SARS-CoV-2 infection of human iPSC-derived cardiac cells reflects cytopathic features in hearts of patients with COVID-19

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Abstract

Although coronavirus disease 2019 (COVID-19) causes cardiac dysfunction in up to 25% of patients, its pathogenesis remains unclear. Exposure of human induced pluripotent stem cell (iPSC)-derived heart cells to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) revealed productive infection and robust transcriptomic and morphological signatures of damage, particularly in cardiomyocytes. Transcriptomic disruption of structural genes corroborates adverse morphologic features, which included a distinct pattern of myofibrillar fragmentation and nuclear disruption. Human autopsy specimens from patients with COVID-19 reflected similar alterations, particularly sarcomeric fragmentation. These striking cytopathic features in cardiomyocytes provide insights into SARS-CoV-2-induced cardiac damage, offer a platform for discovery of potential therapeutics, and raise concerns about the long-term consequences of COVID-19 in asymptomatic as well as severe cases.

Abstract

Infection of human iPSC-derived cardiomyocytes by SARS-CoV-2 leads to specific cytopathic features reflected in patient autopsy samples.

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Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

Fei Zhou, Ting Yu, Ronghui Du … (2020)

Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days. Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

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Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.

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Paul Shannon, Andrew Markiel, Owen Ozier … (2003)

Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

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Author and article information

Journal

Journal ID (nlm-ta): Sci Transl Med

Journal ID (iso-abbrev): Sci Transl Med

Journal ID (publisher-id): STM

Title: Science Translational Medicine

Publisher: American Association for the Advancement of Science

ISSN (Print): 1946-6234

ISSN (Electronic): 1946-6242

Publication date (Electronic): 15 March 2021

Electronic Location Identifier: eabf7872

Affiliations

[1 ]Gladstone Institutes, San Francisco, CA 94158, USA.

[2 ]Biomedical Sciences PhD Program, University of California, San Francisco, CA 94158, USA.

[3 ]UC Berkeley UCSF Joint Program in Bioengineering, Berkeley, CA 94720, USA.

[4 ]UCSF Department of Neurology, San Francisco, CA 94143, USA.

[5 ]UCSF Department of Laboratory Medicine, San Francisco, CA 94143, USA.

[6 ]University of British Columbia Department of Pathology & Laboratory Medicine, Vancouver, B.C. V6Z 1Y6, Canada.

[7 ]Innovative Genomics Institute, Berkeley, CA 94704, USA.

[8 ]UCSF Department of Ophthalmology, San Francisco, CA 94158, USA.

[9 ]UCSF Department of Medicine, San Francisco, CA 94143, USA.

[10 ]UCSF Department of Bioengineering and Therapeutic Sciences, San Francisco, CA 94158, USA.

Author notes

[*]

These authors contributed equally to this work.

[† ]Co-corresponding authors. Email: todd.mcdevitt@ 123456gladstone.ucsf.edu (T.C.M.), bconklin@ 123456gladstone.ucsf.edu (B.R.C.), melanie.ott@ 123456gladstone.ucsf.edu (M.O.)

Author information

Juan A. Perez-Bermejo https://orcid.org/0000-0001-7625-358X

Serah Kang https://orcid.org/0000-0002-7316-778X

Sarah J. Rockwood https://orcid.org/0000-0002-2869-0221

Camille R. Simoneau https://orcid.org/0000-0001-9222-8130

David A. Joy https://orcid.org/0000-0001-9941-9538

Gokul N. Ramadoss https://orcid.org/0000-0002-7506-2711

Will R. Flanigan https://orcid.org/0000-0001-5900-3490

Parinaz Fozouni https://orcid.org/0000-0002-6710-1506

Huihui Li https://orcid.org/0000-0002-4469-3705

Pei-Yi Chen https://orcid.org/0000-0002-7639-2325

Ken Nakamura https://orcid.org/0000-0002-9192-182X

Jeffrey D. Whitman https://orcid.org/0000-0002-3502-5799

Paul J. Hanson https://orcid.org/0000-0002-0655-4843

Melanie Ott https://orcid.org/0000-0002-5697-1274

Bruce R. Conklin https://orcid.org/0000-0003-1463-6061

Todd C. McDevitt https://orcid.org/0000-0002-8905-4931

Article

Publisher ID: abf7872

DOI: 10.1126/scitranslmed.abf7872

PMC ID: 8128284

PubMed ID: 33723017

SO-VID: cecf4bca-d0e8-443f-9211-ed23c2972bbb

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

History

Date received : 20 November 2020

Date accepted : 10 March 2021

Date: 15 March 2021