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Exome sequencing identifies breast cancer susceptibility genes and defines the contribution of coding variants to breast cancer risk (vol 55, pg 1435, 2023)

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NATURE GENETICS 2023年第11期55卷 2009-2009页

作者： Wilcox, Naomi Dumont, Martine Gonzalez-Neira, Anna Carvalho, Sara Beauparlant, Charles Joly Crotti, Marco Luccarini, Craig Soucy, Penny Dubois, Stephane Nunez-Torres, Rocio Pita, Guillermo Gardner, Eugene J. Dennis, Joe Alonso, M. Rosario Alvarez, Nuria Baynes, Caroline Collin-Deschesnes, Annie Claude Desjardins, Sylvie Becher, Heiko Behrens, Sabine Bolla, Manjeet K. Castelao, Jose E. Chang-Claude, Jenny Cornelissen, Sten Dork, Thilo Engel, Christoph Gago-Dominguez, Manuela Guenel, Pascal Hadjisavvas, Andreas Hahnen, Eric Hartman, Mikael Herraez, Belen Jung, Audrey Keeman, Renske Kiechle, Marion Li, Jingmei Loizidou, Maria A. Lush, Michael Michailidou, Kyriaki Panayiotidis, Mihalis I. Sim, Xueling Teo, Soo Hwang Tyrer, Jonathan P. van der Kolk, Lizet E. Wahlstrom, Cecilia Wang, Qin Perry, John R. B. Benitez, Javier Schmidt, Marjanka K. Schmutzler, Rita K. Pharoah, Paul D. P. Droit, Arnaud Dunning, Alison M. Kvist, Anders Devilee, Peter Easton, Douglas F. Simard, Jacques Centre for Cancer Genetic Epidemiology Department of Public Health and Primary Care University of Cambridge Cambridge UK Genomics Center Centre Hospitalier Universitaire de Québec—Université Laval Research Center Québec City Quebec Canada Human Genotyping Unit-CeGen Human Cancer Genetics Programme Spanish National Cancer Research Centre (CNIO) Madrid Spain Centre for Cancer Genetic Epidemiology Department of Oncology University of Cambridge Cambridge UK MRC Epidemiology Unit Wellcome-MRC Institute of Metabolic Science University of Cambridge Cambridge UK Institute of Medical Biometry and Epidemiology University Medical Center Hamburg-Eppendorf Hamburg Germany Division of Cancer Epidemiology German Cancer Research Center (DKFZ) Heidelberg Germany Oncology and Genetics Unit Instituto de Investigación Sanitaria Galicia Sur (IISGS) Xerencia de Xestion Integrada de Vigo-SERGAS Vigo Spain Cancer Epidemiology Group University Cancer Center Hamburg (UCCH) University Medical Center Hamburg-Eppendorf Hamburg Germany Division of Molecular Pathology The Netherlands Cancer Institute Amsterdam the Netherlands Gynaecology Research Unit Hannover Medical School Hannover Germany Institute for Medical Informatics Statistics and Epidemiology University of Leipzig Leipzig Germany LIFE—Leipzig Research Centre for Civilization Diseases University of Leipzig Leipzig Germany Cancer Genetics and Epidemiology Group Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS) Foundation Complejo Hospitalario Universitario de Santiago SERGAS Santiago de Compostela Spain Team ‘Exposome and Heredity ’ CESP Gustave Roussy INSERM University Paris-Saclay UVSQ Villejuif France Department of Cancer Genetics Therapeutics and Ultrastructural Pathology The Cyprus Institute of Neurology & Genetics Nicosia Cyprus Center for Familial Breast and Ovarian Cancer Faculty of Medicine and University Hospital Cologne University of Cologne Cologne Germany Center for Integrated Oncology (C

Linkage and candidate gene studies have identified several breast cancer susceptibility genes, but the overall contribution of coding variation to breast cancer is unclear. To evaluate the role of rare coding variants more comprehensively, we performed a meta-analysis across three large whole-exome sequencing datasets, containing 26,368 female cases and 217,673 female controls. Burden tests were performed for protein-truncating and rare missense variants in 15,616 and 18,601 genes, respectively. Associations between protein-truncating variants and breast cancer were identified for the following six genes at exome-wide significance (P < 2.5 × 10−6): the five known susceptibility genes ATM, BRCA1, BRCA2, CHEK2 and PALB2, together with MAP3K1. Associations were also observed for LZTR1, ATR and BARD1 with P < 1 × 10−4. Associations between predicted deleterious rare missense or protein-truncating variants and breast cancer were additionally identified for CDKN2A at exome-wide significance. The overall contribution of coding variants in genes beyond the previously known genes is estimated to be small.

关键词： Breast cancer Epidemiology Genetics research

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Loss-of-function Gαs rare disease variants exert mutation-specific effects on GPCR signaling

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Science signaling 2025年第887期18卷 eado7543页

作者： Theo Redfern-Nichols Shannon L O'Brien Xianglin Huang Brian Medel-Lacruz Davide Calebiro Jana Selent Graham Ladds Maria Marti-Solano Department of Pharmacology University of Cambridge Tennis Court Road Cambridge CB2 1PD UK. Department of Metabolism and Systems Science College of Medicine and Health University of Birmingham Birmingham B15 2TT UK. Centre of Membrane Proteins and Receptors (COMPARE) Universities of Nottingham and Birmingham Birmingham B15 2TT UK. Research Programme on Biomedical Informatics Hospital del Mar Medical Research Institute Department of Experimental and Health Sciences Pompeu Fabra University Barcelona 08003 Spain.

G protein-coupled receptors (GPCRs) are transmembrane detectors of extracellular signals that activate heterotrimeric G proteins to regulate intracellular responses. Because there are only 16 Gα proteins that can couple to GPCRs, variation in a single Gα can affect the function of numerous receptors. Here, we investigated two mutant forms of Gα (L388R and E392K) that are associated with pseudohypoparathyroidism type Ic (PHPIc), a maternally inherited rare disease. Gα is encoded by an imprinted gene, resulting in the mutant form of Gα being the only version of the protein present in certain tissues, which leads to tissue-specific disease manifestations. By integrating data from three-dimensional structures, GPCR-G protein coupling specificity, transcriptomics, biophysics, and molecular dynamics with systems pharmacology modeling, we identified GPCRs whose signaling could be altered by Gα mutations in the kidney, a tissue involved in the pathophysiology of PHPIc. Analysis of G protein activation by the parathyroid hormone receptor 1 (PTH1R) revealed that L388R impaired Gα interaction with the receptor, whereas E392K reduced the receptor-induced activation of heterotrimeric G. This indicates that different signal transduction steps can be altered by specific Gα mutants associated with the same disease. These findings highlight the importance of investigating mutation-specific perturbations in GPCR signaling to suggest patient-specific treatment strategies. Furthermore, our methods provide a blueprint for interrogating GPCR signaling diversity in different physiological and pathophysiological contexts.

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Towards Clinical AI Fairness: A Translational Perspective

arXiv

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arXiv 2023年

作者： Liu, Mingxuan Ning, Yilin Teixayavong, Salinelat Mertens, Mayli Xu, Jie Ting, Daniel Shu Wei Cheng, Lionel Tim-Ee Ong, Jasmine Chiat Ling Teo, Zhen Ling Tan, Ting Fang Narrendar, Ravi Chandran Wang, Fei Celi, Leo Anthony Ong, Marcus Eng Hock Liu, Nan Centre for Quantitative Medicine Duke-NUS Medical School Singapore Singapore Department of Philosophy University of Antwerp Antwerp Belgium Department of Health Outcomes and Biomedical Informatics University of Florida GainesvilleFL United States Singapore Eye Research Institute Singapore National Eye Centre Singapore Singapore SingHealth AI Office Singapore Health Services Singapore Singapore Department of Diagnostic Radiology Singapore General Hospital Singapore Singapore Department of Pharmacy Singapore General Hospital Singapore Singapore Department of Population Health Sciences Weill Cornell Medicine New YorkNY United States Institute for Medical Engineering and Science Massachusetts Institute of Technology CambridgeMA United States Division of Pulmonary Critical Care and Sleep Medicine Beth Israel Deaconess Medical Center BostonMA United States Department of Biostatistics Harvard T.H. Chan School of Public Health BostonMA United States Programme in Health Services and Systems Research Duke-NUS Medical School Singapore Singapore Department of Emergency Medicine Singapore General Hospital Singapore Singapore Institute of Data Science National University of Singapore Singapore Singapore Centre for Quantitative Medicine Duke-NUS Medical School 8 College Road Singapore169857 Singapore

Artificial intelligence (AI) has demonstrated the ability to extract insights from data, but the issue of fairness remains a concern in high-stakes fields such as healthcare. Despite extensive discussion and efforts in algorithm development, AI fairness and clinical concerns have not been adequately addressed. In this paper, we discuss the misalignment between technical and clinical perspectives of AI fairness, highlight the barriers to AI fairness’ translation to healthcare, advocate multidisciplinary collaboration to bridge the knowledge gap, and provide possible solutions to address the clinical concerns pertaining to AI fairness. © 2023, CC BY.

关键词： Health care

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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)

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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

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Asian diversity in human immune cells

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Cell 2025年第8期188卷 2288-2306.e24页

作者： Kock, Kian Hong Tan, Le Min Han, Kyung Yeon Ando, Yoshinari Jevapatarakul, Damita Chatterjee, Ankita Lin, Quy Xiao Xuan Buyamin, Eliora Violain Sonthalia, Radhika Rajagopalan, Deepa Tomofuji, Yoshihiko Sankaran, Shvetha Park, Mi-So Abe, Mai Chantaraamporn, Juthamard Furukawa, Seiko Ghosh, Supratim Inoue, Gyo Kojima, Miki Kouno, Tsukasa Lim, Jinyeong Myouzen, Keiko Nguantad, Sarintip Oh, Jin-Mi Rayan, Nirmala Arul Sarkar, Sumanta Suzuki, Akari Thungsatianpun, Narita Venkatesh, Prasanna Nori Moody, Jonathan Nakano, Masahiro Chen, Ziyue Tian, Chi Zhang, Yuntian Tong, Yihan Tan, Crystal T.Y. Tizazu, Anteneh Mehari Loh, Marie Hwang, You Yi Ho, Roger C. Larbi, Anis Ng, Tze Pin Won, Hong-Hee Wright, Fred A. Villani, Alexandra-Chloé Park, Jong-Eun Choi, Murim Liu, Boxiang Maitra, Arindam Pithukpakorn, Manop Suktitipat, Bhoom Ishigaki, Kazuyoshi Okada, Yukinori Yamamoto, Kazuhiko Carninci, Piero Chambers, John C. Hon, Chung-Chau Matangkasombut, Ponpan Charoensawan, Varodom Majumder, Partha P. Shin, Jay W. Park, Woong-Yang Prabhakar, Shyam Genome Institute of Singapore (GIS) Agency for Science STAR) 60 Biopolis Street Genome Singapore 138672 Singapore Samsung Genome Institute Samsung Medical Center Seoul 06351 South Korea Laboratory for Advanced Genomics Circuit RIKEN Center for Integrative Medical Sciences (IMS) 1-7-22 Suehiro-cho Tsurumi-ku Kanagawa Yokohama 230-0045 Japan Laboratory for Transcriptome Technology RIKEN Center for IMS 1-7-22 Suehiro-cho Tsurumi-ku Kanagawa Yokohama 230-0045 Japan Single-cell omics and Systems Biology of Diseases (scSyBiD) Research Unit Faculty of Science Mahidol University Bangkok 10400 Thailand Department of Microbiology Faculty of Science Mahidol University Bangkok 10400 Thailand John C. Martin Centre for Liver Research and Innovations Sonarpur Kolkata 700150 India Laboratory for Systems Genetics RIKEN Center for IMS 1-7-22 Suehiro-cho Tsurumi-ku Kanagawa Yokohama 230-0045 Japan Department of Statistical Genetics of Medicine Osaka University 2-2 Yamadaoka Osaka Suita 565-0871 Japan Integrated Frontier Research for Medical Science Division Institute for Open and Transdisciplinary Research Initiatives Osaka University 2-2 Yamadaoka Osaka Suita 565-0871 Japan Samsung Advanced Institute for Health Sciences & Technology Sungkyunkwan University Seoul 06351 South Korea Laboratory for Autoimmune Diseases RIKEN Center for IMS 1-7-22 Suehiro-cho Tsurumi-ku Kanagawa Yokohama 230-0045 Japan Department of Biochemistry Faculty of Science Mahidol University Bangkok 10400 Thailand Integrative Computational BioScience Center Mahidol University Nakhon Pathom 73170 Thailand Biotechnology Research and Innovation Council National Institute of Biomedical Genomics West Bengal Kalyani 741251 India Laboratory for Genome Information Analysis RIKEN Center for IMS 1-7-22 Suehiro-cho Tsurumi-ku Kanagawa Yokohama 230-0045 Japan Department of Allergy and Rheumatology of Medicine The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-8654 Japan D

The relationships of human diversity with biomedical phenotypes are pervasive yet remain understudied, particularly in a single-cell genomics context. Here, we present the Asian Immune Diversity Atlas (AIDA), a multi-national single-cell RNA sequencing (scRNA-seq) healthy reference atlas of human immune cells. AIDA comprises 1,265,624 circulating immune cells from 619 donors, spanning 7 population groups across 5 Asian countries, and 6 controls. Though population groups are frequently compared at the continental level, we found that sub-continental diversity, age, and sex pervasively impacted cellular and molecular properties of immune cells. These included differential abundance of cell neighborhoods as well as cell populations and genes relevant to disease risk, pathogenesis, and diagnostics. We discovered functional genetic variants influencing cell-type-specific gene expression, which were under-represented in non-Asian populations, and helped contextualize disease-associated variants. AIDA enables analyses of multi-ancestry disease datasets and facilitates the development of precision medicine efforts in Asia and beyond. © 2025 The Authors

关键词： eQTL genetic diversity genetics genomics healthy baseline human diversity immune cells precision medicine single-cell RNA sequencing sub-continental diversity

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AB1019 TREATMENT OF SYSTEMIC LUPUS ERYTHEMATOSUS: ANALYSIS OF TREATMENT PATTERNS IN ADULT AND PAEDIATRIC PATIENTS ACROSS FOUR EUROPEAN COUNTRIES

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Annals of the Rheumatic Diseases 2024年 83卷 1828-1828页

作者： F. Dernie M. Du M. Catala Sabate A. Delmestri W.Y. Man J. Brash H. Van Ballegooijen N. Mercadé-Besora T. Duarte-Salles M.A. Mayer A. Leis J.M. Ramirez-Anguita R. Griffier G. Verdy A. Prats-Uribe A. Pacurariu D. Morales R. De Lisa S. Galluzzo G. Egger E.H. Tan Pharmaco- and Device Epidemiology Centre for Statistics in Medicine Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences University of Oxford Oxford United Kingdom Medical Sciences Division University of Oxford Oxford United Kingdom IQVIA Real World Solutions Brighton United Kingdom IQVIA Solutions B.V Amsterdam Netherlands Fundació Institut Universitari per a la Recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol) Barcelona Spain Department of Medical Informatics Erasmus University Medical Center Rotterdam Netherlands Management and Control Department Hospital del Mar Barcelona Spain Department of Medicine and Life Sciences Universitat Pompeu Fabra Barcelona Spain Research Programme on Biomedical Informatics (GRIB) Hospital del Mar Research Institute (IMIM) Barcelona Spain University Hospital of Bordeaux Public Health Department Medical Information Service Medical Informatics and Archiving Unit (IAM) Bordeaux France Paediatric Medicines Office Scientific Evidence Generation Department European Medicines Agency Amsterdam Netherlands European Medicines Agency Amsterdam Netherlands Division of Population Health and Genomics University of Dundee Dundee United Kingdom Italian Medicine Agency (AIFA) Rome Italy

Background: Systemic lupus erythematosus (SLE) is a complex autoimmune disease with multiple treatment options recommended by clinical guidelines. Understanding treatment patterns among SLE patients is important for assessing treatment burden, the impact of clinical guidelines, and guiding medicinal product development. However, only limited data on treatment patterns exist in SLE, especially in paediatric-onset SLE. Objectives: To characterise adult and paediatric patients diagnosed with SLE at the time of diagnosis, and describe the patterns of medications used to treat their condition. Methods: We conducted a cohort study using five databases of routinely collected healthcare data from four European countries. Data sources include three primary or outpatient care databases [Clinical Practice research Datalink (CPRD) GOLD (UK), IQVIA Disease Analyzer (DA) Germany (DE), Sistema d’Informació per al Desenvolupament de la Investigació en Atenció Primària (SIDIAP) (ES)], and two hospital databases [Institut Municipal Assistència Sanitària Hospital del Mar Information System (IMASIS) (ES) and Clinical Data Warehouse of Bordeaux University Hospital (CDWBordeaux) (FR)]. We described the characteristics of adult and paediatric (<18 years) patients at time of SLE diagnosis, including age, sex, comorbidities, and concurrent medication use. We analysed the different medicines used, calculated the percentage of SLE patients commencing pre-specified SLE treatments in the first month and year after diagnosis, reported number of prescriptions, starting dose, cumulative dose, and duration of treatment for each of the treatments, and characterised which drugs were used as first-line or second-line treatments. Results: We included 11,255 patients with a first diagnosis of SLE for patient characterisation and 5,718 for our medicine utilisation analyses. Across all databases, the majority of adult SLE patients were female (80-88%), with median age of 49 to 54 years at diagnosis. In th

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programme for ocular inflammation & infection translational research (PROTON) registry: Cross-sectional analysis of baseline patient characteristics

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Asia-Pacific Journal of Ophthalmology 2025年

作者： Rojas-Carabali, William Chan, Kevin Cifuentes-Gonzalez, Carlos Agarwal, Manisha Sen, Alok Biswas, Jyotirmay Kharel La Distia Nora, Rina Utami, Anna Khatri, Anadi Mahendradas, Padmamalini Schlaen, Ariel Mishra, Chitaranjan Guex-Crosier, Yan Tsui, Edmund Ayachit, Apoorva Gangaputra, Sapna Kempen, John H. Gupta, Vishali de-la-Torre, Alejandra Lee, Bernett Agrawal, Rupesh Tan Tock Seng Hospital National Healthcare Group Singapore Lee Kong Chian School of Medicine Nanyang Technological University Singapore Programme for Ocular Inflammation & Infection Translational Research National Healthcare Group Singapore Neuroscience Research Group (NEUROS) Neurovitae Center for Neuroscience Institute of Translational Medicine (IMT) Escuela de Medicina y Ciencias de la Salud Universidad del Rosario Bogotá Colombia Dr Shroff's Charity Eye Hospital India SNC Eye Hospital Ranchi India Sankara Nethralaya Chennai India Department of Ophthalmology B. P. Koirala Lions Centre for Ophthalmic Studies Maharajgunj Medical Campus Institute of Medicine Tribhuvan University Maharajgunj Kathmandu Nepal Cipto Mangunkusumo Kirana Eye Hospital Jakarta Indonesia Jakarta Eye Centre Jakarta Indonesia Birat Eye Hospital Biratnagar Nepal Narayana Netralaya Bangalore India Hospital de Clinicas Jose de San Martín Universidad de Buenos Aires/Hospital Universitario Austral Buenos Aires Argentina Trilochan Netralaya Odisha India Jules-Gonin Eye Hospital University of Lausanne Lausanne Switzerland UCLA Stein Eye Institute Los Angeles California United States M M Joshi Eye Institute Karnataka India Vanderbilt Medical Center Vanderbilt University United States Department of Ophthalmology and Schepens Eye Research Institute Massachusetts Eye and Ear/ Harvard Medical School Boston United States Sight for Souls Bellevue WA United States Department of Ophthalmology Addis Ababa University Addis Ababa Ethiopia MyungSung Christian Medical Center (MCM) Eye Unit MCM Comprehensive Specialized Hospital Addis Ababa Ethiopia MyungSung Medical School Addis Ababa Ethiopia Advanced Eye Centre Post Graduate Institute of Medical Education & Research Chandigarh India Singapore Immunology Network (SIgN) Agency for Science Technology and Research (A⁎STAR) Singapore Centre for Biomedical Informatics Lee Kong Chian School of Medicine Nanyang Technological University Singapore Inf

Purpose: The programme for Ocular Inflammation & Infection Translational research (PROTON) registry collects real-world data on infectious and non-infectious ocular inflammatory diseases (OID) to enhance understanding of disease progression and treatment outcomes. This report presents the baseline characteristics of patients enrolled in two international multicentric studies, OASIS 1 and OASIS 2, over the first two years. Design: A cross-sectional observational study. Methods: PROTON is an observational ambispective cohort registry comprising OASIS 1, a retrospective study (2000–2021), and OASIS 2, a prospective study (2021 onwards). Data is collected at multiple intervals over a 10-year period, focusing on various OID. Participants include patients diagnosed with anterior uveitis, intermediate uveitis, posterior uveitis, panuveitis, scleritis, retinal vasculitis, and neuroretinitis. Baseline characteristics, ocular examinations, and treatment outcomes are recorded. Results: A total of 2640 patients (3642 eyes) have been recruited across 17 centers worldwide. Infectious was the most common etiology (31.6 %), followed by idiopathic (28.1 %), undetermined (21.7 %), and non-infectious (16.0 %). Most patients (54.8 %) were male, with anterior uveitis being the most common anatomical location (37.5 %). Visual impairment was present in 53.2 % of cases, with 18.8 % experiencing moderate (0.5–1.0 LogMAR) and 22.6 % severe impairment (>1.0 LogMAR). Tuberculosis (64.0 %) and toxoplasmosis (13.5 %) were the leading infectious causes, while HLA-B27-associated uveitis accounted for 19.4 % of non-infectious cases. Conclusions: The PROTON registry provides valuable insights into the global spectrum of OID, with a substantial representation of infectious causes. This real-world evidence highlights the key prevalence of visual impairment and underscores the importance of research on this topic. As the registry evolves, it will help refine clinical management strategies and improve p

关键词： Aetiology Clinical Registry Multicentric Uveitis Visual Impairment

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Polygenic risk modeling for prediction of epithelial ovarian cancer risk (vol 30, pg 349, 2021)

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EUROPEAN JOURNAL OF HUMAN GENETICS 2022年第5期30卷 630-631页

作者： Dareng, Eileen O. Tyrer, Jonathan P. Barnes, Daniel R. Jones, Michelle R. Yang, Xin Aben, Katja K. H. Adank, Muriel A. Agata, Simona Andrulis, Irene L. Anton-Culver, Hoda Antonenkova, Natalia N. Aravantinos, Gerasimos Arun, Banu K. Augustinsson, Annelie Balmana, Judith Bandera, Elisa V. Barkardottir, Rosa B. Barrowdale, Daniel Beckmann, Matthias W. Beeghly-Fadiel, Alicia Benitez, Javier Bermisheva, Marina Bernardini, Marcus Q. Bjorge, Line Black, Amanda Bogdanova, Natalia V. Bonanni, Bernardo Borg, Ake Brenton, James D. Budzilowska, Agnieszka Butzow, Ralf Buys, Saundra S. Cai, Hui Caligo, Maria A. Campbell, Ian Cannioto, Rikki Cassingham, Hayley Chang-Claude, Jenny Chanock, Stephen J. Chen, Kexin Chiew, Yoke-Eng Chung, Wendy K. Claes, Kathleen B. M. Colonna, Sarah Cook, Linda S. Couch, Fergus J. Daly, Mary B. Dao, Fanny Davies, Eleanor de la Hoya, Miguel de Putter, Robin Dennis, Joe DePersia, Allison Devilee, Peter Diez, Orland Ding, Yuan Chun Doherty, Jennifer A. Domchek, Susan M. Dork, Thilo du Bois, Andreas Durst, Matthias Eccles, Diana M. Eliassen, Heather A. Engel, Christoph Evans, Gareth D. Fasching, Peter A. Flanagan, James M. Fortner, Renee T. Machackova, Eva Friedman, Eitan Ganz, Patricia A. Garber, Judy Gensini, Francesca Giles, Graham G. Glendon, Gord Godwin, Andrew K. Goodman, Marc T. Greene, Mark H. Gronwald, Jacek Hahnen, Eric Haiman, Christopher A. Hakansson, Niclas Hamann, Ute Hansen, Thomas V. O. Harris, Holly R. Hartman, Mikael Heitz, Florian Hildebrandt, Michelle A. T. Hogdall, Estrid Hogdall, Claus K. Hopper, John L. Huang, Ruea-Yea Huff, Chad Hulick, Peter J. Huntsman, David G. Imyanitov, Evgeny N. Isaacs, Claudine Jakubowska, Anna James, Paul A. Janavicius, Ramunas Jensen, Allan Johannsson, Oskar Th. John, Esther M. Jones, Michael E. Kang, Daehee Karlan, Beth Y. Karnezis, Anthony Kelemen, Linda E. Khusnutdinova, Elza Kiemeney, Lambertus A. Kim, Byoung-Gie Kjaer, Susanne K. Komenaka, Ian Kupryjanczyk, Jolanta Kurian, Allison W. Kwong, Ava Lambrechts, Diether Larson, Melissa C. Lazaro, Conxi L 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 Epidemiology Department

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.

关键词： Clinical genetics Genetic markers Risk factors Biomedicine general Human Genetics Bioinformatics Gene Expression Cytogenetics

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Correction: Use of Health Apps by Nurses for Professional Purposes: Web-Based Survey Study

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JMIR mHealth and uHealth 2020年第4期8卷 e18516页

作者： Miguel Angel Mayer Octavi Rodríguez Blanco Antonio Torrejon Research Programme on Biomedical Informatics. Hospital del Mar Medical Research Institute Universitat Pompeu Fabra Barcelona Spain. Col·legi Oficial d'Infermeres i Infermers de Barcelona Barcelona Spain.

[This corrects the article DOI: 10.2196/15195.].

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Comprehensive functional annotation of susceptibility variants identifies genetic heterogeneity between lung adenocarcinoma and squamous cell carcinoma

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Frontiers of Medicine 2021年第2期15卷 275-291页

作者： Na Qin Yuancheng Li Cheng Wang Meng Zhu Juncheng Dai Tongtong Hong Demetrius Albanes Stephen Lam Adonina Tardon Chu Chen Gary Goodman Stig EBojesen Maria Teresa Landi Mattias Johansson Angela Risch H-Erich Wichmann Heike Bickeboller Gadi Rennert Susanne Arnold Paul Brennan John KField Sanjay Shete Loic Le Marchand Olle Melander Hans Brunnstrom Geoffrey Liu Rayjean JHung Angeline Andrew Lambertus AKiemeney Shan Zienolddiny Kjell Grankvist Mikael Johansson Neil Caporaso Penella Woll Philip Lazarus Matthew BSchabath Melinda CAldrich Victoria LStevens Guangfu Jin David CChristiani Zhibin Hu Christopher IAmos Hongxia Ma Hongbing Shen Department of Epidemiology Center for Global HealthSchool of Public HealthNanjing Medical UniversityNanjing 211166China State Key Laboratory of Reproductive Medicine Center for Global HealthNanjing Medical UniversityNanjing 211166China Department of Bioinformatics School of Biomedical Engineering and InformaticsNanjing Medical UniversityNanjing 211166China Jiangsu Key Lab of Cancer Biomarkers Prevention and TreatmentCollaborative Innovation Center for Cancer MedicineNanjing Medical UniversityNanjing 211166China China International Cooperation Center for Environment and Human Health School of Public HealthNanjing Medical UniversityNanjing 211166China Division of Cancer Epidemiology and Genetics National Cancer InstituteBethesdaMD 20892-9304USA Department of Integrative Oncology British Columbia Cancer AgencyVancouverBC V5Z 1L3Canada Faculty of Medicine University of Oviedo and CIBERESPOviedo 33006Spain Program in Epidemiology Public Health Sciences DivisionFred Hutchinson Cancer Research CenterSeattleWA 98109-1024USA Public Health Sciences Division Swedish Cancer InstituteSeattleWA 98026USA Department of Clinical Biochemistry Copenhagen University HospitalCopenhagen DK-1017Denmark National Cancer Institute BethesdaMD 20892-9304USA Genetic Epidemiology Group International Agency for Research on CancerLyon 69372France Cancer Center Cluster Salzburg at PLUS Department of Molecular BiologyUniversity of SalzburgHeidelberg 5020Austria Institute of Medical Informatics Biometry and EpidemiologyChair of EpidemiologyLudwig Maximilians UniversityMunichBavaria 80539Germany Department of Genetic Epidemiology University Medical Center GoettingenGoettingen 37075Germany Technion Faculty of Medicine Carmel Medical CenterHaifa 3448516Israel Markey Cancer Center University of KentuckyLexingtonKY 40506-0054USA Department of Molecular and Clinical Cancer Medicine Roy Castle Lung Cancer Research ProgrammeThe University of Liverpool Institute of Translational MedicineLiverpool L697Z

Although genome-wide association studies have identified more than eighty genetic variants associated with non-small cell lung cancer(NSCLC)risk,biological mechanisms of these variants remain largely *** integrating a large-scale genotype data of 15581 lung adenocarcinoma(AD)cases,8350 squamous cell carcinoma(SqCC)cases,and 27355 controls,as well as multiple transcriptome and epigenomic databases,we conducted histology-specific meta-analyses and functional annotations of both reported and novel susceptibility *** identified 3064 credible risk variants for NSCLC,which were overrepresented in enhancer-like and promoter-like histone modification peaks as well as DNase I hypersensitive *** factor enrichment analysis revealed that USF1 was AD-specific while CREB1 was *** annotation and genebased analysis implicated 894 target genes,including 274 specifics for AD and 123 for SqCC,which were overrepresented in somatic driver genes(ER=1.95,P=0.005).Pathway enrichment analysis and Gene-Set Enrichment Analysis revealed that AD genes were primarily involved in immune-related pathways,while SqCC genes were homologous recombination deficiency *** results illustrate the molecular basis of both wellstudied and new susceptibility loci of NSCLC,providing not only novel insights into the genetic heterogeneity between AD and SqCC but also a set of plausible gene targets for post-GWAS functional experiments.

关键词： lung cancer genome-wide association study function annotation immune homologous recombination repair deficiency genetic heterogeneity

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