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Fullerton KE, Clark AP, Krogh-Madsen T, Christini DJ. Optimization of a cardiomyocyte model illuminates role of increased INa,L in repolarization reserve. Am J Physiol Heart Circ Physiol 2024; 326:H334-H345. [PMID: 38038718 DOI: 10.1152/ajpheart.00553.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 11/15/2023] [Accepted: 11/19/2023] [Indexed: 12/02/2023]
Abstract
Cardiac ion currents may compensate for each other when one is compromised by a congenital or drug-induced defect. Such redundancy contributes to a robust repolarization reserve that can prevent the development of lethal arrhythmias. Most efforts made to describe this phenomenon have quantified contributions by individual ion currents. However, it is important to understand the interplay between all major ion-channel conductances, as repolarization reserve is dependent on the balance between all ion currents in a cardiomyocyte. Here, a genetic algorithm was designed to derive profiles of nine ion-channel conductances that optimize repolarization reserve in a mathematical cardiomyocyte model. Repolarization reserve was quantified using a previously defined metric, repolarization reserve current, i.e., the minimum constant current to prevent normal action potential repolarization in a cell. The optimization improved repolarization reserve current up to 84% compared to baseline in a human adult ventricular myocyte model and increased resistance to arrhythmogenic insult. The optimized conductance profiles were not only characterized by increased repolarizing current conductances but also uncovered a previously unreported behavior by the late sodium current. Simulations demonstrated that upregulated late sodium increased action potential duration, without compromising repolarization reserve current. The finding was generalized to multiple models. Ultimately, this computational approach, in which multiple currents were studied simultaneously, illuminated mechanistic insights into how the metric's magnitude could be increased and allowed for the unexpected role of late sodium to be elucidated.NEW & NOTEWORTHY Genetic algorithms are typically used to fit models or extract desired parameters from data. Here, we use the tool to produce a ventricular cardiomyocyte model with increased repolarization reserve. Since arrhythmia mitigation is dependent on multiple cardiac ion-channel conductances, study using a comprehensive, unbiased, and systems-level approach is important. The use of this optimization strategy allowed us to find robust profiles that illuminated unexpected mechanistic determinants of key ion-channel conductances in repolarization reserve.
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Affiliation(s)
- Kristin E Fullerton
- Physiology, Biophysics and Systems Biology Program, Weill Cornell Graduate School of Medical Sciences, New York, New York, United States
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, New York, United States
| | - Alexander P Clark
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, United States
| | - Trine Krogh-Madsen
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, New York, United States
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, New York, United States
| | - David J Christini
- Department of Physiology and Pharmacology, SUNY Downstate Health Sciences University, Brooklyn, New York, United States
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2
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Zhang Z, Brugada P, Weiss JN, Qu Z. Phase 2 Re-Entry Without I to: Role of Sodium Channel Kinetics in Brugada Syndrome Arrhythmias. JACC Clin Electrophysiol 2023; 9:2459-2474. [PMID: 37831035 DOI: 10.1016/j.jacep.2023.08.027] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 07/27/2023] [Accepted: 08/23/2023] [Indexed: 10/14/2023]
Abstract
BACKGROUND In Brugada syndrome (BrS), phase 2 re-excitation/re-entry (P2R) induced by the transient outward potassium current (Ito) is a proposed arrhythmia mechanism; yet, the most common genetic defects are loss-of-function sodium channel mutations. OBJECTIVES The authors used computer simulations to investigate how sodium channel dysfunction affects P2R-mediated arrhythmogenesis in the presence and absence of Ito. METHODS Computer simulations were carried out in 1-dimensional cables and 2-dimensional tissue using guinea pig and human ventricular action potential models. RESULTS In the presence of Ito sufficient to generate robust P2R, reducing sodium current (INa) peak amplitude alone only slightly potentiated P2R. When INa inactivation kinetics were also altered to simulate reported effects of BrS mutations and sodium channel blockers, however, P2R occurred even in the absence of Ito. These effects could be potentiated by delaying L-type calcium channel activation or increasing ATP-sensitive potassium current, consistent with experimental and clinical findings. INa-mediated P2R also accounted for sex-related, day and night-related, and fever-related differences in arrhythmia risk in BrS patients. CONCLUSIONS Altered INa kinetics synergize powerfully with reduced INa amplitude to promote P2R-induced arrhythmias in BrS in the absence of Ito, establishing a robust mechanistic link between altered INa kinetics and the P2R-mediated arrhythmia mechanism.
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Affiliation(s)
- Zhaoyang Zhang
- Department of Physics, School of Physical Science and Technology, Ningbo University, Ningbo, Zhejiang, China; Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, California, USA
| | - Pedro Brugada
- Heart Rhythm Management Centre, Postgraduate Program in Cardiac Electrophysiology and Pacing, Universitair Ziekenhuis Brussel-Vrije Universiteit Brussel, European Reference Networks Guard-Heart, Brussels, Belgium
| | - James N Weiss
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, California, USA
| | - Zhilin Qu
- Division of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, California, USA.
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3
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Bustos-Aibar M, Aguilera CM, Alcalá-Fdez J, Ruiz-Ojeda FJ, Plaza-Díaz J, Plaza-Florido A, Tofe I, Gil-Campos M, Gacto MJ, Anguita-Ruiz A. Shared gene expression signatures between visceral adipose and skeletal muscle tissues are associated with cardiometabolic traits in children with obesity. Comput Biol Med 2023; 163:107085. [PMID: 37399741 DOI: 10.1016/j.compbiomed.2023.107085] [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: 11/25/2022] [Revised: 04/28/2023] [Accepted: 05/27/2023] [Indexed: 07/05/2023]
Abstract
Obesity in children is related to the development of cardiometabolic complications later in life, where molecular changes of visceral adipose tissue (VAT) and skeletal muscle tissue (SMT) have been proven to be fundamental. The aim of this study is to unveil the gene expression architecture of both tissues in a cohort of Spanish boys with obesity, using a clustering method known as weighted gene co-expression network analysis. For this purpose, we have followed a multi-objective analytic pipeline consisting of three main approaches; identification of gene co-expression clusters associated with childhood obesity, individually in VAT and SMT (intra-tissue, approach I); identification of gene co-expression clusters associated with obesity-metabolic alterations, individually in VAT and SMT (intra-tissue, approach II); and identification of gene co-expression clusters associated with obesity-metabolic alterations simultaneously in VAT and SMT (inter-tissue, approach III). In both tissues, we identified independent and inter-tissue gene co-expression signatures associated with obesity and cardiovascular risk, some of which exceeded multiple-test correction filters. In these signatures, we could identify some central hub genes (e.g., NDUFB8, GUCY1B1, KCNMA1, NPR2, PPP3CC) participating in relevant metabolic pathways exceeding multiple-testing correction filters. We identified the central hub genes PIK3R2, PPP3C and PTPN5 associated with MAPK signaling and insulin resistance terms. This is the first time that these genes have been associated with childhood obesity in both tissues. Therefore, they could be potential novel molecular targets for drugs and health interventions, opening new lines of research on the personalized care in this pathology. This work generates interesting hypotheses about the transcriptomics alterations underlying metabolic health alterations in obesity in the pediatric population.
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Affiliation(s)
- Mireia Bustos-Aibar
- Department of Biochemistry and Molecular Biology II, School of Pharmacy, University of Granada, 18071, Granada, Spain.
| | - Concepción M Aguilera
- Department of Biochemistry and Molecular Biology II, School of Pharmacy, University of Granada, 18071, Granada, Spain; Biomedical Research Networking Center for Physiopathology of Obesity and Nutrition, Carlos III Health Institute, 28029, Madrid, Spain.
| | - Jesús Alcalá-Fdez
- Department of Computer Science and Artificial Intelligence, Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada, 18071, Granada, Spain.
| | - Francisco J Ruiz-Ojeda
- Department of Biochemistry and Molecular Biology II, School of Pharmacy, University of Granada, 18071, Granada, Spain; RG Adipocytes and Metabolism, Institute for Diabetes and Obesity, Helmholtz Diabetes Center at the Helmholtz Zentrum München, Neuherberg, 85764, Munich, Germany.
| | - Julio Plaza-Díaz
- Department of Biochemistry and Molecular Biology II, School of Pharmacy, University of Granada, 18071, Granada, Spain; Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON K1H 8L1, Ontario, Canada.
| | - Abel Plaza-Florido
- PROmoting FITness and Health through physical activity research group, Sport and Health University Research Institute, Department of Physical Education and Sports, University of Granada, 18071, Granada, Spain; Pediatric Exercise and Genomics Research Center, Department of Pediatrics, School of Medicine, University of California at Irvine, Irvine, 92617, CA, United States.
| | - Inés Tofe
- Biomedical Research Networking Center for Physiopathology of Obesity and Nutrition, Carlos III Health Institute, 28029, Madrid, Spain; University Clinical Hospital, Institute Maimónides of Biomedicine Investigation of Córdoba, University of Córdoba, 14004, Córdoba, Spain.
| | - Mercedes Gil-Campos
- Biomedical Research Networking Center for Physiopathology of Obesity and Nutrition, Carlos III Health Institute, 28029, Madrid, Spain; University Clinical Hospital, Institute Maimónides of Biomedicine Investigation of Córdoba, University of Córdoba, 14004, Córdoba, Spain.
| | - María J Gacto
- Department of Software Engineering, University of Granada, 18071, Granada, Spain.
| | - Augusto Anguita-Ruiz
- Department of Biochemistry and Molecular Biology II, School of Pharmacy, University of Granada, 18071, Granada, Spain; Barcelona Institute for Global Health, ISGlobal, 08003, Barcelona, Spain.
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4
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Grandi E, Navedo MF, Saucerman JJ, Bers DM, Chiamvimonvat N, Dixon RE, Dobrev D, Gomez AM, Harraz OF, Hegyi B, Jones DK, Krogh-Madsen T, Murfee WL, Nystoriak MA, Posnack NG, Ripplinger CM, Veeraraghavan R, Weinberg S. Diversity of cells and signals in the cardiovascular system. J Physiol 2023; 601:2547-2592. [PMID: 36744541 PMCID: PMC10313794 DOI: 10.1113/jp284011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 01/19/2023] [Indexed: 02/07/2023] Open
Abstract
This white paper is the outcome of the seventh UC Davis Cardiovascular Research Symposium on Systems Approach to Understanding Cardiovascular Disease and Arrhythmia. This biannual meeting aims to bring together leading experts in subfields of cardiovascular biomedicine to focus on topics of importance to the field. The theme of the 2022 Symposium was 'Cell Diversity in the Cardiovascular System, cell-autonomous and cell-cell signalling'. Experts in the field contributed their experimental and mathematical modelling perspectives and discussed emerging questions, controversies, and challenges in examining cell and signal diversity, co-ordination and interrelationships involved in cardiovascular function. This paper originates from the topics of formal presentations and informal discussions from the Symposium, which aimed to develop a holistic view of how the multiple cell types in the cardiovascular system integrate to influence cardiovascular function, disease progression and therapeutic strategies. The first section describes the major cell types (e.g. cardiomyocytes, vascular smooth muscle and endothelial cells, fibroblasts, neurons, immune cells, etc.) and the signals involved in cardiovascular function. The second section emphasizes the complexity at the subcellular, cellular and system levels in the context of cardiovascular development, ageing and disease. Finally, the third section surveys the technological innovations that allow the interrogation of this diversity and advancing our understanding of the integrated cardiovascular function and dysfunction.
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Affiliation(s)
- Eleonora Grandi
- Department of Pharmacology, University of California Davis, Davis, CA, USA
| | - Manuel F. Navedo
- Department of Pharmacology, University of California Davis, Davis, CA, USA
| | - Jeffrey J. Saucerman
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
| | - Donald M. Bers
- Department of Pharmacology, University of California Davis, Davis, CA, USA
| | - Nipavan Chiamvimonvat
- Department of Pharmacology, University of California Davis, Davis, CA, USA
- Department of Internal Medicine, University of California Davis, Davis, CA, USA
| | - Rose E. Dixon
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA, USA
| | - Dobromir Dobrev
- Institute of Pharmacology, West German Heart and Vascular Center, University Duisburg-Essen, Essen, Germany
- Department of Medicine, Montreal Heart Institute and Université de Montréal, Montréal, Canada
- Department of Molecular Physiology & Biophysics, Baylor College of Medicine, Houston, TX, USA
| | - Ana M. Gomez
- Signaling and Cardiovascular Pathophysiology-UMR-S 1180, INSERM, Université Paris-Saclay, Orsay, France
| | - Osama F. Harraz
- Department of Pharmacology, Larner College of Medicine, and Vermont Center for Cardiovascular and Brain Health, University of Vermont, Burlington, VT, USA
| | - Bence Hegyi
- Department of Pharmacology, University of California Davis, Davis, CA, USA
| | - David K. Jones
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Trine Krogh-Madsen
- Department of Physiology & Biophysics, Weill Cornell Medicine, New York, New York, USA
| | - Walter Lee Murfee
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
| | - Matthew A. Nystoriak
- Department of Medicine, Division of Environmental Medicine, Center for Cardiometabolic Science, University of Louisville, Louisville, KY, 40202, USA
| | - Nikki G. Posnack
- Department of Pediatrics, Department of Pharmacology and Physiology, The George Washington University, Washington, DC, USA
- Sheikh Zayed Institute for Pediatric and Surgical Innovation, Children’s National Heart Institute, Children’s National Hospital, Washington, DC, USA
| | | | - Rengasayee Veeraraghavan
- Department of Biomedical Engineering, The Ohio State University, Columbus, OH, USA
- Dorothy M. Davis Heart & Lung Research Institute, The Ohio State University – Wexner Medical Center, Columbus, OH, USA
| | - Seth Weinberg
- Department of Biomedical Engineering, The Ohio State University, Columbus, OH, USA
- Dorothy M. Davis Heart & Lung Research Institute, The Ohio State University – Wexner Medical Center, Columbus, OH, USA
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5
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Nielsen MS, van Opbergen CJM, van Veen TAB, Delmar M. The intercalated disc: a unique organelle for electromechanical synchrony in cardiomyocytes. Physiol Rev 2023; 103:2271-2319. [PMID: 36731030 PMCID: PMC10191137 DOI: 10.1152/physrev.00021.2022] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 01/24/2023] [Accepted: 01/30/2023] [Indexed: 02/04/2023] Open
Abstract
The intercalated disc (ID) is a highly specialized structure that connects cardiomyocytes via mechanical and electrical junctions. Although described in some detail by light microscopy in the 19th century, it was in 1966 that electron microscopy images showed that the ID represented apposing cell borders and provided detailed insight into the complex ID nanostructure. Since then, much has been learned about the ID and its molecular composition, and it has become evident that a large number of proteins, not all of them involved in direct cell-to-cell coupling via mechanical or gap junctions, reside at the ID. Furthermore, an increasing number of functional interactions between ID components are emerging, leading to the concept that the ID is not the sum of isolated molecular silos but an interacting molecular complex, an "organelle" where components work in concert to bring about electrical and mechanical synchrony. The aim of the present review is to give a short historical account of the ID's discovery and an updated overview of its composition and organization, followed by a discussion of the physiological implications of the ID architecture and the local intermolecular interactions. The latter will focus on both the importance of normal conduction of cardiac action potentials as well as the impact on the pathophysiology of arrhythmias.
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Affiliation(s)
- Morten S Nielsen
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Chantal J M van Opbergen
- The Leon Charney Division of Cardiology, New York University Grossmann School of Medicine, New York, New York, United States
| | - Toon A B van Veen
- Department of Medical Physiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Mario Delmar
- The Leon Charney Division of Cardiology, New York University Grossmann School of Medicine, New York, New York, United States
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6
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Moise N, Weinberg SH. Emergent activity, heterogeneity, and robustness in a calcium feedback model of the sinoatrial node. Biophys J 2023; 122:1613-1632. [PMID: 36945778 PMCID: PMC10183324 DOI: 10.1016/j.bpj.2023.03.024] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 02/16/2023] [Accepted: 03/15/2023] [Indexed: 03/23/2023] Open
Abstract
The sinoatrial node (SAN) is the primary pacemaker of the heart. SAN activity emerges at an early point in life and maintains a steady rhythm for the lifetime of the organism. The ion channel composition and currents of SAN cells can be influenced by a variety of factors. Therefore, the emergent activity and long-term stability imply some form of dynamical feedback control of SAN activity. We adapt a recent feedback model-previously utilized to describe control of ion conductances in neurons-to a model of SAN cells and tissue. The model describes a minimal regulatory mechanism of ion channel conductances via feedback between intracellular calcium and an intrinsic target calcium level. By coupling a SAN cell to the calcium feedback model, we show that spontaneous electrical activity emerges from quiescence and is maintained at steady state. In a 2D SAN tissue model, spatial variability in intracellular calcium targets lead to significant, self-organized heterogeneous ion channel expression and calcium transients throughout the tissue. Furthermore, multiple pacemaking regions appear, which interact and lead to time-varying cycle length, demonstrating that variability in heart rate is an emergent property of the feedback model. Finally, we demonstrate that the SAN tissue is robust to the silencing of leading cells or ion channel knockouts. Thus, the calcium feedback model can reproduce and explain many fundamental emergent properties of activity in the SAN that have been observed experimentally based on a minimal description of intracellular calcium and ion channel regulatory networks.
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Affiliation(s)
- Nicolae Moise
- Department of Biomedical Engineering, The Ohio State University, Columbus, Ohio; Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, Ohio
| | - Seth H Weinberg
- Department of Biomedical Engineering, The Ohio State University, Columbus, Ohio; Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, Ohio.
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7
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Yang L, Liu J, Yu Y, Liu S. A novel signature of autophagy-related immunophenotyping biomarkers in osteoarthritis. Life Sci 2023; 321:121599. [PMID: 36966915 DOI: 10.1016/j.lfs.2023.121599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 03/07/2023] [Accepted: 03/15/2023] [Indexed: 04/03/2023]
Abstract
AIMS We aimed to provide an autophagy-related signature to seek immunophenotyping biomarkers in osteoarthritis (OA). MATERIALS AND METHODS Microarray expression profiling of OA subchondral bone samples and screening of an autophagy database for autophagy-related differentially expressed genes (au-DEGs) between OA and normal samples were performed. A weighted gene co-expression network analysis (WGCNA) was constructed using au-DEGs to identify key modules significantly associated with clinical information of OA samples. OA-related autophagy hub genes were identified based on the connectivity with the phenotypes of genes in key modules and the protein-protein interaction (PPI) network in which the genes in the modules are involved, followed by feasibility verification of autophagy hub genes by bioinformatics analysis and biological experiments. KEY FINDINGS We screened 754 au-DEGs between OA and control samples, and co-expression networks were constructed using au-DEGs. Three OA-related autophagy hub genes (HSPA5, HSP90AA1, and ITPKB) were identified. Based on the hub gene expression profiles, OA samples were divided into two clusters with significantly different expression profiles and distinct immunological features, and the three hub genes were significantly differentially expressed between the clusters. Differences in hub genes between OA and control samples regarding sex, age, and grades of OA were examined using external datasets and experimental validation. SIGNIFICANCE Three autophagy-related markers of OA were identified using bioinformatics methods, and these markers may be useful for the autophagy-related immunophenotyping of OA. The present data may facilitate the diagnosis of OA, as well as the design of immunotherapies and individualized medical treatments.
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Affiliation(s)
- Liyu Yang
- Department of Orthopedics, The Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, PR China.
| | - Jiamei Liu
- Department of Pathology, The Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, PR China.
| | - Yuanqi Yu
- Department of Clinical Medicine, Innovation Institute of China Medical University, Shenyang, Liaoning 110122, PR China.
| | - Shengye Liu
- Department of Orthopedics, The Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, PR China.
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8
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Miller JA, Moise N, Weinberg SH. Modeling incomplete penetrance in long QT syndrome type 3 through ion channel heterogeneity: an in silico population study. Am J Physiol Heart Circ Physiol 2023; 324:H179-H197. [PMID: 36487185 PMCID: PMC10072004 DOI: 10.1152/ajpheart.00430.2022] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 11/16/2022] [Accepted: 11/29/2022] [Indexed: 12/14/2022]
Abstract
Many cardiac diseases are characterized by an increased late sodium current, including heart failure, hypertrophic cardiomyopathy, and inherited long QT syndrome type 3 (LQT3). The late sodium current in LQT3 is caused by a gain-of-function mutation in the voltage-gated sodium channel Nav1.5. Despite a well-defined genetic cause of LQT3, treatment remains inconsistent because of incomplete penetrance of the mutation and variability of antiarrhythmic efficacy. Here, we investigate the relationship between LQT3-associated mutation incomplete penetrance and variability in ion channel expression, simulating a population of 1,000 individuals with the O'Hara-Rudy model of the human ventricular myocyte. We first simulate healthy electrical activity (i.e., in the absence of a mutation) and then incorporate heterozygous expression for three LQT3-associated mutations (Y1795C, I1768V, and ΔKPQ), to directly compare the effects of each mutation on individuals across a diverse population. For all mutations, we find that susceptibility, defined by either the presence of an early afterdepolarization (EAD) or prolonged action potential duration (APD), primarily depends on the balance between the conductance of IKr and INa, for which individuals with a higher IKr-to-INa ratio are less susceptible. Furthermore, we find distinct differences across the population, observing individuals susceptible to zero, one, two, or all three mutations. Individuals tend to be less susceptible with an appropriate balance of repolarizing currents, typically via increased IKs or IK1. Interestingly, the more critical repolarizing current is mutation specific. We conclude that the balance between key currents plays a significant role in mutant-specific presentation of the disease phenotype in LQT3.NEW & NOTEWORTHY An in silico population approach investigates the relationship between variability in ion channel expression and gain-of-function mutations in the voltage-gated sodium channel associated with the congenital disorder long QT syndrome type 3 (LQT3). We find that ion channel variability can contribute to incomplete penetrance of the mutation, with mutant-specific differences in ion channel conductances leading to susceptibility to proarrhythmic action potential duration prolongation or early afterdepolarizations.
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Affiliation(s)
- Jacob A Miller
- Department of Biomedical Engineering, The Ohio State University, Columbus, Ohio
| | - Nicolae Moise
- Department of Biomedical Engineering, The Ohio State University, Columbus, Ohio
| | - Seth H Weinberg
- Department of Biomedical Engineering, The Ohio State University, Columbus, Ohio
- Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, Ohio
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9
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Lachaud Q, Aziz MHN, Burton FL, Macquaide N, Myles RC, Simitev RD, Smith GL. Electrophysiological heterogeneity in large populations of rabbit ventricular cardiomyocytes. Cardiovasc Res 2022; 118:3112-3125. [PMID: 35020837 PMCID: PMC9732512 DOI: 10.1093/cvr/cvab375] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 01/07/2022] [Indexed: 01/01/2023] Open
Abstract
AIMS Cardiac electrophysiological heterogeneity includes: (i) regional differences in action potential (AP) waveform, (ii) AP waveform differences in cells isolated from a single region, (iii) variability of the contribution of individual ion currents in cells with similar AP durations (APDs). The aim of this study is to assess intra-regional AP waveform differences, to quantify the contribution of specific ion channels to the APD via drug responses and to generate a population of mathematical models to investigate the mechanisms underlying heterogeneity in rabbit ventricular cells. METHODS AND RESULTS APD in ∼50 isolated cells from subregions of the LV free wall of rabbit hearts were measured using a voltage-sensitive dye. When stimulated at 2 Hz, average APD90 value in cells from the basal epicardial region was 254 ± 25 ms (mean ± standard deviation) in 17 hearts with a mean interquartile range (IQR) of 53 ± 17 ms. Endo-epicardial and apical-basal APD90 differences accounted for ∼10% of the IQR value. Highly variable changes in APD occurred after IK(r) or ICa(L) block that included a sub-population of cells (HR) with an exaggerated (hyper) response to IK(r) inhibition. A set of 4471 AP models matching the experimental APD90 distribution was generated from a larger population of models created by random variation of the maximum conductances (Gmax) of 8 key ion channels/exchangers/pumps. This set reproduced the pattern of cell-specific responses to ICa(L) and IK(r) block, including the HR sub-population. The models exhibited a wide range of Gmax values with constrained relationships linking ICa(L) with IK(r), ICl, INCX, and INaK. CONCLUSION Modelling the measured range of inter-cell APDs required a larger range of key Gmax values indicating that ventricular tissue has considerable inter-cell variation in channel/pump/exchanger activity. AP morphology is retained by relationships linking specific ionic conductances. These interrelationships are necessary for stable repolarization despite large inter-cell variation of individual conductances and this explains the variable sensitivity to ion channel block.
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Affiliation(s)
- Quentin Lachaud
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Muhamad Hifzhudin Noor Aziz
- School of Mathematics and Statistics, University of Glasgow, Glasgow, UK
- Institute of Mathematical Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia
| | - Francis L Burton
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Niall Macquaide
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
- School of Health and Life Sciences, Glasgow Caledonian University, Glasgow, UK
| | - Rachel C Myles
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Radostin D Simitev
- School of Mathematics and Statistics, University of Glasgow, Glasgow, UK
| | - Godfrey L Smith
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
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10
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Chen H, Zhang J, Sun X, Wang Y, Qian Y. Mitophagy-mediated molecular subtypes depict the hallmarks of the tumour metabolism and guide precision chemotherapy in pancreatic adenocarcinoma. Front Cell Dev Biol 2022; 10:901207. [PMID: 35938160 PMCID: PMC9353335 DOI: 10.3389/fcell.2022.901207] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 06/30/2022] [Indexed: 11/16/2022] Open
Abstract
Background: Mitophagy is closely related to cancer initiation and progression. However, heterogeneity with reference to mitophagy remains unexplored in pancreatic adenocarcinoma (PAAD). Materials and methods: We used Reactome database to download the mitophagy-related, glycolysis-related and cholesterol biosynthesis-related signaling pathways. Unsupervised clustering using the “ConsensusClusterPlus” R package was performed to identify molecular subtypes related to mitophagy and metabolism. Prognosis-related mitophagy regulators were identified by univariate Cox regression analysis. Receiver operating characteristics (ROC) and Kaplan-Meier (K-M) survival analyses were used to assess the diagnostic and prognostic role of the hub genes and prognosis risk model. Weighted gene co-expression network analysis (WGCNA) was utilized for screening the mitophagy subtype-related hub genes. Metascape was utilized to carry out functional enrichment analysis. The “glmnet” R package was utilised for LASSO, and the “e1071” R package was utilised for SVM. Chemotherapeutic drug sensitivity was estimated using the R package “pRRophetic” and Genomics of Drug Sensitivity in Cancer (GDSC) database. The nomogram was established by the “rms” R package. Results: Three distinct mitophagy subtypes (low, high and intermediate) of PAAD were identified based on the landscape of mitophagy regulators. The high mitophagy subtype had the worst prognosis, highest mRNA expression-based stemness index scores and most hypoxic environment compared to the other subtypes. Additionally, glycolysis and cholesterol biosynthesis were significantly elevated. Three mitophagy subtype-specific gene signatures (CAST, CCDC6, and ERLIN1) were extracted using WGCNA and machine learning. Moreover, PAAD tumours were insensitive to Erlotinib, Sunitinib and Imatinib in the high mitophagy subtype and high CAST, CCDC6, and ERLIN1 expressed subtypes. Furthermore, CAST, CCDC6, and ERLIN1 affected immune cell infiltration (M1 and CD8Tcm), resulting in the altered prognosis of patients with PAAD. A nomogram was constructed to screen patients with the low mitophagy subtype, which showed a higher sensitivity to chemotherapeutic agents. Conclusion: Based on various bioinformatics tools and databases, the PAAD heterogeneity regarding mitophagy was systematically examined. Three different PAAD subtypes having different outcomes, metabolism patterns and chemosensitivity were observed. Moreover, three novel biomarkers that are closely associated with mitophagy and have the potential to guide individualised treatment regimens in PAAD were obtained.
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Affiliation(s)
- Hao Chen
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- Department of Emergency Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Jianlin Zhang
- Department of Emergency Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xuehu Sun
- Department of Emergency Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yao Wang
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- *Correspondence: Yeben Qian, ; Yao Wang,
| | - Yeben Qian
- Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- *Correspondence: Yeben Qian, ; Yao Wang,
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11
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Transcriptome Analysis of Populus euphratica under Salt Treatment and PeERF1 Gene Enhances Salt Tolerance in Transgenic Populus alba × Populus glandulosa. Int J Mol Sci 2022; 23:ijms23073727. [PMID: 35409087 PMCID: PMC8998595 DOI: 10.3390/ijms23073727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 03/24/2022] [Accepted: 03/24/2022] [Indexed: 12/02/2022] Open
Abstract
Populus euphratica is mainly distributed in desert environments with dry and hot climate in summer and cold in winter. Compared with other poplars, P. euphratica is more resistant to salt stress. It is critical to investigate the transcriptome and molecular basis of salt tolerance in order to uncover stress-related genes. In this study, salt-tolerant treatment of P. euphratica resulted in an increase in osmo-regulatory substances and recovery of antioxidant enzymes. To improve the mining efficiency of candidate genes, the analysis combining both the transcriptome WGCNA and the former GWAS results was selected, and a range of key regulatory factors with salt resistance were found. The PeERF1 gene was highly connected in the turquoise modules with significant differences in salt stress traits, and the expression levels were significantly different in each treatment. For further functional verification of PeERF1, we obtained stable overexpression and dominant suppression transgenic lines by transforming into Populus alba × Populusglandulosa. The growth and physiological characteristics of the PeERF1 overexpressed plants were better than that of the wild type under salt stress. Transcriptome analysis of leaves of transgenic lines and WT revealed that highly enriched GO terms in DEGs were associated with stress responses, including abiotic stimuli responses, chemical responses, and oxidative stress responses. The result is helpful for in-depth analysis of the salt tolerance mechanism of poplar. This work provides important genes for poplar breeding with salt tolerance.
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12
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Zhang Z, Liu MB, Huang X, Song Z, Qu Z. Mechanisms of Premature Ventricular Complexes Caused by QT Prolongation. Biophys J 2020; 120:352-369. [PMID: 33333033 DOI: 10.1016/j.bpj.2020.12.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 11/18/2020] [Accepted: 12/08/2020] [Indexed: 11/26/2022] Open
Abstract
QT prolongation, due to lengthening of the action potential duration in the ventricles, is a major risk factor of lethal ventricular arrhythmias. A widely known consequence of QT prolongation is the genesis of early afterdepolarizations (EADs), which are associated with arrhythmias through the generation of premature ventricular complexes (PVCs). However, the vast majority of the EADs observed experimentally in isolated ventricular myocytes are phase-2 EADs, and whether phase-2 EADs are mechanistically linked to PVCs in cardiac tissue remains an unanswered question. In this study, we investigate the genesis of PVCs using computer simulations with eight different ventricular action potential models of various species. Based on our results, we classify PVCs as arising from two distinct mechanisms: repolarization gradient (RG)-induced PVCs and phase-2 EAD-induced PVCs. The RG-induced PVCs are promoted by increasing RG and L-type calcium current and are insensitive to gap junction coupling. EADs are not required for this PVC mechanism. In a paced beat, a single or multiple PVCs can occur depending on the properties of the RG. In contrast, phase-2 EAD-induced PVCs occur only when the RG is small and are suppressed by increasing RG and more sensitive to gap junction coupling. Unlike with RG-induced PVCs, in each paced beat, only a single EAD-induced PVC can occur no matter how many EADs in an action potential. In the wide parameter ranges we explore, RG-induced PVCs can be observed in all models, but the EAD-induced PVCs can only be observed in five of the eight models. The links between these two distinct PVC mechanisms and arrhythmogenesis in animal experiments and clinical settings are discussed.
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Affiliation(s)
- Zhaoyang Zhang
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, California
| | - Michael B Liu
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, California
| | - Xiaodong Huang
- Department of Physics, South China University of Technology, Guangzhou, China
| | - Zhen Song
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, California
| | - Zhilin Qu
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, California; Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, California.
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13
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Khomtchouk BB, Tran DT, Vand KA, Might M, Gozani O, Assimes TL. Cardioinformatics: the nexus of bioinformatics and precision cardiology. Brief Bioinform 2020; 21:2031-2051. [PMID: 31802103 PMCID: PMC7947182 DOI: 10.1093/bib/bbz119] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Revised: 08/08/2019] [Accepted: 08/13/2019] [Indexed: 12/12/2022] Open
Abstract
Cardiovascular disease (CVD) is the leading cause of death worldwide, causing over 17 million deaths per year, which outpaces global cancer mortality rates. Despite these sobering statistics, most bioinformatics and computational biology research and funding to date has been concentrated predominantly on cancer research, with a relatively modest footprint in CVD. In this paper, we review the existing literary landscape and critically assess the unmet need to further develop an emerging field at the multidisciplinary interface of bioinformatics and precision cardiovascular medicine, which we refer to as 'cardioinformatics'.
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Affiliation(s)
- Bohdan B Khomtchouk
- Department of Biology, Stanford University, Stanford, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, CA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Section of Computational Biomedicine and Biomedical Data Science, University of Chicago, Chicago, IL, USA
| | - Diem-Trang Tran
- School of Computing, University of Utah, Salt Lake City, UT, USA
| | | | - Matthew Might
- Hugh Kaul Personalized Medicine Institute, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Or Gozani
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Themistocles L Assimes
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, CA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
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14
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Ballouz S, Mangala MM, Perry MD, Heitmann S, Gillis JA, Hill AP, Vandenberg JI. Co-expression of calcium and hERG potassium channels reduces the incidence of proarrhythmic events. Cardiovasc Res 2020; 117:2216-2227. [PMID: 33002116 DOI: 10.1093/cvr/cvaa280] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Revised: 08/25/2020] [Accepted: 09/17/2020] [Indexed: 01/02/2023] Open
Abstract
AIMS Cardiac electrical activity is extraordinarily robust. However, when it goes wrong it can have fatal consequences. Electrical activity in the heart is controlled by the carefully orchestrated activity of more than a dozen different ion conductances. While there is considerable variability in cardiac ion channel expression levels between individuals, studies in rodents have indicated that there are modules of ion channels whose expression co-vary. The aim of this study was to investigate whether meta-analytic co-expression analysis of large-scale gene expression datasets could identify modules of co-expressed cardiac ion channel genes in human hearts that are of functional importance. METHODS AND RESULTS Meta-analysis of 3653 public human RNA-seq datasets identified a strong correlation between expression of CACNA1C (L-type calcium current, ICaL) and KCNH2 (rapid delayed rectifier K+ current, IKr), which was also observed in human adult heart tissue samples. In silico modelling suggested that co-expression of CACNA1C and KCNH2 would limit the variability in action potential duration seen with variations in expression of ion channel genes and reduce susceptibility to early afterdepolarizations, a surrogate marker for proarrhythmia. We also found that levels of KCNH2 and CACNA1C expression are correlated in human-induced pluripotent stem cell-derived cardiac myocytes and the levels of CACNA1C and KCNH2 expression were inversely correlated with the magnitude of changes in repolarization duration following inhibition of IKr. CONCLUSION Meta-analytic approaches of multiple independent human gene expression datasets can be used to identify gene modules that are important for regulating heart function. Specifically, we have verified that there is co-expression of CACNA1C and KCNH2 ion channel genes in human heart tissue, and in silico analyses suggest that CACNA1C-KCNH2 co-expression increases the robustness of cardiac electrical activity.
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Affiliation(s)
- Sara Ballouz
- Garvan-Weizmann Centre for Cellular Genomics, Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst NSW 2010, Australia.,University of New South Wales, Sydney, Kensington, NSW 2052, Australia.,Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, One Bungtown Road, NY 11724, USA
| | - Melissa M Mangala
- Victor Chang Cardiac Research Institute, Lowy Packer Building, 405 Liverpool Street, Darlinghurst, New South Wales 2010, Australia
| | - Matthew D Perry
- University of New South Wales, Sydney, Kensington, NSW 2052, Australia.,Victor Chang Cardiac Research Institute, Lowy Packer Building, 405 Liverpool Street, Darlinghurst, New South Wales 2010, Australia
| | - Stewart Heitmann
- Victor Chang Cardiac Research Institute, Lowy Packer Building, 405 Liverpool Street, Darlinghurst, New South Wales 2010, Australia
| | - Jesse A Gillis
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, One Bungtown Road, NY 11724, USA
| | - Adam P Hill
- University of New South Wales, Sydney, Kensington, NSW 2052, Australia.,Victor Chang Cardiac Research Institute, Lowy Packer Building, 405 Liverpool Street, Darlinghurst, New South Wales 2010, Australia
| | - Jamie I Vandenberg
- University of New South Wales, Sydney, Kensington, NSW 2052, Australia.,Victor Chang Cardiac Research Institute, Lowy Packer Building, 405 Liverpool Street, Darlinghurst, New South Wales 2010, Australia
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15
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Ljubojevic-Holzer S, Herren AW, Djalinac N, Voglhuber J, Morotti S, Holzer M, Wood BM, Abdellatif M, Matzer I, Sacherer M, Radulovic S, Wallner M, Ivanov M, Wagner S, Sossalla S, von Lewinski D, Pieske B, Brown JH, Sedej S, Bossuyt J, Bers DM. CaMKIIδC Drives Early Adaptive Ca 2+ Change and Late Eccentric Cardiac Hypertrophy. Circ Res 2020; 127:1159-1178. [PMID: 32821022 PMCID: PMC7547876 DOI: 10.1161/circresaha.120.316947] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Supplemental Digital Content is available in the text. CaMKII (Ca2+-Calmodulin dependent protein kinase) δC activation is implicated in pathological progression of heart failure (HF) and CaMKIIδC transgenic mice rapidly develop HF and arrhythmias. However, little is known about early spatio-temporal Ca2+ handling and CaMKII activation in hypertrophy and HF.
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Affiliation(s)
- Senka Ljubojevic-Holzer
- Department of Cardiology (S.L.-H., N.D., J.V., M.A., I.M., M.S., S.R., M.W., D.v.L., S. Sedej), Medical University of Graz, Austria.,Department of Pharmacology, University of California, Davis, CA (S.L.-H., A.W.H., S.M., B.M.W., J.B., D.M.B.).,BioTechMed Graz, Austria (S.L.-H., J.V., S. Sedej)
| | - Anthony W Herren
- Department of Pharmacology, University of California, Davis, CA (S.L.-H., A.W.H., S.M., B.M.W., J.B., D.M.B.)
| | - Natasa Djalinac
- Department of Cardiology (S.L.-H., N.D., J.V., M.A., I.M., M.S., S.R., M.W., D.v.L., S. Sedej), Medical University of Graz, Austria
| | - Julia Voglhuber
- Department of Cardiology (S.L.-H., N.D., J.V., M.A., I.M., M.S., S.R., M.W., D.v.L., S. Sedej), Medical University of Graz, Austria.,BioTechMed Graz, Austria (S.L.-H., J.V., S. Sedej)
| | - Stefano Morotti
- Department of Pharmacology, University of California, Davis, CA (S.L.-H., A.W.H., S.M., B.M.W., J.B., D.M.B.)
| | - Michael Holzer
- Otto-Loewi Research Centre, Division of Pharmacology (M.H.), Medical University of Graz, Austria
| | - Brent M Wood
- Department of Pharmacology, University of California, Davis, CA (S.L.-H., A.W.H., S.M., B.M.W., J.B., D.M.B.)
| | - Mahmoud Abdellatif
- Department of Cardiology (S.L.-H., N.D., J.V., M.A., I.M., M.S., S.R., M.W., D.v.L., S. Sedej), Medical University of Graz, Austria
| | - Ingrid Matzer
- Department of Cardiology (S.L.-H., N.D., J.V., M.A., I.M., M.S., S.R., M.W., D.v.L., S. Sedej), Medical University of Graz, Austria
| | - Michael Sacherer
- Department of Cardiology (S.L.-H., N.D., J.V., M.A., I.M., M.S., S.R., M.W., D.v.L., S. Sedej), Medical University of Graz, Austria
| | - Snjezana Radulovic
- Department of Cardiology (S.L.-H., N.D., J.V., M.A., I.M., M.S., S.R., M.W., D.v.L., S. Sedej), Medical University of Graz, Austria
| | - Markus Wallner
- Department of Cardiology (S.L.-H., N.D., J.V., M.A., I.M., M.S., S.R., M.W., D.v.L., S. Sedej), Medical University of Graz, Austria
| | - Milan Ivanov
- Institute for Medical Research, University of Belgrade, Serbia (M.I.)
| | - Stefan Wagner
- Klinik und Poliklinik für Innere Medizin II, Universitätsklinikum Regensburg, Germany (S.W., S. Sossalla)
| | - Samuel Sossalla
- Klinik für Kardiologie und Pneumologie, Georg-August-Universität Göttingen, Germany (S. Sossalla).,Klinik und Poliklinik für Innere Medizin II, Universitätsklinikum Regensburg, Germany (S.W., S. Sossalla)
| | - Dirk von Lewinski
- Department of Cardiology (S.L.-H., N.D., J.V., M.A., I.M., M.S., S.R., M.W., D.v.L., S. Sedej), Medical University of Graz, Austria
| | - Burkert Pieske
- Department of Internal Medicine and Cardiology, Charité University Medicine Berlin, Germany (B.P.)
| | - Joan Heller Brown
- Department of Pharmacology, University of California San Diego, La Jolla (J.H.B.)
| | - Simon Sedej
- Department of Cardiology (S.L.-H., N.D., J.V., M.A., I.M., M.S., S.R., M.W., D.v.L., S. Sedej), Medical University of Graz, Austria.,BioTechMed Graz, Austria (S.L.-H., J.V., S. Sedej).,Faculty of Medicine, Institute of Physiology, University of Maribor, Slovenia (S. Sedej)
| | - Julie Bossuyt
- Department of Pharmacology, University of California, Davis, CA (S.L.-H., A.W.H., S.M., B.M.W., J.B., D.M.B.)
| | - Donald M Bers
- Department of Pharmacology, University of California, Davis, CA (S.L.-H., A.W.H., S.M., B.M.W., J.B., D.M.B.)
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16
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Whittaker DG, Clerx M, Lei CL, Christini DJ, Mirams GR. Calibration of ionic and cellular cardiac electrophysiology models. WILEY INTERDISCIPLINARY REVIEWS. SYSTEMS BIOLOGY AND MEDICINE 2020; 12:e1482. [PMID: 32084308 PMCID: PMC8614115 DOI: 10.1002/wsbm.1482] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Revised: 01/17/2020] [Accepted: 01/18/2020] [Indexed: 12/30/2022]
Abstract
Cardiac electrophysiology models are among the most mature and well-studied mathematical models of biological systems. This maturity is bringing new challenges as models are being used increasingly to make quantitative rather than qualitative predictions. As such, calibrating the parameters within ion current and action potential (AP) models to experimental data sets is a crucial step in constructing a predictive model. This review highlights some of the fundamental concepts in cardiac model calibration and is intended to be readily understood by computational and mathematical modelers working in other fields of biology. We discuss the classic and latest approaches to calibration in the electrophysiology field, at both the ion channel and cellular AP scales. We end with a discussion of the many challenges that work to date has raised and the need for reproducible descriptions of the calibration process to enable models to be recalibrated to new data sets and built upon for new studies. This article is categorized under: Analytical and Computational Methods > Computational Methods Physiology > Mammalian Physiology in Health and Disease Models of Systems Properties and Processes > Cellular Models.
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Affiliation(s)
- Dominic G. Whittaker
- Centre for Mathematical Medicine & Biology, School of Mathematical SciencesUniversity of NottinghamNottinghamUK
| | - Michael Clerx
- Computational Biology & Health Informatics, Department of Computer ScienceUniversity of OxfordOxfordUK
| | - Chon Lok Lei
- Computational Biology & Health Informatics, Department of Computer ScienceUniversity of OxfordOxfordUK
| | | | - Gary R. Mirams
- Centre for Mathematical Medicine & Biology, School of Mathematical SciencesUniversity of NottinghamNottinghamUK
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17
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Smirnov D, Pikunov A, Syunyaev R, Deviatiiarov R, Gusev O, Aras K, Gams A, Koppel A, Efimov IR. Genetic algorithm-based personalized models of human cardiac action potential. PLoS One 2020; 15:e0231695. [PMID: 32392258 PMCID: PMC7213718 DOI: 10.1371/journal.pone.0231695] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Accepted: 03/31/2020] [Indexed: 11/21/2022] Open
Abstract
We present a novel modification of genetic algorithm (GA) which determines personalized parameters of cardiomyocyte electrophysiology model based on set of experimental human action potential (AP) recorded at different heart rates. In order to find the steady state solution, the optimized algorithm performs simultaneous search in the parametric and slow variables spaces. We demonstrate that several GA modifications are required for effective convergence. Firstly, we used Cauchy mutation along a random direction in the parametric space. Secondly, relatively large number of elite organisms (6-10% of the population passed on to new generation) was required for effective convergence. Test runs with synthetic AP as input data indicate that algorithm error is low for high amplitude ionic currents (1.6±1.6% for IKr, 3.2±3.5% for IK1, 3.9±3.5% for INa, 8.2±6.3% for ICaL). Experimental signal-to-noise ratio above 28 dB was required for high quality GA performance. GA was validated against optical mapping recordings of human ventricular AP and mRNA expression profile of donor hearts. In particular, GA output parameters were rescaled proportionally to mRNA levels ratio between patients. We have demonstrated that mRNA-based models predict the AP waveform dependence on heart rate with high precision. The latter also provides a novel technique of model personalization that makes it possible to map gene expression profile to cardiac function.
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Affiliation(s)
- Dmitrii Smirnov
- Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | - Andrey Pikunov
- Moscow Institute of Physics and Technology, Dolgoprudny, Russia
| | - Roman Syunyaev
- Moscow Institute of Physics and Technology, Dolgoprudny, Russia
- The George Washington University, Washington, DC, United States of America
- Sechenov University, Moscow, Russia
| | | | | | - Kedar Aras
- The George Washington University, Washington, DC, United States of America
| | - Anna Gams
- The George Washington University, Washington, DC, United States of America
| | - Aaron Koppel
- The George Washington University, Washington, DC, United States of America
| | - Igor R. Efimov
- Moscow Institute of Physics and Technology, Dolgoprudny, Russia
- The George Washington University, Washington, DC, United States of America
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18
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Anguita-Ruiz A, Segura-Delgado A, Alcalá R, Aguilera CM, Alcalá-Fdez J. eXplainable Artificial Intelligence (XAI) for the identification of biologically relevant gene expression patterns in longitudinal human studies, insights from obesity research. PLoS Comput Biol 2020; 16:e1007792. [PMID: 32275707 PMCID: PMC7176286 DOI: 10.1371/journal.pcbi.1007792] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 04/22/2020] [Accepted: 03/17/2020] [Indexed: 12/18/2022] Open
Abstract
Until date, several machine learning approaches have been proposed for the dynamic modeling of temporal omics data. Although they have yielded impressive results in terms of model accuracy and predictive ability, most of these applications are based on "Black-box" algorithms and more interpretable models have been claimed by the research community. The recent eXplainable Artificial Intelligence (XAI) revolution offers a solution for this issue, were rule-based approaches are highly suitable for explanatory purposes. The further integration of the data mining process along with functional-annotation and pathway analyses is an additional way towards more explanatory and biologically soundness models. In this paper, we present a novel rule-based XAI strategy (including pre-processing, knowledge-extraction and functional validation) for finding biologically relevant sequential patterns from longitudinal human gene expression data (GED). To illustrate the performance of our pipeline, we work on in vivo temporal GED collected within the course of a long-term dietary intervention in 57 subjects with obesity (GSE77962). As validation populations, we employ three independent datasets following the same experimental design. As a result, we validate primarily extracted gene patterns and prove the goodness of our strategy for the mining of biologically relevant gene-gene temporal relations. Our whole pipeline has been gathered under open-source software and could be easily extended to other human temporal GED applications.
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Affiliation(s)
- Augusto Anguita-Ruiz
- Department of Biochemistry and Molecular Biology II, Institute of Nutrition and Food Technology "José Mataix", Center of Biomedical Research, University of Granada, Granada, Spain
- Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain
- CIBEROBN (Physiopathology of Obesity and Nutrition), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Alberto Segura-Delgado
- Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain
| | - Rafael Alcalá
- Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain
| | - Concepción M. Aguilera
- Department of Biochemistry and Molecular Biology II, Institute of Nutrition and Food Technology "José Mataix", Center of Biomedical Research, University of Granada, Granada, Spain
- Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain
- CIBEROBN (Physiopathology of Obesity and Nutrition), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Jesús Alcalá-Fdez
- Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain
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19
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High-throughput phenotyping of heteromeric human ether-à-go-go-related gene potassium channel variants can discriminate pathogenic from rare benign variants. Heart Rhythm 2020; 17:492-500. [DOI: 10.1016/j.hrthm.2019.09.020] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Indexed: 12/19/2022]
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20
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Filipe JAN, Kyriazakis I. Bayesian, Likelihood-Free Modelling of Phenotypic Plasticity and Variability in Individuals and Populations. Front Genet 2019; 10:727. [PMID: 31616460 PMCID: PMC6764410 DOI: 10.3389/fgene.2019.00727] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Accepted: 07/11/2019] [Indexed: 12/17/2022] Open
Abstract
There is a paradigm shift from the traditional focus on the “average” individual towards the definition and analysis of trait variation within individual life-history and among individuals in populations. This is a result of increasing availability of individual phenotypic data. The shift allows the use of genetic and environment-driven variations to assess robustness to challenge, gain greater understanding of organismal biological processes, or deliver individual-targeted treatments or genetic selection. These consequences apply, in particular, to variation in ontogenetic growth. We propose an approach to parameterise mathematical models of individual traits (e.g., reaction norms, growth curves) that address two challenges: 1) Estimation of individual traits while making minimal assumptions about data distribution and correlation, addressed via Approximate Bayesian Computation (a form of nonparametric inference). We are motivated by the fact that available information on distribution of biological data is often less precise than assumed by conventional likelihood functions. 2) Scaling-up to population phenotype distributions while facilitating unbiased use of individual data; this is addressed via a probabilistic framework where population distributions build on separately-inferred individual distributions and individual-trait interpretability is preserved. The approach is tested against Bayesian likelihood-based inference, by fitting weight and energy intake growth models to animal data and normal- and skewed-distributed simulated data. i) Individual inferences were accurate and robust to changes in data distribution and sample size; in particular, median-based predictions were more robust than maximum- likelihood-based curves. These results suggest that the approach gives reliable inferences using few observations and monitoring resources. ii) At the population level, each individual contributed via a specific data distribution, and population phenotype estimates were not disproportionally influenced by outlier individuals. Indices measuring population phenotype variation can be derived for study comparisons. The approach offers an alternative for estimating trait variability in biological systems that may be reliable for various applications, for example, in genetics, health, and individualised nutrition, while using fewer assumptions and fewer empirical observations. In livestock breeding, the potentially greater accuracy of trait estimation (without specification of multitrait variance-covariance parameters) could lead to improved selection and to more decisive estimates of trait heritability.
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Affiliation(s)
- Joao A N Filipe
- Agriculture, School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Ilias Kyriazakis
- Agriculture, School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
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21
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Weinheimer CJ, Kovacs A, Evans S, Matkovich SJ, Barger PM, Mann DL. Load-Dependent Changes in Left Ventricular Structure and Function in a Pathophysiologically Relevant Murine Model of Reversible Heart Failure. Circ Heart Fail 2019; 11:e004351. [PMID: 29716898 DOI: 10.1161/circheartfailure.117.004351] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Accepted: 03/22/2018] [Indexed: 01/19/2023]
Abstract
BACKGROUND To better understand reverse left ventricular (LV) remodeling, we developed a murine model wherein mice develop LV remodeling after transverse aortic constriction (TAC) and a small apical myocardial infarct (MI) and undergo reverse LV remodeling after removal of the aortic band. METHODS AND RESULTS Mice studied were subjected to sham (n=6) surgery or TAC+MI (n=12). Two weeks post-TAC+MI, 1 group underwent debanding (referred to as heart failure debanding [HF-DB] mice; n=6), whereas the aortic band remained in a second group (heart failure [HF] group; n=6). LV remodeling was evaluated by 2D echocardiography at 1 day, 2 weeks and 6 weeks post-TAC+MI. The hearts were analyzed by transcriptional profiling at 4 and 6 weeks and histologically at 6 weeks. Debanding normalized LV volumes, LV mass, and cardiac myocyte hypertrophy at 6 weeks in HF-DB mice, with no difference in myofibrillar collagen in the HF and HF-DB mice. LV ejection fraction and radial strain improved after debanding; however, both remained decreased in the HF-DB mice relative to sham and were not different from HF mice at 6 weeks. Hemodynamic unloading in the HF-DB mice was accompanied by a 35% normalization of the HF genes at 2 weeks and 80% of the HF genes at 4 weeks. CONCLUSIONS Hemodynamic unloading of a pathophysiologically relevant mouse model of HF results in normalization of LV structure, incomplete recovery of LV function, and incomplete reversal of the HF transcriptional program. The HF-DB mouse model may provide novel insights into mechanisms of reverse LV remodeling.
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Affiliation(s)
- Carla J Weinheimer
- Center for Cardiovascular Research, Cardiovascular Division, Washington University School of Medicine, St. Louis, MO
| | - Attila Kovacs
- Center for Cardiovascular Research, Cardiovascular Division, Washington University School of Medicine, St. Louis, MO
| | - Sarah Evans
- Center for Cardiovascular Research, Cardiovascular Division, Washington University School of Medicine, St. Louis, MO
| | - Scot J Matkovich
- Center for Cardiovascular Research, Cardiovascular Division, Washington University School of Medicine, St. Louis, MO
| | - Philip M Barger
- Center for Cardiovascular Research, Cardiovascular Division, Washington University School of Medicine, St. Louis, MO
| | - Douglas L Mann
- Center for Cardiovascular Research, Cardiovascular Division, Washington University School of Medicine, St. Louis, MO.
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22
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Weissenböck M, Latham R, Nishita M, Wolff LI, Ho HYH, Minami Y, Hartmann C. Genetic interactions between Ror2 and Wnt9a, Ror1 and Wnt9a and Ror2 and Ror1: Phenotypic analysis of the limb skeleton and palate in compound mutants. Genes Cells 2019; 24:307-317. [PMID: 30801848 DOI: 10.1111/gtc.12676] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Revised: 02/18/2019] [Accepted: 02/19/2019] [Indexed: 01/20/2023]
Abstract
Mutations in the human receptor tyrosine kinase ROR2 are associated with Robinow syndrome (RRS) and brachydactyly type B1. Amongst others, the shortened limb phenotype associated with RRS is recapitulated in Ror2-/- mutant mice. In contrast, Ror1-/- mutant mice are viable and show no limb phenotype. Ror1-/- ;Ror2-/- double mutants are embryonic lethal, whereas double mutants containing a hypomorphic Ror1 allele (Ror1hyp ) survive up to birth and display a more severe shortened limb phenotype. Both orphan receptors have been shown to act as possible Wnt coreceptors and to mediate the Wnt5a signal. Here, we analyzed genetic interactions between the Wnt ligand, Wnt9a, and Ror2 or Ror1, as Wnt9a has also been implicated in skeletal development. Wnt9a-/- single mutants display a mild shortening of the long bones, whereas these are severely shortened in Ror2-/- mutants. Ror2-/- ;Wnt9a-/- double mutants displayed even more severely shortened long bones, and intermediate phenotypes were observed in compound Ror2;Wnt9a mutants. Long bones were also shorter in Ror1hyp/hyp ;Wnt9a-/- double mutants. In addition, Ror1hyp/hyp ;Wnt9a-/- double mutants displayed a secondary palate cleft phenotype, which was not present in the respective single mutants. Interestingly, 50% of compound mutant pups heterozygous for Ror2 and homozygous mutant for Ror1 also developed a secondary palate cleft phenotype.
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Affiliation(s)
| | - Richard Latham
- Research Institute of Molecular Pathology, Vienna, Austria
| | - Michiru Nishita
- Division of Cell Physiology, Department of Physiology and Cell Biology, Graduate School of Medicine, Kobe University, Kobe, Japan
| | - Lena Ingeborg Wolff
- Department of Bone and Skeletal Research, Medical Faculty, Institute of Musculoskeletal Medicine, University of Münster, Münster, Germany
| | - Hsin-Yi Henry Ho
- Department of Cell Biology and Human Anatomy, University of California Davis School of Medicine, Davis, California
| | - Yasuhiro Minami
- Division of Cell Physiology, Department of Physiology and Cell Biology, Graduate School of Medicine, Kobe University, Kobe, Japan
| | - Christine Hartmann
- Department of Bone and Skeletal Research, Medical Faculty, Institute of Musculoskeletal Medicine, University of Münster, Münster, Germany
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23
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Liu W. Chromosome-based gene co-expression analysis reveals regions associated with cancers: chromosome 1 as an example. Mol Biol Rep 2019; 46:1551-1553. [PMID: 30680595 DOI: 10.1007/s11033-019-04596-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Accepted: 01/03/2019] [Indexed: 01/08/2023]
Abstract
Gene co-expression network analysis has been widely performed in systems biology. Here, I use a chromosome-based strategy to find potential chromosome regions associated with disease, and show an example of cancer. All results are available at http://bioinformatics.fafu.edu.cn/chrom-WGCNA/ .
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Affiliation(s)
- Wei Liu
- School of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
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24
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Rees CM, Yang JH, Santolini M, Lusis AJ, Weiss JN, Karma A. The Ca 2+ transient as a feedback sensor controlling cardiomyocyte ionic conductances in mouse populations. eLife 2018; 7:36717. [PMID: 30251624 PMCID: PMC6205808 DOI: 10.7554/elife.36717] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Accepted: 09/24/2018] [Indexed: 12/13/2022] Open
Abstract
Conductances of ion channels and transporters controlling cardiac excitation may vary in a population of subjects with different cardiac gene expression patterns. However, the amount of variability and its origin are not quantitatively known. We propose a new conceptual approach to predict this variability that consists of finding combinations of conductances generating a normal intracellular Ca2+ transient without any constraint on the action potential. Furthermore, we validate experimentally its predictions using the Hybrid Mouse Diversity Panel, a model system of genetically diverse mouse strains that allows us to quantify inter-subject versus intra-subject variability. The method predicts that conductances of inward Ca2+ and outward K+ currents compensate each other to generate a normal Ca2+ transient in good quantitative agreement with current measurements in ventricular myocytes from hearts of different isogenic strains. Our results suggest that a feedback mechanism sensing the aggregate Ca2+ transient of the heart suffices to regulate ionic conductances.
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Affiliation(s)
- Colin M Rees
- Physics Department, Northeastern University, Boston, United states.,Center for Interdisciplinary Research on Complex Systems, Northeastern University, Boston, United States
| | - Jun-Hai Yang
- Department of Medicine (Cardiology), Cardiovascular Research Laboratory, David Geffen School of Medicine, University of California, Los Angeles, United states.,Department of Physiology, David Geffen School of Medicine, University of California, Los Angeles, United States
| | - Marc Santolini
- Physics Department, Northeastern University, Boston, United states.,Center for Interdisciplinary Research on Complex Systems, Northeastern University, Boston, United States
| | - Aldons J Lusis
- Department of Medicine (Cardiology), Cardiovascular Research Laboratory, David Geffen School of Medicine, University of California, Los Angeles, United states.,Department of Physiology, David Geffen School of Medicine, University of California, Los Angeles, United States.,Department of Microbiology, David Geffen School of Medicine, University of California, Los Angeles, United States.,Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, United States
| | - James N Weiss
- Department of Medicine (Cardiology), Cardiovascular Research Laboratory, David Geffen School of Medicine, University of California, Los Angeles, United states.,Department of Physiology, David Geffen School of Medicine, University of California, Los Angeles, United States
| | - Alain Karma
- Physics Department, Northeastern University, Boston, United states.,Center for Interdisciplinary Research on Complex Systems, Northeastern University, Boston, United States
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25
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Co-Expression Network Analysis Identifies miRNA⁻mRNA Networks Potentially Regulating Milk Traits and Blood Metabolites. Int J Mol Sci 2018; 19:ijms19092500. [PMID: 30149509 PMCID: PMC6164576 DOI: 10.3390/ijms19092500] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2018] [Revised: 08/05/2018] [Accepted: 08/16/2018] [Indexed: 12/11/2022] Open
Abstract
MicroRNAs (miRNA) regulate mRNA networks to coordinate cellular functions. In this study, we constructed gene co-expression networks to detect miRNA modules (clusters of miRNAs with similar expression patterns) and miRNA–mRNA pairs associated with blood (triacylglyceride and nonesterified fatty acids) and milk (milk yield, fat, protein, and lactose) components and milk fatty acid traits following dietary supplementation of cows’ diets with 5% linseed oil (LSO) (n = 6 cows) or 5% safflower oil (SFO) (n = 6 cows) for 28 days. Using miRNA transcriptome data from mammary tissues of cows for co-expression network analysis, we identified three consensus modules: blue, brown, and turquoise, composed of 70, 34, and 86 miRNA members, respectively. The hub miRNAs (miRNAs with the most connections with other miRNAs) were miR-30d, miR-484 and miR-16b for blue, brown, and turquoise modules, respectively. Cell cycle arrest, and p53 signaling and transforming growth factor–beta (TGF-β) signaling pathways were the common gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enriched for target genes of the three modules. Protein percent (p = 0.03) correlated with the turquoise module in LSO treatment while protein yield (p = 0.003) and milk yield (p = 7 × 10−04) correlated with the turquoise model, protein and milk yields and lactose percent (p < 0.05) correlated with the blue module and fat percent (p = 0.04) correlated with the brown module in SFO treatment. Several fatty acids correlated (p < 0.05) with the blue (CLA:9,11) and brown (C4:0, C12:0, C22:0, C18:1n9c and CLA:10,12) modules in LSO treatment and with the turquoise (C14:0, C18:3n3 and CLA:9,11), blue (C14:0 and C23:0) and brown (C6:0, C16:0, C22:0, C22:6n3 and CLA:10,12) modules in SFO treatment. Correlation of miRNA and mRNA data from the same animals identified the following miRNA–mRNA pairs: miR-183/RHBDD2 (p = 0.003), miR-484/EIF1AD (p = 0.011) and miR-130a/SBSPON (p = 0.004) with lowest p-values for the blue, brown, and turquoise modules, respectively. Milk yield, protein yield, and protein percentage correlated (p < 0.05) with 28, 31 and 5 miRNA–mRNA pairs, respectively. Our results suggest that, the blue, brown, and turquoise modules miRNAs, hub miRNAs, miRNA–mRNA networks, cell cycle arrest GO term, p53 signaling and TGF-β signaling pathways have considerable influence on milk and blood phenotypes following dietary supplementation of dairy cows’ diets with 5% LSO or 5% SFO.
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26
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Nigenda‐Morales SF, Hu Y, Beasley JC, Ruiz‐Piña HA, Valenzuela‐Galván D, Wayne RK. Transcriptomic analysis of skin pigmentation variation in the Virginia opossum (
Didelphis virginiana
). Mol Ecol 2018; 27:2680-2697. [DOI: 10.1111/mec.14712] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2017] [Revised: 04/05/2018] [Accepted: 04/17/2018] [Indexed: 12/19/2022]
Affiliation(s)
- Sergio F. Nigenda‐Morales
- Department of Ecology and Evolutionary Biology University of California, Los Angeles Los Angeles California
| | - Yibo Hu
- Key Lab of Animal Ecology and Conservation Biology Institute of Zoology Chinese Academy of Sciences Chaoyang, Beijing China
| | - James C. Beasley
- Savannah River Ecology Lab Warnell School of Forestry and Natural Resources University of Georgia Aiken South Carolina
| | - Hugo A. Ruiz‐Piña
- Centro de Investigaciones Regionales “Dr. Hideyo Noguchi” Universidad Autónoma de Yucatán Mérida Yucatán Mexico
| | - David Valenzuela‐Galván
- Departamento de Ecología Evolutiva Centro de Investigación en Biodiversidad y Conservación Universidad Autónoma del Estado de Morelos Cuernavaca Morelos Mexico
| | - Robert K. Wayne
- Department of Ecology and Evolutionary Biology University of California, Los Angeles Los Angeles California
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27
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Abstract
In “classic” biomedical research, diseases have usually been studied individually. The pioneering human disease network (HDN) studies jointly consider a large number of diseases, analyse their interconnections, and provide a more comprehensive description of diseases. However, most of the existing HDN studies are based on molecular information and can only partially describe disease interconnections. Building on the unique Taiwan National Health Insurance Research Database (NHIRD), in this study, we construct the epidemiological HDN (eHDN), where two diseases are concluded as interconnected if their observed probability of co-occurrence deviating that expected under independence. Advancing from the existing HDN, the eHDN can also accommodate non-molecular connections and have more important practical implications. Building on the network construction, we examine important network properties such as connectivity, module, hub, and others and describe their temporal patterns. This study is among the first to systematically construct the eHDN and can have important implications for human disease research and health care and management.
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28
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A personalized, multiomics approach identifies genes involved in cardiac hypertrophy and heart failure. NPJ Syst Biol Appl 2018; 4:12. [PMID: 29507758 PMCID: PMC5825397 DOI: 10.1038/s41540-018-0046-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Revised: 12/14/2017] [Accepted: 01/12/2018] [Indexed: 11/08/2022] Open
Abstract
A traditional approach to investigate the genetic basis of complex diseases is to identify genes with a global change in expression between diseased and healthy individuals. However, population heterogeneity may undermine the effort to uncover genes with significant but individual contribution to the spectrum of disease phenotypes within a population. Here we investigate individual changes of gene expression when inducing hypertrophy and heart failure in 100 + strains of genetically distinct mice from the Hybrid Mouse Diversity Panel (HMDP). We find that genes whose expression fold-change correlates in a statistically significant way with the severity of the disease are either up or down-regulated across strains, and therefore missed by a traditional population-wide analysis of differential gene expression. Furthermore, those "fold-change" genes are enriched in human cardiac disease genes and form a dense co-regulated module strongly interacting with the cardiac hypertrophic signaling network in the human interactome. We validate our approach by showing that the knockdown of Hes1, predicted as a strong candidate, induces a dramatic reduction of hypertrophy by 80-90% in neonatal rat ventricular myocytes. Our results demonstrate that individualized approaches are crucial to identify genes underlying complex diseases as well as to develop personalized therapies.
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29
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Saba L, Hoffman P, Tabakoff B. Using Baseline Transcriptional Connectomes in Rat to Identify Genetic Pathways Associated with Predisposition to Complex Traits. Methods Mol Biol 2018; 1488:299-317. [PMID: 27933531 DOI: 10.1007/978-1-4939-6427-7_14] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Although rat is a critical model organism in preclinical medications development, its use in systems genetics studies remains sparse. The PhenoGen database and website contain detailed information on the qualitative and quantitative aspects of the rat brain, liver, heart, and brown adipose transcriptome. This database has been generated using the HXB/BXH recombinant inbred panel and is being expanded to a hybrid rat diversity panel that includes many common inbred strains as well. By using such a panel, the PhenoGen project has created a renewable and cumulative resource for the rat genomics community. The database has been used to reconstruct the brain transcriptome identifying both annotated and unannotated transcribed elements that range in size from 20 nucleotides to over 30,000 nucleotides and elements that have a wide variety of roles in the cell including generation of proteins and regulation of the transcription and translation processes. In all 4 tissues, baseline transcriptional connectomes have been generated to model the relationships among transcripts. These connectomes can be used to identify genetic pathways associated with complex traits and to gain insight into biological function of individual transcripts. The PhenoGen website contains tools that allow the user to explore qualitative features of individual genes and to see how the gene relates to other genes within a tissue. The PhenoGen database and website continue to grow and to make use of the latest statistical methods for systems genetics creating a national resource for the rat genomics community.
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Affiliation(s)
- Laura Saba
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, 12850 E. Montview Blvd., Aurora, CO, 80045, USA.
| | - Paula Hoffman
- Department of Pharmacology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Boris Tabakoff
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, 12850 E. Montview Blvd., Aurora, CO, 80045, USA
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30
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Muszkiewicz A, Liu X, Bueno-Orovio A, Lawson BAJ, Burrage K, Casadei B, Rodriguez B. From ionic to cellular variability in human atrial myocytes: an integrative computational and experimental study. Am J Physiol Heart Circ Physiol 2017; 314:H895-H916. [PMID: 29351467 PMCID: PMC6008144 DOI: 10.1152/ajpheart.00477.2017] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Variability refers to differences in physiological function between individuals, which may translate into different disease susceptibility and treatment efficacy. Experiments in human cardiomyocytes face wide variability and restricted tissue access; under these conditions, computational models are a useful complementary tool. We conducted a computational and experimental investigation in cardiomyocytes isolated from samples of the right atrial appendage of patients undergoing cardiac surgery to evaluate the impact of variability in action potentials (APs) and subcellular ionic densities on Ca2+ transient dynamics. Results showed that 1) variability in APs and ionic densities is large, even within an apparently homogenous patient cohort, and translates into ±100% variation in ionic conductances; 2) experimentally calibrated populations of models with wide variations in ionic densities yield APs overlapping with those obtained experimentally, even if AP characteristics of the original generic model differed significantly from experimental APs; 3) model calibration with AP recordings restricts the variability in ionic densities affecting upstroke and resting potential, but redundancy in repolarization currents admits substantial variability in ionic densities; and 4) model populations constrained with experimental APs and ionic densities exhibit three Ca2+ transient phenotypes, differing in intracellular Ca2+ handling and Na+/Ca2+ membrane extrusion. These findings advance our understanding of the impact of variability in human atrial electrophysiology. NEW & NOTEWORTHY Variability in human atrial electrophysiology is investigated by integrating for the first time cellular-level and ion channel recordings in computational electrophysiological models. Ion channel calibration restricts current densities but not cellular phenotypic variability. Reduced Na+/Ca2+ exchanger is identified as a primary mechanism underlying diastolic Ca2+ fluctuations in human atrial myocytes.
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Affiliation(s)
- Anna Muszkiewicz
- Department of Computer Science, University of Oxford , Oxford , United Kingdom
| | - Xing Liu
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital , Oxford , United Kingdom
| | | | - Brodie A J Lawson
- ARC Centre of Excellence for Mathematical and Statistical Frontiers, School of Mathematical Sciences, Queensland University of Technology , Brisbane, Queensland , Australia.,School of Mathematics, Queensland University of Technology , Brisbane, Queensland , Australia
| | - Kevin Burrage
- Department of Computer Science, University of Oxford , Oxford , United Kingdom.,ARC Centre of Excellence for Mathematical and Statistical Frontiers, School of Mathematical Sciences, Queensland University of Technology , Brisbane, Queensland , Australia.,School of Mathematics, Queensland University of Technology , Brisbane, Queensland , Australia
| | - Barbara Casadei
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, John Radcliffe Hospital , Oxford , United Kingdom
| | - Blanca Rodriguez
- Department of Computer Science, University of Oxford , Oxford , United Kingdom
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31
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Bondar G, Togashi R, Cadeiras M, Schaenman J, Cheng RK, Masukawa L, Hai J, Bao TM, Chu D, Chang E, Bakir M, Kupiec-Weglinski S, Groysberg V, Grogan T, Meltzer J, Kwon M, Rossetti M, Elashoff D, Reed E, Ping PP, Deng MC. Association between preoperative peripheral blood mononuclear cell gene expression profiles, early postoperative organ function recovery potential and long-term survival in advanced heart failure patients undergoing mechanical circulatory support. PLoS One 2017; 12:e0189420. [PMID: 29236770 PMCID: PMC5728510 DOI: 10.1371/journal.pone.0189420] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2017] [Accepted: 11/25/2017] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Multiorgan dysfunction syndrome contributes to adverse outcomes in advanced heart failure (AdHF) patients after mechanical circulatory support (MCS) implantation and is associated with aberrant leukocyte activity. We tested the hypothesis that preoperative peripheral blood mononuclear cell (PBMC) gene expression profiles (GEP) can predict early postoperative improvement or non-improvement in patients undergoing MCS implantation. We believe this information may be useful in developing prognostic biomarkers. METHODS & DESIGN We conducted a study with 29 patients undergoing MCS-surgery in a tertiary academic medical center from 2012 to 2014. PBMC samples were collected one day before surgery (day -1). Clinical data was collected on day -1 and day 8 postoperatively. Patients were classified by Sequential Organ Failure Assessment score and Model of End-stage Liver Disease Except INR score (measured eight days after surgery): Group I = improving (both scores improved from day -1 to day 8, n = 17) and Group II = not improving (either one or both scores did not improve from day -1 to day 8, n = 12). RNA-sequencing was performed on purified mRNA and analyzed using Next Generation Sequencing Strand. Differentially expressed genes (DEGs) were identified by Mann-Whitney test with Benjamini-Hochberg correction. Preoperative DEGs were used to construct a support vector machine algorithm to predict Group I vs. Group II membership. RESULTS Out of 28 MCS-surgery patients alive 8 days postoperatively, one-year survival was 88% in Group I and 27% in Group II. We identified 28 preoperative DEGs between Group I and II, with an average 93% prediction accuracy. Out of 105 DEGs identified preoperatively between year 1 survivors and non-survivors, 12 genes overlapped with the 28 predictive genes. CONCLUSIONS In AdHF patients following MCS implantation, preoperative PBMC-GEP predicts early changes in organ function scores and correlates with long-term outcomes. Therefore, gene expression lends itself to outcome prediction and warrants further studies in larger longitudinal cohorts.
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Affiliation(s)
- Galyna Bondar
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | - Ryan Togashi
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | - Martin Cadeiras
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | - Joanna Schaenman
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | - Richard K. Cheng
- University of Washington Medical Center, Seattle, Washington, United States of America
| | - Lindsay Masukawa
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | - Josephine Hai
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | - Tra-Mi Bao
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | - Desai Chu
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | - Eleanor Chang
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | - Maral Bakir
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | | | - Victoria Groysberg
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | - Tristan Grogan
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | - Joseph Meltzer
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | - Murray Kwon
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | - Maura Rossetti
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | - David Elashoff
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | - Elaine Reed
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | - Pei Pei Ping
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
| | - Mario C. Deng
- David Geffen School of Medicine, University of California Los Angeles Medical Center, Los Angeles, California, United States of America
- * E-mail:
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32
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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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33
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Harrington J, Fillmore N, Gao S, Yang Y, Zhang X, Liu P, Stoehr A, Chen Y, Springer D, Zhu J, Wang X, Murphy E. A Systems Biology Approach to Investigating Sex Differences in Cardiac Hypertrophy. J Am Heart Assoc 2017; 6:e005838. [PMID: 28862954 PMCID: PMC5586433 DOI: 10.1161/jaha.117.005838] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2017] [Accepted: 06/21/2017] [Indexed: 12/24/2022]
Abstract
BACKGROUND Heart failure preceded by hypertrophy is a leading cause of death, and sex differences in hypertrophy are well known, although the basis for these sex differences is poorly understood. METHODS AND RESULTS This study used a systems biology approach to investigate mechanisms underlying sex differences in cardiac hypertrophy. Male and female mice were treated for 2 and 3 weeks with angiotensin II to induce hypertrophy. Sex differences in cardiac hypertrophy were apparent after 3 weeks of treatment. RNA sequencing was performed on hearts, and sex differences in mRNA expression at baseline and following hypertrophy were observed, as well as within-sex differences between baseline and hypertrophy. Sex differences in mRNA were substantial at baseline and reduced somewhat with hypertrophy, as the mRNA differences induced by hypertrophy tended to overwhelm the sex differences. We performed an integrative analysis to identify mRNA networks that were differentially regulated in the 2 sexes by hypertrophy and obtained a network centered on PPARα (peroxisome proliferator-activated receptor α). Mouse experiments further showed that acute inhibition of PPARα blocked sex differences in the development of hypertrophy. CONCLUSIONS The data in this study suggest that PPARα is involved in the sex-dimorphic regulation of cardiac hypertrophy.
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Affiliation(s)
- Josephine Harrington
- Systems Biology Center, National Heart, Lung and Blood Institute National Institutes of Health, Bethesda, MD
| | - Natasha Fillmore
- Systems Biology Center, National Heart, Lung and Blood Institute National Institutes of Health, Bethesda, MD
| | - Shouguo Gao
- System Biology Core, National Heart, Lung and Blood Institute National Institutes of Health, Bethesda, MD
| | - Yanqin Yang
- DNA Sequencing & Genomics Core, National Heart, Lung and Blood Institute National Institutes of Health, Bethesda, MD
| | - Xue Zhang
- System Biology Core, National Heart, Lung and Blood Institute National Institutes of Health, Bethesda, MD
| | - Poching Liu
- DNA Sequencing & Genomics Core, National Heart, Lung and Blood Institute National Institutes of Health, Bethesda, MD
| | - Andrea Stoehr
- Systems Biology Center, National Heart, Lung and Blood Institute National Institutes of Health, Bethesda, MD
| | - Ye Chen
- System Biology Core, National Heart, Lung and Blood Institute National Institutes of Health, Bethesda, MD
| | - Danielle Springer
- Murine Phenotyping Core, National Heart, Lung and Blood Institute National Institutes of Health, Bethesda, MD
| | - Jun Zhu
- Systems Biology Center, National Heart, Lung and Blood Institute National Institutes of Health, Bethesda, MD
- DNA Sequencing & Genomics Core, National Heart, Lung and Blood Institute National Institutes of Health, Bethesda, MD
| | - Xujing Wang
- System Biology Core, National Heart, Lung and Blood Institute National Institutes of Health, Bethesda, MD
| | - Elizabeth Murphy
- Systems Biology Center, National Heart, Lung and Blood Institute National Institutes of Health, Bethesda, MD
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Kasper DM, Moro A, Ristori E, Narayanan A, Hill-Teran G, Fleming E, Moreno-Mateos M, Vejnar CE, Zhang J, Lee D, Gu M, Gerstein M, Giraldez A, Nicoli S. MicroRNAs Establish Uniform Traits during the Architecture of Vertebrate Embryos. Dev Cell 2017; 40:552-565.e5. [PMID: 28350988 DOI: 10.1016/j.devcel.2017.02.021] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2016] [Revised: 01/10/2017] [Accepted: 02/24/2017] [Indexed: 12/28/2022]
Abstract
Proper functioning of an organism requires cells and tissues to behave in uniform, well-organized ways. How this optimum of phenotypes is achieved during the development of vertebrates is unclear. Here, we carried out a multi-faceted and single-cell resolution screen of zebrafish embryonic blood vessels upon mutagenesis of single and multi-gene microRNA (miRNA) families. We found that embryos lacking particular miRNA-dependent signaling pathways develop a vascular trait similar to wild-type, but with a profound increase in phenotypic heterogeneity. Aberrant trait variance in miRNA mutant embryos uniquely sensitizes their vascular system to environmental perturbations. We discovered a previously unrecognized role for specific vertebrate miRNAs to protect tissue development against phenotypic variability. This discovery marks an important advance in our comprehension of how miRNAs function in the development of higher organisms.
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Affiliation(s)
- Dionna M Kasper
- Section of Cardiology, Department of Internal Medicine, Yale Cardiovascular Research Center, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Albertomaria Moro
- Section of Cardiology, Department of Internal Medicine, Yale Cardiovascular Research Center, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Emma Ristori
- Section of Cardiology, Department of Internal Medicine, Yale Cardiovascular Research Center, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Anand Narayanan
- Section of Cardiology, Department of Internal Medicine, Yale Cardiovascular Research Center, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Guillermina Hill-Teran
- Section of Cardiology, Department of Internal Medicine, Yale Cardiovascular Research Center, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Elizabeth Fleming
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Miguel Moreno-Mateos
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Charles E Vejnar
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Jing Zhang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Donghoon Lee
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Mengting Gu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA; Department of Computer Science, Yale University, New Haven, CT 06520, USA
| | - Antonio Giraldez
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA; Yale Stem Cell Center, Yale University School of Medicine, New Haven, CT 06510, USA; Yale Cancer Center, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Stefania Nicoli
- Section of Cardiology, Department of Internal Medicine, Yale Cardiovascular Research Center, Yale University School of Medicine, New Haven, CT 06511, USA; Department of Pharmacology, Yale University School of Medicine, New Haven, CT 06510, USA.
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35
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Hormones and sex differences: changes in cardiac electrophysiology with pregnancy. Clin Sci (Lond) 2017; 130:747-59. [PMID: 27128800 DOI: 10.1042/cs20150710] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2015] [Accepted: 02/01/2016] [Indexed: 11/17/2022]
Abstract
Disruption of cardiac electrical activity resulting in palpitations and syncope is often an early symptom of pregnancy. Pregnancy is a time of dramatic and dynamic physiological and hormonal changes during which numerous demands are placed on the heart. These changes result in electrical remodelling which can be detected as changes in the electrocardiogram (ECG). This gestational remodelling is a very under-researched area. There are no systematic large studies powered to determine changes in the ECG from pre-pregnancy, through gestation, and into the postpartum period. The large variability between patients and the dynamic nature of pregnancy hampers interpretation of smaller studies, but some facts are consistent. Gestational cardiac hypertrophy and a physical shift of the heart contribute to changes in the ECG. There are also electrical changes such as an increased heart rate and lengthening of the QT interval. There is an increased susceptibility to arrhythmias during pregnancy and the postpartum period. Some changes in the ECG are clearly the result of changes in ion channel expression and behaviour, but little is known about the ionic basis for this electrical remodelling. Most information comes from animal models, and implicates changes in the delayed-rectifier channels. However, it is likely that there are additional roles for sodium channels as well as changes in calcium homoeostasis. The changes in the electrical profile of the heart during pregnancy and the postpartum period have clear implications for the safety of pregnant women, but the field remains relatively undeveloped.
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36
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Gladilin E. Graph-theoretical model of global human interactome reveals enhanced long-range communicability in cancer networks. PLoS One 2017; 12:e0170953. [PMID: 28141819 PMCID: PMC5283687 DOI: 10.1371/journal.pone.0170953] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2016] [Accepted: 01/13/2017] [Indexed: 12/22/2022] Open
Abstract
Malignant transformation is known to involve substantial rearrangement of the molecular genetic landscape of the cell. A common approach to analysis of these alterations is a reductionist one and consists of finding a compact set of differentially expressed genes or associated signaling pathways. However, due to intrinsic tumor heterogeneity and tissue specificity, biomarkers defined by a small number of genes/pathways exhibit substantial variability. As an alternative to compact differential signatures, global features of genetic cell machinery are conceivable. Global network descriptors suggested in previous works are, however, known to potentially be biased by overrepresentation of interactions between frequently studied genes-proteins. Here, we construct a cellular network of 74538 directional and differential gene expression weighted protein-protein and gene regulatory interactions, and perform graph-theoretical analysis of global human interactome using a novel, degree-independent feature—the normalized total communicability (NTC). We apply this framework to assess differences in total information flow between different cancer (BRCA/COAD/GBM) and non-cancer interactomes. Our experimental results reveal that different cancer interactomes are characterized by significant enhancement of long-range NTC, which arises from circulation of information flow within robustly organized gene subnetworks. Although enhancement of NTC emerges in different cancer types from different genomic profiles, we identified a subset of 90 common genes that are related to elevated NTC in all studied tumors. Our ontological analysis shows that these genes are associated with enhanced cell division, DNA replication, stress response, and other cellular functions and processes typically upregulated in cancer. We conclude that enhancement of long-range NTC manifested in the correlated activity of genes whose tight coordination is required for survival and proliferation of all tumor cells, and, thus, can be seen as a graph-theoretical equivalent to some hallmarks of cancer. The computational framework for differential network analysis presented herein is of potential interest for a wide range of network perturbation problems given by single or multiple gene-protein activation-inhibition.
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Affiliation(s)
- Evgeny Gladilin
- Division of Theoretical Bioinformatics, German Cancer Research Center, Berliner Str. 41, 69120 Heidelberg, Germany
- BioQuant and IPMB, University Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany
- * E-mail:
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Chiamvimonvat N, Chen-Izu Y, Clancy CE, Deschenes I, Dobrev D, Heijman J, Izu L, Qu Z, Ripplinger CM, Vandenberg JI, Weiss JN, Koren G, Banyasz T, Grandi E, Sanguinetti MC, Bers DM, Nerbonne JM. Potassium currents in the heart: functional roles in repolarization, arrhythmia and therapeutics. J Physiol 2017; 595:2229-2252. [PMID: 27808412 DOI: 10.1113/jp272883] [Citation(s) in RCA: 67] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2016] [Accepted: 10/11/2016] [Indexed: 12/19/2022] Open
Abstract
This is the second of the two White Papers from the fourth UC Davis Cardiovascular Symposium Systems Approach to Understanding Cardiac Excitation-Contraction Coupling and Arrhythmias (3-4 March 2016), a biennial event that brings together leading experts in different fields of cardiovascular research. The theme of the 2016 symposium was 'K+ channels and regulation', and the objectives of the conference were severalfold: (1) to identify current knowledge gaps; (2) to understand what may go wrong in the diseased heart and why; (3) to identify possible novel therapeutic targets; and (4) to further the development of systems biology approaches to decipher the molecular mechanisms and treatment of cardiac arrhythmias. The sessions of the Symposium focusing on the functional roles of the cardiac K+ channel in health and disease, as well as K+ channels as therapeutic targets, were contributed by Ye Chen-Izu, Gideon Koren, James Weiss, David Paterson, David Christini, Dobromir Dobrev, Jordi Heijman, Thomas O'Hara, Crystal Ripplinger, Zhilin Qu, Jamie Vandenberg, Colleen Clancy, Isabelle Deschenes, Leighton Izu, Tamas Banyasz, Andras Varro, Heike Wulff, Eleonora Grandi, Michael Sanguinetti, Donald Bers, Jeanne Nerbonne and Nipavan Chiamvimonvat as speakers and panel discussants. This article summarizes state-of-the-art knowledge and controversies on the functional roles of cardiac K+ channels in normal and diseased heart. We endeavour to integrate current knowledge at multiple scales, from the single cell to the whole organ levels, and from both experimental and computational studies.
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Affiliation(s)
- Nipavan Chiamvimonvat
- Department of Internal Medicine, University of California, Davis, Genome and Biomedical Science Facility, Rm 6315, Davis, CA, 95616, USA.,Department of Veterans Affairs, Northern California Health Care System, Mather, CA, 95655, USA
| | - Ye Chen-Izu
- Department of Internal Medicine, University of California, Davis, Genome and Biomedical Science Facility, Rm 6315, Davis, CA, 95616, USA.,Department of Pharmacology, University of California, Davis, Genome and Biomedical Science Facility, Rm 3503, Davis, CA, 95616, USA.,Department of Biomedical Engineering, University of California, Davis, Genome and Biomedical Science Facility, Rm 2303, Davis, CA, 95616, USA
| | - Colleen E Clancy
- Department of Pharmacology, University of California, Davis, Genome and Biomedical Science Facility, Rm 3503, Davis, CA, 95616, USA
| | - Isabelle Deschenes
- Department of Physiology and Biophysics, and Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44109, USA.,Heart and Vascular Research Center, MetroHealth Medical Center, Cleveland, OH, 44109, USA
| | - Dobromir Dobrev
- Institute of Pharmacology, West German Heart and Vascular Center, University Duisburg-Essen, Hufelandstrasse 55, 45122, Essen, Germany
| | - Jordi Heijman
- Department of Cardiology, Cardiovascular Research Institute Maastricht, Faculty of Health, Medicine, and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Leighton Izu
- Department of Pharmacology, University of California, Davis, Genome and Biomedical Science Facility, Rm 3503, Davis, CA, 95616, USA
| | - Zhilin Qu
- Division of Cardiology, Cardiovascular Research Laboratory, David Geffen School of Medicine at UCLA, 3645 MRL, Los Angeles, CA, 90095, USA
| | - Crystal M Ripplinger
- Department of Pharmacology, University of California, Davis, Genome and Biomedical Science Facility, Rm 3503, Davis, CA, 95616, USA
| | - Jamie I Vandenberg
- Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW, 2010, Australia
| | - James N Weiss
- Division of Cardiology, Cardiovascular Research Laboratory, David Geffen School of Medicine at UCLA, 3645 MRL, Los Angeles, CA, 90095, USA
| | - Gideon Koren
- Cardiovascular Research Center, Rhode Island Hospital and the Cardiovascular Institute, The Warren Alpert Medical School of Brown University, Providence, RI, 02903, USA
| | - Tamas Banyasz
- Department of Physiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - Eleonora Grandi
- Department of Pharmacology, University of California, Davis, Genome and Biomedical Science Facility, Rm 3503, Davis, CA, 95616, USA
| | - Michael C Sanguinetti
- Department of Internal Medicine, University of Utah, Nora Eccles Harrison Cardiovascular Research & Training Institute, Salt Lake City, UT, 84112, USA
| | - Donald M Bers
- Department of Pharmacology, University of California, Davis, Genome and Biomedical Science Facility, Rm 3503, Davis, CA, 95616, USA
| | - Jeanne M Nerbonne
- Departments of Developmental Biology and Internal Medicine, Cardiovascular Division, Washington University Medical School, St Louis, MO, 63110, USA
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Devenyi RA, Ortega FA, Groenendaal W, Krogh-Madsen T, Christini DJ, Sobie EA. Differential roles of two delayed rectifier potassium currents in regulation of ventricular action potential duration and arrhythmia susceptibility. J Physiol 2016; 595:2301-2317. [PMID: 27779762 DOI: 10.1113/jp273191] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2016] [Accepted: 10/18/2016] [Indexed: 11/08/2022] Open
Abstract
KEY POINTS Arrhythmias result from disruptions to cardiac electrical activity, although the factors that control cellular action potentials are incompletely understood. We combined mathematical modelling with experiments in heart cells from guinea pigs to determine how cellular electrical activity is regulated. A mismatch between modelling predictions and the experimental results allowed us to construct an improved, more predictive mathematical model. The balance between two particular potassium currents dictates how heart cells respond to perturbations and their susceptibility to arrhythmias. ABSTRACT Imbalances of ionic currents can destabilize the cardiac action potential and potentially trigger lethal cardiac arrhythmias. In the present study, we combined mathematical modelling with information-rich dynamic clamp experiments to determine the regulation of action potential morphology in guinea pig ventricular myocytes. Parameter sensitivity analysis was used to predict how changes in ionic currents alter action potential duration, and these were tested experimentally using dynamic clamp, a technique that allows for multiple perturbations to be tested in each cell. Surprisingly, we found that a leading mathematical model, developed with traditional approaches, systematically underestimated experimental responses to dynamic clamp perturbations. We then re-parameterized the model using a genetic algorithm, which allowed us to estimate ionic current levels in each of the cells studied. This unbiased model adjustment consistently predicted an increase in the rapid delayed rectifier K+ current and a drastic decrease in the slow delayed rectifier K+ current, and this prediction was validated experimentally. Subsequent simulations with the adjusted model generated the clinically relevant prediction that the slow delayed rectifier is better able to stabilize the action potential and suppress pro-arrhythmic events than the rapid delayed rectifier. In summary, iterative coupling of simulations and experiments enabled novel insight into how the balance between cardiac K+ currents influences ventricular arrhythmia susceptibility.
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Affiliation(s)
- Ryan A Devenyi
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Francis A Ortega
- Physiology, Biophysics, and Systems Biology Graduate Program, Weill Cornell Graduate School, New York, NY, USA
| | - Willemijn Groenendaal
- Greenberg Division of Cardiology, Weill Cornell Medical College, New York, NY, USA.,IMEC, Holst Centre, Eindhoven, The Netherlands
| | - Trine Krogh-Madsen
- Greenberg Division of Cardiology, Weill Cornell Medical College, New York, NY, USA
| | - David J Christini
- Physiology, Biophysics, and Systems Biology Graduate Program, Weill Cornell Graduate School, New York, NY, USA.,Greenberg Division of Cardiology, Weill Cornell Medical College, New York, NY, USA
| | - Eric A Sobie
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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39
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Lam MPY, Lau E, Ng DCM, Wang D, Ping P. Cardiovascular proteomics in the era of big data: experimental and computational advances. Clin Proteomics 2016; 13:23. [PMID: 27980500 PMCID: PMC5137214 DOI: 10.1186/s12014-016-9124-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2016] [Accepted: 08/24/2016] [Indexed: 01/14/2023] Open
Abstract
Proteomics plays an increasingly important role in our quest to understand cardiovascular biology. Fueled by analytical and computational advances in the past decade, proteomics applications can now go beyond merely inventorying protein species, and address sophisticated questions on cardiac physiology. The advent of massive mass spectrometry datasets has in turn led to increasing intersection between proteomics and big data science. Here we review new frontiers in technological developments and their applications to cardiovascular medicine. The impact of big data science on cardiovascular proteomics investigations and translation to medicine is highlighted.
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Affiliation(s)
- Maggie P Y Lam
- NIH BD2K Center of Excellence at UCLA; Department of Physiology, University of California at Los Angeles, 675 Charles E. Young Drive, Los Angeles, CA 90095 USA
| | - Edward Lau
- NIH BD2K Center of Excellence at UCLA; Department of Physiology, University of California at Los Angeles, 675 Charles E. Young Drive, Los Angeles, CA 90095 USA
| | - Dominic C M Ng
- NIH BD2K Center of Excellence at UCLA; Department of Physiology, University of California at Los Angeles, 675 Charles E. Young Drive, Los Angeles, CA 90095 USA
| | - Ding Wang
- NIH BD2K Center of Excellence at UCLA; Department of Physiology, University of California at Los Angeles, 675 Charles E. Young Drive, Los Angeles, CA 90095 USA
| | - Peipei Ping
- NIH BD2K Center of Excellence at UCLA; Department of Physiology, University of California at Los Angeles, 675 Charles E. Young Drive, Los Angeles, CA 90095 USA ; Department of Medicine, University of California at Los Angeles, 675 Charles E. Young Drive, Los Angeles, CA 90095 USA ; Department of Bioinformatics, University of California at Los Angeles, 675 Charles E. Young Drive, Los Angeles, CA 90095 USA
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40
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Gong JQX, Shim JV, Núñez-Acosta E, Sobie EA. I love it when a plan comes together: Insight gained through convergence of competing mathematical models. J Mol Cell Cardiol 2016; 102:31-33. [PMID: 27913283 DOI: 10.1016/j.yjmcc.2016.10.015] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2016] [Accepted: 10/26/2016] [Indexed: 01/01/2023]
Affiliation(s)
- Jingqi Q X Gong
- Department of Pharmacological Sciences, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jaehee V Shim
- Department of Pharmacological Sciences, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Elisa Núñez-Acosta
- Department of Pharmacological Sciences, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Eric A Sobie
- Department of Pharmacological Sciences, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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41
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Grandi E, Sanguinetti MC, Bartos DC, Bers DM, Chen-Izu Y, Chiamvimonvat N, Colecraft HM, Delisle BP, Heijman J, Navedo MF, Noskov S, Proenza C, Vandenberg JI, Yarov-Yarovoy V. Potassium channels in the heart: structure, function and regulation. J Physiol 2016; 595:2209-2228. [PMID: 27861921 DOI: 10.1113/jp272864] [Citation(s) in RCA: 59] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2016] [Accepted: 07/18/2016] [Indexed: 12/22/2022] Open
Abstract
This paper is the outcome of the fourth UC Davis Systems Approach to Understanding Cardiac Excitation-Contraction Coupling and Arrhythmias Symposium, a biannual event that aims to bring together leading experts in subfields of cardiovascular biomedicine to focus on topics of importance to the field. The theme of the 2016 symposium was 'K+ Channels and Regulation'. Experts in the field contributed their experimental and mathematical modelling perspectives and discussed emerging questions, controversies and challenges on the topic of cardiac K+ channels. This paper summarizes the topics of formal presentations and informal discussions from the symposium on the structural basis of voltage-gated K+ channel function, as well as the mechanisms involved in regulation of K+ channel gating, expression and membrane localization. Given the critical role for K+ channels in determining the rate of cardiac repolarization, it is hardly surprising that essentially every aspect of K+ channel function is exquisitely regulated in cardiac myocytes. This regulation is complex and highly interrelated to other aspects of myocardial function. K+ channel regulatory mechanisms alter, and are altered by, physiological challenges, pathophysiological conditions, and pharmacological agents. An accompanying paper focuses on the integrative role of K+ channels in cardiac electrophysiology, i.e. how K+ currents shape the cardiac action potential, and how their dysfunction can lead to arrhythmias, and discusses K+ channel-based therapeutics. A fundamental understanding of K+ channel regulatory mechanisms and disease processes is fundamental to reveal new targets for human therapy.
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Affiliation(s)
- Eleonora Grandi
- Department of Pharmacology, University of California, Davis, Davis, CA, 95616, USA
| | - Michael C Sanguinetti
- Department of Internal Medicine, University of Utah, Nora Eccles Harrison Cardiovascular Research and Training Institute, Salt Lake City, UT, 84112, USA
| | - Daniel C Bartos
- Department of Pharmacology, University of California, Davis, Davis, CA, 95616, USA
| | - Donald M Bers
- Department of Pharmacology, University of California, Davis, Davis, CA, 95616, USA
| | - Ye Chen-Izu
- Department of Pharmacology, University of California, Davis, Davis, CA, 95616, USA.,Department of Internal Medicine, Division of Cardiology, University of California, Davis, CA, 95616, USA
| | - Nipavan Chiamvimonvat
- Department of Internal Medicine, Division of Cardiology, University of California, Davis, CA, 95616, USA
| | - Henry M Colecraft
- Department of Physiology and Cellular Biophysics, Columbia University, New York, NY, 10032, USA
| | - Brian P Delisle
- Department of Physiology, University of Kentucky, Lexington, KY, 40536, USA
| | - Jordi Heijman
- Department of Cardiology, Cardiovascular Research Institute Maastricht, Faculty of Health, Medicine, and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Manuel F Navedo
- Department of Pharmacology, University of California, Davis, Davis, CA, 95616, USA
| | - Sergei Noskov
- Centre for Molecular Simulation, Department of Biological Sciences, University of Calgary, Calgary, AB, T2N 1N4, Canada
| | - Catherine Proenza
- Department of Physiology and Biophysics, University of Colorado - Anschutz Medical Campus, Denver, CO, 80045, USA
| | - Jamie I Vandenberg
- Victor Chang Cardiac Research Institute, Darlinghurst, NSW, 2010, Australia
| | - Vladimir Yarov-Yarovoy
- Department of Physiology and Membrane Biology, University of California, Davis, CA, 95616, USA
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42
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Mann SA, Imtiaz M, Winbo A, Rydberg A, Perry MD, Couderc JP, Polonsky B, McNitt S, Zareba W, Hill AP, Vandenberg JI. Convergence of models of human ventricular myocyte electrophysiology after global optimization to recapitulate clinical long QT phenotypes. J Mol Cell Cardiol 2016; 100:25-34. [DOI: 10.1016/j.yjmcc.2016.09.011] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2016] [Revised: 09/11/2016] [Accepted: 09/19/2016] [Indexed: 12/15/2022]
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Cote I, Andersen ME, Ankley GT, Barone S, Birnbaum LS, Boekelheide K, Bois FY, Burgoon LD, Chiu WA, Crawford-Brown D, Crofton KM, DeVito M, Devlin RB, Edwards SW, Guyton KZ, Hattis D, Judson RS, Knight D, Krewski D, Lambert J, Maull EA, Mendrick D, Paoli GM, Patel CJ, Perkins EJ, Poje G, Portier CJ, Rusyn I, Schulte PA, Simeonov A, Smith MT, Thayer KA, Thomas RS, Thomas R, Tice RR, Vandenberg JJ, Villeneuve DL, Wesselkamper S, Whelan M, Whittaker C, White R, Xia M, Yauk C, Zeise L, Zhao J, DeWoskin RS. The Next Generation of Risk Assessment Multi-Year Study-Highlights of Findings, Applications to Risk Assessment, and Future Directions. ENVIRONMENTAL HEALTH PERSPECTIVES 2016; 124:1671-1682. [PMID: 27091369 PMCID: PMC5089888 DOI: 10.1289/ehp233] [Citation(s) in RCA: 62] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Revised: 10/30/2015] [Accepted: 03/29/2016] [Indexed: 05/19/2023]
Abstract
BACKGROUND The Next Generation (NexGen) of Risk Assessment effort is a multi-year collaboration among several organizations evaluating new, potentially more efficient molecular, computational, and systems biology approaches to risk assessment. This article summarizes our findings, suggests applications to risk assessment, and identifies strategic research directions. OBJECTIVE Our specific objectives were to test whether advanced biological data and methods could better inform our understanding of public health risks posed by environmental exposures. METHODS New data and methods were applied and evaluated for use in hazard identification and dose-response assessment. Biomarkers of exposure and effect, and risk characterization were also examined. Consideration was given to various decision contexts with increasing regulatory and public health impacts. Data types included transcriptomics, genomics, and proteomics. Methods included molecular epidemiology and clinical studies, bioinformatic knowledge mining, pathway and network analyses, short-duration in vivo and in vitro bioassays, and quantitative structure activity relationship modeling. DISCUSSION NexGen has advanced our ability to apply new science by more rapidly identifying chemicals and exposures of potential concern, helping characterize mechanisms of action that influence conclusions about causality, exposure-response relationships, susceptibility and cumulative risk, and by elucidating new biomarkers of exposure and effects. Additionally, NexGen has fostered extensive discussion among risk scientists and managers and improved confidence in interpreting and applying new data streams. CONCLUSIONS While considerable uncertainties remain, thoughtful application of new knowledge to risk assessment appears reasonable for augmenting major scope assessments, forming the basis for or augmenting limited scope assessments, and for prioritization and screening of very data limited chemicals. Citation: Cote I, Andersen ME, Ankley GT, Barone S, Birnbaum LS, Boekelheide K, Bois FY, Burgoon LD, Chiu WA, Crawford-Brown D, Crofton KM, DeVito M, Devlin RB, Edwards SW, Guyton KZ, Hattis D, Judson RS, Knight D, Krewski D, Lambert J, Maull EA, Mendrick D, Paoli GM, Patel CJ, Perkins EJ, Poje G, Portier CJ, Rusyn I, Schulte PA, Simeonov A, Smith MT, Thayer KA, Thomas RS, Thomas R, Tice RR, Vandenberg JJ, Villeneuve DL, Wesselkamper S, Whelan M, Whittaker C, White R, Xia M, Yauk C, Zeise L, Zhao J, DeWoskin RS. 2016. The Next Generation of Risk Assessment multiyear study-highlights of findings, applications to risk assessment, and future directions. Environ Health Perspect 124:1671-1682; http://dx.doi.org/10.1289/EHP233.
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Affiliation(s)
- Ila Cote
- National Center for Environmental Assessment, U.S. Environmental Protection Agency (EPA), Washington, District of Columbia, USA
- Address correspondence to I. Cote, U.S. Environmental Protection Agency, Region 8, Room 8152, 1595 Wynkoop St., Denver, CO 80202-1129 USA. Telephone: (202) 288-9539. E-mail:
| | | | - Gerald T. Ankley
- National Health and Environmental Effects Research Laboratory, U.S. EPA, Duluth, Minnesota, USA
| | - Stanley Barone
- Office of Chemical Safety and Pollution Prevention, U.S. EPA, Washington, District of Columbia, USA
| | - Linda S. Birnbaum
- National Institute of Environmental Health Sciences, and
- National Toxicology Program, National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Research Triangle Park, North Carolina, USA
| | - Kim Boekelheide
- Department of Pathology and Laboratory Medicine, Brown University, Providence, Rhode Island, USA
| | - Frederic Y. Bois
- Unité Modèles pour l’Écotoxicologie et la Toxicologie, Institut National de l’Environnement Industriel et des Risques, Verneuil en Halatte, France
| | - Lyle D. Burgoon
- U.S. Army Engineer Research and Development Center, Research Triangle Park, North Carolina, USA
| | - Weihsueh A. Chiu
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, USA
| | | | | | - Michael DeVito
- National Institute of Environmental Health Sciences, and
- National Toxicology Program, National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Research Triangle Park, North Carolina, USA
| | - Robert B. Devlin
- National Health and Environmental Effects Research Laboratory, U.S. EPA, Research Triangle Park, North Carolina, USA
| | - Stephen W. Edwards
- National Health and Environmental Effects Research Laboratory, U.S. EPA, Research Triangle Park, North Carolina, USA
| | | | - Dale Hattis
- George Perkins Marsh Institute, Clark University, Worcester, Massachusetts, USA
| | | | - Derek Knight
- European Chemicals Agency, Annankatu, Helsinki, Finland
| | - Daniel Krewski
- McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, Ontario, Canada
| | - Jason Lambert
- National Center for Environmental Assessment, U.S. EPA, Cincinnati, Ohio, USA
| | - Elizabeth Anne Maull
- National Institute of Environmental Health Sciences, and
- National Toxicology Program, National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Research Triangle Park, North Carolina, USA
| | - Donna Mendrick
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, Arkansas, USA
| | | | - Chirag Jagdish Patel
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Edward J. Perkins
- U.S. Army Engineer Research and Development Center, Vicksburg, Mississippi, USA
| | - Gerald Poje
- Grant Consulting Group, Washington, District of Columbia, USA
| | | | - Ivan Rusyn
- Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, USA
| | - Paul A. Schulte
- Education and Information Division, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Cincinnati, Ohio, USA
| | - Anton Simeonov
- National Center for Advancing Translational Sciences, NIH, DHHS, Bethesda, Maryland, USA
| | - Martyn T. Smith
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, California, USA
| | - Kristina A. Thayer
- National Institute of Environmental Health Sciences, and
- National Toxicology Program, National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Research Triangle Park, North Carolina, USA
| | | | - Reuben Thomas
- Gladstone Institutes, University of California, San Francisco, San Francisco, California, USA
| | - Raymond R. Tice
- National Institute of Environmental Health Sciences, and
- National Toxicology Program, National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Research Triangle Park, North Carolina, USA
| | - John J. Vandenberg
- National Center for Environmental Assessment, U.S. Environmental Protection Agency (EPA), Washington, District of Columbia, USA
| | - Daniel L. Villeneuve
- National Health and Environmental Effects Research Laboratory, U.S. EPA, Duluth, Minnesota, USA
| | - Scott Wesselkamper
- National Center for Environmental Assessment, U.S. EPA, Cincinnati, Ohio, USA
| | - Maurice Whelan
- Systems Toxicology Unit, European Commission Joint Research Centre, Ispra, Italy
| | - Christine Whittaker
- Education and Information Division, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Cincinnati, Ohio, USA
| | - Ronald White
- Center for Effective Government, Washington, District of Columbia, USA
| | - Menghang Xia
- National Center for Advancing Translational Sciences, NIH, DHHS, Bethesda, Maryland, USA
| | - Carole Yauk
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, Ontario, Canada
| | - Lauren Zeise
- Office of Environmental Health Hazard Assessment, California EPA, Oakland, California, USA
| | - Jay Zhao
- National Center for Environmental Assessment, U.S. EPA, Cincinnati, Ohio, USA
| | - Robert S. DeWoskin
- National Center for Environmental Assessment, U.S. Environmental Protection Agency (EPA), Washington, District of Columbia, USA
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Monte E, Rosa-Garrido M, Vondriska TM, Wang J. Undiscovered Physiology of Transcript and Protein Networks. Compr Physiol 2016; 6:1851-1872. [PMID: 27783861 PMCID: PMC10751805 DOI: 10.1002/cphy.c160003] [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: 11/07/2022]
Abstract
The past two decades have witnessed a rapid evolution in our ability to measure RNA and protein from biological systems. As a result, new principles have arisen regarding how information is processed in cells, how decisions are made, and the role of networks in biology. This essay examines this technological evolution, reviewing (and critiquing) the conceptual framework that has emerged to explain how RNA and protein networks control cellular function. We identify how future investigations into transcriptomes, proteomes, and other cellular networks will enable development of more robust, quantitative models of cellular behavior whilst also providing new avenues to use knowledge of biological networks to improve human health. © 2016 American Physiological Society. Compr Physiol 6:1851-1872, 2016.
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Affiliation(s)
- Emma Monte
- Department of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine, University of California, Los Angeles, USA
| | - Manuel Rosa-Garrido
- Department of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine, University of California, Los Angeles, USA
| | - Thomas M. Vondriska
- Department of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine, University of California, Los Angeles, USA
- Department of Medicine/Cardiology, David Geffen School of Medicine, University of California, Los Angeles, USA
- Department of Physiology, David Geffen School of Medicine, University of California, Los Angeles, USA
| | - Jessica Wang
- Department of Medicine/Cardiology, David Geffen School of Medicine, University of California, Los Angeles, USA
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Uncovering the liver's role in immunity through RNA co-expression networks. Mamm Genome 2016; 27:469-84. [PMID: 27401171 PMCID: PMC5002042 DOI: 10.1007/s00335-016-9656-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2016] [Accepted: 06/27/2016] [Indexed: 01/16/2023]
Abstract
Gene co-expression analysis has proven to be a powerful tool for ascertaining the organization of gene products into networks that are important for organ function. An organ, such as the liver, engages in a multitude of functions important for the survival of humans, rats, and other animals; these liver functions include energy metabolism, metabolism of xenobiotics, immune system function, and hormonal homeostasis. With the availability of organ-specific transcriptomes, we can now examine the role of RNA transcripts (both protein-coding and non-coding) in these functions. A systems genetic approach for identifying and characterizing liver gene networks within a recombinant inbred panel of rats was used to identify genetically regulated transcriptional networks (modules). For these modules, biological consensus was found between functional enrichment analysis and publicly available phenotypic quantitative trait loci (QTL). In particular, the biological function of two liver modules could be linked to immune response. The eigengene QTLs for these co-expression modules were located at genomic regions coincident with highly significant phenotypic QTLs; these phenotypes were related to rheumatoid arthritis, food preference, and basal corticosterone levels in rats. Our analysis illustrates that genetically and biologically driven RNA-based networks, such as the ones identified as part of this research, provide insight into the genetic influences on organ functions. These networks can pinpoint phenotypes that manifest through the interaction of many organs/tissues and can identify unannotated or under-annotated RNA transcripts that play a role in these phenotypes.
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Electrophysiology of Heart Failure Using a Rabbit Model: From the Failing Myocyte to Ventricular Fibrillation. PLoS Comput Biol 2016; 12:e1004968. [PMID: 27336310 PMCID: PMC4919062 DOI: 10.1371/journal.pcbi.1004968] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2015] [Accepted: 05/05/2016] [Indexed: 02/07/2023] Open
Abstract
Heart failure is a leading cause of death, yet its underlying electrophysiological (EP) mechanisms are not well understood. In this study, we use a multiscale approach to analyze a model of heart failure and connect its results to features of the electrocardiogram (ECG). The heart failure model is derived by modifying a previously validated electrophysiology model for a healthy rabbit heart. Specifically, in accordance with the heart failure literature, we modified the cell EP by changing both membrane currents and calcium handling. At the tissue level, we modeled the increased gap junction lateralization and lower conduction velocity due to downregulation of Connexin 43. At the biventricular level, we reduced the apex-to-base and transmural gradients of action potential duration (APD). The failing cell model was first validated by reproducing the longer action potential, slower and lower calcium transient, and earlier alternans characteristic of heart failure EP. Subsequently, we compared the electrical wave propagation in one dimensional cables of healthy and failing cells. The validated cell model was then used to simulate the EP of heart failure in an anatomically accurate biventricular rabbit model. As pacing cycle length decreases, both the normal and failing heart develop T-wave alternans, but only the failing heart shows QRS alternans (although moderate) at rapid pacing. Moreover, T-wave alternans is significantly more pronounced in the failing heart. At rapid pacing, APD maps show areas of conduction block in the failing heart. Finally, accelerated pacing initiated wave reentry and breakup in the failing heart. Further, the onset of VF was not observed with an upregulation of SERCA, a potential drug therapy, using the same protocol. The changes introduced at the cell and tissue level have increased the failing heart’s susceptibility to dynamic instabilities and arrhythmias under rapid pacing. However, the observed increase in arrhythmogenic potential is not due to a steepening of the restitution curve (not present in our model), but rather to a novel blocking mechanism. Ventricular fibrillation (VF) is one of the leading causes of sudden death. During VF, the electrical wave of activation in the heart breaks up chaotically. Consequently, the heart is unable to contract synchronously and pump blood to the rest of the body. In our work we formulate and validate a model of heart failure (HF) that allows us to evaluate the arrhythmogenic potential of individual and combined electrophysiological changes. In diagnostic cardiology, the electrocardiogram (ECG) is one of the most commonly used tools for detecting abnormalities in the heart electrophysiology. One of our goals is to use our numerical model to link changes at the cellular and tissue level in a failing heart to a numerically computed ECG. This allows us to characterize the precursor to and the risk of VF. In order to understand the mechanisms underlying VF in HF, we design a test that simulates a HF patient performing physical exercise. We show that under fast heart rates with changes in pacing, HF patients are more prone to VF due to a new conduction blocking mechanism. In the long term, our mathematical model is suitable for investigating the effect of drug therapies in HF.
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Gemmell P, Burrage K, Rodríguez B, Quinn TA. Rabbit-specific computational modelling of ventricular cell electrophysiology: Using populations of models to explore variability in the response to ischemia. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2016; 121:169-84. [PMID: 27320382 PMCID: PMC5405055 DOI: 10.1016/j.pbiomolbio.2016.06.003] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2016] [Accepted: 06/13/2016] [Indexed: 11/04/2022]
Abstract
Computational modelling, combined with experimental investigations, is a powerful method for investigating complex cardiac electrophysiological behaviour. The use of rabbit-specific models, due to the similarities of cardiac electrophysiology in this species with human, is especially prevalent. In this paper, we first briefly review rabbit-specific computational modelling of ventricular cell electrophysiology, multi-cellular simulations including cellular heterogeneity, and acute ischemia. This mini-review is followed by an original computational investigation of variability in the electrophysiological response of two experimentally-calibrated populations of rabbit-specific ventricular myocyte action potential models to acute ischemia. We performed a systematic exploration of the response of the model populations to varying degrees of ischemia and individual ischemic parameters, to investigate their individual and combined effects on action potential duration and refractoriness. This revealed complex interactions between model population variability and ischemic factors, which combined to enhance variability during ischemia. This represents an important step towards an improved understanding of the role that physiological variability may play in electrophysiological alterations during acute ischemia.
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Affiliation(s)
- Philip Gemmell
- Department of Computer Science, University of Oxford, Oxford, UK
| | - Kevin Burrage
- Department of Computer Science, University of Oxford, Oxford, UK; School of Mathematical Sciences and ARC Centre of Excellence, ACEMS, Queensland University of Technology, Brisbane, Australia
| | - Blanca Rodríguez
- Department of Computer Science, University of Oxford, Oxford, UK
| | - T Alexander Quinn
- Department of Physiology and Biophysics, Dalhousie University, 5850 College St, Lab 3F, Halifax, NS B3H 4R2, Canada; School of Biomedical Engineering, Dalhousie University, 5850 College St, Lab 3F, Halifax, NS B3H 4R2, Canada.
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48
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Karbassi E, Monte E, Chapski DJ, Lopez R, Rosa Garrido M, Kim J, Wisniewski N, Rau CD, Wang JJ, Weiss JN, Wang Y, Lusis AJ, Vondriska TM. Relationship of disease-associated gene expression to cardiac phenotype is buffered by genetic diversity and chromatin regulation. Physiol Genomics 2016; 48:601-15. [PMID: 27287924 DOI: 10.1152/physiolgenomics.00035.2016] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Accepted: 06/04/2016] [Indexed: 12/11/2022] Open
Abstract
Expression of a cohort of disease-associated genes, some of which are active in fetal myocardium, is considered a hallmark of transcriptional change in cardiac hypertrophy models. How this transcriptome remodeling is affected by the common genetic variation present in populations is unknown. We examined the role of genetics, as well as contributions of chromatin proteins, to regulate cardiac gene expression and heart failure susceptibility. We examined gene expression in 84 genetically distinct inbred strains of control and isoproterenol-treated mice, which exhibited varying degrees of disease. Unexpectedly, fetal gene expression was not correlated with hypertrophic phenotypes. Unbiased modeling identified 74 predictors of heart mass after isoproterenol-induced stress, but these predictors did not enrich for any cardiac pathways. However, expanded analysis of fetal genes and chromatin remodelers as groups correlated significantly with individual systemic phenotypes. Yet, cardiac transcription factors and genes shown by gain-/loss-of-function studies to contribute to hypertrophic signaling did not correlate with cardiac mass or function in disease. Because the relationship between gene expression and phenotype was strain specific, we examined genetic contribution to expression. Strikingly, strains with similar transcriptomes in the basal heart did not cluster together in the isoproterenol state, providing comprehensive evidence that there are different genetic contributors to physiological and pathological gene expression. Furthermore, the divergence in transcriptome similarity versus genetic similarity between strains is organ specific and genome-wide, suggesting chromatin is a critical buffer between genetics and gene expression.
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Affiliation(s)
- Elaheh Karbassi
- Department of Anesthesiology, David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Emma Monte
- Department of Anesthesiology, David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Douglas J Chapski
- Department of Anesthesiology, David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Rachel Lopez
- Department of Anesthesiology, David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Manuel Rosa Garrido
- Department of Anesthesiology, David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Joseph Kim
- Department of Anesthesiology, David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Nicholas Wisniewski
- Department of Integrative Biology and Physiology, David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Christoph D Rau
- Department of Anesthesiology, David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Jessica J Wang
- Department of Medicine/Cardiology, David Geffen School of Medicine at UCLA, Los Angeles, California
| | - James N Weiss
- Department of Medicine/Cardiology, David Geffen School of Medicine at UCLA, Los Angeles, California; Department of Physiology, David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Yibin Wang
- Department of Anesthesiology, David Geffen School of Medicine at UCLA, Los Angeles, California; Department of Medicine/Cardiology, David Geffen School of Medicine at UCLA, Los Angeles, California; Department of Physiology, David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Aldons J Lusis
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, California; Department of Medicine/Cardiology, David Geffen School of Medicine at UCLA, Los Angeles, California; Department of Microbiology Immunology and Molecular Genetics, David Geffen School of Medicine at UCLA, Los Angeles, California; and
| | - Thomas M Vondriska
- Department of Anesthesiology, David Geffen School of Medicine at UCLA, Los Angeles, California; Department of Medicine/Cardiology, David Geffen School of Medicine at UCLA, Los Angeles, California; Department of Physiology, David Geffen School of Medicine at UCLA, Los Angeles, California
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Krogh-Madsen T, Sobie EA, Christini DJ. Improving cardiomyocyte model fidelity and utility via dynamic electrophysiology protocols and optimization algorithms. J Physiol 2016; 594:2525-36. [PMID: 26661516 DOI: 10.1113/jp270618] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2015] [Accepted: 09/30/2015] [Indexed: 12/15/2022] Open
Abstract
Mathematical models of cardiac electrophysiology are instrumental in determining mechanisms of cardiac arrhythmias. However, the foundation of a realistic multiscale heart model is only as strong as the underlying cell model. While there have been myriad advances in the improvement of cellular-level models, the identification of model parameters, such as ion channel conductances and rate constants, remains a challenging problem. The primary limitations to this process include: (1) such parameters are usually estimated from data recorded using standard electrophysiology voltage-clamp protocols that have not been developed with model building in mind, and (2) model parameters are typically tuned manually to subjectively match a desired output. Over the last decade, methods aimed at overcoming these disadvantages have emerged. These approaches include the use of optimization or fitting tools for parameter estimation and incorporating more extensive data for output matching. Here, we review recent advances in parameter estimation for cardiomyocyte models, focusing on the use of more complex electrophysiology protocols and global search heuristics. We also discuss future applications of such parameter identification, including development of cell-specific and patient-specific mathematical models to investigate arrhythmia mechanisms and predict therapy strategies.
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Affiliation(s)
- Trine Krogh-Madsen
- Greenberg Division of Cardiology, Weill Cornell Medical College, New York, NY, USA.,Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY, USA
| | - Eric A Sobie
- Pharmacology and Systems Therapeutics, Mount Sinai School of Medicine, New York, NY, USA
| | - David J Christini
- Greenberg Division of Cardiology, Weill Cornell Medical College, New York, NY, USA.,Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY, USA.,Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY, USA
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50
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Muszkiewicz A, Britton OJ, Gemmell P, Passini E, Sánchez C, Zhou X, Carusi A, Quinn TA, Burrage K, Bueno-Orovio A, Rodriguez B. Variability in cardiac electrophysiology: Using experimentally-calibrated populations of models to move beyond the single virtual physiological human paradigm. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2015; 120:115-27. [PMID: 26701222 PMCID: PMC4821179 DOI: 10.1016/j.pbiomolbio.2015.12.002] [Citation(s) in RCA: 104] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2015] [Revised: 11/24/2015] [Accepted: 12/02/2015] [Indexed: 01/13/2023]
Abstract
Physiological variability manifests itself via differences in physiological function between individuals of the same species, and has crucial implications in disease progression and treatment. Despite its importance, physiological variability has traditionally been ignored in experimental and computational investigations due to averaging over samples from multiple individuals. Recently, modelling frameworks have been devised for studying mechanisms underlying physiological variability in cardiac electrophysiology and pro-arrhythmic risk under a variety of conditions and for several animal species as well as human. One such methodology exploits populations of cardiac cell models constrained with experimental data, or experimentally-calibrated populations of models. In this review, we outline the considerations behind constructing an experimentally-calibrated population of models and review the studies that have employed this approach to investigate variability in cardiac electrophysiology in physiological and pathological conditions, as well as under drug action. We also describe the methodology and compare it with alternative approaches for studying variability in cardiac electrophysiology, including cell-specific modelling approaches, sensitivity-analysis based methods, and populations-of-models frameworks that do not consider the experimental calibration step. We conclude with an outlook for the future, predicting the potential of new methodologies for patient-specific modelling extending beyond the single virtual physiological human paradigm.
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Affiliation(s)
- Anna Muszkiewicz
- Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom
| | - Oliver J Britton
- Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom
| | - Philip Gemmell
- Clyde Biosciences Ltd, West Medical Building, University of Glasgow, Glasgow G12 8QQ, United Kingdom
| | - Elisa Passini
- Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom
| | - Carlos Sánchez
- Center for Computational Medicine in Cardiology (CCMC), Institute of Computational Science, Università della Svizzera italiana, Lugano, Switzerland
| | - Xin Zhou
- Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom
| | | | - T Alexander Quinn
- Department of Physiology and Biophysics, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Kevin Burrage
- Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom; Mathematical Sciences, Queensland University of Technology, Queensland 4072, Australia; ACEMS, ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, Queensland 4072, Australia
| | - Alfonso Bueno-Orovio
- Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom
| | - Blanca Rodriguez
- Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom.
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