Lithium in drinking water and suicide rates across the East of England

Lithium can be found naturally in drinking water. In clinical practice, it is widely used in pharmacological doses for the treatment of bipolar disorder; and may also prevent suicidal behaviour in people with mood disorders. In two studies, lithium levels in tap water have been significantly and negatively correlated with suicide. We measured lithium levels in tap water in the 47 subdivisions of the East of England and correlated these with the respective suicide standardised mortality ratio in each subdivision. We found no association between lithium in drinking water and suicide rates across the East of England from 2006 to 2008

Conditional and inducible transgene expression in mice through the combinatorial use of Cre-mediated recombination and tetracycline induction

Here we describe a triple transgenic mouse system, which combines the tissue specificity of any Cre-transgenic line with the inducibility of the reverse tetracycline transactivator (rtTA)/tetracycline-responsive element (tet-O)-driven transgenes. To ensure reliable rtTA expression in a broad range of cell types, we have targeted the rtTA transgene into the ROSA26 locus. The rtTA expression, however, is conditional to a Cre recombinase-mediated excision of a STOP region from the ROSA26 locus. We demonstrate the utility of this technology through the inducible expression of the vascular endothelial growth factor (VEGF-A) during embryonic development and postnatally in adult mice. Our results of adult induction recapitulate several different hepatic and immune cell pathological phenotypes associated with increased systemic VEGF-A protein levels. This system will be useful for studying genes in which temporal control of expression is necessary for the discovery of the full spectrum of functions. The presented approach abrogates the need to generate tissue-specific rtTA transgenes for tissues where well-characterized Cre lines already exist

Ethnic Minority Status, Age-at-Immigration and Psychosis Risk in Rural Environments:Evidence From the SEPEA Study

Objective: Several ethnic minority groups experience elevated rates of first-episode psychosis (FEP), but most studies have been conducted in urban settings. We investigated whether incidence varied by ethnicity, generation status, and age-at-immigration in a diverse, mixed rural, and urban setting. Method: We identified 687 people, 16–35 years, with an ICD-10 diagnosis of FEP, presenting to Early Intervention Psychosis services in the East of England over 2 million person-years. We used multilevel Poisson regression to examine incidence variation by ethnicity, rural–urban setting, generation status, and age-at-immigration, adjusting for several confounders including age, sex, socioeconomic status, population density, and deprivation. Results: People of black African (incidence rate ratio: 4.06; 95% confidence interval [CI]: 2.63–6.25), black Caribbean (4.63; 95% CI: 2.38–8.98) and Pakistani (2.31; 95% CI: 1.35–3.94) origins were at greatest FEP risk relative to the white British population, after multivariable adjustment. Non-British white migrants were not at increased FEP risk (1.00; 95% CI: 0.77–1.32). These patterns were independently present in rural and urban settings. For first-generation migrants, migration during childhood conferred greatest risk of psychotic disorders (2.20; 95% CI: 1.33–3.62). Conclusions: Elevated psychosis risk in several visible minority groups could not be explained by differences in postmigratory socioeconomic disadvantage. These patterns were observed across rural and urban areas of our catchment, suggesting that elevated psychosis risk for some ethnic minority groups is not a result of selection processes influencing rural–urban living. Timing of exposure to migration during childhood, an important social and neurodevelopmental window, may also elevate risk

The Epidemiology of First-Episode Psychosis in Early Intervention in Psychosis Services: Findings From the Social Epidemiology of Psychoses in East Anglia [SEPEA] Study.

OBJECTIVE: Few studies have characterized the epidemiology of first-episode psychoses in rural or urban settings since the introduction of early intervention psychosis services. To address this, the authors conducted a naturalistic cohort study in England, where such services are well established. METHOD: All new first-episode psychosis cases, 16-35 years old, presenting to early intervention psychosis services in the East of England were identified during 2 million person-years follow-up. Presence of ICD-10 F10-33 psychotic disorder was confirmed using OPCRIT [operational criteria for psychotic illness]. Incidence rate ratios were estimated following multivariable Poisson regression, adjusting for age, sex, ethnicity, socioeconomic status, neighborhood-level deprivation, and population density. RESULTS: Of 1,005 referrals, 687 participants (68.4%) fulfilled epidemiological and diagnostic criteria for first-episode psychosis (34.0 new cases per 100,000 person-years; 95% CI=31.5-36.6). Median age at referral was similar for men (22.5 years; interquartile range: 19.5-26.7) and women (23.4 years; interquartile range: 19.5-29.1); incidence rates were highest for men and women before 20 years of age. Rates increased for ethnic minority groups (incidence rate ratio: 1.4; 95% CI=1.1-1.6), as well as with lower socioeconomic status (incidence rate ratio: 1.3; 95% CI=1.2-1.4) and in more urban (incidence rate ratio: 1.4;95%CI=1.0-1.8) and deprived (incidence rate ratio: 2.1; 95% CI=1.3-3.3) neighborhoods, after adjustment for confounders. CONCLUSIONS: Pronounced variation in psychosis incidence, peaking before 20 years old, exists in populations served by early intervention psychosis services. Excess rates were restricted to urban and deprived communities, suggesting that a threshold of socioenvironmental adversity may be necessary to increase incidence. This robust epidemiology can inform service development in various settings about likely population-level need.Wellcome Trust (Sir Henry Wellcome Research Fellowship; Grant ID: WT085540)This is the author accepted manuscript. The final version is available from the American Psychiatric Association via http://dx.doi.org/10.1176/appi.ajp.2016.1601010

Exploring cellular markers of metabolic syndrome in peripheral blood mononuclear cells across the neuropsychiatric spectrum

Recent evidence suggests that comorbidities between neuropsychiatric conditions and metabolic syndrome may precede and even exacerbate long-term side-effects of psychiatric medication, such as a higher risk of type 2 diabetes and cardiovascular disease, which result in increased mortality. In the present study we compare the expression of key metabolic proteins, including the insulin receptor (CD220), glucose transporter 1 (GLUT1) and fatty acid translocase (CD36), on peripheral blood mononuclear cell subtypes from patients across the neuropsychiatric spectrum, including schizophrenia, bipolar disorder, major depression and autism spectrum conditions (n = 25/condition), relative to typical controls (n = 100). This revealed alterations in the expression of these proteins that were specific to schizophrenia. Further characterization of metabolic alterations in an extended cohort of first-onset antipsychotic drug-naïve schizophrenia patients (n = 58) and controls (n = 63) revealed that the relationship between insulin receptor expression in monocytes and physiological insulin sensitivity was disrupted in schizophrenia and that altered expression of the insulin receptor was associated with whole genome polygenic risk scores for schizophrenia. Finally, longitudinal follow-up of the schizophrenia patients over the course of antipsychotic drug treatment revealed that peripheral metabolic markers predicted changes in psychopathology and the principal side effect of weight gain at clinically relevant time points. These findings suggest that peripheral blood cells can provide an accessible surrogate model for metabolic alterations in schizophrenia and have the potential to stratify subgroups of patients with different clinical outcomes or a greater risk of developing metabolic complications following antipsychotic therapy.This work was supported by grants from the Stanley Medical Research Institute (SMRI); the Engineering and Physical Sciences Research Council UK (EPSRC); the Dutch Government-funded Virgo consortium (ref. FES0908); the Netherlands Genomics Initiative (ref. 050-060-452); the European Union FP7 funding scheme: Marie Curie Actions Industry Academia Partnerships and Pathways (ref. 286334, PSYCH-AID project); SAF2016-76046-R and SAF2013-46292-R (MINECO) and PI16/00156 (isciii and FEDER)

Diagnostic model development for schizophrenia based on peripheral blood mononuclear cell subtype-specific expression of metabolic markers

A significant proportion of the personal and economic burden of schizophrenia can be attributed to the late diagnosis or misdiagnosis of the disorder. A novel, objective diagnostic approaches could facilitate the early detection and treatment of schizophrenia and improve patient outcomes. In the present study, we aimed to identify robust schizophrenia-specific blood biomarkers, with the goal of developing an accurate diagnostic model. The levels of selected serum and peripheral blood mononuclear cell (PBMC) markers relevant to metabolic and immune function were measured in healthy controls (n?=?26) and recent-onset schizophrenia patients (n?=?36) using multiplexed immunoassays and flow cytometry. Analysis of covariance revealed significant upregulation of insulin receptor (IR) and fatty acid translocase (CD36) levels in T helper cells (F?=?10.75, P?=?0.002, Q?=?0.024 and F?=?21.58, P?=?2.8?×?10?5, Q?=?0.0004, respectively), as well as downregulation of glucose transporter 1 (GLUT1) expression in monocytes (F?=?21.46, P?=?2.9?×?10?5, Q?=?0.0004). The most robust predictors, monocyte GLUT1 and T helper cell CD36, were used to develop a diagnostic model, which showed a leave-one-out cross-validated area under the receiver operating characteristic curve (AUC) of 0.78 (95% CI: 0.66?0.92). The diagnostic model was validated in two independent datasets. The model was able to distinguish first-onset, drug-naïve schizophrenia patients (n?=?34) from healthy controls (n?=?39) with an AUC of 0.75 (95% CI: 0.64?0.86), and also differentiated schizophrenia patients (n?=?22) from patients with other neuropsychiatric conditions, including bipolar disorder, major depressive disorder and autism spectrum disorder (n?=?68), with an AUC of 0.83 (95% CI: 0.75?0.92). These findings indicate that PBMC-derived biomarkers have the potential to support an accurate and objective differential diagnosis of schizophrenia.ACKNOWLEDGEMENTS: We are grateful to the participants and their families for their cooperation in this study. We would like to thank blood donors and the clinical centres, for the provision of biological samples, in addition, to supporting staff at the affiliated institutions. We also thank IDIVAL biobank (Inés Santiuste and Jana Arozamena) and UMCU Biobank for clinical sample and data preparation, as well as the PAFIP members for the data collection. This work was supported by the Stanley Medical Research Institute (grant number: 12T-008) and the Dutch Research Council (NWO; grant number: 40–00812–98–12154) received by IES; by grants to SB from the Stanley Medical Research Institute (SMRI) and the Engineering and Physical Sciences Research Council UK (EPSRC); and by grants to BC-F: SAF2016–76046-R and SAF2013–46292-R (MINECO) and PI16/00156 (ISCIII and FEDER)

Exploring the neuropsychiatric spectrum using high-content functional analysis of single-cell signaling networks.

Neuropsychiatric disorders overlap in symptoms and share genetic risk factors, challenging their current classification into distinct diagnostic categories. Novel cross-disorder approaches are needed to improve our understanding of the heterogeneous nature of neuropsychiatric diseases and overcome existing bottlenecks in their diagnosis and treatment. Here we employ high-content multi-parameter phospho-specific flow cytometry, fluorescent cell barcoding and automated sample preparation to characterize ex vivo signaling network responses (n = 1764) measured at the single-cell level in B and T lymphocytes across patients diagnosed with four major neuropsychiatric disorders: autism spectrum condition (ASC), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ; n = 25 each), alongside matched healthy controls (n = 100). We identified 25 nodes (individual cell subtype-epitope-ligand combinations) significantly altered relative to the control group, with variable overlap between different neuropsychiatric diseases and heterogeneously expressed at the level of each individual patient. Reconstruction of the diagnostic categories from the altered nodes revealed an overlapping neuropsychiatric spectrum extending from MDD on one end, through BD and SCZ, to ASC on the other end. Network analysis showed that although the pathway structure of the epitopes was broadly preserved across the clinical groups, there were multiple discrete alterations in network connectivity, such as disconnections within the antigen/integrin receptor pathway and increased negative regulation within the Akt1 pathway in CD4+ T cells from ASC and SCZ patients, in addition to increased correlation of Stat1 (pY701) and Stat5 (pY694) responses in B cells from BD and MDD patients. Our results support the "dimensional" approach to neuropsychiatric disease classification and suggest potential novel drug targets along the neuropsychiatric spectrum

Impact of the COVID-19 pandemic on perinatal mental health screening, illness and pregnancy outcomes: A cohort study

Peer reviewed: TrueBackground The aim was to explore the impact of the COVID-19 pandemic on perinatal mental health screening, illness and related pregnancy complications/outcomes. Methods A single-centre retrospective cohort study in mothers giving birth before versus during the pandemic. Primary outcomes were the comparative prevalence/incidence of peripartum psychiatric diagnoses. Secondary outcomes were the pandemic's effect on psychiatric screening accuracy, and on other pregnancy outcomes linked to mental health. Results The pandemic did not significantly increase the crude incidence of diagnosed peripartum anxiety (risk ratio (RR) = 1.39, 95% CI = 0.66–2.95), depression (RR = 1.63, 95% CI = 0.72–3.70) or other pregnancy outcomes. In multivariate models, the pandemic decreased Apgar scores and was involved in interaction effects for postpartum mental illness and birthweight. Psychiatric screening at the booking appointment exhibited lower sensitivity in predicting antenatal mental illness (pre-pandemic = 85.71%, pandemic = 25.00%; p = 0.035). Conclusions The lowered screening sensitivity likely meant mental illness was poorly anticipated/under-detected during the pandemic, leading to no crude increase in perinatal psychiatric diagnoses. </jats:sec