scholarly journals Pharmacogenetic variants associated with off-target adverse drug reactions are mostly predicted to be benign

2019 ◽  
Author(s):  
Hannah McConnell ◽  
Matthew A Field ◽  
T. Daniel Andrews

AbstractTools that predict the functional importance of genetic variation almost always rely on sequence conservation across deep evolutionary divergences as a primary discriminator. However, sequence conservation information is misleading when predicting the functional importance of pharmacogenetic variants related to off-target adverse drug reactions. Sequence conservation is largely maintained by evolutionary purifying selection, which has not been relevant for most drugs until very recently, especially for off-target effects. Here, we use a simple classification criteria to identify variants with off-target pharmacogenetic effects from the PharmGKB database. We show that off-target pharmacogenetic variation is predicted mostly to be benign by all state-of-the-art prediction tools we tested. Hence, off-target pharmacogenetic variants are overwhelmingly invisible to all predictive methodologies currently employed. Very different analytical approaches will be needed to address this important problem.Author SummaryWhen a personal genome sequence is obtained for a given person, the sequence is compared to the human reference sequence to identify where it differs from the genome of that person. One application of this information is that it may identify how a specific person may react to particular drugs. However, when computationally predicting the functional importance of a genetic variant, the tools used rely heavily on sequence conservation information to make their prediction. From an evolutionary point of view, the use of drugs to treat diseases is a very recent activity – and one that has not had time to cause certain variants to either be selected for or removed from the population. This produces a blind-spot for tools that predict variant functional effects, especially for drugs with off-target interactions that may produce unanticipated effects.

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11774
Author(s):  
Hannah McConnell ◽  
T. Daniel Andrews ◽  
Matt A. Field

Background 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.


2005 ◽  
Vol 38 (01) ◽  
Author(s):  
L Galatti ◽  
S Ettore Giustini ◽  
A Sessa ◽  
G Polimeni ◽  
F Salvo ◽  
...  

Author(s):  
O.I. Slyusar ◽  
◽  
A.B. Kachalov ◽  
M.V. Ryzhkova ◽  
I.В. Slyusar ◽  
...  

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