Showing papers by "Pompeu Fabra University published in 2019"
European Bioinformatics Institute1, University of California, Santa Cruz2, University of Lausanne3, University of Bern4, Broad Institute5, Massachusetts Institute of Technology6, Yale University7, Brunel University London8, University of Warsaw9, Ohio State University10, Pompeu Fabra University11, King's College London12
TL;DR: This work generates primary data, creates bioinformatics tools and provides analysis to support the work of expert manual gene annotators and automated gene annotation pipelines to identify and characterise gene loci to the highest standard.
Abstract: The accurate identification and description of the genes in the human and mouse genomes is a fundamental requirement for high quality analysis of data informing both genome biology and clinical genomics. Over the last 15 years, the GENCODE consortium has been producing reference quality gene annotations to provide this foundational resource. The GENCODE consortium includes both experimental and computational biology groups who work together to improve and extend the GENCODE gene annotation. Specifically, we generate primary data, create bioinformatics tools and provide analysis to support the work of expert manual gene annotators and automated gene annotation pipelines. In addition, manual and computational annotation workflows use any and all publicly available data and analysis, along with the research literature to identify and characterise gene loci to the highest standard. GENCODE gene annotations are accessible via the Ensembl and UCSC Genome Browsers, the Ensembl FTP site, Ensembl Biomart, Ensembl Perl and REST APIs as well as https://www.gencodegenes.org.
2,095 citations
TL;DR: The DisGeNET platform, a knowledge management platform integrating and standardizing data about disease associated genes and variants from multiple sources, is an interoperable resource supporting a variety of applications in genomic medicine and drug R&D.
Abstract: One of the most pressing challenges in genomic medicine is to understand the role played by genetic variation in health and disease. Thanks to the exploration of genomic variants at large scale, hundreds of thousands of disease-associated loci have been uncovered. However, the identification of variants of clinical relevance is a significant challenge that requires comprehensive interrogation of previous knowledge and linkage to new experimental results. To assist in this complex task, we created DisGeNET (http://www.disgenet.org/), a knowledge management platform integrating and standardizing data about disease associated genes and variants from multiple sources, including the scientific literature. DisGeNET covers the full spectrum of human diseases as well as normal and abnormal traits. The current release covers more than 24 000 diseases and traits, 17 000 genes and 117 000 genomic variants. The latest developments of DisGeNET include new sources of data, novel data attributes and prioritization metrics, a redesigned web interface and recently launched APIs. Thanks to the data standardization, the combination of expert curated information with data automatically mined from the scientific literature, and a suite of tools for accessing its publicly available data, DisGeNET is an interoperable resource supporting a variety of applications in genomic medicine and drug R&D.
1,183 citations
University of Saskatchewan1, Centre for Environment, Fisheries and Aquaculture Science2, Natural History Museum3, University of Rhode Island4, Sewanee: The University of the South5, Academy of Sciences of the Czech Republic6, National Institutes of Health7, Saint Petersburg State University8, University of Salzburg9, Centre national de la recherche scientifique10, Mississippi State University11, Science for Life Laboratory12, Uppsala University13, Charles University in Prague14, Spanish National Research Council15, Kaiserslautern University of Technology16, University of Duisburg-Essen17, University of Oslo18, Dalhousie University19, Pierre-and-Marie-Curie University20, American Museum of Natural History21, University of Michigan22, University of Warsaw23, University of São Paulo24, University of Paris25, University of British Columbia26, University of Guelph27, Royal Botanic Garden Edinburgh28, Kyungpook National University29, University of Geneva30, University of Alabama31, Pompeu Fabra University32, Edinburgh Napier University33, University of Arkansas34, Hosei University35, Oklahoma State University–Stillwater36, Chinese Academy of Sciences37
TL;DR: It is confirmed that eukaryotes form at least two domains, the loss of monophyly in the Excavata, robust support for the Haptista and Cryptista, and suggested primer sets for DNA sequences from environmental samples that are effective for each clade are provided.
Abstract: This revision of the classification of eukaryotes follows that of Adl et al., 2012 [J. Euk. Microbiol. 59(5)] and retains an emphasis on protists. Changes since have improved the resolution of many ...
750 citations
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.
698 citations
Humboldt University of Berlin1, Oregon Health & Science University2, Queen Mary University of London3, Lawrence Berkeley National Laboratory4, European Bioinformatics Institute5, Oregon State University6, University of North Carolina at Chapel Hill7, Curtin University8, Government of Western Australia9, Chestnut Hill College10, Vrije Universiteit Brussel11, Garvan Institute of Medical Research12, University of Toronto13, National Institutes of Health14, Medical College of Wisconsin15, Pompeu Fabra University16, Manchester Royal Eye Hospital17, French Institute of Health and Medical Research18, Sanford Health19, Stanford University20, Utrecht University21, Newcastle University22, Icahn School of Medicine at Mount Sinai23, University College London24, University of Strasbourg25, Children's Hospital of Philadelphia26, University of Connecticut27
TL;DR: The HPO’s interoperability with other ontologies has enabled it to be used to improve diagnostic accuracy by incorporating model organism data and plays a key role in the popular Exomiser tool, which identifies potential disease-causing variants from whole-exome or whole-genome sequencing data.
Abstract: The Human Phenotype Ontology (HPO)-a standardized vocabulary of phenotypic abnormalities associated with 7000+ diseases-is used by thousands of researchers, clinicians, informaticians and electronic health record systems around the world. Its detailed descriptions of clinical abnormalities and computable disease definitions have made HPO the de facto standard for deep phenotyping in the field of rare disease. The HPO's interoperability with other ontologies has enabled it to be used to improve diagnostic accuracy by incorporating model organism data. It also plays a key role in the popular Exomiser tool, which identifies potential disease-causing variants from whole-exome or whole-genome sequencing data. Since the HPO was first introduced in 2008, its users have become both more numerous and more diverse. To meet these emerging needs, the project has added new content, language translations, mappings and computational tooling, as well as integrations with external community data. The HPO continues to collaborate with clinical adopters to improve specific areas of the ontology and extend standardized disease descriptions. The newly redesigned HPO website (www.human-phenotype-ontology.org) simplifies browsing terms and exploring clinical features, diseases, and human genes.
532 citations
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.
517 citations
TL;DR: This article reviews the mechanisms of resistance, epidemiology, and clinical impact and current and upcoming therapeutic options of Pseudomonas aeruginosa, and describes future options, such as use of vaccines, antibodies, bacteriocins, anti-quorum sensing, and bacteriophages.
Abstract: In recent years, the worldwide spread of the so-called high-risk clones of multidrug-resistant or extensively drug-resistant (MDR/XDR) Pseudomonas aeruginosa has become a public health threat. This article reviews their mechanisms of resistance, epidemiology, and clinical impact and current and upcoming therapeutic options. In vitro and in vivo treatment studies and pharmacokinetic and pharmacodynamic (PK/PD) models are discussed. Polymyxins are reviewed as an important therapeutic option, outlining dosage, pharmacokinetics and pharmacodynamics, and their clinical efficacy against MDR/XDR P. aeruginosa infections. Their narrow therapeutic window and potential for combination therapy are also discussed. Other "old" antimicrobials, such as certain β-lactams, aminoglycosides, and fosfomycin, are reviewed here. New antipseudomonals, as well as those in the pipeline, are also reviewed. Ceftolozane-tazobactam has clinical activity against a significant percentage of MDR/XDR P. aeruginosa strains, and its microbiological and clinical data, as well as recommendations for improving its use against these bacteria, are described, as are those for ceftazidime-avibactam, which has better activity against MDR/XDR P. aeruginosa, especially strains with certain specific mechanisms of resistance. A section is devoted to reviewing upcoming active drugs such as imipenem-relebactam, cefepime-zidebactam, cefiderocol, and murepavadin. Finally, other therapeutic strategies, such as use of vaccines, antibodies, bacteriocins, anti-quorum sensing, and bacteriophages, are described as future options.
395 citations
Erasmus University Rotterdam1, VU University Amsterdam2, University of Zurich3, Harvard University4, Cornell University5, Hospital for Special Surgery6, University of Amsterdam7, University of Toronto8, University of Copenhagen9, Statens Serum Institut10, University of Queensland11, University of Essex12, ETH Zurich13, Broad Institute14, University of Oxford15, Max Planck Society16, German Institute for Economic Research17, Pompeu Fabra University18, University of Edinburgh19, University of Oulu20, University of California, San Diego21, University of Lübeck22, Institut Pere Mata23, University of Colorado Boulder24, University of Konstanz25, University of North Carolina at Chapel Hill26, University of Fribourg27, Karolinska Institutet28, St. Joseph's Healthcare Hamilton29, University of Guelph30, Ludwig Maximilian University of Munich31, University of Cologne32, University of Innsbruck33, University College London34, University of Chicago35, Imperial College London36, University of Tartu37, Stockholm School of Economics38, Geisinger Health System39, Catalan Institution for Research and Advanced Studies40, University of Mainz41, University of Southern California42, Uniformed Services University of the Health Sciences43, Western General Hospital44, Translational Research Institute45, University of Minnesota46, New York University47, National Bureau of Economic Research48
TL;DR: This paper found evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of their other GWAS, and general risk-tolerance is genetically correlated with a range of risky behaviors.
Abstract: Humans vary substantially in their willingness to take risks. In a combined sample of over 1 million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. Across all GWAS, we identified hundreds of associated loci, including 99 loci associated with general risk tolerance. We report evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is genetically correlated ([Formula: see text] ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near SNPs associated with general risk tolerance are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We found no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.
395 citations
11 Jul 2019
TL;DR: A framework for identifying a broad range of menaces in the research and practices around social data is presented, including biases and inaccuracies at the source of the data, but also introduced during processing.
Abstract: Social data in digital form—including user-generated content, expressed or implicit relations between people, and behavioral traces—are at the core of popular applications and platforms, driving the research agenda of many researchers. The promises of social data are many, including understanding “what the world thinks” about a social issue, brand, celebrity, or other entity, as well as enabling better decision-making in a variety of fields including public policy, healthcare, and economics. Many academics and practitioners have warned against the naive usage of social data. There are biases and inaccuracies occurring at the source of the data, but also introduced during processing. There are methodological limitations and pitfalls, as well as ethical boundaries and unexpected consequences that are often overlooked. This paper recognizes the rigor with which these issues are addressed by different researchers varies across a wide range. We identify a variety of menaces in the practices around social data use, and organize them in a framework that helps to identify them.
“For your own sanity, you have to remember that not all problems can be solved. Not all problems can be solved, but all problems can be illuminated.” –Ursula Franklin1
379 citations
Harvard University1, Radcliffe Institute for Advanced Study2, Broad Institute3, University of California, Berkeley4, Howard Hughes Medical Institute5, Massachusetts Institute of Technology6, Sapienza University of Rome7, University of Padua8, Queen's University Belfast9, Russian Academy of Sciences10, Al-Farabi University11, University of Pennsylvania12, University College Dublin13, University of Vienna14, Pennsylvania State University15, Max Planck Society16, Birbal Sahni Institute of Palaeobotany17, Centre for Cellular and Molecular Biology18, Emory University19, Centre national de la recherche scientifique20, Kyrgyz National University21, Altai State University22, Academy of Sciences of the Czech Republic23, University of Oxford24, South Ural State University25, Kemerovo State University26, Northwest University (China)27, University College London28, University of Pittsburgh29, Samara State University30, Chelyabinsk State University31, University of Bologna32, Academy of Sciences of Uzbekistan33, University of Winnipeg34, Simon Fraser University35, National Museum of Natural History36, Tomsk State University37, Naturhistorisches Museum38, Národní muzeum39, Hazara University40, Deccan College Post-Graduate and Research Institute41, Pompeu Fabra University42, Hartwick College43, University of California, Santa Barbara44, Washington University in St. Louis45
TL;DR: It is shown that Steppe ancestry then integrated further south in the first half of the second millennium BCE, contributing up to 30% of the ancestry of modern groups in South Asia, supporting the idea that the archaeologically documented dispersal of domesticates was accompanied by the spread of people from multiple centers of domestication.
Abstract: By sequencing 523 ancient humans, we show that the primary source of ancestry in modern South Asians is a prehistoric genetic gradient between people related to early hunter-gatherers of Iran and Southeast Asia. After the Indus Valley Civilization's decline, its people mixed with individuals in the southeast to form one of the two main ancestral populations of South Asia, whose direct descendants live in southern India. Simultaneously, they mixed with descendants of Steppe pastoralists who, starting around 4000 years ago, spread via Central Asia to form the other main ancestral population. The Steppe ancestry in South Asia has the same profile as that in Bronze Age Eastern Europe, tracking a movement of people that affected both regions and that likely spread the distinctive features shared between Indo-Iranian and Balto-Slavic languages.
354 citations
TL;DR: Perez and Lehner summarize recent discoveries regarding epigenetic inheritance across generations and review the molecular mechanisms underlying non-DNA sequence-based transmissions.
Abstract: Animals transmit not only DNA but also other molecules, such as RNA, proteins and metabolites, to their progeny via gametes. It is currently unclear to what extent these molecules convey information between generations and whether this information changes according to their physiological state and environment. Here, we review recent work on the molecular mechanisms by which 'epigenetic' information is transmitted between generations over different timescales, and the importance of this information for development and physiology.
University of Paris1, University of São Paulo2, Polytechnic University of Milan3, University of Texas Southwestern Medical Center4, Université de Montréal5, Paris Descartes University6, Pompeu Fabra University7, University of British Columbia8, University of New South Wales9, Loyola University Chicago10, Veterans Health Administration11, Katholieke Universiteit Leuven12, Guangzhou Medical University13, Kingston General Hospital14, University of Edinburgh15, University of Verona16, Laval University17, University of Zurich18, National and Kapodistrian University of Athens19, St. Paul's Hospital20, Northumbria University21, University of Grenoble22
TL;DR: This ERS task force summarises the most recent scientific and methodological developments regarding respiratory mechanics and respiratory muscle assessment by addressing the validity, precision, reproducibility, prognostic value and responsiveness to interventions of various methods.
Abstract: Assessing respiratory mechanics and muscle function is critical for both clinical practice and research purposes. Several methodological developments over the past two decades have enhanced our understanding of respiratory muscle function and responses to interventions across the spectrum of health and disease. They are especially useful in diagnosing, phenotyping and assessing treatment efficacy in patients with respiratory symptoms and neuromuscular diseases. Considerable research has been undertaken over the past 17 years, since the publication of the previous American Thoracic Society (ATS)/European Respiratory Society (ERS) statement on respiratory muscle testing in 2002. Key advances have been made in the field of mechanics of breathing, respiratory muscle neurophysiology (electromyography, electroencephalography and transcranial magnetic stimulation) and on respiratory muscle imaging (ultrasound, optoelectronic plethysmography and structured light plethysmography). Accordingly, this ERS task force reviewed the field of respiratory muscle testing in health and disease, with particular reference to data obtained since the previous ATS/ERS statement. It summarises the most recent scientific and methodological developments regarding respiratory mechanics and respiratory muscle assessment by addressing the validity, precision, reproducibility, prognostic value and responsiveness to interventions of various methods. A particular emphasis is placed on assessment during exercise, which is a useful condition to stress the respiratory system.
TL;DR: Three-dimensional genome architecture has important roles in the regulation of gene expression and is therefore a key determinant of cell identity in normal development and in disease states.
Abstract: How cells adopt different identities has long fascinated biologists. Signal transduction in response to environmental cues results in the activation of transcription factors that determine the gene-expression program characteristic of each cell type. Technological advances in the study of 3D chromatin folding are bringing the role of genome conformation in transcriptional regulation to the fore. Characterizing this role of genome architecture has profound implications, not only for differentiation and development but also for diseases including developmental malformations and cancer. Here we review recent studies indicating that the interplay between transcription and genome conformation is a driving force for cell-fate decisions.
Nicole M. Warrington1, Robin N Beaumont2, Momoko Horikoshi3, Felix R. Day4 +242 more•Institutions (79)
TL;DR: An expanded GWAS of birth weight and subsequent analysis using structural equation modeling and Mendelian randomization decomposes maternal and fetal genetic contributions and causal links between birth weight, blood pressure and glycemic traits.
Abstract: Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.
TL;DR: In this article, the authors reformulate coarse-graining as a supervised machine learning problem and use statistical learning theory to decompose the coarsegraining error and cross-validation to select and compare the performance of different models.
Abstract: Atomistic or ab initio molecular dynamics simulations are widely used to predict thermodynamics and kinetics and relate them to molecular structure. A common approach to go beyond the time- and length-scales accessible with such computationally expensive simulations is the definition of coarse-grained molecular models. Existing coarse-graining approaches define an effective interaction potential to match defined properties of high-resolution models or experimental data. In this paper, we reformulate coarse-graining as a supervised machine learning problem. We use statistical learning theory to decompose the coarse-graining error and cross-validation to select and compare the performance of different models. We introduce CGnets, a deep learning approach, that learns coarse-grained free energy functions and can be trained by a force-matching scheme. CGnets maintain all physically relevant invariances and allow one to incorporate prior physics knowledge to avoid sampling of unphysical structures. We show tha...
TL;DR: To assess the association between gender and suicide attempt/death and identify gender-specific risk/protective factors in adolescents/young adults, population-based longitudinal studies considering non-clinical populations, aged 12–26 years, assessing associations between sex and suicide attempts/death, or evaluating their gender risk/ protective factors were included.
Abstract: To assess the association between gender and suicide attempt/death and identify gender-specific risk/protective factors in adolescents/young adults.
Systematic review (5 databases until January 2017). Population-based longitudinal studies considering non-clinical populations, aged 12–26 years, assessing associations between gender and suicide attempts/death, or evaluating their gender risk/protective factors, were included. Random effect meta-analyses were performed. Sixty-seven studies were included. Females presented higher risk of suicide attempt (OR 1.96, 95% CI 1.54–2.50), and males for suicide death (HR 2.50, 95% CI 1.8–3.6). Common risk factors of suicidal behaviors for both genders are previous mental or substance abuse disorder and exposure to interpersonal violence. Female-specific risk factors for suicide attempts are eating disorder, posttraumatic stress disorder, bipolar disorder, being victim of dating violence, depressive symptoms, interpersonal problems and previous abortion. Male-specific risk factors for suicide attempt are disruptive behavior/conduct problems, hopelessness, parental separation/divorce, friend’s suicidal behavior, and access to means. Male-specific risk factors for suicide death are drug abuse, externalizing disorders, and access to means. For females, no risk factors for suicide death were studied. More evidence about female-specific risk/protective factors of suicide death, for adolescent/young adults, is needed.
TL;DR: The OTFS input–output relation has a simple sparse structure that enables one to use low-complexity detection algorithms and the reduction of out-of-band power may introduce nonuniform channel gains for the transmitted symbols, thus impairing the overall error performance.
Abstract: In this paper, we model $M\times N$ orthogonal time frequency space modulation (OTFS) over a $P$ -path doubly dispersive channel with delays less than $\tau _{\max }$ and Doppler shifts in the range $(
u _{\min },
u _{\max })$ . We first derive in a simple matrix form the input–output relation in the delay-Doppler domain for practical (e.g., rectangular) pulse-shaping waveforms, next generalize it to arbitrary waveforms. This relation extends the original OTFS input–output approach, which assumes ideal pulse-shaping waveforms that are bi-orthogonal in both time and frequency. We show that the OTFS input–output relation has a simple sparse structure that enables one to use low-complexity detection algorithms. Different from previous work, only a single cyclic prefix is added at the end of the OTFS frame, significantly reducing the overhead, without incurring any penalty from the loss of bi-orthogonality of the pulse-shaping waveforms. Finally, we compare the OTFS performance with different pulse-shaping waveforms, and show that the reduction of out-of-band power may introduce nonuniform channel gains for the transmitted symbols, thus impairing the overall error performance.
French Institute of Health and Medical Research1, University of Liège2, University of Buenos Aires3, Collège de France4, Université Paris-Saclay5, Pompeu Fabra University6, National Scientific and Technical Research Council7, University of Western Ontario8, University of Birmingham9, Columbia University10, Cornell University11
TL;DR: The results establish that consciousness rests on the brain’s ability to sustain rich brain dynamics and pave the way for determining specific and generalizable fingerprints of conscious and unconscious states.
Abstract: Adopting the framework of brain dynamics as a cornerstone of human consciousness, we determined whether dynamic signal coordination provides specific and generalizable patterns pertaining to conscious and unconscious states after brain damage. A dynamic pattern of coordinated and anticoordinated functional magnetic resonance imaging signals characterized healthy individuals and minimally conscious patients. The brains of unresponsive patients showed primarily a pattern of low interareal phase coherence mainly mediated by structural connectivity, and had smaller chances to transition between patterns. The complex pattern was further corroborated in patients with covert cognition, who could perform neuroimaging mental imagery tasks, validating this pattern’s implication in consciousness. Anesthesia increased the probability of the less complex pattern to equal levels, validating its implication in unconsciousness. Our results establish that consciousness rests on the brain’s ability to sustain rich brain dynamics and pave the way for determining specific and generalizable fingerprints of conscious and unconscious states.
Harvard University1, Howard Hughes Medical Institute2, Broad Institute3, Max Planck Society4, University of Zaragoza5, University of Huddersfield6, University of Minho7, Pompeu Fabra University8, University of Vienna9, Pennsylvania State University10, University of Coimbra11, University of Zurich12, University of Granada13, University of the Basque Country14, Rovira i Virgili University15, National University of Distance Education16, University of Málaga17, University of Barcelona18, University of Valencia19, Autonomous University of Barcelona20, University of Lisbon21, Facultad de Filosofía y Letras22, University of Almería23, University of Cádiz24, University of Salamanca25, University of Iowa26, University of Las Palmas de Gran Canaria27, Mount Mercy University28, Autonomous University of Madrid29, Complutense University of Madrid30, University of Cantabria31, Liverpool John Moores University32, Gibraltar Hardware33, Anglia Ruskin University34, Spanish National Research Council35, University of California, Santa Barbara36, University of Basel37, Danube Private University38, University of Adelaide39
TL;DR: It is revealed that present-day Basques are best described as a typical Iron Age population without the admixture events that later affected the rest of Iberia, and how the ancestry of the peninsula was transformed by gene flow from North Africa and the eastern Mediterranean is document.
Abstract: J.M.F., F.J.L.-C., J.I.M., F.X.O., J.D., and M.S.B. were supported by HAR2017-86509-P, HAR2017-87695-P, and SGR2017-11 from the Generalitat de Catalunya, AGAUR agency. C.L.-F. was supported by Obra Social La Caixa and by FEDER-MINECO (BFU2015- 64699-P). L.B.d.L.E. was supported by REDISCO-HAR2017-88035-P (Plan Nacional I+D+I, MINECO). C.L., P.R., and C.Bl. were supported by MINECO (HAR2016-77600-P). A.Esp., J.V.-V., G.D., and D.C.S.-G. were supported by MINECO (HAR2009-10105 and HAR2013-43851-P). D.J.K. and B.J.C. were supported by NSF BCS-1460367. K.T.L., A.W., and J.M. were supported by NSF BCS-1153568. J.F.-E. and J.A.M.-A. were supported by IT622-13 Gobierno Vasco, Diputacion Foral de Alava, and Diputacion Foral de Gipuzkoa. We acknowledge support from the Portuguese Foundation for Science and Technology (PTDC/EPH-ARQ/4164/2014) and the FEDER-COMPETE 2020 project 016899. P.S. was supported by the FCT Investigator Program (IF/01641/2013), FCT IP, and ERDF (COMPETE2020 – POCI). M.Si. and K.D. were supported by a Leverhulme Trust Doctoral Scholarship awarded to M.B.R. and M.P. D.R. was supported by an Allen Discovery Center grant from the Paul Allen Foundation, NIH grant GM100233, and the Howard Hughes Medical Institute. V.V.-M. and W.H. were supported by the Max Planck Society.
Erasmus University Rotterdam1, University of Southampton2, University Hospital Southampton NHS Foundation Trust3, University of Porto4, Sorbonne5, Paris Descartes University6, University of Crete7, Maastricht University8, University of Southern California9, National and Kapodistrian University of Athens10, University Medical Center Groningen11, Université de Sherbrooke12, Norwegian Institute of Public Health13, University of Bologna14, Nofer Institute of Occupational Medicine15, University of California, Davis16, Harvard University17, University of Illinois at Chicago18, University of Valencia19, National Institutes of Health20, University of Turku21, University of Bristol22, Helmholtz Centre for Environmental Research - UFZ23, Jagiellonian University Medical College24, Åbo Akademi University25, Harokopio University26, Public Health Research Institute27, University of Copenhagen28, University of Southern Denmark29, La Trobe University30, University of Helsinki31, University of Turin32, Radboud University Nijmegen33, University of Trieste34, University of Bergen35, Ludwig Maximilian University of Munich36, Slovak Medical University37, Utrecht University38, Pompeu Fabra University39
TL;DR: In this meta-analysis of pooled individual participant data from 25 cohort studies, the risk for adverse maternal and infant outcomes varied by gestational weight gain and across the range of prepregnancy weights, however, the optimal gestations weight gain ranges had limited predictive value for the outcomes assessed.
Abstract: Importance Both low and high gestational weight gain have been associated with adverse maternal and infant outcomes, but optimal gestational weight gain remains uncertain and not well defined for all prepregnancy weight ranges. Objectives To examine the association of ranges of gestational weight gain with risk of adverse maternal and infant outcomes and estimate optimal gestational weight gain ranges across prepregnancy body mass index categories. Design, Setting, and Participants Individual participant-level meta-analysis using data from 196 670 participants within 25 cohort studies from Europe and North America (main study sample). Optimal gestational weight gain ranges were estimated for each prepregnancy body mass index (BMI) category by selecting the range of gestational weight gain that was associated with lower risk for any adverse outcome. Individual participant-level data from 3505 participants within 4 separate hospital-based cohorts were used as a validation sample. Data were collected between 1989 and 2015. The final date of follow-up was December 2015. Exposures Gestational weight gain. Main Outcomes and Measures The main outcome termedany adverse outcomewas defined as the presence of 1 or more of the following outcomes: preeclampsia, gestational hypertension, gestational diabetes, cesarean delivery, preterm birth, and small or large size for gestational age at birth. Results Of the 196 670 women (median age, 30.0 years [quartile 1 and 3, 27.0 and 33.0 years] and 40 937 were white) included in the main sample, 7809 (4.0%) were categorized at baseline as underweight (BMI Conclusions and Relevance In this meta-analysis of pooled individual participant data from 25 cohort studies, the risk for adverse maternal and infant outcomes varied by gestational weight gain and across the range of prepregnancy weights. The estimates of optimal gestational weight gain may inform prenatal counseling; however, the optimal gestational weight gain ranges had limited predictive value for the outcomes assessed.
TL;DR: It is demonstrated that using direct RNA sequencing, N 6-methyladenosine (m6A) RNA modifications can be detected with high accuracy, in the form of systematic errors and decreased base-calling qualities, and open avenues to investigate the biological roles of RNA modifications in their native RNA context.
Abstract: The epitranscriptomics field has undergone an enormous expansion in the last few years; however, a major limitation is the lack of generic methods to map RNA modifications transcriptome-wide. Here, we show that using direct RNA sequencing, N6-methyladenosine (m6A) RNA modifications can be detected with high accuracy, in the form of systematic errors and decreased base-calling qualities. Specifically, we find that our algorithm, trained with m6A-modified and unmodified synthetic sequences, can predict m6A RNA modifications with ~90% accuracy. We then extend our findings to yeast data sets, finding that our method can identify m6A RNA modifications in vivo with an accuracy of 87%. Moreover, we further validate our method by showing that these 'errors' are typically not observed in yeast ime4-knockout strains, which lack m6A modifications. Our results open avenues to investigate the biological roles of RNA modifications in their native RNA context.
TL;DR: Evidence of an inverse association between surrounding greenness and all-cause mortality is found, and interventions to increase and manage green spaces should therefore be considered as a strategic public health intervention.
Erasmus University Medical Center1, University of Porto2, University of Western Australia3, Stockholm County Council4, Paris Descartes University5, Maastricht University6, French Institute of Health and Medical Research7, National and Kapodistrian University of Athens8, University Medical Center Groningen9, University of Valencia10, University of Southampton11, Liverpool School of Tropical Medicine12, Université de Sherbrooke13, Norwegian Institute of Public Health14, University of Bologna15, University of Crete16, University Hospital Southampton NHS Foundation Trust17, Ludwig Maximilian University of Munich18, Nofer Institute of Occupational Medicine19, University of California20, Harvard University21, University of Illinois at Chicago22, National Institutes of Health23, Wageningen University and Research Centre24, University of Turku25, Helmholtz Centre for Environmental Research - UFZ26, Jagiellonian University Medical College27, Åbo Akademi University28, Harokopio University29, University College Dublin30, University of Calgary31, Boston Children's Hospital32, University of Copenhagen33, University College Cork34, VU University Medical Center35, University of Helsinki36, University of Turin37, Radboud University Nijmegen38, University of Trieste39, University of Bergen40, Slovak Medical University41, Utrecht University42, Pompeu Fabra University43, Bradford Royal Infirmary44, University of Bristol45
TL;DR: In this paper, the separate and combined associations of maternal pre-pregnancy body mass index (BMI) and gestational weight gain with the risks of pregnancy complications and their population impact were assessed.
Erasmus University Medical Center1, Medical University of Warsaw2, University of Valencia3, University of Porto4, Stockholm County Council5, Sorbonne6, Paris Descartes University7, University of Crete8, Maastricht University9, University of Southern California10, French Institute of Health and Medical Research11, National and Kapodistrian University of Athens12, University Medical Center Groningen13, University of Southampton14, Liverpool School of Tropical Medicine15, Norwegian Institute of Public Health16, Karolinska Institutet17, University of Bologna18, University Hospital Southampton NHS Foundation Trust19, Ludwig Maximilian University of Munich20, Nofer Institute of Occupational Medicine21, University of California, Davis22, University of Illinois at Chicago23, University of Western Australia24, National Institutes of Health25, University College Cork26, University of Bristol27, University of Turku28, Helmholtz Centre for Environmental Research - UFZ29, Jagiellonian University Medical College30, Åbo Akademi University31, Harokopio University32, University College Dublin33, University of Calgary34, Public Health Research Institute35, University of Copenhagen36, University of Southern Denmark37, La Trobe University38, Harvard University39, University of Helsinki40, University of Turin41, University of Trieste42, University of Bergen43, Slovak Medical University44, Boston Children's Hospital45, Utrecht University46, Pompeu Fabra University47, Bradford Royal Infirmary48
TL;DR: In this article, the authors conducted an individual participant data meta-analysis of data from 162,129 mothers and children from 37 pregnancy and birth cohort studies from Europe, North-America and Australia, using multilevel binary logistic regression models with a random intercept at cohort level adjusted for maternal socio-demographic and life style related characteristics.
Abstract: Background:
Maternal obesity and excessive gestational weight gain may have persistent effects on offspring fat development. However, it remains unclear whether these risks differ by severity of obesity, and whether these effects are restricted to the extremes of maternal body mass index (BMI) and gestational weight gain. We aimed to assess the separate and combined associations of maternal BMI and gestational weight gain with the risk of overweight/obesity throughout childhood, and their population impact.
Methods and Findings:
We conducted an individual participant data meta-analysis of data from 162,129 mothers and children from 37 pregnancy and birth cohort studies from Europe, North-America and Australia. We assessed the individual and combined associations of maternal pre-pregnancy BMI and gestational weight gain, both in clinical categories and across their full ranges with the risks of overweight/obesity in early- (2.0-5.0 years), mid- (5.0-10.0 years) and late childhood (10.0-18.0 years), using multilevel binary logistic regression models with a random intercept at cohort level adjusted for maternal socio-demographic and life style related characteristics. We observed that a higher maternal pre-pregnancy BMI and gestational weight gain both in clinical categories and across their full ranges were associated with higher risks of childhood overweight/obesity, with the strongest effects in late childhood (Odds Ratios (OR) for overweight/obesity in early-, mid- and late childhood, respectively: 1.66 (95% Confidence Interval (CI): 1.56, 1.78), OR 1.91 (95% CI: 1.85, 1.98), and OR 2.28 (95% CI: 2.08, 2.50) for maternal overweight, OR 2.43 (95% CI: 2.24, 2.64), OR 3.12 (95% CI: 2.98, 3.27), and OR 4.47 (95% CI: 3.99, 5.23) for maternal obesity, and OR 1.39 (95% CI: 1.30, 1.49), OR 1.55 (95% CI: 1.49, 1.60), and 1.72 (95% CI: 1.56, 1.91) for excessive gestational weight gain. The proportions of childhood overweight/obesity prevalence attributable to maternal overweight, maternal obesity and excessive gestational weight gain ranged from 10.2 to 21.6%. Relative to the effect of maternal BMI, excessive gestational weight gain only slightly increased the risk of childhood overweight/obesity within each clinical BMI category (P-values for interactions of maternal BMI with gestational weight gain: p=0.038, p<0.001 and p=0.637, in early-, mid- and late childhood, respectively). Limitations of this study include the self-report of maternal BMI and gestational weight gain for some of the cohorts, and the potential of residual confounding. Also, as this study only included participants from Europe, North-America and Australia, results need to be interpreted with caution with respect to other populations.
Conclusions:
In this study, higher maternal pre-pregnancy BMI and gestational weight gain were associated with an increased risk of childhood overweight/obesity, with the strongest effects at later ages. The additional effect of gestational weight gain in women who are overweight or obese before pregnancy is small. Given the large population impact, future intervention trials aiming to reduce the prevalence of childhood overweight and obesity should focus on maternal weight status before pregnancy, in addition to weight gain during pregnancy.
Centro Nacional de Investigaciones Cardiovasculares1, Complutense University of Madrid2, Icahn School of Medicine at Mount Sinai3, Spanish National Research Council4, Pompeu Fabra University5, Ludwig Maximilian University of Munich6, University of Münster7, Agency for Science, Technology and Research8, University of Paris-Sud9, Autonomous University of Madrid10, Maastricht University11
TL;DR: The molecular regulators of neutrophil aging are identified and it is shown that genetic disruption of this process has major consequences in immune cell trafficking, anti‐microbial defense, and vascular health.
Radboud University Nijmegen1, Erasmus University Medical Center2, University of Southern California3, National Institutes of Health4, Oregon Health & Science University5, Autonomous University of Barcelona6, Polytechnic University of Valencia7, Hartford Hospital8, University of Groningen9, VU University Amsterdam10, University of São Paulo11, University of Melbourne12, RWTH Aachen University13, Harvard University14, VA Boston Healthcare System15, University of California, San Diego16, University of California, Irvine17, University of Cincinnati18, University of Würzburg19, University of Amsterdam20, Haukeland University Hospital21, University of Bergen22, New York University23, Trinity College, Dublin24, Norwegian University of Science and Technology25, University of Zurich26, University of Barcelona27, University of London28, University of Reading29, University of Brighton30, Heidelberg University31, Federal University of Rio de Janeiro32, University of Tübingen33, Erasmus University Rotterdam34, Russian National Research Medical University35, University Hospital of Lausanne36, Brighton and Sussex University Hospitals NHS Trust37, University of Sussex38, Monash University39, Deakin University40, ETH Zurich41, German Center for Neurodegenerative Diseases42, University of Regensburg43, Nathan Kline Institute for Psychiatric Research44, Goethe University Frankfurt45, VU University Medical Center46, Yale University47, Pompeu Fabra University48, State University of New York System49
TL;DR: Subtle differences in cortical surface area are widespread in children but not adolescents and adults with ADHD, confirming involvement of the frontal cortex and highlighting regions deserving further attention.
Abstract: OBJECTIVE: Neuroimaging studies show structural alterations of various brain regions in children and adults with attention deficit hyperactivity disorder (ADHD), although nonreplications are frequent. The authors sought to identify cortical characteristics related to ADHD using large-scale studies. METHODS: Cortical thickness and surface area (based on the Desikan-Killiany atlas) were compared between case subjects with ADHD (N=2,246) and control subjects (N=1,934) for children, adolescents, and adults separately in ENIGMA-ADHD, a consortium of 36 centers. To assess familial effects on cortical measures, case subjects, unaffected siblings, and control subjects in the NeuroIMAGE study (N=506) were compared. Associations of the attention scale from the Child Behavior Checklist with cortical measures were determined in a pediatric population sample (Generation-R, N=2,707). RESULTS: In the ENIGMA-ADHD sample, lower surface area values were found in children with ADHD, mainly in frontal, cingulate, and temporal regions; the largest significant effect was for total surface area (Cohen's d=-0.21). Fusiform gyrus and temporal pole cortical thickness was also lower in children with ADHD. Neither surface area nor thickness differences were found in the adolescent or adult groups. Familial effects were seen for surface area in several regions. In an overlapping set of regions, surface area, but not thickness, was associated with attention problems in the Generation-R sample. CONCLUSIONS: Subtle differences in cortical surface area are widespread in children but not adolescents and adults with ADHD, confirming involvement of the frontal cortex and highlighting regions deserving further attention. Notably, the alterations behave like endophenotypes in families and are linked to ADHD symptoms in the population, extending evidence that ADHD behaves as a continuous trait in the population. Future longitudinal studies should clarify individual lifespan trajectories that lead to nonsignificant findings in adolescent and adult groups despite the presence of an ADHD diagnosis.
Book•
31 Jan 2019TL;DR: Understand the fundamentals of wireless and MIMO communication with this accessible and comprehensive text, which provides a sound treatment of the key concepts underpinning contemporary wireless communication and M IMO, all the way to massive MIMo.
Abstract: Understand the fundamentals of wireless and MIMO communication with this accessible and comprehensive text. Viewing the subject through an information theory lens, but also drawing on other perspectives, it provides a sound treatment of the key concepts underpinning contemporary wireless communication and MIMO, all the way to massive MIMO. Authoritative and insightful, it includes over 330 worked examples and 450 homework problems, with solutions and MATLAB code and data available online. Altogether, this is an excellent resource for instructors and graduate students, as well as an outstanding reference for researchers and practicing engineers.
TL;DR: An open access resource created over 14 years by IMEx database curators, featuring 28,000 annotations describing the effect of small sequence changes on physical protein interactions, is presented.
Abstract: The current wealth of genomic variation data identified at nucleotide level presents the challenge of understanding by which mechanisms amino acid variation affects cellular processes. These effects may manifest as distinct phenotypic differences between individuals or result in the development of disease. Physical interactions between molecules are the linking steps underlying most, if not all, cellular processes. Understanding the effects that sequence variation has on a molecule's interactions is a key step towards connecting mechanistic characterization of nonsynonymous variation to phenotype. We present an open access resource created over 14 years by IMEx database curators, featuring 28,000 annotations describing the effect of small sequence changes on physical protein interactions. We describe how this resource was built, the formats in which the data is provided and offer a descriptive analysis of the data set. The data set is publicly available through the IntAct website and is enhanced with every monthly release.
TL;DR: Analysis of whole-genome sequences from more than 3,500 metastatic tumors identifies mutational signatures associated with different chemotherapies and provides estimates of the relative contribution of different treatments to tumor mutational burden.
Abstract: Some cancer therapies damage DNA and cause mutations in both cancerous and healthy cells. Therapy-induced mutations may underlie some of the long-term and late side effects of treatments, such as mental disabilities, organ toxicity and secondary neoplasms. Nevertheless, the burden of mutation contributed by different chemotherapies has not been explored. Here we identify the mutational signatures or footprints of six widely used anticancer therapies across more than 3,500 metastatic tumors originating from different organs. These include previously known and new mutational signatures generated by platinum-based drugs as well as a previously unknown signature of nucleoside metabolic inhibitors. Exploiting these mutational footprints, we estimate the contribution of different treatments to the mutation burden of tumors and their risk of contributing coding and potential driver mutations in the genome. The mutational footprints identified here allow for precise assessment of the mutational risk of different cancer therapies to understand their long-term side effects.
TL;DR: This study provides microscale insights into a macroscale cortical hierarchy in the dynamic resting brain using a large-scale dynamical circuit model of human cerebral cortex with region-specific microscale properties.
Abstract: We considered a large-scale dynamical circuit model of human cerebral cortex with region-specific microscale properties. The model was inverted using a stochastic optimization approach, yielding markedly better fit to new, out-of-sample resting functional magnetic resonance imaging (fMRI) data. Without assuming the existence of a hierarchy, the estimated model parameters revealed a large-scale cortical gradient. At one end, sensorimotor regions had strong recurrent connections and excitatory subcortical inputs, consistent with localized processing of external stimuli. At the opposing end, default network regions had weak recurrent connections and excitatory subcortical inputs, consistent with their role in internal thought. Furthermore, recurrent connection strength and subcortical inputs provided complementary information for differentiating the levels of the hierarchy, with only the former showing strong associations with other macroscale and microscale proxies of cortical hierarchies (meta-analysis of cognitive functions, principal resting fMRI gradient, myelin, and laminar-specific neuronal density). Overall, this study provides microscale insights into a macroscale cortical hierarchy in the dynamic resting brain.