Unknown

Dataset Information

0

A virus-free cellular model recapitulates several features of severe COVID-19.


ABSTRACT: As for all newly-emergent pathogens, SARS-CoV-2 presents with a relative paucity of clinical information and experimental models, a situation hampering both the development of new effective treatments and the prediction of future outbreaks. Here, we find that a simple virus-free model, based on publicly available transcriptional data from human cell lines, is surprisingly able to recapitulate several features of the clinically relevant infections. By segregating cell lines (n = 1305) from the CCLE project on the base of their sole angiotensin-converting enzyme 2 (ACE2) mRNA content, we found that overexpressing cells present with molecular features resembling those of at-risk patients, including senescence, impairment of antibody production, epigenetic regulation, DNA repair and apoptosis, neutralization of the interferon response, proneness to an overemphasized innate immune activity, hyperinflammation by IL-1, diabetes, hypercoagulation and hypogonadism. Likewise, several pathways were found to display a differential expression between sexes, with males being in the least advantageous position, thus suggesting that the model could reproduce even the sex-related disparities observed in the clinical outcome of patients with COVID-19. Overall, besides validating a new disease model, our data suggest that, in patients with severe COVID-19, a baseline ground could be already present and, as a consequence, the viral infection might simply exacerbate a variety of latent (or inherent) pre-existing conditions, representing therefore a tipping point at which they become clinically significant.

SUBMITTER: Lavorgna G 

PROVIDER: S-EPMC8410838 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC9203559 | biostudies-literature
| S-BSST416 | biostudies-other
| S-SCDT-EMM-2020-13038 | biostudies-other
2021-11-18 | GSE189015 | GEO
2024-01-22 | PXD043807 | Pride
2021-01-15 | GSE164805 | GEO
2022-09-22 | E-MTAB-12236 | biostudies-arrayexpress
2020-10-28 | GSE158127 | GEO
| S-EPMC7199685 | biostudies-literature
| S-EPMC8427009 | biostudies-literature