Showing papers by "University of Copenhagen published in 2019"
TL;DR: The latest version of STRING more than doubles the number of organisms it covers, and offers an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input.
Abstract: Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein-protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein-protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
10,584 citations
Northern Arizona University1, National Institutes of Health2, University of Minnesota3, University of California, Davis4, Woods Hole Oceanographic Institution5, Massachusetts Institute of Technology6, University of Copenhagen7, University of Trento8, Chinese Academy of Sciences9, University of California, San Francisco10, University of Pennsylvania11, Pacific Northwest National Laboratory12, North Carolina State University13, University of California, San Diego14, Institute for Systems Biology15, Dalhousie University16, University of British Columbia17, Statens Serum Institut18, Anschutz Medical Campus19, University of Washington20, Michigan State University21, Stanford University22, Harvard University23, Broad Institute24, Australian National University25, University of Düsseldorf26, University of New South Wales27, Sookmyung Women's University28, San Diego State University29, Howard Hughes Medical Institute30, Cornell University31, Max Planck Society32, Colorado State University33, Google34, Syracuse University35, Webster University36, United States Department of Agriculture37, University of Arkansas for Medical Sciences38, Colorado School of Mines39, University of Southern Mississippi40, National Oceanic and Atmospheric Administration41, University of California, Merced42, Wageningen University and Research Centre43, University of Arizona44, Environment Agency45, University of Florida46, Merck & Co.47
TL;DR: QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and R.K.P. and partial support was also provided by the following: grants NIH U54CA143925 and U54MD012388.
Abstract: QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and 1565057 to R.K. Partial support was also provided by the following: grants NIH U54CA143925 (J.G.C. and T.P.) and U54MD012388 (J.G.C. and T.P.); grants from the Alfred P. Sloan Foundation (J.G.C. and R.K.); ERCSTG project MetaPG (N.S.); the Strategic Priority Research Program of the Chinese Academy of Sciences QYZDB-SSW-SMC021 (Y.B.); the Australian National Health and Medical Research Council APP1085372 (G.A.H., J.G.C., Von Bing Yap and R.K.); the Natural Sciences and Engineering Research Council (NSERC) to D.L.G.; and the State of Arizona Technology and Research Initiative Fund (TRIF), administered by the Arizona Board of Regents, through Northern Arizona University. All NCI coauthors were supported by the Intramural Research Program of the National Cancer Institute. S.M.G. and C. Diener were supported by the Washington Research Foundation Distinguished Investigator Award.
8,821 citations
University of Glasgow1, Brigham and Women's Hospital2, Yale University3, University of Copenhagen4, University of Missouri–Kansas City5, National University of Cordoba6, Wrocław Medical University7, Harvard University8, University of Minnesota9, Charles University in Prague10, Saarland University11, National Yang-Ming University12, Taipei Veterans General Hospital13, Slovak Medical University14, Fudan University15, University of Calgary16, Libin Cardiovascular Institute of Alberta17, Sofia Medical University18, University of Gothenburg19, Semmelweis University20, University of São Paulo21, Montreal Heart Institute22, University of Toronto23, Uppsala University24, University of Wisconsin-Madison25, AstraZeneca26
TL;DR: Among patients with heart failure and a reduced ejection fraction, the risk of worsening heart failure or death from cardiovascular causes was lower among those who received dapagliflozin than amongThose who received placebo, regardless of the presence or absence of diabetes.
Abstract: Background In patients with type 2 diabetes, inhibitors of sodium–glucose cotransporter 2 (SGLT2) reduce the risk of a first hospitalization for heart failure, possibly through glucose-ind...
3,541 citations
TL;DR: A deep neural network-based approach that improves SP prediction across all domains of life and distinguishes between three types of prokaryotic SPs is presented.
Abstract: Signal peptides (SPs) are short amino acid sequences in the amino terminus of many newly synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can predict SPs from amino acid sequences, but most cannot distinguish between various types of signal peptides. We present a deep neural network-based approach that improves SP prediction across all domains of life and distinguishes between three types of prokaryotic SPs.
2,732 citations
TL;DR: eggNOG as discussed by the authors is a public database of orthology relationships, gene evolutionary histories and functional annotations, with a major update of the underlying genome sets, which have been expanded to 4445 representative bacteria and 168 archaea derived from 25 038 genomes.
Abstract: eggNOG is a public database of orthology relationships, gene evolutionary histories and functional annotations. Here, we present version 5.0, featuring a major update of the underlying genome sets, which have been expanded to 4445 representative bacteria and 168 archaea derived from 25 038 genomes, as well as 477 eukaryotic organisms and 2502 viral proteomes that were selected for diversity and filtered by genome quality. In total, 4.4M orthologous groups (OGs) distributed across 379 taxonomic levels were computed together with their associated sequence alignments, phylogenies, HMM models and functional descriptors. Precomputed evolutionary analysis provides fine-grained resolution of duplication/speciation events within each OG. Our benchmarks show that, despite doubling the amount of genomes, the quality of orthology assignments and functional annotations (80% coverage) has persisted without significant changes across this update. Finally, we improved eggNOG online services for fast functional annotation and orthology prediction of custom genomics or metagenomics datasets. All precomputed data are publicly available for downloading or via API queries at http://eggnog.embl.de.
1,971 citations
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11 Jul 2019TL;DR: The aim of the present paper is to provide an overview of state-of-the-art dose-response analysis, both in terms of general concepts that have evolved and matured over the years and by means of concrete examples.
Abstract: Dose-response analysis can be carried out using multi-purpose commercial statistical software, but except for a few special cases the analysis easily becomes cumbersome as relevant, non-standard output requires manual programming. The extension package drc for the statistical environment R provides a flexible and versatile infrastructure for dose-response analyses in general. The present version of the package, reflecting extensions and modifications over the last decade, provides a user-friendly interface to specify the model assumptions about the dose-response relationship and comes with a number of extractors for summarizing fitted models and carrying out inference on derived parameters. The aim of the present paper is to provide an overview of state-of-the-art dose-response analysis, both in terms of general concepts that have evolved and matured over the years and by means of concrete examples.
1,827 citations
Lundbeck1, Aarhus University2, Broad Institute3, Harvard University4, Karolinska Institutet5, Cardiff University6, Statens Serum Institut7, QIMR Berghofer Medical Research Institute8, University of Iceland9, deCODE genetics10, Mental Health Services11, Charité12, Semel Institute for Neuroscience and Human Behavior13, University of California, Los Angeles14, University of Queensland15, Oslo University Hospital16, King's College London17, University of Toronto18, VU University Amsterdam19, Radboud University Nijmegen20, Veterans Health Administration21, Yale University22, Children's Hospital of Philadelphia23, Haukeland University Hospital24, University of Bergen25, University of Pennsylvania26, University of Würzburg27, Maastricht University28, I.M. Sechenov First Moscow State Medical University29, Goethe University Frankfurt30, Universidade Federal do Rio Grande do Sul31, Icahn School of Medicine at Mount Sinai32, University of North Carolina at Chapel Hill33, Emory University34, University of Copenhagen35, Aarhus University Hospital36, State University of New York Upstate Medical University37
TL;DR: A genome-wide association meta-analysis of 20,183 individuals diagnosed with ADHD and 35,191 controls identifies variants surpassing genome- wide significance in 12 independent loci and implicates neurodevelopmental pathways and conserved regions of the genome as being involved in underlying ADHD biology.
Abstract: Attention deficit/hyperactivity disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 individuals diagnosed with ADHD and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, finding important new information about the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes and around brain-expressed regulatory marks. Analyses of three replication studies: a cohort of individuals diagnosed with ADHD, a self-reported ADHD sample and a meta-analysis of quantitative measures of ADHD symptoms in the population, support these findings while highlighting study-specific differences on genetic overlap with educational attainment. Strong concordance with GWAS of quantitative population measures of ADHD symptoms supports that clinical diagnosis of ADHD is an extreme expression of continuous heritable traits.
1,436 citations
Boston University1, Peking University2, Huazhong Agricultural University3, Birla Institute of Technology and Science4, Karlsruhe Institute of Technology5, Max Planck Society6, Université Paris-Saclay7, University of Copenhagen8, Norwegian Polar Institute9, Indian Institute of Science10, Ames Research Center11
TL;DR: Using satellite data from 2000–2017, this study finds striking greening of both China and India, driven primarily by land-use change, with forest growth and cropland intensification more important in China andCropland moreimportant in India.
Abstract: Satellite data show increasing leaf area of vegetation due to direct (human land-use management) and indirect factors (climate change, CO2 fertilization, nitrogen deposition, recovery from natural disturbances, etc.). Among these, climate change and CO2 fertilization effect seem to be the dominant drivers. However, recent satellite data (2000-2017) reveal a greening pattern that is strikingly prominent in China and India, and overlapping with croplands world-wide. China alone accounts for 25% of the global net increase in leaf area with only 6.6% of global vegetated area. The greening in China is from forests (42%) and croplands (32%), but in India is mostly from croplands (82%) with minor contribution from forests (4.4%). China is engineering ambitious programs to conserve and expand forests with the goal of mitigating land degradation, air pollution and climate change. Food production in China and India has increased by over 35% since 2000 mostly due to increasing harvested area through multiple cropping facilitated by fertilizer use and surface/ground-water irrigation. Our results indicate that the direct factor is a key driver of the "Greening Earth", accounting for over a third, and likely more, of the observed net increase in green leaf area. They highlight the need for realistic representation of human land-use practices in Earth system models.
1,389 citations
TL;DR: Data suggest that obesity may be far more common and requires more urgent attention than what large epidemiological studies suggest, and simply relying on BMI to assess its prevalence could hinder future interventions aimed at obesity prevention and control.
Abstract: Obesity is a complex multifactorial disease. The worldwide prevalence of overweight and obesity has doubled since 1980 to an extent that nearly a third of the world's population is now classified as overweight or obese. Obesity rates have increased in all ages and both sexes irrespective of geographical locality, ethnicity or socioeconomic status, although the prevalence of obesity is generally greater in older persons and women. This trend was similar across regions and countries, although absolute prevalence rates of overweight and obesity varied widely. For some developed countries, the prevalence rates of obesity seem to have levelled off during the past few years. Body mass index (BMI) is typically used to define overweight and obesity in epidemiological studies. However, BMI has low sensitivity and there is a large inter-individual variability in the percent body fat for any given BMI value, partly attributed to age, sex, and ethnicity. For instance, Asians have greater percent body fat than Caucasians for the same BMI. Greater cardiometabolic risk has also been associated with the localization of excess fat in the visceral adipose tissue and ectopic depots (such as muscle and liver), as well as in cases of increased fat to lean mass ratio (e.g. metabolically-obese normal-weight). These data suggest that obesity may be far more common and requires more urgent attention than what large epidemiological studies suggest. Simply relying on BMI to assess its prevalence could hinder future interventions aimed at obesity prevention and control.
1,255 citations
TL;DR: Hallmarks of ageing — genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, mitochondrial dysfunction, cellular senescence, stem cell exhaustion and altered intercellular communication — correlate with susceptibility to neurodegenerative disease.
Abstract: Ageing is the primary risk factor for most neurodegenerative diseases, including Alzheimer disease (AD) and Parkinson disease (PD). One in ten individuals aged ≥65 years has AD and its prevalence continues to increase with increasing age. Few or no effective treatments are available for ageing-related neurodegenerative diseases, which tend to progress in an irreversible manner and are associated with large socioeconomic and personal costs. This Review discusses the pathogenesis of AD, PD and other neurodegenerative diseases, and describes their associations with the nine biological hallmarks of ageing: genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, mitochondrial dysfunction, cellular senescence, deregulated nutrient sensing, stem cell exhaustion and altered intercellular communication. The central biological mechanisms of ageing and their potential as targets of novel therapies for neurodegenerative diseases are also discussed, with potential therapies including NAD+ precursors, mitophagy inducers and inhibitors of cellular senescence.
1,223 citations
TL;DR: In this 8th release of JASPAR, the CORE collection has been expanded with 245 new PFMs, and 156 PFMs were updated, and the genomic tracks, inference tool, and TF-binding profile similarity clusters were updated.
Abstract: JASPAR (http://jaspar.genereg.net) is an open-access database of curated, non-redundant transcription factor (TF)-binding profiles stored as position frequency matrices (PFMs) for TFs across multiple species in six taxonomic groups. In this 8th release of JASPAR, the CORE collection has been expanded with 245 new PFMs (169 for vertebrates, 42 for plants, 17 for nematodes, 10 for insects, and 7 for fungi), and 156 PFMs were updated (125 for vertebrates, 28 for plants and 3 for insects). These new profiles represent an 18% expansion compared to the previous release. JASPAR 2020 comes with a novel collection of unvalidated TF-binding profiles for which our curators did not find orthogonal supporting evidence in the literature. This collection has a dedicated web form to engage the community in the curation of unvalidated TF-binding profiles. Moreover, we created a Q&A forum to ease the communication between the user community and JASPAR curators. Finally, we updated the genomic tracks, inference tool, and TF-binding profile similarity clusters. All the data is available through the JASPAR website, its associated RESTful API, and through the JASPAR2020 R/Bioconductor package.
TL;DR: Genome-wide analysis identifies 30 loci associated with bipolar disorder, allowing for comparisons of shared genes and pathways with other psychiatric disorders, including schizophrenia and depression.
Abstract: Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder.
TL;DR: Two loci close to NKX6.3/MIR486 and RBSG4 are identified in the Canadian discovery cohort and replicated in the DiOGenes cohort and taken forward for Bayesian fine-mapping and functional assessment in flies.
Abstract: Hundreds of genetic variants have been associated with Body Mass Index (BMI) through genome-wide association studies (GWAS) using observational cohorts. However, the genetic contribution to efficient weight loss in response to dietary intervention remains unknown. We perform a GWAS in two large low-caloric diet intervention cohorts of obese participants. Two loci close to NKX6.3/MIR486 and RBSG4 are identified in the Canadian discovery cohort (n = 1166) and replicated in the DiOGenes cohort (n = 789). Modulation of HGTX (NKX6.3 ortholog) levels in Drosophila melanogaster leads to significantly altered triglyceride levels. Additional tissue-specific experiments demonstrate an action through the oenocytes, fly hepatocyte-like cells that regulate lipid metabolism. Our results identify genetic variants associated with the efficacy of weight loss in obese subjects and identify a role for NKX6.3 in lipid metabolism, and thereby possibly weight control. Individuals show large variability in their capacity to lose weight and maintain this weight. Here, the authors perform GWAS in two weight loss intervention cohorts and identify two genetic loci associated with weight loss that are taken forward for Bayesian fine-mapping and functional assessment in flies.
TL;DR: Many of the stringApp features are introduced and shown how they can be used to carry out complex network analysis and visualization tasks on a typical proteomics data set, all through the Cytoscape user interface.
Abstract: Protein networks have become a popular tool for analyzing and visualizing the often long lists of proteins or genes obtained from proteomics and other high-throughput technologies. One of the most popular sources of such networks is the STRING database, which provides protein networks for more than 2000 organisms, including both physical interactions from experimental data and functional associations from curated pathways, automatic text mining, and prediction methods. However, its web interface is mainly intended for inspection of small networks and their underlying evidence. The Cytoscape software, on the other hand, is much better suited for working with large networks and offers greater flexibility in terms of network analysis, import, and visualization of additional data. To include both resources in the same workflow, we created stringApp, a Cytoscape app that makes it easy to import STRING networks into Cytoscape, retains the appearance and many of the features of STRING, and integrates data from associated databases. Here, we introduce many of the stringApp features and show how they can be used to carry out complex network analysis and visualization tasks on a typical proteomics data set, all through the Cytoscape user interface. stringApp is freely available from the Cytoscape app store: http://apps.cytoscape.org/apps/stringapp .
TL;DR: Overall, GLP-1 receptor agonist treatment reduced MACE by 12% and there was no increase in risk of severe hypoglycaemia, pancreatitis, or pancreatic cancer.
TL;DR: Evidence that mitophagy is impaired in the hippocampus of AD patients, in induced pluripotent stem cell-derived human AD neurons, and in animal AD models is provided, suggesting that impaired removal of defective mitochondria is a pivotal event in AD pathogenesis and thatMitophagy represents a potential therapeutic intervention.
Abstract: Accumulation of damaged mitochondria is a hallmark of aging and age-related neurodegeneration, including Alzheimer's disease (AD). The molecular mechanisms of impaired mitochondrial homeostasis in AD are being investigated. Here we provide evidence that mitophagy is impaired in the hippocampus of AD patients, in induced pluripotent stem cell-derived human AD neurons, and in animal AD models. In both amyloid-β (Aβ) and tau Caenorhabditis elegans models of AD, mitophagy stimulation (through NAD+ supplementation, urolithin A, and actinonin) reverses memory impairment through PINK-1 (PTEN-induced kinase-1)-, PDR-1 (Parkinson's disease-related-1; parkin)-, or DCT-1 (DAF-16/FOXO-controlled germline-tumor affecting-1)-dependent pathways. Mitophagy diminishes insoluble Aβ1-42 and Aβ1-40 and prevents cognitive impairment in an APP/PS1 mouse model through microglial phagocytosis of extracellular Aβ plaques and suppression of neuroinflammation. Mitophagy enhancement abolishes AD-related tau hyperphosphorylation in human neuronal cells and reverses memory impairment in transgenic tau nematodes and mice. Our findings suggest that impaired removal of defective mitochondria is a pivotal event in AD pathogenesis and that mitophagy represents a potential therapeutic intervention.
Carlos III Health Institute1, University of Cologne2, University of Sydney3, Paris Descartes University4, Universidade Federal de Ciências da Saúde de Porto Alegre5, Pontifícia Universidade Católica do Rio Grande do Sul6, Medical University of Graz7, University of California, San Diego8, University of Copenhagen9, Katholieke Universiteit Leuven10, University of Bologna11, University of the Witwatersrand12, RMIT University13, McGill University14, Hacettepe University15, University of Paris16, Utrecht University17, Mazandaran University of Medical Sciences18, Tel Aviv University19, Hospital General de México20, Istituto Giannina Gaslini21, Mahidol University22, Federal University of São Paulo23, King's College, Aberdeen24, Comenius University in Bratislava25, Boston Children's Hospital26, Complutense University of Madrid27, Hospital General Universitario Gregorio Marañón28, University Hospital Heidelberg29, University of California, Los Angeles30, American University of Beirut31, Innsbruck Medical University32, University of Lausanne33, Catholic University of Korea34, Goethe University Frankfurt35, Erasmus University Rotterdam36, National and Kapodistrian University of Athens37, Monash University38, Federal University of Rio de Janeiro39, Catholic University of the Sacred Heart40, University of Health Sciences Antigua41, National Institutes of Health42, Amrita Institute of Medical Sciences and Research Centre43, University of Pittsburgh44, University of Melbourne45, Peter MacCallum Cancer Centre46, P. D. Hinduja Hospital and Medical Research Centre47, University of Southern California48, Duke University49, Singapore General Hospital50, NewYork–Presbyterian Hospital51, Cardiff University52, University of Texas Health Science Center at San Antonio53, Children's Hospital of Philadelphia54, Post Graduate Institute of Medical Education and Research55
TL;DR: Management of mucormycosis depends on recognising disease patterns and on early diagnosis, and limited availability of contemporary treatments burdens patients in low and middle income settings.
Abstract: Mucormycosis is a difficult to diagnose rare disease with high morbidity and mortality. Diagnosis is often delayed, and disease tends to progress rapidly. Urgent surgical and medical intervention is lifesaving. Guidance on the complex multidisciplinary management has potential to improve prognosis, but approaches differ between health-care settings. From January, 2018, authors from 33 countries in all United Nations regions analysed the published evidence on mucormycosis management and provided consensus recommendations addressing differences between the regions of the world as part of the "One World One Guideline" initiative of the European Confederation of Medical Mycology (ECMM). Diagnostic management does not differ greatly between world regions. Upon suspicion of mucormycosis appropriate imaging is strongly recommended to document extent of disease and is followed by strongly recommended surgical intervention. First-line treatment with high-dose liposomal amphotericin B is strongly recommended, while intravenous isavuconazole and intravenous or delayed release tablet posaconazole are recommended with moderate strength. Both triazoles are strongly recommended salvage treatments. Amphotericin B deoxycholate is recommended against, because of substantial toxicity, but may be the only option in resource limited settings. Management of mucormycosis depends on recognising disease patterns and on early diagnosis. Limited availability of contemporary treatments burdens patients in low and middle income settings. Areas of uncertainty were identified and future research directions specified.
TL;DR: The fourth update of “European Guidelines for the Management of RDS” by a European panel of experienced neonatologists and an expert perinatal obstetrician based on available literature up to the end of 2018 is reported.
Abstract: As management of respiratory distress syndrome (RDS) advances, clinicians must continually revise their current practice. We report the fourth update of “European Guidelines for the Management of RDS” by a European panel of experienced neonatologists and an expert perinatal obstetrician based on available literature up to the end of 2018. Optimising outcome for babies with RDS includes prediction of risk of preterm delivery, need for appropriate maternal transfer to a perinatal centre and timely use of antenatal steroids. Delivery room management has become more evidence-based, and protocols for lung protection including initiation of CPAP and titration of oxygen should be implemented immediately after birth. Surfactant replacement therapy is a crucial part of management of RDS, and newer protocols for its use recommend early administration and avoidance of mechanical ventilation. Methods of maintaining babies on non-invasive respiratory support have been further developed and may cause less distress and reduce chronic lung disease. As technology for delivering mechanical ventilation improves, the risk of causing lung injury should decrease, although minimising time spent on mechanical ventilation using caffeine and, if necessary, postnatal steroids are also important considerations. Protocols for optimising general care of infants with RDS are also essential with good temperature control, careful fluid and nutritional management, maintenance of perfusion and judicious use of antibiotics all being important determinants of best outcome.
TL;DR: These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community providing the theory and key practical aspects offlow cytometry enabling immunologists to avoid the common errors that often undermine immunological data.
Abstract: These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion.
University of Tübingen1, Novo Nordisk2, Imperial College London3, Duke University4, Lunenfeld-Tanenbaum Research Institute5, Ulster University6, University of Cambridge7, University of Pennsylvania8, Harvard University9, University of Copenhagen10, ETH Zurich11, Ruhr University Bochum12, University of Cincinnati Academic Health Center13, Janssen Pharmaceutica14, University of Michigan15, University of Cincinnati16, Indiana University17, Technische Universität München18
TL;DR: The numerous beneficial effects of GLP-1 render this hormone an interesting candidate for the development of pharmacotherapies to treat obesity, diabetes, and neurodegenerative disorders.
Abstract: Background The glucagon-like peptide-1 (GLP-1) is a multifaceted hormone with broad pharmacological potential. Among the numerous metabolic effects of GLP-1 are the glucose-dependent stimulation of insulin secretion, decrease of gastric emptying, inhibition of food intake, increase of natriuresis and diuresis, and modulation of rodent β-cell proliferation. GLP-1 also has cardio- and neuroprotective effects, decreases inflammation and apoptosis, and has implications for learning and memory, reward behavior, and palatability. Biochemically modified for enhanced potency and sustained action, GLP-1 receptor agonists are successfully in clinical use for the treatment of type-2 diabetes, and several GLP-1-based pharmacotherapies are in clinical evaluation for the treatment of obesity. Scope of review In this review, we provide a detailed overview on the multifaceted nature of GLP-1 and its pharmacology and discuss its therapeutic implications on various diseases. Major conclusions Since its discovery, GLP-1 has emerged as a pleiotropic hormone with a myriad of metabolic functions that go well beyond its classical identification as an incretin hormone. The numerous beneficial effects of GLP-1 render this hormone an interesting candidate for the development of pharmacotherapies to treat obesity, diabetes, and neurodegenerative disorders
Nasim Mavaddat1, Kyriaki Michailidou2, Kyriaki Michailidou1, Joe Dennis1 +307 more•Institutions (105)
TL;DR: This PRS, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset is developed and empirically validated and is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.
Abstract: Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.
11 Jul 2019
TL;DR: Gestational diabetes mellitus is the most common complication in pregnancy and has short-term and long-term effects in both mother and offspring, and dietary modification and increased physical activity are the primary treatments, but pharmacotherapy, usually insulin, is used when normoglycaemia is not achieved.
Abstract: Hyperglycaemia that develops during pregnancy and resolves after birth has been recognized for over 50 years, but uniform worldwide consensus is lacking about threshold hyperglycaemic levels that merit a diagnosis of ‘gestational diabetes mellitus’ (GDM) and thus treatment during pregnancy. GDM is currently the most common medical complication of pregnancy, and prevalence of undiagnosed hyperglycaemia and even overt diabetes in young women is increasing. Maternal overweight and obesity, later age at childbearing, previous history of GDM, family history of type 2 diabetes mellitus and ethnicity are major GDM risk factors. Diagnosis is usually performed using an oral glucose tolerance test (OGTT), although a non-fasting, glucose challenge test (GCT) is used in some parts of the world to screen women for those requiring a full OGTT. Dietary modification and increased physical activity are the primary treatments for GDM, but pharmacotherapy, usually insulin, is used when normoglycaemia is not achieved. Oral hypoglycaemic agents, principally metformin and glibenclamide (glyburide), are also used in some countries. Treatment improves immediate pregnancy outcomes, reducing excess fetal growth and adiposity and pregnancy-related hypertensive disorders. GDM increases the risk of long-term complications, including obesity, impaired glucose metabolism and cardiovascular disease, in both the mother and infant. Optimal management of mother and infant during long-term follow-up remains challenging, with very limited implementation of preventive strategies in most parts of the world. Gestational diabetes mellitus (GDM) is the most common complication in pregnancy and has short-term and long-term effects in both mother and offspring. This Primer discusses the definitions of GDM, diagnosis and management of the disease and areas requiring further research.
TL;DR: This review aims to present consensus recommendations for the optimal perioperative management of patients undergoing thoracic surgery (principally lung resection) using meta-analyses, randomized controlled trials, large non-randomized studies and reviews.
Abstract: Enhanced recovery after surgery is well established in specialties such as colorectal surgery. It is achieved through the introduction of multiple evidence-based perioperative measures that aim to diminish postoperative organ dysfunction while facilitating recovery. This review aims to present consensus recommendations for the optimal perioperative management of patients undergoing thoracic surgery (principally lung resection). A systematic review of meta-analyses, randomized controlled trials, large non-randomized studies and reviews was conducted for each protocol element. Smaller prospective and retrospective cohort studies were considered only when higher-level evidence was unavailable. The quality of the evidence base was graded by the authors and used to form consensus recommendations for each topic. Development of these recommendations was endorsed by the Enhanced Recovery after Surgery Society and the European Society for Thoracic Surgery. Recommendations were developed for a total of 45 enhanced recovery items covering topics related to preadmission, admission, intraoperative care and postoperative care. Most are based on good-quality studies. In some instances, good-quality data were not available, and subsequent recommendations are generic or based on data extrapolated from other specialties. In other cases, no recommendation can currently be made because either equipoise exists or there is a lack of available evidence. Recommendations are based not only on the quality of the evidence but also on the balance between desirable and undesirable effects. Key recommendations include preoperative counselling, nutritional screening, smoking cessation, prehabilitation for high-risk patients, avoidance of fasting, carbohydrate loading, avoidance of preoperative sedatives, venous thromboembolism prophylaxis, prevention of hypothermia, short-acting anaesthetics to facilitate early emergence, regional anaesthesia, nausea and vomiting control, opioid-sparing analgesia, euvolemic fluid management, minimally invasive surgery, early chest drain removal, avoidance of urinary catheters and early mobilization after surgery. These guidelines outline recommendations for the perioperative management of patients undergoing lung surgery based on the best available evidence. As the recommendation grade for most of the elements is strong, the use of a systematic perioperative care pathway has the potential to improve outcomes after surgery.
University of Copenhagen1, Lund University2, Molecular Medicine Partnership Unit3, ETH Zurich4, Fudan University5, German Cancer Research Center6, University of Trento7, University of São Paulo8, European Institute of Oncology9, Japan Society for the Promotion of Science10, Tokyo Institute of Technology11, University of Tokyo12, Osaka University13, National Presto Industries14, City University of New York15, National Institutes of Health16, Huntsman Cancer Institute17, University of Southern Denmark18
TL;DR: A meta-analysis of eight geographically and technically diverse fecal shotgun metagenomic studies of colorectal cancer identified a core set of 29 species significantly enriched in CRC metagenomes, establishing globally generalizable, predictive taxonomic and functional microbiome CRC signatures as a basis for future diagnostics.
Abstract: Association studies have linked microbiome alterations with many human diseases. However, they have not always reported consistent results, thereby necessitating cross-study comparisons. Here, a meta-analysis of eight geographically and technically diverse fecal shotgun metagenomic studies of colorectal cancer (CRC, n = 768), which was controlled for several confounders, identified a core set of 29 species significantly enriched in CRC metagenomes (false discovery rate (FDR) < 1 × 10−5). CRC signatures derived from single studies maintained their accuracy in other studies. By training on multiple studies, we improved detection accuracy and disease specificity for CRC. Functional analysis of CRC metagenomes revealed enriched protein and mucin catabolism genes and depleted carbohydrate degradation genes. Moreover, we inferred elevated production of secondary bile acids from CRC metagenomes, suggesting a metabolic link between cancer-associated gut microbes and a fat- and meat-rich diet. Through extensive validations, this meta-analysis firmly establishes globally generalizable, predictive taxonomic and functional microbiome CRC signatures as a basis for future diagnostics. Cross-study analysis defines fecal microbial species associated with colorectal cancer.
TL;DR: Recent progress is discussed in the understanding of the scope, functional diversity and mechanisms of non-histone protein acetylation, which regulates many cellular processes, such as transcription, DNA repair, signal transduction, protein folding and autophagy.
Abstract: Ne-lysine acetylation was discovered more than half a century ago as a post-translational modification of histones and has been extensively studied in the context of transcription regulation. In the past decade, proteomic analyses have revealed that non-histone proteins are frequently acetylated and constitute a major portion of the acetylome in mammalian cells. Indeed, non-histone protein acetylation is involved in key cellular processes relevant to physiology and disease, such as gene transcription, DNA damage repair, cell division, signal transduction, protein folding, autophagy and metabolism. Acetylation affects protein functions through diverse mechanisms, including by regulating protein stability, enzymatic activity, subcellular localization and crosstalk with other post-translational modifications and by controlling protein-protein and protein-DNA interactions. In this Review, we discuss recent progress in our understanding of the scope, functional diversity and mechanisms of non-histone protein acetylation.
German Cancer Research Center1, University of Tübingen2, University Hospital Heidelberg3, Geneva College4, Leiden University Medical Center5, Herlev Hospital6, University of Copenhagen7, Hebron University8, University of California, San Francisco9, Technion – Israel Institute of Technology10, University of Southampton11, University of Texas MD Anderson Cancer Center12, GlaxoSmithKline13, Charité14, University of Mainz15
TL;DR: In a phase I trial, highly individualized peptide vaccines against unmutated tumour antigens and neoepitopes elicited sustained responses in CD8+ and CD4+ T cells, respectively, in patients with newly diagnosed glioblastoma.
Abstract: Patients with glioblastoma currently do not sufficiently benefit from recent breakthroughs in cancer treatment that use checkpoint inhibitors1,2. For treatments using checkpoint inhibitors to be successful, a high mutational load and responses to neoepitopes are thought to be essential3. There is limited intratumoural infiltration of immune cells4 in glioblastoma and these tumours contain only 30–50 non-synonymous mutations5. Exploitation of the full repertoire of tumour antigens—that is, both unmutated antigens and neoepitopes—may offer more effective immunotherapies, especially for tumours with a low mutational load. Here, in the phase I trial GAPVAC-101 of the Glioma Actively Personalized Vaccine Consortium (GAPVAC), we integrated highly individualized vaccinations with both types of tumour antigens into standard care to optimally exploit the limited target space for patients with newly diagnosed glioblastoma. Fifteen patients with glioblastomas positive for human leukocyte antigen (HLA)-A*02:01 or HLA-A*24:02 were treated with a vaccine (APVAC1) derived from a premanufactured library of unmutated antigens followed by treatment with APVAC2, which preferentially targeted neoepitopes. Personalization was based on mutations and analyses of the transcriptomes and immunopeptidomes of the individual tumours. The GAPVAC approach was feasible and vaccines that had poly-ICLC (polyriboinosinic-polyribocytidylic acid-poly-l-lysine carboxymethylcellulose) and granulocyte–macrophage colony-stimulating factor as adjuvants displayed favourable safety and strong immunogenicity. Unmutated APVAC1 antigens elicited sustained responses of central memory CD8+ T cells. APVAC2 induced predominantly CD4+ T cell responses of T helper 1 type against predicted neoepitopes.
TL;DR: The results suggest that the risk of HIV transmission in gay couples through condomless sex when HIV viral load is suppressed is effectively zero, which supports the message of the U=U (undetectable equals untransmittable) campaign, and the benefits of early testing and treatment for HIV.
TL;DR: An approach to evaluate fragmentation patterns of cell-free DNA across the genome was developed, and found that profiles of healthy individuals reflected nucleosomal patterns of white blood cells, whereas patients with cancer had altered fragmentation profiles.
Abstract: Cell-free DNA in the blood provides a non-invasive diagnostic avenue for patients with cancer1. However, characteristics of the origins and molecular features of cell-free DNA are poorly understood. Here we developed an approach to evaluate fragmentation patterns of cell-free DNA across the genome, and found that profiles of healthy individuals reflected nucleosomal patterns of white blood cells, whereas patients with cancer had altered fragmentation profiles. We used this method to analyse the fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric or bile duct cancer and 245 healthy individuals. A machine learning model that incorporated genome-wide fragmentation features had sensitivities of detection ranging from 57% to more than 99% among the seven cancer types at 98% specificity, with an overall area under the curve value of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation-based cell-free DNA analyses detected 91% of patients with cancer. The results of these analyses highlight important properties of cell-free DNA and provide a proof-of-principle approach for the screening, early detection and monitoring of human cancer.
University of Évora1, University of Copenhagen2, Spanish National Research Council3, City College of New York4, City University of New York5, American Museum of Natural History6, University of York7, University of Freiburg8, University of Exeter9, University of Lausanne10, Stazione Zoologica Anton Dohrn11, Sapienza University of Rome12, École Polytechnique Fédérale de Lausanne13, Norwegian University of Science and Technology14, Imperial College London15
TL;DR: It is argued that implementation of agreed-upon standards for models in biodiversity assessments would promote transparency and repeatability, eventually leading to higher quality of the models and the inferences used in assessments.
Abstract: Demand for models in biodiversity assessments is rising, but which models are adequate for the task? We propose a set of best-practice standards and detailed guidelines enabling scoring of studies based on species distribution models for use in biodiversity assessments. We reviewed and scored 400 modeling studies over the past 20 years using the proposed standards and guidelines. We detected low model adequacy overall, but with a marked tendency of improvement over time in model building and, to a lesser degree, in biological data and model evaluation. We argue that implementation of agreed-upon standards for models in biodiversity assessments would promote transparency and repeatability, eventually leading to higher quality of the models and the inferences used in assessments. We encourage broad community participation toward the expansion and ongoing development of the proposed standards and guidelines.
TL;DR: The genetic architecture of anorexia nervosa mirrors its clinical presentation, showing significant genetic correlations with psychiatric disorders, physical activity, and metabolic (including glycemic), lipid and anthropometric traits, independent of the effects of common variants associated with body-mass index.
Abstract: Characterized primarily by a low body-mass index, anorexia nervosa is a complex and serious illness1, affecting 0.9-4% of women and 0.3% of men2-4, with twin-based heritability estimates of 50-60%5. Mortality rates are higher than those in other psychiatric disorders6, and outcomes are unacceptably poor7. Here we combine data from the Anorexia Nervosa Genetics Initiative (ANGI)8,9 and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and conduct a genome-wide association study of 16,992 cases of anorexia nervosa and 55,525 controls, identifying eight significant loci. The genetic architecture of anorexia nervosa mirrors its clinical presentation, showing significant genetic correlations with psychiatric disorders, physical activity, and metabolic (including glycemic), lipid and anthropometric traits, independent of the effects of common variants associated with body-mass index. These results further encourage a reconceptualization of anorexia nervosa as a metabo-psychiatric disorder. Elucidating the metabolic component is a critical direction for future research, and paying attention to both psychiatric and metabolic components may be key to improving outcomes.