检索结果-内蒙古大学图书馆

Research Square 2021年

作者： Zhang, Martin Jinye Hou, Kangcheng Pasaniuc, Bogdan Price, Alkes L. Dey, Kushal K. Jagadeesh, Karthik A. Weinand, Kathryn Sakaue, Saori Taychameekiatchai, Aris Rao, Poorvi Pisco, Angela Oliveira Zou, James Wang, Bruce Gandal, Michael Raychaudhuri, Soumya Harvard University United States Osaka University Japan Department of Epidemiology Harvard T.H. Chan School of Public Health BostonMA United States Program in Medical and Population Genetics Broad Institute of MIT and Harvard CambridgeMA United States Bioinformatics Interdepartmental Program University of California Los Angeles Los AngelesCA United States Department of Pathology and Laboratory Medicine David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Department of Computational Medicine David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Center for Data Sciences Brigham and Women’s Hospital BostonMA United States Division of Genetics Department of Medicine Brigham and Women’s Hospital Harvard Medical School BostonMA United States Division of Rheumatology Inflammation and Immunity Department of Medicine Brigham and Women’s Hospital Harvard Medical School BostonMA United States Department of Biomedical Informatics Harvard Medical School BostonMA United States Department of Medicine and Liver Center University of California San Francisco San FranciscoCA United States Developmental and Stem Cell Biology Graduate Program University of California San Francisco San FranciscoCA United States Chan Zuckerberg Biohub San FranciscoCA United States Department of Electrical Engineering Stanford University Palo AltoCA United States Department of Biomedical Data Science Stanford University Palo AltoCA United States Department of Psychiatry David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Program in Neurobehavioral Genetics Semel Institute David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Versus Arthritis Centre for Genetics and Genomic

Gene expression at the individual cell-level resolution, as quantified by single-cell RNA-sequencing (scRNA-seq), can provide unique insights into the pathology and cellular origin of diseases and complex traits. Here, we introduce single-cell Disease Relevance Score (scDRS), an approach that links scRNA-seq with polygenic risk of disease at individual cell resolution;scDRS identifies individual cells that show excess expression levels for genes in a disease-specific gene set constructed from GWAS data. We determined via simulations that scDRS is well-calibrated and powerful in identifying individual cells associated to disease. We applied scDRS to GWAS data from 74 diseases and complex traits (average N =341K) in conjunction with 16 scRNA-seq data sets spanning 1.3 million cells from 31 tissues and organs. At the cell type level, scDRS broadly recapitulated known links between classical cell types and disease, and also produced novel biologically plausible findings. At the individual cell level, scDRS identified subpopulations of disease-associated cells that are not captured by existing cell type labels, including subpopulations of CD4+ T cells associated with inflammatory bowel disease, partially characterized by their effector-like states;subpopulations of hippocampal CA1 pyramidal neurons associated with schizophrenia, partially characterized by their spatial location at the proximal part of the hippocampal CA1 region;and subpopulations of hepatocytes associated with triglyceride levels, partially characterized by their higher ploidy levels. At the gene level, we determined that genes whose expression across individual cells was correlated with the scDRS score (thus reflecting co-expression with GWAS disease genes) were strongly enriched for gold-standard drug target and Mendelian disease genes. © 2021, CC BY.

关键词： RNA

来源：评论

学校读者我要写书评

暂无评论

1507TiP Phase Ib multicenter study of trastuzumab deruxtecan (T-DXd) and immunotherapy with or without chemotherapy in first-line treatment of patients (pts) with advanced or metastatic nonsquamous non-small cell lung cancer (NSCLC) and HER2 overexpression (OE): DESTINY-Lung03

引用

Annals of Oncology 2023年 34卷 S848-S849页

作者： D. Planchard J.R. Brahmer J.C-H. Yang H.R. Kim R.K. Li J-Y. Han D.L. Cortinovis Y. Runglodvatana E. Nakajima A. Ragone M. Winter M. Gustavson Department of Medical Oncology Institut Gustave Roussy Villejuif France Thoracic Oncology Program The Johns Hopkins Kimmel Cancer Center Baltimore MD USA Medical Oncology Department National Taiwan University Hospital Taipei City Taiwan Department of Internal Medicine Division of Medical Oncology Yonsei Cancer Center Seoul Republic of Korea Medical Oncology Department St. Luke's Medical Center - Quezon City Quezon City Philippines Center for Lung Cancer National Cancer Center - Graduate School of Cancer Science and Policy Goyang Republic of Korea SC Oncologia Medica Fondazione IRCCS San Gerardo dei Tintori Monza Italy Division of Medical Oncology Vajira Hospital - Faculty of Medicine - Navamindradhiraj University Bangkok Thailand Late Development Oncology R&D AstraZeneca Gaithersburg MD USA Late Development Oncology R&D AstraZeneca Mississauga ON Canada Data Science and Quantitative Biology AstraZeneca Cambridge UK Translational Medicine Oncology R&D AstraZeneca Gaithersburg MD USA

来源：评论

学校读者我要写书评

暂无评论

Adherence to an anti-inflammatory diet is associated with lower Alzheimer’s disease mortality: A modifiable risk factor in a national cohort

引用

The Journal of Prevention of Alzheimer's Disease 2025年 100221页

作者： Ching-Chi Hsu Shiow-Ing Wang Sebastian Yu Eric S. Lin James Cheng-Chung Wei Board of Directors Wizcare Medical Corporation Aggregate Taichung 404022 Taiwan International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu 300044 Taiwan Center for Health Data Science Department of Medical Research Chung Shan Medical University Hospital Taichung 402306 Taiwan Department of Health Policy and Management College of Health Care and Management Chung Shan Medical University Taichung 402306 Taiwan Department of Dermatology College of Medicine Kaohsiung Medical University Kaohsiung 807378 Taiwan Department of Dermatology Kaohsiung Medical University Gangshan Hospital Kaohsiung 820111 Taiwan Department of Dermatology Kaohsiung Medical University Hospital Kaohsiung 807377 Taiwan Master of Public Health Program College of Public Health National Taiwan University Taipei 100025 Taiwan Neuroscience Research Center Kaohsiung Medical University Kaohsiung 807378 Taiwan Department of Economics National Tsing Hua University Hsinchu 300044 Taiwan EMBA/MBA/MFB/MPM/HBA Programs National Tsing Hua University Hsinchu 300044 Taiwan Institute of Medicine Chung Shan Medical University Taichung 402306 Taiwan Department of Allergy Immunology & Rheumatology Chung Shan Medical University Hospital Taichung 402306 Taiwan Graduate Institute of Integrated Medicine China Medical University Taichung 406040 Taiwan

Background Chronic neuroinflammation contributes to Alzheimer’s disease (AD) pathogenesis, and diet is a modifiable factor influencing inflammation. The impact of an anti-inflammatory diet on AD-specific mortality remains unclear. Objectives To examine the association between adherence to an anti-inflammatory diet (measured as the percentage of dietary energy from anti-inflammatory foods) and AD-specific mortality, as well as all-cause mortality, in a large national cohort, and to determine whether associations differ by sex or race/ethnicity. Methods We analyzed 18,795 U.S. adults (≥18 years) from the 2007–2014 National Health and Nutrition Examination Survey. Anti-inflammatory diet adherence was defined as the percentage of total energy intake from anti-inflammatory foods, categorized as 0 %, <5 %, 5–9.99 %, or ≥10 %. Outcomes were AD-specific mortality and all-cause mortality ascertained via the National Death Index. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95 % confidence intervals (CIs) for mortality across intake categories, adjusting for demographic, lifestyle, and health factors. Analyses were stratified by sex, race/ethnicity, and age (≥45 years for AD mortality). Results Participants with 0 % anti-inflammatory intake had a higher all-cause mortality risk (HR 3.82, 95 % CI 1.18–12.33) compared to those with ≥10 % intake. In the overall analysis, 0 % anti-inflammatory intake showed a trend of reduced AD-specific mortality although its did not reach statistical significance after full adjustment (HR 3.04, 95 % CI 0.74–12.46 vs. ≥10 % intake; p>0.05). Notably, the inverse association between anti-inflammatory diet and AD mortality emerged in subgroup analyses. Male participants and non-Hispanic White participants with 0 % intake had the highest AD mortality hazards (HR 12.83 and 3.77, respectively, vs. ≥10 % intake), indicating significant risk reductions with anti-inflammatory diet in these groups. In contrast, no signific

关键词： Brain-gut axis Gut dysbiosis Ketogenic diet Neurodegeneration Neuroinflammation

来源：评论

学校读者我要写书评

暂无评论

Maintaining the Quality and Aroma of Coffee with Fuzzy Logic Coffee Roasting Machine

引用

IOP Conference Series: Earth and Environmental science 2020年第1期426卷

作者： Harsawardana Bayu Samodro Bharuno Mahesworo Teddy Suparyanto Don Bosco Surya Atmaja Bens Pardamean Artificial Intelligence Research and Innovation Center for Agroindustry (AIRICA) Institut Pertanian STIPER Yogyakarta Indonesia 55281 Mechatronics and AI Research & Development Center Biotechnic Innovation Yogyakarta Indonesia 55281 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

With the increasing global demands of coffee, Indonesia need to increase their coffee beans supply and improve the quality to maintain its position in the international coffee industry. One of the most important coffeepre-processing, coffee bean roasting, is under developed in Indonesia. Indonesia coffee farmers prefer to use the traditional cauldron to roast their coffee beans. Roasting coffee beans using traditional cauldron is inefficient and resulting unequal roasted level for the coffee beans. In this study, we proposed atemperature control system based on fuzzy logic for coffee roaster machine. The system controls the temperature in accordance with the demanded roasting level. A thermal camera is attached inside the roasting chamber to monitor the heaton the roasted coffee beans. The thermal camera is integrated with a stirring mechanism to equalise the heat among the beans.

关键词：

来源：评论

学校读者我要写书评

暂无评论

The Black Hole Explorer: Motivation and Vision

arXiv

引用

arXiv 2024年

作者： Johnson, Michael D. Akiyama, Kazunori Baturin, Rebecca Bilyeu, Bryan Blackburn, Lindy Boroson, Don Cárdenas-Avendaño, Alejandro Chael, Andrew Chan, Chi-Kwan Chang, Dominic Cheimets, Peter Chou, Cathy Doeleman, Sheperd S. Farah, Joseph Galison, Peter Gamble, Ronald Gammie, Charles F. Gelles, Zachary Gómez, José L. Gralla, Samuel E. Grimes, Paul Gurvits, Leonid I. Hadar, Shahar Haworth, Kari Hada, Kazuhiro Hecht, Michael H. Honma, Mareki Houston, Janice Hudson, Ben Issaoun, Sara Jia, He Jorstad, Svetlana Kauffmann, Jens Kovalev, Yuri Y. Kurczynski, Peter Lafon, Robert Lupsasca, Alexandru Lehmensiek, Robert Ma, Chung-Pei Marrone, Daniel P. Marscher, Alan P. Melnick, Gary J. Narayan, Ramesh Niinuma, Kotaro Noble, Scott C. Palmer, Eric J. Palumbo, Daniel C.M. Paritsky, Lenny Peretz, Eliad Pesce, Dominic Plavin, Alexander Quataert, Eliot Rana, Hannah Ricarte, Angelo Roelofs, Freek Shtyrkova, Katia Sinclair, Laura C. Small, Jeffrey Kumara, Sridharan Tirupati Srinivasan, Ranjani Strominger, Andrew Tiede, Paul Tong, Edward Wang, Jade Weintroub, Jonathan Wielgus, Maciek Wong, George Zhang, Xinyue Alice Center for Astrophysics | Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States Black Hole Initiative Harvard University 20 Garden Street CambridgeMA02138 United States Haystack Observatory Massachusetts Institute of Technology WestfordMA01886 United States Mizusawa VLBI Observatory National Astronomical Observatory of Japan Iwate023-0861 Japan MIT Lincoln Laboratory LexingtonMA02421 United States Princeton Gravity Initiative Princeton University PrincetonNJ08544 United States Steward Observatory and Department of Astronomy University of Arizona 933 N. Cherry Ave. TucsonAZ85721 United States Data Science Institute University of Arizona 1230 N. Cherry Ave. TucsonAZ85721 United States Program in Applied Mathematics University of Arizona 617 N. Santa Rita TucsonAZ85721 United States Las Cumbres Observatory 6740 Cortona Drive GoletaCA93117-5575 United States Department of Physics University of California Santa BarbaraCA93106-9530 United States Department of History of Science Harvard University CambridgeMA02138 United States Department of Physics Harvard University CambridgeMA02138 United States NASA Goddard Space Flight Center GreenbeltMD20771 United States Departments of Astronomy and of Physics University of Illinois UrbanaIL61801 United States Instituto de Astrofísica de Andalucía CSIC Glorieta de la Astronomía s/n GranadaE-18008 Spain Department of Physics University of Arizona TucsonAZ85719 United States Joint Institute for VLBI ERIC Dwingeloo7991PD Netherlands Faculty of Aerospace Engineering Delft University of Technology Delft2629 HS Netherlands Department of Mathematics and Physics University of Haifa at Oranim Kiryat Tivon3600600 Israel Haifa Research Center for Theoretical Physics and Astrophysics University of Haifa Haifa3498838 Israel 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Department of Astronomy Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-

We present the Black Hole Explorer (BHEX), a mission that will produce the sharpest images in the history of astronomy by extending submillimeter Very-Long-Baseline Interferometry (VLBI) to space. BHEX will discover and measure the bright and narrow "photon ring" that is predicted to exist in images of black holes, produced from light that has orbited the black hole before escaping. This discovery will expose universal features of a black hole's spacetime that are distinct from the complex astrophysics of the emitting plasma, allowing the first direct measurements of a supermassive black hole's spin. In addition to studying the properties of the nearby supermassive black holes M87*and Sgr A*, BHEX will measure the properties of dozens of additional supermassive black holes, providing crucial insights into the processes that drive their creation and growth. BHEX will also connect these supermassive black holes to their relativistic jets, elucidating the power source for the brightest and most efficient engines in the universe. BHEX will address fundamental open questions in the physics and astrophysics of black holes that cannot be answered without submillimeter space VLBI. The mission is enabled by recent technological breakthroughs, including the development of ultra-high-speed downlink using laser communications, and it leverages billions of dollars of existing ground infrastructure. We present the motivation for BHEX, its science goals and associated requirements, and the pathway to launch within the next decade. © 2024, CC BY.

关键词： Photons

来源：评论

学校读者我要写书评

暂无评论

Democratising Knowledge Representation with BioCypher

arXiv

引用

arXiv 2022年

作者： Lobentanzer, Sebastian Aloy, Patrick Baumbach, Jan Bohar, Balazs Charoentong, Pornpimol Danhauser, Katharina Doğan, Tunca Dreo, Johann Dunham, Ian Fernandez-Torras, Adrià Gyori, Benjamin M. Hartung, Michael Hoyt, Charles Tapley Klein, Christoph Korcsmaros, Tamas Maier, Andreas Mann, Matthias Ochoa, David Pareja-Lorente, Elena Popp, Ferdinand Preusse, Martin Probul, Niklas Schwikowski, Benno Sen, Bünyamin Strauss, Maximilian T. Turei, Denes Ulusoy, Erva Heidrun Wodke, Judith Andrea Saez-Rodriguez, Julio Heidelberg University Faculty of Medicine Heidelberg University Hospital Institute for Computational Biomedicine Bioquant Heidelberg Germany The Barcelona Institute of Science and Technology Catalonia Barcelona Spain Catalonia Barcelona Spain Institute for Computational Systems Biology University of Hamburg Germany Earlham Institute Norwich United Kingdom Biological Research Centre Szeged Hungary Heidelberg University Im Neuenheimer Feld 267 Heidelberg69120 Germany Im Neuenheimer Feld 460 Heidelberg69120 Germany Department of Pediatrics Dr. von Hauner Children’s Hospital University Hospital LMU Munich Germany Biological Data Science Lab Department of Computer Engineering Hacettepe University Ankara Turkey Department of Bioinformatics Graduate School of Health Sciences Hacettepe University Ankara Turkey Computational Systems Biomedicine Lab Department of Computational Biology Institut Pasteur Université Paris Cité Paris France Bioinformatics and Biostatistics Hub Institut Pasteur Université Paris Cité Paris France Wellcome Genome Campus Cambridgeshire HinxtonCB10 1SD United Kingdom Open Targets Wellcome Genome Campus Cambridgeshire HinxtonCB10 1SD United Kingdom Laboratory of Systems Pharmacology Harvard Medical School Boston United States Imperial College London London United Kingdom Quadram Institute Bioscience Norwich United Kingdom Proteomics Program Novo Nordisk Foundation Centre for Protein Research University of Copenhagen Copenhagen Denmark Department of Proteomics and Signal Transduction Max Planck Institute of Biochemistry Martinsried Germany Im Neuenheimer Feld 460 Heidelberg69120 Germany Neuherberg Germany Medical Informatics Laboratory University Medicine Greifswald Germany

Standardising the representation of biomedical knowledge among all researchers is an insurmountable task, hindering the effectiveness of many computational methods. To facilitate harmonisation and interoperability despite this fundamental challenge, we propose to standardise the framework of knowledge graph creation instead. We implement this standardisation in BioCypher, a FAIR (findable, accessible, interoperable, reusable) framework to transparently build biomedical knowledge graphs while preserving provenances of the source data. Mapping the knowledge onto biomedical ontologies helps to balance the needs for harmonisation, human and machine readability, and ease of use and accessibility to nonspecialist researchers. We demonstrate the usefulness of this framework on a variety of use cases, from maintenance of task-specific knowledge stores, to interoperability between biomedical domains, to on-demand building of task-specific knowledge graphs for federated learning. BioCypher (https://***) frees up valuable developer time;we encourage further development and usage by the community. © 2022, CC BY-NC-ND.

关键词： Ontology

来源：评论

学校读者我要写书评

暂无评论

scTenifoldXct: A semi-supervised method for predicting cell-cell interactions and mapping cellular communication graphs

引用

Cell systems 2023年第4期14卷 302-311.e4页

作者： Yongjian Yang Guanxun Li Yan Zhong Qian Xu Yu-Te Lin Cristhian Roman-Vicharra Robert S Chapkin James J Cai Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA. Department of Statistics Texas A&M University College Station TX 77843 USA. Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE School of Statistics East China Normal University 3663 North Zhongshan Road Shanghai 200062 China. Department of Veterinary Integrative Biosciences Texas A&M University College Station TX 77843 USA. Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan. Department of Nutrition and the Program in Integrative Nutrition & Complex Diseases Texas A&M University College Station TX 77843 USA. Electronic address: r-chapkin@tamu.edu. Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA Department of Veterinary Integrative Biosciences Texas A&M University College Station TX 77843 USA Interdisciplinary Program of Genetics Texas A&M University College Station TX 77843 USA. Electronic address: jcai@tamu.edu.

We present scTenifoldXct, a semi-supervised computational tool for detecting ligand-receptor (LR)-mediated cell-cell interactions and mapping cellular communication graphs. Our method is based on manifold alignment, using LR pairs as inter-data correspondences to embed ligand and receptor genes expressed in interacting cells into a unified latent space. Neural networks are employed to minimize the distance between corresponding genes while preserving the structure of gene regression networks. We apply scTenifoldXct to real datasets for testing and demonstrate that our method detects interactions with high consistency compared with other methods. More importantly, scTenifoldXct uncovers weak but biologically relevant interactions overlooked by other methods. We also demonstrate how scTenifoldXct can be used to compare different samples, such as healthy vs. diseased and wild type vs. knockout, to identify differential interactions, thereby revealing functional implications associated with changes in cellular communication status.

关键词： cell-cell interaction cellular communication gene regression network machine learning manifold alignment neural networks scRNA-seq single-cell RNA sequencing

来源：评论

学校读者我要写书评

暂无评论

AI-Based Ripeness Grading for Oil Palm Fresh Fruit Bunch in Smart Crane Grabber

引用

IOP Conference Series: Earth and Environmental science 2020年第1期426卷

作者： Harsawardana Reza Rahutomo Bharuno Mahesworo Tjeng Wawan Cenggoro Arif Budiarto Teddy Suparyanto Don Bosco Surya Atmaja Bayu Samoedro Bens Pardamean Artificial Intelligence Research and Innovation Center for Agroindustry (AIRICA) Institut Pertanian STIPER Yogyakarta Indonesia 55281 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Mechatronics and AI Research & Development Center Biotechnic Innovation Yogyakarta Indonesia 55281 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Indonesia is one of the biggest palm oil exporters in the world. For Indonesia to stay competitive in thepalm oil industry, the harvesting and evacuating process in its oil palm plantation need to be optimized. This research introduces machinerycalled as Smart Crane Grabber. This machinery can be used for automatic harvesting and evacuation process of oil palm fresh fruit bunch. To enable automation, Smart Crane Grabber is equipped with an Artificial Intelligencesystem for automatic ripeness sorting. TheArtificial Intelligence system developed for Smart Crane Grabber achieves 71.34% accuracy by using only 400 images as preliminary training data.

关键词：

来源：评论

学校读者我要写书评

暂无评论

High-Throughput Computational Studies in Catalysis and Materials Research, and their Impact on Rational Design

arXiv

引用

arXiv 2019年

作者： Afzal, Mohammad Atif Faiz Hachmann, Johannes Schrödinger Inc. PortlandOR97204 United States Department of Chemical and Biological Engineering University at Buffalo State University of New York BuffaloNY14260 United States Computational and Data-Enabled Science and Engineering Graduate Program University at Buffalo The State University of New York BuffaloNY14260 United States New York State Center of Excellence in Materials Informatics BuffaloNY14203 United States

来源：评论

学校读者我要写书评

暂无评论

Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries (vol 55, pg 89, 2023)

引用

NATURE GENETICS 2023年第3期55卷 519-520页

作者： Fernandez-Rozadilla, Ceres Timofeeva, Maria Chen, Zhishan Law, Philip Thomas, Minta Schmit, Stephanie Diez-Obrero, Virginia Hsu, Li Fernandez-Tajes, Juan Palles, Claire Sherwood, Kitty Briggs, Sarah Svinti, Victoria Donnelly, Kevin Farrington, Susan Blackmur, James Vaughan-Shaw, Peter Shu, Xiao-ou Long, Jirong Cai, Qiuyin Guo, Xingyi Lu, Yingchang Broderick, Peter Studd, James Huyghe, Jeroen Harrison, Tabitha Conti, David Dampier, Christopher Devall, Mathew Schumacher, Fredrick Melas, Marilena Rennert, Gad Obon-Santacana, Mireia Martin-Sanchez, Vicente Moratalla-Navarro, Ferran Oh, Jae Hwan Kim, Jeongseon Jee, Sun Ha Jung, Keum Ji Kweon, Sun-Seog Shin, Min-Ho Shin, Aesun Ahn, Yoon-Ok Kim, Dong-Hyun Oze, Isao Wen, Wanqing Matsuo, Keitaro Matsuda, Koichi Tanikawa, Chizu Ren, Zefang Gao, Yu-Tang Jia, Wei-Hua Hopper, John Jenkins, Mark Win, Aung Ko Pai, Rish Figueiredo, Jane Haile, Robert Gallinger, Steven Woods, Michael Newcomb, Polly Duggan, David Cheadle, Jeremy Kaplan, Richard Maughan, Timothy Kerr, Rachel Kerr, David Kirac, Iva Bohm, Jan Mecklin, Lukka-Pekka Jousilahti, Pekka Knekt, Paul Aaltonen, Lauri Rissanen, Harri Pukkala, Eero Eriksson, Johan Cajuso, Tatiana Hanninen, Ulrika Kondelin, Johanna Palin, Kimmo Tanskanen, Tomas Renkonen-Sinisalo, Laura Zanke, Brent Mannisto, Satu Albanes, Demetrius Weinstein, Stephanie Ruiz-Narvaez, Edward Palmer, Julie Buchanan, Daniel Platz, Elizabeth Visvanathan, Kala Ulrich, Cornelia Siegel, Erin Brezina, Stefanie Gsur, Andrea Campbell, Peter Chang-Claude, Jenny Hoffmeister, Michael Brenner, Hermann Slattery, Martha Potter, John Tsilidis, Konstantinos Schulze, Matthias Gunter, Marc Murphy, Neil Castells, Antoni Castellvi-Bel, Sergi Moreira, Leticia Arndt, Volker Shcherbina, Anna Stern, Mariana Pardamean, Bens Bishop, Timothy Giles, Graham Southey, Melissa Idos, Gregory McDonnell, Kevin Abu-Ful, Zomoroda Greenson, Joel Shulman, Katerina Lejbkowicz, Flavio Offit, Kenneth Su, Yu-Ru Steinfelder, Robert Keku, Temitope van Guelpen, Bethany Hudson, Thomas Hampel, Heather Pearlman, Edinburgh Cancer Research Centre Institute of Genomics and Cancer University of Edinburgh Edinburgh UK Genomic Medicine Group Instituto de Investigacion Sanitaria de Santiago Santiago de Compostela Spain Colon Cancer Genetics Group Medical Research Council Human Genetics Unit Institute of Genetics and Cancer University of Edinburgh Edinburgh UK Danish Institute for Advanced Study Department of Public Health University of Southern Denmark Odense Denmark Division of Epidemiology Department of Medicine Vanderbilt-Ingram Cancer Center Vanderbilt Epidemiology Center Vanderbilt University Medical Center Nashville TN USA Division of Genetics and Epidemiology Institute of Cancer Research London UK Public Health Sciences Division Fred Hutchinson Cancer Research Center Seattle WA USA Genomic Medicine Institute Cleveland Clinic Cleveland OH USA Population and Cancer Prevention Program Case Comprehensive Cancer Center Cleveland OH USA Colorectal Cancer Group ONCOBELL Program Bellvitge Biomedical Research Institute Barcelona Spain Oncology Data Analytics Program Catalan Institute of Oncology Barcelona Spain Consortium for Biomedical Research in Epidemiology and Public Health Madrid Madrid Spain Department of Clinical Sciences Faculty of Medicine University of Barcelona Barcelona Spain Department of Biostatistics School of Public Health University of Washington Seattle WA USA Institute of Cancer and Genomic Sciences College of Medical and Dental Sciences University of Birmingham Birmingham UK Department of Public Health Richard Doll Building University of Oxford Oxford UK Department of Biomedical Informatics Vanderbilt University School of Medicine Nashville TN USA Department of Preventive Medicine USC Norris Comprehensive Cancer Center Keck School of Medicine University of Southern California Los Angeles CA USA Center for Public Health Genomics Department of Public Health Sciences University of Virginia Charlottesville VA USA Department of Populat

Colorectal cancer (CRC) is a leading cause of mortality worldwide. We conducted a genome-wide association study meta-analysis of 100,204 CRC cases and 154,587 controls of European and east Asian ancestry, identifying 205 independent risk associations, of which 50 were unreported. We performed integrative genomic, transcriptomic and methylomic analyses across large bowel mucosa and other tissues. Transcriptome- and methylome-wide association studies revealed an additional 53 risk associations. We identified 155 high-confidence effector genes functionally linked to CRC risk, many of which had no previously established role in CRC. These have multiple different functions and specifically indicate that variation in normal colorectal homeostasis, proliferation, cell adhesion, migration, immunity and microbial interactions determines CRC risk. Crosstissue analyses indicated that over a third of effector genes most probably act outside the colonic mucosa. Our findings provide insights into colorectal oncogenesis and highlight potential targets across tissues for new CRC treatment and chemoprevention strategies.

关键词： Colorectal cancer Epigenomics Genome-wide association studies Transcriptomics

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：