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

dc.creatorCharitou T., Kontou P.I., Tamposis I.A., Pavlopoulos G.A., Braliou G.G., Bagos P.G.en
dc.date.accessioned2023-01-31T07:43:21Z
dc.date.available2023-01-31T07:43:21Z
dc.date.issued2022
dc.identifier10.1038/s41397-022-00289-1
dc.identifier.issn1470269X
dc.identifier.urihttp://hdl.handle.net/11615/72544
dc.description.abstractAvailable 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. © 2022, The Author(s), under exclusive licence to Springer Nature Limited.en
dc.language.isoenen
dc.sourcePharmacogenomics Journalen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85139118298&doi=10.1038%2fs41397-022-00289-1&partnerID=40&md5=7ad2e53232de1b88bb2c85fa4a6f8eda
dc.subjectacetylsalicylic aciden
dc.subjectalpha2 integrinen
dc.subjectanakinraen
dc.subjectapolipoprotein C1en
dc.subjectapolipoprotein C3en
dc.subjectapolipoprotein Een
dc.subjectatazanaviren
dc.subjectazithromycinen
dc.subjectbamlanivimaben
dc.subjectbaricitiniben
dc.subjectbeta interferonen
dc.subjectbeta3 integrinen
dc.subjectbiological markeren
dc.subjectcanakinumaben
dc.subjectcasirivimab plus imdevimaben
dc.subjectchloroquineen
dc.subjectcolchicineen
dc.subjectcytochrome P450 2C19en
dc.subjectcytochrome P450 2C9en
dc.subjectcytochrome P450 2D6en
dc.subjectcytochrome P450 3A4en
dc.subjectcytochrome P450 3A5en
dc.subjectdalteparinen
dc.subjectdexamethasoneen
dc.subjectendothelial nitric oxide synthaseen
dc.subjectenoxaparinen
dc.subjectfavipiraviren
dc.subjectglucuronosyltransferase 1A1en
dc.subjectglucuronosyltransferase 1A3en
dc.subjectglucuronosyltransferase 1A6en
dc.subjectglucuronosyltransferase 1A7en
dc.subjectglutathione peroxidase 1en
dc.subjectHLA DQA1 antigenen
dc.subjectHLA DRB1 antigenen
dc.subjecthydrocortisoneen
dc.subjecthydroxychloroquineen
dc.subjectinsulin receptor substrate 1en
dc.subjectivermectinen
dc.subjectlopinavir plus ritonaviren
dc.subjectmethylprednisoloneen
dc.subjectmultidrug resistance associated protein 1en
dc.subjectnitazoxanideen
dc.subjectreduced folate carrieren
dc.subjectremdesiviren
dc.subjectribavirinen
dc.subjectruxolitiniben
dc.subjectsarilumaben
dc.subjectSARS-CoV-2 vaccineen
dc.subjectsolute carrier organic anion transporter 1B1en
dc.subjecttocilizumaben
dc.subjecttransporter associated with antigen processing 1en
dc.subjectvasculotropin Aen
dc.subjectvitamin D receptoren
dc.subjectArticleen
dc.subjectclinical decision makingen
dc.subjectclinical featureen
dc.subjectclinical outcomeen
dc.subjectcontrolled studyen
dc.subjectcoronavirus disease 2019en
dc.subjectdata miningen
dc.subjectdrug efficacyen
dc.subjectdrug repositioningen
dc.subjectgene identificationen
dc.subjectgene interactionen
dc.subjectgenetic associationen
dc.subjectgenetic variationen
dc.subjectgenome-wide association studyen
dc.subjecthumanen
dc.subjectinfection sensitivityen
dc.subjectpandemicen
dc.subjectpharmacogenetic testingen
dc.subjectprotein protein interactionen
dc.subjectrisk factoren
dc.subjectsystems biologyen
dc.subjecttreatment responseen
dc.subjectdrug therapyen
dc.subjectgenomicsen
dc.subjectpharmacogeneticsen
dc.subjectCOVID-19en
dc.subjectData Miningen
dc.subjectGenomicsen
dc.subjectHumansen
dc.subjectPharmacogeneticsen
dc.subjectSpringer Natureen
dc.titleDrug genetic associations with COVID-19 manifestations: a data mining and network biology approachen
dc.typejournalArticleen


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