Effects of antidepressant on FKBP51 mRNA expression and neuroendocrine hormones in patients with panic disorder.

OBJECTIVE: The purpose of this study was to investigate the effects of escitalopram on the peripheral expression of hypothalamic-pituitary-adrenal (HPA) axis-related genes (FKBP51, HSP90, NR3C1 and POMC) and HPA-axis hormones in patients with panic disorder (PD). METHODS: Seventy-seven patients with PD were treated with escitalopram for 12 weeks. All participants were assessed for the severity of panic symptoms using the Panic Disorder Severity Scale (PDSS). The expression of HPA-axis genes was measured using real-time quantitative fluorescent PCR, and ACTH and cortisol levels were measured using chemiluminescence at baseline and after 12 weeks of treatment. RESULTS: At baseline, patients with PD had elevated levels of ACTH and cortisol, and FKBP51 expression in comparison to healthy controls (all p < 0.01). Correlation analysis revealed that FKBP51 expression levels were significantly positively related to cortisol levels and the severity of PD (all p < 0.01). Furthermore, baseline ACTH and cortisol levels, and FKBP51 expression levels were significantly reduced after 12 weeks of treatment, and the change in the PDSS score from baseline to post-treatment was significantly and positively related to the change in cortisol (p < 0.01). CONCLUSIONS: The results suggest that PD may be associated with elevated levels of ACTH and cortisol, and FKBP51 expression, and that all three biomarkers are substantially decreased in patients who have received escitalopram treatment.

Effectiveness of Antidepressants in Combination with Psychotherapy.

BACKGROUND: Consensus-guidelines for prescribing antidepressants recommend that clinicians should be vigilant to match antidepressants to patient's medical history but provide no specific advice on which antidepressant is best for a given medical history. AIMS OF THE STUDY: For patients with major depression who are in psychotherapy, this study provides an empirically derived guideline for prescribing antidepressant medications that fit patients' medical history. METHODS: This retrospective, observational, cohort study analyzed a large insurance database of 3,678,082 patients. Data was obtained from healthcare providers in the U.S. between January 1, 2001, and December 31, 2018. These patients had 10,221,145 episodes of antidepressant treatments. This study reports the remission rates for the 14 most commonly prescribed single antidepressants (amitriptyline, bupropion, citalopram, desvenlafaxine, doxepin, duloxetine, escitalopram, fluoxetine, mirtazapine, nortriptyline, paroxetine, sertraline, trazodone, and venlafaxine) and a category named "Other" (other antidepressants/combination of antidepressants). The study used robust LASSO regressions to identify factors that affected remission rate and clinicians' selection of antidepressants. The selection bias in observational data was removed through stratification. We organized the data into 16,770 subgroups, of at least 100 cases, using the combination of the largest factors that affected remission and selection bias. This paper reports on 2,467 subgroups of patients who had received psychotherapy. RESULTS: We found large, and statistically significant, differences in remission rates within subgroups of patients. Remission rates for sertraline ranged from 4.5% to 77.86%, for fluoxetine from 2.86% to 77.78%, for venlafaxine from 5.07% to 76.44%, for bupropion from 0.5% to 64.63%, for desvenlafaxine from 1.59% to 75%, for duloxetine from 3.77% to 75%, for paroxetine from 6.48% to 68.79%, for escitalopram from 1.85% to 65%, and for citalopram from 4.67% to 76.23%. Clearly these medications are ideal for patients in some subgroups but not others. If patients are matched to the subgroups, clinicians can prescribe the medication that works best in the subgroup. Some medications (amitriptyline, doxepin, nortriptyline, and trazodone) always had remission rates below 11% and therefore were not suitable as single antidepressant therapy for any of the subgroups. DISCUSSIONS: This study provides an opportunity for clinicians to identify an optimal antidepressant for their patients, before they engage in repeated trials of antidepressants. IMPLICATIONS FOR HEALTH CARE PROVISION AND USE: To facilitate the matching of patients to the most effective antidepressants, this study provides access to a free, non-commercial, decision aid at http://MeAgainMeds.com. IMPLICATIONS FOR HEALTH POLICIES:  Policymakers should evaluate how study findings can be made available through fragmented electronic health records at point-of-care. Alternatively, policymakers can put in place an AI system that recommends antidepressants to patients online, at home, and encourages them to bring the recommendation to their clinicians at their next visit. IMPLICATIONS FOR FURTHER RESEARCH:  Future research could investigate (i) the effectiveness of our recommendations in changing clinical practice, (ii) increasing remission of depression symptoms, and (iii) reducing cost of care. These studies need to be prospective but pragmatic. It is unlikely random clinical trials can address the large number of factors that affect remission.

Utilizing Pharmacogenomics Results to Guide Antidepressant Selection: A Case Report.

The case discussion demonstrates the benefit of using Pharmacogenomic (PGx) results to aid in the selection of antidepressant therapy and improve response to treatment. Nearly half of patients diagnosed with major depressive disorder fail initial therapy and may require multiple trials of antidepressants. Genetic variation in several metabolic enzymes contribute to the variable response to antidepressant therapy. PGx testing provides an opportunity to inform antidepressant selection and optimize therapeutic outcomes, while minimizing risk of adverse events. A 79-year-old female who had been experiencing a suboptimal response to escitalopram following dose escalation over a period of three years was referred for a PGx consultation. A clinical pharmacist assessed significant drug-gene, drug-drug, and drug-drug-gene interactions, and relevant clinical information to recommend alternative antidepressant therapy, which resulted in mood improvement.

Unraveling the potential of Morinda officinalis oligosaccharides as an adjuvant of escitalopram in depression treatment and exploring the underlying mechanisms.

ETHNOPHAMACOLOGICAL RELEVANCE: Morinda officinalis oligosaccharides (MOs) is a mixture of oligosaccharides extracted from the roots of Morinda officinalis (MO). It is approved by Chinese Food and Drug Administration (CFDA) for depression treatment. MOs could improve the antidepressant efficacy of escitalopram in clinic. AIM OF THE STUDY: We aim to explore the antidepressant activity and potential mechanism of the combination usage of MOs and escitalopram on animal model of depression. MATERIALS AND METHODS: Depressive animal model was induced by chronic mild stress (CMS). Behavioral tests were conducted to evaluate the antidepressant efficacy of MOs and escitalopram. Serum neurotransmitter levels were detected by High-performance liquid chromatography (HPLC). Quantitative real-time PCR and Western blotting were applied to assay the hippocampus neurotrophic factors' mRNA and protein levels. Peripheral cytokines levels were measured through Enzyme-Linked Immunosorbent Assay (ELISA). Micorglia polization phenotype was assayed by immunofluorescence and flow cytometry. RESULTS: MOs and escitalopram obviously attenuated depression-like behaviors of CMS mice. Importantly, MOs plus escitalopram exhibited better antidepressant activity on CMS mice than monotherapy. At the same time, MOs combined escitalopram treatment significantly increased hippocampus neurotransmitters and neurotrophic factor levels, stimulated hippocampus neurogenesis and relieved central nervous system (CNS) microglia over-activation of CMS mice. The combination therapy had greater effect on neuroprotection and inflammation attenuation of CMS mice than monotherapy. CONCLUSION: Our results indicates MOs combined escitalopram might produce antidepressant activity through protecting neuron activity, relieving inflammation and modulating microglia polarization process.

Sildenafil, alone and in combination with imipramine or escitalopram, display antidepressant-like effects in an adrenocorticotropic hormone-induced (ACTH) rodent model of treatment-resistant depression.

BACKGROUND: Major depressive disorder (MDD) represents a challenge with high prevalence and limited effectiveness of existing treatments, particularly in cases of treatment-resistant depression (TRD). Innovative strategies and alternative drug targets are therefore necessary. Sildenafil, a selective phosphodiesterase type 5 (PDE5) inhibitor, is known to exert neuroplastic, anti-inflammatory, and antioxidant properties, and is a promising antidepressant drug candidate. AIM: To investigate whether sildenafil monotherapy or in combination with a known antidepressant, can elicit antidepressant-like effects in an adrenocorticotropic hormone (ACTH)-induced rodent model of TRD. METHODS: ACTH-naïve and ACTH-treated male Sprague-Dawley (SD) rats received various sub-acute drug treatments, followed by behavioural tests and biochemical analyses conversant with antidepressant actions. RESULTS: Sub-chronic ACTH treatment induced significant depressive-like behaviour in rats, evidenced by increased immobility during the forced swim test (FST). Sub-acute sildenafil (10 mg/kg) (SIL-10) (but not SIL-3), and combinations of imipramine (15 mg/kg) (IMI-15) and sildenafil (3 mg/kg) (SIL-3) or escitalopram (15 mg/kg) (ESC-15) and SIL-3, exhibited significant antidepressant-like effects. ACTH treatment significantly elevated hippocampal levels of brain-derived neurotrophic factor (BDNF), serotonin, norepinephrine, kynurenic acid (KYNUA), quinolinic acid (QUINA), and glutathione. The various mono- and combined treatments significantly reversed some of these changes, whereas IMI-15 + SIL-10 significantly increased glutathione disulfide levels. ESC-15 + SIL-3 significantly reduced plasma corticosterone levels. CONCLUSION: This study suggests that sildenafil shows promise as a treatment for TRD, either as a stand-alone therapy or in combination with a traditional antidepressant. The neurobiological mechanism underlying the antidepressant-like effects of the different sildenafil mono- and combination therapies reflects a multimodal action and cannot be explained in full by changes in the individually measured biomarker levels.

Perspectives on the impact of vortioxetine on the treatment armamentarium of major depressive disorder.

INTRODUCTION: Major Depressive Disorder (MDD) is a mental health issue that significantly affects patients' quality of life and functioning. Despite available treatments, many patients continue to suffer due to incomplete symptom resolution and side effects. AREAS COVERED: This manuscript examines Vortioxetine's role in Major Depressive Disorder (MDD) treatment, highlighting its potential to reshape therapeutic strategies due to its unique Multimodal action and proven broad-spectrum efficacy in multiple depressive domains. A detailed examination of Vortioxetine's pharmacological aspects, including indications, dosage, pharmacodynamics, and pharmacokinetics, is provided, emphasizing its safety and effectiveness. The discussion extends to Vortioxetine's role in acute-phase treatment and maintenance of MDD and its profound impact on specialized depression domains. EXPERT OPINION: Vortioxetine is distinguished for its novel multimodal serotonin modulation mechanism, showcasing significant promise as an innovative treatment for MDD. Its efficacy, which is dose-dependent, along with a commendable tolerability profile, positions it as a potential leading option for initial treatment strategies. The discourse on dosage titration, particularly the strategy of initiating treatment at lower doses followed by gradual escalation, underscores the approach toward minimizing initial adverse effects while optimizing therapeutic outcomes, aligning with the principles of personalized medicine in psychiatric care.

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.

Symptom clusters in adolescent depression and differential responses of clusters to pharmacologic treatment.

OBJECTIVE: Symptoms of depression in adolescents are widely variable, but they are often interactive and clustered. The analysis of interactions and clusters among individual symptoms may help predict treatment outcomes. We aimed to determine clusters of individual symptoms in adolescent depression and their changes in the response to pharmacological treatment. METHOD: A total of 95 adolescents, aged 12-17 years, with major depressive disorder were included. Participants were treated with escitalopram, and depressive symptoms were assessed at baseline (V1) and 1, 2, 4, 6, and 8 weeks (V6). The severity of depression was assessed using the Children's Depression Rating Scale-Revised. To construct network and clustering structures among symptoms, the Gaussian graphical model and Exploratory Graph Analysis with the tuning parameter to minimize the extended Bayesian information criterion were adopted. RESULTS: Exploratory Graph Analysis revealed that symptoms of depression comprised four clusters: impaired activity, somatic concerns, subjective mood, and observed affect. The main effect of visit with decreased symptom severity was significant in all four clusters; however, the degree of symptom improvement differed among the four clusters. The effect size of score differences from V1 to V6 was the highest in the subjective mood (Cohen's d = 1.075), and lowest in impaired activity (d = 0.501) clusters. CONCLUSION: The present study identified four symptom clusters associated with adolescent depression and their differential changes related to antidepressant treatment. This finding suggests that escitalopram was the most effective at improving subjective mood among different clusters. However, other therapeutic modalities may be needed to improve other clusters of symptoms, consequently leading to increased overall improvement of depression in adolescents.

Serotonin transporter imaging agent as a probe for ß-cells of pancreas.

OBJECTIVE: Diabetes mellitus (DM) is one of the major diseases in the world. Nuclear medicine imaging may be able to detect functional status of pancreatic ß cells in vivo, which might elucidate the pathological mechanisms of diabetes and develop individualized treatment plans. In this study, we evaluated the ability of [125I]ADAM, a serotonin transporter (SERT) imaging agent, as a probe for detecting pancreatic ß-cell mass (BCM). METHODS: In vitro cell studies were evaluated in INS-1 cells (rat islet ß cell line). Biodistribution studies were performed in male normal Sprague-Dawley rats and alloxan-induced type 1 diabetes mellitus (T1DM) rats. Distribution and expression of SERT protein in pancreas of rats were also measured by immunofluorescence staining and Western blot. RESULTS: In vitro cell studies showed that the concentration of [125I]ADAM associated with the INS-1 cells was increased gradually with incubation time, and the SERT specific inhibitor, escitalopram, exhibited the inhibitory effect on this interaction. Biodistribution studies also showed that the uptake of [125I]ADAM in the pancreas of normal rats was decreased in the presence of escitalopram. However, in the T1DM rat model with a significant ß cells reduction, the uptake of pancreas was increased when compared with the control. Through immunofluorescence staining and Western blot, it was found that both the endocrine and exocrine cells of the normal pancreas expressed SERT protein, and the level of SERT protein in the exocrine cells was higher than islets. In the diabetic state, the expression of SERT in the exocrine cells was further increased. CONCLUSIONS: The SERT imaging agent, [125I]ADAM, at the present form will not be suitable for imaging ß cells, specifically because there were extraordinarily high non-specific signals contributing from the exocrine cells of pancreas. In addition, we noticed that the level of SERT expression was abnormally elevated in the diabetic state, which might provide an unexpected target for studying the pathological mechanisms of diabetes.

Assessing Pharmacokinetic Correlates of Escitalopram-Related Adverse Drug Reactions.

BACKGROUND: To assess the pharmacokinetic correlates of reported adverse drug reactions (ADRs) under antidepressant treatment with escitalopram (ESC) using a large therapeutic drug monitoring database. METHODS: A large naturalistic sample of inpatients and outpatients prescribed ESC was analyzed. ADRs were classified using the Udvalg for Kliniske Undersogelser side effect rating scale. We compared ESC-treated patients with (n = 35) and without ADRs (n = 273) using ESC plasma concentrations as the primary outcome. We also compared ADR rates in the 2 groups based on 2 cut-off ESC levels reflecting the recommended upper thresholds of the therapeutic reference range of 80 ng/mL, suggested by the consensus therapeutic drug monitoring guidelines, and 40 ng/mL, based on recent meta-analysis data. The effects of age, sex, smoking, daily ESC dose, plasma concentrations, and concentrations corrected for daily dose were included in a binary logistic regression model to predict ADRs. RESULTS: No differences in clinical, demographic, or pharmacokinetic parameters were observed between patients with and without ADRs ( P > 0.05). Patients with ESC-related ADRs were more frequently diagnosed with psychotic disorders than those without (25% vs. 7.1%, P = 0.004). None of the variables was associated with ADR risk. Overall, ADR rates were not significantly different in patients above versus below thresholds of ESC concentrations (ESC concentrations >40 [n = 59] vs. ≤40 ng/mL [n = 249] and >80 [n = 8] vs. ≤80 ng/mL [n = 300]; P = 0.56 and P = 1.0, respectively). CONCLUSIONS: No distinct pharmacokinetic patterns underlying ESC-associated ADRs were observed. Further studies with more specific assessments of ADRs in larger cohorts are required to better identify potential underlying patterns.

Comparative effectiveness of selective serotonin reuptake inhibitors (SSRIs) for depression in 43,061 older adults with chronic somatic diseases: A Danish target trial emulation study.

OBJECTIVE: To investigate the comparative effectiveness of commonly used selective serotonin reuptake inhibitors (SSRIs) for comorbid depression in older adults with chronic somatic diseases by applying a target-trial-emulation framework. METHODS: Danish target-trial-emulation study including 43,061 individuals aged ≥65 years (54.1% females, mean age 77.8 years) with a first redeemed prescription for depression with sertraline (n = 6673), escitalopram (n = 7104) or citalopram (n = 29,284) in 2006-2017. Individuals had cancer, cardiovascular diseases (CVD), chronic-obstructive-pulmonary-disease (COPD)/asthma, diabetes, neurodegenerative disorders, or osteoporosis. Outcomes were treatment switching, combination/augmentation, psychiatric hospital contact for depression, and any psychiatric in-patient care. Follow-up was one year and adjusted Cox regression analyses calculated hazard rate ratios (HRR) within each somatic disease. RESULTS: Across all six disease groups and four outcomes, we found that citalopram use, compared with sertraline, was associated with lower risks in several analyses, with statistically significant results in cancer, CVD, COPD/asthma, and diabetes (e.g., HRRs for psychiatric hospital contacts for depression/any psychiatric in-patient care ranging between 0.47 and 0.61). For escitalopram, compared with sertraline, some analyses indicated poorer outcomes with significantly higher risks for combination/augmentation treatment (HRRs ranging between 1.15 and 1.40). CONCLUSIONS: Although observational studies are prone to confounding, these findings indicate clinically relevant differences between the SSRIs, with better outcomes in citalopram users and poorer outcomes in escitalopram users than sertraline, urging the need for clinical studies in this vulnerable patient population.

Predicting the outcome of psilocybin treatment for depression from baseline fMRI functional connectivity.

BACKGROUND: Psilocybin is a serotonergic psychedelic drug under assessment as a potential therapy for treatment-resistant and major depression. Heterogeneous treatment responses raise interest in predicting the outcome from baseline data. METHODS: A machine learning pipeline was implemented to investigate baseline resting-state functional connectivity measured with functional magnetic resonance imaging (fMRI) as a predictor of symptom severity in psilocybin monotherapy for treatment-resistant depression (16 patients administered two 5 mg capsules followed by 25 mg, separated by one week). Generalizability was tested in a sample of 22 patients who participated in a psilocybin vs. escitalopram trial for moderate-to-severe major depression (two separate doses of 25 mg of psilocybin 3 weeks apart plus 6 weeks of daily placebo vs. two separate doses of 1 mg of psilocybin 3 weeks apart plus 6 weeks of daily oral escitalopram). The analysis was repeated using both samples combined. RESULTS: Functional connectivity of visual, default mode and executive networks predicted early symptom improvement, while the salience network predicted responders up to 24 weeks after treatment (accuracy≈0.9). Generalization performance was borderline significant. Consistent results were obtained from the combined sample analysis. Fronto-occipital and fronto-temporal coupling predicted early and late symptom reduction, respectively. LIMITATIONS: The number of participants and differences between the two datasets limit the generalizability of the findings, while the lack of a placebo arm limits their specificity. CONCLUSIONS: Baseline neurophysiological measurements can predict the outcome of psilocybin treatment for depression. Future research based on larger datasets should strive to assess the generalizability of these predictions.

Pharmacokinetic correlates of clinical response in a naturalistic sample of escitalopram-treated patients.

OBJECTIVE: We assessed pharmacokinetic correlates of treatment response to escitalopram using a large therapeutic drug monitoring database. METHODS: A large naturalistic sample of patients receiving escitalopram was analyzed. Responders were defined as 'very much improved' or 'much improved' based on the Clinical Global Impression - Improvement score, CGI-I. We compared responders (n = 83) vs. non-responders (n = 388) with the primary outcome being the escitalopram plasma concentration and concentration corrected by the daily dose (C/D ratio). Effects of age, sex, body-mass-index (BMI), and C/D ratio were assessed in a multivariate logistic regression model predicting response. RESULTS: There were no statistically significant differences in clinical and demographic characteristics between responders vs. non-responders. There were also no differences between escitalopram daily doses or plasma concentrations, while C/D ratios were significantly higher in non-responders than in responders (1.6 ± 1.7 vs. 1.2 ± 0.9 (ng/mL)/(mg/day), p = 0.007); C/D ratios (odds ratio 0.52, 95% confidence interval 0.34-0.80, p < 0.003) were associated with response to escitalopram, after controlling for age, sex, and BMI. CONCLUSIONS: Patients with low clearance of escitalopram as reflected upon high C/D ratios may be less likely respond to escitalopram. Identifying these patients during dose titration may support clinical decision-making, including switching to a different antidepressant instead of increasing daily dose.

Functional brain responses to emotional faces after three to five weeks of intake of escitalopram in healthy individuals: a double-blind, placebo-controlled randomised study.

Short-term intake of selective serotonin reuptake inhibitors (SSRIs) modulates threat-related amygdala responses in healthy individuals. However, how SSRI intake over a clinically relevant time period modulates threat-related amygdala responses is less clear. In a semi-randomised, double-blind, placebo-controlled study of 64 healthy individuals (SSRI n = 32, placebo n = 32), we examined the effect of 3-5 weeks of SSRI escitalopram (20 mg daily) on brain response to angry, fearful and neutral faces using BOLD fMRI. Data was analysed using a whole-brain region-wise approach extracting standardised effects (i.e., Cohen's D). The study was conducted at the Copenhagen University Hospital. A priori, we hypothesised that SSRI would attenuate amygdala responses to angry and fearful faces but not to neutral ones. Whether SSRI modulates correlations between amygdala responses to emotional faces and negative mood states was also explored. Compared to placebo, 3-5 weeks of SSRI intake did not significantly affect the amygdala response to angry, fearful, or neutral faces (|Cohen's D|< 0.2, PFWER = 1). Whole-brain, region-wise analyses revealed significant differences in frontal (|Cohen's D|< 0.6, PFWER < .01) and occipital regions (|Cohen's D|< 0.5, PFWER < .01). SSRI did not modulate correlations between amygdala responses to emotional faces and negative mood states. Our findings indicate that a 3-5 week SSRI intake impacts cortical responses to emotional stimuli, an effect possibly involved in SSRI's therapeutic efficacy.Trial registration Clinical Trials NCT04239339.

Psychedelics and sexual functioning: a mixed-methods study.

Do psychedelics affect sexual functioning postacutely? Anecdotal and qualitative evidence suggests they do, but this has never been formally tested. While sexual functioning and satisfaction are generally regarded as an important aspect of human wellbeing, sexual dysfunction is a common symptom of mental health disorders. It is also a common side effect of selective serotonin reuptake inhibitors (SSRIs), a first line treatment for depression. The aim of the present paper was to investigate the post-acute effects of psychedelics on self-reported sexual functioning, combining data from two independent studies, one large and naturalistic and the other a smaller but controlled clinical trial. Naturalistic use of psychedelics was associated with improvements in several facets of sexual functioning and satisfaction, including improved pleasure and communication during sex, satisfaction with one's partner and physical appearance. Convergent results were found in a controlled trial of psilocybin therapy versus an SSRI, escitalopram, for depression. In this trial, patients treated with psilocybin reported positive changes in sexual functioning after treatment, while patients treated with escitalopram did not. Despite focusing on different populations and settings, this is the first research study to quantitively investigate the effects of psychedelics on sexual functioning. Results imply a potential positive effect on post-acute sexual functioning and highlight the need for more research on this.

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.

The Relevance of Integrating CYP2C19 Phenoconversion Effects into Clinical Pharmacogenetics.

INTRODUCTION: CYP2D6 and CYP2C19 functional status as defined by genotype is modulated by phenoconversion (PC) due to pharmacokinetic interactions. As of today, there is no data on the effect size of PC for CYP2C19 functional status. The primary aim of this study was to investigate the impact of PC on CYP2C19 functional status. METHODS: Two patient cohorts (total n=316; 44.2±15.4 years) were investigated for the functional enzyme status of CYP2C19 applying two different correction methods (PCBousman, PCHahn&Roll) as well as serum concentration and metabolite-to-parent ratio of venlafaxine, amitriptyline, mirtazapine, sertraline, escitalopram, risperidone, and quetiapine. RESULTS: There was a decrease in the number of normal metabolizers of CYP2C19 and an increase in the number of poor metabolizers. When controlled for age, sex, and, in the case of amitriptyline, venlafaxine, and risperidone, CYP2D6 functional enzyme status, an association was observed between the CYP2C19 phenotype/functional enzyme status and serum concentration of amitriptyline, sertraline, and escitalopram. DISCUSSION: PC of CYP2C19 changes phenotypes but does not improve correlations with serum concentrations. However, only a limited number of patients received perturbators of CYP2C19. Studies with large numbers of patients are still lacking, and thus, it cannot be decided if there are minor differences and which method of correction to use. For the time being, PC is relevant in individual patients treated with CYP2C19-affecting drugs, for example, esomeprazole. To ensure adequate serum concentrations in these patients, this study suggests the use of therapeutic drug monitoring.

Efficacy and safety of agomelatine in epilepsy patients with sleep and mood disorders: An observational, retrospective cohort study.

OBJECTIVE: To evaluate the therapeutic efficacy and safety of agomelatine for treating the sleep and mood disorders in epilepsy patients. METHODS: Retrospective data were derived from 113 epilepsy patients for at least 8 weeks. All the subjects were divided into two groups, one was treated with agomelatine, the other was treated with escitalopram. Their depression and anxiety states were assessed by Hamilton Depression (HAMD) and Hamilton Anxiety (HAMA) Scales. Sleep quality was assessed by the Pittsburgh Sleep Quality Index (PSQI). RESULTS: The HAMA, HAMD and PSQI scores in both groups significantly declined after the treatments with agomelatine and escitalopram. However, the agomelatine group exhibited greater improvement in terms of HAMA and PSQI scores compared to the escitalopram group. No severe adverse events were observed in agomelatine group. SIGNIFICANCE: Agomelatine performed better in HAMA and PSQI scores compared to escitalopram, where no significant increase in seizure frequency or side effects were observed. Possibly, agomelatine presents a promising therapeutic option for treating the sleep or mood disorders in epilepsy patients.

Age of onset for increased dose-adjusted serum concentrations of antidepressants and association with sex and genotype: An observational study of 34,777 individuals.

PURPOSE: The aim of this study was to examine the age of onset for increased dose-adjusted serum concentrations (C/D ratio) of common antidepressant drugs and to explore the potential association with sex and CYP2C19/CYP2D6 genotype. METHODS: Serum concentrations and prescribed daily doses for citalopram, escitalopram, sertraline, venlafaxine and mirtazapine, and CYP genotypes, were obtained from a therapeutic drug monitoring (TDM) service. Segmented linear regression analysis was used to examine the relationship between age and antidepressant log C/D ratio in (i) all individuals, (ii) men and women, and (iii) CYP2D6/CYP2C19 normal metabolizers (NMs) and CYP2D6/CYP2C19 intermediate or poor metabolizers (IMs/PMs). RESULTS: A total of 34,777 individuals were included in the study; CYP genotype was available for 21.3%. An increase in C/D ratio started at 44‒55 years of age. Thereafter, the increase progressed more rapidly for citalopram and escitalopram than for venlafaxine and mirtazapine. A doubled C/D ratio was estimated to occur at 79 (citalopram), 81 (escitalopram), 86 (venlafaxine), and 90 years (mirtazapine). For sertraline, only modest changes in C/D ratio were observed. For escitalopram and venlafaxine, the observed increase in C/D ratio started earlier in women than in men. The results regarding CYP genotype were inconclusive. CONCLUSION: The age-related increase in C/D ratio starts in middle-aged adults and progresses up to more than twofold higher C/D ratio in the oldest old. Sertraline seems to be less prone to age-related changes in C/D ratio than the other antidepressants.