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arXiv 2019年

作者： Yuan, Ye VanderWerf, Kyle Shattuck, Mark D. O’Hern, Corey S. Department of Mechanics and Engineering Science College of Engineering Peking University Beijing100871 China Department of Mechanical Engineering and Materials Science Yale University New HavenCT06520 United States Department of Physics Yale University New HavenCT06520 United States Benjamin Levich Institute and Physics Department City College of New York New YorkNY10031 United States Department of Applied Physics Yale University New HavenCT06520 United States Graduate Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States

We carry out numerical studies of static packings of frictionless superellipsoidal particles in three spatial dimensions. We consider more than 200 different particle shapes by varying the three shape parameters that define superellipsoids. We characterize the structural and mechanical properties of both disordered and ordered packings using two packing-generation protocols. We perform athermal quasi-static compression simulations starting from either random, dilute configurations (Protocol 1) or thermalized, dense configurations (protocol 2), which allows us to tune the orientational order of the packings. In general, we find that the contact numbers at jamming onset for superellipsoid packings are hypostatic, with zJ f and df = 5 or 6 depending on whether the particles are axi-symmetric or not. Over the full range of orientational order, we find that the number of quartic modes of the dynamical matrix for the packings always matches the number of missing contacts relative to the isostatic value. This result suggests that there are no mechanically redundant contacts for ordered, yet hypostatic packings of superellipsoidal particles. Additionally, we find that the packing fraction at jamming onset for diordered packings of superellipsoidal particles can be collapsed using two particle shape parameters, e.g. the asphericity A and reduced aspect ratio β of the particles. Copyright © 2019, The Authors. All rights reserved.

关键词： Jamming

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Evolution of retrograde orbiters in an AGN disk

arXiv

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arXiv 2020年

作者： Secunda, Amy Hernandez, Betsy Goodman, Jeremy Leigh, Nathan W.C. McKernan, Barry Ford, K.E. Saavik Adorno, Jose I. Department of Astrophysics American Museum of Natural History Central Park West at 79th Street New YorkNY10024 United States Department of Astrophysical Sciences Princeton University Peyton Hall PrincetonNJ08544 United States Departamento de Astronomía Facultad de Ciencias Físicas y Matemáticas Universidad de Concepción Concepción Chile Department of Science Borough of Manhattan Community College City University of New York New YorkNY10007 United States Physics Program Graduate Center CUNY New YorkNY10016 United States Center for Computational Astrophysics Flatiron Institute New YorkNY10010 United States NASA Goddard Space Flight Center GreenbeltMD20771 United States Department of Physics Queens College City University of New York QueensNY11367 United States

AGN disks have been proposed as promising locations for the mergers of stellar mass black hole binaries (BBHs). Much recent work has been done on this merger channel, but the majority focuses on stellar mass black holes (BHs) orbiting in the prograde direction. Little work has been done to examine the impact of retrograde orbiters (ROs) on the formation and mergers of BBHs in AGN disks. Quantifying the retrograde contribution is important, since roughly half of all orbiters should initially be on retrograde orbits when the disk forms. We perform an analytic calculation of the evolution of ROs in an AGN disk. Because this evolution could cause the orbits of ROs to cross those of prograde BBHs, we derive the collision rate between a given RO and a given BBH orbiting in the prograde direction. In the examples given here, ROs in the inner region of the disk experience a rapid decrease in the semimajor axis of their orbits while also becoming highly eccentric in less than a million years. This rapid orbital evolution could lead to extreme mass ratio inspirals detectable by the Laser Interferometer Space Antenna. The collision rates of our example ROs with prograde BBHs in the migration trap depend strongly on the volume of the inner radiation-pressure-dominated region which depends on the mass of the supermassive black hole (SMBH). Rates are lowest for larger mass SMBHs, which dominate the AGN merger channel, suggesting that merger rates for this channel may not be significantly altered by ROs. Copyright © 2020, The Authors. All rights reserved.

关键词： Black holes

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Erratum for Wang et al., "Clinically Applicable System for Rapidly Predicting Enterococcus faecium Susceptibility to Vancomycin"

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Microbiology spectrum 2022年第1期10卷 e0261021页

作者： Hsin-Yao Wang Chia-Ru Chung Chao-Jung Chen Ko-Pei Lu Yi-Ju Tseng Tzu-Hao Chang Min-Hsien Wu Wan-Ting Huang Ting-Wei Lin Tsui-Ping Liu Tzong-Yi Lee Jorng-Tzong Horng Jang-Jih Lu Department of Laboratory Medicine Chang Gung Memorial Hospitalgrid.413801.f at Linkou Taoyuan City Taiwan. Ph.D. Program in Biomedical Engineering Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Department of Computer Science and Information Engineering National Central Universitygrid.37589.30 Taoyuan City Taiwan. Graduate Institute of Integrated Medicine China Medical Universitygrid.254145.3 Taichung Taiwan. Proteomics Core Laboratory China Medical Universitygrid.254145.3 Hospital Taichung Taiwan. Graduate Program in Biomedical Information Yuan-Ze University Taoyuan City Taiwan. Department of Information Management Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Graduate Institute of Biomedical Informatics Taipei Medical University Taipei City Taiwan. Clinical Big Data Research Center Taipei Medical University Hospital Taipei City Taiwan. Graduate Institute of Biomedical Engineering Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Division of Haematology/Oncology Department of Internal Medicine Chang Gung Memorial Hospitalgrid.413801.f at Linkou Taoyuan City Taiwan. Biosensor Group Biomedical Engineering Research Center Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Department of Pathology Kaohsiung Chang Gung Memorial Hospitalgrid.413801.f and Chang Gung University College of Medicine Kaohsiung Taiwan. School of Life and Health Sciences The Chinese University of Hong Kong Shenzhen China. Warshel Institute for Computational Biology The Chinese University of Hong Kong Shenzhen China. Department of Bioinformatics and Medical Engineering Asia University Taichung City Taiwan. School of Medicine Chang Gung Universitygrid.145695.a Taoyuan City Taiwan. Department of Medical Biotechnology and Laboratory Science Chang Gung Universitygrid.145695.a Taoyuan City Taiwan.

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A Neuro-Inspired Approach to Solve a Simultaneous Location and Mapping Task Using Shared Information in Multiple Robots Systems

A Neuro-Inspired Approach to Solve a Simultaneous Location a...

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International Conference on Control, Automation, Robotics and Vision

作者： Matheus Chaves Menezes Edison Pignaton de Freitas Sen Cheng Alexandre Cesar Muniz de Oliveira Paulo Rogerio de Almeida Ribeiro Graduate Program on Computer Science Federal University of Maranhão São Luís Brazil Graduate Program on Computer Science Federal University of Rio Grande do Sul Porto Alegre Brazil Computational Neuroscience Ruhr University Bochum Bochum Germany Department of Informatics Federal University of Maranhão São Luís Maranhão Department of Computer Engineering Federal University of Maranhão São Luís Maranhão

This paper presents a neuro-inspired mapping approach that uses partial information shared by multiple robots to reduce the time to create a map of an entire environment. Robots using a neurobiologically inspired algorithm, namely RatSLAM, map an environment sharing video information among themselves. RatSLAM, which is based on the navigation system present in the hippocampus of rodents' brain, has been widely used on simultaneous localization and mapping (SLAM) problem. This proposal has been able to generate suitable maps mainly when there is redundant information, e.g. a scene is seen more than once, since this fact activates local view cells that inject activity inside the pose cells via an excitatory link. The work here reported extends this approach by merging partial information acquired by multiple robots. The results from the performed experiments show that the final map built by two robots with shared information is similar to one built by two robots performing the same mapping task individually, i.e. without sharing information. However, the time spent to generate the whole map with the proposed shared approach was smaller than the one without the shared information. Thus, the current approach allows creating a complete map of an environment within a reduced time using multiple robots.

关键词： Navigation Simultaneous localization and mapping Feature extraction Robot vision systems Task analysis Hippocampus

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Data-augmented modeling of intracranial pressure

arXiv

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arXiv 2018年

作者： Wang, Jian-Xun Hu, Xiao Shadden, Shawn C. Mechanical Engineering University of California BerkeleyCA United States Aerospace and Mechanical Engineering Center of Informatics and Computational Science University of Notre Dame Notre DameIN United States Department of Physiological Nursing Department of Neurological surgery Institute of Computational Health Sciences UCSF Joint Bio-Engineering Graduate Program University of California San FranciscoCA United States

Precise management of patients with cerebral diseases often requires intracranial pressure (ICP) monitoring, which is highly invasive and requires a specialized ICU setting. The ability to noninvasively estimate ICP is highly compelling as an alternative to, or screening for, invasive ICP measurement. Most existing approaches for noninvasive ICP estimation aim to build a regression function that maps noninvasive measurements to an ICP estimate using statistical learning techniques. These data-based approaches have met limited success, likely because the amount of training data needed is onerous for this complex applications. In this work, we discuss an alternative strategy that aims to better utilize noninvasive measurement data by leveraging mechanistic understanding of physiology. Specifically, we developed a Bayesian framework that combines a multiscale model of intracranial physiology with noninvasive measurements of cerebral blood flow using transcranial Doppler. Virtual experiments with synthetic data are conducted to verify and analyze the proposed framework. A preliminary clinical application study on two patients is also performed in which we demonstrate the ability of this method to improve ICP prediction. Copyright © 2018, The Authors. All rights reserved.

关键词： Diagnosis

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Obesity alters pathology and treatment response in inflammatory disease

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四川生理科学杂志 2022年第3期44卷 446-446页

作者： Sagar P Bapat NOMIS Center for Immunobiology and Microbial Pathogenesis The Salk Institute for Biological Studies La Jolla CA USA Gene Expression Laboratory The Salk Institute for Biological Studies La Jolla CA USA Medical Scientist Training Program University of California San Diego La Jolla CA USA Department of Laboratory Medicine University of California San Francisco San Francisco CA USA Department of Microbiology and Immunology University of California San Francisco San Francisco CA USA Diabetes Center University of California San Francisco San Francisco CA USA Medical Scientist Training Program University of California San Francisco CA USA Division of Pulmonary Critical Care Allergy and Sleep Department of Medicine University of California San Francisco San Francisco CA USA School of Pharmaceutical Sciences Xiamen University Xiamen China Department of Dermatology University of California San Diego La Jolla CA USA Department of Surgery University of California San Francisco San Francisco CA USA Department of Medicine University of California San Francisco San Francisco CA USA Sandler Asthma Basic Research Center University of California San Francisco San Francisco CA USA School of Medicine Wake Forest University Winston–Salem NC USA Department of Dermatology Icahn School of Medicine at Mount Sinai New York NY USA Lung Biology Center Department of Medicine University of California San Francisco San Francisco CA USA Department of Biomedical Science Graduate School Kyungpook National University Kyungpook National University Hospital Daegu South Korea Department of Dermatology University of California San Francisco San Francisco CA USA Department of Pathology University of California San Francisco San Francisco CA USA Department of Internal Medicine Division of Pulmonary Critical Care and Sleep Medicine University of Kentucky Lexington KY USA Pulmonary Critical Care Section Department of Medicine Veterans Affairs San Diego Hea

Decades of work have elucidated cytokine signalling and transcriptional pathways that control T cell differentiation and have led the way to targeted biologic therapies that are effective in a range of autoimmune,allergic and inflammatory *** evidence indicates that obesity and metabolic disease can also influence the immune system1-7,although the mechanisms and effects on immunotherapy outcomes remain largely ***,using two models of atopic dermatitis,we show that lean and obese mice mount markedly different immune *** converted the classical type 2 T helper(TH2)-predominant disease associated with atopic dermatitis to a more severe disease with prominent TH17 *** also observed divergent responses to biologic therapies targeting TH2 cytokines,which robustly protected lean mice but exacerbated disease in obese ***-cell RNA sequencing coupled with genome-wide binding analyses revealed decreased activity of nuclear receptor peroxisome proliferator-activated receptor-γ(PPARγ)in TH2 cells from obese mice relative to lean mice.

关键词： dermatitis inflammatory allergic

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Analyses of protein cores reveal fundamental differences between solution and crystal structures

arXiv

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arXiv 2019年

作者： Mei, Zhe Treado, John D. Grigas, Alex T. Levine, Zachary A. Regan, Lynne O'Hern, Corey S. Integrated Graduate Program in Physical & Engineering Biology Yale University New HavenCT06520 United States Department of Chemistry Yale University New HavenCT06520 United States Department of Mechanical Engineering & Materials Science Yale University New HavenCT06520 United States Graduate Program in Computational Biology & Bioinformatics Yale University New HavenCT06520 United States Department of Pathology Yale University New HavenCT06520 United States Department of Molecular Biophysics and Biochemistry Yale University New HavenCT06520 United States Institute of Quantitative Biology Biochemistry and Biotechnology Center for Synthetic and Systems Biology School of Biological Sciences University of Edinburgh Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States

There have been several studies suggesting that protein structures solved by NMR spectroscopy and x-ray crystallography show significant differences. To understand the origin of these differences, we assembled a database of high-quality protein structures solved by both methods. We also find significant differences between NMR and crystal structures|in the root-mean-square deviations of the Cα atomic positions, identities of core amino acids, backbone and sidechain dihedral angles, and packing fraction of core residues. In contrast to prior studies, we identify the physical basis for these differences by modelling protein cores as jammed packings of amino-acid-shaped particles. We find that we can tune the jammed packing fraction by varying the degree of thermalization used to generate the packings. For an athermal protocol, we find that the average jammed packing fraction is identical to that observed in the cores of protein structures solved by x-ray crystallography. In contrast, highly thermalized packing-generation protocols yield jammed packing fractions that are even higher than those observed in NMR structures. These results indicate that thermalized systems can pack more densely than athermal systems, which suggests a physical basis for the structural differences between protein structures solved by NMR and x-ray crystallography. Copyright © 2019, The Authors. All rights reserved.

关键词： X ray crystallography

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Dynamical charge structure factor of a one-dimensional ionic Hubbard model in the low-energy region

arXiv

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arXiv 2018年

作者： Komaki, Yuhei Iwase, Yuma Yanagimatsu, Shogo Muta, Yoshiyuki Maeshima, Nobuya Hino, Ken-ichi Doctoral Program in Materials Science Graduate School of Pure and Applied Sciences University of Tsukuba Tsukuba Ibaraki305-8573 Japan College of Engineering Sciences University of Tsukuba Tsukuba305-8573 Japan Center for Computational Sciences University of Tsukuba Tsukuba305-8577 Japan Division of Materials Science University of Tsukuba Tsukuba305-8573 Japan

We present a numerical study of the charge dynamical structure factor N(k, ω) of a one-dimensional (1D) ionic Hubbard model in the Mott insulator (MI) phase. We show that the low-energy spectrum of N(k, ω) is expressed in terms of the spin operators for the spin degrees of freedom. Numerical results for the spin degrees of freedom, obtained by the Lanczos diagonalization method, well reproduce the low-energy spectrum of N(k, ω) of the 1D ionic Hubbard model. In addition, we show that these spectral peaks probe the dispersion of the spin-singlet excitations of the system and are observed in the wide parameter region of the MI phase. Copyright © 2018, The Authors. All rights reserved.

关键词： Numerical methods

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Correction to: Authors’ Reply to Letter to the Editor: Continued improvement to genetic diversity indicator for CBD

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Conservation Genetics 2021年第4期22卷 537-539页

作者： Laikre, Linda Hohenlohe, Paul A. Allendorf, Fred W. Bertola, Laura D. Breed, Martin F. Bruford, Michael W. Funk, W. Chris Gajardo, Gonzalo González-Rodríguez, Antonio Grueber, Catherine E. Hedrick, Philip W. Heuertz, Myriam Hunter, Margaret E. Johannesson, Kerstin Liggins, Libby MacDonald, Anna J. Mergeay, Joachim Moharrek, Farideh O’Brien, David Ogden, Rob Orozco-terWengel, Pablo Palma-Silva, Clarisse Pierson, Jennifer Paz-Vinas, Ivan Russo, Isa-Rita M. Ryman, Nils Segelbacher, Gernot Sjögren-Gulve, Per Waits, Lisette P. Vernesi, Cristiano Hoban, Sean Division of Population Genetics Department of Zoology Stockholm University Stockholm Sweden Institute for Bioinformatics and Evolutionary Studies Department of Biological Sciences University of Idaho Moscow USA Division of Biological Sciences University of Montana Missoula USA City College of New York New York USA College of Science and Engineering Flinders University Bedford Park Australia School of Biosciences Cardiff University Cardiff Wales UK Graduate Degree Program in Ecology Department of Biology Colorado State University Fort Collins USA Universidad de Los Lagos Lab Genetics Aquaculture & Biodiversity Osorno Chile Instituto de Investigaciones en Ecosistemas y Sustentabilidad Universidad Nacional Autónoma de México Morelia Mexico School of Life and Environmental Sciences Faculty of Science The University of Sydney Sydney Australia School of Life Sciences Arizona State University Tempe USA INRAE Univ. Bordeaux Biogeco Cestas France U.S. Geological Survey Wetland and Aquatic Research Center Gainesville USA Department of Marine Sciences University of Gothenburg Tjärnö Strömstad Sweden School of Natural and Computational Sciences Massey University Auckland New Zealand The John Curtin School of Medical Research/Research School of Biology The Australian National University Acton Australia Research Institute for Nature and Forest Geraardsbergen Belgium Aquatic Ecology Evolution and Conservation KULeuven Leuven Belgium Novo Nordisk Foundation Center for Basic Metabolic Research Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark Faculty of Biological Sciences Tarbiat Modares University Tehran Iran Scottish Natural Heritage Inverness UK Royal (Dick) School of Veterinary Studies and the Roslin Institute University of Edinburgh Midlothian UK Department of Plant Science Institute of Biology University of Campinas Campinas Brazil Australian Wildlife Conservancy Subiaco East Australia Laboratoire Evolution & Div

A correction to this paper has been published: https://***/10.1007/s10592-021-01376-9

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Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

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Nature 2024年第8003期627卷 347-357页

作者： Ken Suzuki Konstantinos Hatzikotoulas Lorraine Southam Henry J Taylor Xianyong Yin Kim M Lorenz Ravi Mandla Alicia Huerta-Chagoya Giorgio E M Melloni Stavroula Kanoni Nigel W Rayner Ozvan Bocher Ana Luiza Arruda Kyuto Sonehara Shinichi Namba Simon S K Lee Michael H Preuss Lauren E Petty Philip Schroeder Brett Vanderwerff Mart Kals Fiona Bragg Kuang Lin Xiuqing Guo Weihua Zhang Jie Yao Young Jin Kim Mariaelisa Graff Fumihiko Takeuchi Jana Nano Amel Lamri Masahiro Nakatochi Sanghoon Moon Robert A Scott James P Cook Jung-Jin Lee Ian Pan Daniel Taliun Esteban J Parra Jin-Fang Chai Lawrence F Bielak Yasuharu Tabara Yang Hai Gudmar Thorleifsson Niels Grarup Tamar Sofer Matthias Wuttke Chloé Sarnowski Christian Gieger Darryl Nousome Stella Trompet Soo-Heon Kwak Jirong Long Meng Sun Lin Tong Wei-Min Chen Suraj S Nongmaithem Raymond Noordam Victor J Y Lim Claudia H T Tam Yoonjung Yoonie Joo Chien-Hsiun Chen Laura M Raffield Bram Peter Prins Aude Nicolas Lisa R Yanek Guanjie Chen Jennifer A Brody Edmond Kabagambe Ping An Anny H Xiang Hyeok Sun Choi Brian E Cade Jingyi Tan K Alaine Broadaway Alice Williamson Zoha Kamali Jinrui Cui Manonanthini Thangam Linda S Adair Adebowale Adeyemo Carlos A Aguilar-Salinas Tarunveer S Ahluwalia Sonia S Anand Alain Bertoni Jette Bork-Jensen Ivan Brandslund Thomas A Buchanan Charles F Burant Adam S Butterworth Mickaël Canouil Juliana C N Chan Li-Ching Chang Miao-Li Chee Ji Chen Shyh-Huei Chen Yuan-Tsong Chen Zhengming Chen Lee-Ming Chuang Mary Cushman John Danesh Swapan K Das H Janaka de Silva George Dedoussis Latchezar Dimitrov Ayo P Doumatey Shufa Du Qing Duan Kai-Uwe Eckardt Leslie S Emery Daniel S Evans Michele K Evans Krista Fischer James S Floyd Ian Ford Oscar H Franco Timothy M Frayling Barry I Freedman Pauline Genter Hertzel C Gerstein Vilmantas Giedraitis Clicerio González-Villalpando Maria Elena González-Villalpando Penny Gordon-Larsen Myron Gross Lindsay A Guare Sophie Hackinger Liisa Hakaste Sohee Han Andrew T Hattersley Christian Herder Momoko Horikoshi Annie-Green Howard Willa Centre for Genetics and Genomics Versus Arthritis Centre for Musculoskeletal Research Division of Musculoskeletal and Dermatological Sciences University of Manchester Manchester UK. Department of Diabetes and Metabolic Diseases Graduate School of Medicine University of Tokyo Tokyo Japan. Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. konstantinos.hatzikotoulas@helmholtz-munich.de. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. Center for Precision Health Research National Human Genome Research Institute National Institutes of Health Bethesda MD USA. British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary Care University of Cambridge Cambridge UK. Heart and Lung Research Institute University of Cambridge Cambridge UK. Department of Epidemiology School of Public Health Nanjing Medical University Nanjing China. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor MI USA. Corporal Michael J. Crescenz VA Medical Center Philadelphia PA USA. Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Department of Genetics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Programs in Metabolism and Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA. Diabetes Unit and Center for Genomic Medicine Massachusetts General Hospital Boston MA USA. TIMI Study Group Division of Cardiovascular Medicine Brigham and Women's Hospital Harvard Medical School Boston MA USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London L

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

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