Pharmacodynamic Genes Research Articles

Pharmacokinetic, Pharmacodynamic and Pharmacogenetic Studies Related to Vincristine-Induced Peripheral Neuropathy in Chinese Pediatric ALL Patients.

Vincristine (VCR) can cause vincristine-induced peripheral neuropathy (VIPN) during the treatment of acute lymphoblastic leukemia (ALL) and the mechanisms are complicated. The aim of this study was to investigate the influencing factors on the population pharmacokinetics (PopPK) and pharmacodynamics (PD) related to VIPN, including clearance routes, drug-drug interactions (DDI), and genetic characteristics. Pediatric patients being treated for ALL were recruited to PK study where VCR and its metabolite (M1) were measured using a novel assay. The incidence of VIPN was also recorded. DNA sequencing of relevant PK and PD genes was performed. PopPK and PK/PD models were developed, pharmacogenetic and DDI analyses were conducted. In total, 79 children were recruited. The results showed that allometric scaling, ABCB1-rs1128503 genotype, and posaconazole (POS) significantly improved the PopPK model fit. VIPN was significantly correlated with the exposure of VCR. Co-administration with POS shifted the effect curve for VIPN to the left, indicating increased VIPN risk at the same exposure levels. No significant effects on VIPN were observed for CYP3A5 (rs776746), CYP3A4 (rs2242480), CEP72 (rs924607), or various ABCB1 variants (rs1128503, rs2032582, rs1045642, rs4728709, rs4148737, and rs10276036), nor with the co-administration of fluconazole or dasatinib. In summary, co-administration of POS increased VCR exposure by 0.4-fold and raised the risk of VIPN, with an occurrence probability generally exceeding 0.7. Therapeutic drug monitoring of VCR in clinical practice may be necessary to enable appropriate dose adjustments and individualized treatment.

Clinical Pharmacogenetics Implementation Consortium Guideline (CPIC)for CYP2D6, ADRB1, ADRB2, ADRA2C, GRK4, and GRK5 Genotypes and Beta-Blocker Therapy.

Beta-blockers are widely used medications for a variety of indications, including heart failure, myocardial infarction, cardiac arrhythmias, and hypertension. Genetic variability in pharmacokinetic (e.g., CYP2D6) and pharmacodynamic (e.g., ADRB1, ADRB2, ADRA2C, GRK4, GRK5) genes have been studied in relation to beta-blocker exposure and response. We searched and summarized the strength of the evidence linking beta-blocker exposure and response with the six genes listed above. The level of evidence was high for associations between CYP2D6 genetic variation and both metoprolol exposure and heart rate response. Evidence indicates that CYP2D6 poor metabolizers experience clinically significant greater exposure and lower heart rate in response to metoprolol compared with those who are not poor metabolizers. Therefore, we provide therapeutic recommendations regarding genetically predicted CYP2D6 metabolizer status and metoprolol therapy. However, there was insufficient evidence to make therapeutic recommendations for CYP2D6 and other beta-blockers or for any beta-blocker and the other five genes evaluated (updates at www.cpicpgx.org).

The polymorphisms of candidate pharmacokinetic and pharmacodynamic genes and their pharmacogenetic impacts on the effectiveness of risperidone maintenance therapy among Saudi children with autism.

Antipsychotics, including risperidone (RIS), are frequently indicated for various autism spectrum disorder (ASD) manifestations; however, "actionable" PGx testing in psychiatry regarding antipsychotic dosing and selection has limited applications in routine clinical practice because of the lack of standard guidelines, mostly due to the inconsistency and scarcity of genetic variant data. The current study is aimed at examining the association of RIS effectiveness, according to ABC-CV and CGI indexes, with relevant pharmacokinetics (PK) and pharmacodynamics (PD) genes. Eighty-nine ASD children who received a consistent RIS-based regimen for at least 8weeks were included. The Axiom PharmacoFocus Array technique was employed to generate accurate star allele-predicted phenotypes of 3 PK genes (CYP3A4, CYP3A5, and CYP2D6). Genotype calls for 5 candidate PD receptor genes (DRD1, DRD2, DRD3, HTR2C, and HTR2A) were obtained and reported as wild type, heterozygous, or homozygous for 11 variants. Based on the ABC total score, 42 (47.2%) children were classified as responders, while 47 (52.8%) were classified as nonresponders. Multivariate logistic regression analyses, adjusted for nongenetic factors, suggested nonsignificant impacts of the star allele-predicted phenotypes of all 3 PK genes on improvement in ASD symptoms or CGI scores. However, significant positive or negative associations of certain PD variants involved in dopaminergic and serotonergic pathways were observed with specific ASD core and noncore symptom subdomains. Our significant polymorphism findings, mainly those in DRD2 (rs1800497, rs1799978, and rs2734841), HTR2C (rs3813929), and HTR2A (rs6311), were largely consistent with earlier findings (predictors of RIS effectiveness in adult schizophrenia patients), confirming their validity for identifying ASD children with a greater likelihood of core symptom improvement compared to noncarriers/wild types. Other novel findings of this study, such as significant improvements in DRD3 rs167771 carriers, particularly in ABC total and lethargy/social withdrawal scores, and DRD1 rs1875964 homozygotes and DRD2 rs1079598 wild types in stereotypic behavior, warrant further verification in biochemical and clinical studies to confirm their feasibility for inclusion in a PGx panel. In conclusion, we provide evidence of potential genetic markers involved in clinical response variability to RIS therapy in ASD children. However, replication in prospective samples with greater ethnic diversity and sample sizes is necessary.

Predicted deleterious variants in ABCA1, LPL, LPA and KIF6 are associated with statin response and adverse events in patients with familial hypercholesterolemia and disturb protein structure and stability.

This study explored the association of deleterious variants in pharmacodynamics (PD) genes with statin response and adverse effects in patients with familial hypercholesterolemia (FH) and analyzed their potential effects on protein structure and stability. Clinical and laboratory data were obtained from 144 adult FH patients treated with statins. A panel of 32 PD genes was analyzed by exon-targeted gene sequencing. Deleterious variants were identified using prediction algorithms and their structural effects were analyzed by molecular modeling studies. A total of 102 variants were predicted as deleterious (83 missense, 8 stop-gain, 4 frameshift, 1 indel, 6 splicing). The variants ABCA1 rs769705621 (indel), LPA rs41267807 (p.Tyr2023Cys) and KIF6 rs20455 (p.Trp719Arg) were associated with reduced low-density lipoprotein cholesterol (LDLc) response to statins, and the LPL rs1801177 (p.Asp36Asn) with increased LDLc response (P < 0.05). LPA rs3124784 (p.Arg2016Cys) was predicted to increase statin response (P = 0.022), and ABCA1 rs769705621 to increase the risk of statin-related adverse events (SRAE) (P = 0.027). LPA p.Arg2016Cys and LPL p.Asn36Asp maintained interactions with solvent, LPA p.Tyr2023Cys reduced intramolecular interaction with Gln1987, and KIF6 p.Trp719Arg did not affect intramolecular interactions. DDMut analysis showed that LPA p.Arg2016Cys and p.Tyr2023Cys and LPL p.Asp36Asn caused energetically favorable changes, and KIF6 p.Trp719Arg resulted in unfavorable energetic changes, affecting protein stability. Deleterious variants in ABCA1, LPA, LPL and KIF6 are associated with variability in LDLc response to statins, and ABCA1 rs769705621 is associated with SRAE risk in FH patients. Molecular modeling studies suggest that LPA p.Tyr2023Cys and KIF6 p.Trp719Arg disturb protein conformational structure and stability.

Exploratory focused pharmacogenetic testing reveals novel markers associated with risperidone pharmacokinetics in Saudi children with autism.

Background: Autism spectrum disorders (ASDs) encompass a broad range of phenotypes characterized by diverse neurological alterations. Genomic studies have revealed considerable overlap between the molecular mechanisms implicated in the etiology of ASD and genes involved in the pharmacokinetic (PK) and pharmacodynamic (PD) pathways of antipsychotic drugs employed in ASD management. Given the conflicting data originating from candidate PK or PD gene association studies in diverse ethnogeographic ASD populations, dosage individualization based on "actionable" pharmacogenetic (PGx) markers has limited application in clinical practice. Additionally, off-label use of different antipsychotics is an ongoing practice, which is justified given the shortage of approved cures, despite the lack of satisfactory evidence for its safety according to precision medicine. This exploratory study aimed to identify PGx markers predictive of risperidone (RIS) exposure in autistic Saudi children. Methods: This prospective cohort study enrolled 89 Saudi children with ASD treated with RIS-based antipsychotic therapy. Plasma levels of RIS and 9-OH-RIS were measured using a liquid chromatography-tandem mass spectrometry system. To enable focused exploratory testing, genotyping was performed with the Axiom PharmacoFocus Array, which included a collection of probe sets targeting PK/PD genes. A total of 720 PGx markers were included in the association analysis. Results: A total of 27 PGx variants were found to have a prominent impact on various RIS PK parameters; most were not located within the genes involved in the classical RIS PK pathway. Specifically, 8 markers in 7 genes were identified as the PGx markers with the strongest impact on RIS levels (p < 0.01). Four PGx variants in 3 genes were strongly associated with 9-OH-RIS levels, while 5 markers in 5 different genes explained the interindividual variability in the total active moiety. Notably, 6 CYP2D6 variants exhibited strong linkage disequilibrium; however, they significantly influenced only the metabolic ratio and had no considerable effects on the individual estimates of RIS, 9-OH-RIS, or the total active moiety. After correction for multiple testing, rs78998153 in UGT2B17 (which is highly expressed in the brain) remained the most significant PGx marker positively adjusting the metabolic ratio. For the first time, certain human leukocyte antigen (HLA) markers were found to enhance various RIS exposure parameters, which reinforces the gut-brain axis theory of ASD etiology and its suggested inflammatory impacts on drug bioavailability through modulation of the brain, gastrointestinal tract and/or hepatic expression of metabolizing enzymes and transporters. Conclusion: Our hypothesis-generating approach identified a broad spectrum of PGx markers that interactively influence RIS exposure in ASD children, which indicated the need for further validation in population PK modeling studies to define polygenic scores for antipsychotic efficacy and safety, which could facilitate personalized therapeutic decision-making in this complex neurodevelopmental condition.

Pharmacogenetics in Child and Adolescent Psychiatry: Background and Evidence-Based Clinical Applications.

The efficacy and tolerability of psychotropic medications can vary significantly among children and adolescents, and some of this variability relates to pharmacogenetic factors. Pharmacogenetics (PGx) in child and adolescent psychiatry can potentially improve treatment outcomes and minimize adverse drug reactions. This article reviews key pharmacokinetic and pharmacodynamic genes and principles of pharmacogenetic testing and discusses the evidence base for clinical decision-making concerning PGx testing. This article reviews current guidelines from the United States Food and Drug Administration (FDA), the Clinical Pharmacogenetics Implementation Consortium (CPIC), and the Dutch Pharmacogenetics Working Group (DPWG) and explores potential future directions. This review discusses key clinical considerations for clinicians prescribing psychotropic medications in children and adolescents, focusing on antidepressants, antipsychotics, stimulants, norepinephrine reuptake inhibitors, and alpha-2 agonists. Finally, this review synthesizes the practical use of pharmacogenetic testing and clinical decision support systems.

Which can Predict the Outcome of Antidepressants: Metabolic Genes or Pharmacodynamic Genes?

Drug therapy is the primary modality for depression; however, its outcome is often unpredictable, ranging from beneficial effects to serious adverse effects. Genetic variations in drug metabolizing enzymes and pharmacodynamic molecules are responsible for a considerable proportion of interindividual differences in the effectiveness and toxicity of antidepressants. For the improvement in the use of antidepressants, the focus is mainly on personalized treatment emphasizing interindividual differences in genes. This study provides a comprehensive review of the literature on the clinical applications of pharmacogenomics for antidepressant therapy. The polymorphisms of metabolizing enzymes (CYP2D6, CYP2C19, and others) governing the pharmacokinetic behavior of drugs are potential predictors of side effects or treatment failure with medications and there are good pharmacogenetic clinical recommendations for a wide selection of psychopharmacological agents based on functional diplotypes of CYP2C19 and CYP2D6. The relationship between pharmacodynamic genes, including FKBP5, SLC6A4, BDNF, ABCB1, HTR1A, and HTR2A, and clinical outcomes varies in different races. Receptors that are currently used as drug targets for antidepressant drugs are evolutionarily conserved to a higher extent than genes encoding drug metabolism, and the actionability of pharmacodynamic-related genotyping is currently still questionable. The limited availability of largescale, long-term clinical studies on different races and medications currently impedes the implementation of pharmacogenomics in antidepressant treatment. The use of pharmacokinetic and pharmacodynamic modeling, and therapeutic drug monitoring combined with genetic, somatic, dietary, and environmental factors represents a promising avenue for improving the precision and effectiveness of antidepressant therapy.

Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A Genotypes and Serotonin Reuptake Inhibitor Antidepressants.

Serotonin reuptake inhibitor antidepressants, including selective serotonin reuptake inhibitors (SSRIs; i.e., citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, and sertraline), serotonin and norepinephrine reuptake inhibitors (i.e., desvenlafaxine, duloxetine, levomilnacipran, milnacipran, and venlafaxine), and serotonin modulators with SSRI-like properties (i.e., vilazodone and vortioxetine) are primary pharmacologic treatments for major depressive and anxiety disorders. Genetic variation in CYP2D6, CYP2C19, and CYP2B6 influences the metabolism of many of these antidepressants, which may potentially affect dosing, efficacy, and tolerability. In addition, the pharmacodynamic genes SLC6A4 (serotonin transporter) and HTR2A (serotonin-2A receptor) have been examined in relation to efficacy and side effect profiles of these drugs. This guideline updates and expands the 2015 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 and CYP2C19 genotypes and SSRI dosing and summarizes the impact of CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A genotypes on antidepressant dosing, efficacy, and tolerability. We provide recommendations for using CYP2D6, CYP2C19, and CYP2B6 genotype results to help inform prescribing these antidepressants and describe the existing data for SLC6A4 and HTR2A, which do not support their clinical use in antidepressant prescribing.

Transcriptomics and experimental validation-based approach to understand the effect and mechanism of Huangqin tang interfeience with colitis associated colorectal cancer

ContextChronic inflammation is usually caused by persistent irritation or uncontrolled infection and is characterized by ongoing tissue damage, injury-induced cellular proliferation and tissue repair. Colitis-associated colorectal cancer (CAC) isone of the classic examples of tumors that are tightly related to chronic inflammation. BackgroundTo investigated the key pharmacodynamic genes of HQT interventions in CAC by using transcriptome predictions and experiments.Materials & Methods: We used the azoxymethane/dextran sodium sulfate method to induce the mice CAC model. After preventive administration of HQT to the mice model, colonic tissues were taken for transcriptome sequencing and the transcriptome results were then experimentally validated using quantitative Real-Time PCR technique. ResultsTranscriptome sequencing revealed that the effect of the mechanism of HQT on the CAC mice model maybe related to its inhibition of accelerated epithelial mesenchymal transition and induction of pyroptosis. The levels of Matrix-metalloproteinases such as MMP-2, MMP-9 were significantly reduced in CAC mice treated with HQT; The mRNA expression for Krt17, App, CD44 and WNT pathway related sites such as Lrrc15, Cldn-1, Mpc1, Agr2 which are related factors affecting the epithelial mesenchymal transition were significantly reduced in CAC mice treated with HQT; the aberrant mRNA expression of inflammasome components that drive pyroptosis, including Nlrp3, Caspase-1, ASC, GSDMD and its mediated product IL-18 have been improved. ConclusionsOur findings provide preliminary clarification that inhibiting the progression of CAC by using HQT is effective, the mechanism of action may be relatedto the inhibition of epithelial mesenchymal transition and induction of pyroptosis during tumorigenesis.

16.1 Principles of Pharmacogenetic Testing in Children and Adolescents

The objective is to describe basic principles of pharmacogenetic testing and to review the relationship between clinical pharmacokinetics and pharmacodynamics and variation in pharmacokinetic and pharmacodynamic genes.

5.2 Pharmacogenetic Research in Child and Adolescent Psychiatry

Pharmacogenetic studies of pediatric patients are scarce, but clinicians frequently obtain pharmacogenetic testing in children and adolescents. This presentation will review the influence of pharmacokinetic and pharmacodynamic genes on response to antidepressants in youth.

5.3 Clinical Pharmacogenetic Guideline Updates for Antidepressants

Many pharmacogenetic (PGx) tests for medications used in mental health contain pharmacokinetic (PK) and pharmacodynamic (PD) genes thought to be important for drug selection or dosing. The Clinical Pharmacogenetics Implementation Consortium (CPIC) has convened a committee to update guidelines for SSRI and SNRI medications. This presentation will provide an update of these recommendations and PGx in FDA product labeling and apply this information to a patient case.

Genetic determinants associated with response to clozapine in schizophrenia: an umbrella review.

Clozapine response varies widely from person to person, which may be due to inter-individual genetic variability. This umbrella review aims to summarize the current evidence on associations between pharmacodynamic genes and response to clozapine treatment. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis methodology, a systematic literature search was conducted in the PubMed and EMBASE databases from inception to November 2021 to identify systematic reviews and meta-analyses of studies that examined genetic determinants of clozapine response. The quality of the reviews was assessed with the AMSTAR-2 tool. From a total of 128 records, 10 studies representing nine systematic reviews and one meta-analysis met our inclusion criteria. The overall quality of the included studies was poor. All systematic reviews concluded that the results of primary studies were largely negative or conflicting. Most evidence was found for an association with clozapine response and rs6313 and rs6314 within HTR2A and rs1062613 within HTR3A in the serotonergic system. Conclusive evidence for associations between genetic variants and clozapine response is still lacking. Hypothesis-generating genetic studies in large, well-characterized study populations are urgently needed to obtain more consistent and clinically informative results. Future studies may also include multi-omics approaches to identify novel genetic determinants associated with clozapine response.

Application of High-Throughput Sequencing on the Chinese Herbal Medicine for the Data-Mining of the Bioactive Compounds.

The Chinese Herbal Medicine (CHM) has been used worldwide in clinic to treat the vast majority of human diseases, and the healing effect is remarkable. However, the functional components and the corresponding pharmacological mechanism of the herbs are unclear. As one of the main means, the high-throughput sequencing (HTS) technologies have been employed to discover and parse the active ingredients of CHM. Moreover, a tremendous amount of effort is made to uncover the pharmacodynamic genes associated with the synthesis of active substances. Here, based on the genome-assembly and the downstream bioinformatics analysis, we present a comprehensive summary of the application of HTS on CHM for the synthesis pathways of active ingredients from two aspects: active ingredient properties and disease classification, which are important for pharmacological, herb molecular breeding, and synthetic biology studies.

The genetics of drug-induced QT prolongation: evaluating the evidence for pharmacodynamic variants.

Drug-induced long QT syndrome (diLQTS) is an adverse effect of many commonly prescribed drugs, and it can increase the risk for lethal ventricular arrhythmias. Genetic variants in pharmacodynamic genes have been associated with diLQTS, but the strength of the evidence for each of those variants has not yet been evaluated. Therefore, the purpose of this review was to evaluate the strength of the evidence for pharmacodynamic genetic variants associated with diLQTS using a novel, semiquantitative scoring system modified from the approach used for congenital LQTS. KCNE1-D85N and KCNE2-T8A had definitive and strong evidence for diLQTS, respectively. The high level of evidence for these variants supports current consideration as risk factors for patients that will be prescribed a QT-prolonging drug.

Pharmacogenomics in clinical practice to prevent risperidone-induced hyperprolactinemia in autism spectrum disorder.

Autism spectrum disorder (ASD) is a global challenge that may disrupts family and social life significantly. There is robust evidence for the association of apharmacokinetic gene variant (e.g., CYP2D6) with risperidone-induced hyperprolactinemia in ASD. Association of apharmacodynamic gene variant (e.g., DRD2) with risperidone-induced hyperprolactinemia in ASD is also evident from multiple studies. In addition to genetic factors, dose, duration and drug-drug interactions of risperidone might also increase theserum prolactin level. There are several difficulties, such as reimbursement, knowledge and education of healthcare providers, in implementing risperidone pharmacogenomics into clinical practice. However, preparation of national and international pharmacogenomics-based dosing guidelines of risperidone may advance precision medicine of ASD.

Predicting Potential Drug-Drug-Gene Interactions in a Population of Individuals Utilizing a Community-Based Pharmacy

Adverse drug reactions (ADRs) are associated with increased morbidity, mortality, and resource utilization. Drug interactions (DDIs) are among the most common causes of ADRs, and estimates have cited that up to 22% of patients take interacting medications. DDIs are often due to the propensity for agents to induce or inhibit enzymes responsible for the metabolism of concomitantly administered drugs. However, this phenomenon is further complicated by genetic variants of such enzymes. The aim of this study is to quantify and describe potential drug-drug, drug-gene, and drug-drug-gene interactions in a community-based patient population. A regional pharmacy with retail outlets in Arkansas provided deidentified prescription data from March 2020 for 4761 individuals. Drug-drug and drug-drug-gene interactions were assessed utilizing the logic incorporated into GenMedPro, a commercially available digital gene-drug interaction software program that incorporates variants of 9 pharmacokinetic (PK) and 2 pharmacodynamic (PD) genes to evaluate DDIs and drug-gene interactions. The data were first assessed for composite drug-drug interaction risk, and each individual was stratified to a risk category using the logic incorporated in GenMedPro. To calculate the frequency of potential drug-gene interactions, genotypes were imputed and allocated to the cohort according to each gene's frequency in the general population. Potential genotypes were randomly allocated to the population 100 times in a Monte Carlo simulation. Potential drug-drug, gene-drug, or gene-drug-drug interaction risk was characterized as minor, moderate, or major. Based on prescription data only, the probability of a DDI of any impact (mild, moderate, or major) was 26% [95% CI: 0.248-0.272] in the population. This probability increased to 49.6% [95% CI: 0.484-0.507] when simulated genetic polymorphisms were additionally assessed. When assessing only major impact interactions, there was a 7.8% [95% CI: 0.070-0.085] probability of drug-drug interactions and 10.1% [95% CI: 0.095-0.108] probability with the addition of genetic contributions. The probability of drug-drug-gene interactions of any impact was correlated with the number of prescribed medications, with an approximate probability of 77%, 85%, and 94% in patients prescribed 5, 6, or 7+ medications, respectively. When stratified by specific drug class, antidepressants (19.5%), antiemetics (21.4%), analgesics (16%), antipsychotics (15.6%), and antiparasitics (49.7%) had the highest probability of major drug-drug-gene interaction. In a community-based population of outpatients, the probability of drug-drug interaction risk increases when genetic polymorphisms are attributed to the population. These data suggest that pharmacogenetic testing may be useful in predicting drug interactions, drug-gene interactions, and severity of interactions when proactively evaluating patient medication profiles. Genomind, Inc.

Pharmacogenomics: Relevance and opportunities for clinical pharmacology

Pharmacogenomics: Relevance and opportunities for clinical pharmacology

Pharmacogenomics Factors Influencing the Effect of Risperidone on Prolactin Levels in Thai Pediatric Patients With Autism Spectrum Disorder

We investigated the association between genetic variations in pharmacodynamic genes and risperidone-induced increased prolactin levels in children and adolescents with autism spectrum disorder (ASD). In a retrospective study, variants of pharmacodynamic genes were analyzed in 124 ASD patients treated with a risperidone regimen for at least 3 months. To simplify genotype interpretation, we created an algorithm to calculate the dopamine D2 receptor (DRD2) gene genetic risk score. There was no relationship between prolactin levels and single SNPs. However, the H1/H3 diplotype (A2/A2-Cin/Cin-A/G) of DRD2/ankyrin repeat and kinase domain containing 1 (ANKK1) Taq1A, DRD2 -141C indel, and DRD2 -141A>G, which had a genetic risk score of 5.5, was associated with the highest median prolactin levels (23 ng/ml). As the dose-corrected plasma levels of risperidone, 9-OH-risperidone, and the active moiety increased, prolactin levels in patients carrying the H1/H3 diplotype were significantly higher than those of the other diplotypes. DRD2 diplotypes showed significantly high prolactin levels as plasma risperidone levels increased. Lower levels of prolactin were detected in patients who responded to risperidone. This is the first system for describing DRD2 haplotypes using genetic risk scores based on their protein expression. Clinicians should consider using pharmacogenetic-based decision-making in clinical practice to prevent prolactin increase.

52.2 AN UPDATE ON GENE-MEDICATION INTERACTIONS RELEVANT TO PEDIATRIC PSYCHOPHARMACOTHERAPY

Pharmacogenetic studies of pediatric patients are scarce, but clinicians frequently obtain pharmacogenetic testing in children and adolescents. This presentation will review the influence of pharmacokinetic and pharmacodynamic genes on response to antidepressants in youth. A review of the evidence for key pharmacokinetic and pharmacodynamic genes that impact medication tolerability and response in youth will be provided. Specifically, recent studies from our group reporting how: 1) CYP2C19 influences sertraline and escitalopram tolerability; 2) pharmacodynamic genes encoding the serotonin transporter and receptor 2A, SLC6A4, and HTR2A, influence SSRI response; and 3) MTHFR and L-methylfolate do not influence response to antidepressants. Two large retrospective studies in pediatric patients with anxiety and/or depressive disorders reported how CYP2C19 influences response and tolerability to escitalopram (N = 248) and sertraline (N = 352). Another study in a similar population (N = 164) indicated that the response to fluoxetine was associated with SLC6A4 and HTR2A variants but not CYP2D6. One prospective study of patients with anxiety disorders (N = 26) demonstrated that CYP2C19, SLC6A4, and HTR2A were associated with escitalopram response trajectory. In a retrospective analysis of patients that had MTHFR genotyping (n = 292), 23% received L-methylfolate supplementation. Neither the MTHFR genotypes nor L-methylfolate supplementation influenced response to antidepressants. Pharmacogenes are associated with both response and tolerability in youth treated with antidepressants in retrospective studies. Child and adolescent psychiatrists should know the evidence behind these studies as they consider use of pharmacogenetic testing in their clinical practice.