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International Journal of Legal Medicine

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01-11-2019 | Sudden Cardiac Death | Original Article

Whole genome and transcriptome sequencing of post-mortem cardiac tissues from sudden cardiac death victims identifies a gene regulatory variant in NEXN

Authors: Jeppe D. Andersen, Stine B. Jacobsen, Linea C. Trudsø, Marie-Louise Kampmann, Jytte Banner, Niels Morling

Published in: International Journal of Legal Medicine | Issue 6/2019

Abstract

Background

Sudden cardiac death (SCD) is a major public health problem and constitutes a diagnostic and preventive challenge in forensic pathology, especially for cases with structural normal hearts at autopsy, so-called sudden arrhythmic death syndrome (SADS). The identification of new genetic risk factors that predispose to SADS is important, because they may contribute to establish the diagnosis and increase the understanding of disease pathways underlying SADS. Pathogenic mutations in the protein coding regions of cardiac genes were found in relation to SADS. However, much remains unknown about variants in non-coding regions of the genome.

Methods and results

In this study, we explored the potential of whole genome sequencing (WGS) and whole transcriptome sequencing (WTS) to find DNA variants in SCD victims with structural normal hearts.

With focus on the non-coding regulatory regions, we re-examined a cohort of 13 SADS and sudden unexplained death in infancy (SUDI) victims without disease causing DNA variants in recognized cardiac genes. The genetic re-examination of DNA was carried out using frozen tissue samples and WTS was carried out using five distinct formalin fixed and paraffin embedded (FFPE) cardiac tissue samples from each individual, including anterior and posterior walls of the left ventricle, ventricular papillary muscle, septum, and the right ventricle. We identified 23 candidate variants in regulatory sequences of cardiac genes, including a variant in the promotor region of NEXN, c.-194A>G, that was found to be statistically significantly (p < 0.05) associated with decreased expression of NEXN and cardiac hypertrophy.

Conclusion

With the use of post-mortem FFPE tissues, we highlight the potential of using WTS investigations and compare gene expression levels with DNA variation in regulatory non-coding regions of the genome for a better understanding of the genetics of cardiac diseases leading to SCD.

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Campuzano O, Allegue C, Partemi S, Iglesias A, Oliva A, Brugada R (2014) Negative autopsy and sudden cardiac death. Int J Legal Med 128:599–606. https://doi.org/10.1007/s00414-014-0966-4 CrossRefPubMed

Bjune T, Risgaard B, Kruckow L, Glinge C, Ingemann-Hansen O, Leth PM, Linnet K, Banner J, Winkel BG, Tfelt-Hansen J (2018) Post-mortem toxicology in young sudden cardiac death victims: a nationwide cohort study. Europace 20:614–621. https://doi.org/10.1093/europace/euw435 CrossRefPubMed

Semsarian C, Ingles J, Wilde AA (2015) Sudden cardiac death in the young: the molecular autopsy and a practical approach to surviving relatives. Eur Heart J 36:1290–1296. https://doi.org/10.1093/eurheartj/ehv063 CrossRefPubMed

Bagnall RD, Weintraub RG, Ingles J, Duflou J, Yeates L, Lam L, Davis AM, Thompson T, Connell V, Wallace J, Naylor C, Crawford J, Love DR, Hallam L, White J, Lawrence C, Lynch M, Morgan N, James P, du Sart D, Puranik R, Langlois N, Vohra J, Winship I, Atherton J, McGaughran J, Skinner JR, Semsarian C (2016) A prospective study of sudden cardiac death among children and young adults. N Engl J Med 374:2441–2452. https://doi.org/10.1056/NEJMoa1510687 CrossRefPubMed

Basso C, Aguilera B, Banner J et al (2017) Guidelines for autopsy investigation of sudden cardiac death: 2017 update from the Association for European Cardiovascular Pathology. Virchows Arch 471:691–705. https://doi.org/10.1007/s00428-017-2221-0 CrossRefPubMedPubMedCentral

Lahrouchi N, Raju H, Lodder EM, Papatheodorou E, Ware JS, Papadakis M, Tadros R, Cole D, Skinner JR, Crawford J, Love DR, Pua CJ, Soh BY, Bhalshankar JD, Govind R, Tfelt-Hansen J, Winkel BG, van der Werf C, Wijeyeratne YD, Mellor G, Till J, Cohen MC, Tome-Esteban M, Sharma S, Wilde AAM, Cook SA, Bezzina CR, Sheppard MN, Behr ER (2017) Utility of post-mortem genetic testing in cases of sudden arrhythmic death syndrome. J Am Coll Cardiol 69:2134–2145. https://doi.org/10.1016/j.jacc.2017.02.046 CrossRefPubMedPubMedCentral

Bezzina CR, Lahrouchi N, Priori SG (2015) Genetics of sudden cardiac death. Circ Res 116:1919–1936. https://doi.org/10.1161/CIRCRESAHA.116.304030 CrossRefPubMed

Tester DJ, Wong LCH, Chanana P, Jaye A, Evans JM, FitzPatrick DR, Evans MJ, Fleming P, Jeffrey I, Cohen MC, Tfelt-Hansen J, Simpson MA, Behr ER, Ackerman MJ (2018) Cardiac genetic predisposition in sudden infant death syndrome. J Am Coll Cardiol 71:1217–1227. https://doi.org/10.1016/j.jacc.2018.01.030 CrossRefPubMed

Christiansen SL, Hertz CL, Ferrero-Miliani L, Dahl M, Weeke PE, LuCamp, Ottesen GL, Frank-Hansen R, Bundgaard H, Morling N (2016) Genetic investigation of 100 heart genes in sudden unexplained death victims in a forensic setting. Eur J Hum Genet 24:1797–1802. https://doi.org/10.1038/ejhg.2016.118 CrossRefPubMedPubMedCentral

10.

Neubauer J, Lecca MR, Russo G, Bartsch C, Medeiros-Domingo A, Berger W, Haas C (2017) Post-mortem whole-exome analysis in a large sudden infant death syndrome cohort with a focus on cardiovascular and metabolic genetic diseases. Eur J Hum Genet 25:404–409. https://doi.org/10.1038/ejhg.2016.199 CrossRefPubMedPubMedCentral

11.

Neubauer J, Lecca MR, Russo G, Bartsch C, Medeiros-Domingo A, Berger W, Haas C (2018) Exome analysis in 34 sudden unexplained death (SUD) victims mainly identified variants in channelopathy-associated genes. Int J Legal Med 132:1057–1065. https://doi.org/10.1007/s00414-018-1775-y CrossRefPubMed

12.

van den Boogaard M, Wong LY, Tessadori F et al (2012) Genetic variation in T-box binding element functionally affects SCN5A/SCN10A enhancer. J Clin Invest 122:2519–2530. https://doi.org/10.1172/JCI62613 CrossRefPubMedPubMedCentral

13.

Yagihara N, Watanabe H, Barnett P, Duboscq-Bidot L, Thomas AC, Yang P, Ohno S, Hasegawa K, Kuwano R, Chatel S, Redon R, Schott JJ, Probst V, Koopmann TT, Bezzina CR, Wilde AAM, Nakano Y, Aiba T, Miyamoto Y, Kamakura S, Darbar D, Donahue BS, Shigemizu D, Tanaka T, Tsunoda T, Suda M, Sato A, Minamino T, Endo N, Shimizu W, Horie M, Roden DM, Makita N (2016) Variants in the SCN5A promoter associated with various arrhythmia phenotypes. J Am Heart Assoc 5. https://doi.org/10.1161/JAHA.116.003644

14.

Wang J, Wang F, Zhu J, Song M, An J, Li W (2018) Transcriptome profiling reveals PHLDA1 as a novel molecular marker for ischemic cardiomyopathy. J Mol Neurosci 65:102–109. https://doi.org/10.1007/s12031-018-1066-6 CrossRefPubMedPubMedCentral

15.

Hedegaard J, Thorsen K, Lund MK, Hein AMK, Hamilton-Dutoit SJ, Vang S, Nordentoft I, Birkenkamp-Demtröder K, Kruhøffer M, Hager H, Knudsen B, Andersen CL, Sørensen KD, Pedersen JS, Ørntoft TF, Dyrskjøt L (2014) Next-generation sequencing of RNA and DNA isolated from paired fresh-frozen and formalin-fixed paraffin-embedded samples of human cancer and normal tissue. PLoS One 9:e98187. https://doi.org/10.1371/journal.pone.0098187 CrossRefPubMedPubMedCentral

16.

Esteve-Codina A, Arpi O, Martinez-Garcia M et al (2017) A comparison of RNA-Seq results from paired formalin-fixed paraffin-embedded and fresh-frozen glioblastoma tissue samples. PLoS One 12:e0170632. https://doi.org/10.1371/journal.pone.0170632 CrossRefPubMedPubMedCentral

17.

Ferreira PG, Munoz-Aguirre M, Reverter F et al (2018) The effects of death and post-mortem cold ischemia on human tissue transcriptomes. Nat Commun 9:490. https://doi.org/10.1038/s41467-017-02772-x CrossRefPubMedPubMedCentral

18.

Hertz CL, Christiansen SL, Larsen MK, Dahl M, Ferrero-Miliani L, Weeke PE, Pedersen O, Hansen T, Grarup N, Ottesen GL, Frank-Hansen R, Banner J, Morling N (2016) Genetic investigations of sudden unexpected deaths in infancy using next-generation sequencing of 100 genes associated with cardiac diseases. Eur J Hum Genet 24:817–822. https://doi.org/10.1038/ejhg.2015.198 CrossRefPubMed

19.

Lindgreen S (2012) AdapterRemoval: easy cleaning of next-generation sequencing reads. BMC Res Notes 5:337. https://doi.org/10.1186/1756-0500-5-337 CrossRefPubMedPubMedCentral

20.

Li H (2013) Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv preprint arXiv 1303.3997

21.

Van der Auwera GA, Carneiro MO, Hartl C et al (2013) From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline. Curr Protoc Bioinformatics 43:11.10.1-33. https://doi.org/10.1002/0471250953.bi1110s43 CrossRef

22.

Richards S, Aziz N, Bale S et al (2015) Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med 17:405–424. https://doi.org/10.1038/gim.2015.30 CrossRefPubMedPubMedCentral

23.

Ienasescu H, Li K, Andersson R, Vitezic M, Rennie S, Chen Y, Vitting-Seerup K, Lagoni E, Boyd M, Bornholdt J, de Hoon MJL, Kawaji H, Lassmann T, The FANTOM Consortium, Hayashizaki Y, Forrest ARR, Carninci P, Sandelin A (2016) On-the-fly selection of cell-specific enhancers, genes, miRNAs and proteins across the human body using SlideBase. Database (Oxford) 2016. https://doi.org/10.1093/database/baw144

24.

Zerbino DR, Achuthan P, Akanni W, Amode MR, Barrell D, Bhai J, Billis K, Cummins C, Gall A, Girón CG, Gil L, Gordon L, Haggerty L, Haskell E, Hourlier T, Izuogu OG, Janacek SH, Juettemann T, To JK, Laird MR, Lavidas I, Liu Z, Loveland JE, Maurel T, McLaren W, Moore B, Mudge J, Murphy DN, Newman V, Nuhn M, Ogeh D, Ong CK, Parker A, Patricio M, Riat HS, Schuilenburg H, Sheppard D, Sparrow H, Taylor K, Thormann A, Vullo A, Walts B, Zadissa A, Frankish A, Hunt SE, Kostadima M, Langridge N, Martin FJ, Muffato M, Perry E, Ruffier M, Staines DM, Trevanion SJ, Aken BL, Cunningham F, Yates A, Flicek P (2018) Ensembl 2018. Nucleic Acids Res 46:D754–DD61. https://doi.org/10.1093/nar/gkx1098 CrossRefPubMed

25.

Fantom C, the RP, Clst et al (2014) A promoter-level mammalian expression atlas. Nature 507:462–470. https://doi.org/10.1038/nature13182 CrossRef

26.

Encode Project C (2012) An integrated encyclopedia of DNA elements in the human genome. Nature 489:57–74. https://doi.org/10.1038/nature11247 CrossRef

27.

Roadmap Epigenomics C, Kundaje A, Meuleman W et al (2015) Integrative analysis of 111 reference human epigenomes. Nature 518:317–330. https://doi.org/10.1038/nature14248 CrossRef

28.

Visel A, Minovitsky S, Dubchak I, Pennacchio LA (2007) VISTA Enhancer Browser--a database of tissue-specific human enhancers. Nucleic Acids Res 35:D88–D92. https://doi.org/10.1093/nar/gkl822 CrossRefPubMed

29.

Messeguer X, Escudero R, Farre D, Nunez O, Martinez J, Alba MM (2002) PROMO: detection of known transcription regulatory elements using species-tailored searches. Bioinformatics 18:333–334CrossRefPubMed

30.

Farre D, Roset R, Huerta M et al (2003) Identification of patterns in biological sequences at the ALGGEN server: PROMO and MALGEN. Nucleic Acids Res 31:3651–3653CrossRefPubMedPubMedCentral

31.

Wingender E, Dietze P, Karas H, Knuppel R (1996) TRANSFAC: a database on transcription factors and their DNA binding sites. Nucleic Acids Res 24:238–241CrossRefPubMedPubMedCentral

32.

Visel A, Blow MJ, Li Z, Zhang T, Akiyama JA, Holt A, Plajzer-Frick I, Shoukry M, Wright C, Chen F, Afzal V, Ren B, Rubin EM, Pennacchio LA (2009) ChIP-seq accurately predicts tissue-specific activity of enhancers. Nature 457:854–858. https://doi.org/10.1038/nature07730 CrossRefPubMedPubMedCentral

33.

Yeo G, Burge CB (2004) Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals. J Comput Biol 11:377–394. https://doi.org/10.1089/1066527041410418 CrossRefPubMed

34.

Bhattacharya A, Ziebarth JD, Cui Y (2014) PolymiRTS Database 3.0: linking polymorphisms in microRNAs and their target sites with human diseases and biological pathways. Nucleic Acids Res 42:D86–D91. https://doi.org/10.1093/nar/gkt1028 CrossRefPubMed

35.

Layer RM, Chiang C, Quinlan AR, Hall IM (2014) LUMPY: a probabilistic framework for structural variant discovery. Genome Biol 15:R84. https://doi.org/10.1186/gb-2014-15-6-r84 CrossRefPubMedPubMedCentral

36.

Chiang C, Layer RM, Faust GG, Lindberg MR, Rose DB, Garrison EP, Marth GT, Quinlan AR, Hall IM (2015) SpeedSeq: ultra-fast personal genome analysis and interpretation. Nat Methods 12:966–968. https://doi.org/10.1038/nmeth.3505 CrossRefPubMedPubMedCentral

37.

Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29:15–21. https://doi.org/10.1093/bioinformatics/bts635 CrossRefPubMed

38.

Harrow J, Frankish A, Gonzalez JM, Tapanari E, Diekhans M, Kokocinski F, Aken BL, Barrell D, Zadissa A, Searle S, Barnes I, Bignell A, Boychenko V, Hunt T, Kay M, Mukherjee G, Rajan J, Despacio-Reyes G, Saunders G, Steward C, Harte R, Lin M, Howald C, Tanzer A, Derrien T, Chrast J, Walters N, Balasubramanian S, Pei B, Tress M, Rodriguez JM, Ezkurdia I, van Baren J, Brent M, Haussler D, Kellis M, Valencia A, Reymond A, Gerstein M, Guigo R, Hubbard TJ (2012) GENCODE: the reference human genome annotation for The ENCODE Project. Genome Res 22:1760–1774. https://doi.org/10.1101/gr.135350.111 CrossRefPubMedPubMedCentral

39.

Li B, Ruotti V, Stewart RM, Thomson JA, Dewey CN (2010) RNA-Seq gene expression estimation with read mapping uncertainty. Bioinformatics 26:493–500. https://doi.org/10.1093/bioinformatics/btp692 CrossRefPubMed

40.

Hertz CL, Christiansen SL, Ferrero-Miliani L et al (2016) Next-generation sequencing of 100 candidate genes in young victims of suspected sudden cardiac death with structural abnormalities of the heart. Int J Legal Med 130:91–102. https://doi.org/10.1007/s00414-015-1261-8 CrossRefPubMed

41.

Gollob MH, Jones DL, Krahn AD, Danis L, Gong XQ, Shao Q, Liu X, Veinot JP, Tang ASL, Stewart AFR, Tesson F, Klein GJ, Yee R, Skanes AC, Guiraudon GM, Ebihara L, Bai D (2006) Somatic mutations in the connexin 40 gene (GJA5) in atrial fibrillation. N Engl J Med 354:2677–2688. https://doi.org/10.1056/NEJMoa052800 CrossRefPubMed

42.

Olesen MS, Andreasen L, Jabbari J, Refsgaard L, Haunsø S, Olesen SP, Nielsen JB, Schmitt N, Svendsen JH (2014) Very early-onset lone atrial fibrillation patients have a high prevalence of rare variants in genes previously associated with atrial fibrillation. Heart Rhythm 11:246–251. https://doi.org/10.1016/j.hrthm.2013.10.034 CrossRefPubMed

43.

Lubkemeier I, Andrie R, Lickfett L et al (2013) The Connexin40A96S mutation from a patient with atrial fibrillation causes decreased atrial conduction velocities and sustained episodes of induced atrial fibrillation in mice. J Mol Cell Cardiol 65:19–32. https://doi.org/10.1016/j.yjmcc.2013.09.008 CrossRefPubMed

44.

Kanthan A, Fahmy P, Rao R, Pouliopoulos J, Alexander IE, Thomas SP, Kizana E (2018) Human Connexin40 mutations slow conduction and increase propensity for atrial fibrillation. Heart Lung Circ 27:114–121. https://doi.org/10.1016/j.hlc.2017.02.010 CrossRefPubMed

45.

Landrum MJ, Lee JM, Riley GR, Jang W, Rubinstein WS, Church DM, Maglott DR (2014) ClinVar: public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res 42:D980–D985. https://doi.org/10.1093/nar/gkt1113 CrossRefPubMed

46.

Hassel D, Dahme T, Erdmann J, Meder B, Huge A, Stoll M, Just S, Hess A, Ehlermann P, Weichenhan D, Grimmler M, Liptau H, Hetzer R, Regitz-Zagrosek V, Fischer C, Nürnberg P, Schunkert H, Katus HA, Rottbauer W (2009) Nexilin mutations destabilize cardiac Z-disks and lead to dilated cardiomyopathy. Nat Med 15:1281–1288. https://doi.org/10.1038/nm.2037 CrossRefPubMed

47.

Wang H, Li Z, Wang J, Sun K, Cui Q, Song L, Zou Y, Wang X, Liu X, Hui R, Fan Y (2010) Mutations in NEXN, a Z-disc gene, are associated with hypertrophic cardiomyopathy. Am J Hum Genet 87:687–693. https://doi.org/10.1016/j.ajhg.2010.10.002 CrossRefPubMedPubMedCentral

48.

Jansen JA, van Veen TA, de Bakker JM, van Rijen HV (2010) Cardiac connexins and impulse propagation. J Mol Cell Cardiol 48:76–82. https://doi.org/10.1016/j.yjmcc.2009.08.018 CrossRefPubMed

49.

Hew KW, Keller KA (2003) Postnatal anatomical and functional development of the heart: a species comparison. Birth Defects Res B Dev Reprod Toxicol 68:309–320. https://doi.org/10.1002/bdrb.10034 CrossRefPubMed

Title: Whole genome and transcriptome sequencing of post-mortem cardiac tissues from sudden cardiac death victims identifies a gene regulatory variant in NEXN
Authors: Jeppe D. Andersen
Stine B. Jacobsen
Linea C. Trudsø
Marie-Louise Kampmann
Jytte Banner
Niels Morling
Publication date: 01-11-2019
Publisher: Springer Berlin Heidelberg
Keywords: Sudden Cardiac Death
Autopsy
Sudden Infant Death Syndrome
Published in: International Journal of Legal Medicine / Issue 6/2019
Print ISSN: 0937-9827
Electronic ISSN: 1437-1596
DOI: https://doi.org/10.1007/s00414-019-02127-9

At a glance: The STEP trials

Springer Medicine

Whole genome and transcriptome sequencing of post-mortem cardiac tissues from sudden cardiac death victims identifies a gene regulatory variant in NEXN

Abstract

Background

Methods and results

Conclusion

At a glance: The STEP trials

Springer Medicine

Abstract

Background

Methods and results

Conclusion

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