Abstract
Titin-truncating variants (TTNtv) commonly cause dilated cardiomyopathy (DCM). TTNtv are also encountered in ∼1% of the general population, where they may be silent, perhaps reflecting allelic factors. To better understand TTNtv, we integrated TTN allelic series, cardiac imaging and genomic data in humans and studied rat models with disparate TTNtv. In patients with DCM, TTNtv throughout titin were significantly associated with DCM. Ribosomal profiling in rat showed the translational footprint of premature stop codons in Ttn, TTNtv-position-independent nonsense-mediated degradation of the mutant allele and a signature of perturbed cardiac metabolism. Heart physiology in rats with TTNtv was unremarkable at baseline but became impaired during cardiac stress. In healthy humans, machine-learning-based analysis of high-resolution cardiac imaging showed TTNtv to be associated with eccentric cardiac remodeling. These data show that TTNtv have molecular and physiological effects on the heart across species, with a continuum of expressivity in health and disease.
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References
Hershberger, R.E., Hedges, D.J. & Morales, A. Dilated cardiomyopathy: the complexity of a diverse genetic architecture. Nat. Rev. Cardiol. 10, 531–547 (2013).
Herman, D.S. et al. Truncations of titin causing dilated cardiomyopathy. N. Engl. J. Med. 366, 619–628 (2012).
Roberts, A.M. et al. Integrated allelic, transcriptional, and phenomic dissection of the cardiac effects of titin truncations in health and disease. Sci. Transl. Med. 7, 270ra6 (2015).
Norton, N. et al. Exome sequencing and genome-wide linkage analysis in 17 families illustrate the complex contribution of TTN truncating variants to dilated cardiomyopathy. Circ Cardiovasc Genet 6, 144–153 (2013).
Chauveau, C., Rowell, J. & Ferreiro, A. A rising titan: TTN review and mutation update. Hum. Mutat. 35, 1046–1059 (2014).
Akinrinade, O., Koskenvuo, J.W. & Alastalo, T.-P. Prevalence of titin truncating variants in general population. PLoS One 10, e0145284 (2015).
Akinrinade, O., Alastalo, T.P. & Koskenvuo, J.W. Relevance of truncating titin mutations in dilated cardiomyopathy. Clinic. Genet. 90, 49–54 (2016).
Robinson, E.B. et al. Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population. Nat. Genet. 48, 552–555 (2016).
Hinson, J.T. et al. Titin mutations in iPS cells define sarcomere insufficiency as a cause of dilated cardiomyopathy. Science 349, 982–986 (2015).
Gramlich, M. et al. Stress-induced dilated cardiomyopathy in a knock-in mouse model mimicking human titin-based disease. J. Mol. Cell. Cardiol. 47, 352–358 (2009).
Lek, M. et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature 536, 285–291 (2016).
Zou, J. et al. An internal promoter underlies the difference in disease severity between N- and C-terminal truncation mutations of Titin in zebrafish. eLife 4, e09406 (2015).
Forrest, A.R. et al. A promoter-level mammalian expression atlas. Nature 507, 462–470 (2014).
Ingolia, N.T., Ghaemmaghami, S., Newman, J.R. & Weissman, J.S. Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science 324, 218–223 (2009).
Schafer, S. et al. Translational regulation shapes the molecular landscape of complex disease phenotypes. Nat. Commun. 6, 7200 (2015).
Kundaje, A. et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).
Schafer, S. et al. Alternative splicing signatures in RNA–seq data: percent spliced in (PSI). Curr. Protoc. Hum. Genet. 87, 11.16.1–11.16.14 (2015).
Guo, W. et al. RBM20, a gene for hereditary cardiomyopathy, regulates titin splicing. Nat. Med. 18, 766–773 (2012).
Maatz, H. et al. RNA-binding protein RBM20 represses splicing to orchestrate cardiac pre-mRNA processing. J. Clin. Invest. 124, 3419–3430 (2014).
Le Hir, H., Izaurralde, E., Maquat, L.E. & Moore, M.J. The spliceosome deposits multiple proteins 20–24 nucleotides upstream of mRNA exon–exon junctions. EMBO J. 19, 6860–6869 (2000).
Le Hir, H., Gatfield, D., Izaurralde, E. & Moore, M.J. The exon–exon junction complex provides a binding platform for factors involved in mRNA export and nonsense-mediated mRNA decay. EMBO J. 20, 4987–4997 (2001).
Luo, W., Friedman, M.S., Shedden, K., Hankenson, K.D. & Woolf, P.J. GAGE: generally applicable gene set enrichment for pathway analysis. BMC Bioinformatics 10, 161 (2009).
Kanehisa, M. & Goto, S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27–30 (2000).
Lai, L. et al. Energy metabolic reprogramming in the hypertrophied and early stage failing heart: a multisystems approach. Circ Heart Fail 7, 1022–1031 (2014).
Shibayama, J. et al. Metabolic remodeling in moderate synchronous versus dyssynchronous pacing-induced heart failure: integrated metabolomics and proteomics study. PLoS One 10, e0118974 (2015).
Doenst, T., Nguyen, T.D. & Abel, E.D. Cardiac metabolism in heart failure: implications beyond ATP production. Circ. Res. 113, 709–724 (2013).
Stanley, W.C., Recchia, F.A. & Lopaschuk, G.D. Myocardial substrate metabolism in the normal and failing heart. Physiol. Rev. 85, 1093–1129 (2005).
Schisler, J.C. et al. Cardiac energy dependence on glucose increases metabolites related to glutathione and activates metabolic genes controlled by mechanistic target of rapamycin. J. Am. Heart Assoc. 4, e001136 (2015).
Neubauer, S. The failing heart—an engine out of fuel. N. Engl. J. Med. 356, 1140–1151 (2007).
Yano, T. et al. Clinical impact of myocardial mTORC1 activation in nonischemic dilated cardiomyopathy. J. Mol. Cell. Cardiol. 91, 6–9 (2016).
Ramos, F.J. et al. Rapamycin reverses elevated mTORC1 signaling in lamin A/C-deficient mice, rescues cardiac and skeletal muscle function, and extends survival. Sci. Transl. Med. 4, 144ra103 (2012).
Neishabouri, S.H., Hutson, S.M. & Davoodi, J. Chronic activation of mTOR complex 1 by branched chain amino acids and organ hypertrophy. Amino Acids 47, 1167–1182 (2015).
Ait-Mou, Y. et al. Titin strain contributes to the Frank–Starling law of the heart by structural rearrangements of both thin- and thick-filament proteins. Proc. Natl. Acad. Sci. USA 113, 2306–2311 (2016).
Sen, S. et al. Glucose regulation of load-induced mTOR signaling and ER stress in mammalian heart. J. Am. Heart Assoc. 2, e004796 (2013).
Shende, P. et al. Cardiac raptor ablation impairs adaptive hypertrophy, alters metabolic gene expression, and causes heart failure in mice. Circulation 123, 1073–1082 (2011).
Zhang, D. et al. MTORC1 regulates cardiac function and myocyte survival through 4E-BP1 inhibition in mice. J. Clin. Invest. 120, 2805–2816 (2010).
Mestroni, L. et al. Guidelines for the study of familial dilated cardiomyopathies. Eur. Heart J. 20, 93–102 (1999).
Vasan, R.S., Larson, M.G., Benjamin, E.J., Evans, J.C. & Levy, D. Left ventricular dilatation and the risk of congestive heart failure in people without myocardial infarction. N. Engl. J. Med. 336, 1350–1355 (1997).
Levy, D. et al. Genome-wide association study of blood pressure and hypertension. Nat. Genet. 41, 677–687 (2009).
Newton-Cheh, C. et al. Genome-wide association study identifies eight loci associated with blood pressure. Nat. Genet. 41, 666–676 (2009).
de Marvao, A. et al. Population-based studies of myocardial hypertrophy: high resolution cardiovascular magnetic resonance atlases improve statistical power. J. Cardiovasc. Magn. Reson. 16, 16 (2014).
Bai, W. et al. A bi-ventricular cardiac atlas built from 1000+ high resolution MR images of healthy subjects and an analysis of shape and motion. Med. Image Anal. 26, 133–145 (2015).
Ware, J.S. et al. Shared genetic predisposition in peripartum and dilated cardiomyopathies. N. Engl. J. Med. 374, 233–241 (2016).
Watkins, H. Tackling the Achilles' heel of genetic testing. Sci. Transl. Med. 7, 270fs1 (2015).
Pugh, T.J. et al. The landscape of genetic variation in dilated cardiomyopathy as surveyed by clinical DNA sequencing. Genet. Med. 16, 601–608 (2014).
Walsh, R. et al. Reassessment of Mendelian gene pathogenicity using 7,855 cardiomyopathy cases and 60,706 reference samples. Genet. Med. http://dx.doi.org/10.1038/gim.2016.90 (2016).
Pua, C.J. et al. Development of a comprehensive sequencing assay for inherited cardiac condition genes. J. Cardiovasc. Transl. Res. 9, 3–11 (2016).
Langmead, B., Trapnell, C., Pop, M. & Salzberg, S.L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009).
Langmead, B. & Salzberg, S.L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
Cunningham, F. et al. Ensembl 2015. Nucleic Acids Res. 43, D662–D669 (2015).
Kim, D. et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 14, R36 (2013).
Goecks, J., Nekrutenko, A., Taylor, J. & Team, T. Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol. 11, R86 (2010).
Giardine, B. et al. Galaxy: a platform for interactive large-scale genome analysis. Genome Res. 15, 1451–1455 (2005).
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).
Shimoyama, M. et al. The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Res. 43, D743–D750 (2015).
Haberle, V., Forrest, A.R., Hayashizaki, Y., Carninci, P. & Lenhard, B. CAGEr: precise TSS data retrieval and high-resolution promoterome mining for integrative analyses. Nucleic Acids Res. 43, e51 (2015).
Gu, Z., Gu, L., Eils, R., Schlesner, M. & Brors, B. circlize implements and enhances circular visualization in R. Bioinformatics 30, 2811–2812 (2014).
Anders, S., Reyes, A. & Huber, W. Detecting differential usage of exons from RNA–seq data. Genome Res. 22, 2008–2017 (2012).
Price, A.N. et al. Cardiovascular magnetic resonance imaging in experimental models. Open Cardiovasc. Med. J. 4, 278–292 (2010).
Heiberg, E. et al. Design and validation of Segment—freely available software for cardiovascular image analysis. BMC Med. Imaging 10, 1 (2010).
Ross, A.J. et al. Serial MRI evaluation of cardiac structure and function in mice after reperfused myocardial infarction. Magn. Reson. Med. 47, 1158–1168 (2002).
Tortoledo, F.A., Quinones, M.A., Fernandez, G.C., Waggoner, A.D. & Winters, W.L. Jr. Quantification of left ventricular volumes by two-dimensional echocardiography: a simplified and accurate approach. Circulation 67, 579–584 (1983).
Sahn, D.J., DeMaria, A., Kisslo, J. & Weyman, A. Recommendations regarding quantitation in M-mode echocardiography: results of a survey of echocardiographic measurements. Circulation 58, 1072–1083 (1978).
Sutherland, F.J. & Hearse, D.J. The isolated blood and perfusion fluid perfused heart. Pharmacol. Res. 41, 613–627 (2000).
Muoio, D.M. et al. Muscle-specific deletion of carnitine acetyltransferase compromises glucose tolerance and metabolic flexibility. Cell Metab. 15, 764–777 (2012).
Soga, T. & Heiger, D.N. Amino acid analysis by capillary electrophoresis electrospray ionization mass spectrometry. Anal. Chem. 72, 1236–1241 (2000).
Soga, T. et al. Simultaneous determination of anionic intermediates for Bacillus subtilis metabolic pathways by capillary electrophoresis electrospray ionization mass spectrometry. Anal. Chem. 74, 2233–2239 (2002).
Sugimoto, M. et al. Differential metabolomics software for capillary electrophoresis–mass spectrometry data analysis. Metabolomics 6, 27–41 (2010).
de Marvao, A. et al. Precursors of hypertensive heart phenotype develop in healthy adults: a high-resolution 3D MRI study. JACC Cardiovasc. Imaging 8, 1260–1269 (2015).
Bellenger, N.G., Grothues, F., Smith, G.C. & Pennell, D.J. Quantification of right and left ventricular function by cardiovascular magnetic resonance. Herz 25, 392–399 (2000).
Grothues, F. et al. Comparison of interstudy reproducibility of cardiovascular magnetic resonance with two-dimensional echocardiography in normal subjects and in patients with heart failure or left ventricular hypertrophy. Am. J. Cardiol. 90, 29–34 (2002).
Smith, S.M. & Nichols, T.E. Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage 44, 83–98 (2009).
Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995).
Acknowledgements
We thank all the patients and healthy volunteers for taking part in this research and our team of research nurses across the hospital sites. We also thank M. von Frieling-Salewsky for technical support. The research was supported by the MRC Clinical Sciences Centre, UK, to J.S.W., S.A.C., A.d.M. and D.P.O'R., the NIHR Biomedical Research Unit in Cardiovascular Disease at Royal Brompton, the Harefield NHS Foundation Trust and Imperial College London to J.S.W. and S.A.C., the NIHR Imperial Biomedical Research Centre, British Heart Foundation, UK (SP/10/10/28431, PG/12/27/29489) to S.A.C., D.P.O'R. and C.B., the Wellcome Trust, UK (107469/Z/15/Z to J.S.W., 087183/Z/08/Z, 092854/Z/10/Z and WT095908), a Wellcome Trust Fellowship (100211/Z/12/Z and P43579_WMET to T.J.W.D.), Fondation Leducq to J.S.W., the Tanoto Foundation to S.A.C., CORDA, the National Institutes of Health (NHLBI 2R01HL080494 to J.G.S. and C.E.S.), the National Medical Research Council (NMRC) Singapore (CIRG13nov024 and STaR13nov002 to D.P.V.d.K.), the SingHealth Duke–NUS Institute of Precision Medicine, the Rosetrees Trust, the Health Innovation Challenge Fund (HICF-R6-373 to J.S.W.) funding from the Wellcome Trust and the Department of Health, UK, the Howard Hughes Medical Institute, the European Union EURATRANS award (HEALTH-F4-2010-241504 to N.H.), the Helmholtz Alliance ICEMED to N.H., European Union FP7 (CardioNeT-ITN-289600 to F.M.), Deutsche Forschungsgemeinschaft (SFB1002, TPA08 to W.A.L., Forschergruppe 1054 HU 1522/1-1 to N.H. and TP1 to V.R.-Z.), and an EMBO Long-Term Fellowship (ALTF 186-2015 to S.v.H.) and Marie Curie Actions (LTFCOFUND2013, GA-2013-609409 to S.v.H.). This publication includes independent research commissioned by the Health Innovation Challenge Fund (HICF), a parallel funding partnership between the UK Department of Health and the Wellcome Trust. The views expressed in this work are those of the authors and not necessarily those of the UK Department of Health or the Wellcome Trust.
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S.A.C. conceived, managed and arranged funding for the project. A.d.M., E.A., L.R.F., B.N., E.K., S.v.H., C.J.P., U.T., S.K.P., T.J.W.D., N.S.J.K., D.S., L.L.H.C., C.W.L.C., P.J.B., D.P.V.d.K., T.T., C.B., N.T., V.R.-Z., J.G.S., C.E.S. and W.A.L. performed experiments and contributed clinical data. S.S., A.d.M., O.J.L.R., M.K., R.W., F.M., F.K., D.R., V.S., A.F., J.-P.K., D.P.O'R., J.S.W., N.H. and S.A.C. performed data analysis and interpretation. S.S., B.N. and S.A.C. prepared the manuscript with input from co-authors.
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Supplementary Figure 1 Identification of an alternative, distal transcription start site in Titin.
From outside to inside, track 1 shows the location of the subunits of titin; the gene is on the antisense strand and so is transcribed counterclockwise in this view. Track 2 shows the gene structure of titin with the exons shown as orange rectangles and the introns shown as black lines. Track 3 shows the location of transcription start sites identified by the analysis of CAGE data taken from human heart samples in the FANTOM5 consortium as identified using CAGEr. Track 4 shows the location of H3K4me3 ChIP–seq narrow peaks (a mark of active promoters) from fetal heart samples in the Epigenomics Roadmap data set. Track 5 shows H3K4me3 ChIP–seq peaks from adult heart (left ventricle) taken from the Epigenomics Roadmap data set. Track 6 shows H3K9ac (also a mark of active promoters) taken from the fetal heart samples in the Epigenomics Roadmap data set. Together these data show that in the heart there are likely two transcription start sites, the canonical transcription start site at the beginning of the gene and another transcription start site found close to the start A-band, which appears to be most strongly used in fetal heart but is still present in adult human heart.
Supplementary Figure 2 Etiological fraction of TTNtv in 40 bins across the titin locus.
The constitutive (PSI > 90%) regions of titin are split into 40 bins ranging from the N terminus to the C terminus, and the etiological fraction of TTNtv for each individual region is plotted. The dashed line marks the position of the internal Cronos promoter. Purple, Z-disc; green, I-band; pink, A-band; blue, M-line.
Supplementary Figure 3 Truncating mutations introduced to F344 rats.
(a) The proximal truncating variant in titin is a large deletion located near the Z-disc at the N terminus of the meta transcript (TTNtvZ). It spans from exon 2 (b) to exon 6 (c). Exons 3–5 are not present in TTNtvZ rats and can thus be used to assess transcription and translation from the wild-type allele in heterozygous animals. (d) The deletion causes a frameshift that results in a premature stop codon located in exon 7. (e) The truncating variant in the A-band is located in the large exon 312 and an indel that also causes a frameshift and introduces a stop codon shortly after.
Supplementary Figure 4 RNA sequencing and ribosome profiling data for TTNtvA, TTNtvZ and wild-type rats.
(a,b) RNA–seq reads (a) and Ribo–seq reads (b) mapping to mitochondrial and ribosomal sequences were filtered out, and the remaining sequences were mapped to the genome. (c,d) Uniquely mapping RNA–seq (c) and Ribo–seq (d) reads were counted and used in later analyses to assess gene expression on the transcriptional and translational levels. (e) After adaptor trimming, Ribo–seq libraries displayed a size distribution typical for ribosome profiling experiments: ribosomes mostly protected RNA fragments of 28 and 29 bp in size.
Supplementary Figure 5 Absence of truncated Ttn protein in TTNtvA and TTNtvZ rat hearts.
Representative titin gels and immunoblots from 3-month-old wild-type, TTNtvA and TTNtvZ rat hearts. (a) SDS–PAGE was performed on 2.5% polyacrylamide/1% agarose gels, and total protein was visualized by Coomassie blue staining. Each sample was analyzed in duplicate at lower (left) and higher (right) protein concentration. Mhc was used as a loading control. The relative Ttn/Mhc ratio was determined (below). Data are shown as means ± s.e.m. (n = 4/group). (b) Immunoblotting analysis on 1.8% polyacrylamide/1% agarose gel transferred to PVDF and blotted with T12 antibody against titin and Novex3 (top). The corresponding PVDF blot was used as loading control (bottom).
Supplementary Figure 6 Transcriptional and translational gene expression differences between wild-type and TTNtv rats.
(a,b) Differential gene transcription (a) and translation (b) is compared between TTNtv and wild-type rats. Both TTNtvA and TTNtvZ show highly correlated fold changes in differentially expressed genes (DEseq2 FDR ≤ 0.05) when compared to control rats (Pearson correlation). Genes that were not differentially expressed in any comparison were not considered.
Supplementary Figure 7 Differences in cardiac metabolism between wild-type, TTNtvA and TTNtvZ rats.
(a–c) Metabolite profiles showing branched-chain amino acids, including valine (a), leucine (b) and isoleucine (c). (d) Sum of measured glycolytic intermediates (metabolites are detailed in Supplementary Table 3). (e) Glucose-6-phosphate (G6P) levels in cardiac tissue from wild-type (n = 6) and TTNtv (TTNtvA, n = 6; TTNtvZ, n = 6) rats. Data are shown as mean ± s.d. (Dunnett).
Supplementary Figure 8 TTNtv rat hearts have normal energy substrate abundance.
Metabolite levels of ATP, ADP, AMP and ratio of phosphocreatine (PCr) to creatine (Cr) in 4-month-old wild-type (n = 6) and TTNtv (TTNtvA, n = 6; TTNtvZ, n = 6) rat hearts.
Supplementary Figure 9 Relative expression of titin-associated proteins in wild-type and TTNtv rats.
(a,b) Relative difference (TTNtv/WT) in transcription (a) and translation (b) of titin-associated proteins showing a significant decrease in FHL1 and FHL2 expression in 8-week-old TTNtv (TTNtvA, n = 3; TTNtvZ, n = 3) as compared to wild-type (n = 4) rats. Data are shown as mean fold change ± s.e.m. *P < 0.05 (DEseq2 P value, not corrected for genome-wide testing).
Supplementary Figure 10 mTORC1 signaling is altered in TTNtv rat hearts.
(a) Immunoblot analysis showing increased phosphorylation of mTOR (Ser2448), S6 kinase (Thr389) and 4EBP1 (Thr37/46) in TTNtv as compared to wild-type hearts in extracts from rats immediately after sacrifice. (b) Semiquantitative densitometry of band intensities from several immunoblots across separate experiments and shown as means ± s.e.m. (Student’s t test, Welsh correction). (c) Immunoblot analysis of phosphorylated mTOR (Ser2448) and S6 kinase (Thr389) in myocardial tissue following sham treatment or volume overload in wild-type and TTNtv rat hearts on the Langendorff apparatus perfused for the same duration. (d) Semiquantitative densitometry representation of band intensities from the blot in c and other experiments showing mTOR and S6K response to acute stress relative to wild-type unstressed hearts of the respective genotypes. Data are shown as means ± s.d. (versus unstressed wild-type hearts, Student’s t test, Welsh correction).
Supplementary Figure 11 Young TTNtv rats display concentric remodeling.
Echocardiographic measurements of 4- to 8-month-old male wild-type (n = 4) and TTNtv (TTNtvA, n = 4; TTNtvZ, n = 4) rats. PLVWed (mm), posterior left ventricular wall thickness end diastole; PLVWes (mm), posterior left ventricular wall thickness end diastole; LVIDed (mm), left ventricular internal diameter end diastole; LVIDes (mm), left ventricular internal diameter end systole; EDV (μl), end-diastolic volume; ESV (μl), end-systolic volume; SV (μl), stroke volume. EF (%), ejection fraction. P values indicate statistical analysis by two-way analysis of variance (ANOVA).
Supplementary Figure 12 CMR in TTNtvA and TTNtvZ rats.
(a–c) SV (stroke volume) (a), LVEF (left ventricular ejection fraction) (b) and FWT (fractional wall thickening) (c) measured with CMR in 13- to 16-month-old male wild-type (n = 5) and TTNtv (TTNtvA, n = 8; TTNtvZ, n = 6) rats. Data are shown as means ± s.d. (Dunett).
Supplementary Figure 13 Distribution of TTNtv detected in the general population for MRI.
The top track shows the distribution of TTNtv in healthy volunteers (HVOL) who were phenotyped using cardiac magnetic resonance imaging. The track below depicts the distribution of TTNtv from ExAC data. Only truncations located in exons with PSI >15% are shown.
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Supplementary Text and Figures
Supplementary Figures 1–13 and Supplementary Tables 1–5. (PDF 3548 kb)
3D cardiac imaging shows the effect of TTNtv on human left ventricular geometry.
Mass univariate regression models show the relationship between TTNtv genotype (cardiac exons with PSI > 15%) and increasing endocardial volume (positive coefficients) in end systole (left) and end diastole (right). Standardized β coefficients are plotted on the endocardial surface with outlines of left (red) and right (blue) ventricles. The area enclosed by the yellow contour has a corrected P <0.05 (multiple linear regression). (MP4 6250 kb)
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Schafer, S., de Marvao, A., Adami, E. et al. Titin-truncating variants affect heart function in disease cohorts and the general population. Nat Genet 49, 46–53 (2017). https://doi.org/10.1038/ng.3719
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DOI: https://doi.org/10.1038/ng.3719
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