Cross-sectional association between metabolic parameters and psychotic-like experiences in a population-based sample of middle-aged and elderly individuals

Background: Metabolic alterations are often found in patients with clinical psychosis early in the course of the disorder. Psychotic-like experiences are observed in the general population, but it is unclear whether these are associated with markers of metabolism. Methods: A population-based cohort of 1890 individuals (mean age 58.0 years; 56.3% women) was included. Metabolic parameters were measured by body-mass index (BMI), concentrations of low-density and high-density lipoprotein cholesterol (LDL-C and HDL-C), total cholesterol, triglycerides, and fasting glucose and insulin in blood. Frequency and distress ratings of psychotic-like experiences from the positive symptom dimension of the Community Assessment of Psychic Experience questionnaire were assessed. Cross-sectional associations were analysed using linear regression analyses. Results: Higher BMI was associated with higher frequency of psychotic-like experiences (adjusted mean difference: 0.04, 95% CI 0.02–0.06) and more distress (adjusted mean difference: 0.02, 95% CI 0.01–0.03). Lower LDL-C was associated with more psychotic-like experiences (adjusted mean difference: −0.23, 95% CI −0.40 to −0.06). When restricting the sample to those not using lipid-lowering medication, the results of BMI and LDL-C remained and an association between lower HDL-C and higher frequency of psychotic-like experiences was found (adjusted mean difference: −0.37, 95% CI −0.69 to −0.05). We observed no significant associations between cholesterol, triglycerides, glucose, insulin or homeostatic model assessment and psychotic-like experiences. Conclusions: In a population-based sample of middle-aged and elderly individuals, higher BMI and lower LDL-C were associated with psychotic-like experiences. This suggests that metabolic markers are associated with psychotic-like experiences across the vulnerability spectrum.</p

Molecular Sex Differences in Human Serum

Background: Sex is an important factor in the prevalence, incidence, progression, and response to treatment of many medical conditions, including autoimmune and cardiovascular diseases and psychiatric conditions. Identification of molecular differences between typical males and females can provide a valuable basis for exploring conditions differentially affected by sex. Methodology/Principal Findings: Using multiplexed immunoassays, we analyzed 174 serum molecules in 9 independent cohorts of typical individuals, comprising 196 males and 196 females. Sex differences in analyte levels were quantified using a meta-analysis approach and put into biological context using k-means to generate clusters of analytes with distinct biological functions. Natural sex differences were established in these analyte groups and these were applied to illustrate sexually dimorphic analyte expression in a cohort of 22 males and 22 females with Asperger syndrome. Reproducible sex differences were found in the levels of 77 analytes in serum of typical controls, and these comprised clusters of molecules enriched with distinct biological functions. Analytes involved in fatty acid oxidation/hormone regulation, immune cell growth and activation, and cell death were found at higher levels in females, and analytes involved in immune cell chemotaxis and other indistinct functions were higher in males. Comparison of these naturally occurring sex differences against a cohort of people with Asperger syndrome indicated that a cluster of analytes that had functions related to fatty acid oxidation/hormone regulation was associated with sex and the occurren

Towards a blood-based diagnostic panel for bipolar disorder

BACKGROUND: Bipolar disorder (BD) is a costly, devastating and life shortening mental disorder that is often misdiagnosed, especially on initial presentation. Misdiagnosis frequently results in ineffective treatment. We investigated the utility of a biomarker panel as a diagnostic test for BD. METHODS AND FINDINGS: We performed a meta-analysis of eight case-control studies to define a diagnostic biomarker panel for BD. After validating the panel on established BD patients, we applied it to undiagnosed BD patients. We analysed 249 BD, 122 pre-diagnostic BD, 75 pre-diagnostic schizophrenia and 90 first onset major depression disorder (MDD) patients and 371 controls. The biomarker panel was identified using ten-fold cross-validation with lasso regression applied to the 87 analytes available across the meta-analysis studies. We identified 20 protein analytes with excellent predictive performance [area under the curve (AUC)?0.90]. Importantly, the panel had a good predictive performance (AUC 0.84) to differentiate 12 misdiagnosed BD patients from 90 first onset MDD patients, and a fair to good predictive performance (AUC 0.79) to differentiate between 110 pre-diagnostic BD patients and 184 controls. We also demonstrated the disease specificity of the panel. CONCLUSIONS: An early and accurate diagnosis has the potential to delay or even prevent the onset of BD. This study demonstrates the potential utility of a biomarker panel as a diagnostic test for BD.We would like to thank all participants of this study as well as all participating centres for the collaboration and for access to the serum samples. We gratefully acknowledge support by the Stanley Medical Research Institute (no. 07R-1888). The infrastructure for the NESDA study (www.nesda.nl) has been funded through the Geestkracht program of the Netherlands Organisation for Health Research and Development (Zon-Mw, grant number 10-000-1002) and participating universities (VU University Medical Center, Leiden University Medical Center, University Medical Center Groningen). DNC, DWN and NSW efforts were funded by the Stanley Medical Research Institute and the US Department of the Army

Cardiac responses during picture viewing in young male patients with schizophrenia

Previous research investigating emotion recognition ability in patients with schizophrenia has mainly focused on the recognition of facial expressions. To broaden our understanding of emotional processes in patients with schizophrenia, this study aimed to investigate whether these patients experience and process other emotionally evocative stimuli differently from healthy participants. To investigate this, we measured the cardiac and subjective responses of 33 male patients (9 with and 24 without antipsychotic medication) and 40 male control subjects to emotion-eliciting pictures. Cardiac responses were chosen as an outcome measure because previous research has indicated that these are linked with attentional and emotional processes and provide a more objective measure than self-report measures alone. The differences in cardiac responses between patients and controls were limited to medicated patients: only the medicated patients showed significantly decreased cardiac orienting responses compared with control subjects, regardless of picture contents. These results indicate that medicated patients directed less attention towards emotion-eliciting pictures than controls. Decreased attentional resources while processing emotional evocative stimuli could lead to incorrect appraisals of the environment, and may have detrimental emotional and social consequences, contributing to chronic stress levels and increased risk for cardiovascular disease

The relation between AKT1, cannabis use and metabolic risk factors in psychosis

Background: Cardiovascular and metabolic problems combined with a bad lifestyle are a major cause of a shortened life expectancy in chronic psychotic disorders. While the incidence of cannabis use is twice as high in psychosis compared to the general population, use of cannabis has been associated with better outcomes on cardiometabolic risk factors. This study investigates whether this effect is mediated by the AKT1 gene, as activation of the related enzyme by cannabis may cause changes in metabolism. Methods: Patients with a recent onset psychosis (n=623) were included from a cohort study (GROUP). Cannabis use, based on self-report and urine screening, was related to Body Mass index (BMI). Next the mediating effects of six AKT1 polymorphisms (rs1130214, rs1130233, rs2494732, rs2498784, rs3730358 and rs3803300) were investigated. Results: There was a strong, negative association between BMI and cannabis use. Moreover, two SNP's (rs1130233 and rs2494732) showed an association with cannabis use, but did not mediate the effect of cannabis on BMI. Conclusion: In conclusion, cannabis use results in a lower body weight in patients with a psychosis. While AKT1 is related to cannabis use, it does not affect body mass via AKT1. Instead, AKT1 risk alleles may increase the incidence of cannabis use. Future studies may investigate whether other genes mediate the effect between cannabis and metabolic risk factors

Changes in peripheral blood compounds following psychopharmacological treatment in drug-naïve first-episode patients with either schizophrenia or major depressive disorder: A meta-analysis

Background This meta-analysis on peripheral blood compounds in drug-naïve first-episode patients with either schizophrenia or major depressive disorder (MDD) examined which compounds change following psychopharmacological treatment. Methods The Embase, PubMed and PsycINFO databases were systematically searched for longitudinal studies reporting measurements of blood compounds in drug-naïve first-episode schizophrenia or MDD. Results For this random-effects meta-analysis, we retrieved a total of 31 studies comprising 1818 schizophrenia patients, and 14 studies comprising 469 MDD patients. Brain-derived neurotrophic factor (BDNF) increased following treatment in schizophrenia (Hedges' g (g): 0.55; 95% confidence interval (CI) 0.39-0.70; p < 0.001) and MDD (g: 0.51; CI 0.06-0.96; p = 0.027). Interleukin (IL)-6 levels decreased in schizophrenia (g: -0.48; CI -0.85 to -0.11; p = 0.011), and for MDD a trend of decreased IL-6 levels was observed (g: -0.39; CI -0.87 to 0.09; p = 0.115). Tumor necrosis factor alpha (TNFα) also decreased in schizophrenia (g: -0.34; CI -0.68 to -0.01; p = 0.047) and in MDD (g: -1.02; CI -1.79 to -0.25; p = 0.009). Fasting glucose levels increased only in schizophrenia (g: 0.26; CI 0.07-0.44; p = 0.007), but not in MDD. No changes were found for C-reactive protein, IL-1β, IL-2 and IL-4. Conclusions Psychopharmacological treatment has modulating effects on BDNF and TNFα in drug-naïve first-episode patients with either schizophrenia or MDD. These findings support efforts for further research into transdiagnostic preventive strategies and augmentation therapy for those with immune dysfunctions

The effect of antipsychotic medication on facial affect recognition in schizophrenia: a review

Patients with schizophrenia suffer from impairments in facial affect recognition and social functioning. Since antipsychotic medication affects different areas in the brain, they may also affect target areas involved in emotional processing mechanisms. In this article, we review the findings of the effect of antipsychotic medication on facial affect recognition in schizophrenia. We searched PubMed for articles in English with the keywords schizophrenia, facial, affect, emotion, antipsychotic and medication, published till January 2008. Eight relevant articles were found describing original studies. No substantial improvements in facial affect recognition were found after treatment with either typical or atypical antipsychotic drugs. Facial affect recognition was not related to neuropsychological functioning, and it was unclear whether improvement of symptom severity was related to performance on the facial affect recognition tasks. It is recommended that future research should focus on measuring social skills and social functioning more directly, and by investigating the effects of additional behavioural treatments on facial affect recognition and social functioning relative to treatment with antipsychotic medication alone<br/

Identification of subgroups of Schizophrenia patients with changes in either immune or growth factor and hormonal pathways

Schizophrenia is a heterogeneous disorder normally diagnosed using the Diagnostic and Statistical Manual of Mental Disorders criteria. However, these criteria do not necessarily reflect differences in underlying molecular abnormalities of the disorder. Here, we have used multiplexed immunoassay analyses to measure immune molecules, growth factors, and hormones important to schizophrenia in acutely ill antipsychotic-naive patients (n = 180) and matched controls (n = 398). We found that using the resulting molecular profiles, we were capable of separating schizophrenia patients into 2 significantly distinct subgroups with predominant molecular abnormalities in either immune molecules or growth factors and hormones. These molecular profiles were tested using an independent cohort, and this showed the same separation into 2 subgroups. This suggests that distinct abnormalities occur in specific molecular pathways in schizophrenia patients. This may be of relevance for intervention studies that specifically target particular molecular mechanisms and could be a first step to further define the complex schizophrenia syndrome based on molecular profiles