How can we realize the promise of personalized antidepressant medicines?

Precision Psychiatry Approach to Treat Depression and Anxiety Targeting the Stress Hormone System - V1b-antagonists as a Case in Point

The future of depression pharmacotherapy lies in a precision medicine approach that recognizes that depression is a disease where different causalities drive symptoms. That approach calls for a departure from current diagnostic categories, which are broad enough to allow adherence to the "one-size-fits-all" paradigm, which is complementary to the routine use of "broad-spectrum" mono-amine antidepressants. Similar to oncology, narrowing the overinclusive diagnostic window by implementing laboratory tests, which guide specifically targeted treatments, will be a major step forward in overcoming the present drug discovery crisis.A substantial subgroup of patients presents with signs and symptoms of hypothalamic-pituitary-adrenocortical (HPA) overactivity. Therefore, this stress hormone system was considered to offer worthwhile targets. Some promising results emerged, but in sum, the results achieved by targeting corticosteroid receptors were mixed.More specific are non-peptidergic drugs that block stress-responsive neuropeptides, corticotropin-releasing hormone (CRH), and arginine vasopressin (AVP) in the brain by antagonizing their cognate CRHR1-and V1b-receptors. If a patient's depressive symptomatology is driven by overactive V1b-signaling then a V1b-receptor antagonist should be first-line treatment. To identify the patient having this V1b-receptor overactivity, a neuroendocrine test, the so-called dex/CRH-test, was developed, which indicates central AVP release but is too complicated to be routinely used. Therefore, this test was transformed into a gene-based "near-patient" test that allows immediate identification if a depressed patient's symptomatology is driven by overactive V1b-receptor signaling. We believe that this precision medicine approach will be the next major innovation in the pharmacotherapy of depression.

Differential effects of healthcare worker burnout on psychotropic medication use and misuse by occupational level

PURPOSE

Burnout has been well examined among physicians and other high-wage, high-autonomy healthcare positions. However, lower-wage healthcare workers with less workplace autonomy (e.g., medical assistants, nurses' aides) represent a substantial proportion of the workforce, but remain understudied. We aimed to examine the effects of burnout on psychotropic medication use and misuse and whether these effects differed by occupational level.

METHODS

In March 2022, we collected data from a diverse sample of US healthcare workers (N = 200) and examined the cross-sectional relationship between burnout and changes in prescribed psychotropic medication (i.e., starting, stopping, and/or having a change in the dose/frequency) during the COVID-19 pandemic. We also separately examined the relationship between burnout and psychotropic medication misuse (i.e., without a prescription, in greater amounts, more often, longer than prescribed, and/or for a reason other than prescribed). We stratified models by occupational level (prescribers/healthcare administrators vs. other healthcare workers).

RESULTS

Greater burnout was associated with higher odds of changes in prescribed psychotropic medication among prescribers/healthcare administrators (aOR = 1.23, 95% CI 1.01, 1.48), but not among other healthcare workers (aOR = 1.04, 95% CI 0.98, 1.10). Greater burnout was not associated with psychotropic medication misuse among prescribers/healthcare administrators (aOR = 0.96, 95% CI 0.82, 1.12) but was associated with increased odds of psychotropic medication misuse among other healthcare workers (aOR = 1.07, 95% CI 1.01, 1.14).

CONCLUSIONS

Potential disparities in help-seeking and healthcare access might manifest in non-medical use of prescription drugs among some healthcare workers, which has implications for worker safety and well-being.

A pilot exploration of multi-omics research of gut microbiome in major depressive disorders

The pathophysiology of major depressive disorder (MDD) remains obscure. Recently, the microbiota-gut-brain (MGB) axis's role in MDD has an increasing attention. However, the specific mechanism of the multi-level effects of gut microbiota on host metabolism, immunity, and brain structure is unclear. Multi-omics approaches based on the analysis of different body fluids and tissues using a variety of analytical platforms have the potential to provide a deeper understanding of MGB axis disorders. Therefore, the data of metagenomics, metabolomic, inflammatory factors, and MRI scanning are collected from the two groups including 24 drug-naïve MDD patients and 26 healthy controls (HCs). Then, the correlation analysis is performed in all omics. The results confirmed that there are many markedly altered differences, such as elevated Actinobacteria abundance, plasma IL-1β concentration, lipid, vitamin, and carbohydrate metabolism disorder, and diminished grey matter volume (GMV) of inferior frontal gyrus (IFG) in the MDD patients. Notably, three kinds of discriminative bacteria, Ruminococcus bromii, Lactococcus chungangensis, and Streptococcus gallolyticus have an extensive correlation with metabolome, immunology, GMV, and clinical symptoms. All three microbiota are closely related to IL-1β and lipids (as an example, phosphoethanolamine (PEA)). Besides, Lactococcus chungangensis is negatively related to the GMV of left IFG. Overall, this study demonstrate that the effects of gut microbiome exert in MDD is multifactorial.

ABCB1 variants and sex affect serotonin transporter occupancy in the brain

Strategies to personalize psychopharmacological treatment promise to improve efficacy and tolerability. We measured serotonin transporter occupancy immediately after infusion of the widely prescribed P-glycoprotein substrate citalopram and assessed to what extent variants of the ABCB1 gene affect drug target engagement in the brain in vivo. A total of 79 participants (39 female) including 31 patients with major depression and 48 healthy volunteers underwent two PET/MRI scans with the tracer [¹¹C]DASB and placebo-controlled infusion of citalopram (8 mg) in a cross-over design. We tested the effect of six ABCB1 single nucleotide polymorphisms and found lower SERT occupancy in ABCB1 rs2235015 minor allele carriers (n = 26, MAF = 0.18) compared to major allele homozygotes (t₇₃ = 2.73, p_FWE < 0.05) as well as in men compared to women (t₇₃ = 3.33, p_FWE < 0.05). These effects were robust to correction for citalopram plasma concentration, age and diagnosis. From occupancy we derived the ratio of occupied to unoccupied SERT, because in theory this measure is equal to the product of drug affinity and concentration at target sites. A model combining genotype with basic clinical variables, predicted that, at the same dosage, occupied to unoccupied SERT ratio was -14.48 ± 5.38% lower in rs2235015 minor allele carriers, +19.10 ± 6.95% higher in women, -4.83 ± 2.70% lower per 10 kg bodyweight, and -2.68 ± 3.07% lower per 10 years of age. Our results support the exploration of clinical algorithms with adjustment of initial citalopram dosing and highlight the potential of imaging-genetics for precision pharmacotherapy in psychiatry.

Hypothalamic stress systems in mood disorders

Stress system dysfunction is a typical characteristic of acute depression and other mood disorders. The exact pattern of factors predisposing for stress-related mental disorders is yet to be unraveled. However, corticosteroid receptor function plays an important role for appropriate or dysfunctional neuroendocrine responses to stress exposure and hence in resilience or risk for the development and course of both, depression and anxiety disorders. Solid neuroscience data strongly support that both neuropeptides, corticotropin-releasing hormone (CRH) and vasopressin (AVP), are central in coordinating humoral and behavioral adaptation to stress. Other neuropeptides, including oxytocin, neuropeptide S, neuropeptide Y, and orexin, are also considered important contributors. Attempts to turn neuropeptide biology into treatments for stress-related disorders need to consider that neuropeptide receptors are specific drug targets for certain patient populations rather than universal targets for all patients, like biogenic amine systems. That is why most negative clinical trials testing neuropeptide receptor antagonists have been in fact failed trials by design, because no companion tests were used to identify which patients with depression are most likely to benefit from a specific neuropeptide receptor-targeting drug treatment. Therefore, the most important future research task is discovery and development of appropriate companion tests that will allow the successful transfer of the precious treasure of neuropeptide system-targeting drugs into clinics.

The Mechanisms Underlying Autonomous Adrenocorticotropic Hormone Secretion in Cushing's Disease

Cushing’s disease caused due to adrenocorticotropic hormone (ACTH)-secreting pituitary adenomas (ACTHomas) leads to hypercortisolemia, resulting in increased morbidity and mortality. Autonomous ACTH secretion is attributed to the impaired glucocorticoid negative feedback (glucocorticoid resistance) response. Interestingly, other conditions, such as ectopic ACTH syndrome (EAS) and non-neoplastic hypercortisolemia (NNH, also known as pseudo-Cushing’s syndrome) also exhibit glucocorticoid resistance. Therefore, to differentiate between these conditions, several dynamic tests, including those with desmopressin (DDAVP), corticotrophin-releasing hormone (CRH), and Dex/CRH have been developed. In normal pituitary corticotrophs, ACTH synthesis and secretion are regulated mainly by CRH and glucocorticoids, which are the ACTH secretion-stimulating and -suppressing factors, respectively. These factors regulate ACTH synthesis and secretion through genomic and non-genomic mechanisms. Conversely, glucocorticoid negative feedback is impaired in ACTHomas, which could be due to the overexpression of 11β-HSD2, HSP90, or TR4, or loss of expression of CABLES1 or nuclear BRG1 proteins. Genetic analysis has indicated the involvement of several genes in the etiology of ACTHomas, including USP8, USP48, BRAF, and TP53. However, the association between glucocorticoid resistance and these genes remains unclear. Here, we review the clinical aspects and molecular mechanisms of ACTHomas and compare them to those of other related conditions.

Individual response to antidepressants for depression in adults-a meta-analysis and simulation study

BACKGROUND

The observation that some patients appear to respond better to antidepressants for depression than others encourages the assumption that the effect of antidepressants differs between individuals and that treatment can be personalized.

OBJECTIVE

To compare the outcome variance in patients receiving antidepressants with the outcome variance in patients receiving placebo in randomized controlled trials (RCTs) of adults with major depressive disorder (MDD) and to illustrate, using simulated data, components of variation of RCTs.

METHODS

From a dataset comprising 522 RCTs of antidepressants for adult MDD, we selected the placebo-controlled RCTs reporting outcomes on the 17 or 21 item Hamilton Depression Rating Scale or the Montgomery-Asberg Depression Rating Scale and extracted the means and SDs of raw endpoint scores or baseline to endpoint changes scores on eligible depression symptom rating scales. We conducted inverse variance random-effects meta-analysis with the variability ratio (VR), the ratio between the outcome variance in the group of patients receiving antidepressants and the outcome variance in the group receiving placebo, as the primary outcome. An increased variance in the antidepressant group would indicate individual differences in response to antidepressants.

RESULTS

We analysed 222 RCTs that investigated 19 different antidepressants compared with placebo in 345 comparisons, comprising a total of 61144 adults with an MDD diagnosis. Across all comparisons, the VR for raw endpoint scores was 0.98 (95% CI 0.96 to 1.00, I2 = 0%) and 1.00 (95% CI 0.99 to 1.02, I2 = 0%) for baseline-to-endpoint change scores.

CONCLUSION

Based on these data, we cannot reject the null hypothesis of equal variances in the antidepressant group and the placebo group. Given that RCTs cannot provide direct evidence for individual treatment effects, it may be most reasonable to assume that the average effect of antidepressants applies also to the individual patient.

A Bayesian approach to joint modeling of matrix-valued imaging data and treatment outcome with applications to depression studies

In this paper, we propose a unified Bayesian joint modeling framework for studying association between a binary treatment outcome and a baseline matrix-valued predictor. Specifically, a joint modeling approach relating an outcome to a matrix-valued predictor through a probabilistic formulation of multilinear principal component analysis is developed. This framework establishes a theoretical relationship between the outcome and the matrix-valued predictor, although the predictor is not explicitly expressed in the model. Simulation studies are provided showing that the proposed method is superior or competitive to other methods, such as a two-stage approach and a classical principal component regression in terms of both prediction accuracy and estimation of association; its advantage is most notable when the sample size is small and the dimensionality in the imaging covariate is large. Finally, our proposed joint modeling approach is shown to be a very promising tool in an application exploring the association between baseline electroencephalography data and a favorable response to treatment in a depression treatment study by achieving a substantial improvement in prediction accuracy in comparison to competing methods.

Targeted exome sequencing identifies five novel loci at genome-wide significance for modulating antidepressant response in patients with major depressive disorder

In order to determine the role of single nucleotide variants (SNVs) in modulating antidepressant response, we conducted a study, consisting of 929 major depressive disorder (MDD) patients, who were treated with antidepressant drugs (drug-only) or in combination with a repetitive transcranial magnetic stimulation (plus-rTMS), followed by targeted exome sequencing analysis. We found that the "plus-rTMS" patients presented a more effective response to the treatment when compared to the 'drug-only' group. Our data firstly demonstrated that the SNV burden had a significant impact on the antidepressant response presented in the "drug-only" group, but was limited in the "plus-rTMS" group. Further, after controlling for overall SNV burden, seven single nucleotide polymorphisms (SNPs) at five loci, IL1A, GNA15, PPP2CB, PLA2G4C, and GBA, were identified as affecting the antidepressant response at genome-wide significance (P < 5 × 10^-08). Additional multiple variants achieved a level of correction for multiple testing, including GNA11, also shown as a strong signal for MDD risk. Our study showed some promising evidence on genetic variants that could be used as individualized therapeutic guides for MDD patients.

Exploratory analyses of effect modifiers in the antidepressant treatment of major depression: Individual-participant data meta-analysis of 2803 participants in seven placebo-controlled randomized trials

BACKGROUND

It is clinically important to know who are likely to respond more or less to antidepressants. However, meaningful effect modifiers (variables associated with differential response depending on the treatment) are yet to be identified.

METHODS

We conducted individual participant data (IPD) meta-analysis and meta-regression to explore effect modifiers in placebo-controlled antidepressant trials conducted so far in Japan.

RESULTS

We obtained access to IPD from seven placebo-controlled trials comparing bupropion, duloxetine, escitalopram, mirtazapine, paroxetine or venlafaxine with placebo in the acute phase treatment of major depression (total n = 2803). The higher the guilt subscale score of the baseline Hamilton Rating Scale for Depression (HRSD), the greater the difference in reduction in depression severity between the antidepressants and placebo at week 6, while the older the current age or the age at onset, the smaller the difference. At week 8, the guilt subscale score of HRSD and presence of suicidal ideation at baseline predicted greater, and the anhedonia subscale and insomnia subscale scores of HRSD and early response at week 2 predicted smaller, difference in reduction.

LIMITATIONS

Different studies measured different sets of baseline variables and we were able to analyze only a limited set of candidate variables for effect modification.

CONCLUSION

Age, age at onset, several HRSD subscales including guilt, anhedonia and insomnia, presence of suicidal ideation at baseline and early response are potential effect modifiers for response to antidepressants in the acute phase antidepressant treatment of major depression. Future trials need to measure these and additional variables in concerted efforts to enable matching of treatments with individual characteristics in depression.

Probing prefrontal cortex hemodynamic alterations during facial emotion recognition for major depression disorder through functional near-infrared spectroscopy

OBJECTIVE

A serious issue in psychiatric practice is a lack of specific, objective biomarker to assist clinicians in establishing differential diagnosis and improving individualized treatment. Major depression disorder (MDD) is characterized by poorer ability in processing of facial emotional expressions.

APPROACH

Applying a portable neuroimaging system using near-infrared spectroscopy, we investigated the prefrontal cortex hemodynamic activation changes during facial emotion recognition and rest periods for 27 MDD patients compared with 24 healthy controls (HC).

MAIN RESULTS

The hemodynamic changes in the left prefrontal cortex for the MDD group showed significant differences in the median values and the Mayer wave power ratios of the oxygenated hemoglobin (oxy-Hb) and deoxygenated hemoglobin (deoxy-Hb) during the emotional face recognition compared with the HC subjects, indicating the abnormal oxidative metabolism and weaker local hemodynamic oscillations for the MDD. The mean cross wavelet coefficients and the average wavelet coherence coefficient between oxy-Hb and deoxy-Hb over the left prefrontal cortex, and also between the bilateral oxy-Hb in the MDD patients were significantly lower than the HC group, demonstrating abnormal locally functional connectivity over the left prefrontal cortex, and the inter-hemispheric connection between the bilateral prefrontal cortices.

SIGNIFICANCE

These results suggested that the hemodynamic changes over the left prefrontal cortex and between the bilateral prefrontal cortices detected by fNIRS could provide reliable predictors for the diagnosis of the depression in clinic, and also supported the rationale for use of transcranial magnetic stimulation over the left dorsolateral prefrontal cortex to restore excitability of prefrontal cortex that exhibits diminished regulation of emotion-generative systems in the MDD patients.

Is the HPA Axis as Target for Depression Outdated, or Is There a New Hope?

Major depressive disorder (MDD) is a very common stress-related mental disorder that carries a huge burden for affected patients and the society. It is associated with a high mortality that derives from suicidality and the development of serious medical conditions such as heart diseases, diabetes, and stroke. Although a range of effective antidepressants are available, more than 50% of the patients do not respond to the first treatment they are prescribed and around 30% fail to respond even after several treatment attempts. The heterogeneous condition of MDD, the lack of biomarkers matching patients with the right treatments and the situation that almost all available drugs are only targeting the serotonin, norepinephrine, or dopamine signaling, without regulating other potentially dysregulated systems may explain the insufficient treatment status. The hypothalamic-pituitary-adrenal (HPA) axis is one of these other systems, there is numerous and robust evidence that it is implicated in MDD and other stress-related conditions, but up to date there is no specific drug targeting HPA axis components that is approved and no test that is routinely used in the clinical setting identifying patients for such a specific treatment. Is there still hope after these many years for a breakthrough of agents targeting the HPA axis? This review will cover tests detecting altered HPA axis function and the specific treatment options such as glucocorticoid receptor (GR) antagonists, corticotropin-releasing hormone 1 (CRH₁) receptor antagonists, tryptophan 2,3-dioxygenase (TDO) inhibitors and FK506 binding protein 5 (FKBP5) receptor antagonists.

Intraday Activity Levels May Better Reflect the Differences Between Major Depressive Disorder and Bipolar Disorder Than Average Daily Activity Levels

It is important to establish an objective index to differentiate mood disorders (i.e., bipolar disorder; BD and major depressive disorder; MDD). The present study focused on the pattern of changes of physical activity in the amount of activity intraday, and examined the relationship between activity patterns and mood disorders. One hundred and eighteen inpatients with MDD or BD in a depressive state provided the activity data by using wearable activity trackers for 3 weeks. In order to illuminate the characteristic patterns of intraday activities, Principal Component Analysis (PCA) was adopted to extract the main components of intraday activity changes. We found that some of the PCs reflected the differences between the types of mood disorder. BD participants showed high activity pattern in the morning and low activity pattern in evenings. However, MDD showed the opposite. Our results suggest that activity tracking focused on daytime activity patterns may provide objective auxiliary diagnostic information.

Alterations in Systemic and Cognitive Glucocorticoid Sensitivity in Depression

BACKGROUND

Decades of research point to cortisol insensitivity as a biomarker of depression. Despite a vast literature on cortisol's effects on memory, the role of cortisol insensitivity in core psychological features of depression, such as emotional memory biases, is unknown.

METHODS

Sixty-five premenopausal women with varying levels of depression completed this study involving an at-home low-dose dexamethasone suppression test and four experimental sessions (i.e., two visits for memory encoding of emotionally arousing pictures, each of which was followed 48 hours later by a recall test). Participants received 20 mg of oral cortisol (CORT) or placebo prior to encoding. We tested whether systemic cortisol insensitivity measured with the dexamethasone suppression test predicted cognitive sensitivity to CORT, which was operationalized as the change in negatively biased memory formation for pictures encoded following CORT versus placebo administration.

RESULTS

Cortisol insensitivity was associated with more severe depression and flatter diurnal cortisol levels. Cortisol insensitivity predicted negative memory bias for pictures encoded during the placebo session and reduction in negative memory bias for pictures encoded during the CORT (compared with placebo) session, even after accounting for psychiatric symptomatology.

CONCLUSIONS

Our findings replicate research showing that cortisol insensitivity predicts depression severity and flatter diurnal cortisol levels. The results further suggest that systemic cortisol insensitivity is related to negative memory bias and its alleviation by cortisol administration. These novel cognitive findings tie together knowledge regarding endocrine and psychological dysfunction in depression and suggest that boosting cortisol signal may cognitively benefit individuals with cortisol insensitivity.

Effect of Damaging Rare Mutations in Synapse-Related Gene Sets on Response to Short-term Antipsychotic Medication in Chinese Patients With Schizophrenia: A Randomized Clinical Trial

IMPORTANCE

The underlying mechanism for individual differences in patient response to antipsychotic medication remains unknown.

OBJECTIVE

To discover genes and gene sets harboring rare variants associated with short-term antipsychotic medication efficacy.

DESIGN, SETTING, AND PARTICIPANTS

In this multicenter, open-label, randomized clinical trial conducted between July 6, 2010, and December 31, 2011, 3023 patients recruited in China of Chinese Han descent with schizophrenia with total Positive and Negative Syndrome Scale (PANSS) score ≥ 60 received a 6-week treatment of antipsychotic medications randomly chosen from 5 atypical and 2 typical antipsychotic medications. Whole-exome sequencing (WES) was performed in 316 participants (grouped into those with the best response [n=156] and those who had no response [n=160] to the antipsychotic medication prescribed), according to the total PANSS score reduction rate after 6 weeks of treatment. Validation was performed using targeted sequencing in an independent sample of 1920 patients. Data analyses was performed between March 15, 2016, and March 1, 2017.

MAIN OUTCOMES AND MEASURES

Drug efficacy at week 6 was assessed according to the change in PANSS scores from baseline. Extremely good and extremely poor responders were selected for an initial WES association study, from which a subset of genes showing putative association was selected for independent replication with a targeted sequencing approach.

RESULTS

Of the 3023 patients (1549 [51.24%] female and 1474 [48.8%] male; mean [SD] age, 31.2 [7.9] years), 2336 (77.3%) were eligible for genetic analysis. After quality-control exclusions, 316 patients (10.5%) were included for WES and 1920 (63.5%) were included for replication. In the WES discovery stage, 2 gene sets (reduced NMDA [N-methyl-D-aspartate]-mediated synaptic currents and reduced AMPA [α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid]-mediated synaptic currents) were found to be enriched with rare damaging variants in the nonresponder group, suggesting the involvement of these gene sets in antipsychotic medication efficacy. Reduced NMDA-mediated synaptic currents gene set was further replicated in an independent sample using targeting sequencing. No statistically significant differences in antipsychotic drug response were found among the patients who received different antipsychotic drugs.

CONCLUSIONS AND RELEVANCE

Genetic variation in glutamatergic or NMDA neurotransmission is implicated in short-term antipsychotic medication efficacy; WES may have utility in the study of rare genetic variation in pharmacogenetics.

TRIAL REGISTRATION

Chinese Clinical Trials Registry Identifier: ChiCTR-TRC-10000934.

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.

INFLUENCE OF THE SEROTONERGIC SYSTEM POLYMORPHISM ON THE EXPRESSION OF DENTAL ANXIETY

- The aim of the study was to test the correlation between 5-HTTLPR polymorphism and dental anxiety. Research hypothesis was that positive relation between the expression of dental anxiety and the S allele exists in the population of healthy Caucasians. We conducted a prospective study on 159 subjects, volunteers made up of medical and non-medical staff of the Sestre milosrdnice University Hospital Centre. Both genders were included, age range 19 to 59, mentally and physically healthy (according to DSM-5 classification of mental disorders). For the purpose of this research, we used a sociodemographic questionnaire containing the following information: age, gender, education level, work status, marital status and residence. Corah's Dental Anxiety Scale-Revised (DAS-R) was used to measure dental anxiety. Data distribution was tested by Kolmogorov-Smirnov test, difference between the groups by ?χ2-test and one-way analysis of variance, and correlation of variables by logistic regression. In the study population, we found positive correlation between S-allele and total result in DAS-R questionnaire. The presence of S allele suggests that the person will have a higher result in DAS-R questionnaire, i.e. higher expression of dental anxiety.

Pharmacogenetic evaluation of a DISP1 gene variant in antidepressant treatment of obsessive-compulsive disorder

OBJECTIVES

A recent genome-wide association study (GWAS) in obsessive-compulsive disorder (OCD) reported a significant marker in the dispatched homolog 1 (Drosophila) gene (DISP1 gene) associated with serotonin reuptake inhibitor (SRI) antidepressant response (Qin et al., ). DISP1 has never been examined before in terms of association with SRI response until this GWAS. We attempt to replicate the GWAS finding by investigating the association of the DISP1 rs17162912 polymorphism with SRI response in our sample of 112 European Caucasian OCD patients.

METHODS

Patients were previously treated naturalistically with up to 6 different SRIs sequentially, including 5 selective SRIs (fluoxetine, fluvoxamine, sertraline, paroxetine, and citalopram) and 1 SRI (clomipramine). Each medication trial was evaluated retrospectively for response and was rated categorically as either responder or nonresponder using the Clinical Global Impression-Improvement scale. Fisher's exact test was used to investigate the relationship between the DISP1 rs17162912 genotype distribution and SRI response.

RESULTS

We did not observe a significant association between rs17162912 and SRI response (p = .32).

CONCLUSION

This replication study did not support the role of DISP1 in predicting SRI response in OCD; however, methodological differences between the original GWAS and our study, as well as limited power and low minor allele frequency, may have hindered replication.

How to measure glucocorticoid receptor's sensitivity in patients with stress-related psychiatric disorders

Stress is a state of derailed homeostasis and a main environmental risk factor for psychiatric diseases. Chronic or uncontrollable stress may lead to a dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis, which is a common feature of stress-related psychiatric disorders. One of the key mechanisms underlying a disturbed HPA axis is an impaired function of the glucocorticoid receptor (GR) with an enhanced or reduced feedback sensitivity for glucocorticoids and subsequently altered concentrations of peripheral cortisol. GR function is regulated by a multiprotein complex including the different expression of the hsp90 co-chaperone FK 506 binding protein 51 (FKBP5) that may be genetically determined or acquired in response to stressful stimuli. Specific patterns of a dysregulation of the HPA axis and GR function are found in different stress-related psychiatric entities e.g. major depression, job-related exhaustion or posttraumatic stress disorder. GR challenge tests like the dexamethasone-suppression test (DST), the dexamethasone-corticotropin-releasing hormone (dex-CRH) test or most recently the analysis of the dexamethasone-induced gene expression are employed to sensitively measure HPA axis activity in these disorders. They provide information for a stratification of phenotypic similar but neurobiological diverse psychiatric disorders. In this review we present a synopsis of GR challenge tests with a focus on the application of the DST, the CRH test and the dex-CRH test as well as the dexamethasone-induced gene expression in stress-related psychiatric entities.

The MAKE Biomarker Discovery for Enhancing anTidepressant Treatment Effect and Response (MAKE BETTER) Study: Design and Methodology

OBJECTIVE

Depression is associated with a major disease burden, and many individuals suffer from depressive symptoms due to an insufficient response to ostensibly adequate antidepressant treatment. Therefore, it is important to identify reliable treatment response predictors for use in developing personalized treatment strategies.

METHODS

The MAKE Biomarker discovery for Enhancing anTidepressant Treatment Effect and Response (MAKE BETTER) study was performed to identify predictors of antidepressant response using a 2-year naturalistic prospective design. Participants in the MAKE BETTER study were consecutively recruited from patients who visited the Psychiatry Department of Chonnam National University Hospital, Gwangju, South Korea for treatment of a depressive disorder. Data on demographic and clinical characteristics, genetic markers measured by whole-exome sequencing, and blood markers were obtained. The types and doses of antidepressants were determined based on the clinical judgment of the psychiatrist, and the treatment outcomes (e.g., depressive and other psychiatric symptoms and issues related to safety) were assessed.

RESULTS

We will be able to use the data collected in this study to develop a treatment-response prediction index composed of biomarkers.

CONCLUSION

The MAKE BETTER study will provide an empirical basis for a personalized medicine approach to depression by enabling the prediction of antidepressant treatment response according the characteristics of each patient. It will thereby support evidence-based decision-making that decreases the use of a trial-and-error approach to the treatment of depressive disorders.

Using Cognitive Neuroscience to Improve Mental Health Treatment: A Comprehensive Review

Mental health interventions do not yet offer complete, client-defined functional recovery, and novel directions in treatment research are needed to improve the efficacy of available interventions. One promising direction is the integration of social work and cognitive neuroscience methods, which provides new opportunities for clinical intervention research that will guide development of more effective mental health treatments that holistically attend to the biological, social, and environmental contributors to disability and recovery. This article reviews emerging trends in cognitive neuroscience and provides examples of how these advances can be used by social workers and allied professions to improve mental health treatment. We discuss neuroplasticity, which is the dynamic and malleable nature of the brain. We also review the use of risk and resiliency biomarkers and novel treatment targets based on neuroimaging findings to prevent disability, personalize treatment, and make interventions more targeted and effective. The potential of treatment research to contribute to neuroscience discoveries regarding brain change is considered from the experimental-medicine approach adopted by the National Institute of Mental Health. Finally, we provide resources and recommendations to facilitate the integration of cognitive neuroscience into mental health research in social work.

LATENT CLASS MODELING USING MATRIX COVARIATES WITH APPLICATION TO IDENTIFYING EARLY PLACEBO RESPONDERS BASED ON EEG SIGNALS

Latent class models are widely used to identify unobserved subgroups (i.e., latent classes) based upon one or more manifest variables. The probability of belonging to each subgroup is typically modeled as a function of a set of measured covariates. In this paper, we extend existing latent class models to incorporate matrix covariates. This research is motivated by a randomized placebo-controlled depression clinical trial. One study goal is to identify a subgroup of subjects who experience symptoms improvement early on during antidepressant treatment, which is considered to be an indication of a placebo rather than a true pharmacological response. We want to relate the likelihood of belonging to this subgroup of early responders to baseline electroencephalography (EEG) measurement that takes the form of a matrix. The proposed method is built upon a low rank Candecomp/Parafac (CP) decomposition of the target coefficient matrix through low-dimensional latent variables, which effectively reduces the model dimensionality. We adopt a Bayesian hierarchical modeling approach to estimate the latent variables, which allows a flexible way to incorporate prior knowledge about covariate effect heterogeneity and offers a data-driven method of regularization. Simulation studies suggest that the proposed method is robust against potentially misspecified rank in the CP decomposition. With the motivating example we show how the proposed method can be applied to extract valuable information from baseline EEG measurements that explains the likelihood of belonging to the early responder subgroup, helping to identify placebo responders and suggesting new targets for the study of placebo response.

Epigenomics of Major Depressive Disorders and Schizophrenia: Early Life Decides

Brain development is guided by the interactions between the genetic blueprint and the environment. Epigenetic mechanisms, especially DNA methylation, can mediate these interactions and may also trigger long-lasting adaptations in developmental programs that increase the risk of major depressive disorders (MDD) and schizophrenia (SCZ). Early life adversity is a major risk factor for MDD/SCZ and can trigger persistent genome-wide changes in DNA methylation at genes important to early, but also to mature, brain function, including neural proliferation, differentiation, and synaptic plasticity, among others. Moreover, genetic variations controlling dynamic DNA methylation in early life are thought to influence later epigenomic changes in SCZ. This finding corroborates the high genetic load and a neurodevelopmental origin of SCZ and shows that epigenetic responses to the environment are, at least in part, genetically controlled. Interestingly, genetic variants influencing DNA methylation are also enriched in risk variants from genome-wide association studies (GWAS) on SCZ supporting a role in neurodevelopment. Overall, epigenomic responses to early life adversity appear to be controlled to different degrees by genetics in MDD/SCZ, even though the potential reversibility of epigenomic processes may offer new hope for timely therapeutic interventions in MDD/SCZ.

Effects of Selective Serotonin Reuptake Inhibitors on Interregional Relation of Serotonin Transporter Availability in Major Depression

Selective serotonin reuptake inhibitors (SSRIs) modulate serotonergic neurotransmission by blocking reuptake of serotonin from the extracellular space. Up to now, it remains unclear how SSRIs achieve their antidepressant effect. However, task-based and resting state functional magnetic resonance imaging studies, have demonstrated connectivity changes between brain regions. Here, we use positron emission tomography (PET) to quantify SSRI's main target, the serotonin transporter (SERT), and assess treatment-induced molecular changes in the interregional relation of SERT binding potential (BP_ND). Nineteen out-patients with major depressive disorder (MDD) and 19 healthy controls (HC) were included in this study. Patients underwent three PET measurements with the radioligand [¹¹C]DASB: (1) at baseline, (2) after a first SSRI dose; and (3) following at least 3 weeks of daily intake. Controls were measured once with PET. Correlation analyses were restricted to brain regions repeatedly implicated in MDD pathophysiology. After 3 weeks of daily SSRI administration a significant increase in SERT BP_ND correlations of anterior cingulate cortex and insula with the amygdala, midbrain, hippocampus, pallidum and putamen (p < 0.05; false discovery rate, FDR corrected) was revealed. No significant differences were found when comparing MDD patients and HC at baseline. These findings are in line with the clinical observation that treatment response to SSRIs is often achieved only after a latency of several weeks. The elevated associations in interregional SERT associations may be more closely connected to clinical outcomes than regional SERT occupancy measures and could reflect a change in the regional interaction of serotonergic neurotransmission during antidepressant treatment.

The COMT Val158Met Polymorphism Is Associated With Response to Add-on Dextromethorphan Treatment in Bipolar Disorder

PURPOSE/BACKGROUND

We previously conducted a randomized, double-blind, controlled, 12-week study evaluating the effect of add-on dextromethorphan (DM), a noncompetitive N-methyl-D-aspartate receptor antagonist, on patients with bipolar disorder (BD) treated using valproate (VPA), which showed negative clinical differences. The genetic variation between each individual may be responsible for interindividual differences. The catechol-O-methyltransferase (COMT) gene has been a candidate gene for BD. In the current study, we investigated whether the COMT Val158Met polymorphism predicts treatment response to VPA + add-on DM and to VPA + placebo.

METHODS/PROCEDURES

Patients with BD (n = 309) undergoing regular VPA treatments were randomly assigned to groups given either add-on DM (30 mg/d) (n = 102), DM (60 mg/d) (n = 101), or placebo (n = 106) for 12 weeks. The Hamilton Depression Rating Scale and Young Mania Rating Scale were used to evaluate clinical response during weeks 0, 1, 2, 4, 8, and 12. The genotypes of the COMT Val158Met polymorphism were determined using polymerase chain reaction plus restriction fragment length polymorphism analysis. To adjust for within-subject dependence over repeated assessments, multiple linear regression with generalized estimating equation methods was used.

FINDINGS/RESULTS

When stratified by the COMT Val158Met genotypes, significantly greater decreases in Hamilton Depression Rating Scale scores were found in the VPA + DM (30 mg/d) group in patients with the Val/Met genotype (P = 0.008).

CONCLUSIONS

We conclude that the COMT Val158Met polymorphism may influence responses to DM (30 mg/d) by decreasing depressive symptoms in BD patients.

Time-dependent effects of dexamethasone plasma concentrations on glucocorticoid receptor challenge tests

Glucocorticoid challenge tests such as the dexamethasone suppression test (DST) and the combined dexamethasone/corticotropin-releasing hormone (dex-CRH) test are considered to be able to sensitively measure hypothalamic-pituitary-adrenal (HPA) axis activity in stress-related psychiatric and endocrine disorders. We used mass-spectrometry to assess the relationship of plasma dexamethasone concentrations and the outcome of these tests in two independent cohorts. Dexamethasone concentrations were measured after oral ingestion of 1.5mg dexamethasone in two cohorts that underwent a standard (dexamethasone at 23:00h) as well as modified (18:00h) DST and dex-CRH test. The first study population was a case/control cohort of 105 depressed patients and 133 controls in which peripheral blood mRNA expression was also measured. The second was a cohort of 261 depressed patients that underwent a standard dex-CRH test at baseline and after 12 weeks' treatment with cognitive-behavioral therapy or antidepressants. Dexamethasone concentrations explained significant proportions of the variance in the DST in both the first (24.6%) and the second (5.2%) cohort. Dexamethasone concentrations explained a higher proportion of the variance in the dex-CRH test readouts, with 41.9% of the cortisol area under the curve (AUC) in the first sample and 24.7% in the second sample. In contrast to these strong effects at later time points, dexamethasone concentrations did not impact cortisol or ACTH concentrations or mRNA expression 3hours after ingestion. In the second sample, dexamethasone concentrations at baseline and week 12 were highly correlated, independent of treatment type and response status. Importantly, a case/control effect in the Dex-CRH test was only apparent when controlling for dexamethasone concentrations. Our results suggest that the incorporation of plasma dexamethasone concentration or measures of earlier endocrine read-outs may help to improve the assessment of endocrine dysfunction in depression.

Epigenetic Biomarkers of Preterm Birth and Its Risk Factors

A biomarker is a biological measure predictive of a normal or pathogenic process or response. Biomarkers are often useful for making clinical decisions and determining treatment course. One area where such biomarkers would be particularly useful is in identifying women at risk for preterm delivery and related pregnancy complications. Neonates born preterm have significant morbidity and mortality, both in the perinatal period and throughout the life course, and identifying women at risk of delivering preterm may allow for targeted interventions to prevent or delay preterm birth (PTB). In addition to identifying those at increased risk for preterm birth, biomarkers may be able to distinguish neonates at particular risk for future complications due to modifiable environmental factors, such as maternal smoking or alcohol use during pregnancy. Currently, there are no such biomarkers available, though candidate gene and epigenome-wide association studies have identified DNA methylation differences associated with PTB, its risk factors and its long-term outcomes. Further biomarker development is crucial to reducing the health burden associated with adverse intrauterine conditions and preterm birth, and the results of recent DNA methylation studies may advance that goal.

Nanosensors for early cancer detection and for therapeutic drug monitoring

The use of nanotechnology for drug delivery in cancer therapy has raised high expectations. Additionally, the use of nanomaterials in sensors to extract and detect tumor specific biomarkers, circulating tumor cells, or extracellular vesicles shed by the tumor holds the promise to detect cancer much earlier and hence improve long-term survival of the patients. Moreover, the monitoring of the anticancer drug concentration, which has a narrow therapeutic window, will allow for a personalized dosing of the drug and will lead to improved therapeutic outcome and life quality of the patient. This review will provide an overview on the use of nanosensors for the early diagnosis of cancer and for the therapeutic drug monitoring, giving some examples. We envision nanosensors to make significant improvements in the cancer management as easy-to-use point-of-care devices for a broad population of users.

ALDH2 polymorphism, associated with attenuating negative symptoms in patients with schizophrenia treated with add-on dextromethorphan

OBJECTIVE

Increasing the evidence of inflammation's contribution to schizophrenia; using anti-inflammatory or neurotrophic therapeutic agents to see whether they improve schizophrenia treatment. Dextromethorphan (DM), a non-competitive N-methyl-d-aspartate (NMDA) receptor antagonist, might protect monoamine neurons. Whether treating schizophrenia with risperidone plus add-on DM is more effective than risperidone (RISP) alone, and the association between the ALDH2 polymorphism and treatment response were investigated.

METHODS

A double-blind study in which patients with schizophrenia were randomly assigned to the RISP + DM (60 mg/day; n = 74) or the RISP + Placebo (n = 75) group. The Positive and Negative Syndrome Scale (PANSS) and the Scale for the Assessment of Negative Symptoms (SANS) scores were used to evaluate clinical response during weeks 0, 1, 2, 4, 6, 8, and 11. The genotypes of the ALDH2 polymorphism were determined using polymerase chain reactions plus restriction fragment length polymorphism analysis. A generalized estimating equation was used to analyze the effects of ALDH2 polymorphism on the clinical performance of DM.

RESULTS

PANSS and SANS scores were significantly lower in both groups after 11 weeks of treatment. SANS total scores were significantly lower in the RISP + DM group in patients with the ALDH2*2*2 genotype.

CONCLUSIONS

RISP plus add-on DM treatment reduced negative schizophrenia symptoms in patients with the ALDH2 polymorphism.

ABCB1 gene variants and antidepressant treatment outcome: A meta-analysis

The efflux pump P-glycoprotein (P-gp), a gene product of the ABCB1 gene, plays a pivotal role in the transfer of various molecules across the blood-brain barrier. P-gp protects the brain by selectively extruding its substrates, including certain antidepressive drugs, thereby limiting their uptake into the brain. Uhr et al. [2008] first showed that ABCB1 variants predicted the remission to antidepressants with P-gp substrate properties in patients suffering from major depression (MD). Other studies investigating the influence of ABCB1 polymorphisms on antidepressant treatment response produced inconclusive results. In this meta-analysis, we systematically summarized 16 pharmacogenetic studies focused on the association of ABCB1 variants and antidepressant treatment outcome in patients with MD (overall n = 2695). We investigated the association of treatment outcome and six ABCB1 single nucleotide polymorphisms (SNPs): rs2032583, rs2235015, rs2235040, rs1045642, rs2032582, rs1128503. We stratified for admission status, ethnicity, and prescription of concomitant medication. SNP rs2032583 showed a nominally significant association across all studies (P = 0.035, SNP was studied in a total of 2,037 patients) and a significant Bonferroni-corrected association among inpatients (P = 1.5 × 10(-05) , n = 485). Also SNP rs2235015 was significantly associated with antidepressant treatment outcome withstanding Bonferroni correction (P = 3.0 × 10(-04) ) among inpatients in a smaller subsample (n = 195). There were no significant associations of the other SNPs tested with antidepressant treatment outcome. Future pharmacogenetic association studies should focus on the role of the ABCB1 SNP rs2032583 in antidepressant outcome prediction.

The current and potential impact of genetics and genomics on neuropsychopharmacology

One justification for the major scientific and financial investments in genetic and genomic studies in medicine is their therapeutic potential, both for revealing novel targets for drugs which treat the disease process, as well as allowing for more effective and safe use of existing medications. This review considers the extent to which this promise has yet been realised within psychopharmacology, how things are likely to develop in the foreseeable future, and the key issues involved. It draws primarily on examples from schizophrenia and its treatments. One observation is that there is evidence for a range of genetic influences on different aspects of psychopharmacology in terms of discovery science, but far less evidence that meets the standards required before such discoveries impact upon clinical practice. One reason is that results reveal complex genetic influences that are hard to replicate and usually of very small effect. Similarly, the slow progress being made in revealing the genes that underlie the major psychiatric syndromes hampers attempts to apply the findings to identify novel drug targets. Nevertheless, there are some intriguing positive findings of various kinds, and clear potential for genetics and genomics to play an increasing and major role in psychiatric drug discovery.

Serotonin transporter gene polymorphisms: Relation with platelet serotonin level in patients with primary Sjogren's syndrome

Significantly lower platelet serotonin level (PSL) in patients with primary Sjogren's syndrome (pSS) than in healthy controls has been reported in our prior studies. In the present report, we demonstrated effect of functional polymorphisms in the serotonin transporter gene (5-HTT) on PSL. We describe a group of 61 pSS patients and 100 healthy individuals subjects, who received PSL measurement in our prior study. All subjects were genotyped for the promoter 5-HTTLPR (L/S), rs25531 (A/G) and intronic 5-HTTVNTRin2 (l/s) polymorphisms. Overall, the presence of 5-HTTVNTRin2 ss genotype was associated with significantly lower PSL in pSS patients, not in healthy controls. Reduced PSL in pSS patients is in line with hypothesis of association between chronic immunoinflammation and 5-HT system dysregulation, identifying additional mechanisms such as altered 5-HT transport as potential genetic factor contributing to PSL depletion.

Cordance derived from REM sleep EEG as a biomarker for treatment response in depression--a naturalistic study after antidepressant medication

OBJECTIVE

To evaluate whether prefrontal cordance in theta frequency band derived from REM sleep EEG after the first week of antidepressant medication could characterize the treatment response after 4 weeks of therapy in depressed patients.

METHOD

20 in-patients (15 females, 5 males) with a depressive episode and 20 healthy matched controls were recruited into 4-week, open label, case-control study. Patients were treated with various antidepressants. No significant differences in age (responders (mean ± SD): 45 ± 22) years; non-responders: 49 ± 12 years), medication or Hamilton Depression Rating Scale (HAM-D) score (responders: 23.8 ± 4.5; non-responders 24.5 ± 7.6) at inclusion into the study were found between responders and non-responders. Response to treatment was defined as a ≥50% reduction of HAM-D score at the end of four weeks of active medication. Sleep EEG of patients was recorded after the first and the fourth week of medication. Cordance was computed for prefrontal EEG channels in theta frequency band during tonic REM sleep.

RESULTS

The group of 8 responders had significantly higher prefrontal theta cordance in relation to the group of 12 non-responders after the first week of antidepressant medication. This finding was significant also when controlling for age, gender and number of previous depressive episodes (F1,15 = 6.025, P = .027). Furthermore, prefrontal cordance of all patients showed significant positive correlation (r = 0.52; P = .019) with the improvement of HAM-D score between the inclusion week and fourth week of medication.

CONCLUSIONS

The results suggest that prefrontal cordance derived from REM sleep EEG could provide a biomarker for the response to antidepressant treatment in depressed patients.

Personalized medicine in neurodegenerative diseases: how far away?

Neurodegenerative diseases are characterized by progressive dysfunction of the nervous system as a result of neuronal loss in the brain and spinal cord. Despite extensive research efforts aimed at development of new disease-modifying therapeutics, there is still no effective treatment to halt neurodegenerative processes. Thus, modification of current therapeutic and diagnostic research strategies is a goal of increasing urgency. The biggest limitation in neurodegenerative disease research is the lack of appropriate biomarkers. Discovery of universal biomarkers capable of diagnosing patients with neurodegenerative diseases, monitoring their response to therapy, and predicting disease progression seems to be a tall order. Instead, a combination of different methodologies in the discovery of biomarkers specific for each described aspect of the disease seems to be a more viable approach. Although application of personalized medicine in diagnosis and treatment of neurodegenerative diseases may seem far off, some recent developments, such as utilizing specific biological therapies in multiple sclerosis, microRNA profiling as a source of novel biomarkers in Parkinson’s disease, or combination of neuroimaging and proteomic analyses in diagnosis of Alzheimer’s disease patients, already point to the way clinical neurology may integrate new achievements in everyday practice. Combination of genomic, proteomic, glycomic, and metabolomic approaches may yield novel insights into molecular mechanisms of disease pathophysiology, which could then be integrated and translated into clinical neurology. Based on the developments during the past decade, it is feasible to predict that a personalized approach to treating neurological disorders will become more widely applicable in the coming years.

Redesigning antidepressant drug discovery

Antidepressant drug discovery and development have been put on hold by many pharmaceutical companies. The main reason for this is the negative efficacy studies with novel specific drugs. Here I argue that the main obstacles are the absence of gene tests and biomarkers as an integral part of a diagnostic process. Further, too much emphasis has been put on validating drug candidates in animal models of psychiatric disorders. A more rapid transfer of drug candidates into human research is necessary to overcome current obstacles that prevent the discovery of next-generation antidepressants.

The clinical application of ABCB1 genotyping in antidepressant treatment: a pilot study

BACKGROUND

The gene product of the ABCB1 gene, the P-glycoprotein, functions as a custodian molecule in the blood-brain barrier and regulates the access of most antidepressants into the brain. Previous studies showed that ABCB1 polymorphisms predicted the response to antidepressants that are substrates of the P-gp, while the response to nonsubstrates was not influenced by ABCB1 polymorphisms. The aim of the present study was to evaluate the clinical application of ABCB1 genotyping in antidepressant pharmacotherapy.

METHODS

Data came from 58 depressed inpatients participating in the Munich Antidepressant Response Signature (MARS) project, whose ABCB1 gene test results were implemented into the clinical decision making process. Hamilton Depression Rating Scale (HAM-D) scores, remission rates, and duration of hospital stay were documented with dose and kind of antidepressant treatment.

RESULTS

Patients who received ABCB1 genotyping had higher remission rates [χ2(1) = 6.596, p = 0.005, 1-sided] and lower Hamilton sores [t(111) = 2.091, p = 0.0195, 1-sided] at the time of discharge from hospital as compared to patients without ABCB1 testing. Among major allele homozygotes for ABCB1 single nucleotide polymorphisms (SNPs) rs2032583 and rs2235015 (TT/GG genotype), an increase in dose was associated with a shorter duration of hospital stay [rho(28) = -0.441, p = 0.009, 1-sided], whereas other treatment strategies (eg, switching to a nonsubstrate) showed no significant associations with better treatment outcome. Discussion The implementation of ABCB1 genotyping as a diagnostic tool influenced clinical decisions and led to an improvement of treatment outcome. Patients carrying the TT/GG genotype seemed to benefit from an increase in P-gp substrate dose.

CONCLUSION

Results suggest that antidepressant treatment of depression can be optimized by the clinical application of ABCB1 genotyping.

Genotype variant associated with add-on memantine in bipolar II disorder

Memantine is a non-competitive N-methyl-d-asparate (NMDA) receptor antagonist with a mood-stabilizing effect. We investigated whether using valproic acid (VPA) plus add-on memantine to treat bipolar II disorder (BP-II) is more effective than using VPA alone (VPA + Pbo). We also evaluated, in BP-II patients, the association between the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism with treatment response to VPA + add-on memantine and to VPA + Pbo. In this randomized, double-blind, controlled 12 wk study, BP-II patients undergoing regular VPA treatments were randomly assigned to a group: VPA + Memantine (5 mg/day) (n = 115) or VPA + Pbo (n = 117). The Hamilton Depression Rating Scale (HDRS) and Young Mania Rating Scale (YMRS) were used to evaluate clinical response during week 0, 1, 2, 4, 8 and 12. The genotypes of the BDNF Val66Met polymorphisms were determined using polymerase chain reactions plus restriction fragment length polymorphism analysis. To adjust within-subject dependence over repeated assessments, multiple linear regression with generalized estimating equation methods was used to analyze the effects of the BDNF Val66Met polymorphism on the clinical performance of memantine. Both groups showed significantly decreased YMRS and HDRS scores after 12 wk of treatment; the differences between groups were non-significant. When stratified by the BDNF Val66Met genotypes, significantly greater decreases in HDRS scores were found in the VPA + memantine group in patients with the Val Met genotype (p = 0.004). We conclude that the BDNF Val66Met polymorphism influenced responses to add-on memantine by decreasing depressive symptoms in patients with BP-II.

Acid peptic diseases: pharmacological approach to treatment

Acid peptic disorders are the result of distinctive, but overlapping pathogenic mechanisms leading to either excessive acid secretion or diminished mucosal defense. They are common entities present in daily clinical practice that, owing to their chronicity, represent a significant cost to healthcare. Key elements in the success of controlling these entities have been the development of potent and safe drugs based on physiological targets. The histamine-2 receptor antagonists revolutionized the treatment of acid peptic disorders owing to their safety and efficacy profile. The proton-pump inhibitors (PPIs) represent a further therapeutic advance due to more potent inhibition of acid secretion. Ample data from clinical trials and observational experience have confirmed the utility of these agents in the treatment of acid peptic diseases, with differential efficacy and safety characteristics between and within drug classes. Paradigms in their speed and duration of action have underscored the need for new chemical entities that, from a single dose, would provide reliable duration of acid control, particularly at night. Moreover, PPIs reduce, but do not eliminate, the risk of ulcers in patients taking NSAIDs, reflecting untargeted physiopathologic pathways and a breach in the ability to sustain an intragastric pH of more than 4. This review provides an assessment of the current understanding of the physiology of acid production, a discussion of medications targeting gastric acid production and a review of efficacy in specific acid peptic diseases, as well as current challenges and future directions in the treatment of acid-mediated diseases.

Immune changes and neurotransmitters: possible interactions in depression?

A disturbed metabolism of catecholamines and other neurotransmitters appears to play a major role in the pathogenesis of neurospychiatric symptoms, such as changes in mood and depression. This symptomatology is common in patients with chronic inflammatory disorders such as infections, autoimmune diseases, or cancer. The pathogenesis of these symptoms is still unclear. Pro-inflammatory stimuli interfere not only with the neural circuits and neurotransmitters of the serotonergic system but also with those of the adrenergic system. The pro-inflammatory cytokine interferon-γ stimulates the biosynthesis of 5,6,7,8-tetrahydrobiopterin (BH4), which is a co-factor for several aromatic amino acid mono-oxygenases and is rate-limiting for the biosynthesis of the neurotransmitter serotonin and the catecholamines dopamine, epinephrine (adrenaline) and norepinephrine (noradrenaline). Interferon-γ triggers the high output of reactive oxygen species in macrophages, which can destroy the oxidation-labile BH4. Recent data suggests that oxidative loss of BH4 in chronic inflammatory conditions can reduce the biosynthesis of catecholamines, which may relate to disturbed adrenergic neurotransmitter pathways in patients.

Integrative biological analysis for neuropsychopharmacology

Although advances in psychotherapy have been made in recent years, drug discovery for brain diseases such as schizophrenia and mood disorders has stagnated. The need for new biomarkers and validated therapeutic targets in the field of neuropsychopharmacology is widely unmet. The brain is the most complex part of human anatomy from the standpoint of number and types of cells, their interconnections, and circuitry. To better meet patient needs, improved methods to approach brain studies by understanding functional networks that interact with the genome are being developed. The integrated biological approaches--proteomics, transcriptomics, metabolomics, and glycomics--have a strong record in several areas of biomedicine, including neurochemistry and neuro-oncology. Published applications of an integrated approach to projects of neurological, psychiatric, and pharmacological natures are still few but show promise to provide deep biological knowledge derived from cells, animal models, and clinical materials. Future studies that yield insights based on integrated analyses promise to deliver new therapeutic targets and biomarkers for personalized medicine.

Prediction of antidepressant treatment response from gray matter volume across diagnostic categories

Dysfunctional limbic, paralimbic and prefrontal brain circuits represent neural substrates of major depression that are targeted by pharmacotherapy. In a high resolution structural magnetic resonance imaging (MRI) study we investigated the potential of variability of the cortex volume to predict the response to antidepressant treatment among patients with major depression. We enrolled 167 patients participating in the Munich Antidepressant Response Signature (MARS) study and employed voxel based morphometry to investigate covariation of gray matter (GM) maps with changes of depression severity over 5 weeks. Larger left hippocampal and bilateral posterior cingulate GM volumes and lower right temporolateral GM volumes were associated with beneficial treatment response. Subcallosal/orbitofrontal GM volumes were associated with treatment response mainly through gender-by-region interactions. A hippocampal/temporolateral composite marker proved robust in both first episode and recurrent unipolar patients and in bipolar patients. Compared with 92 healthy controls, abnormally low volumes were only detected in the left hippocampal area, particularly in recurrent unipolar patients. These findings indicate that variability of the cortex volume of specific brain areas is associated with different response to antidepressants. In addition, hippocampal findings recursively link together unfavorable treatment response and progressive hippocampal structural changes in recurrent depression.