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The Association Between Levels of Plasma Biomarkers and Cognitive Performance in the Oldest Old

Alzheimer's & Dementia 2023年第S14期19卷

作者： Linda M.C. Lorenz Meng Zhang Niccoló Tesi Sven J van der Lee Marc Hulsman Mariam Gouda Sietske A.M. Sikkes Charlotte E. Teunissen Henne Holstege Genomics of Neurodegenerative Diseases and Aging Human Genetics Vrije Universiteit Amsterdam Amsterdam UMC location VUmc Amsterdam The Netherlands Amsterdam Netherlands Alzheimer Center Amsterdam Department of Neurology Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam Netherlands Amsterdam Neuroscience Neurodegeneration Amsterdam The Netherlands Amsterdam Netherlands Correspondece Delft Bioinformatics Lab Delft Technical University Delft Netherlands Delft University of Technology Delft Netherlands Genomics of Neurodegenerative Diseases and Aging Human Genetics Vrije Universiteit Amsterdam Amsterdam UMC location VUmc Amsterdam Netherlands Alzheimer Center Amsterdam Neurology Vrije Universiteit Amsterdam Amsterdam UMC location VUmc Amsterdam Netherlands Amsterdam Neuroscience Neurodegeneration Amsterdam Netherlands Genomics of Neurodegenerative Diseases and Aging Human Genetics Vrije Universiteit Amsterdam Amsterdam UMC location VUmc Amsterdam Amsterdam Netherlands Alzheimer Centre Department of Neurology Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam The Netherlands Amsterdam Netherlands 3. Delft Bioinformatics Lab Delft University of Technology Delft The Netherlands Delft Netherlands Neurochemistry Laboratory Department of Clinical Chemistry Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam Netherlands Amsterdam UMC location VUmc Amsterdam Netherlands Faculty of Behavioural and Movement Sciences Clinical Developmental Psychology & Clinical Neuropsychology Vrije Universiteit Amsterdam Amsterdam Netherlands Department of Epidemiology and Biostatistics VU University Medical Center Amsterdam Netherlands Neurochemistry Laboratory Department of Clinical Chemistry Amsterdam Neuroscience Program Neurodegeneration Amsterdam UMC Vrije Universiteit Amsterdam Amsterdam The Netherlands Amsterdam Netherlands Genomics of Neurodegenerative Diseases and Aging Human Gene

Background Lower cognitive performance in Alzheimer’s Disease (AD) patients has been correlated with changes in blood-based biomarkers Amyloid-βeta-40 (Aβ 40 ) , Amyloid-βeta-42 (Aβ 42 ), phosphorylated Tau (pTau), neurofilament light (NfL) and glial fibrillary acidic protein (GFAP). However, it is still unclear whether there is an association between cognitive performance and plasma biomarkers in the oldest old. Here we investigate I) The association of plasma biomarkers with age across a wide age-continuum until extreme age (≥100 years); II) To what extent plasma biomarkers associate with cognitive performance ≥100 years. Method The Dutch 100-plus study cohort comprises of self-reported cognitively healthy centenarians. Biomarkers were measured in 202 centenarians (137 females) on the Simoa platform. We also included centenarian siblings, offspring and their respective partners (N = 318), who were cognitively healthy. I) To investigate the relationship between age and biomarkers, we standardized all biomarkers and performed linear regression analyses. II) Cognitive performance in centenarians was determined using a comprehensive neuropsychological test battery assessing several cognitive domains. Biomarker concentrations were divided into tertiles. Cognitive performance was assessed adjusting for age, sex and education. Result I) We observed an age-related increase Aβ 40 (r s = 0.70; range 46.5-286.5 pg/mL) , Aβ 42 (r s = 0.53; range 1.4-17.7 pg/mL), pTau-181(r s = 0.68; range 0.5-12.8 pg/mL), NfL (r s = 0.81; range 4.5-378.7 pg/mL) and GFAP (r s = 0.76; range 24.4-1085.1 pg/mL), or decrease in Aβ 42/40 (r s = -0.43; range 0.01–0.10 pg/mL; P <0.001 for all biomarkers, Figure 1). II) Lower Aβ 42/40 was associated with lower cognitive performance on global cognition (based on composite z -score of all tests) β(95%CI) 0.26(0.00–0.51), P = 0.002) and domain executive functioning β(95%CI) 0.16(-0.07–0.40), P = 0.039), but not with the Mini-Mental State Examination (MMS

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Author Correction: A comprehensive update to the Mycobacterium tuberculosis H37Rv reference genome

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Nature communications 2022年第1期13卷 7538页

作者： Poonam Chitale Alexander D Lemenze Emily C Fogarty Avi Shah Courtney Grady Aubrey R Odom-Mabey W Evan Johnson Jason H Yang A Murat Eren Roland Brosch Pradeep Kumar David Alland Ray V. Lourenco Center for the Study of Emerging and Re-emerging Pathogens Rutgers University-New Jersey Medical School Newark NJ USA. Public Health Research Institute Rutgers University-New Jersey Medical School Newark NJ USA. Department of Pathology Immunology and Laboratory Medicine New Jersey Medical School Rutgers-The State University of New Jersey Newark NJ USA. Department of Medicine University of Chicago Chicago IL USA. Committee on Microbiology University of Chicago Chicago IL USA. Department of Microbiology Biochemistry and Molecular Genetics Rutgers University-New Jersey Medical School Newark NJ USA. Division of Computational Biomedicine Boston University School of Medicine and Bioinformatics Program Boston University Boston MA USA. Bioinformatics Program Boston University Boston MA USA. Center for Data Science Rutgers University-New Jersey Medical School Newark NJ USA. Helmholtz Institute for Functional Marine Biodiversity (HIFMB) Oldenburg Germany. Bay Paul Center Marine Biological Laboratory Woods Hole MA USA. Institut Pasteur Université Paris Cité Unit for Integrated Mycobacterial Pathogenomics CNRS UMR 6047 Paris France. Ray V. Lourenco Center for the Study of Emerging and Re-emerging Pathogens Rutgers University-New Jersey Medical School Newark NJ USA. allandda@njms.rutgers.edu. Public Health Research Institute Rutgers University-New Jersey Medical School Newark NJ USA. allandda@njms.rutgers.edu.

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An integrative approach to investigate the respective roles of single-nucleotide variants and copy-number variants in Attention-Deficit/Hyperactivity Disorder (vol 6, 22851, 2016)

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SCIENTIFIC REPORTS 2016年第1期6卷 22851-22851页

作者： Lima, Leandro de Araujo Feio-dos-Santos, Ana Cecilia Belangero, Sintia Iole Gadelha, Ary Bressan, Rodrigo Affonseca Salum, Giovanni Abrahao Pan, Pedro Mario Moriyama, Tais Silveira Graeff-Martins, Ana Soledade Tamanaha, Ana Carina Alvarenga, Pedro Krieger, Fernanda Valle Fleitlich-Bilyk, Bacy Jackowski, Andrea Parolin Brietzke, Elisa Sato, Joao Ricardo Polanczyk, Guilherme Vanoni Mari, Jair de Jesus Manfro, Gisele Gus do Rosario, Maria Conceiao Miguel, Euripedes Constantino Puga, Renato David Tahira, Ana Carolina Souza, Viviane Neri Chile, Thais Gouveia, Gisele Rodrigues Simoes, Sergio Nery Chang, Xiao Pellegrino, Renata Tian, Lifeng Glessner, Joseph T. Hashimoto, Ronaldo Fumio Rohde, Luis Augusto Sleiman, Patrick M. A. Hakonarson, Hakon Brentani, Helena Inter-institutional Grad Program on Bioinformatics University of São Paulo São Paulo SP Brazil Center for Applied Genomics The Children’s Hospital of Philadelphia Philadelphia PA USA Department & Institute of Psychiatry University of São Paulo Medical School São Paulo SP Brazil National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq) São Paulo SP Brazil Department of Psychiatry Federal University of São Paulo São Paulo SP Brazil National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq) São Paulo SP Brazil Department of Psychiatry Federal University of São Paulo São Paulo SP Brazil National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq) São Paulo SP Brazil Department of Psychiatry Federal University of São Paulo São Paulo SP Brazil National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq) São Paulo SP Brazil Department of Psychiatry Hospital de Clínicas de Porto Alegre Federal University of Rio Grande do Sul Porto Alegre RS Brazil National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq) São Paulo SP Brazil Department of Psychiatry Federal University of São Paulo São Paulo SP Brazil Department & Institute of Psychiatry University of São Paulo Medical School São Paulo SP Brazil National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq) São Paulo SP Brazil Department of Psychiatry Federal University of São Paulo São Paulo SP Brazil Department & Institute of Psychiatry University of São Paulo Medical School São Paulo SP Brazil National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq) São Paulo SP Brazil National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq) São Paulo SP Brazil Department of Psychiatry Federal University of São Paulo São Paulo SP Brazil Department & Institute of Psychiatry University of S

Many studies have attempted to investigate the genetic susceptibility of Attention-Deficit/Hyperactivity Disorder (ADHD), but without much success. The present study aimed to analyze both single-nucleotide and copy-number variants contributing to the genetic architecture of ADHD. We generated exome data from 30 Brazilian trios with sporadic ADHD. We also analyzed a Brazilian sample of 503 children/adolescent controls from a High Risk Cohort Study for the Development of Childhood Psychiatric Disorders, and also previously published results of five CNV studies and one GWAS meta-analysis of ADHD involving children/adolescents. The results from the Brazilian trios showed that cases with de novo SNVs tend not to have de novo CNVs and vice-versa. Although the sample size is small, we could also see that various comorbidities are more frequent in cases with only inherited variants. Moreover, using only genes expressed in brain, we constructed two “in silico” protein-protein interaction networks, one with genes from any analysis, and other with genes with hits in two analyses. Topological and functional analyses of genes in this network uncovered genes related to synapse, cell adhesion, glutamatergic and serotoninergic pathways, both confirming findings of previous studies and capturing new genes and genetic variants in these pathways.

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Creation and analysis of biochemical constraint-based models: The COBRA Toolbox v3.0

arXiv

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arXiv 2017年

作者： Heirendt, Laurent Arreckx, Sylvain Pfau, Thomas Mendoza, Sebastián N. Richelle, Anne Heinken, Almut Haraldsdóttir, Hulda S. Wachowiak, Jacek Keating, Sarah M. Vlasov, Vanja Magnusdóttir, Stefania Ng, Chiam Yu Preciat, German Žagare, Alise Chan, Siu H.J. Aurich, Maike K. Clancy, Catherine M. Modamio, Jennifer Sauls, John T. Noronha, Alberto Bordbar, Aarash Cousins, Benjamin El Assal, Diana C. Valcarcel, Luis V. Apaolaza, Iñigo Ghaderi, Susan Ahookhosh, Masoud Guebila, Marouen Ben Kostromins, Andrejs Sompairac, Nicolas Le, Hoai M. Ma, Ding Sun, Yuekai Wang, Lin Yurkovich, James T. Oliveira, Miguel A.P. Vuong, Phan T. El Assal, Lemmer P. Kuperstein, Inna Zinovyev, Andrei Scott Hinton, H. Bryant, William A. Aragón Artacho, Francisco J. Planes, Francisco J. Stalidzans, Egils Maass, Alejandro Vempala, Santosh Hucka, Michael Saunders, Michael A. Maranas, Costas D. Lewis, Nathan E. Sauter, Thomas Palsson, Bernhard Ø. Thiele, Ines Fleming, Ronan M.T. Luxembourg Centre for Systems Biomedicine University of Luxembourg 6 avenue du Swing BelvauxL-4367 Luxembourg Life Sciences Research Unit University of Luxembourg 6 avenue du Swing BelvauxL-4367 Luxembourg University of Chile Blanco Encalada 2085 Santiago Chile Department of Pediatrics University of California San Diego School of Medicine San DiegoCA92093 United States Hinxton CambridgeCB10 1SD United Kingdom Department of Chemical Engineering Pennsylvania State University University University ParkPA16802 United States Department of Physics University of California San Diego 9500 Gilman Dr. San DiegoCA92093 United States Bioinformatics and Systems Biology Program University of California San Diego San DiegoCA United States Sinopia Biosciences San DiegoCA United States School of Computer Science Algorithms and Randomness Center Georgia Institute of Technology AtlantaGA United States Biomedical Engineering and Sciences Department TECNUN University of Navarra Paseo de Manuel Lardizabal 13 San Sebastian20018 Spain Institute of Microbiology and Biotechnology University of Latvia Jelgavas iela 1 RigaLV-1004 Latvia Department of Management Science and Engineering Stanford University StanfordCA94305-4026 United States Bioengineering Department University of California San Diego San DiegoCA United States Utah State University Research Foundation 1695 North Research Park Way North LoganUT84341 United States Centre for Integrative Systems Biology and Bioinformatics Department of Life Sciences Imperial College London London United Kingdom Department of Mathematics University of Alicante Spain California Institute of Technology Computing and Mathematical Sciences MC 305-16 1200 E. California Blvd. PasadenaCA91125 United States Mathomics Center for Mathematical Modeling University of Chile Beauchef 851 Santiago Chile Novo Nordisk Foundation Center for Biosustainability University of California San Diego San DiegoCA92093 Uni

COnstraint-Based Reconstruction and Analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive software suite of interoperable COBRA methods. It has found widespread applications in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. Version 3.0 includes new methods for quality controlled reconstruction, modelling, topological analysis, strain and experimental design, network visualisation as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimisation solvers for multi-scale, multi-cellular and reaction kinetic modelling, respectively. This protocol can be adapted for the generation and analysis of a constraint-based model in a wide variety of molecular systems biology scenarios. This protocol is an update to the COBRA Toolbox 1.0 and 2.0. The COBRA Toolbox 3.0 provides an unparalleled depth of constraint-based reconstruction and analysis methods. Copyright © 2017, The Authors. All rights reserved.

关键词： Data integration

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Publisher Correction: Integrating yeast chemical genomics and mammalian cell pathway analysis

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Acta pharmacologica Sinica 2020年第5期41卷 729页

作者： Fu-Lai Zhou Sheena C Li Yue Zhu Wan-Jing Guo Li-Jun Shao Justin Nelson Scott Simpkins De-Hua Yang Qing Liu Yoko Yashiroda Jin-Biao Xu Yao-Yue Fan Jian-Min Yue Minoru Yoshida Tian Xia Chad L Myers Charles Boone Ming-Wei Wang The National Center for Drug Screening and the CAS Key Laboratory of Receptor Research Shanghai Institute of Materia Medica Chinese Academy of Sciences (CAS) Shanghai 201203 China. University of Chinese Academy of Sciences Beijing 100049 China. RIKEN Center for Sustainable Resource Science Wako Saitama 3510198 Japan. Bioinformatics and Computational Biology Program University of Minnesota-Twin Cities Minneapolis Minnesota 55455 USA. The State Key Laboratory of Drug Research Shanghai Institute of Materia Medica Chinese Academy of Sciences Shanghai 201203 China. Department of Biology The University of Tokyo Bunkyo-ku Tokyo 1138657 Japan. Collaborative Research for Innovative Microbiology The University of Tokyo Bunkyo-ku Tokyo 1138657 Japan. Department of Electronics and Information Engineering Huazhong University of Science and Technology Wuhan 430074 China. Bioinformatics and Computational Biology Program University of Minnesota-Twin Cities Minneapolis Minnesota 55455 USA. chadm@umn.edu. RIKEN Center for Sustainable Resource Science Wako Saitama 3510198 Japan. charlie.boone@utoronto.ca. Donnelly Centre and Department of Molecular Genetics University of Toronto Ontario M5S 3E1 Canada. charlie.boone@utoronto.ca. The National Center for Drug Screening and the CAS Key Laboratory of Receptor Research Shanghai Institute of Materia Medica Chinese Academy of Sciences (CAS) Shanghai 201203 China. mwwang@***. University of Chinese Academy of Sciences Beijing 100049 China. mwwang@***.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Correction: Single-cell RNA-sequencing identifies anti-cancer immune phenotypes in the early lung metastatic niche during breast cancer

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Clinical & experimental metastasis 2023年第4期40卷 373页

作者： Sophia M Orbach Michael D Brooks Yining Zhang Scott E Campit Grace G Bushnell Joseph T Decker Ryan J Rebernick Sriram Chandrasekaran Max S Wicha Jacqueline S Jeruss Lonnie D Shea Department of Biomedical Engineering University of Michigan Ann Arbor MI USA. Department of Internal Medicine University of Michigan Ann Arbor MI USA. Department of Chemical Engineering University of Michigan Ann Arbor MI USA. Program in Chemical Biology University of Michigan Ann Arbor MI USA. Medical Science Training Program University of Michigan Ann Arbor MI USA. Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA. Rogel Cancer Center University of Michigan Ann Arbor MI USA. Department of Surgery University of Michigan Ann Arbor MI USA. Department of Pathology University of Michigan Ann Arbor MI USA. Department of Biomedical Engineering University of Michigan Ann Arbor MI USA. ldshea@umich.edu. Department of Chemical Engineering University of Michigan Ann Arbor MI USA. ldshea@umich.edu. Rogel Cancer Center University of Michigan Ann Arbor MI USA. ldshea@umich.edu.

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Correction to: Genes associated with survival of female bovine blastocysts produced in vivo

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Cell and tissue research 2020年第3期382卷 679页

作者： A M Zolini J Block M B Rabaglino G Rincon M Hoelker J J Bromfield D Salilew-Wondim P J Hansen Department of Animal Sciences D.H. Barron Reproductive and Perinatal Biology Research Program and Genetics Institute University of Florida PO Box 110910 Gainesville FL 32611-0910 USA. Zoetis Inc. Kalamazoo MI 49007 USA. Instituto de Investigación en Ciencias de La Salud CONICET Córdoba Argentina. Quantitative Genetics Bioinformatics and Computational Biology Group Department of Applied Mathematics and Computer Science Technical University of Denmark Kemitorvet 2800 Kgs. Lyngby Denmark. Institute of Animal Science Animal Breeding and Husbandry University of Bonn Bonn Germany. Teaching and Research Station Frankenforst Faculty of Agriculture University of Bonn Königswinter Germany. Center of Integrated Dairy Research University of Bonn Bonn Germany. Department of Animal Sciences D.H. Barron Reproductive and Perinatal Biology Research Program and Genetics Institute University of Florida PO Box 110910 Gainesville FL 32611-0910 USA. pjhansen@ufl.edu.

The first error is on page 5. A sentence lists two genes as SCNA1A and SCNA2A but they should be SCN1A and SCN2A.

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Genome structures resolve the early diversification of teleost fishes

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Science (New York, N.Y.) 2023年第6632期379卷 572-575页

作者： Elise Parey Alexandra Louis Jerome Montfort Olivier Bouchez Céline Roques Carole Iampietro Jerome Lluch Adrien Castinel Cécile Donnadieu Thomas Desvignes Christabel Floi Bucao Elodie Jouanno Ming Wen Sahar Mejri Ron Dirks Hans Jansen Christiaan Henkel Wei-Jen Chen Margot Zahm Cédric Cabau Christophe Klopp Andrew W Thompson Marc Robinson-Rechavi Ingo Braasch Guillaume Lecointre Julien Bobe John H Postlethwait Camille Berthelot Hugues Roest Crollius Yann Guiguen Institut de Biologie de l'ENS (IBENS) Département de Biologie École Normale Supérieure CNRS INSERM Université PSL Paris France. INRAE LPGP Rennes France. GeT-PlaGe INRAE Genotoul Castanet-Tolosan France. Institute of Neuroscience University of Oregon Eugene OR USA. Department of Ecology and Evolution University of Lausanne Lausanne Switzerland. SIB Swiss Institute of Bioinformatics Lausanne Switzerland. State Key Laboratory of Developmental Biology of Freshwater Fish College of Life Science Hunan Normal University Changsha China. Florida Atlantic University Harbor Branch Oceanographic Institute Fort Pierce FL USA. Future Genomics Technologies Leiden Netherlands. Institute of Biology University of Leiden Leiden Netherlands. Faculty of Veterinary Medicine Norwegian University of Life Sciences Ås Norway. Institute of Oceanography National Taiwan University Taipei 10617 Taiwan. Sigenae GenPhySE INRAE ENVT Université de Toulouse Castanet Tolosan France. Sigenae Genotoul Bioinfo MIAT UR875 INRAE Castanet Tolosan France. Department of Integrative Biology Michigan State University East Lansing MI USA. Ecology Evolution and Behavior Program Michigan State University East Lansing MI USA. Department of Biological Sciences Western Michigan University Kalamazoo MI USA Institut Systématique Evolution Biodiversité (ISYEB) Muséum national d'Histoire naturelle CNRS SU EPHE UA Paris France. Institut Pasteur Université Paris Cité CNRS UMR 3525 INSERM UA12 Comparative Functional Genomics group F-75015 Paris France.

Accurate species phylogenies are a prerequisite for all evolutionary research. Teleosts are the largest and most diversified group of extant vertebrates, but relationships among their three oldest extant lineages remain unresolved. On the basis of seven high-quality new genome assemblies in Elopomorpha (tarpons, eels), we revisited the topology of the deepest branches of the teleost phylogeny using independent gene sequence and chromosomal rearrangement phylogenomic approaches. These analyses converged to a single scenario that unambiguously places the Elopomorpha and Osteoglossomorpha (arapaima, elephantnose fish) in a monophyletic sister group to all other teleosts, i.e., the Clupeocephala lineage (zebrafish, medaka). This finding resolves more than 50 years of controversy on the evolutionary relationships of these lineages and highlights the power of combining different levels of genome-wide information to solve complex phylogenies.

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The molecular epidemiology of multiple zoonotic origins of SARS-CoV-2

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四川生理科学杂志 2022年第7期44卷 1299-1299页

作者： Jonathan E Pekar Bioinformatics and Systems Biology Graduate Program University of California San Diego La Jolla CA 92093 USA Department of Biomedical Informatics University of California San Diego La Jolla CA 92093 USA Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles CA 90095 USA Department of Immunology and Microbiology The Scripps Research Institute La Jolla CA 92037 USA Department of Computer Science and Engineering University of California San Diego La Jolla CA 92093 USA Department of Mathematics University of California San Diego La Jolla CA 92093 USA Department of Ecology and Evolutionary Biology University of Arizona Tucson AZ 85721 USA W. Harry Feinstone Department of Molecular Microbiology and Immunology Johns Hopkins Bloomberg School of Public Health Baltimore MD 21205 USA New York City Public Health Laboratory New York City Department of Health and Mental Hygiene New York NY 11101 USA Department of Microbiology Institute for Viral Diseases Biosafety Center College of Medicine Korea University Seoul South Korea BK21 Graduate Program Department of Biomedical Sciences Korea University College of Medicine Seoul 02841 Republic of Korea National Public Health Laboratory National Centre for Infectious Diseases Singapore Malaysia Genome and Vaccine Institute Jalan Bangi 43000 Kajang Selangor Malaysia Department of Medicine University of California San Diego La Jolla CA 92093 USA Department of Microbiology and Immunology School of Medicine Tulane University New Orleans LA 70112 USA Zalgen Labs Frederick MD 21703 USA Global Virus Network (GVN) Baltimore MD 21201 USA Sydney Institute for Infectious Diseases School of Life and Environmental Sciences and School of Medical Sciences The University of Sydney Sydney NSW 2006 Australia Institute of Evolutionary Biology University of Edinburgh King’s Buildings Edinburgh EH9 3FL UK Department of Biomathematics David Geffen School of Medicine Un

Understanding the circumstances that lead to pandemics is important for their prevention. Here, we analyze the genomic diversity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) early in the coronavirus disease 2019 (COVID-19) pandemic. We show that SARS-CoV-2 genomic diversity before February 2020 likely comprised only two distinct viral lineages, denoted A and B. Phylodynamic rooting methods, coupled with epidemic simulations, reveal that these lineages were the result of at least two separate cross-species transmission events into humans. The first zoonotic transmission likely involved lineage B viruses around 18 November 2019 (23 October-8 December), while the separate introduction of lineage A likely occurred within weeks of this event.

关键词： epidemiology likely acute

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Author Correction: Pathway and network analysis of more than 2500 whole cancer genomes

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Nature communications 2022年第1期13卷 7566页

作者： Matthew A Reyna David Haan Marta Paczkowska Lieven P C Verbeke Miguel Vazquez Abdullah Kahraman Sergio Pulido-Tamayo Jonathan Barenboim Lina Wadi Priyanka Dhingra Raunak Shrestha Gad Getz Michael S Lawrence Jakob Skou Pedersen Mark A Rubin David A Wheeler Søren Brunak Jose M G Izarzugaza Ekta Khurana Kathleen Marchal Christian von Mering S Cenk Sahinalp Alfonso Valencia Jüri Reimand Joshua M Stuart Benjamin J Raphael Department of Computer Science Princeton University Princeton NJ 08540 USA. Department of Biomedical Informatics Emory University Atlanta GA 30322 USA. Department of Biomolecular Engineering and UC Santa Cruz Genomics Institute University of California Santa Cruz Santa Cruz CA 95060 USA. Computational Biology Program Ontario Institute for Cancer Research Toronto Ontario Canada. Department of Information Technology IDLab Ghent University IMEC Ghent the Netherlands. Department of Plant Biotechnology and Bioinformatics Ghent University Ghent the Netherlands. Barcelona Supercomputing Center (BSC) Barcelona 08034 Spain. Department of Clinical and Molecular Medicine Faculty of Medicine and Health Sciences Norwegian University of Science and Technology Trondheim Norway. Institute of Molecular Life Sciences and Swiss Institute of Bioinformatics University of Zurich CH-8057 Zurich Switzerland. Department of Pathology and Molecular Pathology University Hospital Zurich CH-8091 Zurich Switzerland. Department of Physiology and Biophysics Weill Cornell Medicine New York NY 10065 USA. Vancouver Prostate Centre 2660 Oak Street Vancouver BC V6H 3Z6 Canada. The Broad Institute of MIT and Harvard Cambridge MA 02124 USA. Massachusetts General Hospital Center for Cancer Research Charlestown MA 02129 USA. Harvard Medical School 250 Longwood Avenue Boston MA 02115 USA. Massachusetts General Hospital Department of Pathology Boston MA 02114 USA. Department of Molecular Medicine (MOMA) Aarhus University Hospital Aarhus Denmark. Bioinformatics Research Centre (BiRC) Aarhus University Aarhus Denmark. Human Genome Sequencing Center Baylor College of Medicine Houston TX 77030 USA. DTU Bioinformatics Department of Bio and Health Informatics Technical University of Denmark Kemitorvet 2800 Kongens Lyngby Denmark. Novo Nordisk Foundation Center for Protein Research Faculty of Health and Medical Sciences University of Copenhagen 2200 Copenhagen Denmark. De

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