Marine Socio-Environmental Covariates: queryable global layers of environmental and anthropogenic variables for marine ecosystem studies

Biophysical conditions, including climate, environmental stress, and habitat availability, are key drivers of many ecological processes (e.g., community assembly and productivity) and associated ecosystem services (e.g., carbon sequestration and fishery production). Furthermore, anthropogenic impacts such as coastal development and fishing can have drastic effects on the structure and function of marine ecosystems. Scientists need to account for environmental variation and human impacts to accurately model, manage, and conserve marine ecosystems. Although there are many types of environmental data available from global remote sensing and open-source data products, some are inaccessible to potential end-users because they exist as global layers in high temporal and spatial resolutions which require considerable computational power to process. Additionally, coastal locations often suffer from missing data or data quality issues which limit the utility of some global marine products for coastal sites. Herein we present the Marine Socio-Environmental Covariates dataset for the global oceans, which consists of environmental and anthropogenic variables summarized in ecologically relevant ways. The dataset includes four sets of environmental variables related to biophysical conditions (net primary productivity models corrected for shallow-water reflectance, wave energy including sheltered-coastline corrections) and landscape context (coral reef and land cover within varying radii). We also present two sets of anthropogenic variables, human population density (within varying radii) and distance to large population center, which can serve as indicators of local human impacts. We have paired global, summarized layers available for download with an online data querying platform that allows users to extract data for specific point locations with finer control of summary statistics. In creating these global layers and online platform, we hope to make the data accessible to a wide array of end-users with the goal of advancing marine ecosystem studies

The Behavior and Mind Health (BeMIND) study: Methods, design and baseline sample characteristics of a cohort study among adolescents and young adults

Objectives: The Behavior and Mind Health (BeMIND) study is a population‐based cohort study of adolescents and young adults from Dresden, Germany. The aim is to investigate psychological and behavioral factors linked to a range of mental disorders and health behaviors and their interaction with social‐environmental and genetic/biologic factors. Methods: A random sample of 14–21 year olds was drawn from the population registry in 2015. The baseline investigation was completed 11/2015–12/2016 (N = 1,180). Assessments include standardized diagnostic interview, cognitive‐affective tasks, questionnaires, biosamples, and ecologic momentary assessment in real life with combined actigraphic/geographic monitoring. In the family study component, parents completed similar assessments and provided information on child's early development. Results: The participation rate (minimum response proportion) was 21.7%; the cooperation rate was 43.4%. Acceptance and completion of study components were high. General health data indicate that more than 80% reported no or only mild impairment due to mental or somatic health problems in the past year; about 20% ever sought treatment for mental health problems or chronic somatic illnesses, respectively. Conclusions: Data from BeMIND baseline and follow‐up investigations will provide novel insights into contributors to health and disease as adolescents grow into adulthood

Inhibiting phosphoglycerate dehydrogenase counteracts chemotherapeutic efficacy against MYCN‐amplified neuroblastoma

Here we sought metabolic alterations specifically associated with MYCN amplification as nodes to indirectly target the MYCN oncogene. Liquid chromatography-mass spectrometry-based proteomics identified seven proteins consistently correlated with MYCN in proteomes from 49 neuroblastoma biopsies and 13 cell lines. Among these was phosphoglycerate dehydrogenase (PHGDH), the rate-limiting enzyme in de novo serine synthesis. MYCN associated with two regions in the PHGDH promoter, supporting transcriptional PHGDH regulation by MYCN. Pulsed stable isotope-resolved metabolomics utilizing C-13-glucose labeling demonstrated higher de novo serine synthesis in MYCN-amplified cells compared to cells with diploid MYCN. An independence of MYCN-amplified cells from exogenous serine and glycine was demonstrated by serine and glycine starvation, which attenuated nucleotide pools and proliferation only in cells with diploid MYCN but did not diminish these endpoints in MYCN-amplified cells. Proliferation was attenuated in MYCN-amplified cells by CRISPR/Cas9-mediated PHGDH knockout or treatment with PHGDH small molecule inhibitors without affecting cell viability. PHGDH inhibitors administered as single-agent therapy to NOG mice harboring patient-derived MYCN-amplified neuroblastoma xenografts slowed tumor growth. However, combining a PHGDH inhibitor with the standard-of-care chemotherapy drug, cisplatin, revealed antagonism of chemotherapy efficacy in vivo. Emergence of chemotherapy resistance was confirmed in the genetic PHGDH knockout model in vitro. Altogether, PHGDH knockout or inhibition by small molecules consistently slows proliferation, but stops short of killing the cells, which then establish resistance to classical chemotherapy. Although PHGDH inhibition with small molecules has produced encouraging results in other preclinical cancer models, this approach has limited attractiveness for patients with neuroblastoma

Antepartum depression and anxiety associated with disability in African women : cross-sectional results from the CDS Study in Ghana and Cote d’Ivoire

Background: Common mental disorders, particularly unipolar depressive disorders, rank among the top 5 with respect to the global burden of disease. As a major public health concern, antepartum depression and anxiety not only affects the individual woman, but also her offspring. Data on the prevalence of common mental disorders in pregnant women in sub-Saharan Africa are scarce. We provide results from Ghana and Côte d'Ivoire. Methods: We subsequently recruited and screened n=1030 women in the third trimester of their pregnancy for depressed mood, general anxiety, and perceived disability using the Patient Health Questionnaire depression module (PHQ-9), the 7-item Anxiety Scale (GAD-7), and the World Health Organisation Disability Assessment Schedule II (WHO-DAS 2.0, 12-item version). In addition to estimates of means and prevalence, a hierarchical linear regression model was calculated to determine the influence of antepartum depression and anxiety on disability. Results: In Ghana, 26.6% of women showed substantially depressed mood. In Côte d'Ivoire, this figure was even higher (32.9%). Clear indications for a generalized anxiety disorder were observed in 11.4% and 17.4% of pregnant women, respectively. Comorbidity of both conditions was common, affecting about 7.7% of Ghanaian and 12.6% of Ivorian participants. Pregnant women in both countries reported a high degree of disability regarding everyday activity limitations and participation restrictions. Controlled for country and age, depression and anxiety accounted for 33% of variance in the disability score. Conclusions: Antepartum depression and anxiety were highly prevalent in our sample and contributed substantially to perceived disability. These serious threats to health must be further investigated and more data are needed to comprehensively quantify the problem in sub-Saharan Africa.JH Libraries Open Access Fun

Identification of a Bipolar Disorder Vulnerable Gene CHDH at 3p21.1

Genome-wide analysis (GWA) is an effective strategy to discover extreme effects surpassing genome-wide significant levels in studying complex disorders; however, when sample size is limited, the true effects may fail to achieve genome-wide significance. In such case, there may be authentic results among the pools of nominal candidates, and an alternative approach is to consider nominal candidates but are replicable across different samples. Here, we found that mRNA expression of the choline dehydrogenase gene (CHDH) was uniformly upregulated in the brains of bipolar disorder (BPD) patients compared with healthy controls across different studies. Follow-up genetic analyses of CHDH variants in multiple independent clinical datasets (including 11,564 cases and 17,686 controls) identified a risk SNP rs9836592 showing consistent associations with BPD (P meta = 5.72 × 10(-4)), and the risk allele indicated an increased CHDH expression in multiple neuronal tissues (lowest P = 6.70 × 10(-16)). These converging results may identify a nominal but true BPD susceptibility gene CHDH. Further exploratory analysis revealed suggestive associations of rs9836592 with childhood intelligence (P = 0.044) and educational attainment (P = 0.0039), a 'proxy phenotype' of general cognitive abilities. Intriguingly, the CHDH gene is located at chromosome 3p21.1, a risk region implicated in previous BPD genome-wide association studies (GWAS), but CHDH is lying outside of the core GWAS linkage disequilibrium (LD) region, and our studied SNP rs9836592 is ∼1.2 Mb 3' downstream of the previous GWAS loci (e.g., rs2251219) with no LD between them; thus, the association observed here is unlikely a reflection of previous GWAS signals. In summary, our results imply that CHDH may play a previously unknown role in the etiology of BPD and also highlight the informative value of integrating gene expression and genetic code in advancing our understanding of its biological basis

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Search for flavour-changing neutral current top quark decays t → Hq in pp collisions at √s=8 TeV with the ATLAS detector

A search for flavour-changing neutral current decays of a top quark to an uptype quark (q = u, c) and the Standard Model Higgs boson, where the Higgs boson decays to bb¯, is presented. The analysis searches for top quark pair events in which one top quark decays to Wb, with the W boson decaying leptonically, and the other top quark decays to Hq. The search is based on pp collisions at √s=8 TeV recorded in 2012 with the ATLAS detector at the CERN Large Hadron Collider and uses an integrated luminosity of 20.3 fb−1. Data are analysed in the lepton-plus-jets final state, characterised by an isolated electron or muon and at least four jets. The search exploits the high multiplicity of b-quark jets characteristic of signal events, and employs a likelihood discriminant that uses the kinematic differences between the signal and the background, which is dominated by tt¯→WbWb decays. No significant excess of events above the background expectation is found, and observed (expected) 95% CL upper limits of 0.56% (0.42%) and 0.61% (0.64%) are derived for the t → Hc and t → Hu branching ratios respectively. The combination of this search with other ATLAS searches in the H → γγ and H → WW*, ττ decay modes significantly improves the sensitivity, yielding observed (expected) 95% CL upper limits on the t → Hc and t → Hu branching ratios of 0.46% (0.25%) and 0.45% (0.29%) respectively. The corresponding combined observed (expected) upper limits on the |λtcH| and |λtuH| couplings are 0.13 (0.10) and 0.13 (0.10) respectively. These are the most restrictive direct bounds on tqH interactions measured so far