For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
10
views
57
references
 Top references
cited by
42
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
2 collections
    0
    shares
      338
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

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

      Preprint
      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Although COVID-19 causes cardiac dysfunction in up to 25% of patients, its pathogenesis remains unclear. Exposure of human iPSC-derived heart cells to SARS-CoV-2 revealed productive infection and robust transcriptomic and morphological signatures of damage, particularly in cardiomyocytes. Transcriptomic disruption of structural proteins corroborated adverse morphologic features, which included a distinct pattern of myofibrillar fragmentation and numerous iPSC-cardiomyocytes lacking nuclear DNA. Human autopsy specimens from COVID-19 patients displayed similar sarcomeric disruption, as well as cardiomyocytes without DNA staining. These striking cytopathic features provide new insights into SARS-CoV-2 induced cardiac damage, offer a platform for discovery of potential therapeutics, and raise serious concerns about the long-term consequences of COVID-19.

          Related collections

          Most cited references57

          • Record: found
          • Abstract: found
          • Article: not found

          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.
          Article 0 comments Cited 13449 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Cytoscape: a software environment for integrated models of biomolecular interaction networks.

            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.
            Article 0 comments Cited 10949 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              clusterProfiler: an R package for comparing biological themes among gene clusters.

              Guangchuang Yu, Li-Gen Wang, Yanyan Han … (2012)
              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.
              Article 0 comments Cited 10923 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Journal
                Journal ID (nlm-ta): bioRxiv
                Journal ID (publisher-id): BIORXIV
                Title: bioRxiv
                Publisher: Cold Spring Harbor Laboratory
                Publication date (Electronic): 12 September 2020
                Electronic Location Identifier: 2020.08.25.265561
                Affiliations
                [1 ]Gladstone Institutes, San Francisco, CA
                [2 ]Biomedical Sciences PhD Program, University of California, San Francisco, CA
                [3 ]UC Berkeley UCSF Joint Program in Bioengineering, Berkeley, CA
                [4 ]UCSF Department of Neurology, San Francisco, CA
                [5 ]UCSF Department of Laboratory Medicine, San Francisco, CA
                [6 ]Innovative Genomics Institute, Berkeley, CA
                [7 ]UCSF Department of Ophthalmology, San Francisco, CA
                [8 ]UCSF Department of Medicine, San Francisco, CA
                [9 ]UCSF Department of Bioengineering and Therapeutic Sciences, San Francisco, CA
                Author notes
                [*]

                These authors contributed equally to this work.

                Author Contributions

                J.P.B., S.K., S.J.R., B.R.C. and T.C.M. designed and supervised the study. J.P.B., S.K., S.J.R., G.N.R., performed the cell culture and differentiation. C.R.S. prepared SARS-CoV-2 virus, performed the infections and all BSL3 sample collection. J.P.B., S.K., S.J.R. performed the immunostaining and imaging. J.P.B., S.K., S.J.R., G.N.R. performed the qPCR analyses. J.P.B., S.K., S.J.R., D.A.J, performed the RNA library preparation and sequencing. D.A.J. and W.R.F. performed the bioinformatic analyses. J.P.B., S.K., H.L. performed the electron microscopy studies. J.D.W. provided patient samples. A.C.S. performed the histological processing and tissue staining. All authors contributed to data analyses, writing the manuscript and figure preparation.

                [† ]Co-corresponding authors.
                Article
                DOI: 10.1101/2020.08.25.265561
                PMC ID: 7491510
                PubMed ID: 32935097
                SO-VID: de7c8697-a780-49ed-9506-8291ab128ba8
                License:

                This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use.

                History
                Categories
                Subject: Article

                Data availability:

                Comments

                Comment on this article

                scite_

                Similar content338

                See all similar

                Cited by42

                See all cited by

                Most referenced authors3,092

                See all reference authors