Quantifying the Impact of Phenoconversion on Medications With Actionable Pharmacogenomic Guideline Recommendations in an Acute Aged Persons Mental Health Setting

Abstract

Introduction: Polypharmacy and genetic variants that strongly influence medication response (pharmacogenomics, PGx) are two well-described risk factors for adverse drug reactions. Complexities arise in interpreting PGx results in the presence of co-administered medications that can cause cytochrome P450 enzyme phenoconversion.Aim: To quantify phenoconversion in a cohort of acute aged persons mental health patients and evaluate its impact on the reporting of medications with actionable PGx guideline recommendations (APRs).Methods: Acute aged persons mental health patients (N = 137) with PGx and medication data at admission and discharge were selected to describe phenoconversion frequencies for CYP2D6, CYP2C19 and CYP2C9 enzymes. The expected impact of phenoconversion was then assessed on the reporting of medications with APRs.Results: Post-phenoconversion, the predicted frequency at admission and discharge increased for CYP2D6 intermediate metabolisers (IMs) by 11.7 and 16.1%, respectively. Similarly, for CYP2C19 IMs, the predicted frequency at admission and discharge increased by 13.1 and 11.7%, respectively. Nineteen medications with APRs were prescribed 120 times at admission, of which 50 (42%) had APRs pre-phenoconversion, increasing to 60 prescriptions (50%) post-phenoconversion. At discharge, 18 medications with APRs were prescribed 122 times, of which 48 (39%) had APRs pre-phenoconversion, increasing to 57 prescriptions (47%) post-phenoconversion.Discussion: Aged persons mental health patients are commonly prescribed medications with APRs, but interpretation of these recommendations must consider the effects of phenoconversion. Adopting a collaborative care model between prescribers and clinical pharmacists should be considered to address phenoconversion and ensure the potential benefits of PGx are maximised.

Case Report: Performing a Medication Safety Review Assisted by Pharmacogenomics to Explain a Prescribing Cascade Resulting in a Patient Fall

“…Drug-induced phenoconversion is common in older adults with polypharmacy being treated for MDD, as many antidepressants (e.g., selective serotonin reuptake inhibitors [SSRIs]) are metabolized by or interact with CYP2C19 and/or CYP2D6 enzymes [ 12 , 13 , 14 ]. For example, drug-induced phenoconversion can be observed if a patient identified as a CYP2C19 normal metabolizer (NM) takes fluoxetine, a CYP2C19 inhibitor, causing the observed phenotype to resemble a PM for the victim drug.…”

The Relevance of Integrating CYP2C19 Phenoconversion Effects into Clinical Pharmacogenetics

“…Not considering PC in the interpretation of PGx results can lead to an inappropriate drug selection or false dosing recommendation, which in turn increases the risk for adverse drug reactions or nonresponse. Consequently, the phenoconversion effects of CYP2D6 are relevant [12][13][14]; however, integration in clinical routine is currently rare [5].…”

Pharmacogenomics and Drug-Induced Phenoconversion Informed Medication Safety Review in the Management of Pain Control and Quality of Life: A Case Report

“…Polypharmacy may complicate the interpretation of the PGx results, especially when co-administered medications share the same metabolic pathway and affect the drug-induced phenoconversion [ 4 ]. Phenoconversion occurs when nongenetic factors, such as concomitant medications, age, and comorbidities, alter the genotype-predicted phenotype of drug-metabolizing enzymes [ 4 ].…”

“…Polypharmacy may complicate the interpretation of the PGx results, especially when co-administered medications share the same metabolic pathway and affect the drug-induced phenoconversion [ 4 ]. Phenoconversion occurs when nongenetic factors, such as concomitant medications, age, and comorbidities, alter the genotype-predicted phenotype of drug-metabolizing enzymes [ 4 ]. Assessing for the drug-induced phenoconversion, as opposed to solely relying on genetic results, allows for a more accurate prediction of medication response and an optimization of patient outcomes [ 4 ].…”

“…Phenoconversion occurs when nongenetic factors, such as concomitant medications, age, and comorbidities, alter the genotype-predicted phenotype of drug-metabolizing enzymes [ 4 ]. Assessing for the drug-induced phenoconversion, as opposed to solely relying on genetic results, allows for a more accurate prediction of medication response and an optimization of patient outcomes [ 4 ]. The clinical decision support systems (CDSSs) can help to identify drug–drug interactions (DDIs), DGIs, DDGIs, and drug-induced phenoconversion [ 5 ].…”