Cytochrome P450 2C19 Poor Metabolizer Phenotype in Treatment Resistant Depression: Treatment and Diagnostic Implications

Pharmacogenetic Factors Influence Escitalopram Pharmacokinetics and Adverse Events in Youth with a Family History of Bipolar Disorder: A Preliminary Study

Introduction: Escitalopram is an effective and generally well-tolerated antidepressant, but children of parents with bipolar disorder (BD) may be at increased risk for adverse events associated with antidepressants, including increased irritability, restlessness, impulsivity, and manic symptoms. This risk may be influenced by polymorphisms in genes encoding cytochrome P450 enzymes (CYP2C19 or CYP2D6), the serotonin transporter (SLC6A4), and the serotonin receptor 2A subtype (HTR2A). We explored whether gene-drug interactions influence the emergence of adverse events in depressed and/or anxious youth with a family history of BD. Materials and Methods: Children and adolescents aged 12-17 years with a first-degree relative with bipolar I disorder were treated with escitalopram and monitored for adverse effects, underwent pharmacogenetic testing, and provided serum escitalopram levels. Emergence of adverse events was determined by study clinicians, and symptoms were tracked using the Treatment-Emergent Activation and Suicidality Assessment Profile (TEASAP) and Pediatric Adverse Events Rating Scale. Clinical Pharmacogenetics Implementation Consortium guidelines were used to determine CYP2C19 and CYP2D6 phenotypes. Results: Slower CYP2C19 metabolizers had greater dose-normalized 24-hour area under the curve (AUC0-24; p = 0.025), trough concentrations (Ctrough; p = 0.013), and elimination half-lives (t1/2; p < 0.001). CYP2D6 phenotype was not significantly associated with any pharmacokinetic parameter. Slower CYP2D6 metabolizers had increased TEASAP akathisia (p = 0.015) scores. HTR2A A/A and A/G genotypes were associated with increased TEASAP "self-injury, suicidality, and harm to others" subscale scores (p = 0.017). Escitalopram maximum concentration, AUC0-24, CYP2C19 phenotype, and SLC6A4 genotype were not associated with adverse events. Conclusions: CYP2C19 phenotype influences escitalopram pharmacokinetics whereas CYP2D6 phenotype does not. Slower CYP2D6 metabolism was associated with increased akathisia, and HTR2A A/A or A/G genotypes were associated with increased risk of self-harm or harm to others. Larger cohorts are needed to identify associations between genetic test results and antidepressant-associated adverse events. Trial Registration: ClinicalTrials.gov identifier: NCT02553161.

Downregulated NPAS4 in multiple brain regions is associated with major depressive disorder

Major Depressive Disorder (MDD) is a commonly observed psychiatric disorder that affects more than 2% of the world population with a rising trend. However, disease-associated pathways and biomarkers are yet to be fully comprehended. In this study, we analyzed previously generated RNA-seq data across seven different brain regions from three distinct studies to identify differentially and co-expressed genes for patients with MDD. Differential gene expression (DGE) analysis revealed that NPAS4 is the only gene downregulated in three different brain regions. Furthermore, co-expressing gene modules responsible for glutamatergic signaling are negatively enriched in these regions. We used the results of both DGE and co-expression analyses to construct a novel MDD-associated pathway. In our model, we propose that disruption in glutamatergic signaling-related pathways might be associated with the downregulation of NPAS4 and many other immediate-early genes (IEGs) that control synaptic plasticity. In addition to DGE analysis, we identified the relative importance of KEGG pathways in discriminating MDD phenotype using a machine learning-based approach. We anticipate that our study will open doors to developing better therapeutic approaches targeting glutamatergic receptors in the treatment of MDD.

CYP2C19-rs4986893 confers risk to major depressive disorder and bipolar disorder in the Han Chinese population whereas ABCB1-rs1045642 acts as a protective factor

BACKGROUND

Genetic risks may predispose individuals to major mood disorders differently. This study investigated the gene polymorphisms of previously reported candidate genes for major depressive disorder (MDD) and bipolar disorder (BPD) in the Han Chinese population.

METHODS

Twenty loci of 13 candidate genes were detected by MALDI-TOF mass spectrometry in 439 patients with MDD, 600 patients with BPD, and 464 healthy controls. The distribution of genotypes in alleles, Hardy-Weinberg equilibrium, and genetic association were analyzed using the PLINK software. The linkage of disequilibrium and haplotype analyses were performed using the Haploview software.

RESULTS

Out of the 20 loci analyzed, CYP2C19-rs4986893, ABCB1-rs1045642, and SCN2A-rs17183814 passed Bonferroni correction; their statistical powers were > 55%. The minor allele frequencies (MAF) of CYP2C19-rs4986893 in the MDD group (0.0547) and BPD group (0.0533) were higher than that of the control group (0.0259, P < 0.05), leading to the odds ratios (ORs) of MDD (2.178) and BPD (2.122), respectively. In contrast, the lower MAFs of ABCB1-rs1045642 were observed in both MDD (0.3599, OR = 0.726) and BPD (0.3700, OR = 0.758) groups than controls (0.4364, P < 0.05). The MDD group had a higher MAF of SCN2A-rs17183814 than controls (0.1743 vs. 0.1207, OR = 1.538, P < 0.05). Moreover, a G-A haplotype composed by CYP2C19-rs4986893 and -rs4244285 was associated with BPD (OR = 1.361, P < 0.01), and the A-G haplotype increased the risks to both MDD (OR = 2.306, P < 0.01) and BPD (OR = 2.332, P < 0.001). The CYP2C19 intermediate metabolizer and poor metabolizer (IM&PM) status was related to the raised risk of both MDD (OR = 1.547, P < 0.01) and BPD (OR = 1.808, P < 0.001).

CONCLUSION

Our data indicate that the impaired CYP2C19 metabolism caused by the haplotypes integrated by CYP2C19 alleles might confer the risk to MDD and BPD, whereas the ABCB1-rs1045642 T allele serves as a protective factor.

Effect of CYP2C19 polymorphisms on antidepressant prescription patterns and treatment emergent mania in bipolar disorder

Antidepressant medication is used extensively to treat bipolar depression despite uncertain efficacy. The cytochrome P450 (CYP) 2C19 enzyme metabolize several antidepressants, and polymorphisms in the corresponding gene CYP2C19 influence plasma concentration and hence treatment outcomes in major depressive disorder. Here, we investigate if CYP2C19 polymorphisms are associated with antidepressant treatment patterns and the risk of mania when antidepressants are used in bipolar disorder. Two single nucleotide polymorphisms (rs4244285 and rs12248560) were used to classify 5019 bipolar disorder patients into CYP2C19 metabolic phenotypes ranging from poor to ultra-rapid metabolizers. We used Swedish national registry data 2005-2017 on dispensed medications and inpatient care to estimate risks for early-treatment persistence, treatment discontinuation, switching to a new antidepressant medication, and mania within 3 months of treatment initiation in patients treated with citalopram, escitalopram, sertraline, amitriptyline, and clomipramine. Metabolic phenotypes of CYP2C19 were not robustly associated with the investigated treatment outcomes based on dispense patterns. Slower metabolism was associated with an increased risk of treatment emergent mania for sertraline (hazard ratio [HR] = 1.3, 95% CI = 1.04-1.62, p = 0.02) and the tricyclic antidepressants amitriptyline and clomipramine (HR = 1.46, 95% CI = 1.05-2.02, p = 0.024). In a large study of the impact of CYP2C19 metabolic phenotypes on antidepressant treatment of bipolar depression, we found an association between slower CYP2C19 metabolism and higher risk of treatment emergent mania, which is a step towards personalized risk assessments. There were, however, no clear associations with early treatment persistence, treatment discontinuation, and switching to a new antidepressant.

CYP2D6 and CYP2C19 Genes Associated with Tricontinental and Latin American Ancestry of Pe-ruvians

Precision medicine seeks to individualize the dose from the beginning of phar-macological therapy based on the characteristics of each patient, genes involved in the metabolic phenotype, ethnicity or miscegenation, with the purpose to minimize adverse effects and optimize drug efficacy. The objective was to re-view studies that describe the association of the CYP2D6 and CYP2C19 genes with the tricontinental and Latin American ancestry of Peruvians. A biblio-graphic search was carried out in PubMed/Medline and SciELO, with various descriptors in Spanish and English. The results of this review confirm that the ethnic origin of Peruvians is triconti-nental due to European (mainly Spanish), African and Asian migration, in addi-tion to Latin American migration, being 60.2% mixed, 25.8% Amerindian, 5.9% white, 3.6% African descent, 1.2% Chinese and Japanese descent, and 3.3% unspecified. Studies on CYP2C19*3, CYP2D6*2, *3 and *6 have been reported in Peruvians, and the frequency is similar to that studied in Ecuadori-ans and Colombians. The CYP2C19*3, CYP2D6*3, and CYP2D6*6 alleles found in Peruvians are common in Europeans, Africans, and Asians; while CYP2D6*4 in Africans and CYP2D6*2 related to Asians. In some studies, the ethnic/gene association has not been demonstrated; while others have shown a significant association, which is why further investigation is warranted. It is concluded that the studies on CYP2D6 and CYP2C19 genes associated with the tricontinental and Latin American ancestry of Peruvians are little, and ac-cording to what has been investigated, the CYP2C19*3, CYP2D6*2, *3, *4 and *6 alleles have more related to their ancestry.

A Double-Blind Randomized Trial to Investigate Mechanisms of Antidepressant-Related Dysfunctional Arousal in Depressed or Anxious Youth at Familial Risk for Bipolar Disorder

Antidepressants are standardly used to treat moderate to severe symptoms of depression and/or anxiety in youth but may also be associated with rare but serious psychiatric adverse events such as irritability, agitation, aggression, or suicidal ideation. Adverse events are especially common in youth with a family history of bipolar disorder (BD) who are at heightened risk for dysfunction in neurobiological systems that regulate emotion and arousal. To further understand this phenomenon, this study will examine (a) baseline risk factors associated with dysfunctional arousal in a sample of youth at high-risk for BD treated with or without an antidepressant, (b) whether antidepressant-related changes in arousal are mediated by changes in prefrontal-limbic circuitry, and (c) whether pharmacogenetic factors influence antidepressant-related changes in arousal. High-risk youth (aged 12-17 years with moderate to severe depressive and/or anxiety symptoms and at least one first-degree relative with bipolar I disorder) will be randomized to receive psychotherapy plus escitalopram or psychotherapy plus placebo. Neuroimaging and behavioral measures of arousal will be collected prior to randomization and at 4 weeks. Samples for pharmacogenetic analysis (serum escitalopram concentration, CYP2C19 metabolizer phenotype, and HTR2A and SLC6A4 genotypes) will be collected at 8 weeks. Youth will be followed for up to 16 weeks to assess change in arousal measures.

Pharmacogenomics-Guided Pharmacotherapy in Patients with Major Depressive Disorder or Bipolar Disorder Affected by Treatment-Resistant Depressive Episodes: A Long-Term Follow-up Study

Treatment-resistant depression (TRD) reduces affected patients’ quality of life and leads to important social health care costs. Pharmacogenomics-guided treatment (PGT) may be effective in the cure of TRD. The main aim of this study was to evaluate the clinical changes after PGT in patients with TRD (two or more recent failed psychopharmacological trials) affected by bipolar disorder (BD) or major depressive disorder (MDD) compared to a control group with treatment as usual (TAU). We based the PGT on assessing different gene polymorphisms involved in the pharmacodynamics and pharmacokinetics of drugs. We analyzed, with a repeated-measure ANOVA, the changes between the baseline and a 6 month follow-up of the efficacy index assessed through the Clinical Global Impression (CGI) scale, and depressive symptoms through the Hamilton Depression Rating Scale (HDRS). The PGT sample included 53 patients (26 BD and 27 MDD), and the TAU group included 52 patients (31 BD and 21 MDD). We found a significant within-subject effect of treatment time on symptoms and efficacy index for the whole sample, with significant improvements in the efficacy index (F = 8.544; partial η² = 0.077, p < 0.004) and clinical global impression of severity of illness (F = 6.818; partial η² = 0.062, p < 0.01) in the PGT vs. the TAU group. We also found a significantly better follow-up response (χ² = 5.479; p = 0.019) and remission (χ² = 10.351; p = 0.001) rates in the PGT vs. the TAU group. PGT may be an important option for the long-term treatment of patients with TRD affected by mood disorders, providing information that can better define drug treatment strategies and increase therapeutic improvement.

Potential pharmacogenomic targets in bipolar disorder: considerations for current testing and the development of decision support tools to individualize treatment selection

Background

Treatment in bipolar disorder (BD) is commonly applied as a multimodal therapy based on decision algorithms that lack an integrative understanding of molecular mechanisms or a biomarker associated clinical outcome measure. Pharmacogenetics/genomics study the individual genetic variation associated with drug response. This selective review of pharmacogenomics and pharmacogenomic testing (PGT) in BD will focus on candidate genes and genome wide association studies of pharmacokinetic drug metabolism and pharmacodynamic drug response/adverse event, and the potential role of decision support tools that incorporate multiple genotype/phenotype drug recommendations.

Main body

We searched PubMed from January 2013 to May 2019, to identify studies reporting on BD and pharmacogenetics, pharmacogenomics and PGT. Studies were selected considering their contribution to the field. We summarize our findings in: targeted candidate genes of pharmacokinetic and pharmacodynamic pathways, genome-wide association studies and, PGT platforms, related to BD treatment. This field has grown from studies of metabolizing enzymes (i.e., pharmacokinetics) and drug transporters (i.e., pharmacodynamics), to untargeted investigations across the entire genome with the potential to merge genomic data with additional biological information.

Conclusions

The complexity of BD genetics and, the heterogeneity in BD drug-related phenotypes, are important considerations for the design and interpretation of BD PGT. The clinical applicability of PGT in psychiatry is in its infancy and is far from reaching the robust impact it has in other medical disciplines. Nonetheless, promising findings are discovered with increasing frequency with remarkable relevance in neuroscience, pharmacology and biology.

CYP2C9 and CYP2C19: Deep Mutational Scanning and Functional Characterization of Genomic Missense Variants

Single nucleotide variants in the open reading frames (ORFs) of pharmacogenes are important causes of interindividual variability in drug response. The functional characterization of variants of unknown significance within ORFs remains a major challenge for pharmacogenomics. Deep mutational scanning (DMS) is a high-throughput technique that makes it possible to analyze the functional effect of hundreds of variants in a parallel and scalable fashion. We adapted a "landing pad" DMS system to study the function of missense variants in the ORFs of cytochrome P450 family 2 subfamily C member 9 (CYP2C9) and cytochrome P450 family 2 subfamily C member 19 (CYP2C19). We studied 230 observed missense variants in the CYP2C9 and CYP2C19 ORFs and found that 19 of 109 CYP2C9 and 36 of 121 CYP2C19 variants displayed less than ~ 25% of the wild-type protein expression, a level that may have clinical relevance. Our results support DMS as an efficient method for the identification of damaging ORF variants that might have potential clinical pharmacogenomic application.