Drug Genetic Associations with COVID-19 Manifestations: a Data Mining and Network Biology Approach

Overview

Journal Pharmacogenomics J

Specialties Genetics
Molecular Biology
Pharmacology

Date 2022 Sep 28

PMID 36171417

Authors

Theodosia Charitou

Panagiota I Kontou

Ioannis A Tamposis

Georgios A Pavlopoulos

Georgia G Braliou

Pantelis G Bagos

Affiliations

Soon will be listed here.

Abstract

Available drugs have been used as an urgent attempt through clinical trials to minimize severe cases of hospitalizations with Coronavirus disease (COVID-19), however, there are limited data on common pharmacogenomics affecting concomitant medications response in patients with comorbidities. To identify the genomic determinants that influence COVID-19 susceptibility, we use a computational, statistical, and network biology approach to analyze relationships of ineffective concomitant medication with an adverse effect on patients. We statistically construct a pharmacogenetic/biomarker network with significant drug-gene interactions originating from gene-disease associations. Investigation of the predicted pharmacogenes encompassing the gene-disease-gene pharmacogenomics (PGx) network suggests that these genes could play a significant role in COVID-19 clinical manifestation due to their association with autoimmune, metabolic, neurological, cardiovascular, and degenerative disorders, some of which have been reported to be crucial comorbidities in a COVID-19 patient.

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