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Biological Psychiatry

Monday, February 8, 2016

February 2016

Effect of the Putative Lithium Mimetic Ebselen on Brain Myo-Inositol, Sleep, and Emotional Processing in Humans 


Neuropsychopharmacology

Abstract

Lithium remains the gold standard in treating bipolar disorder but has unwanted toxicity and side effects. We previously reported that ebselen inhibits inositol monophosphatase (IMPase) and exhibits lithium-like effects in animal models through lowering of inositol. Ebselen has been tested in clinical trials for other disorders, enabling us to determine for the first time the effect of a blood–brain barrier-penetrant IMPase inhibitor on human central nervous system (CNS) function. We now report that in a double-blind, placebo-controlled trial with healthy participants, acute oral ebselen reduced brain myo-inositol in the anterior cingulate cortex, consistent with CNS target engagement. Ebselen decreased slow-wave sleep and affected emotional processing by increasing recognition of some emotions, decreasing latency time in the acoustic startle paradigm, and decreasing the reinforcement of rewarding stimuli. In summary, ebselen affects the phosphoinositide cycle and has CNS effects on surrogate markers that may be relevant to the treatment of bipolar disorder that can be tested in future clinical trials.



Cross-trial prediction of treatment outcome in depression: a machine learning approach


The Lancet 

Abstract

Background
Antidepressant treatment efficacy is low, but might be improved by matching patients to interventions. At present, clinicians have no empirically validated mechanisms to assess whether a patient with depression will respond to a specific antidepressant. We aimed to develop an algorithm to assess whether patients will achieve symptomatic remission from a 12-week course of citalopram.

Methods
We used patient-reported data from patients with depression (n=4041, with 1949 completers) from level 1 of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D; ClinicalTrials.gov, number NCT00021528) to identify variables that were most predictive of treatment outcome, and used these variables to train a machine-learning model to predict clinical remission. We externally validated the model in the escitalopram treatment group (n=151) of an independent clinical trial (Combining Medications to Enhance Depression Outcomes [COMED]; ClinicalTrials.gov, number NCT00590863).

Findings
We identified 25 variables that were most predictive of treatment outcome from 164 patient-reportable variables, and used these to train the model. The model was internally cross-validated, and predicted outcomes in the STAR*D cohort with accuracy significantly above chance (64·6% [SD 3·2]; p<0·0001). The model was externally validated in the escitalopram treatment group (N=151) of COMED (accuracy 59·6%, p=0.043). The model also performed significantly above chance in a combined escitalopram-buproprion treatment group in COMED (n=134; accuracy 59·7%, p=0·023), but not in a combined venlafaxine-mirtazapine group (n=140; accuracy 51·4%, p=0·53), suggesting specificity of the model to underlying mechanisms.

Interpretation
Building statistical models by mining existing clinical trial data can enable prospective identification of patients who are likely to respond to a specific antidepressant..



The Human Connectome Project


Navigate the brain in a way that was never before possible; fly through major brain pathways, compare essential circuits, zoom into a region to explore the cells that comprise it, and the functions that depend on it.

The Human Connectome Project aims to provide an unparalleled compilation of neural data, an interface to graphically navigate this data and the opportunity to achieve never before realized conclusions about the living human brain.



Association of Age at Menopause and Duration of Reproductive Period With Depression After Menopause


JAMA Psychiatry
  
Abstract

Importance  
Estrogens have neuroprotective and antidepressive effects; however, associations between indices of reduced endogenous estrogens and risk for postmenopausal depression have not been systematically explored.

Objective  
To investigate the association of age at menopause and the duration of the reproductive period with the risk for depression among postmenopausal women with naturally occurring menopause.

Data Sources  
A search strategy for use of MEDLINE was developed (through January 1, 2015) using the key terms menopause, climacteric, reproductive period, depression, and mood disorders. References of included studies and reviews were also screened; authors were contacted to maximize synthesized evidence.

Study Selection  
A total of 12 323 articles, without language restriction, were screened by pairs of reviewers to identify observational studies related to the study hypothesis; 14 studies were eligible for meta-analysis.

Data Extraction and Synthesis  
Pairs of reviewers independently extracted information on study design and type of analysis by participants’ characteristics and methods of depression ascertainment. Study quality was assessed using the Newcastle-Ottawa Scale, and fixed- or random-effects models were implemented.

Main Outcomes and Measures  
Pooled-effect estimates for depression, defined by psychiatric evaluation or validated instruments, by age at menopause and duration of the reproductive period.

Results  
The 14 studies included in the meta-analysis represented 67 714 women. An inverse association (reported as odds ratio [OR]; 95% CI of 2-year increments) with depression in postmenopausal women was shown for increasing age at menopause (0.98; 0.96-0.99 [67 434 unique participants; 13 studies]) and duration of the reproductive period (0.98; 0.96-0.99 [54 715 unique participants; 5 studies]). Menopause at age 40 or more years compared with premature menopause was associated with a 50% decreased risk for depression (3033 unique participants; 4 studies). Pooling of studies examining severe depression showed a 5% decrease in risk of severe depression with increasing (2-year increment) age at menopause (52 736 unique participants; 3 studies); sensitivity analysis of studies controlling for past depression revealed similar results for age at menopause (0.98; 0.96-1.00 [48 894 unique participants; 3 studies). No heterogeneity or publication bias was evident in the main analyses.

Conclusions and Relevance  
Longer exposure to endogenous estrogens, expressed as older age at menopause and longer reproductive period, is associated with a lower risk of depression in later life. Identifying women at higher risk for depression due to early menopause who could benefit from psychiatric intervention or estrogen-based therapies could be useful in the clinical setting.



Intergenerational Transmission of Stress in Humans 


Neuropsychopharmacology

Abstract

The hypothesis that offspring are affected by parental trauma or stress exposure, first noted anecdotally, is now supported empirically by data from Holocaust survivor offspring cohorts and other populations. These findings have been extended to less extreme forms of stress, where differential physical, behavioral, and cognitive outcomes are observed in affected offspring. Parental stress-mediated effects in offspring could be explained by genetics or social learning theory. Alternatively, biological variations stemming from stress exposure in parents could more directly have an impact on offspring, a concept we refer to here as ‘intergenerational transmission’, via changes to gametes and the gestational uterine environment. We further extend this definition to include the transmission of stress to offspring via early postnatal care, as animal studies demonstrate the importance of early maternal care of pups in affecting offsprings’ long-term behavioral changes. Here, we review clinical observations in offspring, noting that offspring of stress- or trauma-exposed parents may be at greater risk for physical, behavioral, and cognitive problems, as well as psychopathology. Furthermore, we review findings concerning offspring biological correlates of parental stress, in particular, offspring neuroendocrine, epigenetic, and neuroanatomical changes, in an attempt to determine the extent of parental stress effects. Although understanding the etiology of effects in offspring is currently impeded by methodological constraints, and limitations in our knowledge, we summarize current information and conclude by presenting hypotheses that have been prompted by recent studies in the field..



Cannabis use is associated with 3 years earlier onset of schizophrenia spectrum disorder in a naturalistic, multi-site sample


Schizophrenia Research

Abstract

Background
Patients with schizophrenia spectrum disorders and substance use may have an earlier onset of illness compared to those without substance use. Most previous studies have, however, too small samples to control for confounding variables and the effect of specific types of substances. The present study aimed to examine the relationship between substance use and age at onset, in addition to the influence of possible confounders and specific substances, in a large and heterogeneous multisite sample of patients with schizophrenia spectrum disorders.

Methods
The patients (N = 1119) were recruited from catchment areas in Oslo, Stavanger and Bergen, Norway, diagnosed according to DSM-IV and screened for substance use history. Linear regression analysis was used to examine the relationship between substance use and age at onset of illness.

Results
Patients with substance use (n = 627) had about 3 years earlier age at onset (23.0 years; SD 7.1) than the abstinent group (n = 492; 25.9 years; SD 9.7). Only cannabis use was statistically significantly related to earlier age at onset. Gender or family history of psychosis did not influence the results.

Conclusion
Cannabis use is associated with 3 years earlier onset of psychosis.



Type 2 Diabetes Mellitus in Youth Exposed to Antipsychotics


JAMA Psychiatry

Abstract

Importance  
Antipsychotics are used increasingly in youth for nonpsychotic and off-label indications, but cardiometabolic adverse effects and (especially) type 2 diabetes mellitus (T2DM) risk have raised additional concern.

Objective  
To assess T2DM risk associated with antipsychotic treatment in youth.

Data Sources  
Systematic literature search of PubMed and PsycINFO without language restrictions from database inception until May 4, 2015. Data analyses were performed in July 2015, and additional analyses were added in November 2015.

Study Selection  
Longitudinal studies reporting on T2DM incidence in youth 2 to 24 years old exposed to antipsychotics for at least 3 months.

Data Extraction and Synthesis  
Two independent investigators extracted study-level data for a random-effects meta-analysis and meta-regression of T2DM risk.

Main Outcomes and Measures  
The coprimary outcomes were study-defined T2DM, expressed as cumulative T2DM risk or as T2DM incidence rate per patient-years. Secondary outcomes included the comparison of the coprimary outcomes in antipsychotic-treated youth with psychiatric controls not receiving antipsychotics or with healthy controls

Results  
Thirteen studies were included in the meta-analysis, including 185 105 youth exposed to antipsychotics and 310 438 patient-years. The mean (SD) age of patients was 14.1 (2.1) years, and 59.5% were male. The mean (SD) follow-up was 1.7 (2.3) years. Among them, 7 studies included psychiatric controls (1 342  121 patients and 2 071 135 patient-years), and 8 studies included healthy controls (298 803 patients and 463 084 patient-years). Antipsychotic-exposed youth had a cumulative T2DM risk of 5.72 (95% CI, 3.45-9.48; P < .001) per 1000 patients. The incidence rate was 3.09 (95% CI, 2.35-3.82; P < .001) cases per 1000 patient-years. Compared with healthy controls, cumulative T2DM risk (odds ratio [OR], 2.58; 95% CI, 1.56-4.24; P < .0001) and incidence rate ratio (IRR) (IRR, 3.02; 95% CI, 1.71-5.35; P < .0001) were significantly greater in antipsychotic-exposed youth. Similarly, compared with psychiatric controls, antipsychotic-exposed youth had significantly higher cumulative T2DM risk (OR, 2.09; 95% CI, 1.50-5 2.90; P  < .0001) and IRR (IRR, 1.79; 95% CI, 1.31-2.44; P < .0001). In multivariable meta-regression analyses of 10 studies, greater cumulative T2DM risk was associated with longer follow-up (P < .001), olanzapine prescription (P < .001), and male sex (P = .002) (r2 = 1.00, P < .001). Greater T2DM incidence was associated with second-generation antipsychotic prescription (P ≤ .050) and less autism spectrum disorder diagnosis (P = .048) (r2 = 0.21, P = .044).

Conclusions and Relevance  
Although T2DM seems rare in antipsychotic-exposed youth, cumulative risk and exposure-adjusted incidences and IRRs were significantly higher than in healthy controls and psychiatric controls. Olanzapine treatment and antipsychotic exposure time were the main modifiable risk factors for T2DM development in antipsychotic-exposed youth. Antipsychotics should be used judiciously and for the shortest necessary duration, and their efficacy and safety should be monitored proactively.



Schizophrenia risk from complex variation of complement component 4


Nature

Abstract

Schizophrenia is a heritable brain illness with unknown pathogenic mechanisms. Schizophrenia’s strongest genetic association at a population level involves variation in the major histocompatibility complex (MHC) locus, but the genes and molecular mechanisms accounting for this have been challenging to identify. Here we show that this association arises in part from many structurally diverse alleles of the complement component 4 (C4) genes. We found that these alleles generated widely varying levels of C4A and C4B expression in the brain, with each common C4 allele associating with schizophrenia in proportion to its tendency to generate greater expression of C4A. Human C4 protein localized to neuronal synapses, dendrites, axons, and cell bodies. In mice, C4 mediated synapse elimination during postnatal development. These results implicate excessive complement activity in the development of schizophrenia and may help explain the reduced numbers of synapses in the brains of individuals with schizophrenia.



Metformin treatment of antipsychotic-induced dyslipidemia: an analysis of two randomized, placebo-controlled trials


Molecular Psychiatry

Abstract

Dyslipidemia is one of the most common adverse effects in schizophrenia patients treated with antipsychotics. However, there are no established effective treatments. In this study, data were pooled from two randomized, placebo-controlled trials, which were originally designed to examine the efficacy of metformin in treating antipsychotic-induced weight gain and other metabolic abnormalities. In total, 201 schizophrenia patients with dyslipidemia after being treated with an antipsychotic were assigned to take 1000 mg day–1 metformin (n=103) or placebo (n=98) for 24 weeks, with evaluation at baseline, week 12 and week 24. The primary outcome was the low-density lipoprotein cholesterol (LDL-C) levels. After metformin treatment, the mean difference in the LDL-C value between metformin treatment and placebo was from 0.16 mmol l–1 at baseline to –0.86 mmol l–1 at the end of week 24, decreased by 1.02 mmol l–1 (P<0.0001); and 25.3% of patients in the metformin group had LDL-C ≥3.37 mmol l–1, which is significantly <64.8% in the placebo group (P<0.001) at week 24. Compared with the placebo, metformin treatment also have a significant effect on reducing weight, body mass index, insulin, insulin resistance index, total cholesterol and triglyceride, and increasing high-density lipoprotein cholesterol. The treatment effects on weight and insulin resistance appeared at week 12 and further improved at week 24, but the effects on improving dyslipidemia only significantly occurred at the end of week 24. We found that metformin treatment was effective in improving antipsychotic-induced dyslipidemia and insulin resistance, and the effects improving antipsychotic-induced insulin resistance appeared earlier than the reducing dyslipidemia.



Temporal Cognitive Decline Associated With Exposure to Infectious Agents in a Population-based, Aging Cohort.


Alzheimer Disease

Abstract

Background:
Numerous cross-sectional studies have related exposure to neurotropic infectious agents with cognitive dysfunction in older adults, however, the temporal sequence is uncertain.


Methods:
In a representative, well-characterized, population-based aging cohort, we determined whether the temporal trajectories of multiple cognitive domains are associated with exposure to cytomegalovirus (CMV), Herpes Simplex virus, type 1 (HSV-1), Herpes Simplex virus, type 2 (HSV-2), or Toxoplasma gondii (TOX). Complex attention, executive functions, memory, language, and visuospatial function were assessed annually for 5 years among consenting individuals. Study entry IgG antibody titers indexing exposure to each infectious agent were examined in relation to slopes of subsequent temporal cognitive decline using multiple linear regressions adjusted for potential confounders.


Results:
The IgG levels for HSV-2 were significantly associated with baseline cognitive domain scores (N=1022 participants). Further, the IgG levels for HSV-2, TOX, and CMV, but not HSV-1 were significantly associated with greater temporal cognitive decline that varied by type of infection.


Conclusions:
Exposure to CMV, HSV-2, or TOX is associated with cognitive deterioration in older individuals, independent of general age-related variables. An increased understanding of the role of infectious agents in cognitive decline may lead to new methods for its prevention and treatment.




Online Journals:




Biological Psychiatry - Volume 79, Issue 5, March 2016



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