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BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

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Nature methods 2023年第6期20卷 824-835页

作者： Linus Manubens-Gil Zhi Zhou Hanbo Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro Bria Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E Bouchard Lin Gu Weidong Cai Shuiwang Ji Badrinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan Bas Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua Bing Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Oberlaender Gregory Jefferis Kei Ito Paloma Gonzalez-Bellido Jinhyun Kim Edwin Rubel Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

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Author Correction: Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines

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Nature communications 2024年第1期15卷 6376页

作者： Alexander P L Martindale Carrie D Llewellyn Richard O de Visser Benjamin Ng Victoria Ngai Aditya U Kale Lavinia Ferrante di Ruffano Robert M Golub Gary S Collins David Moher Melissa D McCradden Lauren Oakden-Rayner Samantha Cruz Rivera Melanie Calvert Christopher J Kelly Cecilia S Lee Christopher Yau An-Wen Chan Pearse A Keane Andrew L Beam Alastair K Denniston Xiaoxuan Liu Brighton and Sussex Medical School Brighton UK. Department of Primary Care and Public Health Brighton and Sussex Medical School Brighton UK. Birmingham and Midland Eye Centre Sandwell and West Birmingham NHS Trust Birmingham UK. Christ Church University of Oxford Oxford UK. University College London Medical School London UK. Institute of Inflammation and Ageing University of Birmingham Birmingham UK. University Hospitals Birmingham NHS Foundation Trust Birmingham UK. National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre University of Birmingham Birmingham UK. York Health Economics Consortium University of York Birmingham UK. Northwestern University Feinberg School of Medicine Chicago Illinois USA. Centre for Statistics in Medicine//UK EQUATOR Centre Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences University of Oxford Oxford UK. Centre for Journalology Clinical Epidemiology Program Ottawa Hospital Research Institute Ottowa Canada. Department of Bioethics The Hospital for Sick Children Toronto Canada. Genetics & Genome Biology Research Program Peter Gilgan Centre for Research & Learning Toronto Canada. Division of Clinical and Public Health Dalla Lana School of Public Health Toronto Canada. Australian Institute for Machine Learning University of Adelaide Adelaide Australia. Birmingham Health Partners Centre for Regulatory Science and Innovation University of Birmingham Birmingham UK. Centre for Patient Reported Outcomes Research (CPROR) Institute of Applied Health Research College of Medical and Dental Sciences University of Birmingham Birmingham UK. NIHR Applied Research Collaboration (ARC) West Midlands University of Birmingham Birmingham UK. NIHR Blood and Transplant Research Unit (BTRU) in Precision Transplant and Cellular Therapeutics University of Birmingham Birmingham UK. Google Health London UK. University of Washington Seattle WA USA. Nuffield Department of Women's and Rep

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Global, regional, and national incidence of six major immune-mediated inflammatory diseases: findings from the global burden of disease study 2019

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eClinicalMedicine 2023年 64卷 102193-102193页

作者： Wu, Dongze Jin, Yingzhao Xing, Yuhan Abate, Melsew Dagne Abbasian, Mohammadreza Abbasi-Kangevari, Mohsen Abbasi-Kangevari, Zeinab Abd-Allah, Foad Abdelmasseh, Michael Abdollahifar, Mohammad-Amin Abdulah, Deldar Morad Abedi, Aidin Abedi, Vida Abidi, Hassan Aboagye, Richard Gyan Abolhassani, Hassan Abuabara, Katrina Abyadeh, Morteza Addo, Isaac Yeboah Adeniji, Kayode Nelson Adepoju, Abiola Victor Adesina, Miracle Ayomikun Adnani, Qorinah Estiningtyas Sakilah Afarideh, Mohsen Aghamiri, Shahin Agodi, Antonella Agrawal, Anurag Arriagada, Constanza Elizabeth Aguilera Ahmad, Aqeel Ahmad, Danish Ahmad, Sohail Ahmadi, Ali Ahmed, Ayman Aithala, Janardhana P. Ajadi, Abdullateef Abiodun Ajami, Marjan Akbarzadeh-Khiavi, Mostafa Alahdab, Fares AlBataineh, Mohammad T. Alemi, Sharifullah Al-Gheethi, Adel Ali Saeed Ali, Liaqat Alif, Sheikh Mohammad Almazan, Joseph Uy Almustanyir, Sami Alqahtani, Jaber S. Alqasmi, Ibrahim Altaf, Ihsan Ullah Khan Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Al-Worafi, Yaser Mohammed Aly, Hany Amani, Reza Amu, Hubert Amusa, Ganiyu Adeniyi Andrei, Catalina Liliana Ansar, Adnan Ansariniya, Hossein Anyasodor, Anayochukwu Edward Arabloo, Jalal Arefnezhad, Reza Arulappan, Judie Asghari-Jafarabadi, Mohammad Ashraf, Tahira Atata, Jamila Abdulhamid Athari, Seyyed Shamsadin Atlaw, Daniel Atout, Maha Moh'd Wahbi Aujayeb, Avinash Awan, Asma Tahir Ayatollahi, Haleh Azadnajafabad, Sina Azzam, Ahmed Y. Badawi, Alaa Badiye, Ashish D. Bagherieh, Sara Baig, Atif Amin Bantie, Berihun Bantie Barchitta, Martina Bardhan, Mainak Barker-Collo, Suzanne Lyn Barone-Adesi, Francesco Batra, Kavita Bayileyegn, Nebiyou Simegnew Behnoush, Amir Hossein Belgaumi, Uzma Iqbal Bemanalizadeh, Maryam Bensenor, Isabela M. Beyene, Kebede A. Bhagavathula, Akshaya Srikanth Bhardwaj, Pankaj Bhaskar, Sonu Bhat, Ajay Nagesh Bitaraf, Saeid Bitra, Veera R. Boloor, Archith Bora, Kaustubh Botelho, João Silva Buchbinder, Rachelle Calina, Daniela Cámera, Luis Alberto Carvalho, Andre F. Chan, Jeffrey Shi Kai Chattu, Vijay Kumar Abebe, Endeshaw Chekol Department of Rheumatology and Immunology Sichuan Provincial People's Hospital School of Medicine University of Electronic Science and Technology of China China Department of Medicine & Therapeutics The Chinese University of Hong Kong Hong Kong Department of Paediatrics The Chinese University of Hong Kong Hong Kong School of Pharmacy The Chinese University of Hong Kong Hong Kong Jockey Club School of Public Health and Primary Care The Chinese University of Hong Kong Hong Kong Department of Nursing Woldia University Woldia Ethiopia Department of Orthopedic Surgery Harvard University Boston MA United States Postgraduate Medical Education Harvard University Boston MA United States Maternal Fetal Care Center Harvard University Boston MA United States Department of Health Policy and Oral Epidemiology Harvard University Boston MA United States Division of General Internal Medicine Harvard University Boston MA United States Department of Orthopaedic Surgery Shahid Beheshti University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Biotechnology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Epidemiology Shahid Beheshti University of Medical Sciences Tehran Iran National Nutrition and Food Technology Research Institute Shahid Beheshti University of Medical Sciences Tehran Iran Department of Immunology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Neurology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Medical Genetics Shahid Beheshti University of Medical Sciences Tehran Iran Center for Comprehensive Genetic Services Shahid Beheshti University of Medical Sciences Tehran Iran Cancer Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Health Economics and Statistics Shahid Beheshti University of Medical Sciences Tehran Iran Functional Neuro

Background: The causes for immune-mediated inflammatory diseases (IMIDs) are diverse and the incidence trends of IMIDs from specific causes are rarely studied. The study aims to investigate the pattern and trend of IMIDs from 1990 to 2019. Methods: We collected detailed information on six major causes of IMIDs, including asthma, inflammatory bowel disease, multiple sclerosis, rheumatoid arthritis, psoriasis, and atopic dermatitis, between 1990 and 2019, derived from the Global Burden of Disease study in 2019. The average annual percent change (AAPC) in number of incidents and age standardized incidence rate (ASR) on IMIDs, by sex, age, region, and causes, were calculated to quantify the temporal trends. Findings: In 2019, rheumatoid arthritis, atopic dermatitis, asthma, multiple sclerosis, psoriasis, inflammatory bowel disease accounted 1.59%, 36.17%, 54.71%, 0.09%, 6.84%, 0.60% of overall new IMIDs cases, respectively. The ASR of IMIDs showed substantial regional and global variation with the highest in High SDI region, High-income North America, and United States of America. Throughout human lifespan, the age distribution of incident cases from six IMIDs was quite different. Globally, incident cases of IMIDs increased with an AAPC of 0.68 and the ASR decreased with an AAPC of −0.34 from 1990 to 2019. The incident cases increased across six IMIDs, the ASR of rheumatoid arthritis increased (0.21, 95% CI 0.18, 0.25), while the ASR of asthma (AAPC = −0.41), inflammatory bowel disease (AAPC = −0.72), multiple sclerosis (AAPC = −0.26), psoriasis (AAPC = −0.77), and atopic dermatitis (AAPC = −0.15) decreased. The ASR of overall and six individual IMID increased with SDI at regional and global level. Countries with higher ASR in 1990 experienced a more rapid decrease in ASR. Interpretation: The incidence patterns of IMIDs varied considerably across the world. Innovative prevention and integrative management strategy are urgently needed to mitigate the increasing ASR of rh

关键词： Global burden of disease study Immune-mediated inflammatory disease Incidence Trend

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Allogeneic Hematopoietic Cell Transplantation (HCT) Vs. Non-HCT Consolidation Therapies in Acute Myeloid Leukemia (AML) Patients 60-75 Years of Age in First Complete Remission (CR1): An Alliance (A151509), SWOG, ECOG-ACRIN and CIBMTR Study

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Blood 2018年 132卷 2170-2170页

作者： Celalettin Ustun Jennifer Le-Rademacher Hai-Lin Wang Megan Othus Zhuoxin Sun Brittny Major Mei-Jie Zhang Elizabeth Storrick Jacqueline M Lafky Selina Chow Krzysztof Mrózek Eyal C. Attar Clara D. Bloomfield Larry D Cripe Richard A. Larson Guido Marcucci Gail J. Roboz Geoffrey L. Uy Richard M. Stone Aminah Jatoi Andrew S Artz Blood and Marrow Transplant Program University of Minnesota Minneapolis MN Dept of Biomedical Statistics and Informatics Mayo Clinic Rochester MN CIBMTR (Center for International Blood and Marrow Transplant Research) Department of Medicine Medical College of Wisconsin Milwaukee WI Public Health Sciences Division Fred Hutchinson Cancer Research Center Seattle Harvard T.H. Chan School of Public Health Boston Department of Health Sciences Research Mayo Clinic Rochester Alliance Statistics and Data Center Mayo Clinic Rochester MN Mayo Clinic Rochester University of Chicago Comprehensive Cancer Center Chicago The Ohio State University Comprehensive Cancer Center Columbus OH Massachusetts General Hospital Boston Agios Pharmaceuticals Inc. Cambridge MA Comprehensive Cancer Center The Ohio State University Columbus OH Indiana University Simon Cancer Center Indianapolis Department of Medicine and Comprehensive Cancer Center University of Chicago Chicago IL Department of Hematological Malignancies Translational Science Gehr Family Center for Leukemia Research Hematologic Malignancies and Stem Cell Transplantation Institute Beckman Research Institute City of Hope Medical Center Duarte CA Weill Cornell Medicine and The Weill Medical College of Cornell University New York NY Washington University School of Medicine Saint Louis MO Dana-Farber Cancer Institute Boston MA Department of Medicine Section of Hematology/Oncology University of Chicago Chicago IL

Introduction: The preferred post-remission therapy for older patients (pts) with AML remains uncertain. We compared outcomes for older AML pts in CR1 receiving HCT reported to the CIBMTR to older AML pts achieving CR1 on National Clinical Trials Network induction and non-HCT consolidation therapy (CT) trials. Methods: This study focused on pts 60-75 years of age treated between 2004 to 2013. CT pts (n=211) underwent induction and consolidation on Alliance for Clinical Trials in Oncology, ECOG-ACRIN or SWOG clinical trials for initial therapy for newly diagnosed AML; the CIBMTR provided data for HCT pts (n=431). CT patients received at least one cycle of CT on study and were excluded if HCT occurred at any time. Time to event started at CR1 and pts entered at CT or HCT, respectively, using left-truncation to account for differential entry times. Results: For the CT cohort, first consolidation included standard therapy (e.g., cytarabine or a hypomethylating agent) and additional study drug (e.g., bortezomib, dasatinib, sorafenib, and Zosuquidar, gemtuzumab) or tipifarnib alone. Among HCT pts, the donor was a HLA-matched sibling or unrelated donor (URD) in 66% and the others were partially HLA-matched/mismatched URD (10%) or cord blood (24%). HCT pts were younger and more frequently had high-risk AML (high WBC, secondary AML and unfavorable cytogenetics) (Table). The median time from CR1 to HCT and CT was 3.2 and 0.5 months, respectively. Allogeneic HCT showed worse overall survival (OS) (HR=1.52, p=0.02) prior to 9 months and better OS thereafter (HR= 0.53, p <0.0001) relative to CT (figure 1A). Treatment-related mortality (TRM) was worse after HCT in the first 9 months (HR=2.8, CI: 1.5 -5.2, p =.0009), while relapse was less frequent beyond 9 months after treatment (HR = 0.42, CI: 0.29 to 0.61, p <.0001). Despite higher early TRM, HCT recipients went on to manifest superior OS [5 year OS: HCT 29% (24-34%), CT 13.8% (9 -22%)] (Figure 1A). The benefit of HCT for surviv

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Psychometric properties of the Alcohol Use Disorders Identification Test (AUDIT) across cross-cultural subgroups, genders, and sexual orientations: Findings from the International Sex Survey (ISS)

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Comprehensive Psychiatry 2023年 127卷 152427页

作者： Horváth, Zsolt Nagy, Léna Koós, Mónika Kraus, Shane W. Demetrovics, Zsolt Potenza, Marc N. Ballester-Arnal, Rafael Batthyány, Dominik Bergeron, Sophie Billieux, Joël Briken, Peer Burkauskas, Julius Cárdenas-López, Georgina Carvalho, Joana Castro-Calvo, Jesús Chen, Lijun Ciocca, Giacomo Corazza, Ornella Csako, Rita Fernandez, David P. Fujiwara, Hironobu Fernandez, Elaine F. Fuss, Johannes Gabrhelík, Roman Gewirtz-Meydan, Ateret Gjoneska, Biljana Gola, Mateusz Grubbs, Joshua B. Hashim, Hashim T. Islam, Md. Saiful Ismail, Mustafa Jiménez-Martínez, Martha C. Jurin, Tanja Kalina, Ondrej Klein, Verena Költő, András Lee, Sang-Kyu Lewczuk, Karol Lin, Chung-Ying Lochner, Christine López-Alvarado, Silvia Lukavská, Kateřina Mayta-Tristán, Percy Miller, Dan J. Orosová, Oľga Orosz, Gábor Ponce, Fernando P. Quintana, Gonzalo R. Quintero Garzola, Gabriel C. Ramos-Diaz, Jano Rigaud, Kévin Rousseau, Ann Scanavino, Marco De Tubino Schulmeyer, Marion K. Sharan, Pratap Shibata, Mami Shoib, Sheikh Sigre-Leirós, Vera Sniewski, Luke Spasovski, Ognen Steibliene, Vesta Stein, Dan J. Strizek, Julian Tsai, Meng-Che Ünsal, Berk C. Vaillancourt-Morel, Marie-Pier Van Hout, Marie Claire Bőthe, Beáta Institute of Psychology ELTE Eötvös Loránd University Budapest Hungary Centre of Excellence in Responsible Gaming University of Gibraltar Gibraltar Gibraltar Doctoral School of Psychology ELTE Eötvös Loránd University Budapest Hungary Department of Psychology University of Nevada Las Vegas Las Vegas NV United States Yale University School of Medicine New Haven CT United States Connecticut Council on Problem Gambling Wethersfield CT United States Connecticut Mental Health Center New Haven CT United States Departmento de Psicología Básica Clínica y Psicobiología University Jaume I of Castellón Spain Institute for Behavioural Addictions Sigmund Freud University Vienna Austria Département de psychologie Université de Montréal Montréal Canada Institute of Psychology University of Lausanne Lausanne Switzerland Center for Excessive Gambling Addiction Medicine Lausanne University Hospitals (CHUV) Lausanne Switzerland Institute for Sex Research Sexual Medicine and Forensic Psychiatry University Medical Centre Hamburg-Eppendorf Hamburg Germany Laboratory of Behavioral Medicine Neuroscience Institute Lithuanian University of Health Sciences Palanga Lithuania Virtual Teaching and Cyberpsychology Laboratory School of Psychology National Autonomous University of Mexico Mexico William James Center for Research Departamento de Educação e Psicologia Universidade de Aveiro Aveiro Portugal Department of Personality Assessment and Psychological Treatments University of Valencia Spain Department of Psychology College of Humanity and Social Science Fuzhou University China Section of Sexual Psychopathology Department of Dynamic and Clinical Psychology and Health Studies Sapienza University of Rome Rome Italy Department of Clinical Pharmaceutical and Biological Sciences University of Hertfordshire United Kingdom Department of Psychocology and Cognitive Science University of Trento Italy Department of Psychology and Neuroscience Auckland University of Technology Auc

Introduction: Despite being a widely used screening questionnaire, there is no consensus on the most appropriate measurement model for the Alcohol Use Disorders Identification Test (AUDIT). Furthermore, there have been limited studies on its measurement invariance across cross-cultural subgroups, genders, and sexual orientations. Aims: The present study aimed to examine the fit of different measurement models for the AUDIT and its measurement invariance across a wide range of subgroups by country, language, gender, and sexual orientation. Methods: Responses concerning past-year alcohol use from the participants of the cross-sectional International Sex Survey were considered (N = 62,943;M_age: 32.73;SD = 12.59). Confirmatory factor analysis, as well as measurement invariance tests were performed for 21 countries, 14 languages, three genders, and four sexual-orientation subgroups that met the minimum sample size requirement for inclusion in these analyses. Results: A two-factor model with factors describing ‘alcohol use’ (items 1–3) and ‘alcohol problems’ (items 4–10) showed the best model fit across countries, languages, genders, and sexual orientations. For the former two, scalar and latent mean levels of invariance were reached considering different criteria. For gender and sexual orientation, a latent mean level of invariance was reached. Conclusions: In line with the two-factor model, the calculation of separate alcohol-use and alcohol-problem scores is recommended when using the AUDIT. The high levels of measurement invariance achieved for the AUDIT support its use in cross-cultural research, capable also of meaningful comparisons among genders and sexual orientations. © 2023

关键词： Addictive behaviors Alcohol Use Disorders Identification Test (AUDIT) Cross-cultural comparison Gender LGBTQ Measurement invariance Sexual orientation

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Sequence diversity analyses of an improved rhesus macaque genome enhance its biomedical utility

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SCIENCE 2020年第6523期370卷 000-000页

作者： Warren, Wesley C. Harris, R. Alan Haukness, Marina Fiddes, Ian T. Murali, Shwetha C. Fernandes, Jason Dishuck, Philip C. Storer, Jessica M. Raveendran, Muthuswamy Hillier, LaDeana W. Porubsky, David Mao, Yafei Gordon, David Vollger, Mitchell R. Lewis, Alexandra P. Munson, Katherine M. DeVogelaere, Elizabeth Armstrong, Joel Diekhans, Mark Walker, Jerilyn A. Tomlinson, Chad Graves-Lindsay, Tina A. Kremitzki, Milinn Salama, Sofie R. Audano, Peter A. Escalona, Merly Maurer, Nicholas W. Antonacci, Francesca Mercuri, Ludovica Maggiolini, Flavia A. M. Catacchio, Claudia Rita Underwood, Jason G. O'Connor, David H. Sanders, Ashley D. Korbel, Jan O. Ferguson, Betsy Kubisch, H. Michael Picker, Louis Kalin, Ned H. Rosene, Douglas Levine, Jon Abbott, David H. Gray, Stanton B. Sanchez, Mar M. Kovacs-Balint, Zsofia A. Kemnitz, Joseph W. Thomasy, Sara M. Roberts, Jeffrey A. Kinnally, Erin L. Capitanio, John P. Skene, J. H. Pate Platt, Michael Cole, Shelley A. Green, Richard E. Ventura, Mario Wiseman, Roger W. Paten, Benedict Batzer, Mark A. Rogers, Jeffrey Eichler, Evan E. Department of Animal Sciences Bond Life Sciences Center University of Missouri Columbia MO 65211 USA. Department of Surgery School of Medicine University of Missouri Columbia MO 65211 USA. Institute of Data Science and Informatics University of Missouri Columbia MO 65211 USA. Human Genome Sequencing Center Department of Molecular and Human Genetics Baylor College of Medicine Houston TX 77030 USA. Computational Genomics Laboratory University of California-Santa Cruz Santa Cruz CA 95064 USA. Inscripta Inc. Boulder CO 80301 USA. Department of Genome Sciences University of Washington Seattle WA 98195 USA. Howard Hughes Medical Institute University of Washington Seattle WA 98195 USA. Department of Biomolecular Engineering University of California-Santa Cruz Santa Cruz CA 95064 USA. Department of Biological Sciences Louisiana State University Baton Rouge LA 70803 USA. Institue for Systems Biology Seattle WA 98109 USA. McDonnell Genome Institute Washington University St. Louis MO 63108 USA. Department of Biology University of Bari ’Aldo Moro’ 70125 Bari Italy. Pacific Biosciences of California Seattle WA 94025 USA. Department of Pathology and Laboratory Medicine Wisconsin National Primate Research Center University of Wisconsin-Madison Madison WI 53711 USA. European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany. Division of Genetics Oregon National Primate Research Center Oregon Health and Science University Beaverton OR 97006 USA. Tulane National Primate Research Center Covington LA 70433 USA. Oregon National Primate Research Center and Vaccine and Gene Therapy Institute Oregon Health Sciences University Beaverton OR 97006 USA. Department of Psychiatry University of Wisconsin School of Medicine and Public Health Madison WI 53719 USA. Department of Anatomy and Neurobiology Boston University School of Medicine Boston MA 02118 USA. Department of Neuroscience University of Wisconsin Madison WI 53175 USA. Wisconsin N

The rhesus macaque (Macaca mulatta) is the most widely studied nonhuman primate (NHP) in biomedical research. We present an updated reference genome assembly (Mmul_10, contig N50 = 46 Mbp) that increases the sequence contiguity 120-fold and annotate it using 6.5 million full-length transcripts, thus improving our understanding of gene content, isoform diversity, and repeat organization. With the improved assembly of segmental duplications, we discovered new lineage-specific genes and expanded gene families that are potentially informative in studies of evolution and disease susceptibility. Whole-genome sequencing (WGS) data from 853 rhesus macaques identified 85.7 million single-nucleotide variants (SNVs) and 10.5 million indel variants, including potentially damaging variants in genes associated with human autism and developmental delay, providing a framework for developing noninvasive NHP models of human disease.

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GREGoR: Accelerating Genomics for Rare Diseases

arXiv

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arXiv 2024年

作者： Dawood, Moez Heavner, Ben Wheeler, Marsha M. Ungar, Rachel A. LoTempio, Jonathan Wiel, Laurens Berger, Seth Bernstein, Jonathan A. Chong, Jessica X. Délot, Emmanuèle C. Eichler, Evan E. Gibbs, Richard A. Lupski, James R. Shojaie, Ali Talkowski, Michael E. Wagner, Alex H. Wei, Chia-Lin Wellington, Christopher Wheeler, Matthew T. Carvalho, Claudia M.B. Gifford, Casey A. May, Susanne Miller, Danny E. Rehm, Heidi L. Sedlazeck, Fritz J. Vilain, Eric O'Donnell-Luria, Anne Posey, Jennifer E. Chadwick, Lisa H. Bamshad, Michael J. Montgomery, Stephen B. Human Genome Sequencing Center Baylor College of Medicine HoustonTX United States Department of Molecular and Human Genetics Baylor College of Medicine HoustonTX United States Medical Scientist Training Program Baylor College of Medicine HoustonTX United States Department of Biostatistics University of Washington SeattleWA United States Department of Genetics School of Medicine Stanford University StanfordCA United States Department of Pathology School of Medicine Stanford University Stanford CA United States Stanford Center for Biomedical Ethics School of Medicine Stanford University Stanford CA United States Institute for Clinical and Translational Science University of California IrvineCA United States Division of Cardiovascular Medicine School of Medicine Stanford University Stanford CA United States Division of Genetics and Metabolism Children’s National Rare Disease Institute WashingtonDC United States Center for Genetic Medicine Research Children’s National Rare Disease Institute WashingtonDC United States Department of Genomics and Precision Medicine George Washington University WashingtonDC United States Department of Pediatrics School of Medicine Stanford University Stanford CA United States Department of Pediatrics Dvision of Genetic Medicine University of Washington SeattleWA United States Brotman Baty Institute for Precision Medicine University of Washington SeattleWA United States Department of Genome Sciences University of Washington SeattleWA United States Howard Hughes Medical Institute University of Washington SeattleWA United States Department of Pediatrics Baylor College of Medicine HoustonTX United States Center for Genomic Medicine Massachusetts General Hospital BostonMA United States Program in Medical and Population Genetics Broad Institute of MIT and Harvard BostonMA United States Department of Neurology Massachusetts General Hospital Harvard Medical School BostonMA United States Stanley Center for

Rare diseases are collectively common, affecting approximately one in twenty individuals worldwide. In recent years, rapid progress has been made in rare disease diagnostics due to advances in DNA sequencing, development of new computational and experimental approaches to prioritize genes and genetic variants, and increased global exchange of clinical and genetic data. However, more than half of individuals suspected to have a rare disease lack a genetic diagnosis. The Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) Consortium was initiated to study thousands of challenging rare disease cases and families and apply, standardize, and evaluate emerging genomics technologies and analytics to accelerate their adoption in clinical practice. Further, all data generated, currently representing ~7500 individuals from ~3000 families, is rapidly made available to researchers worldwide via the Genomic data Science Analysis, Visualization, and informatics Lab-space (AnVIL) to catalyze global efforts to develop approaches for genetic diagnoses in rare diseases (https://***/data). The majority of these families have undergone prior clinical genetic testing but remained unsolved, with most being exome-negative. Here, we describe the collaborative research framework, datasets, and discoveries comprising GREGoR that will provide foundational resources and substrates for the future of rare disease genomics. © 2024, CC BY.

关键词： Genome

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Correction: Polygenic risk modeling for prediction of epithelial ovarian cancer risk

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European journal of human genetics : EJHG 2022年第5期30卷 630-631页

作者： Eileen O Dareng Jonathan P Tyrer Daniel R Barnes Michelle R Jones Xin Yang Katja K H Aben Muriel A Adank Simona Agata Irene L Andrulis Hoda Anton-Culver Natalia N Antonenkova Gerasimos Aravantinos Banu K Arun Annelie Augustinsson Judith Balmaña Elisa V Bandera Rosa B Barkardottir Daniel Barrowdale Matthias W Beckmann Alicia Beeghly-Fadiel Javier Benitez Marina Bermisheva Marcus Q Bernardini Line Bjorge Amanda Black Natalia V Bogdanova Bernardo Bonanni Ake Borg James D Brenton Agnieszka Budzilowska Ralf Butzow Saundra S Buys Hui Cai Maria A Caligo Ian Campbell Rikki Cannioto Hayley Cassingham Jenny Chang-Claude Stephen J Chanock Kexin Chen Yoke-Eng Chiew Wendy K Chung Kathleen B M Claes Sarah Colonna Linda S Cook Fergus J Couch Mary B Daly Fanny Dao Eleanor Davies Miguel de la Hoya Robin de Putter Joe Dennis Allison DePersia Peter Devilee Orland Diez Yuan Chun Ding Jennifer A Doherty Susan M Domchek Thilo Dörk Andreas du Bois Matthias Dürst Diana M Eccles Heather A Eliassen Christoph Engel Gareth D Evans Peter A Fasching James M Flanagan Renée T Fortner Eva Machackova Eitan Friedman Patricia A Ganz Judy Garber Francesca Gensini Graham G Giles Gord Glendon Andrew K Godwin Marc T Goodman Mark H Greene Jacek Gronwald Eric Hahnen Christopher A Haiman Niclas Håkansson Ute Hamann Thomas V O Hansen Holly R Harris Mikael Hartman Florian Heitz Michelle A T Hildebrandt Estrid Høgdall Claus K Høgdall John L Hopper Ruea-Yea Huang Chad Huff Peter J Hulick David G Huntsman Evgeny N Imyanitov Claudine Isaacs Anna Jakubowska Paul A James Ramunas Janavicius Allan Jensen Oskar Th Johannsson Esther M John Michael E Jones Daehee Kang Beth Y Karlan Anthony Karnezis Linda E Kelemen Elza Khusnutdinova Lambertus A Kiemeney Byoung-Gie Kim Susanne K Kjaer Ian Komenaka Jolanta Kupryjanczyk Allison W Kurian Ava Kwong Diether Lambrechts Melissa C Larson Conxi Lazaro Nhu D Le Goska Leslie Jenny Lester Fabienne Lesueur Douglas A Levine Lian Li Jingmei Li Jennifer T Loud Karen H Lu Jan Lubiński Phuong L Mai Siranoush Manoukian Jeffrey R Marks Ra University of Cambridge Centre for Cancer Genetic Epidemiology Department of Public Health and Primary Care Cambridge UK. University of Cambridge Centre for Cancer Genetic Epidemiology Department of Oncology Cambridge UK. Center for Bioinformatics and Functional Genomics Cedars-Sinai Medical Center Los Angeles CA USA. Radboud University Medical Center Radboud Institute for Health Sciences Nijmegen The Netherlands. Netherlands Comprehensive Cancer Organisation Utrecht The Netherlands. The Netherlands Cancer Institute-Antoni van Leeuwenhoek hospital Family Cancer Clinic Amsterdam The Netherlands. Veneto Institute of Oncology IOV-IRCCS Immunology and Molecular Oncology Unit Padua Italy. Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital Fred A. Litwin Center for Cancer Genetics Toronto ON Canada. University of Toronto Department of Molecular Genetics Toronto ON Canada. University of California Irvine Department of Epidemiology Genetic Epidemiology Research Institute Irvine CA USA. N.N. Alexandrov Research Institute of Oncology and Medical Radiology Minsk Belarus. 'Agii Anargiri' Cancer Hospital Athens Greece. University of Texas MD Anderson Cancer Center Department of Breast Medical Oncology Houston TX USA. Lund University Department of Cancer Epidemiology Clinical Sciences Lund Sweden. Vall d'Hebron Institute of Oncology Hereditary cancer Genetics Group Barcelona Spain. University Hospital of Vall d'Hebron Department of Medical Oncology Barcelona Spain. Rutgers Cancer Institute of New Jersey Cancer Prevention and Control Program New Brunswick NJ USA. Landspitali University Hospital Department of Pathology Reykjavik Iceland. University of Iceland BMC (Biomedical Centre) Faculty of Medicine Reykjavik Iceland. University Hospital Erlangen Friedrich-Alexander-University Erlangen-Nuremberg Department of Gynecology and Obstetrics Comprehensive Cancer Center ER-EMN Erlangen Germany. Vanderbilt University School of Medicine Division of Epide

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Correction: Association of low-frequency and rare coding variants with information processing speed

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Translational psychiatry 2022年第1期12卷 88页

作者： Jan Bressler Gail Davies Albert V Smith Yasaman Saba Joshua C Bis Xueqiu Jian Caroline Hayward Lisa Yanek Jennifer A Smith Saira S Mirza Ruiqi Wang Hieab H H Adams Diane Becker Eric Boerwinkle Archie Campbell Simon R Cox Gudny Eiriksdottir Chloe Fawns-Ritchie Rebecca F Gottesman Megan L Grove Xiuqing Guo Edith Hofer Sharon L R Kardia Maria J Knol Marisa Koini Oscar L Lopez Riccardo E Marioni Paul Nyquist Alison Pattie Ozren Polasek David J Porteous Igor Rudan Claudia L Satizabal Helena Schmidt Reinhold Schmidt Stephen Sidney Jeannette Simino Blair H Smith Stephen T Turner Sven J van der Lee Erin B Ware Rachel A Whitmer Kristine Yaffe Qiong Yang Wei Zhao Vilmundur Gudnason Lenore J Launer Annette L Fitzpatrick Bruce M Psaty Myriam Fornage M Arfan Ikram Cornelia M van Duijn Sudha Seshadri Thomas H Mosley Ian J Deary Human Genetics Center School of Public Health University of Texas Health Science Center at Houston Houston TX USA. jan.bressler@uth.tmc.edu. Lothian Birth Cohorts University of Edinburgh Edinburgh UK. Department of Psychology University of Edinburgh Edinburgh UK. Icelandic Heart Association Kopavogur Iceland. Gottfried Schatz Research Center for Cell Signaling Metabolism and Aging Medical University of Graz Graz Austria. Cardiovascular Health Research Unit Department of Medicine University of Washington Seattle WA USA. Brown Foundation Institute of Molecular Medicine University of Texas Health Science Center at Houston Houston TX USA. Medical Research Council Human Genetics Unit Institute of Genetics and Cancer University of Edinburgh Edinburgh UK. Generation Scotland Centre for Genomic and Experimental Medicine Institute of Genetics and Cancer University of Edinburgh Edinburgh UK. Department of General Internal Medicine Johns Hopkins University School of Medicine Baltimore MD USA. Department of Epidemiology School of Public Health University of Michigan Ann Arbor MI USA. Survey Research Center Institute for Social Research University of Michigan Ann Arbor MI USA. Department of Epidemiology Erasmus MC University Medical Center Rotterdam The Netherlands. Department of Neurology Sunnybrook Health Sciences Centre Toronto ON Canada. Department of Medicine University of Toronto Toronto ON Canada. Department of Biostatistics Boston University School of Public Health Boston MA USA. Framingham Heart Study Framingham MA USA. Department of Neurology and Alzheimer Center Amsterdam Neuroscience Vrieje Universiteit Medical Center Amsterdam The Netherlands. Human Genetics Center School of Public Health University of Texas Health Science Center at Houston Houston TX USA. Human Genome Sequencing Center Baylor College of Medicine Houston TX USA. Centre for Genomic and Experimental Medicine Institute of Genetics and Cancer University of Edinburgh Ed

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Correction to: Overlapping genetic architecture between Parkinson disease and melanoma

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Acta neuropathologica 2020年第5期139卷 963页

作者： Umber Dube Laura Ibanez John P Budde Bruno A Benitez Albert A Davis Oscar Harari Mark M Iles Matthew H Law Kevin M Brown Carlos Cruchaga Medical Scientist Training Program Washington University School of Medicine 660 S. Euclid Ave St. Louis MO 63110 USA. Department of Psychiatry Washington University School of Medicine 660 S. Euclid Ave. CB8134 St. Louis MO 63110 USA. Department of Neurology Washington University School of Medicine St Louis MO USA. Department of Psychiatry NeuroGenomics and Informatics Washington University School of Medicine 660 S. Euclid Ave. B8111 St. Louis MO 63110 USA. Leeds Institute for Data Analytics University of Leeds Leeds UK. Statistical Genetics QIMR Berghofer Medical Research Institute Brisbane Australia. Division of Cancer Epidemiology and Genetics National Cancer Institute National Institutes of Health Bethesda Maryland USA. Department of Psychiatry Washington University School of Medicine 660 S. Euclid Ave. CB8134 St. Louis MO 63110 USA. cruchagac@wustl.edu. Department of Neurology Washington University School of Medicine St Louis MO USA. cruchagac@wustl.edu. Department of Psychiatry NeuroGenomics and Informatics Washington University School of Medicine 660 S. Euclid Ave. B8111 St. Louis MO 63110 USA. cruchagac@wustl.edu.

The original version of this article unfortunately contained a mistake. Supplementary Tables 3 and 4 are not available with the rest of the supplementary material available online.

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