Drug genetic associations with COVID-19 manifestations: a data mining and network biology approach

Pharmacogenomics J. 2022 Dec;22(5-6):294-302. doi: 10.1038/s41397-022-00289-1. Epub 2022 Sep 28.


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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19 Drug Treatment*
  • Data Mining
  • Genomics
  • Humans
  • Pharmacogenetics