We recently reported an association between TAAR6 (trace amine associated receptor 6 gene) variations and schizophrenia (SZ). We now report an association of a set of TAAR6 variations and clinical presentation and outcome in a sample of 240 SZ Korean patients. Patients were selected by a Structured Clinical Interview, DSM-IV Axis I disorders – Clinical Version (SCID-CV). Other psychiatric or neurologic disorders, as well as medical diseases, were exclusion criteria. To assess symptom severity, patients were administered the CGI scale and the PANSS at baseline and at the moment of discharge, 1 month later on average. TAAR6 variations rs6903874, rs7452939, rs8192625 and rs4305745 were investigated; rs6903874, rs7452939 and rs8192625 entered the statistical investigation after LD analysis. Rs8192625 G/G homozygosis was found to be significantly associated both with a worse clinical presentation at PANSS total and positive scores and with a shorter period of illness before hospitalization. No haplotype significant findings were found. The present study stands for a role of the TAAR6 in the clinical presentation of SZ. Moreover, our results show that this genetic effect may be counteracted by a correct treatment. Haplotype analysis was not informative in our sample, probably also because of the incomplete SNPs' coverage of the gene we performed. Further studies in this direction are warranted.

Patients with Parkinson’s disease psychosis (PDP) are often treated with an atypical antipsychotic, especially quetiapine or clozapine, but side effects, lack of sufficient efficacy, or both may motivate a switch to pimavanserin, the first medication approved for management of PDP. How best to implement a switch to pimavanserin has not been clear, as there are no controlled trials or case series in the literature to provide guidance. An abrupt switch may interrupt partially effective treatment or potentially trigger rebound effects from antipsychotic withdrawal, whereas cross-taper involves potential drug interactions. A panel of experts drew from published data, their experience treating PDP, lessons from switching antipsychotic drugs in other populations, and the pharmacology of the relevant drugs, to establish consensus recommendations. The panel concluded that patients with PDP can be safely and effectively switched from atypical antipsychotics used off label in PDP to the recently approved pimavanserin by considering each agent’s pharmacokinetics and pharmacodynamics, receptor interactions, and the clinical reason for switching (efficacy or adverse events). Final recommendations are that such a switch should aim to maintain adequate 5-HT2A antagonism during the switch, thus providing a stable transition so that efficacy is maintained. Specifically, the consensus recommendation is to add pimavanserin at the full recommended daily dose (34 mg) for 2–6 weeks in most patients before beginning to taper and discontinue quetiapine or clozapine over several days to weeks. Further details are provided for this recommendation, as well as for special clinical circumstances where switching may need to proceed more rapidly.

The public health burden of alcohol is unevenly distributed across the life course, with levels of use, abuse, and dependence increasing across adolescence and peaking in early adulthood. Here, we leverage this temporal patterning to search for common genetic variants predicting developmental trajectories of alcohol consumption. Comparable psychiatric evaluations measuring alcohol consumption were collected in three longitudinal community samples (N = 2,126, obs = 12,166). Consumption-repeated measurements spanning adolescence and early adulthood were analyzed using linear mixed models, estimating individual consumption trajectories, which were then tested for association with Illumina 660W-Quad genotype data (866,099 SNPs after imputation and QC). Association results were combined across samples using standard meta-analysis methods. Four meta-analysis associations satisfied our pre-determined genome-wide significance criterion (FDR < 0.1) and six others met our ‘suggestive’ criterion (FDR <0.2). Genome-wide significant associations were highly biological plausible, including associations within GABA transporter 1, SLC6A1 (solute carrier family 6, member 1), and exonic hits in LOC100129340 (mitofusin-1-like). Pathway analyses elaborated single marker results, indicating significant enriched associations to intuitive biological mechanisms, including neurotransmission, xenobiotic pharmacodynamics, and nuclear hormone receptors (NHR). These findings underscore the value of combining longitudinal behavioral data and genome-wide genotype information in order to study developmental patterns and improve statistical power in genomic studies.

Bipolar disorder is a chronic, frequently relapsing illness with a prevalence of 1.2% to 3.4% in the general population. It is associated with high disability, higher comorbidity due to medical illnesses, and significant social and economical consequences for patients, their families, and society. The episodic nature of this disease warrants rational use of medications and proper monitoring for adverse events. Various drug classes, such as mood stabilizers, antipsychotics, benzodiazepines, and antidepressants, are used for the acute and maintenance treatment of bipolar disorder. Each group of drugs is associated with wide array of adverse events and drug interactions, which are the main hurdles in treatment outcome and compliance. Common side effects seen with several agents, particularly antipsychotics, are somnolence, weight gain, extrapyramidal symptoms, dyslipidemia, type-2 diabetes, and hyperprolactinemia. Major drug interactions are seen with drugs such as carbamazepine, due to hepatic enzyme induction. Adverse effects such as somnolence are tolerability concerns and can be managed easily; others, such as diabetes mellitus, are safety concerns. It is prudent to have precise knowledge of the individual drug's side-effect profile, pharmacokinetics, and pharmacodynamics, to plan a treatment regimen. More research is needed to understand potential rish of various drugs and to devise and incorporate monitoring protocols in the treatment regimen.

The clinical use of monoamine oxidase inhibitors (MAOIs) has declined due to concerns about food and drug interactions and waning physician experience. Evidence indicates that MAOIs are effective in depressive disorders, in particular depression with atypical features. Efforts to address safety issues have led to the development of more selective and reversible MAOIs, such as moclobemide. Selegiline, a selective monoamine oxidase B inhibitor, has been approved for the adjunctive treatment of Parkinson's disease at low doses. At higher doses, oral selegiline is also effective in major depressive disorder (MDD) but loses its selectivity and has the potential for tyramine interactions.To overcome these problems, a transdermal formulation of selegiline, the selegiline transdermal system (STS), was developed with novel pharmacokinetic and pharmacodynamic properties. Compared with oral administration, transdermal selegiline leads to sustained plasma concentrations of the parent compound, increasing the amount of drug delivered to the brain and decreasing metabolite production. In addition, STS allows targeted inhibition of central nervous system monoamine A (MAO-A) and monoamine B isoenzymes with minimal effects on MAO-A in the gastrointestinal and hepatic systems, thereby reducing the risk of interactions with tyramine-rich foods (the “cheese-reaction”). Clinical trials have found 6 mg/24 hours of STS to be effective in MDD without the need for dietary restrictions. The efficacy and safety profile of STS supports its use in MDD. It is possible that STS may demonstrate benefit in MDD with atypical features or MDD resistant to other antidepressants. However, more research is needed. Clinicians should familiarize themselves with the properties and indications for the new generation of MAOIs.

Background: We performed a meta-analysis in order to determine which neuropsychological domains and tasks would be most sensitive for discriminating between patients with major depressive disorder (MDD) and healthy controls.

Methods: Relevant articles were identified through a literature search of the PubMed and Cochrane Library databases for the period between January 1997 and May 2011. A meta-analysis was conducted using the standardized means of individual cognitive tests in each domain. The heterogeneity was assessed, and subgroup analyses according to age and medication status were performed to explore the sources of heterogeneity.

Results: A total of 22 trials involving 955 MDD patients and 7,664 healthy participants were selected for our meta-analysis. MDD patients showed significantly impaired results compared with healthy participants on the Digit Span and Continuous Performance Test in the attention domain; the Trail Making Test A (TMT-A) and the Digit Symbol Test in the processing speed domain; the Stroop Test, the Wisconsin Card Sorting Test, and Verbal Fluency in the executive function domain; and immediate verbal memory in the memory domain. The Finger Tapping Task, TMT-B, delayed verbal memory, and immediate and delayed visual memory failed to separate MDD patients from healthy controls. The results of subgroup analysis showed that performance of Verbal Fluency was significantly impaired in younger depressed patients (<60 years), and immediate visual memory was significantly reduced in depressed patients using antidepressants.

Conclusions: Our findings have inevitable limitations arising from methodological issues inherent in the meta-analysis and we could not explain high heterogeneity between studies. Despite such limitations, current study has the strength of being the first meta-analysis which tried to specify cognitive function of depressed patients compared with healthy participants. And our findings may provide clinicians with further evidences that some cognitive tests in specific cognitive domains have sensitivity to discriminate MDD patients from healthy controls.

The importance of including developmental and environmental measures in genetic studies of human pathology is widely acknowledged, but few empirical studies have been published. Barriers include the need for longitudinal studies that cover relevant developmental stages and for samples large enough to deal with the challenge of testing gene–environment–development interaction. A solution to some of these problems is to bring together existing data sets that have the necessary characteristics. As part of the National Institute on Drug Abuse-funded Gene-Environment-Development Initiative, our goal is to identify exactly which genes, which environments, and which developmental transitions together predict the development of drug use and misuse. Four data sets were used of which common characteristics include (1) general population samples, including males and females; (2) repeated measures across adolescence and young adulthood; (3) assessment of nicotine, alcohol, and cannabis use and addiction; (4) measures of family and environmental risk; and (5) consent for genotyping DNA from blood or saliva. After quality controls, 2,962 individuals provided over 15,000 total observations. In the first gene–environment analyses, of alcohol misuse and stressful life events, some significant gene–environment and gene–development effects were identified. We conclude that in some circumstances, already collected data sets can be combined for gene–environment and gene–development analyses. This greatly reduces the cost and time needed for this type of research. However, care must be taken to ensure careful matching across studies and variables.