1
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Trayanova NA, Lyon A, Shade J, Heijman J. Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation. Physiol Rev 2024; 104:1265-1333. [PMID: 38153307 DOI: 10.1152/physrev.00017.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 12/19/2023] [Accepted: 12/21/2023] [Indexed: 12/29/2023] Open
Abstract
The complexity of cardiac electrophysiology, involving dynamic changes in numerous components across multiple spatial (from ion channel to organ) and temporal (from milliseconds to days) scales, makes an intuitive or empirical analysis of cardiac arrhythmogenesis challenging. Multiscale mechanistic computational models of cardiac electrophysiology provide precise control over individual parameters, and their reproducibility enables a thorough assessment of arrhythmia mechanisms. This review provides a comprehensive analysis of models of cardiac electrophysiology and arrhythmias, from the single cell to the organ level, and how they can be leveraged to better understand rhythm disorders in cardiac disease and to improve heart patient care. Key issues related to model development based on experimental data are discussed, and major families of human cardiomyocyte models and their applications are highlighted. An overview of organ-level computational modeling of cardiac electrophysiology and its clinical applications in personalized arrhythmia risk assessment and patient-specific therapy of atrial and ventricular arrhythmias is provided. The advancements presented here highlight how patient-specific computational models of the heart reconstructed from patient data have achieved success in predicting risk of sudden cardiac death and guiding optimal treatments of heart rhythm disorders. Finally, an outlook toward potential future advances, including the combination of mechanistic modeling and machine learning/artificial intelligence, is provided. As the field of cardiology is embarking on a journey toward precision medicine, personalized modeling of the heart is expected to become a key technology to guide pharmaceutical therapy, deployment of devices, and surgical interventions.
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Affiliation(s)
- Natalia A Trayanova
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland, United States
| | - Aurore Lyon
- Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
- Division of Heart and Lungs, Department of Medical Physiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Julie Shade
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland, United States
| | - Jordi Heijman
- Department of Cardiology, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands
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2
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Li G, Brumback BD, Huang L, Zhang DM, Yin T, Lipovsky CE, Hicks SC, Jimenez J, Boyle PM, Rentschler SL. Acute Glycogen Synthase Kinase-3 Inhibition Modulates Human Cardiac Conduction. JACC Basic Transl Sci 2022; 7:1001-1017. [PMID: 36337924 PMCID: PMC9626903 DOI: 10.1016/j.jacbts.2022.04.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 04/11/2022] [Accepted: 04/13/2022] [Indexed: 01/14/2023]
Abstract
Glycogen synthase kinase 3 (GSK-3) inhibition has emerged as a potential therapeutic target for several diseases, including cancer. However, the role for GSK-3 regulation of human cardiac electrophysiology remains ill-defined. We demonstrate that SB216763, a GSK-3 inhibitor, can acutely reduce conduction velocity in human cardiac slices. Combined computational modeling and experimental approaches provided mechanistic insight into GSK-3 inhibition-mediated changes, revealing that decreased sodium-channel conductance and tissue conductivity may underlie the observed phenotypes. Our study demonstrates that GSK-3 inhibition in human myocardium alters electrophysiology and may predispose to an arrhythmogenic substrate; therefore, monitoring for adverse arrhythmogenic events could be considered.
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Key Words
- ABC, active β-catenin
- APD, action potential duration
- BDM, 2,3-butanedione monoxime
- CV, conduction velocity
- Cx43, connexin 43
- GNa, sodium-channel conductance
- GOF, gain of function
- GSK-3 inhibitor
- GSK-3, glycogen synthase kinase 3
- INa, sodium current
- LV, left ventricle
- NaV1.5, pore-forming α-subunit protein of the voltage-gated cardiac sodium channel
- PCR, polymerase chain reaction
- RMP, resting membrane potential
- RT-qPCR, reverse transcription-quantitative polymerase chain reaction
- SB2, SB216763
- SB216763
- cDNA, complementary DNA
- dVm/dtmax, maximum upstroke velocity
- electrophysiology
- human cardiac slices
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Affiliation(s)
- Gang Li
- Department of Medicine, Cardiovascular Division, Washington University School of Medicine in St. Louis, Missouri, USA
- Department of Biomedical Engineering, Washington University McKelvey School of Engineering in St. Louis, Missouri, USA
| | - Brittany D. Brumback
- Department of Medicine, Cardiovascular Division, Washington University School of Medicine in St. Louis, Missouri, USA
- Department of Biomedical Engineering, Washington University McKelvey School of Engineering in St. Louis, Missouri, USA
| | - Lei Huang
- Department of Medicine, Cardiovascular Division, Washington University School of Medicine in St. Louis, Missouri, USA
| | - David M. Zhang
- Department of Medicine, Cardiovascular Division, Washington University School of Medicine in St. Louis, Missouri, USA
| | - Tiankai Yin
- Department of Medicine, Cardiovascular Division, Washington University School of Medicine in St. Louis, Missouri, USA
| | - Catherine E. Lipovsky
- Department of Medicine, Cardiovascular Division, Washington University School of Medicine in St. Louis, Missouri, USA
- Department of Developmental Biology, Washington University School of Medicine in St. Louis, Missouri, USA
| | - Stephanie C. Hicks
- Department of Medicine, Cardiovascular Division, Washington University School of Medicine in St. Louis, Missouri, USA
| | - Jesus Jimenez
- Department of Medicine, Cardiovascular Division, Washington University School of Medicine in St. Louis, Missouri, USA
| | - Patrick M. Boyle
- Department of Bioengineering, Center for Cardiovascular Biology, and Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, Washington, USA
| | - Stacey L. Rentschler
- Department of Medicine, Cardiovascular Division, Washington University School of Medicine in St. Louis, Missouri, USA
- Department of Biomedical Engineering, Washington University McKelvey School of Engineering in St. Louis, Missouri, USA
- Department of Developmental Biology, Washington University School of Medicine in St. Louis, Missouri, USA
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3
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Manders F, van Boxtel R, Middelkamp S. The Dynamics of Somatic Mutagenesis During Life in Humans. FRONTIERS IN AGING 2022; 2:802407. [PMID: 35822044 PMCID: PMC9261377 DOI: 10.3389/fragi.2021.802407] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 11/30/2021] [Indexed: 12/12/2022]
Abstract
From conception to death, human cells accumulate somatic mutations in their genomes. These mutations can contribute to the development of cancer and non-malignant diseases and have also been associated with aging. Rapid technological developments in sequencing approaches in the last few years and their application to normal tissues have greatly advanced our knowledge about the accumulation of these mutations during healthy aging. Whole genome sequencing studies have revealed that there are significant differences in mutation burden and patterns across tissues, but also that the mutation rates within tissues are surprisingly constant during adult life. In contrast, recent lineage-tracing studies based on whole-genome sequencing have shown that the rate of mutation accumulation is strongly increased early in life before birth. These early mutations, which can be shared by many cells in the body, may have a large impact on development and the origin of somatic diseases. For example, cancer driver mutations can arise early in life, decades before the detection of the malignancy. Here, we review the recent insights in mutation accumulation and mutagenic processes in normal tissues. We compare mutagenesis early and later in life and discuss how mutation rates and patterns evolve during aging. Additionally, we outline the potential impact of these mutations on development, aging and disease.
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Affiliation(s)
- Freek Manders
- Princess Máxima Center for Pediatric Oncology and Oncode Institute, Utrecht, Netherlands
| | - Ruben van Boxtel
- Princess Máxima Center for Pediatric Oncology and Oncode Institute, Utrecht, Netherlands
| | - Sjors Middelkamp
- Princess Máxima Center for Pediatric Oncology and Oncode Institute, Utrecht, Netherlands
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4
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Lobon I, Solís-Moruno M, Juan D, Muhaisen A, Abascal F, Esteller-Cucala P, García-Pérez R, Martí MJ, Tolosa E, Ávila J, Rahbari R, Marques-Bonet T, Casals F, Soriano E. Somatic Mutations Detected in Parkinson Disease Could Affect Genes With a Role in Synaptic and Neuronal Processes. FRONTIERS IN AGING 2022; 3:851039. [PMID: 35821807 PMCID: PMC9261316 DOI: 10.3389/fragi.2022.851039] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Accepted: 03/16/2022] [Indexed: 12/17/2022]
Abstract
The role of somatic mutations in complex diseases, including neurodevelopmental and neurodegenerative disorders, is becoming increasingly clear. However, to date, no study has shown their relation to Parkinson disease’s phenotype. To explore the relevance of embryonic somatic mutations in sporadic Parkinson disease, we performed whole-exome sequencing in blood and four brain regions of ten patients. We identified 59 candidate somatic single nucleotide variants (sSNVs) through sensitive calling and a careful filtering strategy (COSMOS). We validated 27 of them with amplicon-based ultra-deep sequencing, with a 70% validation rate for the highest-confidence variants. The identified sSNVs are in genes with synaptic functions that are co-expressed with genes previously associated with Parkinson disease. Most of the sSNVs were only called in blood but were also found in the brain tissues with ultra-deep amplicon sequencing, demonstrating the strength of multi-tissue sampling designs.
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Affiliation(s)
- Irene Lobon
- Institute of Evolutionary Biology (UPF-CSIC), Barcelona, Spain
- *Correspondence: Irene Lobon, ; Eduardo Soriano,
| | - Manuel Solís-Moruno
- Institute of Evolutionary Biology (UPF-CSIC), Barcelona, Spain
- Genomics Core Facility, Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Barcelona, Spain
| | - David Juan
- Institute of Evolutionary Biology (UPF-CSIC), Barcelona, Spain
| | - Ashraf Muhaisen
- Department of Cell Biology, Physiology and Immunology and Institute of Neurosciences, Universitat de Barcelona (UB), Barcelona, Spain
- Centre for Networked Biomedical Research on Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Federico Abascal
- Cancer, Ageing, and Somatic Mutation (CASM), Wellcome Sanger Institute, Cambridge, United Kingdom
| | | | | | - Maria Josep Martí
- Centre for Networked Biomedical Research on Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Department of Neurology, Hospital Clínic de Barcelona, Institut d’Investigacions Biomédiques August Pi i Sunyer (IDIBAPS), University of Barcelona (UB), Barcelona, Spain
| | - Eduardo Tolosa
- Centre for Networked Biomedical Research on Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Department of Neurology, Hospital Clínic de Barcelona, Institut d’Investigacions Biomédiques August Pi i Sunyer (IDIBAPS), University of Barcelona (UB), Barcelona, Spain
| | - Jesús Ávila
- Centre for Networked Biomedical Research on Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Centro de Biología Molecular Severo Ochoa, Madrid, Spain
| | - Raheleh Rahbari
- Cancer, Ageing, and Somatic Mutation (CASM), Wellcome Sanger Institute, Cambridge, United Kingdom
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology (UPF-CSIC), Barcelona, Spain
- Catalan Institution of Research and Advanced Studies (ICREA), Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Ferran Casals
- Genomics Core Facility, Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Barcelona, Spain
- Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Barcelona, Spain
| | - Eduardo Soriano
- Department of Cell Biology, Physiology and Immunology and Institute of Neurosciences, Universitat de Barcelona (UB), Barcelona, Spain
- Centre for Networked Biomedical Research on Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- *Correspondence: Irene Lobon, ; Eduardo Soriano,
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5
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Abstract
Advances in population-scale genomic sequencing have greatly expanded the understanding of the inherited basis of cardiovascular disease (CVD). Reanalysis of these genomic datasets identified an unexpected risk factor for CVD, somatically acquired DNA mutations. In this review, we provide an overview of somatic mutations and their contributions to CVD. We focus on the most common and well-described manifestation, clonal hematopoiesis of indeterminate potential. We also review the currently available data regarding how somatic mutations lead to tissue mosaicism in various forms of CVD, including atrial fibrillation and aortic aneurism associated with Marfan Syndrome. Finally, we highlight future research directions given current knowledge gaps and consider how technological advances will enhance the discovery of somatic mutations in CVD and management of patients with somatic mutations.
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Affiliation(s)
- J. Brett Heimlich
- Department of Medicine, Division of Cardiovascular Medicine, Vanderbilt University Medical Center
| | - Alexander G. Bick
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center
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6
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Martínez-Barrios E, Cesar S, Cruzalegui J, Hernandez C, Arbelo E, Fiol V, Brugada J, Brugada R, Campuzano O, Sarquella-Brugada G. Clinical Genetics of Inherited Arrhythmogenic Disease in the Pediatric Population. Biomedicines 2022; 10:106. [PMID: 35052786 PMCID: PMC8773373 DOI: 10.3390/biomedicines10010106] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 12/27/2021] [Accepted: 12/31/2021] [Indexed: 12/19/2022] Open
Abstract
Sudden death is a rare event in the pediatric population but with a social shock due to its presentation as the first symptom in previously healthy children. Comprehensive autopsy in pediatric cases identify an inconclusive cause in 40-50% of cases. In such cases, a diagnosis of sudden arrhythmic death syndrome is suggested as the main potential cause of death. Molecular autopsy identifies nearly 30% of cases under 16 years of age carrying a pathogenic/potentially pathogenic alteration in genes associated with any inherited arrhythmogenic disease. In the last few years, despite the increasing rate of post-mortem genetic diagnosis, many families still remain without a conclusive genetic cause of the unexpected death. Current challenges in genetic diagnosis are the establishment of a correct genotype-phenotype association between genes and inherited arrhythmogenic disease, as well as the classification of variants of uncertain significance. In this review, we provide an update on the state of the art in the genetic diagnosis of inherited arrhythmogenic disease in the pediatric population. We focus on emerging publications on gene curation for genotype-phenotype associations, cases of genetic overlap and advances in the classification of variants of uncertain significance. Our goal is to facilitate the translation of genetic diagnosis to the clinical area, helping risk stratification, treatment and the genetic counselling of families.
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Affiliation(s)
- Estefanía Martínez-Barrios
- Arrhythmias Unit, Hospital Sant Joan de Déu, University of Barcelona, 08007 Barcelona, Spain; (E.M.-B.); (S.C.); (J.C.); (C.H.); (V.F.); (J.B.)
| | - Sergi Cesar
- Arrhythmias Unit, Hospital Sant Joan de Déu, University of Barcelona, 08007 Barcelona, Spain; (E.M.-B.); (S.C.); (J.C.); (C.H.); (V.F.); (J.B.)
| | - José Cruzalegui
- Arrhythmias Unit, Hospital Sant Joan de Déu, University of Barcelona, 08007 Barcelona, Spain; (E.M.-B.); (S.C.); (J.C.); (C.H.); (V.F.); (J.B.)
| | - Clara Hernandez
- Arrhythmias Unit, Hospital Sant Joan de Déu, University of Barcelona, 08007 Barcelona, Spain; (E.M.-B.); (S.C.); (J.C.); (C.H.); (V.F.); (J.B.)
| | - Elena Arbelo
- Centro de Investigación Biomédica en Red, Enfermedades Cardiovasculares (CIBERCV), 28029 Madrid, Spain; (E.A.); (R.B.)
- Arrhythmias Unit, Hospital Clinic, University of Barcelona-IDIBAPS, 08036 Barcelona, Spain
| | - Victoria Fiol
- Arrhythmias Unit, Hospital Sant Joan de Déu, University of Barcelona, 08007 Barcelona, Spain; (E.M.-B.); (S.C.); (J.C.); (C.H.); (V.F.); (J.B.)
| | - Josep Brugada
- Arrhythmias Unit, Hospital Sant Joan de Déu, University of Barcelona, 08007 Barcelona, Spain; (E.M.-B.); (S.C.); (J.C.); (C.H.); (V.F.); (J.B.)
- Centro de Investigación Biomédica en Red, Enfermedades Cardiovasculares (CIBERCV), 28029 Madrid, Spain; (E.A.); (R.B.)
- Arrhythmias Unit, Hospital Clinic, University of Barcelona-IDIBAPS, 08036 Barcelona, Spain
| | - Ramon Brugada
- Centro de Investigación Biomédica en Red, Enfermedades Cardiovasculares (CIBERCV), 28029 Madrid, Spain; (E.A.); (R.B.)
- Medical Science Department, School of Medicine, University of Girona, 17004 Girona, Spain
- Cardiovascular Genetics Center, University of Girona-IDIBGI, 17190 Girona, Spain
- Cardiology Service, Hospital Josep Trueta, University of Girona, 17007 Girona, Spain
| | - Oscar Campuzano
- Centro de Investigación Biomédica en Red, Enfermedades Cardiovasculares (CIBERCV), 28029 Madrid, Spain; (E.A.); (R.B.)
- Medical Science Department, School of Medicine, University of Girona, 17004 Girona, Spain
- Cardiovascular Genetics Center, University of Girona-IDIBGI, 17190 Girona, Spain
| | - Georgia Sarquella-Brugada
- Arrhythmias Unit, Hospital Sant Joan de Déu, University of Barcelona, 08007 Barcelona, Spain; (E.M.-B.); (S.C.); (J.C.); (C.H.); (V.F.); (J.B.)
- Medical Science Department, School of Medicine, University of Girona, 17004 Girona, Spain
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7
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Castle AMR, Ramien ML, Kanigsberg N, El Demellawy D, McGowan-Jordan J, Beaulieu Bergeron M, Armour CM. Porokeratotic eccrine ostial and dermal duct nevus associated with an 11 megabase 3p deletion. Pediatr Dermatol 2022; 39:107-111. [PMID: 34929758 DOI: 10.1111/pde.14850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 10/04/2021] [Accepted: 10/17/2021] [Indexed: 11/28/2022]
Abstract
Porokeratotic eccrine ostial and dermal duct nevus (PEODDN) is a rare eccrine hamartoma; the etiology is incompletely understood. A patient presented with congenital, widespread PEODDN. Clinical assessment, histopathologic, cytogenetic, and molecular genetic investigations on affected cells were pursued. Histopathology confirmed PEODDN, and chromosomal microarray on affected tissues identified a mosaic 3p26.3p25.3 deletion in affected tissues. This 11Mb deletion encompasses 47 OMIM genes. We propose that this and other chromosomal deletions may be implicated in some cases of PEODDN, suggesting locus heterogeneity and underscoring the importance of incorporating cytogenetic and molecular investigations into the multidisciplinary care of individuals with suspected mosaic genetic skin disorders.
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Affiliation(s)
- Alison M R Castle
- Department of Genetics, Children's Hospital of Eastern Ontario, Ottawa, Ontario, Canada
| | - Michele L Ramien
- Division of Community Pediatrics, Department of Pediatrics, Alberta Children's Hospital, Calgary, Alberta, Canada
| | - Nordau Kanigsberg
- Division of Dermatology and Rheumatology, Department of Pediatrics, University of Ottawa, Ottawa, Ontario, Canada
| | - Dina El Demellawy
- Department of Pathology and Laboratory Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Jean McGowan-Jordan
- Department of Genetics, Children's Hospital of Eastern Ontario, Ottawa, Ontario, Canada.,Department of Pathology and Laboratory Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Melanie Beaulieu Bergeron
- Department of Genetics, Children's Hospital of Eastern Ontario, Ottawa, Ontario, Canada.,Department of Pathology and Laboratory Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Christine M Armour
- Department of Genetics, Children's Hospital of Eastern Ontario, Ottawa, Ontario, Canada.,Prenatal Screening Ontario (PSO), Better Outcomes Registry & Network (BORN) Ontario, Ottawa, Ontario, Canada.,Children's Hospital of Eastern Ontario (CHEO) Research Institute, Ottawa, Ontario, Canada
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8
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Valencia-Morales MDP, Sanchez-Flores A, Colín-Castelán D, Alvarado-Caudillo Y, Fragoso-Bargas N, López-González G, Peña-López T, Ramírez-Nava M, de la Rocha C, Rodríguez-Ríos D, Lund G, Zaina S. Somatic Genetic Mosaicism in the Apolipoprotein E-null Mouse Aorta. Thromb Haemost 2021; 121:1541-1553. [PMID: 33677828 DOI: 10.1055/a-1414-4840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
In addition to genetic and epigenetic inheritance, somatic variation may contribute to cardiovascular disease (CVD) risk. CVD-associated somatic mutations have been reported in human clonal hematopoiesis, but evidence in the atheroma is lacking. To probe for somatic variation in atherosclerosis, we sought single-nucleotide private variants (PVs) in whole-exome sequencing (WES) data of aorta, liver, and skeletal muscle of two C57BL/6J coisogenic male ApoE null/wild-type (WT) sibling pairs, and RNA-seq data of one of the two pairs. Relative to the C57BL/6 reference genome, we identified 9 and 11 ApoE null aorta- and liver-specific PVs that were shared by all WES and RNA-seq datasets. Corresponding PVs in WT sibling aorta and liver were 1 and 0, respectively, and not overlapping with ApoE null PVs. Pyrosequencing analysis of 4 representative PVs in 17 ApoE null aortas and livers confirmed tissue-specific shifts toward the alternative allele, in addition to significant deviations from mendelian allele ratios. Notably, all aorta and liver PVs were present in the dbSNP database and were predominantly transition mutations within atherosclerosis-related genes. The majority of PVs were in discrete clusters approximately 3 Mb and 65 to 73 Mb away from hypermutable immunoglobin loci in chromosome 6. These features were largely shared with previously reported CVD-associated somatic mutations in human clonal hematopoiesis. The observation that SNPs exhibit tissue-specific somatic DNA mosaicism in ApoE null mice is potentially relevant for genetic association study design. The proximity of PVs to hypermutable loci suggests testable mechanistic hypotheses.
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Affiliation(s)
- María Del Pilar Valencia-Morales
- Department of Genetic Engineering, CINVESTAV Irapuato Unit, Irapuato, Mexico
- Department of Developmental Genetics and Molecular Physiology, "Unidad Universitaria de Secuenciación Masiva y Bioinformática", Biotechnology Institute, UNAM, Cuernavaca, Mexico
| | - Alejandro Sanchez-Flores
- "Unidad Universitaria de Secuenciación Masiva y Bioinformática", Biotechnology Institute, UNAM, Cuernavaca, Mexico
| | | | | | | | - Gladys López-González
- Bachelor's Degree in Nutrition Programme, Division of Health Sciences, Leon Campus, University of Guanajuato, Leon, Mexico
| | - Tania Peña-López
- Department of Medical Sciences, Leon Campus, University of Guanajuato, Leon, Mexico
| | - Magda Ramírez-Nava
- Bachelor's Degree in Nutrition Programme, Division of Health Sciences, Leon Campus, University of Guanajuato, Leon, Mexico
| | - Carmen de la Rocha
- Department of Genetic Engineering, CINVESTAV Irapuato Unit, Irapuato, Mexico
| | | | - Gertrud Lund
- Department of Genetic Engineering, CINVESTAV Irapuato Unit, Irapuato, Mexico
| | - Silvio Zaina
- Department of Medical Sciences, Leon Campus, University of Guanajuato, Leon, Mexico
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9
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Peirlinck M, Sahli Costabal F, Kuhl E. Sex Differences in Drug-Induced Arrhythmogenesis. Front Physiol 2021; 12:708435. [PMID: 34489728 PMCID: PMC8417068 DOI: 10.3389/fphys.2021.708435] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 07/14/2021] [Indexed: 12/25/2022] Open
Abstract
The electrical activity in the heart varies significantly between men and women and results in a sex-specific response to drugs. Recent evidence suggests that women are more than twice as likely as men to develop drug-induced arrhythmia with potentially fatal consequences. Yet, the sex-specific differences in drug-induced arrhythmogenesis remain poorly understood. Here we integrate multiscale modeling and machine learning to gain mechanistic insight into the sex-specific origin of drug-induced cardiac arrhythmia at differing drug concentrations. To quantify critical drug concentrations in male and female hearts, we identify the most important ion channels that trigger male and female arrhythmogenesis, and create and train a sex-specific multi-fidelity arrhythmogenic risk classifier. Our study reveals that sex differences in ion channel activity, tissue conductivity, and heart dimensions trigger longer QT-intervals in women than in men. We quantify the critical drug concentration for dofetilide, a high risk drug, to be seven times lower for women than for men. Our results emphasize the importance of including sex as an independent biological variable in risk assessment during drug development. Acknowledging and understanding sex differences in drug safety evaluation is critical when developing novel therapeutic treatments on a personalized basis. The general trends of this study have significant implications on the development of safe and efficacious new drugs and the prescription of existing drugs in combination with other drugs.
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Affiliation(s)
- Mathias Peirlinck
- Department of Mechanical Engineering, Stanford University, Stanford, CA, United States
| | - Francisco Sahli Costabal
- Department of Mechanical and Metallurgical Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
- Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological Sciences, Pontificia Universidad Católica de Chile, Santiago, Chile
- Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile
| | - Ellen Kuhl
- Department of Mechanical Engineering, Stanford University, Stanford, CA, United States
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10
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Accurate genomic variant detection in single cells with primary template-directed amplification. Proc Natl Acad Sci U S A 2021; 118:2024176118. [PMID: 34099548 PMCID: PMC8214697 DOI: 10.1073/pnas.2024176118] [Citation(s) in RCA: 74] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Improvements in whole genome amplification (WGA) would enable new types of basic and applied biomedical research, including studies of intratissue genetic diversity that require more accurate single-cell genotyping. Here, we present primary template-directed amplification (PTA), an isothermal WGA method that reproducibly captures >95% of the genomes of single cells in a more uniform and accurate manner than existing approaches, resulting in significantly improved variant calling sensitivity and precision. To illustrate the types of studies that are enabled by PTA, we developed direct measurement of environmental mutagenicity (DMEM), a tool for mapping genome-wide interactions of mutagens with single living human cells at base-pair resolution. In addition, we utilized PTA for genome-wide off-target indel and structural variant detection in cells that had undergone CRISPR-mediated genome editing, establishing the feasibility for performing single-cell evaluations of biopsies from edited tissues. The improved precision and accuracy of variant detection with PTA overcomes the current limitations of accurate WGA, which is the major obstacle to studying genetic diversity and evolution at cellular resolution.
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11
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Sawyer BL, Tristani-Firouzi M, Wells LE, Vatta M, Etheridge SP. Maternal mosaicism in long QT syndrome due to a pathogenic variant in KCNH2. HeartRhythm Case Rep 2021; 7:74-78. [PMID: 33665105 PMCID: PMC7897747 DOI: 10.1016/j.hrcr.2020.11.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Affiliation(s)
- Briana L. Sawyer
- Division of Pediatric Cardiology, Department of Pediatrics, University of Utah, Salt Lake City, Utah
| | - Martin Tristani-Firouzi
- Division of Pediatric Cardiology, Department of Pediatrics, University of Utah, Salt Lake City, Utah
| | - Layne E. Wells
- Department of Precision Genomics, Intermountain Primary Children’s Hospital, Salt Lake City, Utah
| | - Matteo Vatta
- Invitae Corporation, San Francisco, California
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Susan P. Etheridge
- Division of Pediatric Cardiology, Department of Pediatrics, University of Utah, Salt Lake City, Utah
- Address reprint requests and correspondence: Dr Susan P. Etheridge, University of Utah Division of Pediatric Cardiology, Department of Pediatrics, 81 N. Mario Capecchi Dr, Salt Lake City, UT 84113.
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12
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Sahli-Costabal F, Seo K, Ashley E, Kuhl E. Classifying Drugs by their Arrhythmogenic Risk Using Machine Learning. Biophys J 2020; 118:1165-1176. [PMID: 32023435 DOI: 10.1101/545863] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 11/27/2019] [Accepted: 01/13/2020] [Indexed: 05/25/2023] Open
Abstract
All medications have adverse effects. Among the most serious of these are cardiac arrhythmias. Current paradigms for drug safety evaluation are costly, lengthy, conservative, and impede efficient drug development. Here, we combine multiscale experiment and simulation, high-performance computing, and machine learning to create a risk estimator to stratify new and existing drugs according to their proarrhythmic potential. We capitalize on recent developments in machine learning and integrate information across 10 orders of magnitude in space and time to provide a holistic picture of the effects of drugs, either individually or in combination with other drugs. We show, both experimentally and computationally, that drug-induced arrhythmias are dominated by the interplay between two currents with opposing effects: the rapid delayed rectifier potassium current and the L-type calcium current. Using Gaussian process classification, we create a classifier that stratifies drugs into safe and arrhythmic domains for any combinations of these two currents. We demonstrate that our classifier correctly identifies the risk categories of 22 common drugs exclusively on the basis of their concentrations at 50% current block. Our new risk assessment tool explains under which conditions blocking the L-type calcium current can delay or even entirely suppress arrhythmogenic events. Using machine learning in drug safety evaluation can provide a more accurate and comprehensive mechanistic assessment of the proarrhythmic potential of new drugs. Our study paves the way toward establishing science-based criteria to accelerate drug development, design safer drugs, and reduce heart rhythm disorders.
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Affiliation(s)
| | - Kinya Seo
- Department of Medicine, Stanford University, Stanford, California
| | - Euan Ashley
- Department of Medicine, Stanford University, Stanford, California; Department of Pathology, Stanford University, Stanford, California
| | - Ellen Kuhl
- Department of Mechanical Engineering, Stanford University, Stanford, California; Department of Bioengineering, Stanford University, Stanford, California.
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13
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Sahli-Costabal F, Seo K, Ashley E, Kuhl E. Classifying Drugs by their Arrhythmogenic Risk Using Machine Learning. Biophys J 2020; 118:1165-1176. [PMID: 32023435 PMCID: PMC7063479 DOI: 10.1016/j.bpj.2020.01.012] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 11/27/2019] [Accepted: 01/13/2020] [Indexed: 12/17/2022] Open
Abstract
All medications have adverse effects. Among the most serious of these are cardiac arrhythmias. Current paradigms for drug safety evaluation are costly, lengthy, conservative, and impede efficient drug development. Here, we combine multiscale experiment and simulation, high-performance computing, and machine learning to create a risk estimator to stratify new and existing drugs according to their proarrhythmic potential. We capitalize on recent developments in machine learning and integrate information across 10 orders of magnitude in space and time to provide a holistic picture of the effects of drugs, either individually or in combination with other drugs. We show, both experimentally and computationally, that drug-induced arrhythmias are dominated by the interplay between two currents with opposing effects: the rapid delayed rectifier potassium current and the L-type calcium current. Using Gaussian process classification, we create a classifier that stratifies drugs into safe and arrhythmic domains for any combinations of these two currents. We demonstrate that our classifier correctly identifies the risk categories of 22 common drugs exclusively on the basis of their concentrations at 50% current block. Our new risk assessment tool explains under which conditions blocking the L-type calcium current can delay or even entirely suppress arrhythmogenic events. Using machine learning in drug safety evaluation can provide a more accurate and comprehensive mechanistic assessment of the proarrhythmic potential of new drugs. Our study paves the way toward establishing science-based criteria to accelerate drug development, design safer drugs, and reduce heart rhythm disorders.
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Affiliation(s)
| | - Kinya Seo
- Department of Medicine, Stanford University, Stanford, California
| | - Euan Ashley
- Department of Medicine, Stanford University, Stanford, California; Department of Pathology, Stanford University, Stanford, California
| | - Ellen Kuhl
- Department of Mechanical Engineering, Stanford University, Stanford, California; Department of Bioengineering, Stanford University, Stanford, California.
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14
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Abstract
The treatment of individual patients in cardiology practice increasingly relies on advanced imaging, genetic screening and devices. As the amount of imaging and other diagnostic data increases, paralleled by the greater capacity to personalize treatment, the difficulty of using the full array of measurements of a patient to determine an optimal treatment seems also to be paradoxically increasing. Computational models are progressively addressing this issue by providing a common framework for integrating multiple data sets from individual patients. These models, which are based on physiology and physics rather than on population statistics, enable computational simulations to reveal diagnostic information that would have otherwise remained concealed and to predict treatment outcomes for individual patients. The inherent need for patient-specific models in cardiology is clear and is driving the rapid development of tools and techniques for creating personalized methods to guide pharmaceutical therapy, deployment of devices and surgical interventions.
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15
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Harper AR, Parikh VN, Goldfeder RL, Caleshu C, Ashley EA. Delivering Clinical Grade Sequencing and Genetic Test Interpretation for Cardiovascular Medicine. ACTA ACUST UNITED AC 2019; 10:CIRCGENETICS.116.001221. [PMID: 28411191 DOI: 10.1161/circgenetics.116.001221] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Affiliation(s)
- Andrew R Harper
- From the Royal Brompton and Harefield NHS Foundation Trust, London (A.R.H.); Wellcome Trust Centre for Human Genetics, University of Oxford, United Kingdom (A.R.H.); Department of Genetics, Stanford University, Stanford, CA (E.A.A., R.L.G.); and Center for Inherited Cardiovascular Disease, Stanford University, Stanford, CA (V.N.P., R.L.G., C.C., E.A.A.)
| | - Victoria N Parikh
- From the Royal Brompton and Harefield NHS Foundation Trust, London (A.R.H.); Wellcome Trust Centre for Human Genetics, University of Oxford, United Kingdom (A.R.H.); Department of Genetics, Stanford University, Stanford, CA (E.A.A., R.L.G.); and Center for Inherited Cardiovascular Disease, Stanford University, Stanford, CA (V.N.P., R.L.G., C.C., E.A.A.)
| | - Rachel L Goldfeder
- From the Royal Brompton and Harefield NHS Foundation Trust, London (A.R.H.); Wellcome Trust Centre for Human Genetics, University of Oxford, United Kingdom (A.R.H.); Department of Genetics, Stanford University, Stanford, CA (E.A.A., R.L.G.); and Center for Inherited Cardiovascular Disease, Stanford University, Stanford, CA (V.N.P., R.L.G., C.C., E.A.A.)
| | - Colleen Caleshu
- From the Royal Brompton and Harefield NHS Foundation Trust, London (A.R.H.); Wellcome Trust Centre for Human Genetics, University of Oxford, United Kingdom (A.R.H.); Department of Genetics, Stanford University, Stanford, CA (E.A.A., R.L.G.); and Center for Inherited Cardiovascular Disease, Stanford University, Stanford, CA (V.N.P., R.L.G., C.C., E.A.A.)
| | - Euan A Ashley
- From the Royal Brompton and Harefield NHS Foundation Trust, London (A.R.H.); Wellcome Trust Centre for Human Genetics, University of Oxford, United Kingdom (A.R.H.); Department of Genetics, Stanford University, Stanford, CA (E.A.A., R.L.G.); and Center for Inherited Cardiovascular Disease, Stanford University, Stanford, CA (V.N.P., R.L.G., C.C., E.A.A.).
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16
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Sahli Costabal F, Yao J, Sher A, Kuhl E. Predicting critical drug concentrations and torsadogenic risk using a multiscale exposure-response simulator. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2019; 144:61-76. [PMID: 30482568 PMCID: PMC6483901 DOI: 10.1016/j.pbiomolbio.2018.10.003] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Revised: 09/21/2018] [Accepted: 10/11/2018] [Indexed: 12/12/2022]
Abstract
Torsades de pointes is a serious side effect of many drugs that can trigger sudden cardiac death, even in patients with structurally normal hearts. Torsadogenic risk has traditionally been correlated with the blockage of a specific potassium channel and a prolonged recovery period in the electrocardiogram. However, the precise mechanisms by which single channel block translates into heart rhythm disorders remain incompletely understood. Here we establish a multiscale exposure-response simulator that converts block-concentration characteristics from single cell recordings into three-dimensional excitation profiles and electrocardiograms to rapidly assess torsadogenic risk. For the drug dofetilide, we characterize the QT interval and heart rate at different drug concentrations and identify the critical concentration at the onset of torsades de pointes: For dofetilide concentrations of 2x, 3x, and 4x, as multiples of the free plasma concentration Cmax = 2.1 nM, the QT interval increased by +62.0%, +71.2%, and +82.3% compared to baseline, and the heart rate changed by -21.7%, -23.3%, and +88.3%. The last number indicates that, at the critical concentration of 4x, the heart spontaneously developed an episode of a torsades-like arrhythmia. Strikingly, this critical drug concentration is higher than the concentration estimated from early afterdepolarizations in single cells and lower than in one-dimensional cable models. Our results highlight the importance of whole heart modeling and explain, at least in part, why current regulatory paradigms often fail to accurately quantify the pro-arrhythmic potential of a drug. Our exposure-response simulator could provide a more mechanistic assessment of pro-arrhythmic risk and help establish science-based guidelines to reduce rhythm disorders, design safer drugs, and accelerate drug development.
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Affiliation(s)
| | - Jiang Yao
- Dassault Systèmes Simulia Corporation, Johnston, RI, 02919, United States
| | - Anna Sher
- Internal Medicine Research Unit, Pfizer Inc, Cambridge, MA, 02139, United States
| | - Ellen Kuhl
- Department of Mechanical Engineering, Stanford University, Stanford, CA, 94305, United States.
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17
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A comprehensive, multiscale framework for evaluation of arrhythmias arising from cell therapy in the whole post-myocardial infarcted heart. Sci Rep 2019; 9:9238. [PMID: 31239508 PMCID: PMC6592890 DOI: 10.1038/s41598-019-45684-0] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Accepted: 06/12/2019] [Indexed: 12/19/2022] Open
Abstract
Direct remuscularization approaches to cell-based heart repair seek to restore ventricular contractility following myocardial infarction (MI) by introducing new cardiomyocytes (CMs) to replace lost or injured ones. However, despite promising improvements in cardiac function, high incidences of ventricular arrhythmias have been observed in animal models of MI injected with pluripotent stem cell-derived cardiomyocytes (PSC-CMs). The mechanisms of arrhythmogenesis remain unclear. Here, we present a comprehensive framework for computational modeling of direct remuscularization approaches to cell therapy. Our multiscale 3D whole-heart modeling framework integrates realistic representations of cell delivery and transdifferentiation therapy modalities as well as representation of spatial distributions of engrafted cells, enabling simulation of clinical therapy and the prediction of emergent electrophysiological behavior and arrhythmogenensis. We employ this framework to explore how varying parameters of cell delivery and transdifferentiation could result in three mechanisms of arrhythmogenesis: focal ectopy, heart block, and reentry.
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18
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Costabal FS, Matsuno K, Yao J, Perdikaris P, Kuhl E. Machine learning in drug development: Characterizing the effect of 30 drugs on the QT interval using Gaussian process regression, sensitivity analysis, and uncertainty quantification. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2019; 348:313-333. [PMID: 32863454 PMCID: PMC7454226 DOI: 10.1016/j.cma.2019.01.033] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Prolonged QT intervals are a major risk factor for ventricular arrhythmias and a leading cause of sudden cardiac death. Various drugs are known to trigger QT interval prolongation and increase the proarrhythmic potential. Yet, how precisely the action of drugs on the cellular level translates into QT interval prolongation on the whole organ level remains insufficiently understood. Here we use machine learning techniques to systematically characterize the effect of 30 common drugs on the QT interval. We combine information from high fidelity three-dimensional human heart simulations with low fidelity one-dimensional cable simulations to build a surrogate model for the QT interval using multi-fidelity Gaussian process regression. Once trained and cross-validated, we apply our surrogate model to perform sensitivity analysis and uncertainty quantification. Our sensitivity analysis suggests that compounds that block the rapid delayed rectifier potassium current I Kr have the greatest prolonging effect of the QT interval, and that blocking the L-type calcium current I CaL and late sodium current I NaL shortens the QT interval. Our uncertainty quantification allows us to propagate the experimental variability from individual block-concentration measurements into the QT interval and reveals that QT interval uncertainty is mainly driven by the variability in I Kr block. In a final validation study, we demonstrate an excellent agreement between our predicted QT interval changes and the changes observed in a randomized clinical trial for the drugs dofetilide, quinidine, ranolazine, and verapamil. We anticipate that both the machine learning methods and the results of this study will have great potential in the efficient development of safer drugs.
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Affiliation(s)
| | - Kristen Matsuno
- Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Jiang Yao
- Dassault Systèmes Simulia Corporation, Johnston, RI 02919, USA
| | - Paris Perdikaris
- Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ellen Kuhl
- Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA
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19
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Trayanova NA, Pashakhanloo F, Wu KC, Halperin HR. Imaging-Based Simulations for Predicting Sudden Death and Guiding Ventricular Tachycardia Ablation. Circ Arrhythm Electrophysiol 2019; 10:CIRCEP.117.004743. [PMID: 28696219 DOI: 10.1161/circep.117.004743] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2017] [Accepted: 06/08/2017] [Indexed: 11/16/2022]
Affiliation(s)
- Natalia A Trayanova
- From the Institute for Computational Medicine and Department of Biomedical Engineering (N.A.T., F.P.) and Departments of Radiology and Biomedical Engineering (H.R.H.), Johns Hopkins University, Baltimore, MD; and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W., H.R.H.).
| | - Farhad Pashakhanloo
- From the Institute for Computational Medicine and Department of Biomedical Engineering (N.A.T., F.P.) and Departments of Radiology and Biomedical Engineering (H.R.H.), Johns Hopkins University, Baltimore, MD; and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W., H.R.H.)
| | - Katherine C Wu
- From the Institute for Computational Medicine and Department of Biomedical Engineering (N.A.T., F.P.) and Departments of Radiology and Biomedical Engineering (H.R.H.), Johns Hopkins University, Baltimore, MD; and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W., H.R.H.)
| | - Henry R Halperin
- From the Institute for Computational Medicine and Department of Biomedical Engineering (N.A.T., F.P.) and Departments of Radiology and Biomedical Engineering (H.R.H.), Johns Hopkins University, Baltimore, MD; and Division of Cardiology, Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, MD (K.C.W., H.R.H.)
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20
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Search of Somatic Mutations of NKX2-5 and GATA4 Genes in Chinese Patients with Sporadic Congenital Heart Disease. Pediatr Cardiol 2019; 40:17-22. [PMID: 30121862 DOI: 10.1007/s00246-018-1955-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2018] [Accepted: 08/08/2018] [Indexed: 12/30/2022]
Abstract
Congenital heart disease (CHD) usually occurs sporadically, with only a minority of cases associated with a known genetic mechanism. Cardiac-specific transcription factors NKX2-5 and GATA4 play key roles in the mammalian heart development, and the affected cardiac tissues of CHD patients are prone to somatic mutations which thus participate in the pathogenesis of CHD. We collected 98 patients with sporadic CHD, extracted genomic DNA from cardiac tissues and blood, and then screened NKX2-5 and GATA4 genes using PCR-direct sequence analysis. A novel heterozygous missense mutation (c.907G > A, p.V303I) of NKX2-5 gene was identified in a patient with tetralogy of Fallots. Functional assay revealed that this mutant was associated with significantly reduced transcriptional activity. In addition, we found two known single-nucleotide polymorphisms (SNPs) (rs2277923, rs3729753) in NKX2-5 and two known SNPs (rs56166237, rs3729856) in GATA4. All variations identified in cardiac tissues were consistent with those of peripheral blood, and no somatic mutations were found in cardiac tissues. Our study shows no evidence of NKX2-5 and GATA4 somatic mutations playing a role in the pathogenesis of sporadic CHD.
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21
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Abstract
High-throughput sequencing has ushered in a diversity of approaches for identifying genetic variants and understanding genome structure and function. When applied to individuals with rare genetic diseases, these approaches have greatly accelerated gene discovery and patient diagnosis. Over the past decade, exome sequencing has emerged as a comprehensive and cost-effective approach to identify pathogenic variants in the protein-coding regions of the genome. However, for individuals in whom exome-sequencing fails to identify a pathogenic variant, we discuss recent advances that are helping to reduce the diagnostic gap.
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Affiliation(s)
- Laure Frésard
- Department of Pathology, Stanford University, Stanford, California 94305, USA
| | - Stephen B Montgomery
- Department of Pathology, Stanford University, Stanford, California 94305, USA.,Department of Genetics, School of Medicine, Stanford, California 94305, USA
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22
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Genome Sequencing in Hypertrophic Cardiomyopathy. J Am Coll Cardiol 2018; 72:430-433. [DOI: 10.1016/j.jacc.2018.05.029] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Revised: 05/24/2018] [Accepted: 05/24/2018] [Indexed: 11/20/2022]
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23
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Ye AY, Dou Y, Yang X, Wang S, Huang AY, Wei L. A model for postzygotic mosaicisms quantifies the allele fraction drift, mutation rate, and contribution to de novo mutations. Genome Res 2018; 28:943-951. [PMID: 29875290 PMCID: PMC6028137 DOI: 10.1101/gr.230003.117] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2017] [Accepted: 05/02/2018] [Indexed: 12/14/2022]
Abstract
The allele fraction (AF) distribution, occurrence rate, and evolutionary contribution of postzygotic single-nucleotide mosaicisms (pSNMs) remain largely unknown. In this study, we developed a mathematical model to describe the accumulation and AF drift of pSNMs during the development of multicellular organisms. By applying the model, we quantitatively analyzed two large-scale data sets of pSNMs identified from human genomes. We found that the postzygotic mutation rate per cell division during early embryogenesis, especially during the first cell division, was higher than the average mutation rate in either male or female gametes. We estimated that the stochastic cell death rate per cell cleavage during human embryogenesis was ∼5%, and parental pSNMs occurring during the first three cell divisions contributed to ∼10% of the de novo mutations observed in children. We further demonstrated that the genomic profiles of pSNMs could be used to measure the divergence distance between tissues. Our results highlight the importance of pSNMs in estimating recurrence risk and clarified the quantitative relationship between postzygotic and de novo mutations.
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Affiliation(s)
- Adam Yongxin Ye
- Center for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, People's Republic of China.,Peking-Tsinghua Center for Life Sciences, Beijing 100871, People's Republic of China.,Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, People's Republic of China
| | - Yanmei Dou
- Center for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, People's Republic of China.,National Institute of Biological Sciences, Beijing 102206, People's Republic of China
| | - Xiaoxu Yang
- Center for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, People's Republic of China
| | - Sheng Wang
- National Institute of Biological Sciences, Beijing 102206, People's Republic of China.,College of Biological Sciences, China Agricultural University, Beijing 100094, People's Republic of China
| | - August Yue Huang
- Center for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, People's Republic of China
| | - Liping Wei
- Center for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, People's Republic of China
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24
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Sahli Costabal F, Yao J, Kuhl E. Predicting drug-induced arrhythmias by multiscale modeling. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2018; 34:e2964. [PMID: 29424967 DOI: 10.1002/cnm.2964] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2017] [Revised: 01/23/2018] [Accepted: 01/27/2018] [Indexed: 06/08/2023]
Abstract
Drugs often have undesired side effects. In the heart, they can induce lethal arrhythmias such as torsades de pointes. The risk evaluation of a new compound is costly and can take a long time, which often hinders the development of new drugs. Here, we establish a high-resolution, multiscale computational model to quickly assess the cardiac toxicity of new and existing drugs. The input of the model is the drug-specific current block from single cell electrophysiology; the output is the spatio-temporal activation profile and the associated electrocardiogram. We demonstrate the potential of our model for a low-risk drug, ranolazine, and a high-risk drug, quinidine: For ranolazine, our model predicts a prolonged QT interval of 19.4% compared with baseline and a regular sinus rhythm at 60.15 beats per minute. For quinidine, our model predicts a prolonged QT interval of 78.4% and a spontaneous development of torsades de pointes both in the activation profile and in the electrocardiogram. Our model reveals the mechanisms by which electrophysiological abnormalities propagate across the spatio-temporal scales, from specific channel blockage, via altered single cell action potentials and prolonged QT intervals, to the spontaneous emergence of ventricular tachycardia in the form of torsades de pointes. Our model could have important implications for researchers, regulatory agencies, and pharmaceutical companies on rationalizing safe drug development and reducing the time-to-market of new drugs.
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Affiliation(s)
| | - Jiang Yao
- Dassault Systèmes Simulia Corporation, Johnston, RI, USA
| | - Ellen Kuhl
- Departments of Mechanical Engineering, Bioengineering, and Cardiothoracic Surgery, Stanford University, Stanford, CA, USA
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25
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Trayanova NA, Boyle PM, Nikolov PP. Personalized Imaging and Modeling Strategies for Arrhythmia Prevention and Therapy. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2018; 5:21-28. [PMID: 29546250 PMCID: PMC5847279 DOI: 10.1016/j.cobme.2017.11.007] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The goal of this article is to review advances in computational modeling of the heart, with a focus on recent non-invasive clinical imaging- and simulation-based strategies aimed at improving the diagnosis and treatment of patients with arrhythmias and structural heart disease. Following a brief overview of the field of computational cardiology, we present recent applications of the personalized virtual-heart approach in predicting the optimal targets for infarct-related ventricular tachycardia and atrial fibrillation ablation, and in determining risk of sudden cardiac death in myocardial infarction patients. The hope is that with such models at the patient bedside, therapies could be improved, invasiveness of diagnostic procedures minimized, and health-care costs reduced.
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Affiliation(s)
- Natalia A Trayanova
- Institute for Computational Medicine and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD
| | - Patrick M Boyle
- Institute for Computational Medicine and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD
| | - Plamen P Nikolov
- Institute for Computational Medicine and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD
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26
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Sahli Costabal F, Yao J, Kuhl E. Predicting the cardiac toxicity of drugs using a novel multiscale exposure-response simulator. Comput Methods Biomech Biomed Engin 2018; 21:232-246. [PMID: 29493299 PMCID: PMC6361171 DOI: 10.1080/10255842.2018.1439479] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
A common but serious side effect of many drugs is torsades de pointes, a rhythm disorder that can have fatal consequences. Torsadogenic risk has traditionally been associated with blockage of a specific potassium channel and an increased recovery period in the electrocardiogram. However, the mechanisms that trigger torsades de pointes remain incompletely understood. Here we establish a computational model to explore how drug-induced effects propagate from the single channel, via the single cell, to the whole heart level. Our mechanistic exposure-response simulator translates block-concentration characteristics for arbitrary drugs into three-dimensional excitation profiles and electrocardiogram recordings to rapidly assess torsadogenic risk. For the drug of dofetilide, we show that this risk is highly dose-dependent: at a concentration of 1x, QT prolongation is 55% but the heart maintains its regular sinus rhythm; at 5.7x, QT prolongation is 102% and the heart spontaneously transitions into torsades de points; at 30x, QT prolongation is 132% and the heart adapts a quasi-depolarized state with numerous rapidly flickering local excitations. Our simulations suggest that neither potassium channel blockage nor QT interval prolongation alone trigger torsades de pointes. The underlying mechanism predicted by our model is early afterdepolarization, which translates into pronounced U waves in the electrocardiogram, a signature that is correctly predicted by our model. Beyond the risk assessment of existing drugs, our exposure-response simulator can become a powerful tool to optimize the co-administration of drugs and, ultimately, guide the design of new drugs toward reducing life threatening drug-induced rhythm disorders in the heart.
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Affiliation(s)
- Francisco Sahli Costabal
- a Departments of Mechanical Engineering, Bioengineering, and Cardiothoracic Surgery , Stanford University , CA , USA
| | - Jiang Yao
- b Dassault Systèmes Simulia Corporation , Johnston , RI , USA
| | - Ellen Kuhl
- a Departments of Mechanical Engineering, Bioengineering, and Cardiothoracic Surgery , Stanford University , CA , USA
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27
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Manheimer KB, Richter F, Edelmann LJ, D'Souza SL, Shi L, Shen Y, Homsy J, Boskovski MT, Tai AC, Gorham J, Yasso C, Goldmuntz E, Brueckner M, Lifton RP, Chung WK, Seidman CE, Seidman JG, Gelb BD. Robust identification of mosaic variants in congenital heart disease. Hum Genet 2018; 137:183-193. [PMID: 29417219 PMCID: PMC5997246 DOI: 10.1007/s00439-018-1871-6] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Accepted: 01/30/2018] [Indexed: 12/15/2022]
Abstract
Mosaicism due to somatic mutations can cause multiple diseases including cancer, developmental and overgrowth syndromes, neurodevelopmental disorders, autoinflammatory diseases, and atrial fibrillation. With the increased use of next generation sequencing technology, multiple tools have been developed to identify low-frequency variants, specifically from matched tumor-normal tissues in cancer studies. To investigate whether mosaic variants are implicated in congenital heart disease (CHD), we developed a pipeline using the cancer somatic variant caller MuTect to identify mosaic variants in whole-exome sequencing (WES) data from a cohort of parent/affected child trios (n = 715) and a cohort of healthy individuals (n = 416). This is a novel application of the somatic variant caller designed for cancer to WES trio data. We identified two cases with mosaic KMT2D mutations that are likely pathogenic for CHD, but conclude that, overall, mosaicism detectable in peripheral blood or saliva does not account for a significant portion of CHD etiology.
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Affiliation(s)
- Kathryn B Manheimer
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Felix Richter
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lisa J Edelmann
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sunita L D'Souza
- Department of Cell, Developmental and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lisong Shi
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yufeng Shen
- Department of Systems Biology, Columbia University Medical Center, New York, NY, USA
- Department of Biomedical Informatics, Columbia University Medical Center, New York, NY, USA
| | - Jason Homsy
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Cardiovscular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Marko T Boskovski
- Division of Cardiac Surgery, The Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Angela C Tai
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Joshua Gorham
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | | | - Elizabeth Goldmuntz
- Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Cardiology, The Children's Hospital of Philadelphia, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Martina Brueckner
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT, USA
| | - Richard P Lifton
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- Howard Hughes Medical Institute, Yale University, New Haven, CT, USA
- Yale Center for Mendelian Genomics, New Haven, CT, USA
- Yale Center for Genome Analysis, Yale University, New Haven, CT, USA
- Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Wendy K Chung
- Department of Pediatrics, Columbia University Medical Center, New York, NY, USA
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Christine E Seidman
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Department of Medicine (Cardiology), Brigham and Women's Hospital, Boston, MA, USA
- The Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - J G Seidman
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Bruce D Gelb
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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Murphy TW, Zhang Q, Naler LB, Ma S, Lu C. Recent advances in the use of microfluidic technologies for single cell analysis. Analyst 2017; 143:60-80. [PMID: 29170786 PMCID: PMC5839671 DOI: 10.1039/c7an01346a] [Citation(s) in RCA: 103] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
The inherent heterogeneity in cell populations has become of great interest and importance as analytical techniques have improved over the past decades. With the advent of personalized medicine, understanding the impact of this heterogeneity has become an important challenge for the research community. Many different microfluidic approaches with varying levels of throughput and resolution exist to study single cell activity. In this review, we take a broad view of the recent microfluidic developments in single cell analysis based on microwell, microchamber, and droplet platforms. We cover physical, chemical, and molecular biology approaches for cellular and molecular analysis including newly emerging genome-wide analysis.
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Affiliation(s)
- Travis W Murphy
- Department of Chemical Engineering, Virginia Tech, Blacksburg, VA 24061, USA.
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Genomic mosaicism in paternal sperm and multiple parental tissues in a Dravet syndrome cohort. Sci Rep 2017; 7:15677. [PMID: 29142202 PMCID: PMC5688122 DOI: 10.1038/s41598-017-15814-7] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2017] [Accepted: 11/02/2017] [Indexed: 12/21/2022] Open
Abstract
Genomic mosaicism in parental gametes and peripheral tissues is an important consideration for genetic counseling. We studied a Chinese cohort affected by a severe epileptic disorder, Dravet syndrome (DS). There were 56 fathers who donated semen and 15 parents who donated multiple peripheral tissue samples. We used an ultra-sensitive quantification method, micro-droplet digital PCR (mDDPCR), to detect parental mosaicism of the proband’s pathogenic mutation in SCN1A, the causal gene of DS in 112 families. Ten of the 56 paternal sperm samples were found to exhibit mosaicism of the proband’s mutations, with mutant allelic fractions (MAFs) ranging from 0.03% to 39.04%. MAFs in the mosaic fathers’ sperm were significantly higher than those in their blood (p = 0.00098), even after conditional probability correction (p’ = 0.033). In three mosaic fathers, ultra-low fractions of mosaicism (MAF < 1%) were detected in the sperm samples. In 44 of 45 cases, mosaicism was also observed in other parental peripheral tissues. Hierarchical clustering showed that MAFs measured in the paternal sperm, hair follicles and urine samples were clustered closest together. Milder epileptic phenotypes were more likely to be observed in mosaic parents (p = 3.006e-06). Our study provides new insights for genetic counseling.
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Rueda M, Wagner JL, Phillips TC, Topol SE, Muse ED, Lucas JR, Wagner GN, Topol EJ, Torkamani A. Molecular Autopsy for Sudden Death in the Young: Is Data Aggregation the Key? Front Cardiovasc Med 2017; 4:72. [PMID: 29181379 PMCID: PMC5694161 DOI: 10.3389/fcvm.2017.00072] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2017] [Accepted: 10/27/2017] [Indexed: 12/18/2022] Open
Abstract
The Scripps molecular autopsy study seeks to incorporate genetic testing into the postmortem examination of cases of sudden death in the young (<45 years old). Here, we describe the results from the first 2 years of the study, which consisted of whole exome sequencing (WES) of a cohort of 50 cases predominantly from San Diego County. Apart from the individual description of cases, we analyzed the data at the cohort-level, which brought new perspectives on the genetic causes of sudden death. We investigated the advantages and disadvantages of using WES compared to a gene panel for cardiac disease (usually the first genetic test used by medical examiners). In an attempt to connect complex clinical phenotypes with genotypes, we classified samples by their genetic fingerprint. Finally, we studied the benefits of analyzing the mitochondrial DNA genome. In this regard, we found that half of the cases clinically diagnosed as sudden infant death syndrome had an increased ratio of heteroplasmic variants, and that the variants were also present in the mothers. We believe that community-based data aggregation and sharing will eventually lead to an improved classification of variants. Allele frequencies for the all cases can be accessed via our genomics browser at https://genomics.scripps.edu/browser.
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Affiliation(s)
- Manuel Rueda
- The Scripps Translational Science Institute, Scripps Health, The Scripps Research Institute, La Jolla, CA, United States
| | - Jennifer L Wagner
- The Scripps Translational Science Institute, Scripps Health, The Scripps Research Institute, La Jolla, CA, United States
| | - Tierney C Phillips
- The Scripps Translational Science Institute, Scripps Health, The Scripps Research Institute, La Jolla, CA, United States
| | - Sarah E Topol
- The Scripps Translational Science Institute, Scripps Health, The Scripps Research Institute, La Jolla, CA, United States
| | - Evan D Muse
- The Scripps Translational Science Institute, Scripps Health, The Scripps Research Institute, La Jolla, CA, United States.,Division of Cardiology, Scripps Clinic, La Jolla, CA, United States
| | - Jonathan R Lucas
- Medical Examiner Department, San Diego County, San Diego, CA, United States
| | - Glenn N Wagner
- Medical Examiner Department, San Diego County, San Diego, CA, United States
| | - Eric J Topol
- The Scripps Translational Science Institute, Scripps Health, The Scripps Research Institute, La Jolla, CA, United States.,Division of Cardiology, Scripps Clinic, La Jolla, CA, United States
| | - Ali Torkamani
- The Scripps Translational Science Institute, Scripps Health, The Scripps Research Institute, La Jolla, CA, United States
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Abstract
PURPOSE OF REVIEW Genome sequencing is now available as a clinical diagnostic test. There is a significant knowledge and translation gap for nongenetic specialists of the processes necessary to generate and interpret clinical genome sequencing. The purpose of this review is to provide a primer on contemporary clinical genome sequencing for nongenetic specialists describing the human genome project, current techniques and applications in genome sequencing, limitations of current technology, and techniques on the horizon. RECENT FINDINGS As currently implemented, genome sequencing compares short pieces of an individual's genome with a reference sequence developed by the human genome project. Genome sequencing may be used for obtaining timely diagnostic information, cancer pharmacogenomics, or in clinical cases when previous genetic testing has not revealed a clear diagnosis. At present, the implementation of clinical genome sequencing is limited by the availability of clinicians qualified for interpretation, and current techniques in used clinical testing do not detect all types of genetic variation present in a single genome. SUMMARY Clinicians considering a genetic diagnosis have wide array of testing choices which now includes genome sequencing. Although not a comprehensive test in its current form, genome sequencing offers more information than gene-panel or exome sequencing and has the potential to replace targeted single-gene or gene-panel testing in many clinical scenarios.
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Vandenberg JI, Perry MD, Hill AP. Recent advances in understanding and prevention of sudden cardiac death. F1000Res 2017; 6:1614. [PMID: 29026525 PMCID: PMC5583740 DOI: 10.12688/f1000research.11855.1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/01/2017] [Indexed: 01/01/2023] Open
Abstract
There have been tremendous advances in the diagnosis and treatment of heart disease over the last 50 years. Nevertheless, it remains the number one cause of death. About half of heart-related deaths occur suddenly, and in about half of these cases the person was unaware that they had underlying heart disease. Genetic heart disease accounts for only approximately 2% of sudden cardiac deaths, but as it typically occurs in younger people it has been a particular focus of activity in our quest to not only understand the underlying mechanisms of cardiac arrhythmogenesis but also develop better strategies for earlier detection and prevention. In this brief review, we will highlight trends in the recent literature focused on sudden cardiac death in genetic heart diseases and how these studies are contributing to a broader understanding of sudden death in the community.
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Affiliation(s)
- Jamie I Vandenberg
- St Vincent's Clinical School, University of New South Wales, Darlinghurst, Australia.,Victor Chang Cardiac Research Institute, Darlinghurst, Australia
| | - Matthew D Perry
- St Vincent's Clinical School, University of New South Wales, Darlinghurst, Australia.,Victor Chang Cardiac Research Institute, Darlinghurst, Australia
| | - Adam P Hill
- St Vincent's Clinical School, University of New South Wales, Darlinghurst, Australia.,Victor Chang Cardiac Research Institute, Darlinghurst, Australia
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