1
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Salvador M, Kong F, Peirlinck M, Parker DW, Chubb H, Dubin AM, Marsden AL. Digital twinning of cardiac electrophysiology for congenital heart disease. J R Soc Interface 2024; 21:20230729. [PMID: 38835246 DOI: 10.1098/rsif.2023.0729] [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: 12/08/2023] [Accepted: 03/15/2024] [Indexed: 06/06/2024] Open
Abstract
In recent years, blending mechanistic knowledge with machine learning has had a major impact in digital healthcare. In this work, we introduce a computational pipeline to build certified digital replicas of cardiac electrophysiology in paediatric patients with congenital heart disease. We construct the patient-specific geometry by means of semi-automatic segmentation and meshing tools. We generate a dataset of electrophysiology simulations covering cell-to-organ level model parameters and using rigorous mathematical models based on differential equations. We previously proposed Branched Latent Neural Maps (BLNMs) as an accurate and efficient means to recapitulate complex physical processes in a neural network. Here, we employ BLNMs to encode the parametrized temporal dynamics of in silico 12-lead electrocardiograms (ECGs). BLNMs act as a geometry-specific surrogate model of cardiac function for fast and robust parameter estimation to match clinical ECGs in paediatric patients. Identifiability and trustworthiness of calibrated model parameters are assessed by sensitivity analysis and uncertainty quantification.
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Affiliation(s)
- Matteo Salvador
- Institute for Computational and Mathematical Engineering, Stanford University , Stanford, CA, USA
- Cardiovascular Institute, Stanford University , Stanford, CA, USA
- Pediatric Cardiology, Stanford University , Stanford, CA, USA
| | - Fanwei Kong
- Institute for Computational and Mathematical Engineering, Stanford University , Stanford, CA, USA
- Cardiovascular Institute, Stanford University , Stanford, CA, USA
- Pediatric Cardiology, Stanford University , Stanford, CA, USA
| | - Mathias Peirlinck
- Department of Biomechanical Engineering, Delft University of Technology , Delft, The Netherlands
| | - David W Parker
- Stanford Research Computing Center, Stanford University , Stanford, CA, USA
| | - Henry Chubb
- Pediatric Cardiology, Stanford University , Stanford, CA, USA
| | - Anne M Dubin
- Pediatric Cardiology, Stanford University , Stanford, CA, USA
| | - Alison L Marsden
- Institute for Computational and Mathematical Engineering, Stanford University , Stanford, CA, USA
- Cardiovascular Institute, Stanford University , Stanford, CA, USA
- Pediatric Cardiology, Stanford University , Stanford, CA, USA
- Department of Bioengineering, Stanford University , Stanford, CA, USA
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2
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Tikenoğullar i OZ, Peirlinck M, Chubb H, Dubin AM, Kuhl E, Marsden AL. Effects of cardiac growth on electrical dyssynchrony in the single ventricle patient. Comput Methods Biomech Biomed Engin 2024; 27:1011-1027. [PMID: 37314141 PMCID: PMC10719423 DOI: 10.1080/10255842.2023.2222203] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 04/27/2023] [Accepted: 05/04/2023] [Indexed: 06/15/2023]
Abstract
Single ventricle patients, including those with hypoplastic left heart syndrome (HLHS), typically undergo three palliative heart surgeries culminating in the Fontan procedure. HLHS is associated with high rates of morbidity and mortality, and many patients develop arrhythmias, electrical dyssynchrony, and eventually ventricular failure. However, the correlation between ventricular enlargement and electrical dysfunction in HLHS physiology remains poorly understood. Here we characterize the relationship between growth and electrophysiology in HLHS using computational modeling. We integrate a personalized finite element model, a volumetric growth model, and a personalized electrophysiology model to perform controlled in silico experiments. We show that right ventricle enlargement negatively affects QRS duration and interventricular dyssynchrony. Conversely, left ventricle enlargement can partially compensate for this dyssynchrony. These findings have potential implications on our understanding of the origins of electrical dyssynchrony and, ultimately, the treatment of HLHS patients.
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Affiliation(s)
- O. Z. Tikenoğullar i
- Department of Mechanical Engineering, Stanford University, Stanford, California, USA
| | - M. Peirlinck
- Department of Biomechanical Engineering, Delft University of Technology, Delft, Netherlands
| | - H. Chubb
- Department of Pediatrics (Cardiology), Stanford University, Stanford, California, USA
| | - A. M. Dubin
- Department of Pediatrics (Cardiology), Stanford University, Stanford, California, USA
| | - E. Kuhl
- Department of Mechanical Engineering, Stanford University, Stanford, California, USA
| | - A. L. Marsden
- Department of Mechanical Engineering, Stanford University, Stanford, California, USA
- Department of Pediatrics (Cardiology), Stanford University, Stanford, California, USA
- Department of Bioengineering, Stanford University, Stanford, California, USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, California, USA
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3
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Llopis-Lorente J, Baroudi S, Koloskoff K, Mora MT, Basset M, Romero L, Benito S, Dayan F, Saiz J, Trenor B. Combining pharmacokinetic and electrophysiological models for early prediction of drug-induced arrhythmogenicity. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 242:107860. [PMID: 37844488 DOI: 10.1016/j.cmpb.2023.107860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 09/28/2023] [Accepted: 10/10/2023] [Indexed: 10/18/2023]
Abstract
BACKGROUND AND OBJECTIVE In silico methods are gaining attention for predicting drug-induced Torsade de Pointes (TdP) in different stages of drug development. However, many computational models tended not to account for inter-individual response variability due to demographic covariates, such as sex, or physiologic covariates, such as renal function, which may be crucial when predicting TdP. This study aims to compare the effects of drugs in male and female populations with normal and impaired renal function using in silico methods. METHODS Pharmacokinetic models considering sex and renal function as covariates were implemented from data published in pharmacokinetic studies. Drug effects were simulated using an electrophysiologically calibrated population of cellular models of 300 males and 300 females. The population of models was built by modifying the endocardial action potential model published by O'Hara et al. (2011) according to the experimentally measured gene expression levels of 12 ion channels. RESULTS Fifteen pharmacokinetic models for CiPA drugs were implemented and validated in this study. Eight pharmacokinetic models included the effect of renal function and four the effect of sex. The mean difference in action potential duration (APD) between male and female populations was 24.9 ms (p<0.05). Our simulations indicated that women with impaired renal function were particularly susceptible to drug-induced arrhythmias, whereas healthy men were less prone to TdP. Differences between patient groups were more pronounced for high TdP-risk drugs. The proposed in silico tool also revealed that individuals with impaired renal function, electrophysiologically simulated with hyperkalemia (extracellular potassium concentration [K+]o = 7 mM) exhibited less pronounced APD prolongation than individuals with normal potassium levels. The pharmacokinetic/electrophysiological framework was used to determine the maximum safe dose of dofetilide in different patient groups. As a proof of concept, 3D simulations were also run for dofetilide obtaining QT prolongation in accordance with previously reported clinical values. CONCLUSIONS This study presents a novel methodology that combines pharmacokinetic and electrophysiological models to incorporate the effects of sex and renal function into in silico drug simulations and highlights their impact on TdP-risk assessment. Furthermore, it may also help inform maximum dose regimens that ensure TdP-related safety in a specific sub-population of patients.
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Affiliation(s)
- Jordi Llopis-Lorente
- Centro de Investigación e Innovación en Bioingeniería (Ci(2)B), Universitat Politècnica de València, camino de Vera, s/n, 46022, Valencia, Spain
| | | | | | - Maria Teresa Mora
- Centro de Investigación e Innovación en Bioingeniería (Ci(2)B), Universitat Politècnica de València, camino de Vera, s/n, 46022, Valencia, Spain
| | | | - Lucía Romero
- Centro de Investigación e Innovación en Bioingeniería (Ci(2)B), Universitat Politècnica de València, camino de Vera, s/n, 46022, Valencia, Spain
| | | | | | - Javier Saiz
- Centro de Investigación e Innovación en Bioingeniería (Ci(2)B), Universitat Politècnica de València, camino de Vera, s/n, 46022, Valencia, Spain
| | - Beatriz Trenor
- Centro de Investigación e Innovación en Bioingeniería (Ci(2)B), Universitat Politècnica de València, camino de Vera, s/n, 46022, Valencia, Spain.
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4
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Salvador M, Kong F, Peirlinck M, Parker DW, Chubb H, Dubin AM, Marsden AL. Digital twinning of cardiac electrophysiology for congenital heart disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.27.568942. [PMID: 38076810 PMCID: PMC10705388 DOI: 10.1101/2023.11.27.568942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
In recent years, blending mechanistic knowledge with machine learning has had a major impact in digital healthcare. In this work, we introduce a computational pipeline to build certified digital replicas of cardiac electrophysiology in pediatric patients with congenital heart disease. We construct the patient-specific geometry by means of semi-automatic segmentation and meshing tools. We generate a dataset of electrophysiology simulations covering cell-to-organ level model parameters and utilizing rigorous mathematical models based on differential equations. We previously proposed Branched Latent Neural Maps (BLNMs) as an accurate and efficient means to recapitulate complex physical processes in a neural network. Here, we employ BLNMs to encode the parametrized temporal dynamics of in silico 12-lead electrocardiograms (ECGs). BLNMs act as a geometry-specific surrogate model of cardiac function for fast and robust parameter estimation to match clinical ECGs in pediatric patients. Identifiability and trustworthiness of calibrated model parameters are assessed by sensitivity analysis and uncertainty quantification.
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Affiliation(s)
- Matteo Salvador
- Institute for Computational and Mathematical Engineering, Stanford University, California, USA
- Cardiovascular Institute, Stanford University, California, USA
- Pediatric Cardiology, Stanford University, California, USA
| | - Fanwei Kong
- Cardiovascular Institute, Stanford University, California, USA
- Pediatric Cardiology, Stanford University, California, USA
| | - Mathias Peirlinck
- Department of Biomechanical Engineering, Delft University of Technology, Delft, Netherlands
| | - David W Parker
- Stanford Research Computing Center, Stanford University, California, USA
| | - Henry Chubb
- Pediatric Cardiology, Stanford University, California, USA
| | - Anne M Dubin
- Pediatric Cardiology, Stanford University, California, USA
| | - Alison Lesley Marsden
- Department of Bioengineering, Stanford University, California, USA
- Institute for Computational and Mathematical Engineering, Stanford University, California, USA
- Cardiovascular Institute, Stanford University, California, USA
- Pediatric Cardiology, Stanford University, California, USA
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5
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Africa PC, Piersanti R, Regazzoni F, Bucelli M, Salvador M, Fedele M, Pagani S, Dede' L, Quarteroni A. lifex-ep: a robust and efficient software for cardiac electrophysiology simulations. BMC Bioinformatics 2023; 24:389. [PMID: 37828428 PMCID: PMC10571323 DOI: 10.1186/s12859-023-05513-8] [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: 08/03/2023] [Accepted: 10/02/2023] [Indexed: 10/14/2023] Open
Abstract
BACKGROUND Simulating the cardiac function requires the numerical solution of multi-physics and multi-scale mathematical models. This underscores the need for streamlined, accurate, and high-performance computational tools. Despite the dedicated endeavors of various research teams, comprehensive and user-friendly software programs for cardiac simulations, capable of accurately replicating both normal and pathological conditions, are still in the process of achieving full maturity within the scientific community. RESULTS This work introduces [Formula: see text]-ep, a publicly available software for numerical simulations of the electrophysiology activity of the cardiac muscle, under both normal and pathological conditions. [Formula: see text]-ep employs the monodomain equation to model the heart's electrical activity. It incorporates both phenomenological and second-generation ionic models. These models are discretized using the Finite Element method on tetrahedral or hexahedral meshes. Additionally, [Formula: see text]-ep integrates the generation of myocardial fibers based on Laplace-Dirichlet Rule-Based Methods, previously released in Africa et al., 2023, within [Formula: see text]-fiber. As an alternative, users can also choose to import myofibers from a file. This paper provides a concise overview of the mathematical models and numerical methods underlying [Formula: see text]-ep, along with comprehensive implementation details and instructions for users. [Formula: see text]-ep features exceptional parallel speedup, scaling efficiently when using up to thousands of cores, and its implementation has been verified against an established benchmark problem for computational electrophysiology. We showcase the key features of [Formula: see text]-ep through various idealized and realistic simulations conducted in both normal and pathological scenarios. Furthermore, the software offers a user-friendly and flexible interface, simplifying the setup of simulations using self-documenting parameter files. CONCLUSIONS [Formula: see text]-ep provides easy access to cardiac electrophysiology simulations for a wide user community. It offers a computational tool that integrates models and accurate methods for simulating cardiac electrophysiology within a high-performance framework, while maintaining a user-friendly interface. [Formula: see text]-ep represents a valuable tool for conducting in silico patient-specific simulations.
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Affiliation(s)
- Pasquale Claudio Africa
- MOX, Department of Mathematics, Politecnico di Milano, Milano, Italy
- mathLab, Mathematics Area, SISSA International School for Advanced Studies, Trieste, Italy
| | - Roberto Piersanti
- MOX, Department of Mathematics, Politecnico di Milano, Milano, Italy.
| | | | - Michele Bucelli
- MOX, Department of Mathematics, Politecnico di Milano, Milano, Italy
| | - Matteo Salvador
- MOX, Department of Mathematics, Politecnico di Milano, Milano, Italy
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, California, USA
| | - Marco Fedele
- MOX, Department of Mathematics, Politecnico di Milano, Milano, Italy
| | - Stefano Pagani
- MOX, Department of Mathematics, Politecnico di Milano, Milano, Italy
| | - Luca Dede'
- MOX, Department of Mathematics, Politecnico di Milano, Milano, Italy
| | - Alfio Quarteroni
- MOX, Department of Mathematics, Politecnico di Milano, Milano, Italy
- Institute of Mathematics, École Polytechnique Fédérale de Lausanne, Lausanne, Professor emeritus, Switzerland
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6
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Seeman MV. Schizophrenia in Women: Clinical Considerations. Psychiatr Clin North Am 2023; 46:475-486. [PMID: 37500245 DOI: 10.1016/j.psc.2023.04.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Men and women, for biologic and sociocultural reasons, differ in the nature of their risks for schizophrenia and also in their care needs. Women with schizophrenia have several reproduction-associated risks and care needs that require special clinical consideration. They also have several specific risks related to antipsychotics and gender-associated needs not necessarily related to biology. These require clinicians' diagnostic acumen, treatment skills, cultural sensitivity, and advocacy know-how. Although this does not pertain to everyone, awareness on the part of clinicians is essential. This article addresses the current evidence for difference.
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Affiliation(s)
- Mary V Seeman
- Department of Psychiatry, University of Toronto, Toronto, Ontario M5P3L6, Canada.
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7
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Rodero C, Baptiste TMG, Barrows RK, Keramati H, Sillett CP, Strocchi M, Lamata P, Niederer SA. A systematic review of cardiac in-silico clinical trials. PROGRESS IN BIOMEDICAL ENGINEERING (BRISTOL, ENGLAND) 2023; 5:032004. [PMID: 37360227 PMCID: PMC10286106 DOI: 10.1088/2516-1091/acdc71] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 05/26/2023] [Accepted: 06/07/2023] [Indexed: 06/28/2023]
Abstract
Computational models of the heart are now being used to assess the effectiveness and feasibility of interventions through in-silico clinical trials (ISCTs). As the adoption and acceptance of ISCTs increases, best practices for reporting the methodology and analysing the results will emerge. Focusing in the area of cardiology, we aim to evaluate the types of ISCTs, their analysis methods and their reporting standards. To this end, we conducted a systematic review of cardiac ISCTs over the period of 1 January 2012-1 January 2022, following the preferred reporting items for systematic reviews and meta-analysis (PRISMA). We considered cardiac ISCTs of human patient cohorts, and excluded studies of single individuals and those in which models were used to guide a procedure without comparing against a control group. We identified 36 publications that described cardiac ISCTs, with most of the studies coming from the US and the UK. In 75% of the studies, a validation step was performed, although the specific type of validation varied between the studies. ANSYS FLUENT was the most commonly used software in 19% of ISCTs. The specific software used was not reported in 14% of the studies. Unlike clinical trials, we found a lack of consistent reporting of patient demographics, with 28% of the studies not reporting them. Uncertainty quantification was limited, with sensitivity analysis performed in only 19% of the studies. In 97% of the ISCTs, no link was provided to provide easy access to the data or models used in the study. There was no consistent naming of study types with a wide range of studies that could potentially be considered ISCTs. There is a clear need for community agreement on minimal reporting standards on patient demographics, accepted standards for ISCT cohort quality control, uncertainty quantification, and increased model and data sharing.
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Affiliation(s)
- Cristobal Rodero
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Cardiac Electro-Mechanics Research Group (CEMRG), Department of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Cardiac Modelling and Imaging Biomarkers (CMIB), Department of Biomedical Engineering and Imaging Sciences Department, King’s College London, London, United Kingdom
| | - Tiffany M G Baptiste
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Cardiac Electro-Mechanics Research Group (CEMRG), Department of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Rosie K Barrows
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Cardiac Electro-Mechanics Research Group (CEMRG), Department of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Hamed Keramati
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Cardiac Electro-Mechanics Research Group (CEMRG), Department of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Cardiac Modelling and Imaging Biomarkers (CMIB), Department of Biomedical Engineering and Imaging Sciences Department, King’s College London, London, United Kingdom
| | - Charles P Sillett
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Cardiac Electro-Mechanics Research Group (CEMRG), Department of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Marina Strocchi
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Cardiac Electro-Mechanics Research Group (CEMRG), Department of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Pablo Lamata
- Cardiac Modelling and Imaging Biomarkers (CMIB), Department of Biomedical Engineering and Imaging Sciences Department, King’s College London, London, United Kingdom
| | - Steven A Niederer
- Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Imperial College London, London, United Kingdom
- Cardiac Electro-Mechanics Research Group (CEMRG), Department of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Turing Research and Innovation Cluster in Digital Twins (TRIC: DT), The Alan Turing Institute, London, United Kingdom
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8
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Chang DH, Dumanski SM, Ahmed SB. Female sex-specific considerations to improve rigor and reproducibility in cardiovascular research. Am J Physiol Heart Circ Physiol 2023; 324:H279-H287. [PMID: 36563011 DOI: 10.1152/ajpheart.00462.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Cardiovascular disease is the leading cause of death in women. Despite recognition of sex-specific differences in cardiovascular health, females are underrepresented across all aspects of cardiovascular research, playing a key role in reducing rigor and reproducibility in cardiovascular research and contributing to these poorer health outcomes. Therefore, we propose a framework to capture factors associated with the female sex at the preclinical, recruitment, data collection, and data analysis stages. In preclinical cardiovascular research, female experimental models are commonly excluded despite similar variability in findings compared with males. To reduce this sex bias, the inclusion of female models and the incorporation of sex as a biological variable are critical to improve reproducibility and inform clinical research and care. Although funding agencies have mandated the inclusion of women in clinical trials, greater efforts are needed to achieve optimal participation-to-prevalence ratio to increase the generalizability of results to real-world settings. Female participants face more stringent exclusion criteria in research compared with males owing to sex-specific factors. However, their routine exclusion from cardiovascular research is not only unethical but limits generalizability and applicability to clinical practice. Identifying sex assigned at birth, collecting information on female sex-specific and -predominant factors associated with cardiovascular health and risk, and stratifying data by sex, including adverse events, are essential to ensure reproducibility and relevance of findings to target populations. Increasing female representation and the incorporation of female sex-specific cardiovascular risk factors in cardiovascular research will not only lead to enhanced rigor and reproducibility but improved cardiovascular health for all.
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Affiliation(s)
- Danica H Chang
- Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada.,Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Libin Cardiovascular Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Sandra M Dumanski
- Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Libin Cardiovascular Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Alberta Kidney Disease Network, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,O'Brien Institute for Public Health, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Sofia B Ahmed
- Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Libin Cardiovascular Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Alberta Kidney Disease Network, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,O'Brien Institute for Public Health, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
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9
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Sutanto H, Hertanto DM, Susilo H, Wungu CDK. Grapefruit Flavonoid Naringenin Sex-Dependently Modulates Action Potential in an In Silico Human Ventricular Cardiomyocyte Model. Antioxidants (Basel) 2022; 11:antiox11091672. [PMID: 36139745 PMCID: PMC9495662 DOI: 10.3390/antiox11091672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 08/22/2022] [Accepted: 08/25/2022] [Indexed: 11/17/2022] Open
Abstract
Recent in vitro studies showed that grapefruit (Citrus × paradisi) flavonoid naringenin alters the function of cardiac ion channels. Here, we explored the effect of naringenin on cardiomyocyte action potentials (APs) using a detailed in silico model of ventricular electrophysiology. Concentration-dependent effects of naringenin on seven major cardiac ion channels were incorporated into the Tomek–Rodriguez modification of O’Hara–Rudy (ToR-ORd) human ventricular endocardium model. To investigate the sex-dependent effect of naringenin, previously reported sex-specific ionic modifications were implemented into the model. Next, populations of 1000 models accommodating intercellular variability were generated. The results show, naringenin at various concentrations prolonged AP duration (APD) in male and female cardiomyocytes. Pacing cells at higher frequencies abbreviated APD differently in males versus females; for example, at 3 Hz, 50 μM naringenin induced AP and calcium alternans only in the female cardiomyocyte. Finally, a population modeling approach corroborated that naringenin significantly prolonged APD in a concentration-dependent manner, with a larger effect in females than in males. In conclusion, our study demonstrates that the APD-prolonging effect of naringenin was larger in females, and that pacing at faster rates induces AP alternation earlier in females, suggesting a potentially higher proarrhythmic risk of naringenin in females than in males.
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Affiliation(s)
- Henry Sutanto
- Department of Internal Medicine, Faculty of Medicine, Universitas Airlangga, Surabaya 60131, Indonesia
- Correspondence:
| | - Decsa Medika Hertanto
- Department of Internal Medicine, Faculty of Medicine, Universitas Airlangga, Surabaya 60131, Indonesia
- Department of Internal Medicine, Dr. Soetomo General Hospital, Surabaya 60286, Indonesia
| | - Hendri Susilo
- Department of Cardiology and Vascular Medicine, Universitas Airlangga Teaching Hospital, Surabaya 60115, Indonesia
| | - Citrawati Dyah Kencono Wungu
- Department of Physiology and Medical Biochemistry, Faculty of Medicine, Universitas Airlangga, Surabaya 60131, Indonesia
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10
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St. Pierre SR, Peirlinck M, Kuhl E. Sex Matters: A Comprehensive Comparison of Female and Male Hearts. Front Physiol 2022; 13:831179. [PMID: 35392369 PMCID: PMC8980481 DOI: 10.3389/fphys.2022.831179] [Citation(s) in RCA: 53] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 02/02/2022] [Indexed: 12/27/2022] Open
Abstract
Cardiovascular disease in women remains under-diagnosed and under-treated. Recent studies suggest that this is caused, at least in part, by the lack of sex-specific diagnostic criteria. While it is widely recognized that the female heart is smaller than the male heart, it has long been ignored that it also has a different microstructural architecture. This has severe implications on a multitude of cardiac parameters. Here, we systematically review and compare geometric, functional, and structural parameters of female and male hearts, both in the healthy population and in athletes. Our study finds that, compared to the male heart, the female heart has a larger ejection fraction and beats at a faster rate but generates a smaller cardiac output. It has a lower blood pressure but produces universally larger contractile strains. Critically, allometric scaling, e.g., by lean body mass, reduces but does not completely eliminate the sex differences between female and male hearts. Our results suggest that the sex differences in cardiac form and function are too complex to be ignored: the female heart is not just a small version of the male heart. When using similar diagnostic criteria for female and male hearts, cardiac disease in women is frequently overlooked by routine exams, and it is diagnosed later and with more severe symptoms than in men. Clearly, there is an urgent need to better understand the female heart and design sex-specific diagnostic criteria that will allow us to diagnose cardiac disease in women equally as early, robustly, and reliably as in men. Systematic Review Registration https://livingmatter.stanford.edu/.
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Affiliation(s)
- Sarah R. St. Pierre
- Department of Mechanical Engineering, Stanford University, Stanford, CA, United States
| | - Mathias Peirlinck
- Department of Mechanical Engineering, Stanford University, Stanford, CA, United States
- Department of Biomechanical Engineering, Delft University of Technology, Delft, Netherlands
- Department of Biomedical Engineering, Erasmus MC, Rotterdam, Netherlands
| | - Ellen Kuhl
- Department of Mechanical Engineering, Stanford University, Stanford, CA, United States
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