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Sökning: WFRF:(Stahl Philip) > (2020-2023)

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1.
  • Docherty, Anna R, et al. (författare)
  • GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors.
  • 2023
  • Ingår i: The American journal of psychiatry. - : American Psychiatric Association Publishing. - 1535-7228 .- 0002-953X. ; 180:10, s. 723-738
  • Tidskriftsartikel (refereegranskat)abstract
    • Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and cross-validated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS meta-analysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures.This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses.Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values <5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors.This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.
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2.
  • Mullins, Niamh, et al. (författare)
  • Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors
  • 2022
  • Ingår i: Biological Psychiatry. - : Elsevier. - 0006-3223 .- 1873-2402. ; 91:3, s. 313-327
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders.METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors.RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged.CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.
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3.
  • Carneiro, Ana P. B., et al. (författare)
  • A framework for mapping the distribution of seabirds by integrating tracking, demography and phenology
  • 2020
  • Ingår i: Journal of Applied Ecology. - : Wiley. - 0021-8901 .- 1365-2664. ; 57:3, s. 514-525
  • Tidskriftsartikel (refereegranskat)abstract
    • The identification of geographic areas where the densities of animals are highest across their annual cycles is a crucial step in conservation planning. In marine environments, however, it can be particularly difficult to map the distribution of species, and the methods used are usually biased towards adults, neglecting the distribution of other life-history stages even though they can represent a substantial proportion of the total population. Here we develop a methodological framework for estimating population-level density distributions of seabirds, integrating tracking data across the main life-history stages (adult breeders and non-breeders, juveniles and immatures). We incorporate demographic information (adult and juvenile/immature survival, breeding frequency and success, age at first breeding) and phenological data (average timing of breeding and migration) to weight distribution maps according to the proportion of the population represented by each life-history stage. We demonstrate the utility of this framework by applying it to 22 species of albatrosses and petrels that are of conservation concern due to interactions with fisheries. Because juveniles, immatures and non-breeding adults account for 47%-81% of all individuals of the populations analysed, ignoring the distributions of birds in these stages leads to biased estimates of overlap with threats, and may misdirect management and conservation efforts. Population-level distribution maps using only adult distributions underestimated exposure to longline fishing effort by 18%-42%, compared with overlap scores based on data from all life-history stages. Synthesis and applications. Our framework synthesizes and improves on previous approaches to estimate seabird densities at sea, is applicable for data-poor situations, and provides a standard and repeatable method that can be easily updated as new tracking and demographic data become available. We provide scripts in the R language and a Shiny app to facilitate future applications of our approach. We recommend that where sufficient tracking data are available, this framework be used to assess overlap of seabirds with at-sea threats such as overharvesting, fisheries bycatch, shipping, offshore industry and pollutants. Based on such an analysis, conservation interventions could be directed towards areas where they have the greatest impact on populations.
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4.
  • Christakoudi, Sofia, et al. (författare)
  • Development and validation of the first consensus gene-expression signature of operational tolerance in kidney transplantation, incorporating adjustment for immunosuppressive drug therapy
  • 2020
  • Ingår i: EBioMedicine. - : Elsevier BV. - 2352-3964. ; 58
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Kidney transplant recipients (KTRs) with "operational tolerance" (OT) maintain a functioning graft without immunosuppressive (IS) drugs, thus avoiding treatment complications. Nevertheless, IS drugs can influence gene-expression signatures aiming to identify OT among treated KTRs. Methods: We compared five published signatures of OT in peripheral blood samples from 18 tolerant, 183 stable, and 34 chronic rejector KTRs, using gene-expression levels with and without adjustment for IS drugs and regularised logistic regression. Findings: IS drugs explained up to 50% of the variability in gene-expression and 20-30% of the variability in the probability of OT predicted by signatures without drug adjustment. We present a parsimonious consensus gene-set to identify OT, derived from joint analysis of IS-drug-adjusted expression of five published signature gene-sets. This signature, including CD40, CTLA4, HSD11B1, IGKV4-1, MZB1, NR3C2, and RAB40C genes, showed an area under the curve 0.92 (95% confidence interval 0.88-0.94) in cross-validation and 0.97 (0.93-1.00) in six months follow-up samples. Interpretation: We advocate including adjustment for IS drug therapy in the development stage of gene-expression signatures of OT to reduce the risk of capturing features of treatment, which could be lost following IS drug minimisation or withdrawal. Our signature, however, would require further validation in an independent dataset and a biomarker-led trial. (c) 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license. (http://creativecommons.org/licenses/by/4.0/)
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5.
  • Kreibich, Heidi, et al. (författare)
  • Panta Rhei benchmark dataset : Socio-hydrological data of paired events of floods and droughts
  • 2023
  • Ingår i: Earth System Science Data. - : Copernicus Publications. - 1866-3508 .- 1866-3516. ; 15:5, s. 2009-2023
  • Tidskriftsartikel (refereegranskat)abstract
    • As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions, and feedbacks in complex human-water systems leading to flood and drought impacts. Here we present a benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area. The 45 paired events occurred in 42 different study areas and cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed and in the quantity of socio-hydrological data. The benchmark dataset comprises (1) detailed review-style reports about the events and key processes between the two events of a pair; (2) the key data table containing variables that assess the indicators which characterize management shortcomings, hazard, exposure, vulnerability, and impacts of all events; and (3) a table of the indicators of change that indicate the differences between the first and second event of a pair. The advantages of the dataset are that it enables comparative analyses across all the paired events based on the indicators of change and allows for detailed context- and location-specific assessments based on the extensive data and reports of the individual study areas. The dataset can be used by the scientific community for exploratory data analyses, e.g. focused on causal links between risk management; changes in hazard, exposure and vulnerability; and flood or drought impacts. The data can also be used for the development, calibration, and validation of socio-hydrological models. The dataset is available to the public through the GFZ Data Services (Kreibich et al., 2023, 10.5880/GFZ.4.4.2023.001).
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6.
  • Oliver, Dominic, et al. (författare)
  • Transdiagnostic individualized clinically-based risk calculator for the automatic detection of individuals at-risk and the prediction of psychosis : external replication in 2,430,333 US patients
  • 2020
  • Ingår i: Translational Psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 10:1
  • Tidskriftsartikel (refereegranskat)abstract
    • The real-world impact of psychosis prevention is reliant on effective strategies for identifying individuals at risk. A transdiagnostic, individualized, clinically-based risk calculator to improve this has been developed and externally validated twice in two different UK healthcare trusts with convincing results. The prognostic performance of this risk calculator outside the UK is unknown. All individuals who accessed primary or secondary health care services belonging to the IBM® MarketScan® Commercial Database between January 2015 and December 2017, and received a first ICD-10 index diagnosis of nonorganic/nonpsychotic mental disorder, were included. According to the risk calculator, age, gender, ethnicity, age-by-gender, and ICD-10 cluster diagnosis at index date were used to predict development of any ICD-10 nonorganic psychotic disorder. Because patient-level ethnicity data were not available city-level ethnicity proportions were used as proxy. The study included 2,430,333 patients with a mean follow-up of 15.36 months and cumulative incidence of psychosis at two years of 1.43%. There were profound differences compared to the original development UK database in terms of case-mix, psychosis incidence, distribution of baseline predictors (ICD-10 cluster diagnoses), availability of patient-level ethnicity data, follow-up time and availability of specialized clinical services for at-risk individuals. Despite these important differences, the model retained accuracy significantly above chance (Harrell’s C = 0.676, 95% CI: 0.672–0.679). To date, this is the largest international external replication of an individualized prognostic model in the field of psychiatry. This risk calculator is transportable on an international scale to improve the automatic detection of individuals at risk of psychosis.
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