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Genome-wide association study of long COVID

Nature Genetics 2025年 1-16页

作者： Vilma Lammi Tomoko Nakanishi Samuel E. Jones Juha Karjalainen Martin Broberg Hele H. Haapaniemi Matti Pirinen Mari E. K. Niemi Mattia Cordioli Mark J. Daly Andrea Ganna Hanna M. Ollila J. Brent Richards Yukinori Okada Shea J. Andrews Beatriz Cortés Rafael de Cid Susana Iraola-Guzmán Natalia Blay Xavier Farré Heath E. O’Brien Thompson Hannah Patrick J. Short Ana Ochoa-Guzman Michelle Duran-Gomez Brian E. Fulton-Howard Masahiro Kanai Axel Schmidt Daniella Balla Julia Heggemann Sonja Schultz Pari Behzad Markus M. Nöthen Abigail Miller Kerstin U. Ludwig Ruth E. Mitchell George Davey Smith Nicholas J. Timpson Abdou Mousas Evangelos Evangelou Evangelia Ntzani Konstantinos K. Tsilidis Massimo Mangino Alicia Huerta-Chagoya Nasa Sinnott-Armstrong Elizabeth T. Cirulli Francisco Tanudjaja Efren Sandoval Nicole L. Washington Simon White Alexandre Bolze Kelly M. Schiabor Barrett Marc Vaudel Alex S. F. Kwong Amit K. Maiti Minttu M. Marttila Daniel C. Posner Alexis A. Rodriguez Chiara Batini Beatriz Guillen-Guio Olivia C. Leavy Anna L. Guyatt Catherine John Louise V. Wain Francesca Minnai Anna R. Dearman Benedict Hignell Meena Kumari C. A. Robert Warmerdam Lude H. Franke Celia B. Sequeros Søren Brunak David Westergaard Karina Banasik Thomas W. Winkler Iris M. Heid Daniel M. Jordan Ryan C. Thompson Alexander W. Charney Laura G. Sloofman Nicole W. Simons Noam D. Beckmann Raimonds Rešcenko Vita Rovite Peculis Raitis Monta Briviba Janis Klovinš Laura Ansone Lorenzo Miano Flora Peyvandi Francesco Malvestiti Nicola Montano Alessandra Bandera Francesco Bruno Arturo Blasi Jacqueline M. Lane Jakob M. Cherry Ryan K. Chung Laura Carvajal-Silva Kevin Aguilar-Valdés Leslie C. Cerpa Tamara V. Arévalo Eduardo Lamoza Alicia Colombo Ricardo A. Verdugo Erika Frangione Xu Xinyi Jennifer Taher Jordan Lerner-Ellis Lindsay Guare Shefali S. Verma Ekaterina Vergasova Michil Trofimov Layal Shaheen Nikolay Plotnikov Anna Kim Dmitrii Kharitonov Alexei Kamelin Alexander Rakitko Eirini Marouli Pasquale Striano Ummu Afeera Zainulabid Ashutosh Kumar Hajar Fa Institute for Molecular Medicine Finland (FIMM) Helsinki Institute of Life Science (HiLIFE) University of Helsinki Helsinki Finland Department of Human Genetics McGill University Montreal Quebec Canada Centre for Clinical Epidemiology Department of Medicine Lady Davis Institute Jewish General Hospital McGill University Montreal Quebec Canada Kyoto-McGill International Collaborative Program in Genomic Medicine Graduate School of Medicine Kyoto University Kyoto Japan Department of Genome Informatics Graduate School of Medicine the University of Tokyo Tokyo Japan Research Fellow Japan Society for the Promotion of Science Tokyo Japan Program in Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA Stanley Center for Psychiatric Research Broad Institute of Harvard and MIT Cambridge MA USA Analytic and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Department of Mathematics and Statistics University of Helsinki Helsinki Finland Department of Public Health University of Helsinki Helsinki Finland Broad Institute Cambridge MA USA Analytical and Translational Genetics Unit Massachusetts General Hospital Harvard Medical School Boston MA USA Center for Genomic Medicine Massachusetts General Hospital Boston MA USA Anesthesia Critical Care and Pain Medicine Massachusetts General Hospital and Harvard Medical School Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Twin Research King’s College London London UK 5 Prime Sciences Inc Montreal Quebec Canada Department of Epidemiology Biostatistics and Occupational Health McGill University Montreal Quebec Canada Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan Laboratory for Systems Genetics RIKEN Center for Integrative Medical Sciences Yokohama Japan Laboratory of Statistical Immunology Immunology Frontier Research Center (WPI-IFReC) Osaka University Suita Japan Departmen

Infections can lead to persistent symptoms and diseases such as shingles after varicella zoster or rheumatic fever after streptococcal infections. Similarly, severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) infection can result in long coronavirus disease (COVID), typically manifesting as fatigue, pulmonary symptoms and cognitive dysfunction. The biological mechanisms behind long COVID remain unclear. We performed a genome-wide association study for long COVID including up to 6,450 long COVID cases and 1,093,995 population controls from 24 studies across 16 countries. We discovered an association ofFOXP4with long COVID, independent of its previously identified association with severe COVID-19. The signal was replicated in 9,500 long COVID cases and 798,835 population controls. Given the transcription factor FOXP4’s role in lung physiology and pathology, our findings highlight the importance of lung function in the pathophysiology of long COVID.

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OTHR-04. DEVELOPMENT OF A FUNCTIONAL PLATFORM FOR REAL-TIME PERSONALIZED DRUG SENSITIVITY PROFILING OF PATIENT-DERIVED 3D FRESH TUMOR TISSUE CULTURES IN THE PEDIATRIC PRECISION ONCOLOGY PROGRAM INFORM

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Neuro-Oncology 2023年第SUPPLEMENT_1期25卷 i74–i75页

作者： Heike Peterziel Nora Jamaladdin Dina ElHarouni Xenia F Gerloff Sonja Herter Petra Fiesel Yannick Berker Mirjam Blattner-Johnson Kathrin Schramm Barbara C Jones David Reuss Laura Turunen Aileen Friedenauer Tim Holland-Letz Martin Sill Lena Weiser Christopher Previti Gnanaprakash Balasubramanian Nicolas U Gerber Johannes Gojo Caroline Hutter Ingrid Øra Olli Lohi Antonis Kattamis Bram de Wilde Frank Westermann Stephan Tippelt Norbert Graf Michaela Nathrath Monika Sparber-Sauer Astrid Sehested Christof M Kramm Uta Dirksen Olli Kallioniemi Stefan M Pfister Cornelis M van Tilburg David T W Jones Jani Saarela Vilja Pietiäinen Natalie Jäger Matthias Schlesner Annette Kopp-Schneider Sina Oppermann Till Milde Olaf Witt Ina Oehme Hopp Children’s Cancer Center Heidelberg (KiTZ) Heidelberg Germany Clinical Cooperation Unit Pediatric Oncology German Cancer Research Center (DKFZ) National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Consortium (DKTK) Heidelberg Germany Bioinformatics and Omics Data Analytics German Cancer Research Center (DKFZ) Division of Pediatric Neurooncology German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK) Heidelberg Germany Clinical Cooperation Unit Neuropathology German Cancer Research Center (DKFZ) Heidelberg Germany Division of Pediatric Glioma Research German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK) Heidelberg Germany Division of Pediatric Glioma Research German Cancer Research Center (DKFZ) Department of Pediatric Oncology Hematology Immunology and Pulmonology Heidelberg University Hospital and German Cancer Consortium (DKTK) Heidelberg Germany Department Neuropathology at Institute of Pathology Heidelberg University Hospital Heidelberg Germany Institute for Molecular Medicine Finland (FIMM) Helsinki Institute of Life Science (HiLIFE) University of Helsinki Helsinki Finland Division of Biostatistics German Cancer Research Center (DKFZ) Heidelberg Heidelberg Germany Division of Pediatric Neurooncology German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK) Heidelberg Germany Core Facility Omics IT and Data Management (ODCF) German Cancer Research Center (DKFZ) Heidelberg Germany Department of Oncology University Children’s Hospital Zürich Zürich Switzerland Department of Pediatrics and Adolescent Medicine Comprehensive Cancer Center and Comprehensive Center for Pediatrics Medical University of Vienna Vienna Austria St. Anna Children’s Hospital Department of Pediatrics and Adolescent Medicine Medical University of Vienna and St. Anna Children’s Cancer Research Institute (CCRI) Vienna Austria Children’s Hospital Pediatric Oncology Skåne University Hospital Lund &amp Karolinska Univ

The international precision oncology program INFORM enrolls relapsed/refractory pediatric cancer patients for comprehensive molecular analysis. We report a two-year pilot study implementing ex vivo drug sensitivity profiling (DSP) using a library of 75-78 clinically relevant drugs. We included 132 viable tumor samples from 35 pediatric oncology centers in seven countries. DSP was conducted on multicellular fresh tumor tissue spheroid cultures in 384-well plates with an overall mean processing time of three weeks. In 89 cases (67%), sufficient viable tissue was received; 69 (78%) passed internal quality controls. The DSP results matched the identified molecular targets, including BRAF, ALK, MET and TP53 status. Drug vulnerabilities were identified in 80% of cases lacking actionable (very) high-evidence molecular events, adding value to the molecular data. Striking parallels between clinical courses and the DSP results were observed in selected patients. Overall, DSP in clinical real-time is feasible in international multicenter precision oncology programs.

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Author Correction: Widespread exposure to SARS-CoV-2 in wildlife communities

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Nature communications 2024年第1期15卷 6940页

作者： Amanda R Goldberg Kate E Langwig Katherine L Brown Jeffrey M Marano Pallavi Rai Kelsie M King Amanda K Sharp Alessandro Ceci Christopher D Kailing Macy J Kailing Russell Briggs Matthew G Urbano Clinton Roby Anne M Brown James Weger-Lucarelli Carla V Finkielstein Joseph R Hoyt Department of Biological Sciences Virginia Tech Blacksburg VA USA. Virginia Tech Carilion School of Medicine Virginia Tech Roanoke VA USA. Center for Emerging Zoonotic and Arthropod-borne Pathogens Virginia Tech Blacksburg VA USA. Molecular Diagnostics Laboratory Fralin Biomedical Research Institute Virginia Tech Roanoke VA USA. Department of Biomedical Sciences and Pathobiology Virginia Tech Blacksburg VA USA. Translational Biology Medicine and Health Graduate Program Virginia Tech Roanoke VA USA. Program in Genetics Bioinformatics and Computational Biology Virginia Tech Blacksburg VA USA. Department of Biochemistry Virginia Tech Blacksburg VA USA. Data Services University Libraries Virginia Tech Blacksburg VA USA. Virginia Tech Center for Drug Discovery Virginia Tech Blacksburg VA USA. Academy of Integrated Science Virginia Tech Blacksburg VA USA. Department of Biological Sciences Virginia Tech Blacksburg VA USA. finkielc@vt.edu. Virginia Tech Carilion School of Medicine Virginia Tech Roanoke VA USA. finkielc@vt.edu. Center for Emerging Zoonotic and Arthropod-borne Pathogens Virginia Tech Blacksburg VA USA. finkielc@vt.edu. Molecular Diagnostics Laboratory Fralin Biomedical Research Institute Virginia Tech Roanoke VA USA. finkielc@vt.edu. Virginia Tech Center for Drug Discovery Virginia Tech Blacksburg VA USA. finkielc@vt.edu. Academy of Integrated Science Virginia Tech Blacksburg VA USA. finkielc@vt.edu. Department of Biological Sciences Virginia Tech Blacksburg VA USA. hoytjosephr@***.

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Dynamic prediction of mortality in COVID-19 patients in the intensive care unit: A retrospective multi-center cohort study

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Intelligence-Based Medicine 2022年 6卷 100071-100071页

作者： Smit, J.M. Krijthe, J.H. Endeman, H. Tintu, A.N. de Rijke, Y.B. Gommers, D.A.M.P.J. Cremer, O.L. Bosman, R.J. Rigter, S. Wils, E.-J. Frenzel, T. Dongelmans, D.A. De Jong, R. Peters, M.A.A. Kamps, M.J.A. Ramnarain, D. Nowitzky, R. Nooteboom, F.G.C.A. De Ruijter, W. Urlings-Strop, L.C. Smit, E.G.M. Mehagnoul-Schipper, D.J. Dormans, T. De Jager, C.P.C. Hendriks, S.H.A. Achterberg, S. Oostdijk, E. Reidinga, A.C. Festen-Spanjer, B. Brunnekreef, G.B. Cornet, A.D. Van den Tempel, W. Boelens, A.D. Koetsier, P. Lens, J.A. Faber, H.J. karakus, A. Entjes, R. De Jong, P. Rettig, T.C.D. Arbous, M.S. Lalisang, R.C.A. Tonutti, M. De Bruin, D.P. Elbers, P.W.G. Van Bommel, J. Reinders, M.J.T. Intensive Care Erasmus University Medical Center Rotterdam Netherlands Pattern Recognition & Bioinformatics Group EEMCS Delft University of Technology Delft Netherlands Clinical Chemistry Erasmus University Medical Center Rotterdam Netherlands Intensive Care UMC Utrecht Utrecht Netherlands Intensive Care OLVG Amsterdam Netherlands Anesthesiology and Intensive Care St. Antonius Hospital Nieuwegein Netherlands Intensive Care Franciscus Gasthuis Vlietland Rotterdam Netherlands Intensive Care Radboud University Medical Center Nijmegen Netherlands Intensive Care Amsterdam UMC Amsterdam Netherlands Intensive Care Bovenij Ziekenhuis Amsterdam Netherlands Intensive Care Canisius Wilhelmina Ziekenhuis Nijmegen Netherlands Intensive Care Catharina Ziekenhuis Eindhoven Eindhoven Netherlands Intensive Care ETZ Tilburg Tilburg Netherlands Intensive Care HagaZiekenhuis Den Haag Netherlands Intensive Care Laurentius Ziekenhuis Roermond Netherlands Intensive Care Northwest Clinics Alkmaar Netherlands Intensive Care Reinier de Graaf Gasthuis Delft Netherlands Intensive Care Spaarne Gasthuis Haarlem en Hoofddorp Netherlands Intensive Care VieCuri Medisch Centrum Venlo Netherlands Intensive Care Zuyderland MC Heerlen Netherlands Intensive Care Jeroen Bosch Ziekenhuis 's-Hertogenbosch Netherlands Intensive Care Albert Schweitzerziekenhuis Dordrecht Netherlands Intensive Care Haaglanden Medisch Centrum Den Haag Netherlands Intensive Care Maasstad Ziekenhuis Rotterdam Rotterdam Netherlands Intensive Care SEH BWC Martiniziekenhuis Groningen Netherlands Intensive Care Ziekenhuis Gelderse Vallei Ede Netherlands Intensive Care Ziekenhuisgroep Twente Almelo Netherlands Intensive Care Medisch Spectrum Twente Enschede Netherlands Intensive Care Ikazia Ziekenhuis Rotterdam Rotterdam Netherlands Anesthesiology Antonius Ziekenhuis Sneek Sneek Netherlands Intensive Care Medisch Centrum Leeuwarden Leeuwarden Netherlands Intensive Care IJsselland Zieke

Background: The COVID-19 pandemic continues to overwhelm intensive care units (ICUs) worldwide, and improved prediction of mortality among COVID-19 patients could assist decision making in the ICU setting. In this work, we report on the development and validation of a dynamic mortality model specifically for critically ill COVID-19 patients and discuss its potential utility in the ICU. Methods: We collected electronic medical record (EMR) data from 3222 ICU admissions with a COVID-19 infection from 25 different ICUs in the Netherlands. We extracted daily observations of each patient and fitted both a linear (logistic regression) and non-linear (random forest) model to predict mortality within 24 h from the moment of prediction. Isotonic regression was used to re-calibrate the predictions of the fitted models. We evaluated the models in a leave-one-ICU-out (LOIO) cross-validation procedure. Results: The logistic regression and random forest model yielded an area under the receiver operating characteristic curve of 0.87 [0.85;0.88] and 0.86 [0.84;0.88], respectively. The recalibrated model predictions showed a calibration intercept of −0.04 [−0.12;0.04] and slope of 0.90 [0.85;0.95] for logistic regression model and a calibration intercept of −0.19 [−0.27;−0.10] and slope of 0.89 [0.84;0.94] for the random forest model. Discussion: We presented a model for dynamic mortality prediction, specifically for critically ill COVID-19 patients, which predicts near-term mortality rather than in-ICU mortality. The potential clinical utility of dynamic mortality models such as benchmarking, improving resource allocation and informing family members, as well as the development of models with more causal structure, should be topics for future research. © 2022 The Authors

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1355. Cluster of Multi-drug ResistanceNeisseria gonorrhoeaeIsolates with Reduce Ceftriaxone Susceptibility, First Report in Thailand

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Open Forum Infectious Diseases 2021年第SUPPLEMENT_1期8卷 S764–S764页

作者： Wannigama, Dhammika Leshan Kueakulpattana, Naris Luk-In, Sirirat Hongsing, Parichart Hurst, Cameron Badavath, Vishnu Nayak Jenjaroenpun, Piroon Wongsurawat, Thidathip Teeratakulpisan, Nipat Kerr, Stephen J Abe, Shuichi Pearson, Lachlan Saethang, Thammakorn Chantaravisoot, Naphat Higgins, Paul G Chatsuwan, Tanittha Antimicrobial Resistance and Stewardship Research Unit Faculty of Medicine Chulalongkorn University King Chulalongkorn Memorial Hospital Thai Red Cross Society Bangkok Thailand Bangkok Krung Thep Thailand Department of Clinical Microbiology and Applied Technology Faculty of Medical Technology Mahidol University Bangkok Thailand Pathumwan Krung Thep Thailand Mae Fah Luang University Hospital School of Integrative Medicine Mae Fah Luang University Chiang Rai Thailand Chiang Rai Chiang Rai Thailand Department of Statistic QIMR Berghofer Medical Research Institute Brisbane Queensland Australia Brisbane Queensland Australia Applied Medical Virology Research Unit Department of Microbiology Faculty of Medicine Chulalongkorn University Bangkok Thailand Pathumwan Krung Thep Thailand Division of Bioinformatics and Data Management for Research Department of Research and Development Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand Pathumwan Krung Thep Thailand HIV-NAT Thai Red Cross AIDS Research Centre Bangkok Thailand Pathumwan Krung Thep Thailand Chulalongkorn University Pathumwan Krung Thep Thailand Department of Infectious Diseases and Infection Control Yamagata Prefectural Central Hospital Yamagata Japan Yamagata Yamagata Japan Centre for Heart Research Westmead Institute for Medical Research Sydney New South Wales Australia Sydney New South Wales Australia Department of Computer Science Faculty of Science Kasetsart University Bangkok Thailand Pathumwan Krung Thep Thailand Department of Biochemistry Faculty of Medicine Chulalongkorn University Bangkok Thailand Pathumwan Krung Thep Thailand Institute for Medical Microbiology Immunology and Hygiene University of Cologne Cologne Germany Cologne Nordrhein-Westfalen Germany Faculty of Medicine Chulalongkorn University King Chulalongkorn Memorial Hospital Thai Red Cross Society Pathumwan Krung Thep Thailand

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Author Correction: Greengenes2 unifies microbial data in a single reference tree

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Nature biotechnology 2024年第5期42卷 813页

作者： Daniel McDonald Yueyu Jiang Metin Balaban Kalen Cantrell Qiyun Zhu Antonio Gonzalez James T Morton Giorgia Nicolaou Donovan H Parks Søren M Karst Mads Albertsen Philip Hugenholtz Todd DeSantis Se Jin Song Andrew Bartko Aki S Havulinna Pekka Jousilahti Susan Cheng Michael Inouye Teemu Niiranen Mohit Jain Veikko Salomaa Leo Lahti Siavash Mirarab Rob Knight Department of Pediatrics University of California San Diego School of Medicine La Jolla CA USA. Department of Electrical and Computer Engineering University of California San Diego La Jolla CA USA. Bioinformatics and Systems Biology Program University of California San Diego La Jolla CA USA. Department of Computer Science and Engineering University of California San Diego La Jolla CA USA. School of Life Sciences Arizona State University Tempe AZ USA. Biodesign Center for Fundamental and Applied Microbiomics Arizona State University Tempe AZ USA. Biostatistics & Bioinformatics Branch Eunice Kennedy Shriver National Institute of Child Health and Human Development National Institutes of Health Bethesda MD USA. Halicioglu Data Science Institute University of California San Diego La Jolla CA USA. Australian Centre for Ecogenomics School of Chemistry and Molecular Biosciences The University of Queensland St Lucia Queensland Australia. Department of Obstetrics and Gynecology Columbia University New York NY USA. Department of Chemistry and Bioscience Aalborg University Aalborg Denmark. Department of Informatics Second Genome Brisbane CA USA. Center for Microbiome Innovation Jacobs School of Engineering University of California San Diego La Jolla CA USA. Finnish Institute for Health and Welfare Helsinki Finland. Institute for Molecular Medicine Finland FIMM-HiLIFE Helsinki Finland. Division of Cardiology Brigham and Women's Hospital Boston MA USA. Cedars-Sinai Medical Center Los Angeles CA USA. Cambridge Baker Systems Genomics Initiative Baker Heart and Diabetes Institute Melbourne Victoria Australia. Cambridge Baker Systems Genomics Initiative Department of Public Health and Primary Care University of Cambridge Cambridge UK. Division of Medicine Turku University Hospital and University of Turku Turku Finland. Sapient Bioanalytics LLC San Diego CA USA. Department of Computing University of Turku Turku Finland. Department of Pediatrics Uni

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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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Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity (vol 50, pg 765, 2017)

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NATURE GENETICS 2018年第5期50卷 765-766页

作者： Turcot, Valerie Lu, Yingchang Highland, Heather M. Schurmann, Claudia Justice, Anne E. Fine, Rebecca S. Bradfield, Jonathan P. Esko, Tonu Giri, Ayush Graff, Mariaelisa Guo, Xiuqing Hendricks, Audrey E. Karaderi, Tugce Lempradl, Adelheid Locke, Adam E. Mahajan, Anubha Marouli, Eirini Sivapalaratnam, Suthesh Young, Kristin L. Alfred, Tamuno Feitosa, Mary F. Masca, Nicholas G. D. Manning, Alisa K. Medina-Gomez, Carolina Mudgal, Poorva Ng, Maggie C. Y. Reiner, Alex P. Vedantam, Sailaja Willems, Sara M. Winkler, Thomas W. Abecasis, Goncalo Aben, Katja K. Alam, Dewan S. Alharthi, Sameer E. Allison, Matthew Amouyel, Philippe Asselbergs, Folkert W. Auer, Paul L. Balkau, Beverley Bang, Lia E. Barroso, Ines Bastarache, Lisa Benn, Marianne Bergmann, Sven Bielak, Lawrence F. Bluher, Matthias Boehnke, Michael Boeing, Heiner Boerwinkle, Eric Boger, Carsten A. Bork-Jensen, Jette Bots, Michiel L. Bottinger, Erwin P. Bowden, Donald W. Brandslund, Ivan Breen, Gerome Brilliant, Murray H. Broer, Linda Brumat, Marco Burt, Amber A. Butterworth, Adam S. Campbell, Peter T. Cappellani, Stefania Carey, David J. Catamo, Eulalia Caulfield, Mark J. Chambers, John C. Chasman, Daniel I. Chen, Yii-Der I. Chowdhury, Rajiv Christensen, Cramer Chu, Audrey Y. Cocca, Massimiliano Collins, Francis S. Cook, James P. Corley, Janie Galbany, Jordi Corominas Cox, Amanda J. Crosslin, David S. Cuellar-Partida, Gabriel D'Eustacchio, Angela Danesh, John Davies, Gail Bakker, Paul I. W. Groot, Mark C. H. Mutsert, Renee Deary, Ian J. Dedoussis, George Demerath, Ellen W. Heijer, Martin Hollander, Anneke I. Ruijter, Hester M. Dennis, Joe G. Denny, Josh C. Angelantonio, Emanuele Drenos, Fotios Du, Mengmeng Dube, Marie-Pierre Dunning, Alison M. Easton, Douglas F. Edwards, Todd L. Ellinghaus, David Ellinor, Patrick T. Elliott, Paul Evangelou, Evangelos Farmaki, Aliki-Eleni Farooqi, I. Sadaf Faul, Jessica D. Fauser, Sascha Feng, Shuang Ferrannini, Ele Ferrieres, Jean Florez, Jose C. Ford, Ian Fornage, Myriam Franco, Oscar H. Franke, Andre Franks, Paul W. Friedrich, Ne Montreal Heart Institute Université de Montréal Montreal Quebec Canada Division of Epidemiology Department of Medicine Vanderbilt-Ingram Cancer Center Vanderbilt Epidemiology Center Vanderbilt University School of Medicine Nashville TN USA Charles Bronfman Institute for Personalized Medicine Icahn School of Medicine at Mount Sinai New York NY USA Genetics of Obesity and Related Metabolic Traits Program Icahn School of Medicine at Mount Sinai New York NY USA Department of Epidemiology University of North Carolina Chapel Hill NC USA Human Genetics Center University of Texas School of Public Health University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences University of Texas Health Science Center at Houston Houston TX USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Genetics Harvard Medical School Boston MA USA Division of Endocrinology and Center for Basic and Translational Obesity Research Boston Children’s Hospital Boston MA USA Center for Applied Genomics Division of Human Genetics Children’s Hospital of Philadelphia Philadelphia PA USA Quantinuum Research LLC San Diego CA USA Estonian Genome Center University of Tartu Tartu Estonia Division of Epidemiology Department of Medicine Institute for Medicine and Public Health Vanderbilt Genetics Institute Vanderbilt University Nashville TN USA Institute for Translational Genomics and Population Sciences LABioMed at Harbor-UCLA Medical Center Torrance CA USA Wellcome Trust Sanger Institute Hinxton UK Department of Mathematical and Statistical Sciences University of Colorado Denver CO USA Wellcome Trust Centre for Human Genetics University of Oxford Oxford UK Department of Biological Sciences Faculty of Arts and Sciences Eastern Mediterranean University Famagusta Cyprus Max Planck Institute of Immunobiology and Epigenetics Freiburg Germany Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (***35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.

关键词： Genome-wide association studies Obesity

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Author Correction: Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition

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Nature genetics 2023年第6期55卷 1080页

作者： Bernardo Rodriguez-Martin Eva G Alvarez Adrian Baez-Ortega Jorge Zamora Fran Supek Jonas Demeulemeester Martin Santamarina Young Seok Ju Javier Temes Daniel Garcia-Souto Harald Detering Yilong Li Jorge Rodriguez-Castro Ana Dueso-Barroso Alicia L Bruzos Stefan C Dentro Miguel G Blanco Gianmarco Contino Daniel Ardeljan Marta Tojo Nicola D Roberts Sonia Zumalave Paul A Edwards Joachim Weischenfeldt Montserrat Puiggròs Zechen Chong Ken Chen Eunjung Alice Lee Jeremiah A Wala Keiran M Raine Adam Butler Sebastian M Waszak Fabio C P Navarro Steven E Schumacher Jean Monlong Francesco Maura Niccolo Bolli Guillaume Bourque Mark Gerstein Peter J Park David C Wedge Rameen Beroukhim David Torrents Jan O Korbel Iñigo Martincorena Rebecca C Fitzgerald Peter Van Loo Haig H Kazazian Kathleen H Burns Peter J Campbell Jose M C Tubio Department of Zoology Genetics and Physical Anthropology Universidade de Santiago de Compostela Santiago de Compostela Spain. Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain. Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain. Transmissible Cancer Group Department of Veterinary Medicine University of Cambridge Cambridge UK. The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain. Wellcome Sanger Institute Wellcome Genome Campus Cambridge UK. Genome Data Science Institute for Research in Biomedicine (IRB Barcelona) The Barcelona Institute of Science and Technology (BIST) Barcelona Spain. Institucio Catalana de Recerca i Estudis Avançats (ICREA) Barcelona Spain. The Francis Crick Institute London UK. Department of Human Genetics University of Leuven Leuven Belgium. Genomes and Disease Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain. Graduate School of Medical Science and Engineering Korea Advanced Institute of Science and Technology Daejeon South Korea. Cancer Ageing and Somatic Mutation Programme Wellcome Sanger Institute Cambridge UK. Department of Biochemistry Genetics and Immunology University of Vigo Vigo Spain. Galicia Sur Health Research Institute Vigo Spain. Faculty of Science and Technology University of Vic-Central University of Catalonia (UVic-UCC) Vic Spain. Barcelona Supercomputing Center (BSC) Barcelona Spain. Experimental Cancer Genetics Wellcome Sanger Institute Cambridge UK. Oxford Big Data Institute University of Oxford Oxford UK. DNA Repair and Genome Integrity Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain. Department of Biochemistry and Molecular Biology Universidade de Santiago de Compostela Santiago de Compostela Spain. Medical R

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2MO First-line (1L) nivolumab (NIVO) + ipilimumab (IPI) in metastatic non-small cell lung cancer (mNSCLC): Clinical outcomes and biomarker analyses from CheckMate 592

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Immuno-Oncology and Technology 2022年 16卷 100107-100107页

作者： S. Gettinger M. Schenker J. De Langen J.R. Fischer D. Morgensztern T-E. Ciuleanu T. Beck J. De Castro Carpeno C. Schumann X. Yang B. Telivala K. Deschepper E. Nadal K. Schalper T. Spires D. Balli A. Nassar S. Karam A. Bhingare D.R. Spigel Thoracic Medical Oncology Yale Comprehensive Cancer Center Yale University New Haven CT USA Department of Medical Oncology Sf Nectarie Oncology Center Craiova Dolj Romania Department of Thoracic Oncology The Netherlands Cancer Institute Antoni van Leeuwenhowek Hospital Amsterdam Netherlands Department of Oncology Lugenklinik Löwenstein GmbH Löwenstein Germany Division of Oncology Washington University St. Louis MO USA Medical Oncology IOCN - The Oncology Institute Prof. Dr. Ion Chiricuta Cluj-Napoca Romania Oncology Department Highlands Oncology Springdale AR USA Department of Medicine Hospital Universitario La Paz Madrid Spain Pulmonary Medicine Klinikverbund Kempten Kempten Germany Hematology & Medical Oncology Bon Secours Saint Francis Center Greenville SC USA Hematology & Medical Oncology Cancer Specialists of North Florida Jacksonville FL USA Lung Diseases Vitaz Sint-Niklaas Belgium Thoracic Tumors Unit Catalan Institute of Oncology Barcelona Barcelona Spain Department of Pathology Yale School of Medicine Yale University New Haven CT USA Translational Medicine Bristol Myers Squibb Princeton NJ USA Translational Bioinformatics - Informatics and Predictive Sciences Bristol Myers Squibb Princeton NJ USA Oncology Clinical Development Bristol Myers Squibb Princeton NJ USA Global Oncology Drug Development Bristol Myers Squibb Princeton NJ USA Global Biometrics and Data Science Bristol Myers Squibb Princeton NJ USA Medical Oncology Tennessee Oncology Nashville TN USA

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