Pharmacogenetics of antidepressant response

A New Intervention for Implementation of Pharmacogenetics in Psychiatry: A Description of the PSY-PGx Clinical Study

(1) Background Pharmacological treatment for psychiatric disorders has shown to only be effective in about one-third of patients, as it is associated with frequent treatment failure, often because of side effects, and a long process of trial-and-error pharmacotherapy until an effective and tolerable treatment is found. This notion emphasizes the urgency for a personalized medicine approach in psychiatry. (2) Methods This prospective patient- and rater-blinded, randomized, controlled study will investigate the effect of dose-adjustment of antidepressants escitalopram and sertraline or antipsychotics risperidone and aripiprazole according to the latest state-of-the-art international dosing recommendations for CYP2C19 and CYP2D6 metabolizer status in patients with mood, anxiety, and psychotic disorders. A total sample of N = 2500 will be recruited at nine sites in seven countries (expected drop-out rate of 30%). Patients will be randomized to a pharmacogenetic group or a dosing-as-usual group and treated over a 24-week period with four study visits. The primary outcome is personal recovery using the Recovery Assessment Scale as assessed by the patient (RAS-DS), with secondary outcomes including clinical effects (response or symptomatic remission), side effects, general well-being, digital phenotyping, and psychosocial functioning. (3) Conclusions This is, to our knowledge, the first international, multi-center, non-industry-sponsored randomized controlled trial (RCT) that may provide insights into the effectiveness and utility of implementing pharmacogenetic-guided treatment of psychiatric disorders, and as such, results will be incorporated in already available dosing guidelines.

An integrated precision medicine approach in major depressive disorder: a study protocol to create a new algorithm for the prediction of treatment response

Major depressive disorder (MDD) is the most common psychiatric disease worldwide with a huge socio-economic impact. Pharmacotherapy represents the most common option among the first-line treatment choice; however, only about one third of patients respond to the first trial and about 30% are classified as treatment-resistant depression (TRD). TRD is associated with specific clinical features and genetic/gene expression signatures. To date, single sets of markers have shown limited power in response prediction. Here we describe the methodology of the PROMPT project that aims at the development of a precision medicine algorithm that would help early detection of non-responder patients, who might be more prone to later develop TRD. To address this, the project will be organized in 2 phases. Phase 1 will involve 300 patients with MDD already recruited, comprising 150 TRD and 150 responders, considered as extremes phenotypes of response. A deep clinical stratification will be performed for all patients; moreover, a genomic, transcriptomic and miRNomic profiling will be conducted. The data generated will be exploited to develop an innovative algorithm integrating clinical, omics and sex-related data, in order to predict treatment response and TRD development. In phase 2, a new naturalistic cohort of 300 MDD patients will be recruited to assess, under real-world conditions, the capability of the algorithm to correctly predict the treatment outcomes. Moreover, in this phase we will investigate shared decision making (SDM) in the context of pharmacogenetic testing and evaluate various needs and perspectives of different stakeholders toward the use of predictive tools for MDD treatment to foster active participation and patients' empowerment. This project represents a proof-of-concept study. The obtained results will provide information about the feasibility and usefulness of the proposed approach, with the perspective of designing future clinical trials in which algorithms could be tested as a predictive tool to drive decision making by clinicians, enabling a better prevention and management of MDD resistance.

Pharmacogenomics and the Management of Mood Disorders-A Review

Due to the chronic relapsing nature of mental disorders and increased life expectancy, the societal burden of these non-communicable diseases will increase even further. Treatments for mental disorders, such as depression, are available, but their effect is limited due to patients' (genetic) heterogeneity, low treatment compliance and frequent side effects. In general, only one-third of the patients respond to treatment. Today, medication selection in psychiatry relies on a trial-and-error approach based mainly on physicians' experience. Pharmacogenetic (PGx) testing can help in this process by determining the person-specific genetic factors that may predict clinical response and side effects associated with genetic variants that impact drug-metabolizing enzymes, drug transporters or drug targets. PGxis a discipline that investigates genetic factors that affect the absorption, metabolism, and transport of drugs, thereby affecting therapy outcome. These genetic factors can, among other things, lead to differences in the activity of enzymes that metabolize drugs. Studies in depressed patients show that genotyping of drug-metabolizing enzymes can increase the effectiveness of treatment, which could benefit millions of patients worldwide. This review highlights these studies, gives recommendations and provides future perspectives on how to proceed with PGx testing. Finally, it is recommended to consider genotyping for CYP2D6 and CYP2C19, when there is an indication (side effects or inefficacy).

Review on Surface-Modified Electrodes for the Enhanced Electrochemical Detection of Selective Serotonin Reuptake Inhibitors (SSRIs)

Selective serotonin re-uptake inhibitors (SSRIs) are one of the most commonly prescribed classes of antidepressants used for the treatment of moderate to severe depressive disorder, personality disorders and various phobias. This class of antidepressants was created with improved margins of safety. However, genetic polymorphism may be responsible for the high variability in patients' responses to treatment, ranging from failure to delayed therapeutic responses to severe adverse effects of treatment. It is crucial that the appropriate amount of SSRI drugs is administered to ensure the optimum therapeutic efficacy and intervention to minimise severe and toxic effects in patients, which may be the result of accidental and deliberate cases of poisoning. Determining SSRI concentration in human fluids and the environment with high sensitivity, specificity and reproducibility, and at a low cost and real-time monitoring, is imperative. Electrochemical sensors with advanced functional materials have drawn the attention of researchers as a result of these advantages over conventional techniques. This review article aims to present functional materials such as polymers, carbon nanomaterials, metal nanomaterials as well as composites for surface modification of electrodes for sensitive detection and quantification of SSRIs, including fluoxetine, citalopram, paroxetine, fluvoxamine and sertraline. Sensor fabrication, sensor/analyte interactions, design rationale and properties of functional material and the electrocatalytic effect of the modified electrode on SSRI detection are discussed.

Integrating multiple traits for improving polygenic risk prediction in disease and pharmacogenomics GWAS

Polygenic risk score (PRS) has been recently developed for predicting complex traits and drug responses. It remains unknown whether multi-trait PRS (mtPRS) methods, by integrating information from multiple genetically correlated traits, can improve prediction accuracy and power for PRS analysis compared with single-trait PRS (stPRS) methods. In this paper, we first review commonly used mtPRS methods and find that they do not directly model the underlying genetic correlations among traits, which has been shown to be useful in guiding multi-trait association analysis in the literature. To overcome this limitation, we propose a mtPRS-PCA method to combine PRSs from multiple traits with weights obtained from performing principal component analysis (PCA) on the genetic correlation matrix. To accommodate various genetic architectures covering different effect directions, signal sparseness and across-trait correlation structures, we further propose an omnibus mtPRS method (mtPRS-O) by combining P values from mtPRS-PCA, mtPRS-ML (mtPRS based on machine learning) and stPRSs using Cauchy Combination Test. Our extensive simulation studies show that mtPRS-PCA outperforms other mtPRS methods in both disease and pharmacogenomics (PGx) genome-wide association studies (GWAS) contexts when traits are similarly correlated, with dense signal effects and in similar effect directions, and mtPRS-O is consistently superior to most other methods due to its robustness under various genetic architectures. We further apply mtPRS-PCA, mtPRS-O and other methods to PGx GWAS data from a randomized clinical trial in the cardiovascular domain and demonstrate performance improvement of mtPRS-PCA in both prediction accuracy and patient stratification as well as the robustness of mtPRS-O in PRS association test.

The Role of Pharmacogenetics in Personalizing the Antidepressant and Anxiolytic Therapy

Pharmacotherapy for neuropsychiatric disorders, such as anxiety and depression, has been characterized by significant inter-individual variability in drug response and the development of side effects. Pharmacogenetics, as a key part of personalized medicine, aims to optimize therapy according to a patient's individual genetic signature by targeting genetic variations involved in pharmacokinetic or pharmacodynamic processes. Pharmacokinetic variability refers to variations in a drug's absorption, distribution, metabolism, and elimination, whereas pharmacodynamic variability results from variable interactions of an active drug with its target molecules. Pharmacogenetic research on depression and anxiety has focused on genetic polymorphisms affecting metabolizing cytochrome P450 (CYP) and uridine 5'-diphospho-glucuronosyltransferase (UGT) enzymes, P-glycoprotein ATP-binding cassette (ABC) transporters, and monoamine and γ-aminobutyric acid (GABA) metabolic enzymes, transporters, and receptors. Recent pharmacogenetic studies have revealed that more efficient and safer treatments with antidepressants and anxiolytics could be achieved through genotype-guided decisions. However, because pharmacogenetics cannot explain all observed heritable variations in drug response, an emerging field of pharmacoepigenetics investigates how epigenetic mechanisms, which modify gene expression without altering the genetic code, might influence individual responses to drugs. By understanding the epi(genetic) variability of a patient's response to pharmacotherapy, clinicians could select more effective drugs while minimizing the likelihood of adverse reactions and therefore improve the quality of treatment.

Early antidepressant treatment response prediction in major depression using clinical and TPH2 DNA methylation features based on machine learning approaches

OBJECTIVE

To identify DNA methylation and clinical features, and to construct machine learning classifiers to assign the patients with major depressive disorder (MDD) into responders and non-responders after a 2-week treatment into responders and non-responders.

METHOD

Han Chinese patients (291 in total) with MDD comprised the study population. Datasets contained demographic information, environment stress factors, and the methylation levels of 38 methylated sites of tryptophan hydroxylase 2 (TPH2) genes in peripheral blood samples. Recursive Feature Elimination (RFE) was employed to select features. Five classification algorithms (logistic regression, classification and regression trees, support vector machine, logitboost and random forests) were used to establish the models. Performance metrics (AUC, F-Measure, G-Mean, accuracy, sensitivity, specificity, positive predictive value and negative predictive value) were computed with 5-fold-cross-validation. Variable importance was evaluated by random forest algorithm.

RESULT

RF with RFE outperformed the other models in our samples based on the demographic information and clinical features (AUC = 61.2%, 95%CI: 60.1-62.4%) / TPH2 CpGs features (AUC = 66.6%, 95%CI: 65.4-67.8%) / both clinical and TPH2 CpGs features (AUC = 72.9%, 95%CI: 71.8-74.0%).

CONCLUSION

The effects of TPH2 on the early-stage antidepressant response were explored by machine learning algorithms. On the basis of the baseline depression severity and TPH2 CpG sites, machine learning approaches can enhance our ability to predict the early-stage antidepressant response. Some potentially important predictors (e.g., TPH2-10-60 (rs2129575), TPH2-2-163 (rs11178998), age of first onset, age) in early-stage treatment response could be utilized in future fundamental research, drug development and clinical practice.

Liking of salt is associated with depression, anxiety, and stress

Early research has shown variations in salt taste qualities in depression, anxiety, and stress. These studies evaluated changes to salt taste intensity and liking (pleasantness) of salt solutions but not of salty foods. Therefore, an Australian population survey (n = 424) was conducted where participants rated recalled intensity and liking of salt index foods and completed the Depression, Anxiety, and Stress Scale (DASS-21) to measure these states. Standard least squares regression (post hoc Tukey's HSD) compared means between groups, and nominal logistic regression assessed differences in distributions between categories. Higher salt liking was found in participants with DASS-21 scores indicative of severe depression (68.3 vs. 60.0, P = 0.005) and severe anxiety (68.4 vs. 60.0, P = 0.001) in comparison to those with normal scores, in all models. Higher salt liking was found in participants with DASS-21 scores indicative of moderate stress (67.7 vs. 60.2, P = 0.009) in the unadjusted model only. Higher salt liking was found in females with DASS-21 scores indicative of anxiety and stress, and in males with indicative depression and anxiety. No relationships between salt taste intensity ratings and the mood states were found. Results indicate that liking salty foods is positively correlated with depression, anxiety, and stress scores. Further research on the relationships between salt liking and intake of salt and salty foods, and the biological mechanisms of these mood states are needed to direct the application of findings toward potential new risk assessment measures, dietary interventions, or therapeutics.

Biological Psychiatry in Displaced Populations: What We Know, and What We Need to Begin to Learn

Conflict and climate change continue to displace millions of people, who experience unique trauma and stressors as they resettle in host countries. Both children and adults who are forcibly displaced, or choose to migrate, experience posttraumatic stress disorder, anxiety, depression, and other mental health conditions at higher rates than the general population. This may be attributed to severe, cumulative stress and trauma (largely interpersonal traumas); discrimination and harassment in host countries; and structural barriers to accessing and addressing mental health concerns, including clinician availability, language barriers, cultural differences, geographic accessibility, health care access, and stigma. Despite high exposure to and clinical impact of such experiences, and despite representing 1% of the world population, forcibly displaced people are underrepresented in neuroscientific research. The availability of such literature and research findings is significant in understanding the unique genetic and cultural aspects of trauma- and stress-related mental health, advocacy, reducing stigma, informing prevention, and treatment. The present work aimed to explore how the field of neuroscience can address mental health equity for individuals who have been uprooted in relation to land, with a focus on refugee populations. We offer practical suggestions on how to improve research in this area and narrow the gap in knowledge.

The pharmacogenomics of selective serotonin reuptake inhibitors

Antidepressant medications are frequently used as the first line of treatment for depression. However, their effectiveness is highly variable and influenced by genetic factors. Recently, pharmacogenetic studies, including candidate-gene, genome-wide association studies or polygenic risk scores, have attempted to uncover the genetic architecture of antidepressant response. Genetic variants in at least 27 genes are linked to antidepressant treatment response in both coding and non-coding genomic regions, but evidence is largely inconclusive due to the high polygenicity of the trait and limited cohort sizes in published studies. Future studies should increase the number and diversity of participants to yield sufficient statistical power to characterize the genetic underpinnings and biological mechanisms of treatment response, improve results generalizability and reduce racial health-related inequities.

Electrophysiological correlates and predictors of the antidepressant response to repeated ketamine infusions in treatment-resistant depression

BACKGROUND

Sub-anesthetic ketamine doses rapidly reduce depressive symptoms, although additional investigations of the underlying neural mechanisms and the prediction of response outcomes are needed. Electroencephalographic (EEG)-derived measures have shown promise in predicting antidepressant response to a variety of treatments, and are sensitive to ketamine administration. This study examined their utility in characterizing changes in depressive symptoms following single and repeated ketamine infusions.

METHODS

Recordings were obtained from patients with treatment-resistant major depressive disorder (MDD) (N = 24) enrolled in a multi-phase clinical ketamine trial. During the randomized, double-blind, crossover phase (Phase 1), patients received intravenous ketamine (0.5 mg/kg) and midazolam (30 μg/kg), at least 1 week apart. For each medication, three resting, eyes-closed recordings were obtained per session (pre-infusion, immediately post-infusion, 2 h post-infusion), and changes in power (delta, theta1/2/total, alpha1/2/total, beta, gamma), alpha asymmetry, theta cordance, and theta source-localized anterior cingulate cortex activity were quantified. The relationships between ketamine-induced changes with early (Phase 1) and sustained (Phases 2,3: open-label repeated infusions) decreases in depressive symptoms (Montgomery-Åsberg Depression Rating Score, MADRS) and suicidal ideation (MADRS item 10) were examined.

RESULTS

Both medications decreased alpha and theta immediately post-infusion, however, only midazolam increased delta (post-infusion), and only ketamine increased gamma (immediately post- and 2 h post-infusion). Regional- and frequency-specific ketamine-induced EEG changes were related to and predictive of decreases in depressive symptoms (theta, gamma) and suicidal ideation (alpha). Early and sustained treatment responders differed at baseline in surface-level and source-localized theta.

CONCLUSIONS

Ketamine exerts frequency-specific changes on EEG-derived measures, which are related to depressive symptom decreases in treatment-resistant MDD and provide information regarding early and sustained individual response to ketamine.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov: Action of Ketamine in Treatment-Resistant Depression, NCT01945047.

Venlafaxine and O-desmethylvenlafaxine serum levels are positively associated with antidepressant response in elder depressed out-patients

BACKGROUND

Therapeutic Drug Monitoring (TDM) represents one of the most promising tools in clinical practice to optimise antidepressant treatment. Nevertheless, little is still known regarding the relationship between clinical efficacy and serum concentration of venlafaxine (VEN). The aim of our study was to investigate the association between serum concentration of venlafaxine + O-desmethylvenlafaxine (SCVO) and antidepressant response (AR).

METHODS

52 depressed outpatients treated with VEN were recruited and followed in a naturalistic setting for three months. Hamilton Depression Rating Scale-21 was administered at baseline, at month 1 and at month 3 to assess AR. SCVO was measured at steady state. Linear regression analysis and nonlinear least-squares regression were used to estimate association between SCVO and AR.

RESULTS

Our results showed an association between AR and SCVO that follows a bell-shaped quadratic function with a progressive increase of AR within the therapeutic reference range of SCVO (i.e. 100-400 ng/mL) and a subsequent decrease of AR at higher serum levels.

DISCUSSION

This study strongly suggests that TDM could represent a more appropriate tool than the oral dosage to optimise the treatment with VEN. Specifically, highest efficacy might be achieved by titrating patients at SCVO levels around 400 ng/mL.

Impact of gender, depression severity and type of depressive episode on efficacy and safety of escitalopram: an observational study on major depressive disorder patients in southern India

Background

Antidepressant response is a complex trait influenced by clinical, demographic and genetic factors.

Objectives

To explore the influences of baseline depression severity, gender and type of depressive episode on efficacy and safety of escitalopram (10–20 mg/day) in South Indian patients with major depressive disorder (MDD).

Methods

The study was conducted on 18–65-year-old patients (n = 151) suffering from a first or recurrent episode of MDD with a 17-item Hamilton Depression Rating Scale (HDRS-17) score of ≥ 18 at baseline. Efficacy assessments were done using HDRS-17, Montgomery-Asberg Depression Rating Scale (MADRS), and Clinical Global Impression (CGI) at baseline and weeks 4, 8 and 12. Patients were monitored for adverse drug reactions (ADRs). Clinical outcomes were compared among various groups based on gender, type of depressive episode (first or recurrent episode) and baseline HDRS-17 scores (moderate depression—score between 17 and 23; severe depression—score ≥ 24).

Results

Among the 148 subjects who completed the 12-week study, 43.9% and 42.6% achieved response and remission, respectively. The decline in HDRS-17 and MADRS scores from baseline was significant (p value < 0.05) at all follow-up visits and a similar pattern was seen with CGI. Efficacy outcomes were better in the moderate baseline depression group compared with severe depression. There were no associations of efficacy with gender and type of depressive episode. A total of 247 adverse drug reactions (ADR) were reported and 119 (80.41%) subjects experienced at least one ADR during the study period. No serious ADR was reported. Male patients experienced more ADRs compared with females. The safety profile of escitalopram was similar across various groups based on baseline depression severity and type of depressive episode.

Conclusion

The study revealed that escitalopram is efficacious in south Indian MDD patients with a favourable safety profile. The efficacy was influenced by baseline depression severity whereas more ADRs were reported by male patients.

Tools for optimising pharmacotherapy in psychiatry (therapeutic drug monitoring, molecular brain imaging and pharmacogenetic tests): focus on antidepressants

Objectives: More than 40 drugs are available to treat affective disorders. Individual selection of the optimal drug and dose is required to attain the highest possible efficacy and acceptable tolerability for every patient.Methods: This review, which includes more than 500 articles selected by 30 experts, combines relevant knowledge on studies investigating the pharmacokinetics, pharmacodynamics and pharmacogenetics of 33 antidepressant drugs and of 4 drugs approved for augmentation in cases of insufficient response to antidepressant monotherapy. Such studies typically measure drug concentrations in blood (i.e. therapeutic drug monitoring) and genotype relevant genetic polymorphisms of enzymes, transporters or receptors involved in drug metabolism or mechanism of action. Imaging studies, primarily positron emission tomography that relates drug concentrations in blood and radioligand binding, are considered to quantify target structure occupancy by the antidepressant drugs in vivo. Results: Evidence is given that in vivo imaging, therapeutic drug monitoring and genotyping and/or phenotyping of drug metabolising enzymes should be an integral part in the development of any new antidepressant drug.Conclusions: To guide antidepressant drug therapy in everyday practice, there are multiple indications such as uncertain adherence, polypharmacy, nonresponse and/or adverse reactions under therapeutically recommended doses, where therapeutic drug monitoring and cytochrome P450 genotyping and/or phenotyping should be applied as valid tools of precision medicine.

Anxiety symptom remission is associated with genetic variation of PTPRZ1 among patients with major depressive disorder treated with escitalopram

OBJECTIVES

Genome-wide analyses of antidepressant response have suggested that genes initially associated with risk for schizophrenia may also serve as promising candidates for selective serotonin reuptake inhibitor (SSRI) efficacy. Protein tyrosine phosphatase, receptor-type, zeta-1 (PTPRZ1) has previously been shown to be associated with schizophrenia, but it has not been investigated as a predictor of antidepressant efficacy. The main objective of the study was to assess whether SSRI-mediated depressive and anxiety symptom remission in Chinese patients with major depressive disorder (MDD) are associated with specific PTPRZ1 variants.

METHODS

Two independent cohorts were investigated, the first sample (N = 344) received an SSRI (i.e. fluoxetine, sertraline, citalopram, escitalopram, fluvoxamine, or paroxetine) for 8 weeks. The second sample (N = 160) only received escitalopram for 8 weeks. Hamilton Depression and Hamilton Anxiety Rating Scale scores at 8-weeks post-baseline in both cohorts were used to determine remission status. Five PTPRZ1 variants (rs12154537, rs6466810, rs6466808, rs6955395, and rs1918031) were genotyped in both cohorts.

RESULTS

Anxiety symptom remission was robustly associated with PTPRZ1 rs12154537 (P = 0.004) and the G-G-G-G haplotype (rs12154537-rs6466810-rs6466808-rs6955395; P = 0.005) in cohort 2 but not cohort 1 (mixed SSRI use). Associations with depressive symptom remission did not survive correction for multiple testing.

CONCLUSIONS

These findings suggest that PTPRZ1 variants may serve as a marker of escitalopram-mediated anxiety symptom remission in MDD.

Rare genetic variability in human drug target genes modulates drug response and can guide precision medicine

Interindividual variability in drug response constitutes a major concern in pharmacotherapy. While polymorphisms in genes involved in drug disposition have been extensively studied, drug target variability remains underappreciated. By mapping the genomic variability of all human drug target genes onto high-resolution crystal structures of drug target complexes, we identified 1094 variants localized within 6 Å of drug-binding pockets and directly affecting their geometry, topology, or physicochemical properties. We experimentally show that binding site variants affect pharmacodynamics with marked drug- and variant-specific differences. In addition, we demonstrate that a common BCHE variant confers resistance to tacrine and rivastigmine, which can be overcome by the use of derivatives based on squaric acid scaffolds or tryptophan conjugation. These findings underscore the importance of genetic drug target variability and demonstrate that integration of genomic data and structural information can inform personalized drug selection and genetically guided drug development to overcome resistance.

Every Night and Every Morn: Effect of Variation in CLOCK Gene on Depression Depends on Exposure to Early and Recent Stress

The role of circadian dysregulation is increasingly acknowledged in the background of depressive symptoms, and is also a promising treatment target. Similarly, stress shows a complex relationship with the circadian system. The CLOCK gene, encoding a key element in circadian regulation has been implicated in previous candidate variant studies in depression with contradictory findings, and only a few such studies considered the interacting effects of stress. We investigated the effect of CLOCK variation with a linkage-disequilibrium-based clumping method, in interaction with childhood adversities and recent negative life events, on two phenotypes of depression, lifetime depression and current depressive symptoms in a general population sample. Methods: Participants in NewMood study completed questionnaires assessing childhood adversities and recent negative life events, the Brief Symptom Inventory to assess current depressive symptoms, provided data on lifetime depression, and were genotyped for 1054 SNPs in the CLOCK gene, 370 of which survived quality control and were entered into linear and logistic regression models with current depressive symptoms and lifetime depression as the outcome variable, and childhood adversities or recent life events as interaction variables followed by a linkage disequilibrium-based clumping process to identify clumps of SNPs with a significant main or interaction effect. Results: No significant clumps with a main effect were found. In interaction with recent life events a significant clump containing 94 SNPs with top SNP rs6825994 for dominant and rs6850524 for additive models on current depression was identified, while in interaction with childhood adversities on current depressive symptoms, two clumps, both containing 9 SNPs were found with top SNPs rs6828454 and rs711533. Conclusion: Our findings suggest that CLOCK contributes to depressive symptoms, but via mediating the effects of early adversities and recent stressors. Given the increasing burden on circadian rhythmicity in the modern lifestyle and our expanding insight into the contribution of circadian disruption in depression especially as a possible mediator of stress, our results may pave the way for identifying those who would be at an increased risk for depressogenic effects of circadian dysregulation in association with stress as well as new molecular targets for intervention in stress-related psychopathologies in mood disorders.

Policy and Practice Review: A First Guideline on the Use of Pharmacogenetics in Clinical Psychiatric Practice

Effective pharmacologic treatments for psychiatric disorders are available, but their effect is limited due to patients' genetic heterogeneity and low compliance-related to frequent adverse events. Only one third of patients respond to treatment and experience remission. Pharmacogenetics is a relatively young field which focusses on genetic analyses in the context of the metabolism and outcome of drug treatment. These genetic factors can, among other things, lead to differences in the activity of enzymes that metabolize drugs. Recently, a clinical guideline was authorized by the Dutch Clinical Psychiatric Association (NVvP) on the clinical use of pharmacogenetics in psychiatry. The main goal was to provide guidance, based on current evidence, on how to best use genotyping in clinical psychiatric practice. A systematic literature search was performed, and available publications were assessed using the GRADE methodology. General recommendations for psychiatric clinical practice were provided, and specific recommendations per medication were made available. This clinical guideline for caregivers prescribing psychotropic drugs is the product of a broad collaboration of professionals from different disciplines, making use of the information available at the Dutch Pharmacogenetics Working Group (DPWG) and the Clinical Pharmacogenetics Implementation Consortium (CPIC) so far. We summarize the relevant literature and all recommendations in this article. General recommendations are provided and also detailed recommendations per medication. In summary we advise to consider genotyping, when there are side effects or inefficacy for CYP2C19 and CYP2D6. When genotype information is available use this to select the right drug in the right dose for the right patient.

Prospects for personalization of depression treatment with genome sequencing

The effectiveness of antidepressants in the treatment of major depressive disorder varies considerably between patients. With these interindividual differences and a number of antidepressants to choose from, the first choice of treatment often fails to produce improvement in the patient's condition. A substantial part of the variation in response to antidepressants can be explained by genetic factors. Accordingly, variants related to drug metabolism in two pharmacogenes, CYP2D6 and CYP2C19, have already been translated into guidelines for antidepressant prescriptions. The role of variants in other genes that influence antidepressant responses is not yet understood. Furthermore, rare and individual variants account for a substantial part of genetic differences in antidepressant efficacy. Recent years have brought a tremendous increase in the accessibility of genome sequencing in terms of data availability and its clinical use. In this review, we summarize recent developments and current issues in the personalization of major depressive disorder treatment through pharmacogenomics.

The effect of rs1076560 (DRD2) and rs4680 (COMT) on tardive dyskinesia and cognition in schizophrenia subjects

OBJECTIVE

The aim of the study is to test the association of a functional variant each in DRD2 and COMT genes with schizophrenia and its endophenotypes.

BASIC METHODS

Effect of two functional variants rs1076560 in DRD2 and rs4680 in COMT on (1) schizophrenia (502 cases, 448 controls) diagnosed by Diagnostic and Statistical Manual of Mental Disorders-IV criteria and in subsets with (2) tardive dyskinesia (80 positive, 103 negative), assessed by Abnormal Involuntary Movement Scale (AIMS), positive and negative symptoms assessed by Positive and Negative Syndrome Scale (PANSS) and (3) cognition (299 cases, 245 controls), estimated by Penn Computerized Neurocognitive Battery, were analysed either using analysis of variance (ANOVA) or regression analysis.

MAIN RESULTS

No association of two SNPs with schizophrenia, but association of rs4680 (P < 0.05) with tardive dyskinesia was observed. On ANOVA, main effect of smoking [F(2,148) = 16.3; P = 3.9 × 10]; rs4680 [F(2,148) = 3.3; P = 0.04] and interaction effect of tardive dyskinesia-status*Smoking [F(2,148) = 5.4, P = 0.006]; Smoking*rs1076560 [F(3,148) = 3.6; P = 0.01]; Smoking*rs4680 [F(4,148) = 5.3; P = 4.7 × 10] were significant with AIMS tardive dyskinesia score. The main effect of rs1076560 [F(2,148) = 4.5; P = 0.013] and rs4680 [F(2,148) = 4.0; P = 0.02] were significant with limb truncal tardive dyskinesia. Allelic/genotypic (P = 0.004/P = 0.01) association of rs1076560 with negative scale of PANSS in tardive dyskinesia-negative; diminished expression factor of PANSS in tardive dyskinesia-negative subcohort (allelic/genotypic P = 3.3 × 10/6.6 × 10) and tardive dyskinesia cohorts (P = 0.003/0.002); genotypic association (P = 0.05) with disorganised/concrete factor in tardive dyskinesia-positive subcohorts were observed by regression analysis using gPLINKv2.050. Further allelic/genotypic (P = 0.02) association of rs4680 with depressed factor of PANSS in tardive dyskinesia cohort was observed. Allelic/genotypic association of rs1076560 with abstraction and mental flexibilityaccuracy (P = 0.03/0.04), abstraction and mental flexibilityefficiency (P = 0.01/0.02); allelic association with spatial abilityprocessing speed (P = 0.03), emotionefficiency (P = 0.05); and with spatial abilityefficiency (genotypic, P = 0.05) in healthy controls and allelic association of rs4680 with emotionefficiency in cases with schizophrenia (P = 0.04) were notable.

PRINCIPAL CONCLUSION

Dopaminergic genes seem to contribute to tardive dyskinesia and cognition warranting replication.

Influence of Genetic Variation in COMT on Cisplatin-Induced Nephrotoxicity in Cancer Patients

Cisplatin is a chemotherapeutic agent widely used for multiple indications. Unfortunately, in a substantial set of patients treated with cisplatin, dose-limiting acute kidney injury (AKI) occurs. Here, we assessed the association of 3 catechol-O-methyltransferase (COMT) single nucleotide polymorphisms (SNPs) with increased cisplatin-induced nephrotoxicity. In total, 551 patients were genotyped for the 1947 G>A (Val158Met, rs4680), c.615 + 310 C>T (rs4646316), and c.616–367 C>T (rs9332377) polymorphisms. Associations between these variants and AKI grade ≥3 were studied. The presence of a homozygous variant of c.616-367C>T was associated with a decreased occurrence of AKI grade 3 toxicity (p = 0.014, odds ratio (OR) 0.201, 95% confidence interval (CI) (0.047–0.861)). However, we could not exclude the role of dehydration as a potential cause of AKI in 25 of the 27 patients with AKI grade 3, which potentially affected the results substantially. As a result of the low incidence of AKI grade 3 in this dataset, the lack of patients with a COMT variant, and the high number of patients with dehydration, the association between COMT variants and AKI does not seem clinically relevant.

Reveals of New Candidate Active Components in Hemerocallis Radix and Its Anti-Depression Action of Mechanism Based on Network Pharmacology Approach

The global depression population is showing a significant increase. Hemerocallis fulva L. is a common Traditional Chinese Medicine (TCM). Its flower buds are known to have ability to clear away heat and dampness, detoxify, and relieve depression. Ancient TCM literature shows that its roots have a beneficial effect in calming the spirit and even the temper in order to reduce the feeling of melancholy. Therefore, it is inferred that the root of Hemerocallis fulva L. can be used as a therapeutic medicine for depression. This study aims to uncover the pharmacological mechanism of the antidepressant effect of Hemerocallis Radix (HR) through network pharmacology method. During the analysis, 11 active components were obtained and screened using ADME—absorption, distribution, metabolism, and excretion— method. Furthermore, 267 HR targets and 740 depressive disorder (DD) targets were gathered from various databases. Then protein–protein interaction (PPI) network of HR and DD targets were constructed and cluster analysis was applied to further explore the connection between the targets. In addition, gene ontology (GO) enrichment and pathway analysis was applied to further verify that the biological process related to the target protein is associated with the occurrence of depression disorder. In conclusion, the most important bioactive components—anthraquinone, kaempferol, and vanillic acid—can alleviate depression symptoms by regulating MAOA, MAOB, and ESR1. The proposed network pharmacology strategy provides an integrating method to explore the therapeutic mechanism of multi-component drugs on a systematic level.

Review of the Neural Processes of Working Memory Training: Controlling the Impulse to Throw the Baby Out With the Bathwater

BACKGROUND

Smartphone technology has enabled the creation of many working memory training (WMT) Apps, with those peer-reviewed described in a recent review. WMT claims to improve working memory, attention deficits, hyperactivity and fluid intelligence, in line with plasticity brain changes. Critics argue that WMT is unable to achieve "far-transfer"-the attainment of benefits to cognition from one taught context to another dissimilar context-associated with improved quality of life. However, brain changes after a course of WMT in frontoparietal and striatal circuits-that often occur prior to behavioral changes-may be a better indicator of far-transfer efficacy, especially to improve impulse control commonly dysregulated in those with addictive disorders, yet not commonly examined in WMT studies.

METHOD

In contrast to previous reviews, the aim here is to focus on the findings of brain imaging WMT training studies across various imaging modalities that use various paradigms, published via PubMed, Scopus, Medline, and Google Scholar.

RESULTS

35 brain imaging studies utilized fMRI, structural imaging (MRI, DTI), functional connectivity, EEG, transcranial direct current stimulation (tDCS), cerebral perfusion, and neurogenetic analyses with tasks based on visuospatial and auditory working memory, dual and standard n-back.

DISCUSSION

Evidence suggests that repeated WMT reduces brain activation in frontoparietal and striatal networks reflective of increased neural circuitry efficiency via myelination and functional connectivity changes. Neural effects of WMT may persist months after training has ended, lead to non-trained task transfer, be strengthened by auxiliary methods such as tDCS and be related to COMT polymorphisms. WMT could be utilized as an effective, non-invasive intervention for working memory deficits to treat impulse and affective control problems in people with addictive disorders.

Analysis of the Deleterious Single-Nucleotide Polymorphisms Associated With Antidepressant Efficacy in Major Depressive Disorder

Major depressive disorder (MDD) is a serious mental disease with negative effects on both mental and physical health of the patient. Currently, antidepressants are among the major ways to ease or treat MDD. However, the existing antidepressants have limited efficacy in treating MDD, with a large fraction of patients either responding inadequately or differently to antidepressants during the treatment. Pharmacogenetics studies have found that the genetic features of some genes are associated with the antidepressant efficacy. In order to obtain a better understanding on the relationship between the genetic factors and antidepressant treatment response, we compiled a list of 233 single-nucleotide polymorphisms (SNPs) significantly associated with the antidepressant efficacy in treating MDD. Of the 13 non-synonymous SNPs in the list, three (rs1065852, rs3810651, and rs117986340) may influence the structures and function of the corresponding proteins. Besides, the influence of rs1065852 on the structure of CYP2D6 was further investigated via molecular dynamics simulations. Our results showed that compared to the native CYP2D6 the flexibility of the F-G loop was reduced in the mutant. As a portion of the substrate access channel, the lower flexibility of F-G loop may reduce the ability of the substrates to enter the channel, which may be the reason for the lower enzyme activity of mutant. This study may help us to understand the impact of genetic variation on antidepressant efficacy and provide clues for developing new antidepressants.

The potential impact of COMT gene variants on dopamine regulation and phenotypic traits of ASD patients

Catechol-O-methyltransferase (COMT) enzyme has a major role in the adjustment of catechol-dependent functions, for example, cognition, cardiac function, and pain processing. The pathogenesis of autism may be related to dysfunction in the midbrain dopaminergic system. Therefore, we aimed to clarify how COMT gene variants affect dopamine level, and its potential impact on phenotype traits of autistic patients. 52 autistic patients were subjected to comprehensive clinical investigation, sequencing of exon 4 of the COMT gene by direct Sanger Sequencing, and measuring of dopamine levels. The clinical presentations of autistic subjects were correlated with detected COMT variants and dopamine level. Our molecular results revealed that three COMT variants were found: rs8192488 [C > T], rs4680 (Val158Met) and rs4818 [C > G]. Within autistic subjects, Val158Met rs4680 carriers were significantly distributed (71.2% P = 0.014) accompanied with abnormal dopamine, abnormal Electroencephalogram (EEG) and increasing the severity of autistic behaviour. As regards the haplotypes, CC/VM/CG block was significantly distributed among the autistic subjects (30.8%) presented with low mean dopamine level (15.8 ± 4.7 pg/ml, p = 0.05), while CC/MM/CC were presented with high mean level (77.8 ± 8.6 pg/ml, p = 0.05). Evidence is currently limited and preliminary, further studies are necessary in order to set up a coherent dopaminergic model of Autism Spectrum Disorder (ASD), which would further pave the way for an adequate treatment.

Chronic Systemic Symptoms in Head and Neck Cancer Patients

The systemic effects and manifestations of disease and treatment have been of interest for millennium. Until recently, basic and clinical research is just now reaching a watershed. Systemic symptoms usually do not occur in isolation but rather in clusters; however, much of the cutting-edge research pertaining to the etiology, mechanism, manifestations, and moderators of systemic symptoms in humans has been directed at individual symptoms, thus creating silos of knowledge. Breaching these silos and bridging the knowledge from disparate arenas of investigation to build a comprehensive depiction of acute and chronic systemic symptoms has been a challenge. In addition, much of the recent work in systemic symptoms has been conducted in the setting of nonmalignant disease. The degree to which the findings from other chronic disease processes can be translated into the oncologic realm is unknown. This article will explore inflammation as a major contributing factor to systemic symptoms and sickness behavior, discuss the most common manifestations in cancer survivors, and, where available, discuss specific data pertaining to head and neck cancer survivors.

A panel of miRNAs is involved in the effect of sertraline on panic disorder, as implicated by a microarray-based analysis

BACKGROUND

MiRNAs are considered to be significant contributors to the pathogenesis of psychiatric diseases, but little is known about the potential roles of miRNAs in the treatment effect of panic disorder (PD). Therefore, we aimed to identify the miRNAs association with PD over the course of sertraline treatment.

METHODS

Sixty-seven patients were collected for a 6-week period of sertraline treatment, and evaluated using HAMD-17, HAMA-14 and PDSS both at the baseline and 6 weeks later. Blood samples were collected before and after treatment, respectively. Ten pairs of samples were analyzed using miRNA array, and the differentially expressed miRNAs were further validated using RT-PCR in the whole sample.

RESULTS

miR-451a, miR-144-5p, miR-25-3p and miR-660-5p were found to be significantly up-regulated, while miR-1 and miR-148-5p significantly down-regulated after sertraline treatment. The change of miR-25-3p before and after treatment (△miR-25-3p) was positively related to both the changes of PDSS3 scores (△PDSS3) (p = 0.017, 31.5% contribution) and △ PDSS7 (p = 0.016, 32.3% contribution). The △miR-660-5p was positively related to both the △HAMA5 (p = 0.03, 26% contribution) and △PDSS7 (p = 0.032). The △miR-148-5p was positively related to the △PDSS4 (p = 0.046, 21.5% contribution), but negatively related to the △HAMA13 (p = 0.005, 41.9% contribution). The △miR-144-5p was negatively related to the △HAMA9 (p = 0.032, 25.3% contribution).

CONCLUSIONS

These findings might provide some evidences to the involvement of miRNA in the effect of anti-anxiety agents, which contributed to the better understanding the disease and developing new therapeutic genetic targets.

Estimating patient-specific treatment advantages in the 'Treatment for Adolescents with Depression Study'

The 'Treatment for Adolescents with Depression Study' (TADS, ClinicalTrials.gov, identifier: NCT00006286) was a cornerstone, randomized controlled trial evaluating the effectiveness of standard treatment options for major depression in adolescents. Whereas previous TADS analyses examined primarily effect modifications of treatment-placebo differences by various patient characteristics, less is known about the modification of inter-treatment differences, and hence, patient characteristics that might guide treatment selection. We sought to fill this gap by estimating patient-specific inter-treatment differences as a function of patients' baseline characteristics. We did so by applying the 'model-based random forest', a recently-introduced machine learning-based method for evaluating effect heterogeneity that allows for the estimation of patient-specific treatment effects as a function of arbitrary baseline characteristics. Treatment conditions were cognitive-behavioural therapy (CBT) alone, fluoxetine (FLX) alone, and the combination of CBT and fluoxetine (COMB). All inter-treatment differences (CBT vs. FLX; CBT vs. COMB; FLX vs. COMB) were evaluated across 23 potential effect modifiers extracted from previous studies. Overall, FLX was superior to CBT, while COMB was superior to both CBT and FLX. Evidence for effect heterogeneity was found for the CBT-FLX difference and the FLX-COMB difference, but not for the CBT-COMB difference. Baseline depression severity modified the CBT-FLX difference; whereas baseline depression severity, patients' treatment expectations, and childhood trauma modified the FLX-COMB difference. All modifications were quantitative rather than qualitative, however, meaning that the differences varied only in magnitude, but not direction. These findings imply that combining CBT with fluoxetine may be superior to either therapy used alone across a broad range of patients.

Further Support for the Involvement of Genetic Variants Related to the Serotonergic Pathway in the Antidepressant Response in Children and Adolescents After a 12-Month Follow-Up: Impact of the HTR2A rs7997012 Polymorphism

Objective: Fluoxetine is an effective and well-tolerated pharmacological treatment for children and adolescents with major depressive disorder (MDD). However, a high percentage of patients do not respond. There is a substantial genetic contribution to this variable clinical outcome. Based on previous genetic results of our group and given the lack of pharmacogenetics studies of antidepressant response with a long follow-up period, we evaluated the influence of single nucleotide polymorphisms (SNPs) in genes related to the serotonergic pathway on remission and recovery in children and adolescents diagnosed with MDD after 12 months of initiating fluoxetine treatment. Methods: The assessment was performed in 46 patients. All of them were visited at least once a month during the 12-month follow-up. Psychiatrists interviewed patients and their parents to explore clinical improvement. A total of 75 genotyped SNPs in 10 candidate genes were included in the genetic association analysis with remission and recovery. Bonferroni correction for multiple testing was applied to avoid false positive results. Results: The HTR2A rs7997012 SNP was significantly associated after Bonferroni correction with clinical improvement. Particularly, the homozygotes for the major allele (GG) showed the highest percentage of remitters and the highest score reductions on the Clinical Global Impressions-Severity (CGI-S) scale. Moreover, although the results were on the border of statistical significance, the GG homozygotes also tended to experience fewer readmissions during the follow-up period Conclusions: These results provide more evidence of the involvement of genetic variants related to the serotonergic pathway in the antidepressant response. Studies with larger cohorts are needed to integrate all relevant variants into clinical predictors of antidepressant response.

Clinical Implementation of Pharmacogenetic Decision Support Tools for Antidepressant Drug Prescribing

The accrual and analysis of genomic sequencing data have identified specific genetic variants that are associated with major depressive disorder. Moreover, substantial investigations have been devoted to identifying gene-drug interactions that affect the response to antidepressant medications by modulating their pharmacokinetic or pharmacodynamic properties. Despite these advances, individual responses to antidepressants, as well as the unpredictability of adverse side effects, leave clinicians with an imprecise prescribing strategy that often relies on trial and error. These limitations have spawned several combinatorial pharmacogenetic testing products that are marketed to physicians. Typically, combinatorial pharmacogenetic decision support tools use algorithms to integrate multiple genetic variants and assemble the results into an easily interpretable report to guide prescribing of antidepressants and other psychotropic medications. The authors review the evidence base for several combinatorial pharmacogenetic decision support tools whose potential utility has been evaluated in clinical settings. They find that, at present, there are insufficient data to support the widespread use of combinatorial pharmacogenetic testing in clinical practice, although there are clinical situations in which the technology may be informative, particularly in predicting side effects.

The relationship between the serotonin 2A receptor gene -1438A/G and 102T/C polymorphisms and citalopram/sertraline-induced nausea in major depressed patients

OBJECTIVE

The aim of the present study was to determine the relationship between the polymorphisms of -1438A/G and 102T/C in the 5-HT2A receptor (HTR2A) gene and nausea/vomiting as a side effect induced by sertraline (SERT) or citalopram (CIT) in patients with major depressive disorder.

METHODS

A total of 128 patients were enrolled, 63 patients received CIT, whereas 65 patients were treated with SERT. Nausea/vomiting were assessed with the UKU Side-effects Rating Scale at baseline and at the end of the second and fourth weeks. Polymerase chain reaction-restriction fragment length polymorphism technique was employed to determine genetic differences.

RESULTS

We have found that, in the patients treated with CIT, there was a nominally significant difference in the genotypic distribution associated with -1438A/G polymorphism between patients with and without nausea (X²  = 6.15, p = 0.041). Moreover, logistic regression analysis revealed a significant association between nausea/vomiting as a side effect and -1438A/G polymorphism. That is, patients with the G allele were at a higher risk for developing nausea/vomiting (p = 0.044, odds ratio = 2.213). The 102T/C polymorphism in the HTR2A gene had no significant effect on the nausea/vomiting as a side effect among participants treated with either CIT or SERT.

CONCLUSION

The present study suggests the association of the HTR2A gene -1438A/G polymorphism with nausea/vomiting as a side effect related to CIT treatment.

Progress in Elucidating Biomarkers of Antidepressant Pharmacological Treatment Response: A Systematic Review and Meta-analysis of the Last 15 Years

BACKGROUND

Antidepressant drugs are widely prescribed, but response rates after 3 months are only around one-third, explaining the importance of the search of objectively measurable markers predicting positive treatment response. These markers are being developed in different fields, with different techniques, sample sizes, costs, and efficiency. It is therefore difficult to know which ones are the most promising.

OBJECTIVE

Our purpose was to compute comparable (i.e., standardized) effect sizes, at study level but also at marker level, in order to conclude on the efficacy of each technique used and all analyzed markers.

METHODS

We conducted a systematic search on the PubMed database to gather all articles published since 2000 using objectively measurable markers to predict antidepressant response from five domains, namely cognition, electrophysiology, imaging, genetics, and transcriptomics/proteomics/epigenetics. A manual screening of the abstracts and the reference lists of these articles completed the search process.

RESULTS

Executive functioning, theta activity in the rostral Anterior Cingular Cortex (rACC), and polysomnographic sleep measures could be considered as belonging to the best objectively measured markers, with a combined d around 1 and at least four positive studies. For inter-category comparisons, the approaches that showed the highest effect sizes are, in descending order, imaging (combined d between 0.703 and 1.353), electrophysiology (0.294-1.138), cognition (0.929-1.022), proteins/nucleotides (0.520-1.18), and genetics (0.021-0.515).

CONCLUSION

Markers of antidepressant treatment outcome are numerous, but with a discrepant level of accuracy. Many biomarkers and cognitions have sufficient predictive value (d ≥ 1) to be potentially useful for clinicians to predict outcome and personalize antidepressant treatment.

Blood-based biomarkers predicting response to antidepressants

Major depressive disorder is a common, serious and in some cases, life-threatening condition and affects approximately 350 million people globally. Although there is effective treatment available for it, more than 50% of the patients fail to respond to the first antidepressant they receive. The selection of a distinct treatment is still exclusively based on clinical judgment without incorporating lab-derived objective measures. However, there is growing evidence of biomarkers that it helps to improve diagnostic processes and treatment algorithms. Here genetic markers and blood-based biomarkers of the monoamine pathways, inflammatory pathways and the hypothalamic-pituitary-adrenal (HPA) axis are reviewed. Promising findings arise from studies investigating inflammatory pathways and immune markers that may identify patients suitable for anti-inflammatory based treatment regimes. Next, an early normalization of a disturbed HPA axis or depleted neurotrophic factors may predict stable treatment response. Genetic markers within the serotonergic system may identify patients who are vulnerable because of stressful life events, but evidence for guiding treatment regimes still is inconsistent. Therefore, there is still a great need for studies investigating and validating biomarkers for the prediction of treatment response to facilitate the treatment selection and shorten the time to remission and thus provide personalized medicine in psychiatry.

Pharmacogenomics and Biomarkers of Depression

The standard of care for antidepressant treatment in major depressive disorder (MDD) is a trial-and-error approach. Patients often have to undergo multiple medication trials for weeks to months before finding an effective treatment. Clinical factors such as severity of baseline symptoms and the presence of specific individual (anhedonia or insomnia) or cluster (atypical, melancholic, or anxious) of symptoms are commonly used without any evidence of their utility in selecting among currently available antidepressants. Genomic and proteomic biomarker have gained recent attention for their potential in informing antidepressant medication selection. In this report, we have reviewed some of the major pharmacogenomics studies along with individual genetic and proteomic biomarker of antidepressant response. Additionally, we have reviewed the blood-based protein biomarkers that can inform selection of one antidepressant over another. Among all currently available biomarkers, C-reactive protein (CRP) appears to be the most promising and pragmatic choice. Low CRP (<1 mg/L) in patients with MDD predicts better response to escitalopram while higher levels are associated with better response to noradrenergic/dopaminergic antidepressants. Future studies are needed to demonstrate the superiority of a CRP-based treatment assignment over high-quality measurement-based care in real-world clinical practices.

Improved efficacy with targeted pharmacogenetic-guided treatment of patients with depression and anxiety: A randomized clinical trial demonstrating clinical utility

The objective of this study was to evaluate the effect of pharmacogenetics-guided treatment on patients diagnosed with depression and/or anxiety, in a diverse set of clinical settings, as compared to the standard of care. The trial design followed a prospective, randomized, subject- and rater-blinded approach enrolling 685 patients from clinical providers specializing in Psychiatry, Internal Medicine, Obstetrics & Gynecology, and Family Medicine. The NeuroIDgenetix^® test uses a genetic variant panel of ten genes, along with concomitant medications, to make medication management recommendations based on gene-drug and drug-drug interactions for over 40 medications used in the treatment of depression and anxiety. Pharmacogenetic testing was performed at the initial screening visit and baseline patient assessments were determined using the 17-item Hamilton Rating Scale for Depression (HAM-D17) and the Hamilton Rating Scale for Anxiety (HAM-A). Following enrollment and randomization, pharmacogenetic results for subjects assigned to the experimental group were provided to physicians to guide treatment selection, while control subjects were treated according to the usual standard of care. HAM-D17 and HAM-A assessments were collected at 4 weeks, 8 weeks, and 12 weeks after baseline to assess the efficacy of therapeutic selection. In patients diagnosed with depression, response rates (p = 0.001; OR: 4.72 [1.93-11.52]) and remission rates (p = 0.02; OR: 3.54 [1.27-9.88]) were significantly higher in the pharmacogenetics-guided group as compared to the control group at 12 weeks. In addition, patients in the experimental group diagnosed with anxiety showed a meaningful improvement in HAM-A scores at both 8 and 12 weeks (p = 0.02 and 0.02, respectively), along with higher response rates (p = 0.04; OR: 1.76 [1.03-2.99]). From these results, we conclude that pharmacogenetic-guided medication selection significantly improves outcomes of patients diagnosed with depression or anxiety, in a variety of healthcare settings.

Optimization of Antidepressant use with Pharmacogenetic Strategies

BACKGROUND

The response rate in the pharmacological treatment of depression has been estimated to be around 50%, achieving a remission in symptomatology in only one third of the patients. Suboptimal prescription of antidepressants has been proposed as a significant explanatory factor for this therapeutic inefficacy. The use of pharmacogenetic testing might favor the optimization of pharmacotherapy in emotional disorders. However, its implementation in the clinical routine requires studies which prove its efficacy.

OBJECTIVE

The aim is to explore the clinical effects obtained by means of the personalization of antidepressant treatment derived from the pharmacogenetic profile of the individual.

METHOD

A sample of 291 patients under antidepressant treatment was selected, and these patients were genotyped for the most common polymorphisms of the CYP2D6, CYP2C9, CYP2C19 and CYP3A4/5 genes using RT-PCR and TaqMan® technology. 30 of them were subjected to psycho-affective assessment using the HDRS scale before and after a process of individualization of their psychopharmacological treatment in accordance with the genotype obtained.

RESULTS

70% of the individuals treated using the traditional criterion of trial-and-error were not taking the active ingredient most suited to their pharmacogenetic profile. The inclusion of this genetic information in the choice of drug and its dosage entailed a significant, progressive reduction in depressive symptomatology, with an efficacy ratio of 80% and a remission of the pathology in almost 30% of the cases.

CONCLUSION

These results suggest that the prescription of pharmacogenetic profile-based strategies has a positive effect on the therapeutic response to antidepressants.

Integrating evolutionary and regulatory information with a multispecies approach implicates genes and pathways in obsessive-compulsive disorder

Obsessive-compulsive disorder is a severe psychiatric disorder linked to abnormalities in glutamate signaling and the cortico-striatal circuit. We sequenced coding and regulatory elements for 608 genes potentially involved in obsessive-compulsive disorder in human, dog, and mouse. Using a new method that prioritizes likely functional variants, we compared 592 cases to 560 controls and found four strongly associated genes, validated in a larger cohort. NRXN1 and HTR2A are enriched for coding variants altering postsynaptic protein-binding domains. CTTNBP2 (synapse maintenance) and REEP3 (vesicle trafficking) are enriched for regulatory variants, of which at least six (35%) alter transcription factor-DNA binding in neuroblastoma cells. NRXN1 achieves genome-wide significance (p = 6.37 × 10⁻¹¹) when we include 33,370 population-matched controls. Our findings suggest synaptic adhesion as a key component in compulsive behaviors, and show that targeted sequencing plus functional annotation can identify potentially causative variants, even when genomic data are limited.

Obsessive-compulsive disorder (OCD) is a neuropsychiatric disorder with symptoms including intrusive thoughts and time-consuming repetitive behaviors. Here Noh and colleagues identify genes enriched for functional variants associated with increased risk of OCD.

Toward a multiscale modeling framework for understanding serotonergic function

Despite its importance in regulating emotion and mental wellbeing, the complex structure and function of the serotonergic system present formidable challenges toward understanding its mechanisms. In this paper, we review studies investigating the interactions between serotonergic and related brain systems and their behavior at multiple scales, with a focus on biologically-based computational modeling. We first discuss serotonergic intracellular signaling and neuronal excitability, followed by neuronal circuit and systems levels. At each level of organization, we will discuss the experimental work accompanied by related computational modeling work. We then suggest that a multiscale modeling approach that integrates the various levels of neurobiological organization could potentially transform the way we understand the complex functions associated with serotonin.

Escitalopram plasma levels and antidepressant response

Major Depression Disorder (MDD) has a highly variable treatment response due to the large inter-individual variation in the pharmacokinetics and pharmacodynamics of drug treatments. In detail the correlation between plasma level and efficacy has been much debated. Among first-line drugs for MDD, one of the most used is escitalopram. In the present study we investigated the association between serum concentration of escitalopram (SCE) and antidepressant response (AR). 70 MDD patients treated with escitalopram monotherapy were recruited and followed for three months. Hamilton Depression Rating Scale - 21 (HAMD-21) was administrated at baseline, month 1, and month 3 to assess AR. SCE was measured at steady state. Linear regression analysis and nonlinear least-squares regression were used to estimate association between SCE and AR. We found an association between SCE and AR both at month 1 (p<0.001) and month 3 (p=0.0003), which persists also excluding 3 patients with SCE equal to 0. Interestingly, by excluding patients with SCE < 20ng/mL, i.e. with a SCE lower than the putative therapeutic threshold, these associations disappeared. The curvilinear function AR = a + (SCE-SCE²) explained a higher proportion of variance compared to the linear other models (p<0.001). Our results suggest that for escitalopram the association between SCE and AR likely follows a nearly-asymptotic function, with poor AR at sub-therapeutic SCE and stable AR response at therapeutic SCE. Thus, when a patient reaches the therapeutic SCE range, further increase of escitalopram dosage seems to be useless, although further studies are needed to confirm our findings.

Optimization of Antidepressant use with Pharmacogenetic Strategies

Background:

The response rate in the pharmacological treatment of depression has been estimated to be around 50%, achieving a remission in symptomatology in only one third of the patients. Suboptimal prescription of antidepressants has been proposed as a significant explanatory factor for this therapeutic inefficacy. The use of pharmacogenetic testing might favor the optimization of pharmacotherapy in emotional disorders. However, its implementation in the clinical routine requires studies which prove its efficacy.

Objective:

The aim is to explore the clinical effects obtained by means of the personalization of antidepressant treatment derived from the pharmacogenetic profile of the individual.

Method:

A sample of 291 patients under antidepressant treatment was selected, and these patients were genotyped for the most common polymorphisms of the CYP2D6, CYP2C9, CYP2C19 and CYP3A4/5 genes using RT-PCR and TaqMan® technology. 30 of them were subjected to psycho-affective assessment using the HDRS scale before and after a process of individualization of their psychopharmacological treatment in accordance with the genotype obtained.

Results:

70% of the individuals treated using the traditional criterion of trial-and-error were not taking the active ingredient most suited to their pharmacogenetic profile. The inclusion of this genetic information in the choice of drug and its dosage entailed a significant, progressive reduction in depressive symptomatology, with an efficacy ratio of 80% and a remission of the pathology in almost 30% of the cases.

Conclusion:

These results suggest that the prescription of pharmacogenetic profile-based strategies has a positive effect on the therapeutic response to antidepressants.

Association of regulatory TPH2 polymorphisms with higher reduction in depressive symptoms in children and adolescents treated with fluoxetine

Genetic variability related to the brain serotonergic system has a significant impact on both the susceptibility to psychiatric disorders, such as major depressive disorder (MDD), and the response to antidepressant drugs, such as fluoxetine. TPH2 is one of the most important serotonergic candidate genes in selective serotonin reuptake inhibitors (SSRIs) pharmacogenetic studies. The aim of the present study was to evaluate the influence of regulatory polymorphisms that are specifically located in human TPH2 transcription factor binding sites (TFBSs), and therefore could be functional by altering gene expression, on clinical improvement in children and adolescents treated with fluoxetine. The selection of SNPs was also based on their linkage disequilibrium with TPH2 rs4570625, a genetic variant with questionable functionality, which was previously associated with clinical response in our pediatric population. A total of 83 children and adolescents were clinically evaluated 12weeks after initiating antidepressant treatment with fluoxetine for the first time. Clinical improvement was assessed by reductions in depressive symptoms measured using the Children's Depression Inventory (CDI) scale. The polymorphisms rs11179002, rs60032326 and rs34517220 were, for the first time in the literature, significantly associated with higher clinical improvement. The strongest association was found for rs34517220. In particular, minor allele homozygotes showed higher score reductions on the CDI scale compared with the major allele carriers. Interestingly, this polymorphism is located in a human TPH2 TFBS for two relevant transcription factors in the serotoninergic neurons, Foxa1 and Foxa2, which together with the high level of significance found for this SNP, could indicate that rs34517220 is in fact the crucial functional genetic variant related to the fluoxetine response. These results provide new evidence for the role of regulatory genetic variants that could modulate human TPH2 expression in the SSRI antidepressant response.

The influence of the rs6295 gene polymorphism on serotonin-1A receptor distribution investigated with PET in patients with major depression applying machine learning

Major depressive disorder (MDD) is the most common neuropsychiatric disease and despite extensive research, its genetic substrate is still not sufficiently understood. The common polymorphism rs6295 of the serotonin-1A receptor gene (HTR1A) is affecting the transcriptional regulation of the 5-HT_1A receptor and has been closely linked to MDD. Here, we used positron emission tomography (PET) exploiting advances in data mining and statistics by using machine learning in 62 healthy subjects and 19 patients with MDD, which were scanned with PET using the radioligand [carbonyl-¹¹C]WAY-100635. All the subjects were genotyped for rs6295 and genotype was grouped in GG vs C allele carriers. Mixed model was applied in a ROI-based (region of interest) approach. ROI binding potential (BP_ND) was divided by dorsal raphe BP_ND as a specific measure to highlight rs6295 effects (BP_Div). Mixed model produced an interaction effect of ROI and genotype in the patients' group but no effects in healthy controls. Differences of BP_Div was demonstrated in seven ROIs; parahippocampus, hippocampus, fusiform gyrus, gyrus rectus, supplementary motor area, inferior frontal occipital gyrus and lingual gyrus. For classification of genotype, 'RandomForest' and Support Vector Machines were used, however, no model with sufficient predictive capability could be computed. Our results are in line with preclinical data, mouse model knockout studies as well as previous clinical analyses, demonstrating the two-pronged effect of the G allele on 5-HT_1A BP_ND for, we believe, the first time. Future endeavors should address epigenetic effects and allosteric heteroreceptor complexes. Replication in larger samples of MDD patients is necessary to substantiate our findings.

Proposal for a Pharmacogenetic Decision Algorithm

Personalized medicine is playing an ever-increasing role in patient care. Over the past decade, awareness of the role of pharmacogenetics and its benefits is leading to its growing acceptance among providers. Though providers are using pharmacogenetics in practice, the decision-making process of when to use this tool can be ambiguous. Herein, we propose an algorithm to help guide providers on when to use pharmacogenetics for patient care.

Pharmacogenetic studies: a tool to improve antidepressant therapy

The World Health Organization (WHO) predicts that major depressive disorder (MDD) will be the second leading cause of death and disability by 2020. Nowadays, approximately 60-70% of patients with this disorder have shown the lack of effectiveness and tolerability of the therapy with antidepressants. The US Food and Drug Administration (FDA) and the European Medicine Agency (EMA) are including pharmacogenetic information in the labeling of several antidepressants. The presence of this information represents the relevance of genetic polymorphisms in drug response. These pharmacogenetic studies have been based on the knowledge of genes involved in pharmacokinetic (CYP2D6, CYP2C19 and ABCB1) and pharmacodynamic (SLC6A4, HTR2A, BDNF, GNB3 and FKBP5) processes of antidepressant medications. The knowledge of the genotype of patients with MDD is an important tool for personalized therapy that can improve their clinical response to treatment. In this review, we highlight the most relevant genes involved in the metabolism of antidepressants (ADs) or the genes related to the presence of adverse reactions.