Document Type

Article

Publication Date

11-30-2020

Keywords

JMG

JAX Source

Sci Rep 2020 Nov 30; 10(1):20848

PMID

33257774

DOI

https://doi.org/10.1038/s41598-020-77632-8

Grant

HG000330; OD020351; AA18776

Abstract

The emergence of the SARS-CoV-2 virus and subsequent COVID-19 pandemic initiated intense research into the mechanisms of action for this virus. It was quickly noted that COVID-19 presents more seriously in conjunction with other human disease conditions such as hypertension, diabetes, and lung diseases. We conducted a bioinformatics analysis of COVID-19 comorbidity-associated gene sets, identifying genes and pathways shared among the comorbidities, and evaluated current knowledge about these genes and pathways as related to current information about SARS-CoV-2 infection. We performed our analysis using GeneWeaver (GW), Reactome, and several biomedical ontologies to represent and compare common COVID-19 comorbidities. Phenotypic analysis of shared genes revealed significant enrichment for immune system phenotypes and for cardiovascular-related phenotypes, which might point to alleles and phenotypes in mouse models that could be evaluated for clues to COVID-19 severity. Through pathway analysis, we identified enriched pathways shared by comorbidity datasets and datasets associated with SARS-CoV-2 infection.

Comments

The authors would like to thank Dr. Peter D’Eustachio and Dr. Laurens Wilming for their critical reading of the manuscript.

This article is licensed under a Creative Commons Attribution 4.0 International License.

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