (arrow) at E17.5. AL, PL, IVS, LV = anterior and posterior mitral leaflets, interventricular septum, and left ventricle, respectively. Green = MF20 (sarcomeric myosin-myocytes), Blue = Hoescht (nuclei).

Supplementary Figure 7 Assessment of cardiac regurgitation in zebrafish morpholino knockdown for genes on Chr17p13.

(a) Genomic context of the association signal observed in the GWAS meta-analysis. (b) Morpholino-mediated knockdown efficacy. Efficacy for smg6 and sgsm2 in embryonic zebrafish was measured by RT-PCR. (c) Fold change in observed mitral regurgitation in 72-hpf zebrafish embryos after morpholino-mediated knockdown. All results are relative to clutchmate controls. n = number of biological replicates per morpholino. (d) Brightfield micrographs displaying gross morphology of 72-hpf embryos following smg6 or sgsm2 knockdown. Scale bar represents 1 mm. CN = control morpholino-injected embryos.

Supplementary Figure 8 Multidimensional scale–based principal-component analysis.

Cases and controls positions on first and second components axis are presented for the two discovery samples (GWAS 1 and GWAS 2). C1, first principal component. C2, second principal component. All individuals plotted are those included in the discovery GWAS who are all French with European ancestry origin. Cases and controls with non-European ancestry based on the principal component analyses were excluded before association tests.

Supplementary Figure 9 Representative gel images from analysis of morpholino efficacy.

rsID indicates the sentinel SNP at the analyzed locus. CN indicates samples amplified from control-injected embryos, whereas MO indicates amplicons from samples obtained following microinjection of gene-specific morpholino. All samples were obtained from 72-hpf embryos.

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Dina, C., Bouatia-Naji, N., Tucker, N. et al. Genetic association analyses highlight biological pathways underlying mitral valve prolapse. Nat Genet 47, 1206–1211 (2015). https://doi.org/10.1038/ng.3383

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