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Sex differences in viral entry protein expression, host responses to SARS-CoV-2, and in vitro responses to sex steroid hormone treatment in COVID-19.


ABSTRACT: Epidemiological studies suggest that men exhibit a higher mortality rate to COVID-19 than women, yet the underlying biology is largely unknown. Here, we seek to delineate sex differences in the expression of entry genes ACE2 and TMPRSS2 , host responses to SARS-CoV-2, and in vitro responses to sex steroid hormone treatment. Using over 220,000 human gene expression profiles covering a wide range of age, tissues, and diseases, we found that male samples show higher expression levels of ACE2 and TMPRSS2 , especially in the older group (>60 years) and in the kidney. Analysis of 6,031 COVID-19 patients at Mount Sinai Health System revealed that men have significantly higher creatinine levels, an indicator of impaired kidney function. Further analysis of 782 COVID-19 patient gene expression profiles taken from upper airway and blood suggested men and women present profound expression differences in responses to SARS-CoV-2. Computational deconvolution analysis of these profiles revealed male COVID-19 patients have enriched kidney-specific mesangial cells in blood compared to healthy patients. Finally, we observed selective estrogen receptor modulators, but not other hormone drugs (agonists/antagonists of estrogen, androgen, and progesterone), could reduce SARS-CoV-2 infection in vitro.

SUBMITTER: Sun M 

PROVIDER: S-EPMC7654875 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Epidemiological studies suggest that men exhibit a higher mortality rate to COVID-19 than women, yet the underlying biology is largely unknown. Here, we seek to delineate sex differences in the gene expression of viral entry proteins ACE2 and TMPRSS2, and host transcriptional responses to SARS-CoV-2 through large-scale analysis of genomic and clinical data. We first compiled 220,000 human gene expression profiles from three databases and completed the meta-information through machine learning an  ...[more]

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