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arXiv 2021年

作者： Sanders, Lauren M. Yang, Jason H. Scott, Ryan T. Qutub, Amina Ann Martin, Hector Garcia Berrios, Daniel C. Hastings, Jaden J.A. Rask, Jon Mackintosh, Graham Hoarfrost, Adrienne L. Chalk, Stuart Kalantari, John Khezeli, Kia Antonsen, Erik L. Babdor, Joel Barker, Richard Baranzini, Sergio E. Beheshti, Afshin Delgado-Aparicio, Guillermo M. Glicksberg, Benjamin S. Greene, Casey S. Haendel, Melissa Hamid, Arif A. Heller, Philip Jamieson, Daniel Jarvis, Katelyn J. Komarova, Svetlana V. Komorowski, Matthieu Kothiyal, Prachi Mahabal, Ashish Manor, Uri Mason, Christopher E. Matar, Mona Mias, George I. Miller, Jack Myers, Jerry G. Nelson, Charlotte Oribello, Jonathan Park, Seung-Min Parsons-Wingerter, Patricia Prabhu, R.K. Reynolds, Robert J. Saravia-Butler, Amanda Saria, Suchi Sawyer, Aenor Singh, Nitin Kumar Soboczenski, Frank Snyder, Michael Soman, Karthik Theriot, Corey A. van Valen, David Venkateswaran, Kasthuri Warren, Liz Worthey, Liz Zitnik, Marinka Costes, Sylvain V. Blue Marble Space Institute of Science Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States Center for Emerging and Re-Emerging Pathogens Department of Microbiology Biochemistry and Molecular Genetics Rutgers New Jersey Medical School NewarkNJ07103 United States KBR Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States AI MATRIX Consortium Department of Biomedical Engineering University of Texas San Antonio and UT Health Sciences San AntonioTX78249 United States Biological Systems and Engineering Division Lawrence Berkeley National Lab. BerkeleyCA94608 United States DOE Agile BioFoundry EmeryvilleCA94608 United States Joint BioEnergy Institute EmeryvilleCA94608 United States Department of Physiology and Biophysics Weill Cornell Medicine New YorkNY10065 United States Office of the Center Director NASA Ames Research Center Moffett Field CA94035 United States Bay Area Environmental Research Institute NASA Ames Research Center Moffett Field CA94035 United States Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States Department of Chemistry University of North Florida JacksonvilleFL32224 United States Center for Individualized Medicine Department of Surgery Department of Quantitative Health Sciences Mayo Clinic RochesterMN55905 United States Department of Emergency Medicine Center for Space Medicine Baylor College of Medicine HoustonTX77030 United States Department of Microbiology and Immunology Department of Otolaryngology Head and Neck Surgery University of California San Francisco San FranciscoCA94143 United States The Gilroy AstroBiology Research Group The University of Wisconsin - Madison MadisonWI53706 United States Weill Institute for Neurosciences Department of Neurology University of California San Francisco San FranciscoCA94158 United States Data Science Analytics Georgia Institute of Technology Lima15024

Space biology research aims to understand fundamental effects of spaceflight on organisms, develop foundational knowledge to support deep space exploration, and ultimately bioengineer spacecraft and habitats to stabilize the ecosystem of plants, crops, microbes, animals, and humans for sustained multi-planetary life. To advance these aims, the field leverages experiments, platforms, data, and model organisms from both spaceborne and ground-analog studies. As research is extended beyond low Earth orbit, experiments and platforms must be maximally autonomous, light, agile, and intelligent to expedite knowledge discovery. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration on artificial intelligence, machine learning, and modeling applications which offer key solutions toward these space biology challenges. In the next decade, the synthesis of artificial intelligence into the field of space biology will deepen the biological understanding of spaceflight effects, facilitate predictive modeling and analytics, support maximally autonomous and reproducible experiments, and efficiently manage spaceborne data and metadata, all with the goal to enable life to thrive in deep space. © 2021, CC BY.

关键词： Predictive analytics

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Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health

arXiv

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arXiv 2021年

作者： Scott, Ryan T. Antonsen, Erik L. Sanders, Lauren M. Hastings, Jaden J.A. Park, Seung-Min Mackintosh, Graham Reynolds, Robert J. Hoarfrost, Adrienne L. Sawyer, Aenor Greene, Casey S. Glicksberg, Benjamin S. Theriot, Corey A. Berrios, Daniel C. Miller, Jack Babdor, Joel Barker, Richard Baranzini, Sergio E. Beheshti, Afshin Chalk, Stuart Delgado-Aparicio, Guillermo M. Haendel, Melissa Hamid, Arif A. Heller, Philip Jamieson, Daniel Jarvis, Katelyn J. Kalantari, John Khezeli, Kia Komarova, Svetlana V. Komorowski, Matthieu Kothiyal, Prachi Mahabal, Ashish Manor, Uri Martin, Hector Garcia Mason, Christopher E. Matar, Mona Mias, George I. Myers, Jerry G. Nelson, Charlotte Oribello, Jonathan Parsons-Wingerter, Patricia Prabhu, R.K. Qutub, Amina Ann Rask, Jon Saravia-Butler, Amanda Saria, Suchi Singh, Nitin Kumar Soboczenski, Frank Snyder, Michael Soman, Karthik van Valen, David Venkateswaran, Kasthuri Warren, Liz Worthey, Liz Yang, Jason H. Zitnik, Marinka Costes, Sylvain V. KBR Space Biosciences Division NASA Ames Research Center Moffett FieldCA94035 United States Department of Emergency Medicine Center for Space Medicine Baylor College of Medicine HoustonTX77030 United States Blue Marble Space Institute of Science Space Biosciences Division NASA Ames Research Center Moffett FieldCA94035 United States Department of Physiology and Biophysics Weill Cornell Medicine New YorkNY10065 United States Department of Urology Department of Radiology Stanford University School of Medicine StanfordCA94305 United States Bay Area Environmental Research Institute NASA Ames Research Center Moffett FieldCA94035 United States Mortality Research & Consulting Inc. HoustonTX77058 United States Space Biosciences Division NASA Ames Research Center Moffett FieldCA94035 United States UC Space Health Department of Orthopaedic Surgery University of California San Francisco San FranciscoCA94143 United States Center for Health AI Department of Biochemistry and Molecular Genetics University of Colorado School of Medicine Anschutz Medical Campus AuroraCO80045 United States Hasso Plattner Institute for Digital Health at Mount Sinai Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New YorkNY10065 United States Department of Preventive Medicine and Community Health UTMB GalvestonTX77551 United States Human Health and Performance Directorate NASA Johnson Space Center HoustonTX77058 United States Department of Microbiology and Immunology Department of Otolaryngology Head and Neck Surgery University of California San Francisco San FranciscoCA94143 United States The Gilroy AstroBiology Research Group The University of Wisconsin Madison MadisonWI53706 United States Weill Institute for Neurosciences Department of Neurology University of California San Francisco San FranciscoCA94158 United States Department of Chemistry University of North Florida JacksonvilleFL32224 United States Data Scienc

Human space exploration beyond low Earth orbit will involve missions of significant distance and duration. To effectively mitigate myriad space health hazards, paradigm shifts in data and space health systems are necessary to enable Earth-independence, rather than Earth-reliance. Promising developments in the fields of artificial intelligence and machine learning for biology and health can address these needs. We propose an appropriately autonomous and intelligent Precision Space Health system that will monitor, aggregate, and assess biomedical statuses;analyze and predict personalized adverse health outcomes;adapt and respond to newly accumulated data;and provide preventive, actionable, and timely insights to individual deep space crew members and iterative decision support to their crew medical officer. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration, on future applications of artificial intelligence in space biology and health. In the next decade, biomonitoring technology, biomarker science, spacecraft hardware, intelligent software, and streamlined data management must mature and be woven together into a Precision Space Health system to enable humanity to thrive in deep space. © 2021, CC BY.

关键词： Earth (planet)

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Author Correction: Multi-ancestry polygenic mechanisms of type 2 diabetes

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Nature medicine 2024年第7期30卷 2091页

作者： Kirk Smith Aaron J Deutsch Carolyn McGrail Hyunkyung Kim Sarah Hsu Alicia Huerta-Chagoya Ravi Mandla Philip H Schroeder Kenneth E Westerman Lukasz Szczerbinski Timothy D Majarian Varinderpal Kaur Alice Williamson Noah Zaitlen Melina Claussnitzer Jose C Florez Alisa K Manning Josep M Mercader Kyle J Gaulton Miriam S Udler Diabetes Unit Endocrine Division Department of Medicine Massachusetts General Hospital Boston MA USA. Center for Genomic Medicine Massachusetts General Hospital Boston MA USA. Programs in Metabolism and Medical & Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA. Department of Medicine Harvard Medical School Boston MA USA. Biomedical Sciences Graduate Program University of California San Diego La Jolla CA USA. Committee on Genetics Genomics and Systems Biology University of Chicago Chicago IL USA. Section of Genetic Medicine Department of Medicine University of Chicago Chicago IL USA. Clinical and Translational Epidemiology Unit Massachusetts General Hospital Boston MA USA. Department of Endocrinology Diabetology and Internal Medicine Medical University of Bialystok Bialystok Poland. Clinical Research Centre Medical University of Bialystok Bialystok Poland. Vertex Pharmaceuticals Boston MA USA. Precision Healthcare University Research Institute Queen Mary University of London London UK. MRC Epidemiology Unit Institute of Metabolic Science University of Cambridge Cambridge UK. Department of Neurology University of California Los Angeles Los Angeles CA USA. Department of Computational Medicine University of California Los Angeles Los Angeles CA USA. Department of Human Genetics University of California Los Angeles Los Angeles CA USA. Novo Nordisk Foundation Center for Genomic Mechanisms of Disease Broad Institute of MIT and Harvard Cambridge MA USA. Department of Pediatrics University of California San Diego San Diego CA USA. Diabetes Unit Endocrine Division Department of Medicine Massachusetts General Hospital Boston MA USA. mudler@mgh.harvard.edu. Center for Genomic Medicine Massachusetts General Hospital Boston MA USA. mudler@mgh.harvard.edu. Programs in Metabolism and Medical & Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA. mudler@mgh.harvard.edu. Department of Medicine Ha

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Author Correction: Conserved and divergent gene regulatory programs of the mammalian neocortex

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Nature 2024年第7996期625卷 E26页

作者： Nathan R Zemke Ethan J Armand Wenliang Wang Seoyeon Lee Jingtian Zhou Yang Eric Li Hanqing Liu Wei Tian Joseph R Nery Rosa G Castanon Anna Bartlett Julia K Osteen Daofeng Li Xiaoyu Zhuo Vincent Xu Lei Chang Keyi Dong Hannah S Indralingam Jonathan A Rink Yang Xie Michael Miller Fenna M Krienen Qiangge Zhang Naz Taskin Jonathan Ting Guoping Feng Steven A McCarroll Edward M Callaway Ting Wang Ed S Lein M Margarita Behrens Joseph R Ecker Bing Ren Department of Cellular and Molecular Medicine University of California San Diego School of Medicine La Jolla CA USA. Center for Epigenomics University of California San Diego School of Medicine La Jolla CA USA. Bioinformatics and Systems Biology Program University of California San Diego La Jolla CA USA. Genomic Analysis Laboratory The Salk Institute for Biological Studies La Jolla CA USA. Division of Biological Sciences University of California San Diego La Jolla CA USA. Computational Neurobiology Laboratory The Salk Institute for Biological Studies La Jolla CA USA. Department of Genetics The Edison Family Center for Genome Sciences & Systems Biology Washington University School of Medicine St Louis MO USA. Princeton Neuroscience Institute Princeton University Princeton NJ USA. Department of Genetics Harvard Medical School Boston USA. Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge MA USA. McGovern Institute for Brain Research Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Cambridge MA USA. Allen Institute for Brain Science Seattle WA USA. Systems Neurobiology Laboratories The Salk Institute for Biological Studies La Jolla CA USA. Department of Neurosciences University of California San Diego La Jolla CA USA. McDonnell Genome Institute Washington University School of Medicine St. Louis MO USA. Department of Neurological Surgery University of Washington Seattle WA USA. Genomic Analysis Laboratory The Salk Institute for Biological Studies La Jolla CA USA. ecker@salk.edu. Howard Hughes Medical Institute The Salk Institute for Biological Studies La Jolla CA USA. ecker@salk.edu. Department of Cellular and Molecular Medicine University of California San Diego School of Medicine La Jolla CA USA. biren@ucsd.edu. Center for Epigenomics University of California San Diego School of Medicine La Jolla CA USA. biren@ucsd.edu. Institute of Genomic Medicine Moores Cancer C

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Gene expression imputation across multiple brain regions provides insights into schizophrenia risk (vol 51, pg 659, 2019)

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NATURE GENETICS 2019年第6期51卷 1068-1068页

作者： Huckins, Laura M. Dobbyn, Amanda Ruderfer, Douglas M. Hoffman, Gabriel Wang, Weiqing Pardinas, Antonio F. Rajagopal, Veera M. Als, Thomas D. Nguyen, Hoang T. Girdhar, Kiran Boocock, James Roussos, Panos Fromer, Menachem Kramer, Robin Domenici, Enrico Gamazon, Eric R. Purcell, Shaun Demontis, Ditte Borglum, Anders D. Walters, James T. R. O'Donovan, Michael C. Sullivan, Patrick Owen, Michael J. Devlin, Bernie Sieberts, Solveig K. Cox, Nancy J. Im, Hae Kyung Sklar, Pamela Stahl, Eli A. Pamela Sklar Division of Psychiatric Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Genetics and Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Psychiatry Icahn School of Medicine at Mount Sinai New York NY USA Icahn Institute for Genomics and Multiscale Biology Icahn School of Medicine at Mount Sinai New York NY USA Vanderbilt University Medical Center Nashville TN USA MRC Centre for Neuropsychiatric Genetics and Genomics Cardiff University Cardiff UK Department of Biomedicine Aarhus University Aarhus Denmark The Lundbeck Foundation Initiative for Integrative Psychiatric Research iPSYCH Denmark Center for Integrative Sequencing Aarhus University Aarhus Denmark Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA Human Brain Collection Core National Institute of Mental Health Bethesda MD USA Laboratory of Neurogenomic Biomarkers Centre for Integrative Biology (CIBIO) University of Trento Trento Italy Clare Hall University of Cambridge Cambridge UK University of North Carolina at Chapel Hill Chapel Hill NC USA Karolinska Institutet Stockholm Sweden Department of Psychiatry University of Pittsburgh Pittsburgh PA USA Systems Biology Sage Bionetworks Seattle WA USA Section of Genetic Medicine Department of Medicine University of Chicago Chicago IL USA Integrated Technology Research Laboratories Pharmaceutical Research Division Takeda Pharmaceutical Company Limited Fujisawa Japan Neuropsychiatry Section Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Neuropsychiatric Signaling Program Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Psychiatry JJ Peters Virginia Medical Center Bronx NY USA Department of Neuroscience Icahn School of Medicine at Mount Sinai New York New York NY USA Friedman Brain Institute

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

关键词： Gene expression Genome-wide association studies Schizophrenia Transcriptomics

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Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure Information (vol 91, pg 626, 2022)

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BIOLOGICAL PSYCHIATRY 2022年第7期91卷 690-690页

作者： Maihofer, Adam X. Vinkers, Christiaan H. Department of Psychiatry University of California San Diego La Jolla California Department of Family Medicine and Public Health University of California San Diego La Jolla California Center of Excellence for Stress and Mental Health Veterans Affairs Healthcare System San Diego California. Electronic address: amaihofer@health.ucsd.edu. Department of Epidemiology Harvard T.H. Chan School of Public Health Boston Massachusetts Department of Psychiatry Massachusetts General Hospital Boston Massachusetts. Social Genetic and Developmental Psychiatry Centre Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom National Institute of Health Research Maudsley Biomedical Research Centre King's College London London United Kingdom. Department of Psychiatry Harvard Medical School Boston Massachusetts Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge Massachusetts Center of Excellence in Depression and Anxiety Disorders Belmont Massachusetts. Department of Epidemiology Harvard T.H. Chan School of Public Health Boston Massachusetts Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge Massachusetts. Department of Psychiatry University of California San Diego La Jolla California Center of Excellence for Stress and Mental Health Veterans Affairs Healthcare System San Diego California Research Service Veterans Affairs Healthcare System San Diego California. Duke Molecular Physiology Institute Duke University School of Medicine Durham North Carolina. Department of Psychiatry Veterans Affairs Connecticut Healthcare System West Haven Connecticut Department of Psychiatry Yale University School of Medicine New Haven Connecticut. Department of Epidemiology Harvard T.H. Chan School of Public Health Boston Massachusetts Department of Epidemiology Columbia University Mailman School of Public Health New York. Division of Mental Health Atlanta Veterans Affairs Medical Center

BACKGROUND: Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). METHODS: A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran program GWAS of PTSD total symptoms. RESULTS: GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran program. CONCLUSIONS: Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods.

关键词： GWAS Genetics Heritability PTSD PheWAS Trauma

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Author Correction: GWAS of thyroid stimulating hormone highlights the pleiotropic effects and inverse association with thyroid cancer

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Nature communications 2021年第1期12卷 7354页

作者： Wei Zhou Ben Brumpton Omer Kabil Julius Gudmundsson Gudmar Thorleifsson Josh Weinstock Matthew Zawistowski Jonas B Nielsen Layal Chaker Marco Medici Alexander Teumer Silvia Naitza Serena Sanna Ulla T Schultheiss Anne Cappola Juha Karjalainen mitja Kurki Morgan Oneka Peter Taylor Lars G Fritsche Sarah E Graham Brooke N Wolford William Overton Humaira Rasheed Eirin B Haug Maiken E Gabrielsen Anne Heidi Skogholt Ida Surakka George Davey Smith Anita Pandit Tanmoy Roychowdhury Whitney E Hornsby Jon G Jonasson Leigha Senter Sandya Liyanarachchi Matthew D Ringel Li Xu Lambertus A Kiemeney Huiling He Romana T Netea-Maier Jose I Mayordomo Theo S Plantinga Jon Hrafnkelsson Hannes Hjartarson Erich M Sturgis Aarno Palotie Mark Daly Cintia E Citterio Peter Arvan Chad M Brummett Michael Boehnke Albert de la Chapelle Kari Stefansson Kristian Hveem Cristen J Willer Bjørn Olav Åsvold Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor Michigan USA. wzhou@***. Analytic and Translational Genetics Unit Massachusetts General Hospital Boston Massachusetts USA. wzhou@***. Program in Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge Massachusetts USA. wzhou@***. Stanley Center for Psychiatric Research Broad Institute of Harvard and MIT Cambridge Massachusetts USA. wzhou@***. K.G. Jebsen Center for Genetic Epidemiology Department of Public Health and Nursing NTNU Norwegian University of Science and Technology Trondheim Norway. Medical Research Council (MRC) Integrative Epidemiology Unit University of Bristol Bristol UK. Department of Thoracic Medicine St. Olavs Hospital Trondheim University Hospital Trondheim Norway. Department of Biological Chemistry University of Michigan Medical School Ann Arbor Michigan USA. Division of Metabolism Endocrinology and Diabetes University of Michigan Medical School Ann Arbor Michigan USA. deCODE genetics/AMGEN 101 Reykjavik Iceland. Center for Statistical Genetics and Department of Biostatistics University of Michigan School of Public Health Ann Arbor Michigan USA. Department of Internal Medicine Division of Cardiology University of Michigan Medical School Ann Arbor Michigan USA. Department of Epidemiology Research Statens Serum Institute Copenhagen Denmark. Erasmus MC Academic Center for Thyroid Diseases Rotterdam The Netherlands. Department of Epidemiology Erasmus Medical Center Rotterdam The Netherlands. Department of Internal Medicine Erasmus Medical Center Rotterdam The Netherlands. Division of Endocrinology Department of Internal Medicine Radboud University Medical Centre Radboud Institute for Molecular Life Sciences 6500HB Nijmegen The Netherlands. Institute for Community Medicine University Medicine Greifswald Greifswald Germany. DZHK (German Center for Cardiovascular Research) Partner Site Greifswald Greifswald Germany. Istit

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Proceedings of the Frontiers of Retrovirology Conference 2016

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Retrovirology 2016年第1期13卷 1-40页

作者： Irena Zurnic Sylvia Hütter Nicole Stanke Tobias Kern Fabian Lindel Gesche Gerresheim Martin Hamann Erik Müllers Dirk Lindemann Ute Lehmann Juliane Reh Paul Lesbats Peter Cherepanov Melanie Mann Erik Serrao Alan Engelman Claire Da Silva Santos Kevin Tartour Andrea Cimarelli Rya Burdick Jianbo Chen Jaya Sastri Wei-Shau Hu Vinay Pathak Oliver T. Keppler Patrícia de Sousa-Pereira Hanna-Mari Baldauf Marcel Stern Karine Pradeau Sylvia Eiler Nicolas Levy Marc Ruff Sarah Lennon Sarah Cianferani Stéphane Emiliani Vincent Parissi Sylvie Rato Miguel Munoz Angela Ciuffi Antonio Rausell Amalio Telenti Alexander Zhyvoloup Ian Anderson Chen- Hsuin Lee Ariberto Fassati Anat Melamed Delphine Planas Petronela Ancuta Yuwei Zhang Huicheng Chen Annie Bernier Annie Gosselin Janos Kriston-Vizi Robin Ketteler Andy Merritt Charles Bangham Jocelyn Turpin Anthony Rodari Benoit Van Driessche Mathilde Galais Nadége Delacourt Sylvain Fauquenoy Caroline Vanhulle Anna Kula Carine Van Lint Ernst J. Wolvetang Arsène Burny Olivier Rohr Thijs van Montfort Renee van der Sluis Ben Berkhout Dave Speijer Gang Wang Na Zhao Atze T. Das Mirte Scherpenisse Bo Meng Andrzej Rutkowski Lars Dölken Andrew Lever Neil Berry Claire Ham Neil Almond Hoi Ping Mok Nicholas Norton Axel Fun Jack Hirst Mark Wills Chris Hellmund Harriet Groom Thomas Schuster Benedikt Asbach Ralf Wagner Christine Gross Martina Kalmer Andrea K. Thoma-Kress Norbert Donhauser Sebastian Millen Sandra M. Müller-Schmucker Veit Wiesmann Thomas Wittenberg Jan Gettemans Minghua Li Shan-Lu Liu Eric O. Freed Janis Müller Jan Münch Simone Joas Clement Wesley Gnanadurai Edina Lump Christina M. Stürzel Daniel Sauter Frank Kirchhoff Katharina Mack Kathrin Starz Christina Stürzel Xaver Sewald Nasim Motamedi Pradeep Uchil Ruoxi Pi Christin Herrmann Walther Mothes Mark Ladinsky Pamela Bjorkman Jagadish Beloor Priti Kumar Thomas Murooka Thorsten Mempel Michael Brehm Dale Greiner Erica Parrish Nicholas F. Parrish Beatrice H. Hahn Frederic Bibollet-Ruche Ulrike Sauermann Katharina Töpfer Tina Schultheiss Chris Molecular Virology and Gene Therapy Molecular Medicine Leuven Belgium Molecular Virology Technical University Dresden Dresden Germany Center for Regenerative Therapies Dresden Dresden Germany Potsdam University Potsdam Germany The Francis Crick Institute London Great Britain Institute of Clinical and Molecular Virology Friedrich-Alexander-Universität Erlangen-Nuremberg Erlangen Germany Dana Farber Cancer Institute Boston MA United States CIRI Lyon France National Cancer Institute Frederick MD United States Virology Max von Pettenkofer-Institut LMU Munich Munich Germany Institute of Medical Virology University of Frankfurt Frankfurt a. M. Germany German Center for Infection Research Munich Germany Institute of Medical Virology University Hospital Frankfurt Frankfurt a. M. Germany CIBIO/InBIO University of Porto Vairão Portugal Faculty of Sciences University of Porto Porto Portugal Virology Max von Pettenkofer Institute LMU Munich Germany Institute for Medical Virology Frankfurt a. M. Germany Integrative structural Biology IGBMC Illkirch France Institut Pluridisciplinaire Hubert Curien Strasbourg France Institut Cochin Paris France CNRS UMR5234 MFP Lab Bordeaux France Associated International Laboratory (LIA) Microbiology and Immunology CNRS/Université de Bordeaux/Heinrich Pette Institute-Leibniz Institute for Experimental Virology Bordeaux/Hamburg France Institute of Microbiology University Hospital Center and University of Lausanne Lausanne Switzerland Imagine Institute Paris Descartes University Paris France J. Craig Venter Institute La Jolla CA United States Infection University College London London Great Britain Medicine Imperial College London Great Britain Microbiology & Infection University of Montreal Montreal Great Britain CRCHUM Montreal Canada University College London LMCB London Great Britain MRC Technology Centre for Therapeutic Discovery London Great Britain Section of Virology Department of Medicine Imperial Co

Oral presentationsSession 1: Entry & uncoatingO1 Host cell polo-like kinases (PLKs) promote early prototype foamy virus (PFV) replicationIrena Zurnic, Sylvia Hütter, Ute Lehmann, Nicole Stanke, Juliane Re... 详细信息

Oral presentations

Session 1: Entry & uncoating

O1 Host cell polo-like kinases (PLKs) promote early prototype foamy virus (PFV) replication

Irena Zurnic, Sylvia Hütter, Ute Lehmann, Nicole Stanke, Juliane Reh, Tobias Kern, Fabian Lindel, Gesche Gerresheim, Martin Hamann, Erik Müllers, Paul Lesbats, Peter Cherepanov, Erik Serrao, Alan Engelman, Dirk Lindemann

O2 A novel entry/uncoating assay reveals the presence of at least two species of viral capsids during synchronized HIV-1 infection

Claire Da Silva Santos, Kevin Tartour, Andrea Cimarelli

O3 Dynamics of nuclear envelope association and nuclear import of HIV-1 complexes

Rya Burdick, Jianbo Chen, Jaya Sastri, Wei-Shau Hu, Vinay Pathak

O4 Human papillomavirus protein E4 potently enhances the susceptibility to HIV infection

Oliver T. Keppler

Session 2: Reverse transcription & integration

O5 Structure and function of HIV-1 integrase post translational modifications

Karine Pradeau, Sylvia Eiler, Nicolas Levy, Sarah Lennon, Sarah Cianferani, Stéphane Emiliani, Marc Ruff

O6 Regulation of retroviral integration by RNA polymerase II associated factors and chromatin structure

Vincent Parissi

Session 3: Transcription and latency

O7 A novel single-cell analysis pipeline to identify specific biomarkers of HIV permissiveness

Sylvie Rato, Antonio Rausell, Miguel Munoz, Amalio Telenti, Angela Ciuffi

O8 A capsid-dependent integration program linking T cell activation to HIV-1 gene expression

Alexander Zhyvoloup, Anat Melamed, Ian Anderson, Delphine Planas, Janos Kriston-Vizi, Robin Ketteler, Chen-Hsuin Lee, Andy Merritt, Petronela Ancuta, Charles Bangham, Ariberto Fassati

O9 Characterisation of new RNA polymerase III and RNA polymerase II transcriptional promoters in the Bovine Leukemia Virus genome

Anthony Rodari, Benoit Van Driessche, Mathilde Galais, Nadége Delacourt, Sylv

关键词： Human Immunodeficiency Virus Infection Simian Immunodeficiency Virus Feline Immunodeficiency Virus Bovine Leukemia Virus Prototype Foamy Virus

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Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

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Scientific data 2017年第1期4卷 170179页

作者： Jason Flannick Christian Fuchsberger Anubha Mahajan Tanya M Teslovich Vineeta Agarwala Kyle J Gaulton Lizz Caulkins Ryan Koesterer Clement Ma Loukas Moutsianas Davis J McCarthy Manuel A Rivas John R B Perry Xueling Sim Thomas W Blackwell Neil R Robertson N William Rayner Pablo Cingolani Adam E Locke Juan Fernandez Tajes Heather M Highland Josee Dupuis Peter S Chines Cecilia M Lindgren Christopher Hartl Anne U Jackson Han Chen Jeroen R Huyghe Martijn van de Bunt Richard D Pearson Ashish Kumar Martina Müller-Nurasyid Niels Grarup Heather M Stringham Eric R Gamazon Jaehoon Lee Yuhui Chen Robert A Scott Jennifer E Below Peng Chen Jinyan Huang Min Jin Go Michael L Stitzel Dorota Pasko Stephen C J Parker Tibor V Varga Todd Green Nicola L Beer Aaron G Day-Williams Teresa Ferreira Tasha Fingerlin Momoko Horikoshi Cheng Hu Iksoo Huh Mohammad Kamran Ikram Bong-Jo Kim Yongkang Kim Young Jin Kim Min-Seok Kwon Juyoung Lee Selyeong Lee Keng-Han Lin Taylor J Maxwell Yoshihiko Nagai Xu Wang Ryan P Welch Joon Yoon Weihua Zhang Nir Barzilai Benjamin F Voight Bok-Ghee Han Christopher P Jenkinson Teemu Kuulasmaa Johanna Kuusisto Alisa Manning Maggie C Y Ng Nicholette D Palmer Beverley Balkau Alena Stančáková Hanna E Abboud Heiner Boeing Vilmantas Giedraitis Dorairaj Prabhakaran Omri Gottesman James Scott Jason Carey Phoenix Kwan George Grant Joshua D Smith Benjamin M Neale Shaun Purcell Adam S Butterworth Joanna M M Howson Heung Man Lee Yingchang Lu Soo-Heon Kwak Wei Zhao John Danesh Vincent K L Lam Kyong Soo Park Danish Saleheen Wing Yee So Claudia H T Tam Uzma Afzal David Aguilar Rector Arya Tin Aung Edmund Chan Carmen Navarro Ching-Yu Cheng Domenico Palli Adolfo Correa Joanne E Curran Dennis Rybin Vidya S Farook Sharon P Fowler Barry I Freedman Michael Griswold Daniel Esten Hale Pamela J Hicks Chiea-Chuen Khor Satish Kumar Benjamin Lehne Dorothée Thuillier Wei Yen Lim Jianjun Liu Marie Loh Solomon K Musani Sobha Puppala William R Scott Loïc Yengo Sian-Tsung Tan Herman A Taylor Farook Thameem Gregory Wilson Tien Yin Wong Pål Rasmu Department of Molecular Biology Massachusetts General Hospital Boston Massachusetts USA. Program in Medical and Population Genetics Broad Institute Cambridge Massachusetts USA. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor Michigan USA. Wellcome Trust Centre for Human Genetics Nuffield Department of Medicine University of Oxford Oxford UK. Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology Cambridge Massachusetts USA. Department of Statistics University of Oxford Oxford UK. Genetics of Complex Traits University of Exeter Medical School University of Exeter Exeter UK. MRC Epidemiology Unit Institute of Metabolic Science University of Cambridge Cambridge UK. Department of Twin Research and Genetic Epidemiology King's College London London UK. Oxford Centre for Diabetes Endocrinology and Metabolism Radcliffe Department of Medicine University of Oxford Oxford UK. Department of Human Genetics Wellcome Trust Sanger Institute Hinxton Cambridgeshire UK. School of Computer Science McGill University Montreal Quebec Canada. McGill University and Génome Québec Innovation Centre Montreal Quebec Canada. Human Genetics Center The University of Texas Graduate School of Biomedical Sciences at Houston The University of Texas Health Science Center at Houston Houston Texas USA. Department of Biostatistics Boston University School of Public Health Boston Massachusetts USA. National Heart Lung and Blood Institute's Framingham Heart Study Framingham Massachusetts USA. Medical Genomics and Metabolic Genetics Branch National Human Genome Research Institute National Institutes of Health Bethesda Maryland USA. Department of Biostatistics Harvard School of Public Health Boston Massachusetts USA. Chronic Disease Epidemiology Swiss Tropical and Public Health Institute University of Basel Basel Switzerland. Institute of Genetic Epidemiology Helmholtz Zentrum München German R

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

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GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture

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Nature genetics 2023年第9期55卷 1471-1482页

作者： Remi Stevelink Dorothee Kasteleijn-Nolst Trenite Bobby P. C. Koeleman Dick Lindhout Anja C. M. Sonsma Ciarán Campbell Gianpiero L. Cavalleri Norman Delanty Hany El-Naggar Austin Lacey Peter Widdess-Walsh Colin P. Doherty Siwei Chen Claire Churchhouse Mark J. Daly Yen-Chen A. Feng Daniel P. Howrigan mitja I. Kurki Benjamin M. Neale Aarno Palotie Wei Zhou Namrata Gupta Henrike O. Heyne Bassel Abou-Khalil Kevin F. Haas R. S. Taneja Oluyomi M. Adesoji Michael Nothnagel Peter Nürnberg Thomas Sander Zaid Afawi Ilan Blatt Amos D. Korczyn Elisabetta Amadori Ganna Balagura Antonella Riva Marcello Scala Paolo Scudieri Pasquale Striano Federico Zara Michele Iacomino Francesca Madia Alison Anderson Patrick Kwan Terence J. O’Brien Slavé Petrovski K. Meng Tan Marian Todaro Joseph Anderson Danielle M. Andrade Quratulain Zulfiqar Ali Grazia Annesi Pauls Auce Andreja Avbersek Simona Balestrini Vera Braatz Claudia B. Catarino Krishna Chinthapalli Jennifer Jamnadas-Khoda Dalia Kasperavičiūte Costin Leu Josemir W. Sander Sanjay M. Sisodiya Sara Zagaglia Melanie Bahlo Karen L. Oliver Mark D. Baker Beata Fonferko-Shadrach William O. Pickrell Carmen Barba Claudia Bianchini Viola Doccini Renzo Guerrini Davide Mei Martino Montomoli Elena Parrini Annalisa Vetro Karen Barboza Fabrice Bartolomei Thomas Bast Bernhard J. Steinhoff Larry Baum Stacey S. Cherny Pak Sham Tobias Baumgartner Christian E. Elger Kerstin Hallmann Wolfram S. Kunz Rainer Surges Randi von Wrede Gábor Zsurka Betül Baykan Nerses Bebek Yeşim Kesim Albert J. Becker Susanne Schoch Felicitas Becker Caitlin A. Bennett Samuel F. Berkovic Stephanie L. Leech Brigid M. Regan Ingrid E. Scheffer Bianca Berghuis Ahmad Beydoun Wassim Nasreddine Francesca Bisulli Lidia Di Vito Lorenzo Ferri Tania Giangregorio Laura Licchetta Raffaella Minardi Barbara Mostacci Carlotta Stipa Paolo Tinuper Lorenzo Muccioli Federica Pondrelli Dheeraj R. Bobbili Emadeldin Hassanin Roland Krause Zied Landoulsi Patrick May Ingo Borggraefe Christian Bosselmann Christian Hengsbach Josua Kegele Stephen Lauxmann Department of Genetics University Medical Center Utrecht Utrecht The Netherlands Stichting Epilepsie Instellingen Nederland (SEIN) Heemstede The Netherlands School of Pharmacy and Biomolecular Sciences The Royal College of Surgeons in Ireland Dublin Ireland The FutureNeuro Research Centre Dublin Ireland Department of Neurology Beaumont Hospital Dublin Ireland Department of Neurology St. James’s Hospital Dublin Ireland Analytic and Translational Genetics Unit Department of Medicine Massachusetts General Hospital and Harvard Medical School Boston MA USA Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Stanley Center for Psychiatric Research Broad Institute of Harvard and M.I.T Cambridge MA USA Institute for Molecular Medicine Finland (FIMM) University of Helsinki Helsinki Finland Psychiatric & Neurodevelopmental Genetics Unit Department of Psychiatry Massachusetts General Hospital and Harvard Medical School Boston MA USA Division of Biostatistics Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei Taiwan Hasso Plattner Institute Digital Health Center University of Potsdam Potsdam Germany Hasso Plattner Institute Mount Sinai School of Medicine New York City NY USA Department of Neurology Vanderbilt University Medical Center Nashville TN USA Cologne Center for Genomics (CCG) University of Cologne Faculty of Medicine and University Hospital Cologne Cologne Germany University Hospital Cologne Cologne Germany Department of Neurology Charité Universitaetsmedizin Berlin Campus Virchow-Clinic Berlin Germany Tel-Aviv University Sackler Faculty of Medicine Ramat Aviv Israel Department of Neurology Sheba Medical Center Ramat Gan Israel Department of Neurosciences Rehabilitation Ophthalmology Genetics Maternal and Child Health University of Genova Genova Italy IRCCS Istituto Giannina Gaslini Genova Italy Department of Medicine University of Melbour

Epilepsy is a highly heritable disorder affecting over 50 million people worldwide, of which about one-third are resistant to current treatments. Here we report a multi-ancestry genome-wide association study including 29,944 cases, stratified into three broad categories and seven subtypes of epilepsy, and 52,538 controls. We identify 26 genome-wide significant loci, 19 of which are specific to genetic generalized epilepsy (GGE). We implicate 29 likely causal genes underlying these 26 loci. SNP-based heritability analyses show that common variants explain between 39.6% and 90% of genetic risk for GGE and its subtypes. Subtype analysis revealed markedly different genetic architectures between focal and generalized epilepsies. Gene-set analyses of GGE signals implicate synaptic processes in both excitatory and inhibitory neurons in the brain. Prioritized candidate genes overlap with monogenic epilepsy genes and with targets of current antiseizure medications. Finally, we leverage our results to identify alternate drugs with predicted efficacy if repurposed for epilepsy treatment.

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