HOW IMPORTANT ARE DIFFICULT ENVIRONMENTS TO ACHIEVING THE MDGS?

Food Security and Poverty,

Nitrogen cycle disruption through the application of de-icing salts on upland highways

It is hypothesized that episodic introductions of road salt severely disrupt the soil nitrogen cycle at a range of spatial and temporal scales. A field-scale study has confirmed impacts on the nitrogen cycle in soil, soil solution and river samples. There is evidence that ammonium-N retention on cation exchange sites has been reduced by the presence of sodium ions, and that ammonium-N has been flushed from the exchange sites. Increases in soil pH have been caused in naturally acidic uplands. These have enhanced mineralization of organic-N, especially nitrification, leading to a reduction in the mineralizable-N pool of roadside soils. There is evidence to support the hypothesis that organic matter content has been lowered over decades either through desorption or dispersal processes. Multiple drivers are identified that contribute to the disruption of nitrogen cycling processes, but their relative importance is difficult to quantify unequivocally. The influence of road salt on soil and soil solution declines with distance from the highway, but impacts on water chemistry in a local stream are still strongly evident at some distance from the road

Schizophrenia polygenic risk and experiences of childhood adversity: a systematic review and meta-analysis

Background and Hypothesis Schizophrenia has been robustly associated with multiple genetic and environmental risk factors. Childhood adversity is one of the most widely replicated environmental risk factors for schizophrenia, but it is unclear if schizophrenia genetic risk alleles contribute to this association. Study Design In this systematic review and meta-analysis, we assessed the evidence for gene-environment correlation (genes influence likelihood of environmental exposure) between schizophrenia polygenic risk score (PRS) and reported childhood adversity. We also assessed the evidence for a gene-environment interaction (genes influence sensitivity to environmental exposure) in relation to the outcome of schizophrenia and/or psychosis. This study was registered on PROSPERO (CRD42020182812). Following PRISMA guidelines, a search for relevant literature was conducted using Cochrane, MEDLINE, PsycINFO, Web of Science, and Scopus databases until February 2022. All studies that examined the association between schizophrenia PRS and childhood adversity were included. Study Results Seventeen of 650 identified studies met the inclusion criteria and were assessed against the Newcastle-Ottawa Scale for quality. The meta-analysis found evidence for gene-environment correlation between schizophrenia PRS and childhood adversity (r = .02; 95% CI = 0.01, 0.03; P = .001), but the effect was small and therefore likely to explain only a small proportion of the association between childhood adversity and psychosis. The 4 studies that investigated a gene-environment interaction between schizophrenia PRS and childhood adversity in increasing risk of psychosis reported inconsistent results. Conclusions These findings suggest that a gene-environment correlation could explain a small proportion of the relationship between reported childhood adversity and psychosis

Interaction testing and polygenic risk scoring to estimate the contribution of common genetic variants to treatment resistance in schizophrenia

Importance About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. Objective To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Design, Setting, and Participants Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10 501) and individuals with non-TRS (n = 20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). Main Outcomes and Measures GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. Results The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r2 = 2.03%; P = .001), which was replicated in the STRATA-G incidence sample (r2 = 1.09%; P = .04). Conclusions and Relevance In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance

The psychological impact of prolonged disorders of consciousness on caregivers:a systematic review of quantitative studies

Objective: Systematic review of the nature, frequency and severity of psychological experiences of people who have a close relationship with a person with a prolonged disorder of consciousness. Data sources: Cochrane Library, Web of Science, PsycINFO, PubMed, Embase®, MEDLINE®, Allied and Complementary Medicine™, were searched from inceptions until December 2016 with additional hand searching of reference lists of included articles. Review methods: Studies were included that used quantitative methodologies and psychological measures to investigate experiences. The PRISMA statement was followed with inclusion criteria set a priori. A data synthesis summarized psychological constructs studied. Results: A total of 18 studies (ranging between n = 16–487 participants) met the inclusion criteria with 15 of 18 studies focused on the primary caregiver. A total of 23 standardized psychological measures were identified to assess four primary psychological constructs: Loss and grief, psychological wellbeing changes, burden and use of coping strategies. Conclusions: Small sample sizes, limited variables and reliance on observational methods affected quality. Caregivers do find ways to manage independently, but some exhibit clinically significant psychological distress that does not change over time alone and may get worse

A volunteer-run, face-to-face, early intervention service for reducing suicidality: a service evaluation of the listening place

Background: Befriending is one of many strategies with the potential to reduce suicidal ideation and decrease the risk of suicide. Aims: To measure change in suicidal ideation and behavior among visitors (service users) supported at The Listening Place (TLP), a charity which offers volunteer-run, face-to-face befriending to people who are suicidal. Method: This study was peer reviewed and preregistered on the Open Science Framework prior to data extraction. Anonymized data were extracted for visitors at the point of referral and after 3 months of receiving support. Paired-sample tests were used to test whether self-reported suicidal ideation and behaviors changed after 3 months of support from TLP. Multivariable regressions were used to test whether change in suicidal feelings was associated with demographic characteristics or baseline self-reported suicidality. Results: TLP received 13,938 referrals from July 2016 to February 2022. Self-reported suicidal ideation, suicidal behavior, and feelings of distress decreased after 3 months, while feelings of support increased. Only self-reported suicidal behavior prior to referral was associated with a lesser reduction in self-reported suicidality after 3 months. Limitations: In the absence of a control group, it cannot be concluded that TLP causes the reduction in self-reported suicidality. Conclusions: An empathetic, nonjudgmental, listening service for people who are feeling suicidal was well received by users, who experienced a reduction in suicidality

Applying the Higher Education Academy framework for partnership in learning and teaching in higher education to online partnership learning communities: A case study and an extended model

As internet access and use increase exponentially, pedagogical practice becomes increasingly embedded in online platforms. We report on an online initiative of engaged student learning, the peer-led, staff-assisted e-helpdesk for research methods and statistics, which we evaluated and redeveloped using the lens and guiding principles of the framework for partnership in learning and teaching of the Higher Education Academy (HEA). The aim of the redevelopment was to steer the initiative towards a more integrative and sustainable implementation, as manifest in the applied construct of an online partnership learning community. Our evolving experience of the e-helpdesk highlighted the central role of the facilitator in engineering and maintaining social presence in the online community. We propose an extended model for building an online partnership learning community, whereby partnership encapsulates all the essential elements of student and staff partnership as outlined in the HEA framework, but is also critically defined by similar parameters of partnership between users and facilitators. In this model, the facilitator’s role becomes more involved in instructional teaching as disciplinary expertise increases, but descending levels of disciplinary expertise can foster ascending levels of independent learning and shared discovery for both users and facilitators.  &nbsp

Interaction testing and polygenic risk scoring to estimate the association of common genetic variants with treatment resistance in schizophrenia

Importance About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. Objective To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Design, Setting, and Participants Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n=10 501) and individuals with non-TRS (n=20 325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). Main Outcomes and Measures GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. Results The study included a total of 85 490 participants (48 635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r² = 2.03%; P = .001), which was replicated in the STRATA-G incidence sample (r² = 1.09%; P = .04). Conclusions and Relevance In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance.Funding/Support: This work was supported by Medical Research Council Centre grant MR/ L010305/1, Medical Research Council Program grant MR/P005748/1, and Medical Research Council Project grants MR/L011794/1 and MC_PC_17212 to Cardiff University and by the National Centre for Mental Health, funded by the Welsh Government through Health and Care Research Wales. This work acknowledges the support of the Supercomputing Wales project, which is partially funded by the European Regional Development Fund via the Welsh Government. Dr Pardiñas was supported by an Academy of Medical Sciences Springboard Award (SBF005\1083). Dr Andreassen was supported by the Research Council of Norway (grants 283798, 262656, 248980, 273291, 248828, 248778, and 223273); KG Jebsen Stiftelsen, South-East Norway Health Authority, and the European Union’s Horizon 2020 Research and Innovation Programme (grant 847776). Dr Ajnakina was supported by an National Institute for Health Research postdoctoral fellowship (PDF-2018-11-ST2-020). Dr Joyce was supported by the University College London Hospitals/UCL University College London Biomedical Research Centre. Dr Kowalec received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie grant agreement (793530) from the government of Canada Banting postdoctoral fellowship programme and the University of Manitoba. Dr Sullivan was supported by the Swedish Research Council (Vetenskapsrådet, D0886501), the European Union’s Horizon 2020 programme (COSYN, 610307) and the US National Institute of Mental Health (U01 MH109528 and R01 MH077139). The Psychiatric Genomics Consortium was partly supported by the National Institute Of Mental Health (grants R01MH124873). The Sweden Schizophrenia Study was supported by the National Institute Of Mental Health (grant R01MH077139). The STRATA consortium was supported by a Stratified Medicine Programme grant to Dr MacCabe from the Medical Research Council (grant MR/L011794/1), which funded the research and supported Drs Pardiñas, Smart, Kassoumeri, Murray, Walters, and MacCabe. Dr Smart was supported by a Collaboration for Leadership in Applied Health Research and Care South London at King’s College Hospital National Health Service Foundation Trust. The AESOP (US) cohort was funded by the UK Medical Research Council (grant G0500817). The Belfast (UK) cohort was funded by the Research and Development Office of Northern Ireland. The Bologna (Italy) cohort was funded by the European Community’s Seventh Framework program (HEALTH-F2-2010–241909, project EU-GEI). The Genetics and Psychosis project (London, UK) cohort was funded by the UK National Institute of Health Research Specialist Biomedical Research Centre for Mental Health, South London and the Maudsley National Health Service Mental Health Foundation Trust (SLAM) and the Institute of Psychiatry, Psychology, and Neuroscience at King’s College London; Psychiatry Research Trust; Maudsley Charity Research Fund; and the European Community’s Seventh Framework program (HEALTH-F2-2009-241909, project EU-GEI). The Lausanne (Switzerland) cohort was funded by the Swiss National Science Foundation (grants 320030_135736/1, 320030-120686, 324730-144064, 320030-173211, and 171804); the National Center of Competence in Research Synaptic Bases of Mental Diseases from the Swiss National Science Foundation (grant 51AU40_125759); and Fondation Alamaya. The Oslo (Norway) cohort was funded by the Research Council of Norway (grant 223273/F50, under the Centers of Excellence funding scheme, 300309, 283798) and the South-Eastern Norway Regional Health Authority (grants 2006233, 2006258, 2011085, 2014102, 2015088, and 2017-112). The Paris (France) cohort was funded by European Community’s Seventh Framework program (HEALTH-F2-2010–241909, project EU-GEI). The Prague (Czech Republic) cohort was funded by the Ministry of Health of the Czech Republic (grant NU20-04-00393). The Santander (Spain) cohort was funded by the following grants to Dr Crespo-Facorro: Instituto de Salud Carlos III (grants FIS00/3095, PI020499, PI050427, and PI060507), Plan Nacional de Drogas Research (grant 2005-Orden sco/3246/2004), SENY Fundatio Research (grant 2005-0308007), Fundacion Marques de Valdecilla (grant A/02/07, API07/011) and Ministry of Economy and Competitiveness and the European Fund for Regional Development (grants SAF2016-76046-R and SAF2013-46292-R). The West London (UK) cohort was funded by The Wellcome Trust (grants 042025, 052247, and 064607)

Treatment resistance NMDA receptor pathway polygenic score is associated with brain glutamate in schizophrenia

Dysfunction of glutamate neurotransmission has been implicated in the pathophysiology of schizophrenia and may be particularly relevant in severe, treatment-resistant symptoms. The underlying mechanism may involve hypofunction of the NMDA receptor. We investigated whether schizophrenia-related pathway polygenic scores, composed of genetic variants within NMDA receptor encoding genes, are associated with cortical glutamate in schizophrenia. Anterior cingulate cortex (ACC) glutamate was measured in 70 participants across 4 research sites using Proton Magnetic Resonance Spectroscopy (1H-MRS). Two NMDA receptor gene sets were sourced from the Molecular Signatories Database and NMDA receptor pathway polygenic scores were constructed using PRSet. The NMDA receptor pathway polygenic scores were weighted by single nucleotide polymorphism (SNP) associations with treatment-resistant schizophrenia, and associations with ACC glutamate were tested. We then tested whether NMDA receptor pathway polygenic scores with SNPs weighted by associations with non-treatment-resistant schizophrenia were associated with ACC glutamate. A higher NMDA receptor complex pathway polygenic score was significantly associated with lower ACC glutamate (β = −0.25, 95 % CI = −0.49, −0.02, competitive p = 0.03). When SNPs were weighted by associations with non-treatment-resistant schizophrenia, there was no association between the NMDA receptor complex pathway polygenic score and ACC glutamate (β = 0.05, 95 % CI = −0.18, 0.27, competitive p = 0.79). These results provide initial evidence of an association between common genetic variation implicated in NMDA receptor function and ACC glutamate levels in schizophrenia. This association was specific to when the NMDA receptor complex pathway polygenic score was weighted by SNP associations with treatment-resistant schizophrenia

Integrated metastate functional connectivity networks predict change in symptom severity in clinical high risk for psychosis

The ability to identify biomarkers of psychosis risk is essential in defining effective preventive measures to potentially circumvent the transition to psychosis. Using samples of people at clinical high risk for psychosis (CHR) and Healthy controls (HC) who were administered a task fMRI paradigm, we used a framework for labelling time windows of fMRI scans as ‘integrated’ FC networks to provide a granular representation of functional connectivity (FC). Periods of integration were defined using the ‘cartographic profile’ of time windows and k‐means clustering, and sub‐network discovery was carried out using Network Based Statistics (NBS). There were no network differences between CHR and HC groups. Within the CHR group, using integrated FC networks, we identified a sub‐network negatively associated with longitudinal changes in the severity of psychotic symptoms. This sub‐network comprised brain areas implicated in bottom‐up sensory processing and in integration with motor control, suggesting it may be related to the demands of the fMRI task. These data suggest that extracting integrated FC networks may be useful in the investigation of biomarkers of psychosis risk