Clinical Approach to Sudden Cardiac Death Syndromes 9781848829268, 1848829264

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Clinical Approach to Sudden Cardiac Death Syndromes

Ramon Brugada (Ed.)

Clinical Approach to Sudden Cardiac Death Syndromes

Ramon Brugada Dean, School of Medicine Director, Cardiovascular Genetics Center UdG-IDIBGi Universitat de Girona Pic de Peguera 11 17003 Girona, Catalonia, Spain

Pedro Brugada Scientific Director, Cardiovascular Division Head, Heart Rhythm Management Centre Free University of Brussels (UZ Brussel) VUB Laarbeeklaan 101 1090 Brussels. Belgium

Josep Brugada Medical Director Hospital Clínic Universitat de Barcelona Villarroel 170 08036 Barcelona, Catalonia, Spain

ISBN: 978-1-84882-926-8     e-ISBN: 978-1-84882-927-5 DOI: 10.1007/978-1-84882-927-5 Springer London Dordrecht Heidelberg New York Library of Congress Control Number: 2009938027 © Springer-Verlag London Limited 2010 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is ­concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant ­protective laws and regulations and therefore free for general use. Product liability: The publishers cannot guarantee the accuracy of any information about dosage and application contained in this book. In every individual case the user must check such information by consulting the relevant literature. Cover design: eStudio Calamar, Figueres/Berlin Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)

Preface

Much has changed in the field of arrhythmias and sudden cardiac death in these last decades. Successful innovative catheter therapies and protective devices have been determinant in enhancing treatment and prevention strategies of individuals at risk. However, despite the advances, sudden cardiac death still remains a major contributor to mortality in our society. While most deaths occur in adult cases and are associated with ischemic heart disease, occasionally the youngest and the fittest, even those who have become our role models for their athletic abilities, may also die suddenly, usually from noncoronary cardiac causes. It has not been until the advent of molecular biology and genetics in cardiology when we have been able to further deepen in our knowledge of these dreadful events in the young. In the last 20 years, genetic research in subjects and families with sudden cardiac death syndromes has brought a vast amount of information on genetic defects responsible for arrhythmogenesis, improving our understanding on how the abnormally codified proteins are involved in the pathogenesis of a disease and how this protein disrupts the myocyte electrical activity, generates a chaotic rhythm, and predisposes to ventricular fibrillation. Inherited sudden cardiac death syndromes are indeed rare diseases, much rarer than hypertension or coronary artery disease. However, it is highly likely that as physicians we will at some point encounter a patient with one of these genetic diseases, and we have to be aware of at least two clinical implications. First, the field of cardiac genetics has brought a new tool, genetic screening, which is presently standing out as a key diagnostic test, complementing the highly sophisticated, but often inaccurate, clinical instruments. With the use of genetic information in our practice, we have moved the information from the bench to the bedside, from research to clinical care, translational medicine at its best. Second, cardiac genetics is also bringing a fundamental change for our clinical practice, which is not to be taken lightly. With the care for patients with inherited arrhythmias, we have gone from facing the single patient to facing the family, from one individual with signs and symptoms of a disease to several family members with a genetic defect. Familial global care is a tremendous and complex new task that includes genetic screening, treatment decisions especially difficult in children, childbearing choices, disease expression, and genetic penetrance. The family, with all its complexity, cannot be assumed by the lone physician but only by a multidisciplinary team of geneticists, cardiologists, psychologists, and genetic counselors. Most cardiologists already appreciate that there is more to the sudden death of a young individual than just “natural” causes. Genetic information is changing the way we approach medical care in this genomic era. With this book, our goal is to provide v

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Preface

the latest information on sudden cardiac death and genetic syndromes, with the aim to guide the physician in this complex field.

Ramon, Josep and Pedro Brugada

Acknowledgments

A la nostra germana A la nostra família A totes les famílies

To our sister, to our family, to all families.

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Contents

Part I  Sudden Unexplained Death . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1

  1 Sudden Unexplained Death in the Community . . . . . . . . . . . . . . . . . . . Sumeet S. Chugh, Carmen Teodorescu, Audrey Evanado, and Kyndaron Reinier

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  2 Sudden Infant Death Syndrome: Gene–Environment Interactions . . . . Carl E. Hunt, and Fern R. Hauck

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Part II  Arrhythmias and sudden cardiac death.     The initial investigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .   3 Unexplained Syncope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Carlos A. Morillo and Víctor Expósito-García   4 Arrhythmias and Sudden Cardiac Death in Adult Congenital Heart Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Paul Khairy

23 25

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  5 Endurance Sport Practice and Arrhythmias . . . . . . . . . . . . . . . . . . . . . Eduard Guasch and Lluís Mont

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  6 Electrocardiograms Not to Miss . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Andres Perez-Riera

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  7 Sudden Cardiac Death in Forensic Pathology . . . . . . . . . . . . . . . . . . . . Antonio Oliva and Vincenzo L. Pascali

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Part III  Cardiac genetic syndromes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111   8 Genetic Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Marie-Pierre Dubé and John Rioux   9 The Long QT Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Ramon Brugada and Oscar Campuzano 10 Brugada Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Begoña Benito, Ramon Brugada, Josep Brugada, and Pedro Brugada ix

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11 Short QT Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149 Christian Wolpert, Christian Veltmann, Rainer Schimpf, and Martin Borggrefe 12 Catecholaminergic Polymorphic Ventricular Tachycardia . . . . . . . . . . 157 M. Juhani Junttila, Olli Anttonen, and Heikki V. Huikuri 13 Arrhythmogenic Right Ventricular Cardiomyopathy/Dysplasia . . . . . 163 Michela Bevilacqua, Federico Migliore, Cristina Basso, Gaetano Thiene, and Domenico Corrado, 14 Atrial Fibrillation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 Oscar Campuzano and Ramon Brugada 15 Dilated Cardiomyopathy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 Michelle S. C. Khoo, Luisa Mestroni, and Matthew R. G. Taylor 16 Hypertrophic Cardiomyopathy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 A. J. Marian 17 Genetic Lipoprotein Disorders and Cardiovascular Disease . . . . . . . . 203 Khalid Alwaili, Khalid Alrasadi, Zari Dastani, Iulia Iatan, Zuhier Awan, and Jacques Genest 18 A Systematic Approach to Marfan Syndrome and Hereditary Forms of Aortic Dilatation and Dissection . . . . . . . . . . . . . . . . . . . . . . . 223 Peter N. Robinson and Yskert von Kodolitsch 19 Inherited Metabolic Diseases: Emphasis on Myocardial Disease and Arrhythmogenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 Eduardo Back Sternick 20 Clinical Genetics in Congenital Heart Disease . . . . . . . . . . . . . . . . . . . . 259 Georgia Sarquella Brugada and Gregor Andelfinger Part IV  Polygenic cardiovascular genetics . . . . . . . . . . . . . . . . . . . . . . . . . 271 21 Pharmacogenomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273 Simon de Denus, Michael Phillips, and Jean-Claude Tardif 22 Polygenic Studies in the Risk of Arrhythmias . . . . . . . . . . . . . . . . . . . . 289 Moritz F. Sinner and Stefan Kääb 23 The Genetic Challenge of Coronary Artery Disease . . . . . . . . . . . . . . . 297 Robert Roberts, George Wells, and Li Chen

Contents

Contents

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Part V  Ethical, legal and Social implications . . . . . . . . . . . . . . . . . . . . . . . 309 24 Psychological Implications of Genetic Investigations . . . . . . . . . . . . . . 311 April Manuel, Fern Brunger, and Kathy Hodgkinson 25 Participation in Recreational Sports for Young Patients with Genetic Cardiovascular Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . 317 Barry J. Maron 26 Genetic Counseling in Cardiovascular Conditions . . . . . . . . . . . . . . . . 327 Laura Robb Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337

Contributors

Khalid Alrasadi  Medical Biochemistry, McGill University, Royal Victoria Hospital, Montreal, QC, Canada H3A 1A1 Khalid Alwaili  Medical Biochemistry, McGill University, Royal Victoria Hospital, Montreal, QC, Canada H3A 1A1 G. Andelfinger  Department of Pediatrics, CHU Sainte Justine, University of Montreal, Montreal, QC, Canada H3A 1A1 Olli Anttonen  Department of Cardiology, Päijät Häme Central Hospital, Lahli, Finland Zuhier Awan  Medical Biochemistry, McGill University, Royal Victoria Hospital, Montreal, QC, Canada H3A 1A1 Eduardo Back Sternick  Arrhythmia and Electrophysiology Unit, Biocor Instituto, Nova Lima, Minas Gerais, Brazil [email protected] Cristina Basso  Department of Cardiac, Division of Cardiology, Thoracic and Vascular Sciences and Cardiovascular Pathology, University of Padua, Padova, Italy Begoña Benito  Research Center, Montreal Heart Institute, 5000 Rue Belanger Montreal, H1T 1C8 Canada Michela Bevilacqua  Department of Cardiac, Division of Cardiology, Thoracic and Vascular Sciences and Cardiovascular Pathology, University of Padua, Padova, Italy Martin Borggrefe  Department of Medicine – Cardiology, University Hospital Mannheim, Mannheim 68167, Germany Josep Brugada  Department of Cardiology, The Thorax Institute, Hospital Clinic of Barcelona, Barcelona, Spain Pedro Brugada  Heart Rhythm Management Centre, Cardiovascular Institute, UZ Brussel, VUB Brussels, Belgium Ramon Brugada  Cardiovascular Genetics Center UdG-IDIBGi, School of Medicine, University of Girona, Girona, Spain [email protected] Fern Brunger  Memorial University of Newfoundland, St. John’s, Newfoundland, Canada A1B 3V6

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Oscar Campuzano  Cardiovascular Genetics Center, UdG-IDIBGI, Girona, Spain [email protected] Li Chen  Cardiovascular Research Methods Centre, University of Ottawa Heart Institute, Ottawa, ON, Canada K1Y 4W7 Sumeet S. Chugh  Associate Director, the Heart Institute, Cedars-Sinai Medical Center, Los Angeles CA, USA 90048. [email protected] Francis Collins  National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20894, USA Domenico Corrado  Professor of Cardiovascular Medicine, Department of Cardiac, Thoracic and Vascular Sciences, University of Padua Medical School, Via Giustiniani, 2 35121Padua, Italy [email protected] Zari Dastani  Human Genetics, McGill University, Montreal, QC, Canada H3A 1A1 Simon de Denus  Université de Montréal, Montreal Heart Institute, Montreal, QC, Canada H3A 1A1 [email protected] Marie-Pierre Dubé  Department of medicine, Montreal Heart Institute Research Center, and Université de Montréal, 5000, Bélanger, Montreal, QC, Canada H1T1C8 [email protected] Víctor Expósito-García  Universitary Hospital “Marqués de Valdecilla,” Santander – Cantabria, Spain Audrey Evanado  Cardiac Arrhythmia Center, Division of Cardiovascular Medicine, Oregon Health Sciences University, Portland, OR 97239, USA Jacques Genest  Division of Cardiology, McGill University, Royal Victoria Hospital, 687 Pine Avenue West, Montreal, QC, Canada H3A 1A1 [email protected] Eduard Guasch  Department of Cardiology, Thorax Institute, Hospital Clinic, University of Barcelona, Barcelona, Spain Fern R. Hauck  University of Virginia, Charlottesville, VA 22903, USA Kathy Hodgkinson  Clinical Epidemiology Unit, Memorial University, St. John’s, Newfoundland, Canada A1B 3V6 Heikki V. Huikuri  Department of Medicine, Institute of Clinical Medicine, University of Oulu, Oulu, Finland [email protected] Carl E. Hunt  Uniformed University of the Health Sciences, 4550 North Park Avenue, Suite 405, Chevy Chase, MD 20815, USA [email protected] [email protected] Lulia Latan  Biochemistry, McGill University, Montreal, QC, Canada H3A 1A1

Contributors

Contributors

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Juhani M. Junttila  Department of Medicine, Institute of Clinical Medicine, University of Oulu, PO Box 5000, Oulu 90014, Finland [email protected] Stefan Kääb  Ludwig-Maximilians University Klinikum Grosshadern, Medizinische Klinik und Poliklinik I, Marchioninistrasse 15, Munich 81377, Germany [email protected] Paul Khairy  Montreal Heart Institute, University of Montreal, Montreal, QC, Canada H3A 1A1 [email protected] Michelle S. C. Khoo  University of Colorado Denver, 12401 East 17th. Avenue, Leprino Building, Room 559, Aurora, CO 80045, USA [email protected] Yskert von Kodolitsch  Abteilung Kardiologie, Universitaires Herzzentrum, UKE, Martinistrasse 52, 20246 Hamburg, Germany April Manuel  Memorail University of Newfoundland and Labrador, St. John’s, Newfoundland, Canada A1B 3V6 [email protected] A. J. Marian  Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center, 6770 Bertner Street, Texas Heart Institute at St. Luke’s Episcopal Hospital, DAC 900A, Houston, TX 77030, USA [email protected] Barry J. Maron  The Hypertrophic Cardiomyopathy Center, Minneapolis Heart Institute Foundation, 920 E. 28th Street, Suite 620, Minneapolis, MN 55407, USA [email protected] Luisa Mestroni  Electrophysiology Division, Medicine/Cardiology, University of Colorado Denver, Aurora, CO 80909, USA Federico Migliore  Department of Cardiac, Division of Cardiology, Thoracic and Vascular Sciences and Cardiovascular Pathology, University of Padua, Padova, Italy Lluís Mont  Thorax Institute, Department of Cardiology, Hospital Clinic, University of Barcelona, Villarroel 170, Barcelona 08036, Spain [email protected] Carlos A. Morillo  Department of Internal Medicine, Cardiology Division, McMaster University, Hamilton Health Sciences, HGH-McMaster Clinic 5th Floor, 237 Barton Street East, Hamilton, ON, Canada L8L2X2 [email protected] Antonio Oliva  Institute of Forensic Medicine, Catholic University, School of Medicine, Rome, Italy [email protected] Vincenzo L. Pascali  Institute of Forensic Medicine, Catholic University, School of Medicine, Rome, Italy

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Andres Perez Riera  Electro-Vectocardiography, ABC Foundation, São Paulo, Brazil [email protected] Michael Phillips  The Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA Kyndaron Reinier  Cardiac Arrhythmia Center, Division of Cardiovascular Medicine, Oregon Health Sciences University, Portland, OR 97239, USA John Rioux  Department of medicine, University of Montreal, Montreal Heart Institute, 5000 Bélanger, Montreal, QC, Canada H1T1C8 Laura Robb  Cardiovascular Genetic Centre, Montreal Heart Institute, Montreal, QC, Canada H3A 1A1 [email protected] Robert Roberts  Ruddy Canadian Cardiovascular Genetics Centre, University of Ottawa Heart Institute, 40 Ruskin Street, Ottawa, ON, Canada K1Y 4W7 [email protected] Peter N. Robinson  Institut für Medizinische Genetik, Charité Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany [email protected] Georgia Sarquella-Brugada  Department of Pediatrics, CHU Sainte Justine, University of Montreal, Montreal, QC, Canada H3A 1A1 Rainer Schimpf  Department of Medicine – Cardiology, University Hospital Mannheim, Mannheim 68167, Germany Moritz F. Sinner  Ludwig-Maximilians University Klinikum Grosshadern, Medizinische Klinik und Poliklinik I, Marchioninistrasse 15, Munich 81377, Germany [email protected] Jean-Claude Tardif  University of Montreal/Montreal Heart Institute, Montreal, QC, Canada H3A 1A1 Matthew R.G. Taylor  Electrophysiology Division, Medicine/Cardiology, University of Colorado Denver, Aurora, CO 80909, USA Carmen Teodorescu  Cardiac Arrhythmia Center, Division of Cardiovascular Medicine, Oregon Health Sciences University, Portland, OR 97239, USA Gaetano Thiene  Division of Cardiology, Department of Cardiac, Thoracic and Vascular Sciences and Cardiovascular Pathology, University of Padua, Padova, Italy Christian Veltmann  Department of Medicine – Cardiology, University Hospital Mannheim, Mannheim 68167, Germany George Wells  Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, ON, Canada K1Y 4W7 Christian Wolpert  Department of Medicine-Cardiology, Klinikum Ludwigsburg, Ludwigsburg, Germany [email protected]

Contributors

Part Sudden Unexplained Death

I

1

Sudden Unexplained Death in the Community Sumeet S. Chugh, Carmen Teodorescu, Audrey Evanado, and Kyndaron Reinier

With approximately 250,000 US lives lost to this condition on a yearly basis, sudden cardiac death (SCD) is a public health problem of significant magnitude.1,2 In most cases, an associated cardiac disease condition leading to the fatal event can be identified, but for a distinct subgroup of cases, SCD can remain completely unexplained.3 The postmortem examination is negative, with a structurally normal heart and no other identifiable etiologies of sudden death. Most commonly, this form of SCD is referred to as sudden unexplained death syndrome (SUDS), but other terms such as sudden arrhythmic death syndrome and idiopathic ventricular fibrillation have also been used.3-5 The vast majority of cases have some form of primary electrical disorder of the heart leading to a fatal cardiac arrhythmia. Since this syndrome mostly afflicts younger adults and there are significant limitations for predicting risk in family members who are left behind, SUDS is a devastating manifestation of heart disease.6 The goal of this review is to discuss the magnitude of the problem, age-and gender-related prevalence, diagnostic considerations, and clinical/research implications of these observations.

1.1 Magnitude of the Problem While these subjects constitute a small subgroup of overall SCD cases, SUDS is recognized as a distinct phenotype, frequent enough, and with implications

S. S. Chugh () Associate Director, the Heart Institute, Cedars-Sinai Medical Center, Los Angeles CA, USA, 90048 e-mail: [email protected]

significant enough, to merit serious ongoing clinical as well as investigational attention. By definition, the diagnosis of sudden cardiac arrest or death in a structurally normal heart requires detailed imaging of the heart in the survivor, or detailed postmortem examination in the nonsurvivor. With the US national percentage of survival from cardiac arrest estimated at 5%, survivors are by far in the minority. For a variety of reasons, autopsy examination rates have decreased significantly, and even among sudden death victims, these are usually performed in 5–15%. As a consequence, an accurate estimate of the community-wide magnitude of SUDS is difficult to obtain, and we have to rely on studies of cardiac arrest survivors, or autopsy series of SCD. Studies of cardiac arrest survivors have reported a »5% prevalence of SUDS.7-11 Similar observations regarding SUDS have been made from autopsy series of SCD. A 270-patient autopsy series of SCD cases from the Jesse Edwards Registry of Cardiovascular Disease reported that 256 patients (95%) had evidence of structural abnormalities, but 14 patients (5%) had structurally normal hearts.3 The mean age was 35 ± 9 years (median age, 33 years), and the majority (10 of 14) were females. Seven patients had a history of syncope, palpitations, or chest pain prior to SCD. In the remaining seven cases, sudden death was the first presentation of an illness. A detailed review of other published autopsy series identifies interesting trends related to age and gender. In general, the younger the age group, the higher the prevalence of SUDS. In two separate postmortem studies of subjects less than 35 years of age, prevalence of SUDS was 18%12 and 28%.13 The National Swedish Rattsbase study (age 15–35 years) has reported SUDS prevalence rates of 21%.14 In a retrospective study of military recruits aged 18–35 years, prevalence of SUDS was as high as 35%.15 A 30-year population-based postmortem study in Olmsted County,

R. Brugada et al. (eds.), Clinical Approach to Sudden Cardiac Death Syndromes, DOI: 10.1007/978-1-84882-927-5_1, © Springer-Verlag London Limited 2010

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Minnesota observed a 13% prevalence of SUDS among 54 young adults aged 20–40 years.16 Among age groups older than 50 years, though detailed studies have not been performed, chances are that the prevalence of SUDS will be well below 5% of overall SCD cases. Therefore, depending on the age group, SUDS prevalence can range between 10 distinct LQTS-susceptibility genes that encode critical channel pore-forming alpha subunits or essential channel interacting proteins.17,18 On the basis of the molecular analysis of 93 SIDS cases, 2% had a distinct sodium channel gene (SCN5A) channel defect, one related to exon 17 and one related to exon 28. The high prevalence of SCN5A mutations in SIDS is consistent with their established role in causing arrhythmia during sleep, when most sudden and unexpected deaths occur. LQTS can also be caused by potassium channel polymorphisms. To date, polymorphisms have been observed in increased frequency in SIDS vs. controls for KCNQ1, KCNH2, and KCNE2. The mechanism by which potassium channel variants can contribute to SIDS is thought to be mediated at least in part through increased sympathetic activity during sleep, including REM sleep, and associated sleep-related hypoxemia and chemoreceptive reflexes.19 A recent molecular study in a large number of SIDS infants and controls from Norway further substantiates the importance of LQTS variants in SUDI.20 Polymor­ phisms in 5 genes [KCNQ1, KCNH2, SCN5A, Caveolin-3 (CAV3), and KCNE2] associated with LQTS were observed in 9.5% of 201 SIDS infants (CI. 5.8–14.4%). On the basis of functional analyses, a total of eight mutations and seven rare variants found in 19 cases were considered to be likely contributors to sudden and unexpected death. Since disease-causing mutations have been identified only in about 70% of clinically diagnosed LQTS, the true prevalence of LQTS associated with SUDI or SIDS may be underestimated in this study. Functional characterization of multiple SCN5A polymorphisms revealed a spectrum of sodium channel dysfunction ranging from overt to latent or concealed pathological phenotypes. In variants with latent dysfunction, persistent current was evident only under conditions of internal acidosis, or when expressed in the context of a common SCN5A splice variant.21 In a separate study of 224 U.S. cases of SIDS, an increased frequency of a SCN5A polymorphism

2  Sudden Infant Death Syndrome: Gene–Environment Interactions

was also observed, and African Americans homozygous for the S1103Y mutation had a 24-fold increased risk for SIDS compared with controls.22 Of particular note, acidosis was again shown to be an important perturbation in that the molecular phenotype of increased late sodium current and hence prolonged QT interval was expressed only when the mutant channels were exposed to acidosis. Sodium channel-interacting proteins are also implicated in SIDS.23 Caveolin-3 (CAV3) and sodium channel beta-4 subunit (SCH4B), for example, are two mutations in SCN5-A associated channel-interacting proteins that are novel LQTS-susceptibility genes.24,25 CAV3 mutations have been reported in black SIDS infants.24 Most recently, three novel SIDS-associated mutations have been reported in a novel sodium channel-interacting protein, glycerol-3-phosphate dehydrogenase 1-like gene (GPD1-L).23 Mutations in the RyR2-encoded cardiac ryanodine receptor cause the highly lethal catecholaminergic polymorphic ventricular tachycardia (CPVT1).26 It closely mimics LQTS, but is not associated with an abnormal resting electrocardiogram. It typically manifests in response to stress and may lead to sudden arrest during sleep, in which instances the causal stress could be hypoxia or other sleep-related increases in sympathetic activity. Two distinct and novel RyR2 gain-offunction mutations have been documented in SIDS infants, and neither mutation was observed in 400 reference alleles from 100 African American and 100 Caucasian healthy control subjects.26 A short QT interval (SQTS) has also been associated with familial sudden death and may be a cause of arrhythmogenic sudden death in early infancy.27 Gainof-function mutations in at least three potassium channel genes have been reported, resulting in enhanced repolarization, and hence a shortened QT interval and increased risk of atrial and ventricular arrhythmias and cardiac arrest. Although the extent to which SQTS may contribute to risk for SIDS is unknown, a gain-offunction KCNQ1 mutation has been identified postmortem in one Norwegian SIDS infant, and three children later diagnosed with SQTS had a history of an apparent life-threatening event (ALTE) or syncope in infancy.27,28 No antemortem analyses of QT intervals are available in infants who were found to have a sodium/potassium cardiac channel gene polymorphism postmortem. However, one infant with an ALTE has been reported,

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in whom LQTS was subsequently diagnosed and was associated with a spontaneous mutation on the SCN5A gene.14 On the basis of the aggregate of all the genetic studies, it is presently estimated that 10%, and perhaps as many as 15% of SUDI are associated with a primary cardiac channelopathy, causing a sudden, unexpected lethal arrhythmia.13

2.2.2 Serotonin Transporter (5-HTT) Several polymorphisms have been identified in the promoter region of the serotonin (5-HT) transporter protein (5-HTT) gene which is located on chromosome 17.4,13 Variations in the promoter region of 5-HTT affect 5-HT membrane uptake and regulation. The long “L” allele increases effectiveness of the promoter and hence would lead to reduced extracellular 5-HT concentrations at nerve endings compared to the short “S” allele.29,30 The L/L genotype is associated with increased 5-HTT binding on postmortem neuroimaging and binding studies.29 Caucasian, African American, and Japanese SIDS victims are more likely than matched controls to have the “L” allele.29,30 Among 27 Japanese SIDS victims and 115 controls, for example, there are differences in genotype distribution (p600  ms) or increase in U wave width, with possible typical 180° rotation of QRS axis

6.5 Electrophysiological Mechanism Onset by early after depolarization EADs by triggered activity. It depends on the oscillations of action potential (AP), that occur before repolarization is fulfilled at the end of phase 2 and phase 3, which originate potentials that spread during the process of repolarization in phases 2 or 3. EADs are divided into: 1. From Phase 2 (a) Oscillations that occur when in the plateau, dome or phase 2 by increase in inward Ca2+ by the slow I Ca-L channel.

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Fig. 6.9  ECG of congenital long QT syndrome Romano-Ward variant of LQT3. Seven-year-old boy, without sensorineural deafness. LQT3 affects the SCN5A gene in chromosome 3p2124. The affected channel is the Na+ current in the alpha subunit.

A. Perez-Riera

There is abnormal prolongation of QT interval (620  ms) with delayed T wave onset. This patient suffered repetitive syncopes. The patient with LQT3 tends to suffer more events during sleep

Fig. 6.10  “Swinging pattern” typical 180° rotation of QRS axis around the baseline. Rotation of QRS apices of upto 180° along the baseline

(b) There is an additional and persistent inflow of the sodium cation in phase 2 or AP plateau. This is observed in variant 3 or LQT3. This explains the increase in ST segment duration in ECG. QT interval prolongation at the expense of ST segment prolongation. EADs originate TdPs. 2. From Phase 3 of Fast Repolarization (a) These postdepolarizations occur during phase 3 of AP by reduction in the activity of outward K+

channels (Ik–R or Ik–s) as it happens in congenital LQTs LQT2 and LQT1 respectively. The latter differentiate from the former in that they present Ca2+ release from the Ca2+ release channel or ryanodine receptor. Moreover, activation of the INa+- Ca2+ cation exchange channel by electrogenic mechanism (there is exchange of three Na+ molecules by one of Ca2+). TdPs are maintained by re-entry secondary to TDR, where heterogeneous response of ventricular myocardium thickness cells stands out.

6  Electrocardiograms Not to Miss

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6.6 Cardinal Sign

6.8.2 Main ECG Features

Polymorphic QRS. Rotation of QRS apices of up to 180° along the baseline: swinging pattern of Marriot; Usual Duration: from 5 to 20 QRS complexes; HR: from 150 to 300 bpm (usually 200–250 bpm); Clinical Repercussions: asymptomatic, presyncope, syncope or degeneration into VF with cardiorespiratory arrest; Onset: by extrasystole of long, delayed or telediastolic coupling; however, with R on T phenomenon. Frequent after pauses by “long-short” sequence or in bradyarrhythmias, complete atrioventricular (AV) block and sudden PR interval prolongation. There are three predominant different initiating patterns/modes of TdP:27

Ninety percent of individuals with ARVC/D have some ECG abnormalities. The most commonly seen ECG abnormality is T wave inversion in leads V1–V3. (Fig. 6.11) However, this is a nonspecific finding, and may be considered a normal variant in RBBB, women, and children under 12 years. In absence of CRBBB in patients >12 years old, negative T wave from V1 to V3 is a sign with great value for diagnosis. In normal, young patients, there is usually positive T polarity in V1; however, it may flatten and nearly always has a positive polarity in V2. In symptomatic patient carriers of ARVD, the ECG generally shows T wave inversion in V1 and V2, which may reach up to V6 QRSD ³110 ms has sensitivity of 91%, specificity of 90%, and a total predictive accuracy of 90% in predicting inducibility of VT in ARVC/D patients (Fig. 6.12).29 The so-called Epsilon wave is found in about 33% of those with ARVC/D. This is described as a terminal notch in the QRS complex. It is due to slowed intraventricular conduction. The epsilon wave may be seen on a surface ECG;30 however, it is more commonly seen on SAECGs (Fig. 6.13).

1. A “short-long-short” sequence pattern (65%) defined as one or more short-long cardiac cycles followed by an initiating short-coupled PVC. 2. An “increased sinus rate” pattern (25%) defined as a gradual increase in sinus rate with or without T-wave alternans. 3. A “changed depolarization” pattern (10%) defined as sudden long-coupled PVC or fusion beat followed by short-coupled PVC.

6.7 Most Common Causes Severe bradyarrhythmia, hypopotasemia, drugs; Effective Measures: b-blockers, bretylium tosylate, diphenylhydantoin, association of b-blockers and diphenylhydantoin or b-blockers associated to permanent pacemaker. In refractory cases, left sympathectomy or ICD is indicated.

6.8 Arrhythmogenic Right Ventricular Dysplasia 6.8.1 Introduction Arrhythmogenic right ventricular dysplasia (ARVC/D) is a cardiomypathy that predominantly affects the right side of the heart and causes ventricular arrhythmias. It is characterized by the progressive replacement of myocardial cells by fat and fibrous tissue. Today, the entity is considered a disease of cell adhesion because of mutations in desmosomal genes.28

Fig. 6.11  We observe T wave inversion on right precordial leads in a patient with ARVD/C. Inverted T wave in right precordial leads (V1 and V2) >12 years old, in absence of Complete Right Bundle Branch Block is an important ECG clue for the diagnosis

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Fig.  6.12  QRSD of V1 + V2 + V3/V4, V5 and V6 or ³1.2 in approximately 65% of cases. QRS prolongation located ³ in right precordial leads. QRSD ³ from V1 to V3 with 91% sensitivity, 90% specificity that predicts VT in patient carriers of ARVD

In ARVC/D, sometimes there is evidence of peripheral blocks of the right bundle branch: the IRBBB or CRBBB topography occurs in the divisional portion of the right branch, i.e., in the free wall of the RV after the trunk of the branch splits in the base of the papillary muscle of the tricuspid valve, and its mechanism seems to respond to dysplastic involvement of the free wall, whether in the RVOT, the RVIT, or in the apical region (dysphasia triangle) where the dysplastic area is found.31,32

A. Perez-Riera

Ventricular ectopy seen on a surface ECG in the setting of ARVC/D is typically of LBBB morphology, with a QRS axis of −90 to +110°. The origin of the ectopic beats is usually from one of the three regions of fatty degeneration (the “triangle of dysplasia”): the RV outflow tract, the RV inflow tract, and the RV apex. In ARVC/D, the VT is usually M-VT, sustained or not, and with morphology of LBBB because its origin is in the RV. If its origin is in the RVOT, the SÂQRS is generally deviated to the right between +90° and +120° (QRS of the “qR” or “QS” type in DI). In cases with LBBB morphology and SAQRS to the left, the focus is located in the RVIT, the apex, or the inferior wall of the RV. A VT with LBBB morphology, and SÂQRS to the left, nearly always suggests structural heart disease (Fig. 6.14). 6.8.2.1 ECG with Modified Protocol Protocol for obtaining ECG in patients with suspected ARVC/D 1. Rhythm strips of the precordial leads V1–V6 should be obtained at double speed (50 mm/s) and double amplitude (20  mm/mv) in order to compare the duration of the QRS complex (QRSD) in different leads as well as to record the epsilon wave.

Fig. 6.13  SR, CRBBB, terminal notch located in the J point (EPSILON wave). The EPSILON wave could be the result of delayed activation in the RV. It is visible from V1 to V3 and in the FP leads. T wave inversion is observed in V1 to V3, characteristic of ARVD

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Fig. 6.14  MVT with a heart rate (HR) of 214 bpm, pattern of CLBBB and electrical axis with extreme shift to the left: it originates in the RVIT. This axis indicates presence of structural heart disease

2. Rhythm strips of leads DI-aVF should be obtained at double speed (50  mm/s) and double amplitude (20 mm/mv). Place the left arm lead over the xyphoid process, the right arm lead on the manubrium sternum, and the left leg lead over a rib at the V4 or V5 position in order to elicit the epsilon wave. Localized prolongation of QRSD interval in V1–V3/QRSD interval in > than 1.2 has been found in 97% of cases of V4–V6 ARVC/D. The QRSD is correlated with the amount of fibrous tissue in patients with VT of RV origin The sensitivity of this QRS diagnostic criterion has not been established in patients who do not have overt manifestation of this disease. If difference is equal to or larger than 25 ms, this is in favor of slowing of conduction in the RV. The specificity of this criterion has not yet been completely established in patients without this entity.

6.9 Short QT Syndrome 6.9.1 Introduction Hereditary, congenital, or familial short QT syndrome (SQTS) is a clinic-electrocardiographic entity, clinically

characterized by a large set of signs and symptoms, such as: syncope, sudden death, dizziness, and high tendency to appearance of episodes of paroxysmal runs of AF, high risk of ventricular tachyarrhythmia, and sudden death. A few families have been identified, with 3 types existing: SQT1 (Ikr), SQT2 (Iks) and SQT3 (Ik1).33 The entity is the opposite of long QT syndrome, since they exert opposite effects regarding potassium rectifier channels function: SQTS causes increase in the function of such channels; on the contrary, long QT syndrome causes decrease of function.

6.9.2 Electrocardiographic Characterization T wave: morphology: tall T wave from V3 through V5 with narrow base and a tendency to be symmetrical (the patient does not have serum potassium increase); SAT: +42° in the FP and discretely heading to the front and below in the HP; QT/QTc interval: 302/315: short for this rate (the inferior limit for a 67 bpm HR in men is 324  ms); JT/JTc interval: 182/199  ms: extremely short (QT-QRSD > JT. 302–120 > 182  ms). (The inferior limit for a 67 bpm HR in men is 224 ms).

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Conclusion: (1) Complete RBBB; (2) Short QT interval with no use of drugs, electrolytic disorders, or any associated pathophysiological state; (3) Very short JT interval; (4) Probable early repolarization pattern (Fig. 6.15–6.17). It is important to recognize the ECG pattern of this entity because it is related to a high risk of sudden death in young, otherwise healthy subjects. 1. Rhythm: high tendency to appearance of episodes of paroxysmal runs of AF in family members and no known history of SCD. In KCNH2 mutation, the class Ic agent propafenone could be effective to prevent episodes of paroxysmal AF.34 Approximately 31% of cases have palpitations secondary to AF documented even in young subjects (Fig. 6.18). In this tracing, we can see a short period of gross AF. The patient described palpitations. Congenital short QT syndrome is associated to high incidence of

Fig. 6.15  Name: JSVB; age: 27; sex: male; race: white; weight: 67  Kg. Height: 1.72  m; date: 06/24/2004; medication in use: none. QRS duration (QRSD): 120 ms; QRS morphology: tripha-

A. Perez-Riera

paroxysmal AF, the electrophysiological mechanism of which would be caused by heterogeneous shortening of the cardiac potential and refractory period of atrial cardiomyocytes. Approximately 8  h later during the same test, the patient spontaneously reversed into SR (Fig. 6.19). 2. T wave: T waves of great voltage and narrow base, in which: Polarity: Positive; Voltage: great voltage; Duration: narrow base; Aspect: resemble T wave in “desert tent” of hyperpotasemia. 3. U wave: The form of congenital SQTS caused by the mutation in KCNH2 abolishes rectification of HERG currents and specifically causes gain of function, I(Kr) in the ventricle with minimal effects on the Purkinje fiber action potential duration (APD).35 Such preferential prolongation may explain the separation of the T and U waves observed in the ECG of SQT1 patients and lead to re-excitation of the ventricle endocardium.36

sic rSR’ pattern in V1 and broad S wave in left leads DI, aVL V5 and V6 (right terminal forces); intrinsic deflection in V1>50 ms

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Fig. 6.16  ECG/VCG correlation FP

Fig. 6.17  CG/VCG correlation horizontal plane

4. QT interval: Short QT interval is defined as QTc of less than 350 ms.37 In congenital SQTS, all patients have a constantly and uniformly very short QT/QTc interval, which was £280  ms and QTc £300  ms.7

More recently, the same authors considered the QT interval of £320 ms and QTc £340 ms as maximal superior limit. 5. JT interval: Very short (Fig. 6.20).

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A. Perez-Riera

Fig. 6.18  Long duration electrocardiogram recording (holter)

6.10 Catecholaminergic Polymorphic Ventricular Tachycardia 6.10.1 Introduction Catecholaminergic polymorphic ventricular tachy­ cardia (CPVT) is a rare, clinically and genetically heterogeneous disease characterized by exercise, adrenergic stress induced or adrenergically-mediated ventricular tachyarryhtmias, with recurrent syncope of uncertain etiology after physical and emotional stress or SCD, usually in the pediatric or juvenile age group.38

2. Rhtyhm: Sinus rhtyhm is the rule. Abnormalities in sinoatrial node function, as well as atrioventricular nodal function, could produce AF, atrial flutter, and atrial standstill (sick sinus syndrome). 3. QTc Interval: normal at resting ECG.39 See proposed algorithm diagnostic scheme for PVT or VF in structurally normal hearts based initially in QT interval duration. 4. U Wave Alternans: U-wave alternans was observed in following clinical circumstances: After ventricular pacing at 160 bpm, during the recovery phase after the exercise stress test, following a pause from sinus arrest and a change in T-wave was also noted, precordial V3–V5 are the leads showing alternans most clearly.40 5. Arrhythmias

6.10.2 Electrocardiographic Features

(a) Supraventricular Arrhythmias

1. HR: baseline bradycardia tendency off drugs is observed in all carriers. (slow HR);

AF, atrial flutter, atrial standstill, and sick sinus syndrome may be present.41 (b) Ventricular Arrhythmias

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Fig. 6.19  This trace shows spontaneously reversion from atrial fibrillation to sinus rhythm in the same Holter Recording, eight hours later

1. Ventricular arrhythmias elicited exclusively by exercise or adrenergic stress. Typically, they are induced by isoproterenol infusion. 2. Premature ventricular complex (PVCs) Calcium channel antagonist, verapamil, can suppress PVCs and nonsustained VT salvoes in CPVT caused by RyR2 mutations.42 3. PVT occurs during physical exercise or emotional stress. Most cases are nonsustained (72%), but 21% are sustained and 7% are associated with VF. 4. PVT and bidirectional VT in association are observed in 21% of cases in pediatric group. 5. There is 100% inducement of CPVT by exercise, 75% by catecholamine infusion, and none by programmed stimulation. No late potential is recorded. Onset is in the right ventricular outflow tract in more than 50% the cases.42 His-Purkinje system is an important source of focal arrhythmias in CPVT. 6. Bidirectional VT is a more typical feature. Its characteristics are:

(b) HR between 140 and 200 bpm. (c) Complete RBBB pattern. (d) Sudden change of QRS morphology by change of SÃQRS, successively from beat to beat. (e) SÂQRS in the FP with differences close to 180°: one beat presents ÂQRS between −60° and −90° (Complete RBBB + LAFB) and the following between +120° and +130° (CRBBB + LPFB). (f) Eventually alternating RBBB and LBBB morphology. The origin of the tachycardia is located near the His bundle bifurcation. This suggested a single focus at the interventricular septum with two exit sites, depolarizing the right and left ventricle in an alternate fashion. Two sets of fairly constant and alternating VA intervals are recorded. This fact is consistent with two ventricular circuits used alternatively. It is postulated that the tachycardia is due to macrore-entry involving the two fascicles of the left branch. Re-entry may be a possible mechanism in some cases of bidirectional tachycardia.

(a) Regular VT.

The Fig. 6.21 shows a typical pattern of bidirectional VT

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A. Perez-Riera

Fig. 6.20  In V1 lead we observe typical Complete Right Bundle Branch Block QRS pattern and very short JT and QT intervals (170ms and 281ms). In V6 lead we can see a broad final S wave typical of RBBB associated with short JT and QT intervals

Fig.  6.21  Female, white, 20-year-old, recurrent syncope of uncertain etiology after physical and emotional stress carrier of familial catecholaminergic cardiomyopathy. Alternans QRS

complexes are observed with alternating right and left bundle branch block morphology. The QRS axis shifts from −60° to +120°

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6.11 Clue for Electrocardiographic Diagnosis of CPVT Association of ECG sinus bradycardia + normal QTc interval + stress-related, bidirectional VT or PVT in the absence of apparent structural heart disease42

References   1. Sovari AA, Prasun MA, Kocheril AG. ST segment elevation on electrocardiogram: the electrocardiographic pattern of Brugada syndrome. MedGenMed. 2007;9:59   2. Hisamatsu K, Kusano KF, Morita H, et  al. Relationships between depolarization abnormality and repolarization abnormality in patients with Brugada syndrome: using body surface signal-averaged electrocardiography and body surface maps. J Cardiovasc Electrophysiol. 2004;15:870–876   3. Morita H, Zipes DP, Morita ST, Wu J. Differences in arrhythmogenicity between the canine right ventricular outflow tract and anteroinferior right ventricle in a model of Brugada syndrome. Heart Rhythm. 2007;4:66–74   4. Torres PI, Nava S, Gómez-Flores J, et al. Association of congenital, diffuse electrical disease in children with normal heart: sick sinus syndrome, intraventricular conduction block, and monomorphic ventricular tachycardia. J Cardiovasc Electrophysiol. 2008;19(5):550–555   5. Probst V, Denjoy I, Meregalli PG, et al. Clinical aspects and prognosis of Brugada syndrome in children. Circulation. 2007;115:2042–2048   6. Yokokawa M, Noda T, Okamura H, et  al. Comparison of long-term follow-up of electrocardiographic features in Brugada syndrome between the SCN5A-positive probands and the SCN5A-negative probands. Am J Cardiol. 2007;100: 649–655   7. Bigi MA, Aslani A, Shahrzad S. Clinical predictors of atrial fibrillation in Brugada syndrome. Europace. 2007;9: 947–950   8. Takagi M, Yokoyama Y, Aonuma K, Aihara N, Hiraoka M; Japan Idiopathic Ventricular Fibrillation Study (J-IVFS) Investigators. Clinical characteristics and risk stratification in symptomatic and asymptomatic patients with Brugada syndrome: multicenter study in Japan. Cardiovasc Electro­ physiol. 2007;18:1244–1251   9. Junttila MJ, Brugada P, Hong K, et al. Differences in 12-lead electrocardiogram between symptomatic and asymptomatic Brugada syndrome patients. J Cardiovasc Electrophysiol. 2008;19(4):380–383 10. Babai Bigi MA, Aslani A, Shahrzad S. aVR sign as a risk factor for life-threatening arrhythmic events in patients with Brugada syndrome. Heart Rhythm. 2007;4:1009–1012 11. Wilde AA, Antzelevitch C, Borggrefe M, Brugada J, Brugada R, Brugada P, Corrado D, Hauer RN, Kass RS, Nademanee K, Priori SG, Towbin JA; Study Group on the Molecular Basis of Arrhythmias of the European Society of Cardiology. Proposed diagnostic criteria for the Brugada syndrome: consensus report. Circulation. 2002;106:2514–2519

89 12. Cau C. The Brugada syndrome. A predicted sudden juvenile death. Minerva Med. 1999;90:359–364 13. Junttila MJ, Raatikainen MJ, Perkiomaki JS, Hong K, Brugada R, Huikuri HV. Familial clustering of lone atrial fibrillation in patients with saddleback-type ST-segment elevation in right precordial leads. Eur Heart J.  2007;28: 463–468 14. Tada T, Kusano KF, Nagase S, et al. Clinical significance of macroscopic T-wave alternans after sodium channel blocker administration in patients with Brugada syndrome. J Cardiovasc Electrophysiol. 2008;19:56–61 15. Nishizaki M, Fujii H, Sakurada H, Kimura A, Hiraoka M. Spontaneous T wave alternans in a patient with Brugada syndrome–responses to intravenous administration of class I antiarrhythmic drug, glucose tolerance test, and atrial pacing. J Cardiovasc Electrophysiol. 2005;16:217–220 16. Morita H, Zipes DP, Lopshire J, Morita ST, Wu J. T wave alternans in an in vitro canine tissue model of Brugada syndrome. Am J Physiol Heart Circ Physiol. 2006;291: H421-H428 17. Bezzina C, Veldkamp MW, van Den Berg MP, et al. A single Na(+) channel mutation causing both long-QT and Brugada syndromes. Circ Res. 1999;85:1206–12013 18. Mizumaki K, Fujiki A, Nishida K, et  al. Bradycardiadependent ECG changes in Brugada syndrome. Circ J. 2006; 70:896–901 19. Pitzalis MV, Anaclerio M, Iacoviello M, et  al. Rizzon P QT-interval prolongation in right precordial leads: an additional electrocardiographic hallmark of Brugada syndrome. J Am Coll Cardiol. 2003;42:1632–1637 20. Antzelevitch C, Pollevick GD, Cordeiro JM, et al. Loss-offunction mutations in the cardiac calcium channel underlie a new clinical entity characterized by ST-segment elevation, short QT intervals, and sudden cardiac death. Circulation. 2007;115:442–449 21. Brugada P, Brugada J. Right bundle branch block, persistent ST segment elevation and sudden cardiac death: a distinct clinical and electrocardiographic syndrome. J Am Coll Cardiol. 1992;20:1391–1396 22. Zareba W, Moss AJ, le Cessie S, Hall WJ. T wave alternans in idiopathic long QT syndrome. J Am Coll Cardiol. 1994;23: 1541–1546 23. Mönnig G, Eckardt L, Wedekind H, et al. Electrocardiographic risk stratification in families with congenital long QT syndrome. Eur Heart J. 2006;27:2074–2080 24. Shimizu W, Noda T, Takaki H, et  al. Diagnostic value of epinephrine test for genotyping LQT1, LQT2, and LQT3 forms of congenital long QT syndrome. Heart Rhythm. 2004;1: 276–283 25. Denjoy I, Lupoglazoff JM, Villain E, et  al. The Jervell and Lange-Nielsen syndrome. Natural history, molecular basis and clinical outcome. Arch Mal Coeur Vaiss. 2007;100:359–364 26. Zareba W. Drug induced QT prolongation. Cardiol J. 2007; 14:523–535 27. Noda T, Shimizu W, Satomi K, et  al. Classification and mechanism of Torsade de Pointes initiation in patients with congenital long QT syndrome. Eur Heart J. 2004;25: 2149–2154 28. Syrris P, Ward D, Asimaki A, et  al. Clinical expression of Plakophilin-2 mutations in familial arrhythmogenic right ventricular cardiomyopathy. Circulation. 2006;113:356–364

90 29. Nasir K, Tandri H, Rutberg J, et al. Filtered QRS duration on signal-averaged electrocardiography predicts inducibility of ventricular tachycardia in arrhythmogenic right ventricle dysplasia. Pacing Clin Electrophysiol. 2003;26:1955–1960 30. Gregor P. Electrocardiography in cardiomyopathies. Vnitr Lek. 2003;49:727–729 31. Fontaine G, Frank R, Guiraudon G, et  al. Significance of intraventricular conduction disorders observed in arrhythmogenic right ventricular dysplasia. Arch Mal Coeur Vaiss. 1984;77:872–879 32. Jaoude SA, Leclercq JF, Coumel P. Progressive ECG changes in arrhythmogenic right ventricular disease. Evidence for an evolving disease. Eur Heart J. 1996;17:1717–1722 33. Brugada R, Hong K, Cordeiro JM, Dumaine R. Short QT syndrome. CMAJ. 2005;173(11):1349–1354 34. Hong K, Bjerregaard P, Gussak I, Brugada R. Short QT syndrome and atrial fibrillation caused by mutation in KCNH2. J Cardiovasc Electrophysiol. 2005;16:394–396 35. Brugada R, Hong K, Dumaine R, et al. Sudden death associated with short-QT syndrome linked to mutations in HERG. Circulation. 2004;109(1):30–35 36. Anttonen O, Junttila MJ, Rissanen H, Reunanen A, Viitasalo M, Huikuri HV. Prevalence and prognostic significance of short QT interval in a middle-aged Finnish population. Circulation. 2007;116:714–720

A. Perez-Riera 37. Laitinen PJ, Swan H, Piippo K, Viitasalo M, Toivonen L, Kontula K. Genes, exercise and sudden death: molecular basis of familial catecholaminergic polymorphic ventricular tachycardia. Ann Med. 2004;36(suppl 1):81–86 38. Postma AV, Denjoy I, Kamblock J, et al. Catecholaminergic polymorphic ventricular tachycardia: RYR2 mutations, bradycardia, and follow up of the patients. J Med Genet. 2005; 42:863–870 39. Aizawa Y, Komura S, Okada S, et  al. Distinct U wave changes in patients with catecholaminergic polymorphic ventricular tachycardia (CPVT). Int Heart J. 2006;47: 381–389 40. Fazelifar AF, Nikoo MH, Haghjoo M, et al. A patient with sick sinus syndrome, atrial flutter and bidirectional ventricular tachycardia: coincident or concomitant presentations? Cardiol J. 2007;6:585–588 41. Swan H, Laitinen P, Kontula K, Toivonen L. Calcium channel antagonism reduces exercise-induced ventricular arrhythmias in catecholaminergic polymorphic ventricular tachycardia patients with RyR2 mutations. J Cardiovasc Electrophysiol. 2005;16:162–166 42. Sumitomo N, Harada K, Nagashima M, et al. Catecholamin­ ergic polymorphic ventricular tachycardia: electrocardiographic characteristics and optimal therapeutic strategies to prevent sudden death. Heart. 2003;89:66–70

7

Sudden Cardiac Death in Forensic Pathology Antonio Oliva and Vincenzo L. Pascali

7.1 Introduction Sudden cardiac death (SCD) is the leading mode of death in all communities of the United States and the European Union, but its precise incidence is unknown. Internationally accepted methods of death certification do not include a specific category of SCD. Estimates for the United States range from 250,000 to 400,000 adult people dying suddenly each year owing to cardiovascular causes, with an overall incidence of 1–2/1,000 population per year.1-3 A task force of the European Society of Cardiology has adopted the incidence ranges from 36 to 128 deaths per 100,000 population per year.4,5 More than 60% of these are because of coronary heart disease. Among the general population of adolescents and adults younger than the age of 30 years, the overall risk of SCD is 1/100,000 and a wider spectrum of diseases can account for the final event.6 The major difficulties in interpreting the epidemiological data on sudden death are the lack of standardization in death certificate coding and the variability in the definition of sudden death. Sudden death has been defined as “a natural, unexpected fatal event occurring within one hour from the onset of symptoms in an apparently healthy subject or whose disease was not so severe as to predict an abrupt outcome.7” This well describes many witnessed deaths in the community or in emergency departments. It is less satisfactory in forensic practice, where autopsies may be requested on patients whose deaths were not witnessed, occurred during sleep, or at an unknown time before their bodies were discovered. Under the

latter circumstances, it is probably more satisfactory to assume that the death was sudden if the deceased was known to be in good health 24 h before the occurrence of death.8 Moreover, for practical purposes, a death can be classified as sudden if a patient is resuscitated after cardiac arrest, survives on life support for a limited period of time, and then dies owing to irreversible brain damage. Forensic pathologists are responsible for determining the precise cause of sudden death, but there is considerable variation in their approach to this increasingly complex task. A variety of book chapters, professional guidelines, and articles have described how pathologists should investigate sudden death,9-14 but there is little consistency among different centers, and even among different countries. Furthermore, recent advances in the field of molecular genetics have expanded our understanding of the etiology of many lethal and heritable channelopathies leading to fatal arrhythmias, such as congenital long QT syndrome (LQTS), catecholaminergic polymorphic ventricular tachycardia (CPVT), and Brugada syndrome (BrS); thus, forensic pathologists actually play a crucial role in such circumstances because an accurate postmortem diagnosis of the causes of SCD is of particular importance to establish preemptive strategies to avoid other tragedies among the relatives.15 In this chapter, we have summarized the state of the art forensic investigation and autopsy techniques for an adequate assessment of SCD in general population, and have described the main pathological findings at postmortem analysis.

7.1.1 The Range of Pathology A. Oliva () Institute of Forensic Medicine, Catholic University, School of Medicine, Rome, Italy e-mail: [email protected]

Many reports describe the pathological findings in SCD (Tables 7.1 and 7.2). These studies differ in many

R. Brugada et al. (eds.), Clinical Approach to Sudden Cardiac Death Syndromes, DOI: 10.1007/978-1-84882-927-5_7, © Springer-Verlag London Limited 2010

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Table 7.1  Sudden Cardiac Death in Adult Authors Setting

Patients and Methods

Selected Results

Davies et al. 199911

London, England

168 patients (21 female) dying from cardiac disease within 6 h of onset of symptoms. Detailed histology

73% had intraluminal or occlusive coronary thrombosis. Presence of thrombus associated with single vessel disease, acute myocardial infarction and prodromal symptoms

Leach et al. 199516

Nottingham, England

206 out-of-hospital sudden deaths due to coronary heart disease. Detailed histology

Coronary artery thrombosis +/– acute infarction in 48.5% of cases. Presence of these changes decreased with age and a previous history of IHD

Burke et al. 199717

Usa

113 males who died of coronary heart disease. Detailed histology

52% acute coronary thrombosis (10 with acute infarcts) 48% coronary stenosis without thrombosis (two with acute infarcts)

 Chugh et al. 200071

Usa

270 hearts referred to a cardiac pathology unit over 13-year-period. 190 males and 80 females aged > 20 years

 65% coronary artery disease  9% cardiomyopathy  11% myocarditis 14% CHD  5% structurally normal

Bowker et al. 200319

UK

National study of SCD in white males aged 16–64 years, no history of cardiac disease, seen alive within 12 h of death. Limited histology

37% acute coronary thrombosis or acute infarction 20% coronary stenosis with healed infarction 18% coronary stenosis without infarction 8% cardiomyopathy or LVH 4% unexplained

Chase, 200518

Southern England

321 SCDs in males and females aged >16 years, 2002–2003. Limited histology

33% acute myocardial infarction or acute coronary thrombosis 33% coronary stenosis with healed infarction 17% coronary stenosis without healed infarction 14% cardiomyopathy or LVH 2% unexplained

Fabre and Sheppard 200620

UK

453 hearts referred to a cardiac pathology unit, 1994–2003

59% structurally normal 24% cardiac muscle disease

Di Gioia et al. 200672

Italy

100 hearts referred to cardiac pathology unit, 2001-2005

30%, atherosclerotic 22% cardiomyopathies 28% various cardiac abnormalities 20% Inherited cardiac disease CHD, congenital heart disease; IHD, ischaemic heart disease; LVH, left ventricular hypertrophy; SCD, sudden cardiac death. (SOURCE: Data modified from Gallagher PJ 69)

ways, especially with respect to the age and type of patients investigated and the extent of histological sampling. In adults, coronary artery disease (CAD) is by far, the leading cause of death. The proportion of cases with the evidence of acute coronary thrombosis or recent myocardial infarction (MI) is higher in studies in which detailed histology was performed

(Table 7.1). With detailed histology, acute thrombosis was identified in 72, 52, and 47% of the cases.11,16,17 In contrast, recent studies where histology was limited showed acute thrombosis in 37% and 33% of the cases.18,19 Whether this represents a genuine change in the incidence of acute thrombosis in SCD or a failure of the pathologists to recognize thrombi without

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Table 7.2  Sudden Cardiac Death in young patients Authors Setting Patients and Methods

Selected Results

Wren et al. 2000

North England

229 sudden deaths in patients aged 1–20 years, 1985–1994

Asthma, respiratory infection or epilepsy 111 (48.5%) SIDS 20 (8.7%) Previous diagnosis of cardiac disease, chiefly congenital heart disease 33 (14.5%) Cardiomyopathy 8 (3.5%) Myocarditis 5 (2.2%) Coronary atheroma 1 (0.4%) Unexplained 21 (9.2%)

Corrado et al. 200167

Italy

273 SCDs, 218 males, 82 females aged 1–35 years, 1979–1998

Cardiomyopathy 66 (24%) Myocarditis 27 (10%) Coronary atheroma 54 (20%)

Maron 200374

Usa

387 sudden deaths in athletes aged 0–35 years

Unexplained 16 (6%) Cardiomyopathy 122 (32%) Myocarditis 20 (5%) Coronary atheroma 10 (3%) ‘Unexplained’ 2%

Fornes and Lecomte 200375

France

31 sudden deaths during sport, 29 males, 2 females aged 7–60 (mean 30) years

Cardiomyopathy 10 Coronary atheroma 9

Henriques de Gouveia et al. 200376

The Netherlands

11 sudden deaths from coronary heart disease in patients aged 24–35 years. No history of heart disease

Nine plaque erosions and two claque ruptures. Histology and immunohistochemistry suggested that thrombus was fresh in only three cases

Doolan et al. 200477

Australia

193 SCDs in patients aged 75% with or without healed myocardial infarction

Minor anomalies of the coronary arteries from the aorta (RCA from the left sinus, LCA from the right without inter-arterial course, high take-off from the tubular portion, LCx originating from the right sinus or RCA, coronary ostia plication, fibromuscular dysplasia, intramural small vessel disease)

Haemopericardium due to aortic or cardiac rupture

Anomalous origin of the LCA from the right sinus and inter-arterial course

Intra-myocardial course of a coronary artery (myocardial bridge)

Mitral valve papillary muscle or chordae tendineae rupture with acute mitral valve incompetence and pulmonary edema

Cardiomyopathies (hypertrophic, arrhythmogenic right ventricular, dilated, others)

Focal myocarditis, hypertensive heart disease, idiopathic left ventricular hypertrophy

Acute coronary occlusion due to thrombosis, dissection or embolism

Myxoid degeneration of the mitral valve with prolapse, with atrial dilatation or left ventricular hypertrophy and intact chordae

Myxoid degeneration of the mitral valve with prolapse, without atrial dilatation or left ventricular hypertrophy and intact chordae

Anomalous origin of the coronary artery from the pulmonary trunk

Aortic stenosis with left ventricular hypertrophy

Dystrophic calcification of the membranous septum (±mitral annulus/aortic valve)

Neoplasm/thrombus obstructing the valve orifice

ECG documented ventricular pre-excitation (Wolff– Parkinson–White syndrome, Lown Ganong Levine syndrome)

Atrial septum lipoma

Thrombotic block of the valve prosthesis

ECG documented sinoatrial or AV block

AV node cystic tumor without ECG evidence of AV block, conducting system disease without ECG documentation

Laceration/dehiscence/poppet escape of the valve prosthesis with acute valve incompetence

Congenital heart diseases, operated

Congenital heart diseases, un-operated with or without Eisenmenger syndrome

Massive acute myocarditis   AV atrioventricular; ECG electrocardiogram; LCA left coronary artery; LCx left circumflex branch; RCA right coronary artery (SOURCE: Data from Basso C et al. [23])

7.7 Conclusions Sudden and unexpected cardiac death frequently represents one the most challenging task faced by the forensic pathologist, especially with regard to the difficulties encountered in determining the precise cause of death. The progress in autopsy diagnosis of SCD depends on the death scene investigation, quality of autopsies, which is strictly linked to the use of a rigorous protocol in

collecting essential biological samples or in dissection procedures, and on the use of complementary techniques, especially histology, toxicology, and molecular biology. In other words, SCD scene investigation requires a careful interrogation of witnesses, family members, and physicians of the rescue team who eventually attempted the resuscitation. Recent symptoms before death and past medical history must be sought. Prodromal symptoms are unfortunately often nonspecific, and even those

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employed to indicate ischemia (chest pain), tachyarrhythmia (palpitations), or congestive heart failure symptoms (dyspnea) can only be considered suggestive. Although the vast majority of these deaths may be ascribed to coronary atherosclerosis, there are many other potential causes of sudden cardiac death, such as cardiomyopathies, which are more frequently encountered in people aged less than 35 years. In the majority of cases, only a detailed pathologic examination of the heart, in conjunction with meaningful clinicopathologic correlation, allows the pathologist to determine the underlying disease process leading to death. When no anatomic abnormality is present at autopsy, it may be of benefit to archive DNA for genetic studies if an ionchannel disorder is suspected. In fact, recent advances in the field of molecular genetics have expanded our understanding of the etiology and classification of many of the aforementioned cardiac diseases. These new techniques not only augment our diagnostic capabilities, but also highlight the importance of molecular diagnostics in identifying new ­disease-causing mutations. Thereafter, the major challenge is faced by cardiologists who are directly involved in managing postautopsy care pathways to the relatives of the deceased, especially in identifying asymptomatic subjects at high risk of sudden death. To develop preventive strategies, such as the use of antiarrhythmic agents or implantable cardioverterdefibrillator, the incidence, causes, and circumstances surrounding sudden cardiac death must be better known, and are mainly provided by forensic pathology. Acknowledgments  This work has been supported by Fondi di Ateneo Linea D1–2008, Università Cattolica del Sacro Cuore, Rome, Italy.

References   1. Gillum RF. Sudden coronary death in the United States 1980–1985. Circulation. 1989;79:756–765   2. Myerburg RJ, Castellanos A. Cardiac arrest and sudden cardiac death. In: Braunwald E, ed. Heart disease: a textbook of cardiovascular medicine. Philadelphia, PA: Saunders; 2001:890–931   3. Zheng ZJ, Croft JB, Giles WH, Mensah GA. Sudden cardiac death in the United States, 1989 to 1998. Circulation. 2001; 104:2158–2163   4. Becker LB, Smith DW. Rhodes KV Incidence of cardiac arrest: a neglected factor in evaluating survival rates. Ann Emerg Med. 1993;22:86–91

A. Oliva and V. L. Pascali   5. Priori SG, Aliot E, Blomstrom-Lundqvist C, et al. Task force on sudden cardiac death of the European Society of Cardiology. Eur Heart J. 2001;22:1374–1450   6. Corrado D, Basso C, Pavei A, et al. Trends in sudden cardiovascular death in young competitive athletes after implementation of a preparticipation screening program. JAMA. 2006;296:1593–1601   7. Goldstein S. The necessity of a uniform definition of sudden coronary death: witnessed death within 1 hour of the onset of acute symptoms. Am Heart J. 1982;103:156–159   8. Virmani R, Burke AP, Farb A. Sudden cardiac death. Cardiovasc Pathol. 2001;10:211–218   9. Basso C, Calabrese F, Corrado D, et al. Postmortem ­diagnosis in sudden cardiac death victims: macroscopic, microscopic and molecular findings. Cardiovasc Res. 2001;50: 290–330 10. Brinkmann B. Harmonization of medico-legal autopsy rules. Committee of Ministers. Council of Europe. Int J Legal Med. 1999;113:1–14 11. Davies MJ. The investigation of sudden cardiac death. Histopathology. 1999;34:93–98 12. Royal College of Pathologists. Guidelines on autopsy practice 2005, scenario 1: sudden death with likely cardiac pathology. 2005: 1–7. http://www.rcpath.org/index.asp?PageID=687 13. Sheppard M, Davies MJ. Investigation of sudden cardiac death. In: Sheppard M, Davies MJ, eds. Practical cardiovascular pathology. London: Arnold; 1998:191–204 14. Thiene G, Basso C, Corrado D. Cardiovascular causes of sudden death. In: Silver MD, Gotlieb AI, Schoen FJ, eds. Cardiovascular pathology. Philadelphia, PA: Churchill Livingstone; 2001:326–374 15. Behr E, Wood DA, Wright M, et  al. Cardiological assessment of first-degree relatives in sudden arrhythmic death syndrome. Lancet. 2003;362:1457 16. Leach IH, Blundell JW, Rowley JM, et al. Acute ischaemic lesions in death due to ischaemic heart disease: an autopsy study of 333 out of hospital deaths. Eur Heart J. 1995;16: 1181–1185 17. Burke AP, Farb A, Malcolm GT, et al. Coronary risk factor and plaque morphology in men with coronary disease who died suddenly. N Engl J Med. 1997;336:1276–1282 18. Chase DL. Ph.D. thesis. Southampton: University of Southampton; 2006 19. Bowker TJ, Wood DA, Davies MJ, et al. Sudden, unexpected cardiac or unexplained death in England: a national survey. Quart J Med. 2003;96:269–279 20. Fabre A, Sheppard MN. Sudden adult death syndrome an other non-ischaemic causes of sudden cardiac death. Heart. 2006;92:316–320 21. Cohle SD, Sampson BA. The negative autopsy. Sudden cardiac death or other. Cardiovasc Pathol 2001;10:271–4 22. Finkbeiner WE, Ursell PC, Davis RL. Basic post-mortem examination in autopsy pathology. A Manual and Atlas. Philadelphia, PA: Churchill Livingstone; 2004:41–65 23. Basso C, Burke M, Fornes P, et al. Guidelines for autopsy investigation of sudden cardiac death. Virchows Arch. 2008 Jan;452(1):11–18. Epub 2007 Oct 20 24. Saukko P, Knight B. The pathology of sudden death. In: Knight’s Forensic Pathology. 3rd ed. London: Edward Arnold; 2004:492–526 25. Kitzman DW, Scholz DG, Hagen PT, et  al. Age-related changes in normal human hearts during the first 10 decades

7  Sudden Cardiac Death in Forensic Pathology of life. Part II (maturity): a quantitative anatomic study of 765 specimens from subjects 20 to 99 years old. Mayo Clin Proc. 1988;63:137–146 26. Scholz DG, Kitzman DW, Hagen PT, et  al.: Age-related changes in normal human hearts during the first 10 decades of life. Part I (growth): a quantitative anatomic study of 200 specimens from subjects from birth to 19 years old. Mayo Clin Proc. 1988;63:126–136 27. Schulz DM, Giordano DA. Hearts of infants and children: weights and measurements. Arch Pathol. 1962;73:464–471 28. Medical Devices Agency Safety Notice 2002(35) Removal of implantable cardioverter defibrillators (ICDs). 2002. http://www.mhra.gov.uk/home/idcplg?IdcService= SS_GET_PAGE&useSecondary= true&ssDocName=CON0 08731&ssTargetNodeId=420 (pp 1–3) 29. SOFT and AAFS. Forensic toxicology laboratory guidelines. 2002:1–23. www.soft-tox.org/docs/Guidelines.2002. final.pdf 30. Carturan E, Tester DJ, Brost BB, et al. Postmortem genetic testing for conventional autopsy negative sudden unexplained death: an evaluation of different DNA extraction protocols and the feasibility of mutational analysis from archival paraffin embedded heart tissue. Am J Clin Pathol. 2008 Mar;129(3):391–397 31. Chugh SS, Senashova O, Watts A, et al. Postmortem molecular screening in unexplained sudden death. J Am Coll Cardiol. 2004;43:1625–1629 32. Tester DJ. Ackerman MJ The role of molecular autopsy in unexplained sudden cardiac death. Curr Opin Cardiol. 2006;21:166–172 33. Kannel WB, Cupples LA, D’Agostino RB. Sudden death risk in overt coronary heart disease: the Framingham Study. Am Heart J. 1987;113:799–804 34. Zipes DP, Wellens HJJ. Sudden cardiac death. Circulation. 1998;98:2334–2351 35. Weaver WD, Lorch GS, Alvarez HA, et  al. Angiographic findings and prognostic indicators in patients resuscitated from sudden cardiac death. Circulation. 1976;54:895–900 36. Perper JA, Kuller LH, Cooper M. Arteriosclerosis of coronary arteries in sudden unexpected deaths. Circulation. 1975;52(Suppl 6):III27–III33 37. Theroux P, Fuster V. Acute coronary syndromes: unstable angina and non-Q-wave myocardial infarction. Circulation. 1998;97:1195–1206 38. Huikuri HV, Castellanos A, Myerburg RJ. Sudden death due to cardiac arrhythmias. N Engl J Med. 2001;345:1473–1482 39. Basso C, Corrado D, Thiene G. Congenital coronary artery anomalies as an important cause of sudden death in the young. Cardiol Rev. 2001;9:312–317 40. Schwartz PJ, La Rovere MT, Vanoli E. Autonomic nervous system and sudden cardiac death: experimental basis and clinical observations for post-myocardial infarction risk stratification. Circulation. 1992;85(Suppl I):I77–I91 41. Cittadini F, Oliva A, Arena V, et  al. Sudden cardiac death associated with a coronary artery anomaly considered benign. Int J Cardiol. 2008. In press 42. Corrado D, Thiene G, Cocco P, et  al. Non-atherosclerotic coronary artery disease and sudden death in the young. Br Heart J. 1992;68:601–607 43. Richardson P, McKenna W, Bristow M, et al. Report of the 1995 World Health Organization/International Society and

109 Federation of Cardiology Task Force on the Definition and Classification of cardiomyopathies. Circulation. 1996;93: 841–842 44. Codd MB, Sugrue DD, Gersh BJ, et  al. Epidemiology of idiopathic dilated and hypertrophic cardiomyopathy. A population-based study in Olmsted County, Minnesota, 1975– 1984. Circulation. 1989;80(3):564–572 45. Roberts WC, McAllister HA Jr, Ferrans VJ. Sarcoidosis o the heart. A clinicopathologic study of 35 necropsy patients (group 1) and review of 78 previously described necropsy patients (group 11). Am J Med. 1977;63:86–108 46. Moolman JC, Corfield VA, Posen B, et al. Sudden death due to troponin T mutations. J Am Coll Cardiol. 1997;29:549–555 47. Maron BJ, Anan TJ, Roberts WC. Quantitative analysis of the distribution of cardiac muscle cell disorganization in the left ventricular wall of patients with hypertrophic cardiomyopathy. Circulation. 1981;63:882–894 48. Scheffold T, Binner P, Erdmann J, et al. Hypertrophic cardiomyopathy. Herz. 2005;30:550–557 49. Ackerman MJ, VanDriest SL, Ommen SR, et al. Prevalence and age-dependence of malignant mutations in the beta-myosin heavy chain and troponin T genes in hypertrophic cardiomyopathy: a comprehensive outpatient perspective. J Am Coll Cardiol. 2002;39:2042–2048 50. Nava A, Thiene G, Canciani B, et al. Familial occurrence of right ventricular dysplasia: a study involving nine families. J Am Coll Cardiol. 1988;12:1222–1228 51. Corrado D, Basso C, Thiene G, et al. Spectrum of clinicopathologic manifestations of arrhythmogenic right ventricular cardiomyopathy/dysplasia: a multicenter study. J Am Coll Cardiol. 1997;30:1512–1520 52. De Pasquale CG, Heddle WF. Left sided arrhythmogenic ventricular dysplasia in siblings. Heart. 2001;86:128–130 53. Gallo P, d’Amati G, Pelliccia F. Pathologic evidence of extensive left ventricular involvement in arrhythmogenic right ventricular cardiomyopathy. Hum Pathol. 1992;23: 948–952 54. Burke A, Mont E, Kutys R, et al. Left ventricular noncompaction: a pathological study of 14 cases. Hum Pathol. 2005; 36:403–411 55. Norman M, Simpson M, Mogensen J, et al. Novel mutation in desmoplakin causes arrhythmogenic left ventricular cardiomyopathy. Circulation. 2005;112:636–642 56. Oechslin EN, Attenhofer Jost CH, Rojas JR, et al. Long-term follow-up of 34 adults with isolated left ventricular noncompaction: a distinct cardiomyopathy with poor prognosis. J Am Coll Cardiol. 2000;36:493–500 57. Ladich E, Virmani R, Burke A. Sudden cardiac death not related to coronary atherosclerosis. Toxicol Pathol. 2006; 34(1):52–57 58. Martin AB, Webber S, Fricker FJ, et al. Acute myocarditis. Rapid diagnosis by PCR in children. Circulation. 1994;90: 330–339 59. Litovsky SH, Burke AP, Virmani R. Giant cell myocarditis: an entity distinct from sarcoidosis characterized by multiphasic myocyte destruction by cytotoxic T cells and histiocytic giant cells. Mod Pathos. 1996;9:1126–1134 60. Roberts WC, McAllister HA Jr, Ferrans VJ. Sarcoidosis of the heart. A clinicopathologic study of 35 necropsy patients (group 1) and review of 78 previously described necropsy patients (group 11). Am J Med. 1977:63:86–108 61. Liberthson RR. Sudden death from cardiac causes in children and young adults. N Engl J Med. 1996;334:1039–1044

110 62. Oliva A, Pascali VL, Hong K, Brugada R. Molecular autopsy of sudden cardiac death (SCD): the challenge of forensic pathologist to the complexity of genomics. Am J Forensic Med Pathol. 2005;26:369–370 63. Oliva A, D’Aloja E, Pascali VL. Focussing on hard science in forensic medicine: genetics of sudden cardiac death (SCD). Forensic Sci Int. 2007 Oct 25;172(2–3):e2–3 64. Tester DJ, Spoon DB, Valdivia HH, et  al. Targeted mutational analysis of the RyR2-encoded cardiac ryanodine receptor in sudden unexplained death: a molecular autopsy of 49 medical examiner/coroner’s cases. Mayo Clin Proc. 2004;79: 1380–1384 65. Maron BJ, Shirani J, Poliac LC, et al. Sudden death in young competitive athletes: clinical, demographic, and pathological profiles. JAMA. 1996;276:199–204 66. Puranik R, Chow CK, Duflou JA, et al. Sudden death in the young. Heart Rhythm. 2005;2:1277–1282 67. Corrado D, Basso C, Thiene G. Sudden cardiac death in young people with apparently normal heart. Cardiovasc Res. 2001;50:399–408 68. Eckart RE, Scoville SL, Campbell CL, et al. Sudden death in young adults: a 25-year review of autopsies in military recruits. Ann Intern Med. 2004;141:829–834 69. Gallagher PJ. The pathologic investigation of sudden death. Curr Diagn Pathol. 2007;13:366–374

A. Oliva and V. L. Pascali 70. Leach IH, Blundell JW, Rowley JM, Turner DR. Acute ischaemic lesions in death due to ischaemic heart disease: an autopsy study of 333 out of hospital deaths. Eur Heart J. 1995;16:1181–1185 71. Chugh SS, Kelley KL, Titus JL. Sudden cardiac death with apparently normal heart. Circulation. 2000;102:649–654 72. Di Gioia C, Autore C, Romeo D, et al. Sudden cardiac death in younger adults: autopsy diagnosis as a tool for preventive medicine. Hum Pathol. 2006;37:794–801 73. Wren C, O’Sullivan JJ, Wright C. Sudden death in children and adolescents. Heart. 2000;84:410–413 74. Maron BJ. Sudden death in young athletes. N Engl J Med. 2003;349:1064–1075 75. Fornes P, Lecompte D. Pathology of sudden death durino recreational sports activity: an autopsy study of 31 cases. Am J Foren Med Path. 2003;24:9–16 76. Henriques de Gouveia R, van der Wal AC, van der Loos CM, Becker AE. Sudden unexpected death in young adults. Discrepancies between initiation of acute plaque complications and the onset of acute coronary death. Eur Heart J. 2002;23:1433–1440 77. Doolan A, Langois N, Semsarian C. Causes of sudden death in young Australians. Med J Aust. 2004;18:110–112

Part Cardiac genetic syndromes

III

8

Genetic Studies Marie-Pierre Dubé and John Rioux

8.1 Introduction The human genome consists of 3.3 billion base pairs of DNA encoding 20–30 thousand genes in the genome of every individual nucleated cell of the human body. Numerous DNA base-pair differences are observed when comparing the genome of any two individuals. Genetic variation can take different forms, but the most common variation is that of the single nucleotide polymorphism (SNP; pronounced “snip”). Single nucleotide polymorphisms (SNPs) occur in both coding and noncoding sequences at a frequency of approximately 1 per 300 base pairs, totaling approximately 10,000,000 SNPs in the human genome. Although the majority of SNPs are believed not to have a direct physiological outcome, most disease-causing mutations identified to date are of this type than other types of chromosomal changes. According to The Human Gene Mutation Database (HGMD),1 which assembles published genetic lesions responsible for human inherited disease, missense and nonsense mutations (SNPs in protein-coding regions) are responsible for 48,343 of the 85,558 (57%) mutations listed in the database, followed by small deletions (17%), splicing mutations (10%), and small insertions (7%). Large deletions and insertions and more complex chromosomal mutations account for less than 9% of disease-causing mutations.

M.-P. Dubé (*) Department of medicine, Montreal Heart Institute Research Center, and Université de Montréal, 5000, Bélanger, Montreal, QC, Canada H1T1C8 e-mail: [email protected]

Traditionally, genetic traits have been categorized as monogenic or polygenic. In a monogenic trait, the phenotype observed can be explained by variations in a single gene, and their transmission patterns are usually easily traceable within families. Marfan syndrome, Holt-Oram syndrome, DiGeorge syndrome, and sickle-cell disease are examples of monogenic disorders. Polygenic traits, on the other hand, are expressed through the interaction of several genes and can be modulated by environmental influences and thus are commonly named complex genetic traits. Many complex disorders exist, such as inflammatory bowel diseases, cardiovascular diseases, and diabetes. Cardiovascular diseases are among the most prevalent complex disorders. Medical genetic research has had substantial success in finding genes involved in the etiology of rare monogenic diseases with the use of linkage analysis and positional cloning. Nearly 1,500 disease genes have been associated with monogenic diseases mostly by the identification of rare, high-risk mutations.1 Polygenic traits, on the other hand, have proved more difficult to study using familial data. These are often referred to as complex genetic diseases due to the diversity of factors contributing to disease occurrence, including multiple environmental and genetic elements. Examples of complex diseases include type II diabetes, coronary artery disease, and several congenital heart diseases. Until 2006, the vast majority of disease genes for complex genetic traits had been identified by association studies of candidate genes or by association mapping of linkage regions. More recently, the development of tools which test hundreds of thousands or more SNPs in parallel have enabled genome-wide association (GWA) studies. These GWA studies have dramatically changed our ability to identify genetic risk factors for complex human traits.

R. Brugada et al. (eds.), Clinical Approach to Sudden Cardiac Death Syndromes, DOI: 10.1007/978-1-84882-927-5_8, © Springer-Verlag London Limited 2010

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8.2 Genetic Determinants of Disease The first step in the study of potentially genetic diseases is to assess whether the disease clusters in families. Familial resemblance between family members that is stronger than that of unrelated pairs of individuals is a common hallmark of genetic etiology. The extent of familial resemblance is generally measured by using correlation statistics between pairs of relatives. Maximum likelihood procedures can be used to estimate the familial correlations2 and hypotheses can be tested by using a likelihood ratio test. In a simple nuclear family for instance, one can evaluate correlations between father-son, father-daughter, fathermother, mother-son, mother-daughter, son-daughter, son-son, and daughter-daughter. One can test whether the correlations are different from zero, or there are sex-specific correlations. Familial resemblance, however, can be the result of shared genes, environment, or both, and means to distinguish the different sources of relatedness between family members are necessary.3,4 Furthermore, the accuracy and reliability with which a trait is measured can have a considerable effect on the correlation estimates. Heritability is one of the fundamental concepts in genetics. When estimated in extended pedigrees, it allows for the estimation of the genetic heritability without the effects due to shared environment. Classically, heritability is intended to represent the proportion of phenotypic variance that is due to additive genetic effects and generalized heritability represents the proportion of variance that is due to all additive effects including familiarity due to shared environment effects. It should be noted that heritability is not an absolute measurement, and heritability estimates are specific to a given population. Twins provide a simple means of estimating heritability by comparing monozygotic twin pairs which share 100% of their genetic complement to dizygotic twin pairs which share on average 50% of their genetic complement. According to Falconer’s formula, heritability is estimated as h2 > 2(rmz−rdz), where rmz and rdz are the twin correlations.5 Assuming that the shared environment of dizygotic and monozygotic twins is comparable, the difference in correlations can be attributed to genetic effects; if on the other hand, the shared environment is greater for monozygotic twins, then heritability would be overestimated. Adoption studies have been used to

M.-P. Dubé and J. Rioux

estimate heritability while distinguishing genetic from cultural familial effects. It is assumed that that the correlation between an adopted child and the biological parents is due to genetic effects only, while that between the child and adoptive parents is due to familial environmental effects only.6 Extended pedigrees offer the advantage of comparing family members of a variety of relationships and of different degrees, which are less likely to share environmental influences. Another method for the assessment of the genetic component of disease relies on a relative risk ratio involving disease risk in family members. This approach shares parallels with relative risk estimates used when comparing exposed vs. unexposed in classical cohort studies, but they should not be confused with each other. In genetics, we seek to determine the risk to relatives of an individual afflicted with a disease which is regrettably sometimes referred to as the “relative risk” but should rather be referred to as “the risk to relatives” or “recurrence risk” for the sake of clarity. The risk to relatives is commonly compared to the population prevalence risk in a ratio that is referred to as the “recurrence risk ratio” lR,7 where R can stand for different classes of relatives such as siblings (S), offspring (O), and so on. If lR is significantly greater than 1, then one can infer that familial factors including genes explain a greater fraction of the risk than the population prevalence risk and can accordingly be recognized as heritable. The recurrence risk ratio for aortic valve sclerosis, for example, was estimated at 2.31 (1.72–3.11) in a cohort of hypertensive siblings.8

8.3 Mendelian Traits Single-gene traits are often referred to as Mendelian for their shared characteristics with the Gregor Mendel’s study of garden variety peas. Mendelian diseases are classically characterized by their patterns of transmission in families. Familial pedigrees provide an essential tool for genetic research and for the practical application of genetic knowledge into clinical care. The pedigree depicts in a diagram, a convenient single view of multiple generations, illustrating the number of affected relatives, the transmission patterns, and the sex of transmitting individuals (Fig.  8.1). It is, however, not always possible to reach a simple definitive solution to the mode of disease transmission because

8  Genetic Studies

a

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b

Fig. 8.1  Diagram of pedigrees depicting the disease status of family members. Squares represent males, circles females; centered horizontal lines represent a parental union, vertical lines link to descendents, and superior horizontal lines represent sibships. Darkened symbols depict affected individuals and clear symbols unaffected individuals. (a) A dominantly transmitted trait; (b) a recessive trait

of small family sizes, limited information about family history, or modifiers of disease gene penetrance. A dominant trait transmission is the easiest to recognize; it is transmitted at every generation with a probability of 1/2 in the children of a couple consisting of a single affected parent, and will afflict both sexes equally (Fig. 8.1a).There is a 25 % chance that a recessive trait will occur in children of parents who are both unaffected carriers of the responsible genetic mutation. Recessive traits tend to surface in children of consanguineous parents (Fig.  8.1b). Mutations in genes located on the X chromosome display a sex-linked inheritance pattern. Alternatively, transmissions involving chromosomes other than the X and Y chromosomes are labeled autosomal transmissions. As males carry only one X chromosome, they tend to be more susceptible to X-linked genetic disorders than females, who have two copies with a chance of being protected from full disease expression when heterozygous for the mutation in question. Father-son transmission patterns are not possible in X-linked inheritance as the father will obligatorily transmit a Y chromosome to his sons. Penetrance and expressivity are important aspects of pedigree analysis. Penetrance can be reduced or age-dependent. For example, hypertrophic cardiomyopathy shows age-dependent penetrance, with approximately 95% of individuals with a predisposing genotype affected by age 50–60 years. Low penetrance has been reported for specific long Q-T syndrome

mutations. Because of the reduced and age-dependent penetrance observed in these disorders, it is important to identify carriers of the mutation because they can transmit the disease regardless of their phenotype. A wide range in severity of symptoms can also occur which can be explained by genetic and environmental modifying factors. For example, multilocus mutations and double heterozygosity are associated with earlier onset, severe forms of long QT syndrome, and hypertrophic cardiomyopathy, respectively.9,10

8.4 Genetic Linkage Studies Linkage analysis aims to detect the cosegregation of a chromosomal segment with a phenotype of interest in a set of related patients such as a family unit.11,12 The approach is ideally suited for the analysis of Mendelian traits and aims to test whether any particular chromosome segment in the genome cosegregates with the phenotype in a pedigree more frequently than one would expect by chance alone. These tests are traditionally broadly subdivided into two main categories: those in which explicit modeling assumptions are made concerning the behavior of a presumptive causal allele, and those in which no such assumptions are made. These are termed parametric (or model-based) and nonparametric (or model-free) analysis respectively. In model-based analysis, assumptions are made about the disease gene population frequency and the penetrance of the disease alleles in homozygote and heterozygote carriers. When the mode of action of the disease gene cannot be predicted with confidence, as is the case for more complex diseases, model-free analyses are typically used. Generally, these simply test for excess sharing or preferential transmission of particular marker alleles in family units. The most commonly used statistics for model-based linkage analysis is the maximum likelihood ratio. This tests the hypothesis of disease and marker cosegregation vs. the null hypothesis of random segregation. For historical reasons of convenience, the base 10 logarithm of the ratio of the likelihoods is used and referred to as the LOD score (log of odds).13 The conventional significance threshold used in linkage analysis is LOD³3 for Mendelian diseases. The genome-wide significance threshold is sometimes set higher to LOD > 3.3 for complex trait analysis.14 Linkage analysis can

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proceed using a single genetic marker at a time (twopoint linkage, that is disease locus and marker locus), or alternatively using multiple genetic markers simultaneously (multipoint linkage). Multipoint analysis provides phasing information that adds precision and accuracy to the linkage evidence and to the location estimate of the disease gene, provided that the prespecified marker map is accurate for the data at hand. Exact solutions of multipoint linkage, however, are incomputable for very large pedigrees or marker sets, in which case Markov Chain Monte Carlo approximation methods can be used. Haplotype reconstruction of phased alleles over regions of interest is a widely used procedure that allows for manual review of linkage analysis results. Phasing of alleles refers to the assignment of the two alleles of each marker to either the paternal or maternal chromosome. In monogenic as well as complex disorders, mutations in different genes can result in a similar phenotype, so that groups of families displaying a shared phenotype may not segregate a causal variant in the same gene (genetic or locus heterogeneity). Care must be taken, therefore, when pooling pedigrees for linkage analysis. It may be possible, in some instances, to subgroup pedigrees according to subtle phenotypic differences. Alternatively, robust statistical analyses that allow for locus heterogeneity in the calculation of heterogeneity LOD scores (hLOD) can be used. Alternatively, different families may segregate different mutations in the same gene for a given phenotype (allelic heterogeneity). In this case, different families will generate linkage to the same chromosomal interval although not sharing the same marker haplotype. In special cases such as French Canada, Newfoundland, Finland, etc., identical chromosomal segments or haplotypes can often be detected in different family units whose genealogical relationship may not be known.15-17 Such populations are frequently referred to as founder populations or population isolates.

8.5 Genetic Association Studies for Complex Traits GWA studies have revolutionized human genetics by providing a powerful approach for the identification of genetic variants associated with common diseases and complex traits. Compared to candidate gene-based

M.-P. Dubé and J. Rioux

genetic association studies where only a fraction of the genome is surveyed, GWA studies offer the possibility to analyze common genetic variation across the whole genome without a priori assumptions about the expected location. The method relies on testing association between genetic markers such as SNPs and a disease status or other qualitative or quantitative phenotypes. Hundreds of thousands of SNPs covering the entire genome are used. The approach is dependent on the expectation that the underlying disease mutation will be correlated (in linkage disequilibrium) with one or a few of the SNPs being tested with sufficient strength to be detectable. The advent of GWA studies was made possible by the development of better genotyping platforms18 and the creation of a large catalog of common DNA polymorphisms in the human genome across three ethnic groups (The HapMap Project; http://www.hapmap.org/).19,20 Although GWAS are powerful discovery tools, they are limited in the spectrum of genetic variation that they can survey. Genomewide genotyping arrays were designed with the goal to capture common SNPs, without consideration for the rarer variants and other types of possible structural variations. New technologies, in particular nextgeneration DNA sequencers may in a not-so-distant future allow geneticists to comprehensively survey common, rare, and structural genetic variation in wellcharacterized DNA samples. The success in GWA studies has been seen in nearly all complex human phenotypes, both continuous and discrete traits. The number of confirmed genetic risk factors found by GWAS has gotten too long to list in a short text, and is practically kept updated in a database. The public database of the National Human Genome Research Institute (http://www.genome.gov/gwastudies/) currently lists 191 published GWA studies that have identified 412 novel SNPs (i.e., not previously identified by non GWA approaches) that have p-values 480

3

460–470

2

450 (in males)

1

Torsades de pointesb

2

T-wave alternant

1

Notched T-wave in three leads

1

Low heart rate for agec

0.5

Clinical history Syncopeb With stress

2

Without stress

1

Congenital deafness

0.5

Family history Family members with definite LQTS

1

Unexplained sudden cardiac death (SCD) 0.5 in immediate family members 500 at heart rates 500 ms, congenital deafness, syncope, ventricular arrhythmias, family hx of scd, female gender, and medical noncompliance after the event. Different levels of severity can be defined by compiling these data:59

9.10 Management Strategies

• Higher risk: Hx of aborted SCD or documented torsades de pointes. • Intermediate risk: Syncope or QTc>500. • Lower risk: QTc 0.018)

of the high-dose statin strategy, with patients carrying the 719Arg allele deriving the greatest benefit.134 Hence, the KIF6 Trp719Arg genetic polymorphism represents another candidate marker to select patients who will benefit the most from statin therapy. The major question regarding this gene is that its role in cardiovascular diseases is currently uncertain and thus, it is difficult to exactly explain from a physiological perspective regarding how it modulates the cardiovascular risks or benefits of statins.

21.6 Impact of Nongenetic Factors on Associations Between Genotypes and Phenotypes In complex genetics such as pharmacogenomics, nongenetic factors can significantly influence the associations between genotypes and phenotypes. Indeed, ignoring these factors can minimize or completely blur the genetic associations in cardiovascular diseases.135 These factors include, but are not limited to, the disease treated, comorbidities, drug interactions, dietary components, and other lifestyle differences.

The disease for which an agent is used may affect the impact of a genotype on a given phenotype. For example, the hypotensive effect of the ARB candesartan greatly differs between patients with prehypertension,136 hypertension,137 and HF.138 This could be attributed in part to the differences in RAAS activation among these patients, in addition to the hemodynamic and myocardial abnormalities that are the characteristics of the patients with HF.139-144 Hence, the strength of associations between candidate genetic variants and blood pressure reductions may differ among individuals presenting these different conditions, or even for a given individual in his/her lifetime. Comorbidities can also have a significant impact on the phenotypes studied, and thus, the genetic association studies. For example, diabetes and renal dysfunction are known risk factors for RAAS inhibitor-induced hyperkalemia.145

21.6.2 Drug Interactions Drug interactions may be another confounding factor in many pharmacogenomic studies. Indeed, the use of inhibitors of the selected CYPs can modify a phenotype from a rapid metabolizer to a slow metabolizer.146 Pharmacodynamic drug interactions should not be ignored as well. For example, concomitant antiplatelet therapy in patients treated with warfarin significantly increases the risk of bleeding, possibly masking the genetic associations or resulting in false positives.147

21.6.3 Life Habits Life habits are potentially important confounding factors that have been largely ignored in pharmacogenomic studies. Tobacco, for example, is a powerful inducer of CYP1A2 activity and smoking status has been shown to modify the pharmacokinetics of numerous drugs metabolized by this isoenzyme, such as theophylline, clozapine, and possibly, warfarin.148,149

282

Diet is another nongenetic confounder that is extremely difficult to quantify, and therefore, to control in pharmacogenomics studies. The impact of vitamin K consumption on warfarin dosing requirements has been previously discussed. Sodium consumption is an important dietary factor that influences blood pressure and therefore, possibly the response to antihypertensive agents.150 Data from the EPOGH investigators and others have shown that sodium excretion, a surrogate marker of sodium intake, is a powerful modulator of the relationship between cardiovascular phenotypes and candidate genes.135,151-153 The authors demonstrated that when the interaction between sodium excretion and genotypes was not considered, some associations between the genotypes and the phenotypes were not apparent.

21.7 Pharmacogenomics: Hope or Hype? The hope for personalized medicine generated by pharmacogenomics has recently faced some skepticism, because many associations have not been replicated in subsequent studies. Indeed, the road to individualized medicine is a long and tortuous one. This, of course, by no means should imply that it is a road not worth exploring and using. These inconsistencies between the studies can be attributed to a number of factors such as limited statistical power, poorly phenotyped individuals, or ignoring nongenetic factors. Hence, future efforts should address and correct these shortcomings to fulfill the promise of pharmacogenomics to give the right drug, at the right dose, to the right patient at the right time.

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S. de Denus et al. in the Women’s Health Study. J Am Coll Cardiol. 2008; 51(4):444–448 132. Shiffman D, O’Meara ES, Bare LA, et al. Association of gene variants with incident myocardial infarction in the Cardiovascular Health Study. Arterioscler Thromb Vasc Biol. 2008;28(1):173–179 133. Iakoubova OA, Tong CH, Rowland CM, et al. Association of the Trp719Arg polymorphism in kinesin-like protein 6 with myocardial infarction and coronary heart disease in 2 prospective trials: the CARE and WOSCOPS trials. J Am Coll Cardiol. 2008;51(4):435–443 134. Iakoubova OA, Sabatine MS, Rowland CM, et  al. Polymorphism in KIF6 gene and benefit from statins after acute coronary syndromes: results from the PROVE IT-TIMI 22 study. J Am Coll Cardiol. 2008;51(4):449–455 135. Stolarz K, Staessen JA, Kawecka-Jaszcz K, et al. Genetic variation in CYP11B2 and AT1R influences heart rate variability conditional on sodium excretion. Hypertension. 2004;44(2):156–162 136. Julius S, Nesbitt SD, Egan BM, et al. Feasibility of treating prehypertension with an angiotensin-receptor blocker. N Engl J Med. 2006;354(16):1685–1697 137. McClellan KJ, Goa KL. Candesartan cilexetil. A review of its use in essential hypertension. Drugs. 1998;56(5): 847–869 138. Granger CB, McMurray JJ, Yusuf S, et al. Effects of candesartan in patients with chronic heart failure and reduced left-ventricular systolic function intolerant to angiotensinconverting-enzyme inhibitors: the CHARM-Alternative trial. Lancet. 2003;362(9386):772–776 139. Danser AH, van Kesteren CA, Bax WA, et  al. Prorenin, renin, angiotensinogen, and angiotensin-converting enzyme in normal and failing human hearts. Evidence for renin binding. Circulation. 1997;96(1):220–226 140. Zisman LS, Asano K, Dutcher DL, et al. Differential regulation of cardiac angiotensin converting enzyme binding sites and AT1 receptor density in the failing human heart. Circulation. 1998;98(17):1735–1741 141. Matsubara H. Renin-angiotensin system in human failing hearts: message from nonmyocyte cells to myocytes. Circ Res. 2001;88(9):861–863 142. Serneri GG, Boddi M, Cecioni I, et al. Cardiac angiotensin II formation in the clinical course of heart failure and its relationship with left ventricular function. Circ Res. 2001;88(9):961–968 143. Pieruzzi F, Abassi ZA, Keiser HR. Expression of reninangiotensin system components in the heart, kidneys, and lungs of rats with experimental heart failure. Circulation. 1995;92(10):3105–3112 144. Yoshimura M, Nakamura S, Ito T, et  al. Expression of aldosterone synthase gene in failing human heart: quantitative analysis using modified real-time polymerase chain reaction. J Clin Endocrinol Metab. 2002;87(8):3936–3940 145. de Denus S, Tardif JC, White M, et al. Quantification of the risk and predictors of hyperkalemia in patients with left ventricular dysfunction: a retrospective analysis of the Studies of Left Ventricular Dysfunction (SOLVD) trials. Am Heart J. 2006;152(4):705–712 146. Hamelin BA, Bouayad A, Methot J, et al. Significant interaction between the nonprescription antihistamine diphen-

21  Pharmacogenomics hydramine and the CYP2D6 substrate metoprolol in healthy men with high or low CYP2D6 activity. Clin Pharmacol Ther. 2000;67(5):466–477 147. Johnson SG, Rogers K, Delate T, et al. Outcomes associated with combined antiplatelet and anticoagulant therapy. Chest. 2008;133(4):948–954 148. Kroon LA. Drug interactions with smoking. Am J Health Syst Pharm. 2007;64(18):1917–1921 149. Millican EA, Lenzini PA, Milligan PE, et al. Genetic-based dosing in orthopedic patients beginning warfarin therapy. Blood. 2007;110(5):1511–1515 150. Dickinson BD, Havas S. Reducing the population burden of cardiovascular disease by reducing sodium intake: a report of the Council on Science and Public Health. Arch Intern Med. 2007;167(14):1460–1468 151. Kuznetsova T, Staessen JA, Thijs L, et al. Left ventricular mass in relation to genetic variation in angiotensin II receptors, renin system genes, and sodium excretion. Circulation. 2004;110(17):2644–2650 152. Wojciechowska W, Staessen JA, Stolarz K, et al. Association of peripheral and central arterial wave reflections with the CYP11B2–344C allele and sodium excretion. J Hypertens. 2004;22(12):2311–2319 153. Kuznetsova T, Staessen JA, Brand E, et al. Sodium excretion as a modulator of genetic associations with cardiovascular phenotypes in the European Project on Genes in Hypertension. J Hypertens. 2006;24(2):235–242 154. Salazar NC, Chen J, Rockman HA. Cardiac GPCRs: GPCR signaling in healthy and failing hearts. Biochim Biophys Acta. 2007;1768(4):1006–1018 155. Schmieder RE, Hilgers KF, Schlaich MP, et  al. Reninangiotensin system and cardiovascular risk. Lancet. 2007 ;369(9568):1208–1219 156. Kirchheiner J, Schmidt H, Tzvetkov MK, et  al. Pharmacokinetics of codeine and its metabolite morphine in ultra-rapid metabolizers due to CYP2D6 duplication. Pharmacogenomics J. 2007;7(4):257–265 157. Takekuma Y, Takenaka T, Kiyokawa M, et al. Contribution of polymorphisms in UDP-glucuronosyltransferase and CYP2D6 to the individual variation in disposition of carvedilol. J Pharm Pharm Sci. 2006;9(1):101–112 158. Geisler T, Schaeffeler E, Dippon J, et  al. CYP2C19 and nongenetic factors predict poor responsiveness to clopidogrel loading dose after coronary stent implantation. Pharmacogenomics. 2008;9(9):1251–1259 159. Trenk D, Hochholzer W, Fromm MF, et  al. Cytochrome P450 2C19 681G>A polymorphism and high on-clopidogrel platelet reactivity associated with adverse 1-year clinical outcome of elective percutaneous coronary intervention with drug-eluting or bare-metal stents. J Am Coll Cardiol. 2008;51(20):1925–1934 160. Hulot JS, Bura A, Villard E, et al. Cytochrome P450 2C19 loss-of-function polymorphism is a major determinant of

287 clopidogrel responsiveness in healthy subjects. Blood. 2006;108(7):2244–2247 161. Zheng H, Webber S, Zeevi A, et al. Tacrolimus dosing in pediatric heart transplant patients is related to CYP3A5 and MDR1 gene polymorphisms. Am J Transplant. 2003;3(4): 477–483 162. Zheng H, Zeevi A, Schuetz E, et  al. Tacrolimus dosing in adult lung transplant patients is related to cytochrome P4503A5 gene polymorphism. J Clin Pharmacol. 2004;44(2): 135–140 163. Kim KA, Park PW, Lee OJ, et  al. Effect of polymorphic CYP3A5 genotype on the single-dose simvastatin pharmacokinetics in healthy subjects. J Clin Pharmacol. 2007;47(1):87–93 164. Ladero JM. Influence of polymorphic N-acetyltransferases on non-malignant spontaneous disorders and on response to drugs. Curr Drug Metab. 2008;9(6):532–537 165. Pasanen MK, Neuvonen M, Neuvonen PJ, et  al. SLCO1B1 polymorphism markedly affects the pharmacokinetics of simvastatin acid. Pharmacogenet Genomics. 2006;16(12):873–879 166. Ho RH, Choi L, Lee W, et  al. Effect of drug transporter genotypes on pravastatin disposition in European- and African-American participants. Pharmacogenet Genomics. 2007;17(8):647–656 167. Aarnoudse AJ, Dieleman JP, Visser LE, et al. Common ATPbinding cassette B1 variants are associated with increased digoxin serum concentration. Pharmacogenet Genomics. 2008;18(4):299–305 168. Beta-Blocker Evaluation of Survival Trial Investigators. A trial of the beta-blocker bucindolol in patients with advanced chronic heart failure. N Engl J Med. 2001;344(22): 1659–1667 169. Lanfear DE, Jones PG, Marsh S, et  al. Beta2-adrenergic receptor genotype and survival among patients receiving beta-blocker therapy after an acute coronary syndrome. JAMA. 2005;294(12):1526–1533 170. Donnelly LA, Doney AS, Dannfald J, et  al. A paucimorphic variant in the HMG-CoA reductase gene is associated with lipid-lowering response to statin treatment in diabetes: a GoDARTS study. Pharmacogenet Genomics. 2008;18(12): 1021–1026 171. Krauss RM, Mangravite LM, Smith JD, et al. Variation in the 3-hydroxyl-3-methylglutaryl coenzyme a reductase gene is associated with racial differences in low-density lipoprotein cholesterol response to simvastatin treatment. Circulation. 2008;117(12):1537–1544 172. Lynch AI, Boerwinkle E, Davis BR, et al. Pharmacogenetic association of the NPPA T2238C genetic variant with cardiovascular disease outcomes in patients with hypertension. JAMA. 2008;299(3):296–307 173. Cooper GM, Johnson JA, Langaee TY, et  al. A genomewide scan for common genetic variants with a large influence on warfarin maintenance dose. Blood. 2008;112(4): 1022-1027

22

Polygenic Studies in the Risk of Arrhythmias Moritz F. Sinner and Stefan Kääb

22.1 Polygenic Studies in the Risk of Arrhythmias

22.2 Common Genetic Variants as Modifiers of Arrhythmia Risk in the Context of Monogenic Diseases Research into rare genetic variants causing cardiovascular diseases in general and cardiac arrhythmias in particular has led to a tremendous accumulation of knowledge and insight into disease mechanisms within the last decade. These genetic cardiovascular disorders are commonly viewed as monogenic diseases following largely Mendelian inheritance with a variable penetrance, which accounts for the widely seen lack of strong genotype−phenotype correlation. Increasingly, research efforts focus on the role of common genetic variants, the so-called polymorphisms (or single nucleotide polymorphisms or SNPs) as modifier alleles to disease susceptibility. Historically, the initial studies on common genetic variants investigated exonic common variants in candidate genes that had been linked to arrhythmia risk by experimental data or in the context of monogenic diseases. Recently, the search for disease modifying common genetic variants has reached a more systematic approach based on public data on the human genome allowing for the systematic evaluation of larger numbers of SNPs in the genomic region of candidate genes or in the whole genome (e.g., http://www.hapmap.org, http://genome. ucsc.edu, http://snpper.chip.org or http://www.ncbi. nlm.nih.gov/sites/entrez?db > snp). M. F. Sinner (*) Ludwig-Maximilians University Klinikum Grosshadern, Medizinische Klinik und Poliklinik I, Marchioninistrasse. 15, 81377 Munich, Germany e-mail: [email protected]

Though we have learned a lot in the past decade about the primary defects and general aspects of arrhythmogenesis as well as underlying primary arrhythmia syndromes such as the congenital long QT syndromes, advances in a more specific genotype−phenotype correlation are slow. In the context of monogenic diseases, the term “modifiers” is also and importantly used for common genetic variants that account for the interindividual variability among patients harboring the same mutation. Few studies have tried to gain a deeper insight into the consequence of mutations by incorporating in their models at least another factor that may influence the phenotype.1 Baroudi et al were the first to introduce the concept that the interaction of common polymorphisms and rare mutations may exert profound effects on functional consequences. The combination of a mutation in the SCN5A gene (T1620M), known to affect channel gating, resulted in impaired protein trafficking when expressed in tsA201 cells.2 Splawski et al suggested that the polymorphism SCN5A-Y1102, which is present in 13.2% of the African-American population, is strongly associated with the development of arrhythmias, namely drug-induced long QT syndrome in the absence of a clinical phenotype of LQT3 or any other heritable arrhythmia that has been linked to mutations in the Na+ channel gene.3

R. Brugada et al. (eds.), Clinical Approach to Sudden Cardiac Death Syndromes, DOI: 10.1007/978-1-84882-927-5_22, © Springer-Verlag London Limited 2010

289

290

M. F. Sinner and S. Kääb

22.3 Common Genetic Variants in Candidate Genes Modify the Risk for Supraventricular Arrhythmias

22.4 Common Genetic Variants in Candidate Genes Modify the Risk for Ventricular Arrhythmias

Recent evidence increasingly identifies familial clustering of atrial fibrillation (AF), the most common cardiac arrhythmia in humans, suggesting that genetic components are relevant also in common forms of AF. Results from the Framingham Heart Offspring Study4 and a large investigation on the Icelandic population5 indicate a relative risk of up to 3.2 for AF if one parent was affected before age 75 and up to 4.7 if one parent had the onset of AF before the age of 60. Though this kind of heritable component is implying a polygenic substrate with multiple alleles defining the individual’s risk for AF, until today only a small number of common variants have been associated with AF. An overview is given in Table 22.1 (with the genetic variants listed in chromosomal order).6-30 Among these are SNPs in the KCNE1, KCNE5, and SCN5A genes as well as in those coding for Connexin 40, Angiotensinogen, Angiotensin Converting Enzyme, and G-protein b3. However, unfortunately all these association studies for AF have been underpowered or have not been replicated reliably. A significant association has been observed between AF and the coding variant K897T (rs1805123) in KCNH2 as the first candidate gene based SNP association study in AF with robust replication.16 A genome-wide association study in Icelanders identified a locus on Chromosome (Chr) 4q25 associated with undifferentiated AF in subjects of all ages.13 Within this locus, two noncoding SNPs were independently associated with AF and these findings were replicated in two populations of European descent and one of Asian descent. The SNP most strongly associated with AF, rs2200733, conferred a 1.71-fold increased odds of AF (p > 6.1 × 10−41) and the other SNP, rs10033464 conferred a 1.42-fold increased odds of AF (p > 3.1 × 10−11). Recently, the association with these two variants on Chr4q25 could be replicated in subjects of all ages. Over 3,500 affected individuals with AF and 12,000 referent subjects were genotyped, originating from four studies of European descent: the Framingham Heart Study, Rotterdam Study, Vanderbilt AF Registry, and German AF Network.14 A meta-analysis of all four studies revealed an OR of 1.90 (95% CI, 1.61–2.25; 1.0 × 10−13) for rs2200733 and 1.35 (95% CI, 1.25–1.46; 3.8 × 10−14) for rs10033464.

The lack of serologic biomarkers to predict ventricular tachycardia (VT), ventricular fibrillation (VF), and sudden cardiac death has made systematic searches for common genetic variants influencing these traits extremely important.31 To date, only a small number of candidate gene based studies with a focus on exonic SNPs are available. The majority of these association studies are underpowered and lack independent replication (Table 22.2).32-47 The polymorphism SCN5A-Y1103, as mentioned earlier, is present in 13.2% of the AfricanAmerican population. It is strongly associated with the development of arrhythmias, namely drug-induced long QT syndrome.3 This common variant has been recognized as an independent marker of arrhythmia risk and sudden infant death syndrome in the African population.48,49 To date, systematic large-scale SNP association studies with independent replication studies are missing. The first genome-wide association efforts in defined populations with ventricular arrhythmias are currently under way and will hopefully identify novel genetic loci and alleles contributing to ventricular arrhythmia risk.

22.5 Searching for the Genetic Susceptibility to Common Cardiac Arrhythmias Cardiac arrhythmias are electrical disorders of the heart ranging from harmless single ectopic beats to common atrial arrhythmias such as AF to lethal ventricular arrhythmias that cause sudden cardiac death (SCD). When searching for the polygenic contribution of a complex trait such as cardiac arrhythmias, it is essential to focus on a specific phenotype and collect a large cohort with a high degree of homogeneity as well as a substantial evidence for heritability to limit the degrees of complexity (Fig. 22.1). Data from the first genome-wide association study in AF patients demonstrate the validity of this rationale leading to the identification of a novel genetic locus associated with an increased risk for AF.13,14

M235T

−6 g>a

−217 g>a

T174M, −20 a>c, −152 g>a

−6 g>a (I/D)

A985G

−44A

−592 a>c

E145D

A1166C

H558R

chr4: 111929618 c>t, chr4: 111940210 g>t

−174 g>c

K897T

−786 t>c

4a, 4b (tandem repeat, intron4)

E298D

20210 g>a

P448R, R519H, G643S

AGT

AGT

AGT

AGT

AGT (ACE)

EDN2

GJA5 (Cx40)

IL10

KCNE4

AGTR1

SCN5A

Unknown (PITX2 ?)

IL 6

KCNH2 (HERG)

NOS3

NOS3

NOS3

F2

KCNQ1

Atrial fibrillation/atrial flutter

rs1799963

rs1799983

rs2070744

rs1805123

11

11

7

7

7

7

7

4

rs2200733, rs10033464

rs1800795

3

3

2

1

1

1

1

1

1

1

1

rs1805124

rs12621643

rs18007872

rs35594137

rs5800

rs5051

rs5049

rs5051

rs699

Table 22.1  Common variants in supraventricular rhythm disorders Gene Variant/SNP rs-number Chromosome

142

336

[51–331]

[51–331]

[51–331]

1,207

26

[143–3,508]

157

250

142

196

173

26

968

250

250

250

250

Cases (n/[n-range])

238

336

[289–441]

[289–441]

[289–441]

2,475

84

[738–17,714]

314

250

238

873

232

84

8,267

250

250

250

250

Controls (n/ [n-range])

n.a.

2.4

[1.19–3.2]

[n.a.–0.81]

[1.23–2.67]

1.3

3.25

[1.72–2.50], [1.34–1.39]

1.6

n.a.

1.66

n.a.

1.514

5.89

1.1 (1.2)

n.a.

2

3.3

2.5

OR

n.s.

c

SLN

rs35594137

rs17003955

rs1805218

rs1805127

rs243865

rs708272

rs5443

rs-number

Table 22.1  (continued) Gene Variant/SNP

1

X

21

21

17

16

16

12

11

Chromosome

158

142

[69–331]

[51–510]

196

97

291

147

Cases (n/[n-range])

96

238

[60–441]

[83–520]

873

97

292

92

Controls (n/ [n-range])

0.52

n.a.

1.55–2.67

[0.9–3.24]

n.a.

0.35

0.46

n.a.

OR

0.007

n.s.

0.024–0.002

[0.418– a n.a., rs18007872 1 23 CERKL chr2:182281500 t>c rs993648 2 183 SCN5A S1103Y rs7626962 3 ANK2 T1404I, V1516D, T1552N, 4 190 V1777M, E1813K ANK2 P2835S rs3733617 4 34 PALLD chr4:169904988 t>c rs17054392 4 183 ADRB2 Gly16/Gln27 Haplotype 5 93 TNF −238 g>a, −308 g>a 6 23 KCNH2 K897T rs1805123 7 KCNH2 K897T rs1805123 7 8 KCNH2 R1047L rs36210421 7 7 NRG3 chr10:83809105 g>t rs4933824 10 183 KCNJ11 K23E rs5219 11 86 KCNJ11 A190A rs5218 11 86 KCNJ11 L267V 11 86 KCNJ11 L267L rs5216 11 86 KCNJ11 L270V rs1800467 11 86 KCNJ11 K381K rs8175351 11 86 KCNQ1 G643S rs1800172 11 6 NUBPL chr14:31163299 g>a rs7142881 14 183 SLCO3A1 chr15:90246877 t>c rs3924426 15 183 BRUNOL4 chr18:33182637 t>c rs4799915 18 183 KCNE2 T8A rs2234916 21

3

1

Arrhythmogenic right ventricular cardiomyopathy RYR2 G1886S rs3766871 rs1805124

22

Ventricular extrasystole CYP2D6 CYP2D6*10

Brugada syndrome SCN5A H558R VT/VF SCN5A H558R

Chromosome

Table 22.2  Common variants in ventricular rhythm disorders Gene Variant SNP-rs-number

84 84 84 84 84 84 89

14 98

226 12/100

95

n.a.

12/100

n.a.

120

463

n.a.

Controls

1.60 × 10−6 2.05 × 10−6 3.30 × 10−6

1.98 × 10−6 n.s. n.s. n.s. n.s. n.s. n.s.

n.a.

3.48 × 10

−6

n.a. 2.83 × 10−6

n.a.

n.s.

0.05