Showing papers by "University of Düsseldorf published in 2018"
TL;DR: This work presents a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and shows that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods.
Abstract: Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.
1,620 citations
TL;DR: The results suggest that gwMRF parcellations reveal neurobiologically meaningful features of brain organization and are potentially useful for future applications requiring dimensionality reduction of voxel-wise fMRI data.
Abstract: A central goal in systems neuroscience is the parcellation of the cerebral cortex into discrete neurobiological "atoms". Resting-state functional magnetic resonance imaging (rs-fMRI) offers the possibility of in vivo human cortical parcellation. Almost all previous parcellations relied on 1 of 2 approaches. The local gradient approach detects abrupt transitions in functional connectivity patterns. These transitions potentially reflect cortical areal boundaries defined by histology or visuotopic fMRI. By contrast, the global similarity approach clusters similar functional connectivity patterns regardless of spatial proximity, resulting in parcels with homogeneous (similar) rs-fMRI signals. Here, we propose a gradient-weighted Markov Random Field (gwMRF) model integrating local gradient and global similarity approaches. Using task-fMRI and rs-fMRI across diverse acquisition protocols, we found gwMRF parcellations to be more homogeneous than 4 previously published parcellations. Furthermore, gwMRF parcellations agreed with the boundaries of certain cortical areas defined using histology and visuotopic fMRI. Some parcels captured subareal (somatotopic and visuotopic) features that likely reflect distinct computational units within known cortical areas. These results suggest that gwMRF parcellations reveal neurobiologically meaningful features of brain organization and are potentially useful for future applications requiring dimensionality reduction of voxel-wise fMRI data. Multiresolution parcellations generated from 1489 participants are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Schaefer2018_LocalGlobal).
1,567 citations
University of Oxford1, University of Michigan2, Wellcome Trust Sanger Institute3, Amgen4, University of Cambridge5, University of Copenhagen6, University of Liverpool7, University of Freiburg8, Boston University9, University of Tartu10, Erasmus University Medical Center11, Leiden University Medical Center12, Pasteur Institute13, Icahn School of Medicine at Mount Sinai14, UCLA Medical Center15, Vanderbilt University Medical Center16, Wake Forest University17, National University of Singapore18, Imperial College London19, London North West Healthcare NHS Trust20, Charité21, Innsbruck Medical University22, Washington University in St. Louis23, Queen Mary University of London24, University of Southern Denmark25, National and Kapodistrian University of Athens26, Robertson Centre for Biostatistics27, University of Exeter28, Uppsala University29, University of Düsseldorf30, Steno Diabetes Center31, Aalborg University32, University of Eastern Finland33, Broad Institute34, Frederiksberg Hospital35, University of Bergen36, Lund University37, Technische Universität München38, University of North Carolina at Chapel Hill39, University of Edinburgh40, Ninewells Hospital41, University of Minnesota42, University of Glasgow43, Ludwig Maximilian University of Munich44, University of Iceland45, Aarhus University46, Stanford University47, Science for Life Laboratory48, University of Helsinki49, National Institutes of Health50, University of Dundee51, Harvard University52
TL;DR: Combining 32 genome-wide association studies with high-density imputation provides a comprehensive view of the genetic contribution to type 2 diabetes in individuals of European ancestry with respect to locus discovery, causal-variant resolution, and mechanistic insight.
Abstract: We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci, 135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency 2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).
1,136 citations
Susanne Gröbner1, Barbara C. Worst, Joachim Weischenfeldt2, Joachim Weischenfeldt3 +182 more•Institutions (23)
TL;DR: The data suggest that 7–8% of the children in this cohort carry an unambiguous predisposing germline variant and that nearly 50% of paediatric neoplasms harbour a potentially druggable event, which is highly relevant for the design of future clinical trials.
Abstract: Pan-cancer analyses that examine commonalities and differences among various cancer types have emerged as a powerful way to obtain novel insights into cancer biology. Here we present a comprehensive analysis of genetic alterations in a pan-cancer cohort including 961 tumours from children, adolescents, and young adults, comprising 24 distinct molecular types of cancer. Using a standardized workflow, we identified marked differences in terms of mutation frequency and significantly mutated genes in comparison to previously analysed adult cancers. Genetic alterations in 149 putative cancer driver genes separate the tumours into two classes: small mutation and structural/copy-number variant (correlating with germline variants). Structural variants, hyperdiploidy, and chromothripsis are linked to TP53 mutation status and mutational signatures. Our data suggest that 7-8% of the children in this cohort carry an unambiguous predisposing germline variant and that nearly 50% of paediatric neoplasms harbour a potentially druggable event, which is highly relevant for the design of future clinical trials.
958 citations
Northern Arizona University1, University of Minnesota2, Woods Hole Oceanographic Institution3, University of California, Davis4, Massachusetts Institute of Technology5, University of Copenhagen6, University of Trento7, Chinese Academy of Sciences8, University of California, San Francisco9, Children's Hospital of Philadelphia10, Pacific Northwest National Laboratory11, North Carolina State University12, University of Montana13, Dalhousie University14, University of British Columbia15, Shedd Aquarium16, University of Colorado Denver17, University of California, San Diego18, Michigan State University19, Stanford University20, Harvard University21, Broad Institute22, Australian National University23, University of Düsseldorf24, Sookmyung Women's University25, San Diego State University26, Howard Hughes Medical Institute27, Cornell University28, Max Planck Society29, University of Washington30, Colorado State University31, Google32, Syracuse University33, Webster University34, United States Department of Agriculture35, University of Arkansas for Medical Sciences36, Colorado School of Mines37, University of Southern Mississippi38, Atlantic Oceanographic and Meteorological Laboratory39, University of California, Merced40, Wageningen University and Research Centre41, University of Arizona42, Environment Agency43, University of Florida44, Merck & Co.45
TL;DR: QIIME 2 provides new features that will drive the next generation of microbiome research, including interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.
Abstract: We present QIIME 2, an open-source microbiome data science platform accessible to users spanning the microbiome research ecosystem, from scientists and engineers to clinicians and policy makers. QIIME 2 provides new features that will drive the next generation of microbiome research. These include interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.
875 citations
TL;DR: Assessment of classification by DNA methylation profiling and additional +7/−10 signatures appear to be promising as well and could be considered in the future following additional experience and validation.
Abstract: Working Committee 1 concluded that histologic grade II and III IDH-wildtype diffuse astrocytic gliomas that contain high-level EGFR amplification, the combination of whole chromosome 7 gain and whole chromosome 10 loss (+7/−10), or TERT promoter mutations, correspond to WHO grade IV and should be referred to as diffuse astrocytic glioma, IDH-wildtype, with molecular features of glioblastoma, WHO grade IV. Assessment of classification by DNA methylation profiling and additional +7/−10 signatures appear to be promising as well and could be considered in the future following additional experience and validation. We also concluded that specific molecular signatures in subsets of IDH-wildtype diffuse astrocytic gliomas are associated with better clinical outcomes and should not lead to a high-grade designation, including, but not limited to, those gliomas with MYB/MYBL or BRAF alterations as individual drivers.
528 citations
TL;DR: The theory and fundamental principles of the spin-vibronic mechanism for ISC are presented, followed by empirical rules to estimate the rate of ISC within this regime.
Abstract: Intersystem crossing (ISC), formally forbidden within nonrelativistic quantum theory, is the mechanism by which a molecule changes its spin state. It plays an important role in the excited state decay dynamics of many molecular systems and not just those containing heavy elements. In the simplest case, ISC is driven by direct spin–orbit coupling between two states of different multiplicities. This coupling is usually assumed to remain unchanged by vibrational motion. It is also often presumed that spin-allowed radiationless transitions, i.e. internal conversion, and the nonadiabatic coupling that drives them, can be considered separately from ISC and spin–orbit coupling owing to the vastly different time scales upon which these processes are assumed to occur. However, these assumptions are too restrictive. Indeed, the strong mixing brought about by the simultaneous presence of nonadiabatic and spin–orbit coupling means that often the spin, electronic, and vibrational dynamics cannot be described independe...
505 citations
University Hospital Heidelberg1, Humboldt University of Berlin2, Charité3, University of Düsseldorf4, University of Southern Denmark5, Children's Hospital at Westmead6, Tohoku University7, Walton Centre8, Ruhr University Bochum9, Ludwig Maximilian University of Munich10, Johns Hopkins University11, John Radcliffe Hospital12, University of Barcelona13, Hannover Medical School14, Mayo Clinic15
TL;DR: In this article, the authors proposed indications for MOG-IgG testing based on expert consensus, and gave a list of conditions atypical for MG-EM (red flags) that should prompt physicians to challenge a positive MOG IgG test result, and provided recommendations regarding assay methodology, specimen sampling and data interpretation.
Abstract: Over the past few years, new-generation cell-based assays have demonstrated a robust association of autoantibodies to full-length human myelin oligodendrocyte glycoprotein (MOG-IgG) with (mostly recurrent) optic neuritis, myelitis and brainstem encephalitis, as well as with acute disseminated encephalomyelitis (ADEM)-like presentations. Most experts now consider MOG-IgG-associated encephalomyelitis (MOG-EM) a disease entity in its own right, immunopathogenetically distinct from both classic multiple sclerosis (MS) and aquaporin-4 (AQP4)-IgG-positive neuromyelitis optica spectrum disorders (NMOSD). Owing to a substantial overlap in clinicoradiological presentation, MOG-EM was often unwittingly misdiagnosed as MS in the past. Accordingly, increasing numbers of patients with suspected or established MS are currently being tested for MOG-IgG. However, screening of large unselected cohorts for rare biomarkers can significantly reduce the positive predictive value of a test. To lessen the hazard of overdiagnosing MOG-EM, which may lead to inappropriate treatment, more selective criteria for MOG-IgG testing are urgently needed. In this paper, we propose indications for MOG-IgG testing based on expert consensus. In addition, we give a list of conditions atypical for MOG-EM (“red flags”) that should prompt physicians to challenge a positive MOG-IgG test result. Finally, we provide recommendations regarding assay methodology, specimen sampling and data interpretation.
493 citations
University of Düsseldorf1, Florida International University2, University of Texas Health Science Center at San Antonio3, King's College London4, Karolinska Institutet5, University of Nottingham6, University of Texas at Austin7, University of Warwick8, MedStar National Rehabilitation Hospital9, University of Colorado Boulder10
TL;DR: Specific guidelines and a checklist are provided that will hopefully improve the transparency, traceability, replicability and reporting of meta‐analytical results of neuroimaging data.
481 citations
Raymond K. Walters1, Raymond K. Walters2, Renato Polimanti3, Emma C. Johnson4 +168 more•Institutions (48)
TL;DR: The largest genome-wide association study to date of DSM-IV-diagnosed AD found loci associated with AD and characterized the relationship between AD and other psychiatric and behavioral outcomes, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.
Abstract: Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case-control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n = 46,568; African, n = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; P = 9.8 × 10-13) and African ancestries (rs2066702; P = 2.2 × 10-9). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit-hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.
434 citations
TL;DR: Previous models of the similarities in the networks for Motor Imagery, Action Observation, and Movement Execution are quantified and amended, while highlighting key differences in their recruitment of motor cortex, parietal cortex, and subcortical structures.
Hebron University1, Ruhr University Bochum2, University College London3, University of Florence4, Multiple Sclerosis International Federation5, University of Toulouse6, Vita-Salute San Raffaele University7, University Hospital of Basel8, Medical University of Graz9, University of Düsseldorf10, First Faculty of Medicine, Charles University in Prague11, Technische Universität München12, University of Paris13, Karolinska University Hospital14, Medical University of Łódź15, Istanbul University16, Copenhagen University Hospital17, University of Genoa18, University of Münster19, University of Mainz20
TL;DR: An evidence-based clinical practice guideline for the pharmacological treatment of people with MS, which takes into account all disease-modifying drugs approved by the European Medicine Agency at the time of publication.
Abstract: Background:Multiple sclerosis (MS) is a complex disease with new drugs becoming available in the past years There is a need for a reference tool compiling current data to aid professionals in trea
South London and Maudsley NHS Foundation Trust1, King's College London2, Katholieke Universiteit Leuven3, Karolinska Institutet4, University of Melbourne5, National Research Council6, University of Padua7, Kermanshah University of Medical Sciences8, University of Düsseldorf9, Ludwig Maximilian University of Munich10, University of Basel11, University of São Paulo12, Hofstra University13, RWTH Aachen University14, Loughborough University15, Hannover Medical School16
TL;DR: A meta-review of PA interventions and their impact on health outcomes for people with SMI, including schizophrenia-spectrum disorders, major depressive disorder (MDD) and bipolar disorder makes multiple recommendations to fill existing research gaps and increase the use of PA in routine clinical care aimed at improving psychiatric and medical outcomes.
TL;DR: This work used trio binning to recover both haplotypes of a diploid human genome and identified complex structural variants missed by alternative approaches, topping the quality of current cattle reference genomes.
Abstract: Complex allelic variation hampers the assembly of haplotype-resolved sequences from diploid genomes. We developed trio binning, an approach that simplifies haplotype assembly by resolving allelic variation before assembly. In contrast with prior approaches, the effectiveness of our method improved with increasing heterozygosity. Trio binning uses short reads from two parental genomes to first partition long reads from an offspring into haplotype-specific sets. Each haplotype is then assembled independently, resulting in a complete diploid reconstruction. We used trio binning to recover both haplotypes of a diploid human genome and identified complex structural variants missed by alternative approaches. We sequenced an F1 cross between the cattle subspecies Bos taurus taurus and Bos taurus indicus and completely assembled both parental haplotypes with NG50 haplotig sizes of >20 Mb and 99.998% accuracy, surpassing the quality of current cattle reference genomes. We suggest that trio binning improves diploid genome assembly and will facilitate new studies of haplotype variation and inheritance.
Kanazawa University1, Kobe University2, Dalhousie University3, University of Düsseldorf4, University of Osnabrück5, University of Lyon6, University of Oxford7, University of Marburg8, Ghent University9, University of Würzburg10, Charles University in Prague11, Martin Luther University of Halle-Wittenberg12, Adelphi University13, University of Jena14, Leibniz Association15, University of Maryland, College Park16, National Institute of Genetics17, University of Tokyo18, Wageningen University and Research Centre19, John Innes Centre20, New York Botanical Garden21, University of Copenhagen22, University of Cologne23, University of Pretoria24, Institute of Science and Technology Austria25, University of New South Wales26, University of Toulouse27, Université Paris-Saclay28
TL;DR: Transcriptomic analysis of sexual reproductive structures reveals intricate control by TFs, activity of the ROS gene network, and the ancestral use of plant-like storage and stress protection proteins in the zygote.
TL;DR: Trans-ethnic analyses of exome array data identify new risk loci for type 2 diabetes and fine-mapping analyses using genome-wide association data show that the index coding variants represent the likely causal variants at only a subset of these loci.
Abstract: We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10−7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent ‘false leads’ with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.
Columbia University1, University of Freiburg2, Delft University of Technology3, University of Düsseldorf4, Clemson University5, University of Sheffield6, Aarhus University7, Ludwig Maximilian University of Munich8, Stony Brook University9, University of California, Irvine10, University of Groningen11, University of Ulm12, Wageningen University and Research Centre13, Johns Hopkins University14, North Carolina State University15, Dresden University of Technology16, Katholieke Universiteit Leuven17, University of Hasselt18, University of Lübeck19, University of Oxford20, Seoul National University21, Kaiserslautern University of Technology22, Institute of Molecular Biotechnology23, University of Mainz24, Arizona State University25, University of Zurich26, Braunschweig University of Technology27
TL;DR: A multi-laboratory study finds that single-molecule FRET is a reproducible and reliable approach for determining accurate distances in dye-labeled DNA duplexes.
Abstract: Single-molecule Forster resonance energy transfer (smFRET) is increasingly being used to determine distances, structures, and dynamics of biomolecules in vitro and in vivo. However, generalized protocols and FRET standards to ensure the reproducibility and accuracy of measurements of FRET efficiencies are currently lacking. Here we report the results of a comparative blind study in which 20 labs determined the FRET efficiencies (E) of several dye-labeled DNA duplexes. Using a unified, straightforward method, we obtained FRET efficiencies with s.d. between ±0.02 and ±0.05. We suggest experimental and computational procedures for converting FRET efficiencies into accurate distances, and discuss potential uncertainties in the experiment and the modeling. Our quantitative assessment of the reproducibility of intensity-based smFRET measurements and a unified correction procedure represents an important step toward the validation of distance networks, with the ultimate aim of achieving reliable structural models of biomolecular systems by smFRET-based hybrid methods.
Cornell University1, Boyce Thompson Institute for Plant Research2, Utrecht University3, Ghent University4, Dalhousie University5, University of Toulouse6, Duke University7, University of Düsseldorf8, University of Arizona9, California State University, Fullerton10, University of Western Australia11, Pennsylvania State University12, Bielefeld University13, Max Planck Society14, University of Tokyo15, University of Marburg16, Utah State University17, University of California, Berkeley18, University of Louisiana at Lafayette19, University of Pretoria20, University of Alberta21
TL;DR: The genomes of two fern species, Azolla filiculoides and Salvinia cucullata, are reported and insights into fern-specific whole-genome duplications, f Fern-specific insect-resistant gene evolution and fern–cyanobacterial symbiosis are provided.
Abstract: Ferns are the closest sister group to all seed plants, yet little is known about their genomes other than that they are generally colossal. Here, we report on the genomes of Azolla filiculoides and Salvinia cucullata (Salviniales) and present evidence for episodic whole-genome duplication in ferns—one at the base of ‘core leptosporangiates’ and one specific to Azolla. One fern-specific gene that we identified, recently shown to confer high insect resistance, seems to have been derived from bacteria through horizontal gene transfer. Azolla coexists in a unique symbiosis with N2-fixing cyanobacteria, and we demonstrate a clear pattern of cospeciation between the two partners. Furthermore, the Azolla genome lacks genes that are common to arbuscular mycorrhizal and root nodule symbioses, and we identify several putative transporter genes specific to Azolla–cyanobacterial symbiosis. These genomic resources will help in exploring the biotechnological potential of Azolla and address fundamental questions in the evolution of plant life.
TL;DR: A recent explosion of in vivo MRI-based approaches to identify and parcellate the brain on the basis of a wealth of different features, ranging from local properties of brain tissue to long-range connectivity patterns, in addition to structural and functional markers as mentioned in this paper.
Abstract: A defining aspect of brain organization is its spatial heterogeneity, which gives rise to multiple topographies at different scales. Brain parcellation - defining distinct partitions in the brain, be they areas or networks that comprise multiple discontinuous but closely interacting regions - is thus fundamental for understanding brain organization and function. The past decade has seen an explosion of in vivo MRI-based approaches to identify and parcellate the brain on the basis of a wealth of different features, ranging from local properties of brain tissue to long-range connectivity patterns, in addition to structural and functional markers. Given the high diversity of these various approaches, assessing the convergence and divergence among these ensuing maps is a challenge. Inter-individual variability adds to this challenge but also provides new opportunities when coupled with cross-species and developmental parcellation studies.
TL;DR: Evidence of atypical connectivity transitions between sensory and higher-order cortical areas in people with ASD is provided, which could underlie the diverse symptoms.
Abstract: One paradox of autism is the co-occurrence of deficits in sensory and higher-order socio-cognitive processing. Here, we examined whether these phenotypical patterns may relate to an overarching system-level imbalance-specifically a disruption in macroscale hierarchy affecting integration and segregation of unimodal and transmodal networks. Combining connectome gradient and stepwise connectivity analysis based on task-free functional magnetic resonance imaging (fMRI), we demonstrated atypical connectivity transitions between sensory and higher-order default mode regions in a large cohort of individuals with autism relative to typically-developing controls. Further analyses indicated that reduced differentiation related to perturbed stepwise connectivity from sensory towards transmodal areas, as well as atypical long-range rich-club connectivity. Supervised pattern learning revealed that hierarchical features predicted deficits in social cognition and low-level behavioral symptoms, but not communication-related symptoms. Our findings provide new evidence for imbalances in network hierarchy in autism, which offers a parsimonious reference frame to consolidate its diverse features.
Boston University1, University of Edinburgh2, University of Queensland3, Science for Life Laboratory4, King's College London5, Wake Forest University6, Icahn School of Medicine at Mount Sinai7, University of North Carolina at Chapel Hill8, Erasmus University Rotterdam9, National Institutes of Health10, University of Cambridge11, University of Alabama at Birmingham12, University of Washington13, University of Düsseldorf14, Emory University15, University of Texas Health Science Center at Houston16, Harvard University17, University of Minnesota18, Technische Universität München19, Ludwig Maximilian University of Munich20, UCLA Medical Center21, Max Planck Society22, McLean Hospital23, VA Boston Healthcare System24, Uppsala University25, University of Kentucky26, Columbia University27
TL;DR: An epigenome-wide association study of methylation of cytosine-phosphate-guanine dinucleotide (CpG) sites in relation to alcohol intake identified a robust alcohol-related DNA methylation signature and shown the potential utility ofDNA methylation as a clinically useful diagnostic test to detect current heavy alcohol consumption.
Abstract: The lack of reliable measures of alcohol intake is a major obstacle to the diagnosis and treatment of alcohol-related diseases. Epigenetic modifications such as DNA methylation may provide novel biomarkers of alcohol use. To examine this possibility, we performed an epigenome-wide association study of methylation of cytosine-phosphate-guanine dinucleotide (CpG) sites in relation to alcohol intake in 13 population-based cohorts (ntotal=13 317; 54% women; mean age across cohorts 42-76 years) using whole blood (9643 European and 2423 African ancestries) or monocyte-derived DNA (588 European, 263 African and 400 Hispanic ancestry) samples. We performed meta-analysis and variable selection in whole-blood samples of people of European ancestry (n=6926) and identified 144 CpGs that provided substantial discrimination (area under the curve=0.90-0.99) for current heavy alcohol intake (⩾42 g per day in men and ⩾28 g per day in women) in four replication cohorts. The ancestry-stratified meta-analysis in whole blood identified 328 (9643 European ancestry samples) and 165 (2423 African ancestry samples) alcohol-related CpGs at Bonferroni-adjusted P<1 × 10-7. Analysis of the monocyte-derived DNA (n=1251) identified 62 alcohol-related CpGs at P<1 × 10-7. In whole-blood samples of people of European ancestry, we detected differential methylation in two neurotransmitter receptor genes, the γ-Aminobutyric acid-A receptor delta and γ-aminobutyric acid B receptor subunit 1; their differential methylation was associated with expression levels of a number of genes involved in immune function. In conclusion, we have identified a robust alcohol-related DNA methylation signature and shown the potential utility of DNA methylation as a clinically useful diagnostic test to detect current heavy alcohol consumption.
TL;DR: A pathogen-inducible L-Lys catabolic pathway in plants that generates the N-hydroxylated amino acid NHP as a critical regulator of systemic acquired resistance to pathogen infection is identified.
01 Oct 2018
TL;DR: There was a good agreement of the incidence or prevalence of major chronic diseases in the outpatient DA with German reference data, and the higher diabetes prevalence in the DA is due to the increased number of outpatient visits of diabetes patients.
Abstract: Purpose The aim of this study was to evaluate the representativeness of diagnoses in the Disease Analyzer (DA) database for major chronic diseases (cancer, dementia, diabetes) Materials and methods DA contains anonymized longitudinal data on drug prescriptions, diagnoses as well as medical and demographic data directly obtained from the computer system of a representative sample of practices throughout Germany DA contains data from 2,498 practices with 78 million patients (2017) The distribution and sex-specific incidence of various cancer subsites among new cancer cases, the age- and sex-specific prevalence of dementia, and the prevalence of diabetes were assessed National reference data were obtained from official sources Results Mean age (43 years) and sex distribution (47% men) of primary care patients in DA were similar to the German population Among incident cancer cases, there was good agreement between DA data and national data with respect to the various cancer subsites (eg, breast cancer: DA 17%; reference: 15%) Furthermore, sex distribution was largely similar The age distribution of prevalent dementia was similar to national reference data, both in men (80 - 84 years: DA: 268%; reference: 270%) and in women (80 - 84 years: DA: 246%; reference: 241%) Diabetes prevalence in the DA (107%) was higher than in claims data from physicians (98%) or patients from statutory health insurances (99%) Conclusion There was a good agreement of the incidence or prevalence of major chronic diseases in the outpatient DA with German reference data The higher diabetes prevalence in the DA is due to the increased number of outpatient visits of diabetes patients
Geneva College1, Imperial College London2, University of Gothenburg3, Sahlgrenska University Hospital4, University of Milan5, National Institutes of Health6, University of Western Ontario7, Emory University8, Children's Hospital Oakland Research Institute9, Leipzig University10, University of Toronto11, Heidelberg University12, University of Graz13, Copenhagen University Hospital14, University of Copenhagen15, University of the Witwatersrand16, University of Düsseldorf17, University of São Paulo18, Hartford Hospital19, Hacettepe University20, State University of New York System21, Columbia University22
TL;DR: Long-term statin treatment is remarkably safe with a low risk of clinically relevant adverse effects as defined above, and the established cardiovascular benefits of statin therapy far outweigh the risk of adverse effects.
Abstract: Aims
To objectively appraise evidence for possible adverse effects of long-term statin therapy on glucose homeostasis, cognitive, renal and hepatic function, and risk for haemorrhagic stroke or cataract.
TL;DR: This work offers an alternative conceptual framework for preference stability that builds on research regarding the stability of personality traits in psychology and accommodates evidence on systematic changes in risk preferences over the life cycle, due to exogenous shocks such as economic crises or natural catastrophes, and due to temporary changes in self-control resources, emotions, or stress.
Abstract: It is ultimately an empirical question whether risk preferences are stable over time. The evidence comes from diverse strands of literature, covering the stability of risk preferences in panel data over shorter periods of time, life-cycle dynamics in risk preferences, the possibly long-lasting effects of exogenous shocks on risk preferences as well as temporary variations in risk preferences. Individual risk preferences appear to be persistent and moderately stable over time, but their degree of stability is too low to be reconciled with the assumption of perfect stability in neoclassical economic theory. We offer an alternative conceptual framework for preference stability that builds on research regarding the stability of personality traits in psychology. The definition of stability used in psychology implies high levels of rank-order stability across individuals and not that the individual will maintain the same level of a trait over time. Preference parameters are considered as distributions with a mean that is significantly but less than perfectly stable, plus some systematic variance. This framework accommodates evidence on systematic changes in risk preferences over the life cycle, due to exogenous shocks such as economic crises or natural catastrophes, and due to temporary changes in self-control resources, emotions, or stress. We note that research on the stability of (risk) preferences is conceptually at the heart of microeconomics and systematic changes in risk preferences have vital real-world consequences.
TL;DR: Precision medicine tools could augment effective therapeutic strategies aiming at the prevention of social functioning impairments in patients with CHR states or with ROD and machine learning outperformed expert prognostication.
Abstract: Importance Social and occupational impairments contribute to the burden of psychosis and depression. There is a need for risk stratification tools to inform personalized functional-disability preventive strategies for individuals in at-risk and early phases of these illnesses. Objective To determine whether predictors associated with social and role functioning can be identified in patients in clinical high-risk (CHR) states for psychosis or with recent-onset depression (ROD) using clinical, imaging-based, and combined machine learning; assess the geographic, transdiagnostic, and prognostic generalizability of machine learning and compare it with human prognostication; and explore sequential prognosis encompassing clinical and combined machine learning. Design, Setting, and Participants This multisite naturalistic study followed up patients in CHR states, with ROD, and with recent-onset psychosis, and healthy control participants for 18 months in 7 academic early-recognition services in 5 European countries. Participants were recruited between February 2014 and May 2016, and data were analyzed from April 2017 to January 2018. Main Outcomes and Measures Performance and generalizability of prognostic models. Results A total of 116 individuals in CHR states (mean [SD] age, 24.0 [5.1] years; 58 [50.0%] female) and 120 patients with ROD (mean [SD] age, 26.1 [6.1] years; 65 [54.2%] female) were followed up for a mean (SD) of 329 (142) days. Machine learning predicted the 1-year social-functioning outcomes with a balanced accuracy of 76.9% of patients in CHR states and 66.2% of patients with ROD using clinical baseline data. Balanced accuracy in models using structural neuroimaging was 76.2% in patients in CHR states and 65.0% in patients with ROD, and in combined models, it was 82.7% for CHR states and 70.3% for ROD. Lower functioning before study entry was a transdiagnostic predictor. Medial prefrontal and temporo-parieto-occipital gray matter volume (GMV) reductions and cerebellar and dorsolateral prefrontal GMV increments had predictive value in the CHR group; reduced mediotemporal and increased prefrontal-perisylvian GMV had predictive value in patients with ROD. Poor prognoses were associated with increased risk of psychotic, depressive, and anxiety disorders at follow-up in patients in the CHR state but not ones with ROD. Machine learning outperformed expert prognostication. Adding neuroimaging machine learning to clinical machine learning provided a 1.9-fold increase of prognostic certainty in uncertain cases of patients in CHR states, and a 10.5-fold increase of prognostic certainty for patients with ROD. Conclusions and Relevance Precision medicine tools could augment effective therapeutic strategies aiming at the prevention of social functioning impairments in patients with CHR states or with ROD.
University of St. Gallen1, Queen Mary University of London2, University of Bern3, Karolinska University Hospital4, Copenhagen University Hospital5, University of Paris-Sud6, Oslo University Hospital7, University of Barcelona8, University Medical Center Groningen9, Kantonsspital St. Gallen10, University Hospital of North Norway11, University of Cologne12, German Cancer Research Center13, Institute of Cancer Research14, University Health Network15, University of Düsseldorf16, Akershus University Hospital17, Comenius University in Bratislava18, University Hospital of Basel19, The Royal Marsden NHS Foundation Trust20, Lund University21, Peter MacCallum Cancer Centre22
TL;DR: The aim of the conference was to develop detailed recommendations on topics relating to testicular cancer that are not covered in detail in the current ESMO Clinical Practice Guidelines (CPGs) and where the available level of evidence is insufficient.
TL;DR: Filamentous fungi constitute a large group of eukaryotic microorganisms that grow by forming simple tube-like hyphae that are capable of differentiating into more-complex morphological structures and distinct cell types.
Abstract: Filamentous fungi constitute a large group of eukaryotic microorganisms that grow by forming simple tube-like hyphae that are capable of differentiating into more-complex morphological structures and distinct cell types. Hyphae form filamentous networks by extending at their tips while branching in subapical regions. Rapid tip elongation requires massive membrane insertion and extension of the rigid chitin-containing cell wall. This process is sustained by a continuous flow of secretory vesicles that depends on the coordinated action of the microtubule and actin cytoskeletons and the corresponding motors and associated proteins. Vesicles transport cell wall-synthesizing enzymes and accumulate in a special structure, the Spitzenkorper, before traveling further and fusing with the tip membrane. The place of vesicle fusion and growth direction are enabled and defined by the position of the Spitzenkorper, the so-called cell end markers, and other proteins involved in the exocytic process. Also important for tip extension is membrane recycling by endocytosis via early endosomes, which function as multipurpose transport vehicles for mRNA, septins, ribosomes, and peroxisomes. Cell integrity, hyphal branching, and morphogenesis are all processes that are largely dependent on vesicle and cytoskeleton dynamics. When hyphae differentiate structures for asexual or sexual reproduction or to mediate interspecies interactions, the hyphal basic cellular machinery may be reprogrammed through the synthesis of new proteins and/or the modification of protein activity. Although some transcriptional networks involved in such reprogramming of hyphae are well studied in several model filamentous fungi, clear connections between these networks and known determinants of hyphal morphogenesis are yet to be established.
TL;DR: In addition to known founder mutations, mutations of relatively high frequency were identified in specific racial/ethnic or geographic groups that may reflect founder mutations and which could be used in targeted (panel) first pass genotyping for specific populations.
Abstract: The prevalence and spectrum of germline mutations in BRCA1 and BRCA2 have been reported in single populations, with the majority of reports focused on White in Europe and North America. The Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) has assembled data on 18,435 families with BRCA1 mutations and 11,351 families with BRCA2 mutations ascertained from 69 centers in 49 countries on six continents. This study comprehensively describes the characteristics of the 1,650 unique BRCA1 and 1,731 unique BRCA2 deleterious (disease-associated) mutations identified in the CIMBA database. We observed substantial variation in mutation type and frequency by geographical region and race/ethnicity. In addition to known founder mutations, mutations of relatively high frequency were identified in specific racial/ethnic or geographic groups that may reflect founder mutations and which could be used in targeted (panel) first pass genotyping for specific populations. Knowledge of the population-specific mutational spectrum in BRCA1 and BRCA2 could inform efficient strategies for genetic testing and may justify a more broad-based oncogenetic testing in some populations.
University of Oslo1, CERN2, Cockcroft Institute3, University of Manchester4, Lancaster University5, Technische Universität München6, Max Planck Society7, Ulsan National Institute of Science and Technology8, University of Marburg9, University of Düsseldorf10, University of Liverpool11, ISCTE – University Institute of Lisbon12, Novosibirsk State University13, Budker Institute of Nuclear Physics14, Technical University of Denmark15, Instituto Superior Técnico16, TRIUMF17, Ludwig Maximilian University of Munich18, University of Milan19
TL;DR: Measurements of electrons accelerated up to two gigaelectronvolts at the AWAKE experiment are presented, in a demonstration of proton-driven plasma wakefield acceleration and are an important step towards the development of future high-energy particle accelerators.
Abstract: High-energy particle accelerators have been crucial in providing a deeper understanding of fundamental particles and the forces that govern their interactions. To increase the energy or to reduce the size of the accelerator, new acceleration schemes need to be developed. Plasma wakefield acceleration1–5, in which the electrons in a plasma are excited, leading to strong electric fields, is one such promising novel acceleration technique. Pioneering experiments have shown that an intense laser pulse6–9 or electron bunch10,11 traversing a plasma drives electric fields of tens of gigavolts per metre and above. These values are well beyond those achieved in conventional radio-frequency accelerators, which are limited to about 0.1 gigavolt per metre. A limitation of laser pulses and electron bunches is their low stored energy, which motivates the use of multiple stages to reach very high energies5,12. The use of proton bunches is compelling, as they have the potential to drive wakefields and accelerate electrons to high energy in a single accelerating stage13. The long proton bunches currently available can be used, as they undergo a process called self-modulation14–16, a particle–plasma interaction which longitudinally splits the bunch into a series of high-density microbunches, which then act resonantly to create large wakefields. The Advanced Wakefield (AWAKE) experiment at CERN17–19 uses intense bunches of protons, each of energy 400 gigaelectronvolts (GeV), with a total bunch energy of 19 kilojoules, to drive a wakefield in a 10-metre-long plasma. Bunches of electrons are injected into the wakefield formed by the proton microbunches. Here we present measurements of electrons accelerated up to 2 GeV at the AWAKE experiment. This constitutes the first demonstration of proton-driven plasma wakefield acceleration. The potential for this scheme to produce very high-energy electron bunches in a single accelerating stage20 means that the results shown here are a significant step towards the development of future high-energy particle accelerators21,22.