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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2021
Data sources: Datacite
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2021
Data sources: ZENODO
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2021
Data sources: Datacite
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Dataset related to article "ACE2 and TMPRSS2 variants and expression as candidates to sex and country differences in COVID-19 severity in Italy"

Authors: Asselta, Rosanna; Paraboschi, Elvezia Maria; Mantovani, Alberto; Duga, Stefano;

Dataset related to article "ACE2 and TMPRSS2 variants and expression as candidates to sex and country differences in COVID-19 severity in Italy"

Abstract

This record contains data related to article "ACE2 and TMPRSS2 variants and expression as candidates to sex and country differences in COVID-19 severity in Italy" Abstract: As the outbreak of coronavirus disease 2019 (COVID-19) progresses, prognostic markers for early identification of high-risk individuals are an urgent medical need. Italy has one of the highest numbers of SARS-CoV-2-related deaths and one of the highest mortality rates. Worldwide, a more severe course of COVID-19 is associated with older age, comorbidities, and male sex. Hence, we searched for possible genetic components of COVID-19 severity among Italians by looking at expression levels and variants in ACE2 and TMPRSS2 genes, crucial for viral infection. Exome and SNP-array data from a large Italian cohort were used to compare the rare-variants burden and polymorphisms frequency with Europeans and East Asians. Moreover, we looked into gene expression databases to check for sex-unbalanced expression. While we found no significant evidence that ACE2 is associated with disease severity/sex bias, TMPRSS2 levels and genetic variants proved to be possible candidate disease modulators, prompting for rapid experimental validations on large patient cohorts.

Keywords

SARS-CoV-2, genetic variants, ACE2, COVID-19, TMPRSS2

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
0
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9