Epigenetic-mediated N -methyl-D-aspartate receptor changes in the brain of isolated reared rats

Aim: We investigated: Grin1, Grin2a, Grin2b DNA methylation; NR1 and NR2 mRNA/protein in the prefrontal cortex (PFC); and hippocampus of male Wistar rats exposed to isolation rearing. Materials & methods: Animals were kept isolated or grouped (n = 10/group) from weaning for 10 weeks. Tissues were dissected for RNA/DNA extraction and N-methyl-D-aspartate receptor subunits were analyzed using quantitative reverse transcription (RT)-PCR, ELISA and pyrosequencing. Results: Isolated-reared animals had: decreased mRNA in PFC for all markers, increased NR1 protein in hippocampus and hypermethylation of Grin1 in PFC and Grin2b in hippocampus, compared with grouped rats. Associations between mRNA/protein and DNA methylation were found for both brain areas. Conclusion: This study indicates that epigenetic DNA methylation may underlie N-methyl-D-aspartate receptor mRNA/protein expression alterations caused by isolation rearing

Observation of the Baryonic Flavor-Changing Neutral Current Decay Lambda_b -> Lambda mu+ mu-

We report the first observation of the baryonic flavor-changing neutral current decay Lambda_b -> Lambda mu+ mu- with 24 signal events and a statistical significance of 5.8 Gaussian standard deviations. This measurement uses ppbar collisions data sample corresponding to 6.8fb-1 at sqrt{s}=1.96TeV collected by the CDF II detector at the Tevatron collider. The total and differential branching ratios for Lambda_b -> Lambda mu+ mu- are measured. We find B(Lambda_b -> Lambda mu+ mu-) = [1.73+-0.42(stat)+-0.55(syst)] x 10^{-6}. We also report the first measurement of the differential branching ratio of B_s -> phi mu+ mu- using 49 signal events. In addition, we report branching ratios for B+ -> K+ mu+ mu-, B0 -> K0 mu+ mu-, and B -> K*(892) mu+ mu- decays.Comment: 8 pages, 2 figures, 4 tables. Submitted to Phys. Rev. Let

Treated Incidence of Psychotic Disorders in the Multinational EU-GEI Study

Importance: Psychotic disorders contribute significantly to the global disease burden, yet the latest international incidence study of psychotic disorders was conducted in the 1980s. Objectives: To estimate the incidence of psychotic disorders using comparable methods across 17 catchment areas in 6 countries and to examine the variance between catchment areas by putative environmental risk factors. Design, Setting, and Participants: An international multisite incidence study (the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions) was conducted from May 1, 2010, to April 1, 2015, among 2774 individuals from England (2 catchment areas), France (3 catchment areas), Italy (3 catchment areas), the Netherlands (2 catchment areas), Spain (6 catchment areas), and Brazil (1 catchment area) with a first episode of nonorganic psychotic disorders (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision [ICD-10] codes F20-F33) confirmed by the Operational Criteria Checklist. Denominator populations were estimated using official national statistics. Exposures: Age, sex, and racial/ethnic minority status were treated as a priori confounders. Latitude, population density, percentage unemployment, owner-occupied housing, and single-person households were treated as catchment area-level exposures. Main Outcomes and Measures: Incidence of nonorganic psychotic disorders (ICD-10 codes F20-F33), nonaffective psychoses (ICD-10 codes F20-F29), and affective psychoses (ICD-10 codes F30-F33) confirmed by the Operational Criteria Checklist. Results: A total of 2774 patients (1196 women and 1578 men; median age, 30.5 years [interquartile range, 23.0-41.0 years]) with incident cases of psychotic disorders were identified during 12.9 million person-years at risk (crude incidence, 21.4 per 100 000 person-years; 95% CI, 19.4-23.4 per 100 000 person-years). A total of 2183 patients (78.7%) had nonaffective psychotic disorders. After direct standardization for age, sex, and racial/ethnic minority status, an 8-fold variation was seen in the incidence of all psychotic disorders, from 6.0 (95% CI, 3.5-8.6) per 100 000 person-years in Santiago, Spain, to 46.1 (95% CI, 37.3-55.0) per 100 000 person-years in Paris, France. Rates were elevated in racial/ethnic minority groups (incidence rate ratio, 1.6; 95% CI, 1.5-1.7), were highest for men 18 to 24 years of age, and were lower in catchment areas with more owner-occupied homes (incidence rate ratio, 0.8; 95% CI, 0.7-0.8). Similar patterns were observed for nonaffective psychoses; a lower incidence of affective psychoses was associated with higher area-level unemployment (incidence rate ratio, 0.3; 95% CI, 0.2-0.5). Conclusions and Relevance: This study confirmed marked heterogeneity in risk for psychotic disorders by person and place, including higher rates in younger men, racial/ethnic minorities, and areas characterized by a lower percentage of owner-occupied houses.The European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) Project is funded by grant agreement HEALTH-F2-2010-241909 (Project EU-GEI) from the European Community’s Seventh Framework Programme. The Brazilian study was funded by grant 2012/0417-0 from the São Paulo Research Foundation. Dr Kirkbride is funded by the Wellcome Trust and grant 101272/Z/13/Z from the Royal Society. Ms Jongsma and Dr Jones are funded by the National Institute of Health Research Collaboration of Leadership in Applied Health Research and Care East of England

Lifetime cannabis use and childhood trauma associated with CNR1 genetic variants increase the risk of psychosis: findings from the STREAM study

Objectives: Gene-environment interactions increase the risk of psychosis. The objective of this study was to investigate gene-gene and gene-environment interactions in psychosis, including single nucleotide variants (SNVs) of dopamine-2 receptor (D2R), N-methyl-d-aspartate receptor (NMDAR), and cannabinoid receptor type 1 (CB1R), lifetime cannabis use, and childhood trauma. Methods: Twenty-three SNVs of genes encoding D2R (DRD2: rs1799978, rs7131056, rs6275), NMDAR (GRIN1: rs4880213, rs11146020; GRIN2A: rs1420040, rs11866328; GRIN2B: rs890, rs2098469, rs7298664), and CB1R (CNR1: rs806380, rs806379, rs1049353, rs6454674, rs1535255, rs2023239, rs12720071, rs6928499, rs806374, rs7766029, rs806378, rs10485170, rs9450898) were genotyped in 143 first-episode psychosis patients (FEPp) and 286 communitybased controls by Illumina HumanCoreExome-24 BeadChip. Gene-gene and gene-environment associations were assessed using nonparametric Multifactor Dimensionality Reduction software. Results: Single-locus analyses among the 23 SNVs for psychosis and gene-gene interactions were not significant (p 4 0.05 for all comparisons); however, both environmental risk factors showed an association with psychosis (p o 0.001). Moreover, gene-environment interactions were significant for an SNV in CNR1 and cannabis use. The best-performing model was the combination of CNR1 rs12720071 and lifetime cannabis use (p o 0.001), suggesting an increased risk of psychosis. Conclusion: Our study supports the hypothesis of gene-environment interactions for psychosis involving T-allele carriers of CNR1 SNVs, childhood trauma, and cannabis use

The EUropean Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI): Incidence and First-Episode Case-Control Programme.

PURPOSE: The EUropean Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) study contains an unparalleled wealth of comprehensive data that allows for testing hypotheses about (1) variations in incidence within and between countries, including by urbanicity and minority ethnic groups; and (2) the role of multiple environmental and genetic risk factors, and their interactions, in the development of psychotic disorders. METHODS: Between 2010 and 2015, we identified 2774 incident cases of psychotic disorders during 12.9 million person-years at risk, across 17 sites in 6 countries (UK, The Netherlands, France, Spain, Italy, and Brazil). Of the 2774 incident cases, 1130 cases were assessed in detail and form the case sample for case-control analyses. Across all sites, 1497 controls were recruited and assessed. We collected data on an extensive range of exposures and outcomes, including demographic, clinical (e.g. premorbid adjustment), social (e.g. childhood and adult adversity, cannabis use, migration, discrimination), cognitive (e.g. IQ, facial affect processing, attributional biases), and biological (DNA via blood sample/cheek swab). We describe the methodology of the study and some descriptive results, including representativeness of the cohort. CONCLUSIONS: This resource constitutes the largest and most extensive incidence and case-control study of psychosis ever conducted.The EU-GEI Study is funded by grant agreement HEALTH-F2-2010-241909 (Project EU-GEI) from the European Community’s Seventh Framework Programme, and grant 2012/0417-0 from the São Paulo Research Foundatio

Development and Validation of Predictive Model for a Diagnosis of First Episode Psychosis Using the Multinational EU-GEI Case-control Study and Modern Statistical Learning Methods

Background and Hypothesis: It is argued that availability of diagnostic models will facilitate a more rapid identification of individuals who are at a higher risk of first episode psychosis (FEP). Therefore, we developed, evaluated, and validated a diagnostic risk estimation model to classify individual with FEP and controls across six countries. Study Design: We used data from a large multi-center study encompassing 2627 phenotypically well-defined participants (aged 18-64 years) recruited from six countries spanning 17 research sites, as part of the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions study. To build the diagnostic model and identify which of important factors for estimating an individual risk of FEP, we applied a binary logistic model with regularization by the least absolute shrinkage and selection operator. The model was validated employing the internal-external cross-validation approach. The model performance was assessed with the area under the receiver operating characteristic curve (AUROC), calibration, sensitivity, and specificity. Study Results: Having included preselected 22 predictor variables, the model was able to discriminate adults with FEP and controls with high accuracy across all six countries (rangesAUROC=0.84-0.86). Specificity (range=73.9-78.0%) and sensitivity (range=75.6-79.3%) were equally good, cumulatively indicating an excellent model accuracy; though, calibration slope for the diagnostic model showed a presence of some overfitting when applied specifically to participants from France, the UK, and The Netherlands. Conclusions: The new FEP model achieved a good discrimination and good calibration across six countries with different ethnic contributions supporting its robustness and good generalizability.</p