Efficacy of computational predictions of the functional effect of idiosyncratic pharmacogenetic variants

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dc.contributor.authorMcConnell, Hannah
dc.contributor.authorAndrews, Dan
dc.contributor.authorField, Matthew
dc.date.accessioned2023-08-22T00:23:14Z
dc.date.available2023-08-22T00:23:14Z
dc.date.issued2021
dc.date.updated2022-07-24T08:19:18Z
dc.description.abstractBackground Pharmacogenetic variation is important to drug responses through diverse and complex mechanisms. Predictions of the functional impact of missense pharmacogenetic variants primarily rely on the degree of sequence conservation between species as a primary discriminator. However, idiosyncratic or off-target drug-variant interactions sometimes involve effects that are peripheral or accessory to the central systems in which a gene functions. Given the importance of sequence conservation to functional prediction tools—these idiosyncratic pharmacogenetic variants may violate the assumptions of predictive software commonly used to infer their effect. Methods Here we exhaustively assess the effectiveness of eleven missense mutation functional inference tools on all known pharmacogenetic missense variants contained in the Pharmacogenomics Knowledgebase (PharmGKB) repository. We categorize PharmGKB entries into sub-classes to catalog likely off-target interactions, such that we may compare predictions across different variant annotations. Results As previously demonstrated, functional inference tools perform variably across the complete set of PharmGKB variants, with large numbers of variants incorrectly classified as ‘benign’. However, we find substantial differences amongst PharmGKB variant sub-classes, particularly in variants known to cause off-target, type B adverse drug reactions, that are largely unrelated to the main pharmacological action of the drug. Specifically, variants associated with off-target effects (hence referred to as off-target variants) were most often incorrectly classified as ‘benign’. These results highlight the importance of understanding the underlying mechanism of pharmacogenetic variants and how variants associated with off-target effects will ultimately require new predictive algorithms. Conclusion In this work we demonstrate that functional inference tools perform poorly on pharmacogenetic variants, particularly on subsets enriched for variants causing off-target, type B adverse drug reactions. We describe how to identify variants associated with off-target effects within PharmGKB in order to generate a training set of variants that is needed to develop new algorithms specifically for this class of variant. Development of such tools will lead to more accurate functional predictions and pave the way for the increased wide-spread adoption of pharmacogenetics in clinical practice.en_AU
dc.description.sponsorshipThis work was supported by Australian government fellowship for Matt A Field: NHMRC APP5121190. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn2167-8359en_AU
dc.identifier.urihttp://hdl.handle.net/1885/296713
dc.language.isoen_AUen_AU
dc.provenanceThis is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be citeden_AU
dc.publisherPeerJen_AU
dc.rights© 2021 The authorsen_AU
dc.rights.licenseCreative Commons Attribution licenceen_AU
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_AU
dc.sourcePeerJen_AU
dc.subjectPharmacogeneticsen_AU
dc.subjectPharmacogenomicsen_AU
dc.subjectVarianten_AU
dc.subjectOff-targeten_AU
dc.subjectMissense mutationen_AU
dc.subjectFunctional inference predictionen_AU
dc.titleEfficacy of computational predictions of the functional effect of idiosyncratic pharmacogenetic variantsen_AU
dc.typeJournal articleen_AU
dcterms.accessRightsOpen Accessen_AU
local.bibliographicCitation.lastpage15en_AU
local.bibliographicCitation.startpage1en_AU
local.contributor.affiliationMcConnell, Hannah, College of Health and Medicine, ANUen_AU
local.contributor.affiliationAndrews, Dan, College of Health and Medicine, ANUen_AU
local.contributor.affiliationField, Matthew, James Cook Universityen_AU
local.contributor.authoremailu3508431@anu.edu.auen_AU
local.contributor.authoruidMcConnell, Hannah, u6053831en_AU
local.contributor.authoruidAndrews, Dan, u3508431en_AU
local.description.notesImported from ARIESen_AU
local.identifier.absfor321406 - Pharmacogenomicsen_AU
local.identifier.ariespublicationa383154xPUB21361en_AU
local.identifier.ariespublicationu7114465xPUB1
local.identifier.citationvolume9en_AU
local.identifier.doi10.7717/peerj.11774en_AU
local.identifier.scopusID2-s2.0-85110284748
local.identifier.thomsonIDWOS:000672852800008
local.identifier.uidSubmittedBya383154en_AU
local.publisher.urlhttps://peerj.com/en_AU
local.type.statusPublished Versionen_AU

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