Pharmacogenetics to Predict Adverse Events Associated With Antidepressants

Machine Learning-Based Prediction of Escitalopram and Sertraline Side Effects With Pharmacokinetic Data in Children and Adolescents

Selective serotonin reuptake inhibitors (SSRI) are the first-line pharmacologic treatment for anxiety and depressive disorders in children and adolescents. Many patients experience side effects that are difficult to predict, are associated with significant morbidity, and can lead to treatment discontinuation. Variation in SSRI pharmacokinetics could explain differences in treatment outcomes, but this is often overlooked as a contributing factor to SSRI tolerability. This study evaluated data from 288 escitalopram-treated and 255 sertraline-treated patients ≤ 18 years old to develop machine learning models to predict side effects using electronic health record data and Bayesian estimated pharmacokinetic parameters. Trained on a combined cohort of escitalopram- and sertraline-treated patients, a penalized logistic regression model achieved an area under the receiver operating characteristic curve (AUROC) of 0.77 (95% confidence interval (CI): 0.66-0.88), with 0.69 sensitivity (95% CI: 0.54-0.86), and 0.82 specificity (95% CI: 0.72-0.87). Medication exposure, clearance, and time since the last dose increase were among the top features. Individual escitalopram and sertraline models yielded an AUROC of 0.73 (95% CI: 0.65-0.81) and 0.64 (95% CI: 0.55-0.73), respectively. Post hoc analysis showed sertraline-treated patients with activation side effects had slower clearance (P = 0.01), which attenuated after accounting for age (P = 0.055). These findings raise the possibility that a machine learning approach leveraging pharmacokinetic data can predict escitalopram- and sertraline-related side effects. Clinicians may consider differences in medication pharmacokinetics, especially during dose titration and as opposed to relying on dose, when managing side effects. With further validation, application of this model to predict side effects may enhance SSRI precision dosing strategies in youth.

Pharmacogenetic Testing in Patients with Autism Spectrum Disorder Evaluated in a Precision Medicine Clinic

OBJECTIVE

This study investigated outcomes of pharmacogenetic testing of youth with autism spectrum disorder (ASD) referred to a precision medicine clinic and explored associations between patient characteristics and pharmacogenomic testing results.

METHODS

Records for patients diagnosed with ASD and subsequently referred to a pediatric hospital's precision medicine clinic between July 1, 2010, and June 30, 2020, were reviewed. Pharmacogenetic testing results were abstracted focusing on CYP2D6 and CYP2C19. In addition, we compiled counts of patients' co-occurring diagnoses, histories of adverse drug reactions (ADRs), previously trialed ineffective medications, and previous psychiatric medication changes. Logistic regression models were fit to examine CYP2C19 and CYP2D6 metabolizer status as functions of patient demographics and prereferral medication histories.

RESULTS

Of 202 patients (mean age = 12.18 yrs), 66% were referred to precision medicine because of poor medication response. Among patients with pharmacogenomic testing results for CYP2D6, 9% were classified as poor metabolizers; among patients with results for CYP2C19, 10% were classified as rapid/ultrarapid metabolizers. Patient demographics and medication response history did not predict pharmacogenomic results. However, the number of co-occurring diagnoses positively predicted the number of nonpsychiatric ADRs and a higher probability of CYP2D6 poor metabolizer status; moreover, nonpsychiatric ADRs positively predicted CYP2C19 rapid/ultrarapid metabolizer status.

CONCLUSION

In one of the largest reported samples of youth with ASD clinically referred for pharmacogenetic testing, we observed high variability in medication response and yield for actionable results. Our findings suggest potential clinical utility for pharmacogenetic testing and introduce possible clinical profiles associated with metabolizer status.

Associations of antidepressants and antipsychotics with lipid parameters: Do CYP2C19/CYP2D6 genes play a role? A UK population-based study

BACKGROUND

Dyslipidaemia is an important cardiovascular risk factor for people with severe mental illness, contributing to premature mortality. The link between antipsychotics and dyslipidaemia is well established, while evidence on antidepressants is mixed.

AIMS

To investigate if antidepressant/antipsychotic use was associated with lipid parameters in UK Biobank participants and if CYP2C19 and CYP2D6 genetic variation plays a role.

METHODS

Review of self-reported prescription medications identified participants taking antidepressants/antipsychotics. Total, low-, and high-density lipoprotein cholesterol (L/HDL-C) and triglycerides derived from blood samples. CYP2C19 and CYP2D6 metabolic phenotypes were assigned from genetic data. Linear regression investigated aims, adjusted for key covariates.

RESULTS

Of 469,739 participants, 36,043 took antidepressants (53% female, median age 58, 17% taking cholesterol-lowering medications) and 3255 took antipsychotics (58% female, median age 57, 27% taking cholesterol-lowering medications). Significant associations were found between use of each amitriptyline, fluoxetine, citalopram/escitalopram, sertraline, paroxetine and venlafaxine with higher total cholesterol, LDL-C, and triglycerides and lower HDL-C, compared to participants not taking each medication. Venlafaxine was associated with the worst lipid profile (total cholesterol, adjusted mean difference: 0.21 mmol/L, 95% confidence interval (CI): 0.17 to 0.26, p < 0.001). Antipsychotic use was significantly associated with lower HDL-C and higher triglycerides. In participants taking sertraline, CYP2C19 intermediate metabolisers had higher HDL-C (0.05 mmol/L, 95% CI: 0.01 to 0.09, p = 0.007) and lower triglycerides (-0.17 mmol/L, 95% CI: -0.29 to -0.05, p = 0.007), compared to normal metabolisers.

CONCLUSIONS

Antidepressants were significantly associated with adverse lipid profiles, potentially warranting baseline and regular monitoring. Further research should investigate the mechanistic pathways underlying the protective effects of the CYP2C19 intermediate metaboliser phenotype on HDL-C and triglycerides in people taking sertraline.

Pediatric considerations for pharmacogenetic selective serotonin reuptake inhibitors clinical decision support

Pharmacogenetic testing for psychiatry is growing at a rapid pace, with multiple sites utilizing results to help clinical decision-making. Genotype-guided dosing and drug selection have been implemented at several sites, including Vanderbilt University Medical Center, where clinical decision support (CDS) based on pharmacogenetic results went live for selective serotonin reuptake inhibitors in 2020 for both adult and pediatric patients. Effective and appropriate implementation of CYP2D6- and CYP2C19-guided CDS for the pediatric population requires consideration of the evidence for the pharmacogenetic associations, medication indications, and appropriate alternative therapies to be used when a pharmacogenetic contraindication is identified. In this article, we review these pediatric pharmacogenetic considerations for selective serotonin reuptake inhibitor CDS. We include a case study, the current literature supporting clinical recommendations, considerations when designing pediatric CDS, future implications, and examples of sertraline, (es)citalopram, paroxetine, and fluvoxamine alerts.

Pediatric CYP2D6 metabolizer status and post-tonsillectomy nausea and vomiting after ondansetron

The goal of this study was to determine whether CYP2D6 metabolizer status within the ondansetron-treated pediatric tonsillectomy population is associated with risk of postoperative nausea and vomiting (PONV) in the post-anesthesia care unit. We conducted a retrospective cohort study of pediatric patients (<18 years) who underwent tonsillectomy and received ondansetron on the day of the procedure. Data were obtained from BioVU, an institutional biobank that links DNA to de-identified electronic health record data. Subjects were tested for 10 CYP2D6 allelic variants and copy number variation, and genotype data translated into CYP2D6 metabolizer status. The cohort included 652 individuals, 105 (16.1%) of whom had PONV. Rates of PONV were similar across groups: ultrarapid metabolizers (UMs), 1 of 9 (11.1%); normal metabolizers (NMs), 64 of 354 (18.1%); intermediate metabolizers (IMs), 33 of 234 (14.1%); poor metabolizers (PMs), 6 of 39 (15.4%); and ambiguous phenotypes, 1 of 16 (6.3%). In multivariable analysis adjusted for age, sex, and time under anesthesia, CYP2D6 metabolizer status was not associated with PONV, with an odds ratio of 1.37 (95% confidence interval 0.9, 2.1) when comparing PM/IM versus NM/UM. In this large pediatric population, no significant differences were detected for PONV based on CYP2D6 metabolizer status. Further investigation is needed to determine mechanisms for ondansetron inefficacy in children.

Pharmacogenetic Expression of CYP2C19 in a Pediatric Population

Genetic variability in CYP2C19 may be associated with both lack of efficacy and toxicity of drugs due to its different metabolic status based on the presence of particular alleles. This literature review summarizes current knowledge relative to the association or treatment adaptation based on CYP2C19 genetics in a pediatric population receiving drugs metabolized by CYP2C19, such as voriconazole, antidepressants, clopidogrel and proton pump inhibitors. Additionally, we also presented one of the approaches that we developed for detection of variant alleles in the CYP2C19 gene. A total of 25 articles on PubMed were retained for the study. All studies included pediatric patients (age up to 21 years) having benefited from an assessment of CYP2C19. CYP2C19 poor and intermediate metabolizers exhibit a higher trough plasma concentration of voriconazole, and PPIs compared to the rapid and ultra-rapid metabolizers. The pharmacogenetic data relative to CYP2C19 and clopidogrel in the pediatric population are not yet available. CYP2C19 poor metabolizers have a higher trough plasma concentration of antidepressants compared to the rapid and the ultra-rapid metabolizers. Modification of allele-specific PCR through the introduction of artificial mismatch is presented. CYP2C19 genotyping remains a powerful tool needed to optimize the treatment of children receiving voriconazole, PPIs, and anti-depressants.

The comparative effectiveness of antidepressants for youths with major depressive disorder: a nationwide population-based study in Taiwan

Background:

Guidelines recommend fluoxetine as a first-line medication for youths diagnosed with major depressive disorder (MDD). However, little is known about the long-term effectiveness of different antidepressants in juveniles in the real world. This study aimed to compare the effectiveness of antidepressants in youths with MDD.

Methods:

Youths (<20 years old) with a diagnosis of MDD who were new users of antidepressants were selected from a nationwide population-based cohort in Taiwan between 1997 and 2013. We divided a total of 16,981 users (39.9% male; mean age: 16.6 years) into 10 different antidepressant groups (fluoxetine, sertraline, paroxetine, venlafaxine, citalopram, escitalopram, bupropion, fluvoxamine, mirtazapine and moclobemide). Regarding treatment outcomes (hospitalisation and medication discontinuation), Cox proportional hazards regression models were applied to estimate the hazards of such outcomes.

Results:

Compared with the youths treated with fluoxetine, the bupropion-treated group demonstrated lower rates of hospitalisation and discontinuation. Mirtazapine-treated group demonstrated a higher hospitalisation risk mainly when administered for single depressive episodes. Furthermore, patients treated with sertraline and fluvoxamine had higher discontinuation rates. Among the younger teenage subgroups (< 16 years), significantly higher rates of discontinuation were observed in those treated with sertraline, escitalopram and fluvoxamine. Among the older teenage subgroups (⩾ 16 years), bupropion was superior to fluoxetine in preventing hospitalisation and discontinuation.

Conclusion:

We concluded that bupropion might surpass fluoxetine with regard to hospitalisation prevention and drug therapy maintenance among youths with MDD, while mirtazapine users demonstrated a higher hospitalisation risk. Our findings might serve as a reference for clinicians in future studies.

Perspectives from the Society for Pediatric Research: pharmacogenetics for pediatricians

This review evaluates the pediatric evidence for pharmacogenetic associations for drugs that are commonly prescribed by or encountered by pediatric clinicians across multiple subspecialties, organized from most to least pediatric evidence. We begin with the pharmacogenetic research that led to the warning of increased risk of death in certain pediatric populations ("ultrarapid metabolizers") who are prescribed codeine after tonsillectomy or adenoidectomy. We review the evidence for genetic testing for thiopurine metabolism, which has become routine in multiple pediatric subspecialties. We discuss the pharmacogenetic research in proton pump inhibitors, for which clinical guidelines have recently been made available. With an increase in the prevalence of behavioral health disorders including attention deficit hyperactivity disorder (ADHD), we review the pharmacogenetic literature on selective serotonin reuptake inhibitors, selective norepinephrine reuptake inhibitors, and ADHD medications. We will conclude this section on the current pharmacogenetic data on ondansetron. We also provide our perspective on how to integrate the current research on pharmacogenetics into clinical care and what further research is needed. We discuss how institutions are managing pharmacogenetic test results and implementing them clinically, and how the electronic health record can be leveraged to ensure testing results are available and taken into consideration when prescribing medications. IMPACT: While many reviews of pharmacogenetics literature are available, there are few focused on pediatrics. Pediatricians across subspecialties will become more comfortable with pharmacogenetics terminology, know resources they can use to help inform their prescribing habits for drugs with known pharmacogenetic associations, and understand the limitations of testing and where further research is needed.

Genophenotypic Factors and Pharmacogenomics in Adverse Drug Reactions

Adverse drug reactions (ADRs) rank as one of the top 10 leading causes of death and illness in developed countries. ADRs show differential features depending upon genotype, age, sex, race, pathology, drug category, route of administration, and drug–drug interactions. Pharmacogenomics (PGx) provides the physician effective clues for optimizing drug efficacy and safety in major problems of health such as cardiovascular disease and associated disorders, cancer and brain disorders. Important aspects to be considered are also the impact of immunopharmacogenomics in cutaneous ADRs as well as the influence of genomic factors associated with COVID-19 and vaccination strategies. Major limitations for the routine use of PGx procedures for ADRs prevention are the lack of education and training in physicians and pharmacists, poor characterization of drug-related PGx, unspecific biomarkers of drug efficacy and toxicity, cost-effectiveness, administrative problems in health organizations, and insufficient regulation for the generalized use of PGx in the clinical setting. The implementation of PGx requires: (i) education of physicians and all other parties involved in the use and benefits of PGx; (ii) prospective studies to demonstrate the benefits of PGx genotyping; (iii) standardization of PGx procedures and development of clinical guidelines; (iv) NGS and microarrays to cover genes with high PGx potential; and (v) new regulations for PGx-related drug development and PGx drug labelling.

Pediatric Therapeutic Drug Monitoring for Selective Serotonin Reuptake Inhibitors

Therapeutic drug monitoring (TDM) is uncommon in child and adolescent psychiatry, particularly for selective serotonin reuptake inhibitors (SSRIs)—the first-line pharmacologic treatments for depressive and anxiety disorders. However, TDM in children and adolescents offers the opportunity to leverage individual variability of antidepressant pharmacokinetics to shed light on non-response and partial response, understand drug-drug interactions, evaluate adherence, and characterize the impact of genetic and developmental variation in pharmacokinetic genes. This perspective aims to educate clinicians about TDM principles and examines evolving uses of TDM in SSRI-treated youths and their early applications in clinical practice, as well as barriers to TDM in pediatric patients. First, the impact of pharmacokinetic genes on SSRI pharmacokinetics in youths could be used to predict tolerability and response for some SSRIs (e.g., escitalopram). Second, plasma concentrations are significantly influenced by adherence, which may relate to decreased efficacy. Third, pharmacometric analyses reveal interactions with proton pump inhibitors, oral contraceptives, cannabinoids, and SSRIs in youths. Rapid developments in TDM and associated modeling have enhanced the understanding of variation in SSRI pharmacokinetics, although the treatment of anxiety and depressive disorders with SSRIs in youths often remains a trial-and-error process.

The role of pharmacogenetics in the treatment of anxiety disorders and the future potential for targeted therapeutics

INTRODUCTION

Anxiety disorders (AD) are among the most common mental disorders worldwide. Pharmacotherapy, including benzodiazepines, selective serotonin reuptake inhibitors, serotonin-norepinephrine reuptake inhibitors, and tricyclic antidepressants is currently based on 'trial-and-error,' and is effective in a subset of patients or produces partial response only. Recent research proposes that treatment response and tolerability of the drugs are associated with genetic factors.

AREAS COVERED

In the present review, we provide information on pharmacogenetics (PGx) in AD, including pharmacokinetic and pharmacodynamic genes. Moreover, we discuss the future potential of PGx for personalized treatment.

EXPERT OPINION

In psychiatry, PGx testing is still in its infancy, especially in the treatment of AD. As of today, implementation in clinical routine is recommended only for CYP2D6 and CYP2C19, mainly in terms of safety of treatment and potentially of treatment outcome in general. However, the evidence for PGx testing addressing pharmacodynamics for specific AD is limited to date. Nevertheless, PGx may develop into a valuable and promising tool to improve therapy in AD, but there is a need for more research to fully exploit its possibilities. Future perspectives include research into single genes, polygenic risk scores, and pharmacoepigenetics to provide targeted therapy.

The Impact of Marijuana on Antidepressant Treatment in Adolescents: Clinical and Pharmacologic Considerations

The neuropharmacology of marijuana, including its effects on selective serotonin reuptake inhibitor (SSRI)/antidepressant metabolism and the subsequent response and tolerability in youth, has received limited attention. We sought to (1) review clinically relevant pharmacokinetic (PK) and pharmacodynamic (PD) interactions between cannabinoids and selected SSRIs, (2) use PK models to examine the impact of cannabinoids on SSRI exposure (area under curve (AUC)) and maximum concentration (C_MAX) in adolescents, and (3) examine the frequency of adverse events reported when SSRIs and cannabinoids are used concomitantly. Cannabinoid metabolism, interactions with SSRIs, impact on relevant PK/PD pathways and known drug–drug interactions were reviewed. Then, the impact of tetrahydrocannabinol (THC) and cannabidiol (CBD) on exposure (AUC₂₄) and C_MAX for escitalopram and sertraline was modeled using pediatric PK data. Using data from the Food and Drug Administration Adverse Events Reporting System (FAERS), the relationship between CBD and CYP2C19-metabolized SSRIs and side effects was examined. Cannabis and CBD inhibit cytochrome activity, alter serotonergic transmission, and modulate SSRI response. In PK models, CBD and/or THC increases sertraline and es/citalopram concentrations in adolescents, and coadministration of CBD and CYP2C19-metabolized SSRIs increases the risk of cough, diarrhea, dizziness, and fatigue. Given the significant SSRI–cannabinoid interactions, clinicians should discuss THC and CBD use in youth prescribed SSRIs and be aware of the impact of initiating, stopping, or decreasing cannabinoid use as this may significantly affect es/citalopram and sertraline exposure.

Severe Pain in Chronic Pancreatitis Patients: Considering Mental Health and Associated Genetic Factors

Pain is the most distressing and disruptive feature of recurrent acute pancreatitis (RAP) and chronic pancreatitis (CP) resulting in low quality of life (QOL) and disabilities. There is no single, characteristic pain pattern in patients with RAP and CP. Abdominal imaging features of CP accurately reflect morphologic features but they do not correlate with pain. Pain is the major driver of poor quality of life (QOL) and it is the constant pain, rather than intermittent pain that drives poor QOL. Furthermore, the most severe constant pain experience in CP is also a complex condition. The ability to target the etiopathogenesis of severe pain requires new methods to detect the exact pain mechanisms in an individual at cellular, tissue, system and psychiatric levels. In patients with complex and severe disease, it is likely that multiple overlapping mechanisms are simultaneously driving pain, anxiety and depression. Quantitative sensory testing (QST) shows promise in detecting alterations in central processing of pain signals and to classify patients for mechanistic and therapeutic studies. New genetic research suggests that genetic loci for severe pain in CP overlap with genetic loci for depression and other psychiatric disorders, providing additional insights and therapeutic targets for individual patients with severe CP pain. Well-designed clinical trials that integrate clinical features, QST, genetics and psychological assessments with targeted treatment and assessment of responses are required for a quantum leap forward. A better understanding of the context and mechanisms contributing to severe pain experiences in individual patients is predicted to lead to better therapies and quality of life.