ArticleStem cell research & therapy2023
SARS-CoV-2-infected hiPSC-derived cardiomyocytes reveal dynamic changes in the COVID-19 hearts.
Article in Stem cell research & therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- COVID-19 multi-omics reveal organ-specific responses and biomarkers.Journal of translational medicine · 2026Article
- Risk impact of SARS-CoV-2 coronavirus and spike protein on cardiac tissue: a comprehensive review.Physiological research · 2024Review
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Authors and funding
11 authors at 5 institutions in 1 country.
Funding
Abstract
backgroundThe ongoing coronavirus disease 2019 (COVID-19) pandemic has had an enormous impact on our societies. Moreover, the disease's extensive and sustained symptoms are now becoming a nonnegligible medical challenge. In this respect, data indicate that heart failure is one of the most common readmission diagnoses among COVID-19 patients.
methodsIn this study, we used human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes to develop an in vitro model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and studied the dynamic changes occurring in cardiomyocytes after SARS-CoV-2 infection.
resultsTo this end, we have created an effective time series SARS-CoV-2 infection model exhibiting different functional patterns of up- and downregulated proteins, and demonstrating that SARS-CoV-2 mainly affects (i) the lipid and the energy metabolism of hiPSC-derived cardiomyocytes during the early infection stage, and (ii) the DNA repair ability of cardiomyocytes during the late infection stage. By analyzing the proteome changes occurring at different infection timepoints, we were able to observe that the simulated disease (COVID-19) course developed rapidly, and that each of the studied timepoints was characterized by a distinct protein expression pattern.
conclusionsOur findings highlight the importance of early detection and personalized treatment based on the disease stage. Finally, by combing the proteomics data with virus-host interaction network analysis, we were able to identify several potential drug targets for the disease.
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