Extrapulmonary manifestations of COVID-19 are associated with a much higher mortality rate than pulmonary manifestations. However, little is known about the pathogenesis of systemic complications of COVID-19. Here, we create a murine model of SARS-CoV-2–induced severe systemic toxicity and multiorgan involvement by expressing the human ACE2 transgene in multiple tissues via viral delivery, followed by systemic administration of SARS-CoV-2. The animals develop a profound phenotype within 7 days with severe weight loss, morbidity, and failure to thrive. We demonstrate that there is metabolic suppression of oxidative phosphorylation and the tricarboxylic acid (TCA) cycle in multiple organs with neutrophilia, lymphopenia, and splenic atrophy, mirroring human COVID-19 phenotypes. Animals had a significantly lower heart rate, and electron microscopy demonstrated myofibrillar disarray and myocardial edema, a common pathogenic cardiac phenotype in human COVID-19. We performed metabolomic profiling of peripheral blood and identified a panel of TCA cycle metabolites that served as biomarkers of depressed oxidative phosphorylation. Finally, we observed that SARS-CoV-2 induces epigenetic changes of DNA methylation, which affects expression of immune response genes and could, in part, contribute to COVID-19 pathogenesis. Our model suggests that SARS-CoV-2–induced metabolic reprogramming and epigenetic changes in internal organs could contribute to systemic toxicity and lethality in COVID-19.
Shen Li, Feiyang Ma, Tomohiro Yokota, Gustavo Garcia Jr., Amelia Palermo, Yijie Wang, Colin Farrell, Yu-Chen Wang, Rimao Wu, Zhiqiang Zhou, Calvin Pan, Marco Morselli, Michael A. Teitell, Sergey Ryazantsev, Gregory A. Fishbein, Johanna ten Hoeve, Valerie A. Arboleda, Joshua Bloom, Barbara Dillon, Matteo Pellegrini, Aldons J. Lusis, Thomas G. Graeber, Vaithilingaraja Arumugaswami, Arjun Deb
Usage data is cumulative from December 2021 through December 2022.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.