The Present and Future of Precision Medicine in Psychiatry: Focus on Clinical Psychopharmacology of Antidepressants

Machine learning for antidepressant treatment selection in depression

Finding the right antidepressant for the individual patient with major depressive disorder can be a difficult endeavor and is mostly based on trial-and-error. Machine learning (ML) is a promising tool to personalize antidepressant prescription. In this review, we summarize the current evidence of ML in the selection of antidepressants and conclude that its value for clinical practice is still limited. Apart from the current focus on effectiveness, several other factors should be taken into account to make ML-based prediction models useful for clinical application.

A Critical View on New and Future Antidepressants

For the first time after many decades, many new antidepressants have been approved and many more are under various stages of development and will soon be available in the market. The new drugs present a range of new mechanisms of action with benefits in terms of speed of action, tolerability and range of treatable disorders. Neurosteroids have been recently approved and their rapid benefit may extend from postpartum depression to anxious depression and bipolar depression, dextromethorphan and bupropion combination may prove useful in major depression but also in treatment resistant depression, dextromethadone is a possible augmentation in partial antidepressant response, psychedelic drugs have the potential of long lasting benefits after a single administration, though are still experimental treatments. Botulinum has the same advantage of psychedelics of a single administration and its antidepressant effects may last for weeks or more. Further potentially interesting new antidepressant mechanisms include new drug targets, drug repurposing and genetic or epigenetic manipulations. It is therefore important that clinicians are kept up to date with new evidence so that new evidence can be rapidly translated into clinical practice.

The bidirectional interaction between antidepressants and the gut microbiota: are there implications for treatment response?

This review synthesizes the evidence on associations between antidepressant use and gut microbiota composition and function, exploring the microbiota's possible role in modulating antidepressant treatment outcomes. Antidepressants exert an influence on measures of gut microbial diversity. The most consistently reported differences were in β-diversity between those exposed to antidepressants and those not exposed, with longitudinal studies supporting a potential causal association. Compositional alterations in antidepressant users include an increase in the Bacteroidetes phylum, Christensenellaceae family, and Bacteroides and Clostridium genera, while a decrease was found in the Firmicutes phylum, Ruminococcaceae family, and Ruminococcus genus. In addition, antidepressants attenuate gut microbial differences between depressed and healthy individuals, modulate microbial serotonin transport, and influence microbiota's metabolic functions. These include lyxose degradation, peptidoglycan maturation, membrane transport, and methylerythritol phosphate pathways, alongside gamma-aminobutyric acid metabolism. Importantly, baseline increased α-diversity and abundance of the Roseburia and Faecalibacterium genera, in the Firmicutes phylum, are associated with antidepressant response, emerging as promising biomarkers. This review highlights the potential for gut microbiota as a predictor of treatment response and emphasizes the need for further research to elucidate the mechanisms underlying antidepressant-microbiota interactions. More homogeneous studies and standardized techniques are required to confirm these initial findings.

A cultural-ecosocial systems view for psychiatry

While contemporary psychiatry seeks the mechanisms of mental disorders in neurobiology, mental health problems clearly depend on developmental processes of learning and adaptation through ongoing interactions with the social environment. Symptoms or disorders emerge in specific social contexts and involve predicaments that cannot be fully characterized in terms of brain function but require a larger social-ecological view. Causal processes that result in mental health problems can begin anywhere within the extended system of body-person-environment. In particular, individuals' narrative self-construal, culturally mediated interpretations of symptoms and coping strategies as well as the responses of others in the social world contribute to the mechanisms of mental disorders, illness experience, and recovery. In this paper, we outline the conceptual basis and practical implications of a hierarchical ecosocial systems view for an integrative approach to psychiatric theory and practice. The cultural-ecosocial systems view we propose understands mind, brain and person as situated in the social world and as constituted by cultural and self-reflexive processes. This view can be incorporated into a pragmatic approach to clinical assessment and case formulation that characterizes mechanisms of pathology and identifies targets for intervention.

Real-world characteristics of European patients receiving SNRIs as first-line treatment for major depressive disorder

BACKGROUND

Serotonin-norepinephrine reuptake inhibitors (SNRIs) are among the most frequently prescribed antidepressants (ADs) for major depressive disorder (MDD), with an increasing trend in the last decade. Given the relative dearth of information regarding rationales for their preferred use as first-line ADs in the broad clinical routine, the present study systematically investigated real-world characteristics of MDD patients prescribed either SNRIs or other AD substances across different countries and treatment settings.

METHODS

In the present secondary analyses based on a large European, multi-site, naturalistic and cross-sectional investigation with a retrospective assessment of treatment outcome, we firstly defined the proportion of MDD patients receiving SNRIs as first-line AD psychopharmacotherapy and secondly compared their sociodemographic and clinical characteristics to those patients prescribed alternative first-line ADs during their current major depressive episode (MDE).

RESULTS

Within the total sample of 1410 MDD patients, 336 (23.8 %) received first-line SNRIs. Compared to other ADs, SNRIs were significantly associated with inpatient care, suicidality and treatment resistance during the current MDE, and a longer lifetime duration of psychiatric hospitalizations. Moreover, greater severity of depressive symptoms at study entry, higher daily doses of the administered ADs, as well as more frequent prescriptions of psychopharmacotherapeutic add-on strategies in general and antipsychotic augmentation in particular, were significantly related to first-line SNRIs.

CONCLUSIONS

Considering the limitations of a cross-sectional and retrospective study design, our data point towards a preferred use of first-line SNRIs in a generally more severely ill MDD patients, although they did not lead to superior treatment outcomes compared to alternative ADs.

Melancholic features and typical neurovegetative symptoms of major depressive disorder show specific polygenic patterns

BACKGROUND

Major depressive disorder (MDD) is a highly prevalent psychiatric condition characterised by a heterogeneous clinical presentation and an estimated twin-based heritability of ~40-50 %. Different clinical MDD subtypes might partly reflect distinctive underlying genetics. This study aims to investigate if polygenic risk scores (PRSs) for different psychiatric disorders, personality traits, and substance use-related traits may be associated with different clinical subtypes of MDD (i.e., MDD with melancholic or psychotic features), higher symptom severity, or different clusters of depressive symptoms (i.e., sadness symptoms, typical neurovegetative symptoms, detachment symptoms, and negative thoughts).

METHODS

The target sample included 1149 patients with MDD, recruited by the European Group for the Study of Resistant Depression. PRSs for 25 psychiatric disorders and traits were computed based on the most recent publicly available summary statistics of the largest genome-wide association studies. PRSs were then used as predictors in regression models, adjusting for age, sex, population stratification, and recruitment sites.

RESULTS

Patients with MDD having higher PRS for MDD and loneliness were more likely to exhibit melancholic features of MDD (p = 0.0009 and p = 0.005, respectively). Moreover, patients with higher PRS for alcohol intake and post-traumatic stress disorder were more likely to experience greater typical neurovegetative symptoms (p = 0.0012 and p = 0.0045, respectively).

LIMITATIONS

The proportion of phenotypic variance explained by the PRSs was limited.

CONCLUSIONS

This study suggests that melancholic features and typical neurovegetative symptoms of MDD may show distinctive underlying genetics. Our findings provide a new contribution to the understanding of the genetic heterogeneity of MDD.

Role of Pharmacogenomics in Comprehensive Medication Management: Considerations for Employers

Rising prescription costs, poor medication adherence, and safety issues pose persistent challenges to employer-sponsored health care plans and their beneficiaries. Comprehensive medication management (CMM), a patient-centered approach to medication optimization, enriched by pharmacogenomics (PGx), has been shown to improve the efficacy and safety of pharmaceutical regimens. This has contributed to improved health care outcomes, reduced costs of treatments, better adherence, shorter durations of treatment, and fewer adverse effects from drug therapy. Despite compelling clinical and economic evidence to justify the application of CMM guided by PGx, implementation in clinical settings remains sparse; notable barriers include limited physician adoption and health insurance coverage. Ultimately, these challenges may be overcome through comprehensive programs that include clinical decision support systems and education through employer-sponsored population health management channels to the benefit of the employees, employers, health care providers, and health care systems. This article discusses benefits, considerations, and barriers of scalable PGx-enriched CMM programs in the context of self-insured employers.

Glucocorticoid Receptor Gene (NR3C1) Expression in the Pathogenesis of Depression in Cancer

Background

This study aimed to compare the NR3C1 expression among cancer patients with major depressive disorder (cancer depression), cancer patients without major depressive disorder (cancer non-depression), and major depressive disorder patients without cancer (general depression), as a preliminary investigation of epigenetic changes in the glucocorticoid receptor gene.

Methods

From May 2019 to November 2019, patients were recruited from the Department of Psychiatry, Cancer Center in Busan, Korea. For gene expression studies, primers were designed using the Primer3 web tool (http://frodo.wi.mit.edu/primer3), and amplification reactions were performed.

Results

Expression levels of NR3C1 were lower in cancer depression and general depression than in cancer non-depression group. Given that we observed downregulation of the NR3C1 gene expression in depressive patients regardless of cancer status, it appears that methylation changes in NR3C1 may contribute to the pathophysiology of depression.

Conclusion

The results of this study imply that the expression of NR3C1 may be decreased in major depressive disorder.

Prediction of prognosis in patients with panic disorder using pre-treatment brain white matter features

BACKGROUND

The early identification of patients with panic disorder (PD) with a poor prognosis is important for improving treatment outcomes; however, it is challenging due to a lack of objective biomarkers. We investigated the reliability of characterizing structural white matter (WM) connectivity and its ability to predict PD prognosis after pharmacotherapy.

METHODS

A total of 138 patients (59 men) with PD and 153 healthy controls (HCs; 73 men) participated in this study. PD symptom severity was measured using the Panic Disorder Severity Scale (PDSS) at baseline and follow-up periods of 8 weeks, 6 months, and 1 year. The least absolute shrinkage and selection operator (Lasso) was utilized to identify prognosis-related WM regions on diffusion imaging features.

RESULTS

Lasso identified seven prognosis-related WM regions: the bilateral posterior corona radiata, bilateral posterior limb of the internal capsule, the left retrolenticular part of the internal capsule, the left sagittal stratum, and the right fornix/stria terminalis. Some of these regions showed lower mean fractional anisotropy (FA) values in patients with PD than in HCs. The predicted PDSS scores using FA from these regions consistently correlated with the actual prognosis in all periods.

LIMITATIONS

This study had limited ability to evaluate individual longitudinal changes in detail owing to the data acquisition time and brain atlas resolution.

CONCLUSIONS

Our findings suggest the possibility of using structural WM connectivity as a biomarker for the clinical characterization of PD. Our findings will expand our understanding of the neurobiology of PD and improve biomarker-based prognosis prediction in clinical practice.

Safety and Effectiveness of Desvenlafaxine in Korean Patients with Major Depressive Disorder: A 6-month Postmarketing Surveillance Study

Objective

Although the safety and efficacy of desvenlafaxine have been demonstrated, long-term evidence in Asians is lacking. We examined the safety and effectiveness of desvenlafaxine for up to 6 months in routine clinical practice in Korea.

Methods

This multicenter, open-label, prospective observational study was conducted from February 2014 to February 2020 as a postmarketing surveillance study of desvenlafaxine (ClinicalTrials.gov identifier NCT02548949). Adult patients with major depressive disorder (MDD) were observed from the initiation of treatment for 8 weeks (acute treatment phase) and then up to 6 months (continuation treatment phase) in a subsample. Safety was evaluated by incidence of adverse events (AE) and adverse drug reactions. Treatment response was assessed using the Clinical Global Impression- Improvement (CGI-I) scale.

Results

We included 700 and 236 study subjects in the analysis of acute and continuation treatment phase, respectively. In acute treatment phase, AE incidence was 9.86%, with nausea being most common (2.00%). In continuation treatment phase, AE incidence was 2.97%, with tremor occurring most frequently. After acute treatment (n = 464), the treatment response rate according to the CGI-I score at week 8 was 28.9%. In long-term users (n = 213), the response rate at month 6 was 45.5%. During the study period, no clinically relevant changes in BP were found regardless of concomitant use of antihypertensive drugs.

Conclusion

This study provides evidence on the safety and effectiveness of desvenlafaxine in adults with MDD, with a low incidence of AE, consistent AE profile with previous studies, and improved response after long-term treatment.

Psychopharmacology: past, present and future

The origin of modern psychopharmacology dates to the 50s, with the discovery of imipramine and chlorpromazine. At present, we can choose among over 100 different compounds, which are effective in many psychiatric disturbances but are far from perfect in terms of efficacy and tolerability. The main limitation of available treatments is their lack in specificity, both in terms of pharmacologic targets and regional brain specificity. Several new compounds with innovative mechanisms of action have been recently approved; however, pharmacologic treatments targeted for specific tissues are still not available. Recent imaging and genetic findings suggest that we may be close to discovering the regional pathophysiologic mechanisms of psychiatric disorders. Targeted treatment to specific proteins or even genes may be possible using monoclonal antibodies, RNA silencing, gene editing or drug repurposing. We may be therefore close to a shift of paradigm in the treatment of psychiatric disorders, with innovative and targeted treatments.

Precision medicine in mood disorders

The choice of the most appropriate psychoactive medication for each of our patients is always a challenge. We can use more than 100 psychoactive drugs in the treatment of mood disorders, which can be prescribed either alone or in combination. Response and tolerability problems are common, and much trial and error is often needed before achieving a satisfactory outcome. Precision medicine is therefore needed for tailoring treatment to optimize outcome. Pharmacological, clinical, and demographic factors are important and informative, but biological factors may further inform and refine prediction. Twenty years after the first reports of gene variants modulating antidepressant response, we are now confronted with the prospect of routine clinical pharmacogenetic applications in the treatment of depression. The scientific community is divided into two camps: those who are enthusiastic and those who are skeptical. Although it appears clear that the benefit of existing tools is still not completely defined, at least in the case of central nervous system gene variants, this is not the case for metabolic gene variants, which is generally accepted. Cumulative scores encompassing many variants across the entire genome will soon predict psychiatric disorder liability and outcome. At present, precision medicine in mood disorders may be implemented using clinical and pharmacokinetic factors. In the near future, a genome-wide composite genetic score in conjunction with clinical factors within each patient is the most promising approach for developing a more effective way to target treatment for patients suffering from mood disorders.

Temporal dynamics of affect in the brain: Evidence from human imaging and animal models

Emotions are time-varying internal states that promote survival in the face of dynamic environments and shifting homeostatic needs. Research in non-human organisms has recently afforded specific insights into the neural mechanisms that support the emergence, persistence, and decay of affective states. Concurrently, a separate affective neuroscience literature has begun to dissect the neural bases of affective dynamics in humans. However, the circuit-level mechanisms identified in animals lack a clear mapping to the human neuroscience literature. As a result, critical questions pertaining to the neural bases of affective dynamics in humans remain unanswered. To address these shortcomings, the present review integrates findings from humans and non-human organisms to highlight the neural mechanisms that govern the temporal features of emotional states. Using the theory of affective chronometry as an organizing framework, we describe the specific neural mechanisms and modulatory factors that arbitrate the rise-time, intensity, and duration of emotional states.

An overview of the molecular and physiological antidepressant mechanisms of physical exercise in animal models of depression

BACKGROUND

Depression is a global disease that affects the physical and mental health of people of all ages. Non-pharmacological and unconventional methods of treatment, such as regular physical exercise, have been recommended to treat depression.

METHODS

Here, we briefly review the literature about the physiological and molecular mechanisms of exercise antidepressants in depressive-like behavior in animal models of depression.

RESULTS

The main hysiological and molecular mechanisms of physical exercise in depression include blood flow changes in several areas of the brain, increase in brain serotonin synthesis, increase in antioxidant enzymes, increase in serum and brain brain-derived neuro factor (BDNF) levels, decrease in cortisol levels and reduced inflammation in peripheral and brain tissues. Physical exercise also leads to increased activation of the phosphatidylinositol-3-kinase (PI3K), PGC-1α/FNDC5/Irisin pathway, BDNF concentrations (serum and cerebral), extracellular signal-regulated kinase and cAMP-response element binding protein (mainly in neurons of the hippocampus and prefrontal cortex), which together contribute to fight or inhibit the development of depression symptoms. These molecular and physiological mechanisms work in synchrony, further enhancing their effects.

CONCLUSION

Physical exercise can be used as a safe and effective non-pharmacological treatment in depression.

Translational Informatics for Natural Products as Antidepressant Agents

Depression, a neurological disorder, is a universally common and debilitating illness where social and economic issues could also become one of its etiologic factors. From a global perspective, it is the fourth leading cause of long-term disability in human beings. For centuries, natural products have proven their true potential to combat various diseases and disorders, including depression and its associated ailments. Translational informatics applies informatics models at molecular, imaging, individual, and population levels to promote the translation of basic research to clinical applications. The present review summarizes natural-antidepressant-based translational informatics studies and addresses challenges and opportunities for future research in the field.

Patients' and psychiatrists' stance on the current state of pharmacological depression treatment in Serbia and prospects of introduction of personalized pharmacotherapy and its potential effects

The use of antidepressants has been steadily increasing. Even though the amount of evidence on the usefulness of personalized drug dosing in depression treatment is growing, there is still resistance and skepticism among physicians and regulators regarding the implementation of CYP450 genotyping and therapeutic drug monitoring in psychiatric clinical practice. The aim of this study was to quantify the opinions of psychiatrists and patients from three large psychiatric clinics in Belgrade, Serbia, and to examine what requirements need to be met to make changes in clinical guidelines or recommendations. All participants completed an anonymous questionnaire that was developed at the Faculty of Pharmacy, University of Belgrade. Fourteen practicing psychiatrists and 30 patients currently treated for depression completed the questionnaire. Distributions of opinion scores were compared between the psychiatrists and patients upon the visual inspection of the violin plots. Our results show that psychiatrists predominantly have a positive opinion on personalized dosing in psychiatry and that patients are most likely to comply with new approaches in depression pharmacotherapy. However, due to the long time needed for regulatory change, it is very unlikely that personalized dosing would be rapidly implemented in clinical practice, even if adequate evidence was to emerge.

Ethical concerns in the age of an advanced psychopharmacology

The article's abstract is not available.

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.

Gastrointestinal side effects associated with antidepressant treatments in patients with major depressive disorder: A systematic review and meta-analysis

Gastrointestinal side effects (SEs) are frequently observed in patients with major depressive disorder (MDD) while taking antidepressants and may lead to treatment discontinuation. The aim of this meta-analysis is to provide quantitative measures on short-term rates of gastrointestinal SEs in MDD patients treated with second-generation antidepressants. An electronic search of the literature was conducted by using MEDLINE, ISI Web of Science - Web of Science Core Collection, and Cochrane Library databases. Eligible studies had to focus on the use of at least one of 15 antidepressants commonly used in MDD (i.e., agomelatine, bupropion, citalopram, desvenlafaxine, duloxetine, escitalopram, fluoxetine, fluvoxamine, levomilnacipran, mirtazapine, paroxetine, reboxetine, sertraline, venlafaxine, and vortioxetine) and report data on treatment-emergent gastrointestinal SEs (i.e. nausea/vomiting, diarrhoea, constipation, abdominal pain, dyspepsia, anorexia, increased appetite and dry mouth) within 12 weeks of treatment. Overall, 304 studies were included in the meta-analyses. All the considered antidepressants showed higher rates of gastrointestinal SEs than placebo. Escitalopram and sertraline were shown to be the least tolerated antidepressants on the gastrointestinal tract, being associated with all the considered SEs with the exception of constipation and increased appetite, while mirtazapine was shown to be the antidepressant with fewer side effects on the gut, being only associated with increased appetite. In conclusion, commonly used antidepressants showed different profiles of gastrointestinal SEs, possibly related to their mechanisms of action. The specific tolerability profile of each compound should be considered by clinicians when prescribing antidepressants in order to improve adherence to treatment and increase positive outcomes in patients with MDD.

Precision psychiatry in clinical practice

The treatment of depression represents a major challenge for healthcare systems and choosing among the many available drugs without objective guidance criteria is an error-prone process. Recently, pharmacogenetic biomarkers entered in prescribing guidelines, giving clinicians the possibility to use this additional tool to guide prescription and improve therapeutic outcomes. This marked an important step towards precision psychiatry, which aim is to integrate biological and environmental information to personalise treatments. Only genetic variants in cytochrome enzymes are endorsed by prescribing guidelines, but in the future polygenic predictors of treatment outcomes may be translated into the clinic. The integration of genetics with other relevant information (e.g., concomitant diseases and treatments, drug plasma levels) could be managed in a standardised way through ad hoc software. The overcoming of the current obstacles (e.g., staff training, genotyping and informatics facilities) can lead to a broad implementation of precision psychiatry and represent a revolution for psychiatric care.Key pointsPrecision psychiatry aims to integrate biological and environmental information to personalise treatments and complement clinical judgementPharmacogenetic biomarkers in cytochrome genes were included in prescribing guidelines and represented an important step towards precision psychiatryTherapeutic drug monitoring is an important and cost-effective tool which should be integrated with genetic testing and clinical evaluation in order to optimise pharmacotherapyOther individual factors relevant to pharmacotherapy response (e.g., individual's symptom profile, concomitant diseases) can be integrated with genetic information through artificial intelligence to provide treatment recommendationsThe creation of pharmacogenetic services within healthcare systems is a challenging and multi-step process, education of health professionals, promotion by institutions and regulatory bodies, economic and ethical barriers are the main issues.

Individualized identification of first-episode bipolar disorder using machine learning and cognitive tests

Identifying cognitive dysfunction in the early stages of Bipolar Disorder (BD) can allow for early intervention. Previous studies have shown a strong correlation between cognitive dysfunction and number of manic episodes. The objective of this study was to apply machine learning (ML) techniques on a battery of cognitive tests to identify first-episode BD patients (FE-BD). Two cohorts of participants were used for this study. Cohort #1 included 74 chronic BD patients (CHR-BD) and 53 healthy controls (HC), while the Cohort #2 included 37 FE-BD and 18 age- and sex-matched HC. Cognitive functioning was assessed using the Cambridge Neuropsychological Test Automated Battery (CANTAB). The tests examined domains of visual processing, spatial memory, attention and executive function. We trained an ML model to distinguish between chronic BD patients (CHR-BD) and HC at the individual level. We used linear Support Vector Machines (SVM) and were able to identify individual CHR-BD patients at 77% accuracy. We then applied the model to Cohort #2 (FE-BD patients) and achieved an accuracy of 76% (AUC = 0.77). These results reveal that cognitive impairments may appear in early stages of BD and persist into later stages. This suggests that the same deficits may exist for both CHR-BD and FE-BD. These cognitive deficits may serve as markers for early BD. Our study provides a tool that these early markers can be used for detection of BD.

A Practical Utility and Benefit of Pharmacogenetic-based Antidepressant Treatment Strategy for Major Depressive Disorder Patients with Difficult-to-treat

Objective

We report the results of pharmacogenomics-based antidepressant treatment (PGXt) results in treating treatment-resistant major depressive disorder (TRD) patients in real practice.

Methods

Nine patients were prescribed Neuropharmagen^Ⓡ for selection of antidepressants for individual patient and their clinical outcomes were followed.

Results

After treatment by PGXt results from current antidepressants, substantial reduction of depressive symptoms was observed at some point and maintained during observation period in six patients.

Conclusion

Our case series potentially shows the clinical utility and benefit of PGXt for treatment of TRD patients.

Stem cell-based models and therapies: a key approach into schizophrenia treatment

Psychiatric disorders such as schizophrenia can generate distress and disability along with heavy costs on individuals and health care systems. Different genetic and environmental factors play a pivotal role in the appearance of the mentioned disorders. Since the conventional treatment options for psychiatric disorders are suboptimal, investigators are trying to find novel strategies. Herein, stem cell therapies have been recommended as novel choices. In this context, the preclinical examination of stem cell-based therapies specifically using appropriate models can facilitate passing strong filters and serious examination to ensure proper quality and safety of them as a novel treatment approach. Animal models cannot be adequately helpful to follow pathophysiological features. Nowadays, stem cell-based models, particularly induced pluripotent stem cells reflected as suitable alternative models in this field. Accordingly, the importance of stem cell-based models, especially to experiment with the regenerative medicine outcomes for schizophrenia as one of the severe typing of psychiatric disorders, is addressed here.

Combining machine learning algorithms for prediction of antidepressant treatment response

OBJECTIVES

Predictors for unfavorable treatment outcome in major depressive disorder (MDD) applicable for treatment selection are still lacking. The database of a longitudinal multicenter study on 1079 acutely depressed patients, performed by the German research network on depression (GRND), allows supervised and unsupervised learning to further elucidate the interplay of clinical and psycho-sociodemographic variables and their predictive impact on treatment outcome phenotypes.

EXPERIMENTAL PROCEDURES

Treatment response was defined by a change of HAM-D 17-item baseline score ≥50% and remission by the established threshold of ≤7, respectively, after up to eight weeks of inpatient treatment. After hierarchical symptom clustering and stratification by treatment subtypes (serotonin reuptake inhibitors, tricyclic antidepressants, antipsychotic, and lithium augmentation), prediction models for different outcome phenotypes were computed with random forest in a cross-center validation design. In total, 88 predictors were implemented.

RESULTS

Clustering revealed four distinct HAM-D subscores related to emotional, anxious, sleep, and appetite symptoms, respectively. After feature selection, classification models reached moderate to high accuracies up to 0.85. Highest accuracies were observed for the SSRI and TCA subgroups and for sleep and appetite symptoms, while anxious symptoms showed poor predictability.

CONCLUSION

Our results support a decisive role for machine learning in the management of antidepressant treatment. Treatment- and symptom-specific algorithms may increase accuracies by reducing heterogeneity. Especially, predictors related to duration of illness, baseline depression severity, anxiety and somatic symptoms, and personality traits moderate treatment success. However, prospectives application of machine learning models will be necessary to prove their value for the clinic.

Effectiveness and Tolerability of Korean Red Ginseng Augmentation in Major Depressive Disorder Patients with Difficult-to-treat in Routine Practice

Objective

: To test clinical effectiveness and tolerability of Korean Red Ginseng augmentation (RGA) in major depressive disorder (MDD) patients with difficult-to-treat.

Methods

Thirty six patients were enrolled in this 6 weeks, prospective, clinical trial. Rating scales were MontgomeryÅsberg Depression Rating Scale (MADRS), Patient Health Questionnaire-15, Clinical Global Impression-improvement (CGI-I), and Patient Satisfaction Score. The primary endpoint was a remission rate measured by MADRS score at the end of study (≤ 10). Clinical outcomes and tolerability were assessed at baseline, week 2, and week 6.

Results

Among 36 patients, 26 patients completed the study and 28 patients had post-baseline visit data. The remission rate by MADRS score was 39.3% (11/28) and 57.1% by CGI-I scores of 1 or 2 at the end of the study. The mean change of MADRS score was significantly decreased by 44.4% from baseline to the end of study. The most frequent adverse events were headache (7/28, 25.0%) during the study.

Conclusion

Our study indicates the putative effectiveness and tolerability of RGA for treating MDD with difficult-to-treat in clinical practice. However, adequately powered, randomized, controlled trials will be needed to confirm these results.

How to Utilize Clinical and Genetic Information for Personalized Treatment of Major Depressive Disorder: Step by Step Strategic Approach

Depression is the single largest contributor to non-fatal health loss and affects 322 million people globally. The clinical heterogeneity of this disorder shows biological correlates and it makes the personalization of antidepressant prescription an important pillar of treatment. There is increasing evidence of genetic overlap between depression, other psychiatric and non-psychiatric disorders, which varies across depression subtypes. Therefore, the first step of clinical evaluation should include a careful assessment of psychopathology and physical health, not limited to previously diagnosed disorders. In part of the patients indeed the pathogenesis of depression may be strictly linked to inflammatory and metabolic abnormalities, and the treatment should target these as much as the depressive symptoms themselves. When the evaluation of the symptom and drug tolerability profile, the concomitant biochemical abnormalities and physical conditions is not enough and at least one pharmacotherapy failed, the genotyping of variants in CYP2D6/CYP2C19 (cytochromes responsible for antidepressant metabolism) should be considered. Individuals with altered metabolism through one of these enzymes may benefit from some antidepressants rather than others or need dose adjustments. Finally, if available, the polygenic predisposition towards cardio-metabolic disorders can be integrated with non-genetic risk factors to tune the identification of patients who should avoid medications associated with this type of side effects. A sufficient knowledge of the polygenic risk of complex medical and psychiatric conditions is becoming relevant as this information can be obtained through direct-to-consumer genetic tests and in the future it may provided by national health care systems.

Four Actionable Bottlenecks and Potential Solutions to Translating Psychiatric Genetics Research: An Expert Review

BACKGROUND

Psychiatric genetics has had limited success in translational efforts. A thorough understanding of the present state of translation in this field will be useful in the facilitation and assessment of future translational progress.

PURPOSE

A narrative literature review was conducted. Combinations of 3 groups of terms were searched in EBSCOhost, Google Scholar, and PubMed. The review occurred in multiple steps, including abstract collection, inclusion/exclusion criteria review, coding, and analysis of included papers.

RESULTS

One hundred and fourteen articles were analyzed for the narrative review. Across those, 4 bottlenecks were noted that, if addressed, may provide insights and help improve and increase translation in the field of psychiatric genetics. These 4 bottlenecks are emphasizing linear translational frameworks, relying on molecular genomic findings, prioritizing certain psychiatric disorders, and publishing more reviews than experiments.

CONCLUSIONS

These entwined bottlenecks are examined with one another. Awareness of these bottlenecks can inform stakeholders who work to translate and/or utilize psychiatric genetic information. Potential solutions include utilizing nonlinear translational frameworks as well as a wider array of psychiatric genetic information (e.g., family history and gene-environment interplay) in this area of research, expanding which psychiatric disorders are considered for translation, and when possible, conducting original research. Researchers are urged to consider how their research is translational in the context of the frameworks, genetic information, and psychiatric disorders discussed in this review. At a broader level, these efforts should be supported with translational efforts in funding and policy shifts.

The search for personalized antidepressant treatments: what have we learned and where are we going

Over 20 years after the initial report of gene variants within the central nervous system modulating antidepressant response, we are now facing for the first time routine clinical pharmacogenetic applications. The scientific community is divided between enthusiasm and skepticism. It seems clear that the benefit of existing tools is not huge, at least for the central nervous system gene variants, while it is generally accepted for the metabolic gene variants. Findings from large international consortia suggest for the first time in psychiatric genetic research history that cumulative scores comprising many variants across the whole genome may reliably constitute liability factors for psychiatric disorders, this approach will most likely improve also present pharmacogenetic tools. A composite genetic score complemented with clinical risk factors for each patient is the most promising approach for a more effective method of targeted treatment for patients with depression.

Analysis of 14 drugs in dried blood microsamples in a single workflow using whole blood and serum calibrators

Aim: Multiplexed, high-throughput analysis facilitates therapeutic drug monitoring. 14 drugs with various physico-chemical properties were quantitated in dried blood microsamples. Methods: Analytes were extracted employing eight solvent compositions and seven extraction methods. The applicability of liquid serum, dried serum and dried whole blood calibrators was investigated. Results: High recoveries were attained. Calibration using dried serum yielded lowest total error. Reducing sample hematocrit caused outstanding elevations in recovery of analytes with high polarity or affinity to erythrocytes. 9-day analyte stability was demonstrated. Conclusion: Based on the analysis of spiked samples, multiplexed testing of drugs in dried blood microsamples seems feasible, but with analyte-dependent method performance. Dried serum calibration allows the adaptation of serum-based workflows. Further evaluation using real-life specimens is needed.

Improving Mental Health Services: A 50-Year Journey from Randomized Experiments to Artificial Intelligence and Precision Mental Health

This conceptual paper describes the current state of mental health services, identifies critical problems, and suggests how to solve them. I focus on the potential contributions of artificial intelligence and precision mental health to improving mental health services. Toward that end, I draw upon my own research, which has changed over the last half century, to highlight the need to transform the way we conduct mental health services research. I identify exemplars from the emerging literature on artificial intelligence and precision approaches to treatment in which there is an attempt to personalize or fit the treatment to the client in order to produce more effective interventions.

Agomelatine for the Treatment of Generalized Anxiety Disorder: A Meta-Analysis

Objective

Despite multiple drugs available, a large proportion of patients with generalized anxiety disorder (GAD) do not show adequate response and remission. Thus, additional novel pharmacological agents are needed to increase treatment option for GAD. We aimed to investigate efficacy and safety of agomelatine in the treatment of GAD by conducting a meta-analysis.

Methods

An extensive search of multiple databases and clinical trial registries were conducted. Mean change in total scores on Hamilton Anxiety Rating Scale (HAM-A) from baseline to endpoint was our primary outcome measure. Secondary efficacy measures included response and remission rates, as defined by a 50% or greater reduction in HAM-A total scores and a score of 7 or less in HAM-A total scores at study endpoint respectively.

Results

Four published double blinded, randomized, placebo-controlled trials were included in this meta-analysis. Agomelatine more significantly (standardized mean difference = −0.56, p = 0.004) improved HAM-A total scores than placebo. The odds ratios (ORs) of agomelatine over placebo for response and remission rates were 3.75 (p < 0.00001) and 2.74 (p < 0.00001), respectively. Agomelatine was generally well tolerated with insignificance in dropout rate, somnolence, headache, nasopharyngitis, and dizziness compared with placebo. However, agomelatine showed significantly higher incidence of liver function increment (OR = 3.13, p = 0.01) and nausea (OR = 3.27, p = 0.02).

Conclusion

We showed that agomelatine may be another treatment option in patients with GAD. However, the results should be interpreted and translated into clinical practice with caution because the meta-analysis was based on limited numbers of clinical trials.

The Usefulness and Clinical Characteristics of Antidepressant Use for Stroke Patients with Rehabilitation Program: An Exploratory Analysis

Objective

There has been a lack of data regarding the usefulness and clinical characteristic between patients-treated with and without antidepressants (Pw/Pwo ADs).

Methods

One hundred and eighty inpatients were recruited and observed for a 6-month. The depressive, cognitive, daily activity, and motor symptoms were evaluated at baseline and tracked at month 6, with the use of rating scales including Beck Depression Inventory (BDI), Mini Mental State Examination (MMSE), Global Deterioration Scale (GDS), modified Rankin Scale (MRS), modified Barthel Index (MBI), and Berg Balance Scale (BBS).

Results

Among 178 patients, 84 (47.2%) were treated with ADs. PwAD had numerically or significantly higher depressive cognitive, and motor symptoms along with daily activity impairment (8.3 point higher in BDI score, p < 0.001; 3.6 point lower in MMSE, p = 0.003; 0.8 point higher in GDS score, p = nonsignificant; 8.2 point lower in BBS score, p = 0.053, and 0.4 point higher in MBI score, p = nonsignificant) than PwoAD. Psychiatric consultation was also significantly higher in PwAD than in PwoAD (p < 0.001). The numbers need to treat for good clinical outcomes between PwAD and PwoAD were 5.8, 6.0, and 7.5, respectively, by MRS, MBI, and BBS scores.

Conclusion

Our findings suggest the potential utility of AD treatment and different clinical parameters between patients-treated with and without ADs. Adequately-powered and well-controlled further studies are mandatory to confirm and fully elaborate such association.

Personalized medicine begins with the phenotype: identifying antipsychotic response phenotypes in a first-episode psychosis cohort

AIMS

Here, we present a clustering strategy to identify phenotypes of antipsychotic (AP) response by using longitudinal data from patients presenting first-episode psychosis (FEP).

METHOD

One hundred and ninety FEP with complete data were selected from the PEPs project. The efficacy was assessed using total PANSS, and adverse effects using total UKU, during one-year follow-up. We used the Klm3D method to cluster longitudinal data.

RESULTS

We identified four clusters: cluster A, drug not toxic and beneficial; cluster B, drug beneficial but toxic; cluster C, drug neither toxic nor beneficial; and cluster D, drug toxic and not beneficial. These groups significantly differ in baseline demographics, clinical, and neuropsychological characteristics (PAS, total PANSS, DUP, insight, pIQ, age of onset, cocaine use and family history of mental illness).

CONCLUSIONS

The results presented here allow the identification of phenotypes of AP response that differ in well-known simple and classic clinical variables opening the door to clinical prediction and application of personalized medicine.

Genetics of Treatment Outcomes in Major Depressive Disorder: Present and Future

Pharmacogenetic testing is a useful and increasingly widespread tool to assist in antidepressant prescription. More than ten antidepressants (including tricyclics, selective serotonin reuptake inhibitors and venlafaxine) have already genetic biomarkers of response/side effects in clinical guidelines and drug labels. These are represented by functional genetic variants in genes coding for cytochrome enzymes (CYP2D6 and CYP2C19). Depending on the predicted metabolic activity, guidelines provide recommendations on drug choice and dosing. Despite not conclusive, the current evidence suggests that testing can be useful in patients who did not respond or tolerate at least one previous pharmacotherapy. However, the current recommendations are based on pharmacokinetic genes only (CYP450 enzymes), while pharmacodynamic genes (modulating antidepressant mechanisms of action in the brain) are still being studied because of their greater complexity. This may be captured by polygenic risk scores, which reflect the cumulative contribution of many genetic variants to a trait, and they may provide future clinical applications of pharmacogenetics. A more extensive use of genotyping in clinical practice may lead to improvement in treatment outcomes thanks to personalized treatments, but possible ethical issues and disparities should be taken into account and prevented.

Precision Psychiatry Applications with Pharmacogenomics: Artificial Intelligence and Machine Learning Approaches

A growing body of evidence now suggests that precision psychiatry, an interdisciplinary field of psychiatry, precision medicine, and pharmacogenomics, serves as an indispensable foundation of medical practices by offering the accurate medication with the accurate dose at the accurate time to patients with psychiatric disorders. In light of the latest advancements in artificial intelligence and machine learning techniques, numerous biomarkers and genetic loci associated with psychiatric diseases and relevant treatments are being discovered in precision psychiatry research by employing neuroimaging and multi-omics. In this review, we focus on the latest developments for precision psychiatry research using artificial intelligence and machine learning approaches, such as deep learning and neural network algorithms, together with multi-omics and neuroimaging data. Firstly, we review precision psychiatry and pharmacogenomics studies that leverage various artificial intelligence and machine learning techniques to assess treatment prediction, prognosis prediction, diagnosis prediction, and the detection of potential biomarkers. In addition, we describe potential biomarkers and genetic loci that have been discovered to be associated with psychiatric diseases and relevant treatments. Moreover, we outline the limitations in regard to the previous precision psychiatry and pharmacogenomics studies. Finally, we present a discussion of directions and challenges for future research.

Will We Be Ready? Preparing Psychiatric-Mental Health Nurses for Future Practice

OBJECTIVE: To review the challenges and issues facing educators as they prepare the psychiatric-mental health (PMH) nursing workforce to meet the needs of future practice. METHODS: Based on the author's 40-plus-year career as an educator, clinician, and researcher, combined with a review of the literature, this article analyzes the current educational milieu for undergraduate, graduate, postgraduate, and continuing education of PMH nurses, including urgent educational priorities. It also offers recommendations to meet the needs of PMH nurses both in education and in clinical practice. RESULTS: PMH nursing education must evolve to provide nursing experiences in nontraditional as well as traditional clinical settings, and incorporate simulation and telehealth/digital/mobile platforms for delivery of content. Development of qualified faculty members and preceptors who represent the diversity of the American population must be addressed to adequately train PMH nurses to meet the demands of their future roles. Methods must also be created to define, teach, and evaluate PMH nurses' clinical competencies pre- and postclinical experiences. CONCLUSIONS: PMH nursing education must evolve and transform to attract, appropriately educate and prepare students for practice, and meet the growing need for qualified practitioners as well as faculty members and preceptors.

The cellular and molecular basis of major depressive disorder: towards a unified model for understanding clinical depression

Major depressive disorder (MDD) is considered a serious public health issue that adversely impacts an individual's quality of life and contributes significantly to the global burden of disease. The clinical heterogeneity that exists among patients limits the ability of MDD to be accurately diagnosed and currently, a symptom-based approach is utilized in many cases. Due to the complex nature of this disorder, and lack of precise knowledge regarding the pathophysiology, effective management is challenging. The aetiology and pathophysiology of MDD remain largely unknown given the complex genetic and environmental interactions that are involved. Nonetheless, the aetiology and pathophysiology of MDD have been the subject of extensive research, and there is a vast body of literature that exists. Here we overview the key hypotheses that have been proposed for the neurobiology of MDD and highlight the need for a unified model, as many of these pathways are integrated. Key pathways discussed include neurotransmission, neuroinflammation, clock gene machinery pathways, oxidative stress, role of neurotrophins, stress response pathways, the endocannabinoid and endovanilloid systems, and the endogenous opioid system. We also describe the current management of MDD, and emerging novel therapies, with particular focus on patients with treatment-resistant depression (TRD).

The prevalence and diagnostic classification of mixed features in patients with major depressive episodes: A multicenter study based on the DSM-5

OBJECTIVES

The purpose of this study was to evaluate the prevalence of mixed features using the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) and to examine how patients with mixed states would be classified using the DSM-5.

METHODS

In total, 12 hospitals participated in this study, and data on the demographic characteristics and clinical diagnoses of patients treated between October 2013 and September 2016 were obtained. We reviewed the data for opposite-polarity symptoms according to the DSM-5 criteria and the research-based diagnostic criteria.

RESULTS

Of the 859 patients included in the final analysis, the prevalence of mixed features in patients with major depressive episodes based on the DSM-5 remained low. Patients with major depressive disorder were more likely to be classified as experiencing anxious distress and/or a cluster-B personality disorder in mixed state patients not diagnosed with DSM-5 mixed features, whereas more mixed state patients with bipolar disorder were diagnosed with mixed features using the DSM-5.

CONCLUSIONS

The prevalence of mixed features did not increase significantly when the DSM-5 was used, and patients with mixed states were more likely to be classified as having anxious distress and/or a cluster-B personality disorder in addition to mixed features.

Genes Involved in Neurodevelopment, Neuroplasticity and Major Depression: No Association for CACNA1C, CHRNA7 and MAPK1

Objective

Genetics factors are likely to play a role in the risk, clinical presentation and treatment outcome in major depressive disorder (MDD). In this study, we investigated the role of three candidate genes for MDD; calcium voltage-gated channel subunit alpha1 C (CACNA1C ), cholinergic receptor nicotinic alpha 7 subunit (CHRNA7 ), and mitogen-activated protein kinase 1 (MAPK1).

Methods

Two-hundred forty-two MDD patients and 326 healthy controls of Korean ancestry served as samples for the analyses. Thirty-nine single nucleotide polymorphisms (SNPs) within CACNA1C, CHRNA7, and MAPK1 genes were genotyped and subsequently tested for association with MDD (primary analysis) and other clinical features (symptoms’ severity, age of onset, history of suicide attempt, treatment outcome) (secondary analyses). Single SNPs, haplotypes and epistatic analyses were performed.

Results

Single SNPs were not associated with disease risk and clinical features. However, a combination of alleles (haplotype) within MAPK1 was found associated with MDD-status. Secondary analyses detected a possible involvement of CACNA1C haplotype in resistance to antidepressant treatment.

Conclusion

These data suggest a role for MAPK1 and CACNA1C in MDD risk and treatment resistance, respectively. However, since many limitations characterize the analysis, the results must be considered with great caution and verified.

Characterization of the Brain Penetrant Neuropeptide Y Y2 Receptor Antagonist SF-11

This paper discusses the biological and three-dimensional molecular structure of the novel, nonpeptide Y2R antagonist, SF-11 [N-(4-ethoxyphenyl)-4-(hydroxydiphenylmethyl)-1-piperidinecarbothioamide]. Pharmacokinetic studies in a rat model indicated that, following intraperitoneal dosing, SF-11 crossed the blood-brain barrier and was able to penetrate the brain, making it a suitable tool for behavioral studies. We showed for the first time that SF-11 decreased the immobility time in the forced swim test (FST) after acute peripheral administration (10 and 20 mg/kg), indicating that it has antidepressant potential. Inhibitors of the mitogen-activated protein kinase/extracellular signal regulated kinase (MAPK/ERK) and phosphatidylinositol 3-kinase (PI3K) signaling pathways blocked the anti-immobility effect of SF-11, suggesting that these pathways are involved in the antidepressant-like activity of SF-11 in the FST. The results of locomotor activity of rats indicate that the effects observed in the FST are specific and due to the antidepressant-like activity of SF-11. These findings provide further evidence for the antidepressant potential of Y2R antagonists. Also, the application of Fourier transform infrared absorption (FT-IR) and Raman spectroscopy (RS) methods combined with theoretical density functional theory (DFT) calculations allowed us to present the optimized spatial orientation of the investigated drug. Structural characterization of SF-11 based on vibrational spectroscopic data is of great importance and will aid in understanding its biological activity and pave the way for its development as a new antidepressant agent.

Perceived mechanisms of change in therapeutic yoga targeting psychological distress

INTRODUCTION

This study was designed to investigate yoga teachers' and yoga therapists' perceptions of the ways yoga is applied to treat symptoms of psychological distress, and identify the defining features, main components, and mechanisms of change in therapeutic practice.

METHODS

A qualitative design was employed. Six yoga teachers who had specific training and experience in teaching therapeutic yoga or practicing 'yoga therapy' took part in one-to-one interviews during which they gave accounts of their experiences of helping people cope with psychological distress through yoga. Participants' interviews were transcribed verbatim and were analysed using an integrative inductive-deductive thematic analysis.

RESULTS

Four key themes were identified in relation to the benefits of therapeutic yoga: Awareness, Choice, Relationships, and Tailoring.

CONCLUSIONS

The findings support previous research which suggests that individualised yoga therapy is a promising intervention, and may help to form a theoretical rationale for the future treatment of psychological distress with yoga.

Results of the European Group for the Study of Resistant Depression (GSRD) - basis for further research and clinical practice

Objectives: The overview outlines two decades of research from the European Group for the Study of Resistant Depression (GSRD) that fundamentally impacted evidence-based algorithms for diagnostics and psychopharmacotherapy of treatment-resistant depression (TRD). Methods: The GSRD staging model characterising response, non-response and resistance to antidepressant (AD) treatment was applied to 2762 patients in eight European countries. Results: In case of non-response, dose escalation and switching between different AD classes did not show superiority over continuation of original AD treatment. Predictors for TRD were symptom severity, duration of the current major depressive episode (MDE), suicidality, psychotic and melancholic features, comorbid anxiety and personality disorders, add-on treatment, non-response to the first AD, adverse effects, high occupational level, recurrent disease course, previous hospitalisations, positive family history of MDD, early age of onset and novel associations of single nucleoid polymorphisms (SNPs) within the PPP3CC, ST8SIA2, CHL1, GAP43 and ITGB3 genes and gene pathways associated with neuroplasticity, intracellular signalling and chromatin silencing. A prediction model reaching accuracy of above 0.7 highlighted symptom severity, suicidality, comorbid anxiety and lifetime MDEs as the most informative predictors for TRD. Applying machine-learning algorithms, a signature of three SNPs of the BDNF, PPP3CC and HTR2A genes and lacking melancholia predicted treatment response. Conclusions: The GSRD findings offer a unique and balanced perspective on TRD representing foundation for further research elaborating on specific clinical and genetic hypotheses and treatment strategies within appropriate study-designs, especially interaction-based models and randomized controlled trials.

Pharmacological Therapy in Panic Disorder: Current Guidelines and Novel Drugs Discovery for Treatment-resistant Patient

Panic disorder (PD) being one of the most intensively investigated anxiety disorders is considered a heterogeneous psychiatric disease which has difficulties with early diagnosis. The disorder is recurrent and usually associated with low remission rates and high rates of relapse which may exacerbated social and quality of life, causes unnecessary cost and increased risk for complication and suicide. Current pharmacotherapy for PD are available but these drugs have slow therapeutic onset, several side effects and most patients do not fully respond to these standard pharmacological treatments. Ongoing investigations indicate the need for new and promising agents for the treatment of PD. This article will cover the importance of immediate and proper treatment, the gap in the current management of PD with special emphasis on pharmacotherapy, and evidence regarding the novel anti-panic drugs including the drugs in developments such as metabotropic glutamate (mGlu 2/3) agonist and levetiracetam. Preliminary results suggest the anti-panic properties and the efficacy of duloxetine, reboxetine, mirtazapine, nefazodone, risperidone and inositol as a monotherapy drug. Apart for their effectiveness, the aforementioned compounds were generally well tolerated compared to the standard available pharmacotherapy drugs, indicating their potential therapeutic usefulness for ambivalent and hypervigilance patient. Further strong clinical trials will provide an ample support to these novel compounds as an alternative monotherapy for PD treatment-resistant patient.

Pharmacogenetics of Antidepressants: from Genetic Findings to Predictive Strategies

The constantly growing contribution of depressive disorders to the global disease statistics calls for a growth of treatment effectiveness and optimization. Antidepressants are the most frequently prescribed medicines for depressive disorders. However, development of a standardized pharmacotherapeutic approach is burdened by the genomic heterogeneity, lack of reliable predictive biomarkers and variability of the medicines metabolism aggravated by multiple side effects of antidepressants. According to modern assessments up to 20 % of the genes expressed in our brain are involved in the pathogenesis of depression. Large-scale genetic and genomic research has found a number of potentially prognostic genes. It has also been proven that the effectiveness and tolerability of antidepressants directly depend on the variable activity of the enzymes that metabolize medicines. Almost all modern antidepressants are metabolized by the cytochrome P450 family enzymes. The most promising direction of research today is the GWAS (Genome-Wide Association Study) method that is aimed to link genomic variations with phenotypical manifestations. In this type of research genomes of depressive patients with different phenotypes are compared to the genomes of the control group containing same age, sex and other parameters healthy people. Notably, regardless of the large cohorts of patients analyzed, none of the GWA studies conducted so far can reliably reproduce the results of other analogous studies. The explicit heterogeneity of the genes associated with the depression pathogenesis and their pleiotropic effects are strongly influenced by environmental factors. This may explain the difficulty of obtaining clear and reproducible results. However, despite any negative circumstances, the active multidirectional research conducted today, raises the hope of clinicians and their patients to get a whole number of schedules how to achieve remission faster and with guaranteed results

The Role of Intranasal Oxytocin in Anxiety and Depressive Disorders: A Systematic Review of Randomized Controlled Trials

Several studies have demonstrated the neuromodulating function of oxytocin (OT) in response to anxiogenic stimuli as well as its potential role in the pathogenesis of depression. Consequently, intranasal OT (IN-OT) has been proposed as a potential treatment of anxiety and depressive disorders. The present systematic review aimed to summarize the randomized controlled trials (RCTs) evaluating the effect of IN-OT on anxiety and depressive symptoms. Overall, 15 studies were included, involving patients with social anxiety disorders (7 studies), arachnophobia (1), major depression (3) or post-natal depression (4), and mainly evaluating single-dose administrations of IN-OT. Results showed no significant effects on core symptomatology. Five crossover studies included functional magnetic resonance imaging investigation: one trial showed reduced amygdala hyper-reactivity after IN-OT in subjects with anxiety, while another one showed enhanced connectivity between amygdala and bilateral insula and middle cingulate gyrus after IN-OT in patients but not in healthy controls. More studies are needed to confirm these results. In conclusion, up to date, evidence regarding the potential utility of IN-OT in treating anxiety and depression is still inconclusive. Further RCTs with larger samples and long-term administration of IN-OT are needed to better elucidate its potential efficacy alone or in association with standard care.

International Union of Basic and Clinical Pharmacology CIV: The Neurobiology of Treatment-resistant Depression: From Antidepressant Classifications to Novel Pharmacological Targets

Major depressive disorder is one of the most prevalent and life-threatening forms of mental illnesses and a major cause of morbidity worldwide. Currently available antidepressants are effective for most patients, although around 30% are considered treatment resistant (TRD), a condition that is associated with a significant impairment of cognitive function and poor quality of life. In this respect, the identification of the molecular mechanisms contributing to TRD represents an essential step for the design of novel and more efficacious drugs able to modify the clinical course of this disorder and increase remission rates in clinical practice. New insights into the neurobiology of TRD have shed light on the role of a number of different mechanisms, including the glutamatergic system, immune/inflammatory systems, neurotrophin function, and epigenetics. Advances in drug discovery processes in TRD have also influenced the classification of antidepressant drugs and novel classifications are available, such as the neuroscience-based nomenclature that can incorporate such advances in drug development for TRD. This review aims to provide an up-to-date description of key mechanisms in TRD and describe current therapeutic strategies for TRD before examining novel approaches that may ultimately address important neurobiological mechanisms not targeted by currently available antidepressants. All in all, we suggest that drug targeting different neurobiological systems should be able to restore normal function but must also promote resilience to reduce the long-term vulnerability to recurrent depressive episodes.

Precision pharmacotherapy: psychiatry's future direction in preventing, diagnosing, and treating mental disorders

Mental disorders account for around one-third of disability worldwide and cause enormous personal and societal burden. Current pharmacotherapies and nonpharmacotherapies do help many patients, but there are still high rates of partial or no response, delayed effect, and unfavorable adverse effects. The current diagnostic taxonomy of mental disorders by the Diagnostic and Statistical Manual of Mental Disorders and the International Classification of Diseases relies on presenting signs and symptoms, but does not reflect evidence from neurobiological and behavioral systems. However, in the last decades, the understanding of biological mechanisms underlying mental disorders has grown and can be used for the development of precision medicine, that is, to deliver a patient-tailored individual treatment. Precision medicine may incorporate genetic variants contributing to the mental disorder and the response to pharmacotherapies, but also consider gene ¥ environment interactions, blood-based markers, neuropsychological tests, data from electronic health records, early life adversity, stressful life events, and very proximal factors such as lifestyle, nutrition, and sport. Methods such as artificial intelligence and the underlying machine learning and deep learning approaches provide the framework to stratify patients, initiate specific tailored treatments and thus increase response rates, reduce adverse effects and medical errors. In conclusion, precision medicine uses measurable health parameters to identify individuals at risk of a mental disorder, to improve the diagnostic process and to deliver a patient-tailored treatment.

Brexpiprazole: a step forward for precision medicine in resistant depression

INTRODUCTION

Resistant depression is still a common and burdensome issue and there is an urgent need for new and effective adjunctive treatments. Areas covered: In this paper, the author discusses the background, trial design, results and implications of a recent study (NCT02196506, Sirius study) which confirmed the possible benefit of brexpiprazole as adjunctive treatment in depressed subjects with inadequate benefit from first line treatments. As secondary aims, the study confirmed the effects in subjects with minimal benefit from standard treatments and in subjects with anxious distress. Despite some reported side effects such as akathisia, restlessness, and increased weight, the treatment was well tolerated. Expert opinion: The unique pharmacodynamic profile of brexpiprazole, in terms of reduced dopamine intrinsic stimulation and a range of other more anxiolytic receptor effects, suggests that brexpiprazole should be preferred in specific subpopulations, particularly where a more sedative profile is needed. Indeed, this study suggests another step in the direction of precision medicine.