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

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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

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Publisher Correction: Age at onset as stratifier in idiopathic Parkinson's disease - effect of ageing and polygenic risk score on clinical phenotypes

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NPJ Parkinson's disease 2022年第1期8卷 112页

作者： L Pavelka A Rauschenberger Z Landoulsi S Pachchek P May E Glaab R Krüger Clinical and Experimental Neuroscience Luxembourg Centre for Systems Biomedicine (LCSB) University of Luxembourg Esch-sur-Alzette Luxembourg. lukas.pavelka@uni.lu. Parkinson's Research Clinic Centre Hospitalier de Luxembourg (CHL) Luxembourg Luxembourg. lukas.pavelka@uni.lu. Biomedical Data Science Group Luxembourg Centre for Systems Biomedicine (LCSB) University of Luxembourg Esch-sur-Alzette Luxembourg. Bioinformatics Core Luxembourg Centre for Systems Biomedicine (LCSB) Esch-sur-Alzette Luxembourg. Clinical and Experimental Neuroscience Luxembourg Centre for Systems Biomedicine (LCSB) University of Luxembourg Esch-sur-Alzette Luxembourg. Clinical and Experimental Neuroscience Luxembourg Centre for Systems Biomedicine (LCSB) University of Luxembourg Esch-sur-Alzette Luxembourg. rejko.krueger@uni.lu. Parkinson's Research Clinic Centre Hospitalier de Luxembourg (CHL) Luxembourg Luxembourg. rejko.krueger@uni.lu. Transversal Translational Medicine Luxembourg Institute of Health (LIH) Strassen Luxembourg. rejko.krueger@uni.lu.

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Author Correction: Multidisciplinary study of the secondary immune response in grandparents re-exposed to chickenpox

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Scientific reports 2018年第1期8卷 10824页

作者： B Ogunjimi J Van den Bergh P Meysman S Heynderickx K Bergs H Jansens E Leuridan A Vorsters H Goossens K Laukens N Cools Viggo Van Tendeloo N Hens P Van Damme Evelien Smits Ph Beutels Centre for Health Economics Research & Modeling Infectious Diseases (CHERMID) Vaccine & Infectious Disease Institute (VAXINFECTIO) University of Antwerp Antwerp Belgium. benson.ogunjimi@uantwerp.be. Interuniversity Institute for Biostatistics and Statistical Bioinformatics Hasselt University Hasselt Belgium. benson.ogunjimi@uantwerp.be. Department of Pediatrics Antwerp University Hospital Edegem Belgium. benson.ogunjimi@uantwerp.be. Laboratory of Experimental Hematology (LEH) Vaccine & Infectious Disease Institute (VAXINFECTIO) University of Antwerp Antwerp Belgium. benson.ogunjimi@uantwerp.be. Department of Pediatrics Ghent University Hospital Ghent Belgium. benson.ogunjimi@uantwerp.be. Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS) Antwerp Belgium. benson.ogunjimi@uantwerp.be. Laboratory of Experimental Hematology (LEH) Vaccine & Infectious Disease Institute (VAXINFECTIO) University of Antwerp Antwerp Belgium. Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS) Antwerp Belgium. Advanced Database Research and Modelling (ADReM) Department of Mathematics and Computer Science University of Antwerp Antwerp Belgium. Biomedical Informatics Research Network Antwerp (BIOMINA) University of Antwerp/Antwerp University Hospital Edegem Belgium. Center for Cell Therapy and Regenerative Medicine Antwerp University Hospital Edegem Belgium. Department of Laboratory Medicine Antwerp University Hospital Edegem Belgium. Centre for the Evaluation of Vaccination (CEV) Vaccine & Infectious Disease Institute (VAXINFECTIO) University of Antwerp Antwerp Belgium. Laboratory of Medical Microbiology Vaccine & Infectious Disease Institute (VAXINFECTIO) University of Antwerp Antwerp Belgium. Centre for Health Economics Research & Modeling Infectious Diseases (CHERMID) Vaccine & Infectious Disease Institute (VAXINFECTIO) University of Antwerp Antwerp Belgium. Interuniversity Institute for Biostatistics and Statistical Bio

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

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Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits (vol 50, pg 1412, 2018)

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NATURE GENETICS 2018年第12期50卷 1755-1755页

作者： Evangelou, Evangelos Warren, Helen R. Mosen-Ansorena, David Mifsud, Borbala Pazoki, Raha Gao, He Ntritsos, Georgios Dimou, Niki Cabrera, Claudia P. Karaman, Ibrahim Fu Liang Ng Evangelou, Marina Witkowska, Katarzyna Tzanis, Evan Hellwege, Jacklyn N. Giri, Ayush Edwards, Digna R. Velez Sun, Yan V. Cho, Kelly Gaziano, J. Michael Wilson, Peter W. F. Tsao, Philip S. Kovesdy, Csaba P. Esko, Tonu Magi, Reedik Milani, Lili Almgren, Peter Boutin, Thibaud Debette, Stephanie Ding, Jun Giulianini, Franco Holliday, Elizabeth G. Jackson, Anne U. Li-Gao, Ruifang Lin, Wei-Yu Luan, Jian'an Mangino, Massimo Oldmeadow, Christopher Prins, Bram Peter Qian, Yong Sargurupremraj, Muralidharan Shah, Nabi Surendran, Praveen Theriault, Sebastien Verweij, Niek Willems, Sara M. Zhao, Jing-Hua Amouyel, Philippe Connell, John de Mutsert, Renee Doney, Alex S. F. Farrall, Martin Menni, Cristina Morris, Andrew D. Noordam, Raymond Pare, Guillaume Poulter, Neil R. Shields, Denis C. Stanton, Alice Thom, Simon Abecasis, Goncalo Amin, Najaf Arking, Dan E. Ayers, Kristin L. Barbieri, Caterina M. Batini, Chiara Bis, Joshua C. Blake, Tineka Bochud, Murielle Boehnke, Michael Boerwinkle, Eric Boomsma, Dorret I. Bottinger, Erwin P. Braund, Peter S. Brumat, Marco Campbell, Archie Campbell, Harry Chakravarti, Aravinda Chambers, John C. Chauhan, Ganesh Ciullo, Marina Cocca, Massimiliano Collins, Francis Cordell, Heather J. Davies, Gail de Borst, Martin H. de Geus, Eco J. Deary, Ian J. Deelen, Joris Del Greco, Fabiola M. Demirkale, Cumhur Yusuf Dorr, Marcus Ehret, Georg B. Elosua, Roberto Enroth, Stefan Erzurumluoglu, A. Mesut Ferreira, Teresa Franberg, Mattias Franco, Oscar H. Gandin, Ilaria Gasparini, Paolo Giedraitis, Vilmantas Gieger, Christian Girotto, Giorgia Goel, Anuj Gow, Alan J. Gudnason, Vilmundur Guo, Xiuqing Gyllensten, Ulf Hamsten, Anders Harris, Tamara B. Harris, Sarah E. Hartman, Catharina A. Havulinna, Aki S. Hicks, Andrew A. Hofer, Edith Hofman, Albert Hottenga, Jouke-Jan Huffman, Jennifer E. Hwang, Shih-Jen Ingelsson, Erik James, Alan Jansen Department of Epidemiology and Biostatistics Imperial College London London UK Department of Hygiene and Epidemiology University of Ioannina Medical School Ioannina Greece William Harvey Research Institute Barts and The London School of Medicine and Dentistry Queen Mary University of London London UK National Institute for Health Research Barts Cardiovascular Biomedical Research Center Queen Mary University of London London UK MRC-PHE Centre for Environment and Health Imperial College London London UK Department of Mathematics Imperial College London London UK Division of Epidemiology Department of Medicine Institute for Medicine and Public Health Vanderbilt Genetics Institute Vanderbilt University Medical Center Tennessee Valley Healthcare System (626)/Vanderbilt University Nashville TN USA Vanderbilt Genetics Institute Vanderbilt Epidemiology Center Department of Obstetrics and Gynecology Vanderbilt University Medical Center Tennessee Valley Health Systems VA Nashville TN USA Department of Epidemiology Emory University Rollins School of Public Health Atlanta GA USA Department of Biomedical Informatics Emory University School of Medicine Atlanta GA USA Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) VA Boston Healthcare System Boston MA USA Division of Aging Department of Medicine Brigham and Women’s Hospital Department of Medicine Harvard Medical School Boston MA USA Atlanta VAMC and Emory Clinical Cardiovascular Research Institute Atlanta GA USA VA Palo Alto Health Care System Division of Cardiovascular Medicine Stanford University School of Medicine Stanford CA USA Nephrology Section Memphis VA Medical Center and University of Tennessee Health Science Center Memphis TN USA Estonian Genome Center University of Tartu Tartu Estonia Program in Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA Department Clinical Sciences Malmö Lund University Malmö Sweden MRC Human Genetics Un

High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.

关键词： Cardiovascular diseases Genome informatics Genome-wide association studies

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33P Immune analysis of lymph nodes in relation to the presence or absence of tumour infiltrating lymphocytes in triple negative breast cancers

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Annals of Oncology 2020年 31卷 S27-S27页

作者： A. Quintana V. Peg T. Moline A. Prat L. Paré P. Galván G. Villacampa R. Dientsmann J. Perez E. Muñoz M. Martí J. Blanco-Heredia C. Dos Anjos M. Vazquez L. de Mattos J. Cortés Breast Cancer Unit Vall d'Hebron University Hospital Barcelona Spain Pathology Department Vall d'Hebron University Hospital Universidad Autónoma de Barcelona Spanish Biomedical Research Network Centre in Oncology (CIBERONC) (Madrid) Barcelona Spain Pathology Department Vall d'Hebron University Hospital Barcelona Spain Medical Oncology Department Hospital Clinic y Provincial de Barcelona Translational Genomics and Targeted Therapeutics Group (IDIBAPS) Barcelona Spain Translational Genomics and Targeted Therapeutics Group Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) Barcelona Spain Oncology Data Science (ODysSey Group) Vall d'Hebron University Hospital Barcelona Spain Medical Oncology Department IOB Institute of Oncology Quironsalud Group Barcelona Spain Medical Oncology Department Vall d'Hebron University Hospital Barcelona Spain Cell Immunology Laboratory Universidad Autónoma de Barcelona Bellaterra Spain IrsiCaixa Hospital Universitari Trias i Pujol Badalona Spain Genome Bioinformatics Barcelona Supercomputing Center Barcelona Spain Vall d'Hebron Institute of Oncology (VHIO) IOB Institute of Oncology Madrid & Barcelona Quironsalud Group Barcelona Spain

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Building a precision medicine infrastructure at a national level: The Swedish experience

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Cambridge prisms. Precision medicine 2023年 1卷 e15页

作者： Anders Edsjö Anna Lindstrand David Gisselsson Paula Mölling Mikaela Friedman Lucia Cavelier Maria Johansson Hans Ehrencrona Therese Fagerqvist Tobias Strid Lovisa Lovmar Bo Jacobsson Åsa Johansson Lars Engstrand Craig E Wheelock Per Sikora Valtteri Wirta Thoas Fioretos Richard Rosenquist Department of Clinical Genetics Pathology and Molecular Diagnostics Office for Medical Services Region Skåne Lund Sweden. Division of Pathology Department of Clinical Sciences Lund University Lund Sweden. Department of Molecular Medicine and Surgery Karolinska Institutet Stockholm Sweden. Clinical Genetics Karolinska University Hospital Solna Sweden. Genomic Medicine Center Karolinska Karolinska University Hospital Stockholm Sweden. Division of Clinical Genetics Department of Laboratory Medicine Lund University Lund Sweden. Department of Laboratory Medicine Faculty of Medicine and Health Örebro University Örebro Sweden. Lund University Collaboration Office Lund University Lund Sweden. Innovation Partnership Office Uppsala University Uppsala Sweden. Department of Clinical Pathology Biological and Clinical Sciences Linköping University Linköping Sweden. Clinical Genomics Linköping Linköping University Linköping Sweden. Department of Clinical Genetics and Genomics Sahlgrenska University Hospital Gothenburg Sweden. Department of Obstetrics and Gynecology Sahlgrenska Academy Gothenburg University Gothenburg Sweden. Department of Obstetrics and Gynecology Sahlgrenska University Hospital Gothenburg Sweden. Department of Immunology Genetics and Pathology Science for Life Laboratory Uppsala University Uppsala Sweden. Department of Microbiology Tumor and Cell Biology Centre for Translational Microbiome Research Karolinska Institutet Solna Sweden. Unit of Integrative Metabolomics Institute of Environmental Medicine Karolinska Institutet Stockholm Sweden. Department of Respiratory Medicine and Allergy Karolinska University Hospital Stockholm Sweden. Clinical Genomics Gothenburg Science for Life Laboratory University of Gothenburg Gothenburg Sweden. Bioinformatics Data Center Core Facilities Sahlgrenska Academy University of Gothenburg Gothenburg Sweden. Department of Microbiology Tumor and Cell Biology Clinical Genomics Stockholm Science Life Labor

Precision medicine has the potential to transform healthcare by moving from one-size-fits-all to personalised treatment and care. This transition has been greatly facilitated through new high-throughput sequencing technologies that can provide the unique molecular profile of each individual patient, along with the rapid development of targeted therapies directed to the Achilles heels of each disease. To implement precision medicine approaches in healthcare, many countries have adopted national strategies and initiated genomic/precision medicine initiatives to provide equal access to all citizens. In other countries, such as Sweden, this has proven more difficult due to regionally organised healthcare. Using a bottom-up approach, key stakeholders from academia, healthcare, industry and patient organisations joined forces and formed Genomic Medicine Sweden (GMS), a national infrastructure for the implementation of precision medicine across the country. To achieve this, Genomic Medicine Centres have been established to provide regionally distributed genomic services, and a national informatics infrastructure has been built to allow secure data handling and sharing. GMS has a broad scope focusing on rare diseases, cancer, pharmacogenomics, infectious diseases and complex diseases, while also providing expertise in informatics, ethical and legal issues, health economy, industry collaboration and education. In this review, we summarise our experience in building a national infrastructure for precision medicine. We also provide key examples how precision medicine already has been successfully implemented within our focus areas. Finally, we bring up challenges and opportunities associated with precision medicine implementation, the importance of international collaboration, as well as the future perspective in the field of precision medicine.

关键词： genomic medicine implementation national infrastructure precision medicine

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A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer's disease (Sep, 10.1038/s41588-021-00921-z, 2021)

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NATURE GENETICS 2022年第7期54卷 1062-1062页

作者： Wightman, Douglas P. Jansen, Iris E. Savage, Jeanne E. Shadrin, Alexey A. Bahrami, Shahram Holland, Dominic Rongve, Arvid Borte, Sigrid Winsvold, Bendik S. Drange, Ole Kristian Martinsen, Amy E. Skogholt, Anne Heidi Willer, Cristen Brathen, Geir Bosnes, Ingunn Nielsen, Jonas Bille Fritsche, Lars G. Thomas, Laurent F. Pedersen, Linda M. Gabrielsen, Maiken E. Johnsen, Marianne Bakke Meisingset, Tore Wergeland Zhou, Wei Proitsi, Petroula Hodges, Angela Dobson, Richard Velayudhan, Latha Heilbron, Karl Auton, Adam Sealock, Julia M. Davis, Lea K. Pedersen, Nancy L. Reynolds, Chandra A. Karlsson, Ida K. Magnusson, Sigurdur Stefansson, Hreinn Thordardottir, Steinunn Jonsson, Palmi V. Snaedal, Jon Zettergren, Anna Skoog, Ingmar Kern, Silke Waern, Margda Zetterberg, Henrik Blennow, Kaj Stordal, Eystein Hveem, Kristian Zwart, John-Anker Athanasiu, Lavinia Selnes, Per Saltvedt, Ingvild Sando, Sigrid B. Ulstein, Ingun Djurovic, Srdjan Fladby, Tormod Aarsland, Dag Selbaek, Geir Ripke, Stephan Stefansson, Kari Andreassen, Ole A. Posthuma, Danielle Department of Complex Trait Genetics Center for Neurogenomics and Cognitive Research Amsterdam Neuroscience VU Amsterdam Amsterdam the Netherlands Department of Child and Adolescent Psychiatry and Pediatric Psychology Section Complex Trait Genetics Amsterdam Neuroscience Vrije Universiteit Medical Center Amsterdam University Medical Center Amsterdam the Netherlands NORMENT Centre University of Oslo Oslo Norway Institute of Clinical Medicine University of Oslo Oslo Norway Division of Mental Health and Addiction Oslo University Hospital Oslo Norway Research and Communication Unit for Musculoskeletal Health (FORMI) Department of Research Innovation and Education Division of Clinical Neuroscience Oslo University Hospital Oslo Norway K. G. Jebsen Center for Genetic Epidemiology Department of Public Health and Nursing Faculty of Medicine and Health Sciences Norwegian University of Science and Technology Trondheim Norway Department of Research Innovation and Education Division of Clinical Neuroscience Oslo University Hospital Oslo Norway Department of Neurology Akershus University Hospital Lørenskog Norway Department of Geriatric Medicine Oslo University Hospital Oslo Norway Norwegian National Advisory Unit on Ageing and Health Vestfold Hospital Trust Tønsberg Norway Department of Neurosciences University of California San Diego La Jolla CA USA Department of Research and Innovation Helse Fonna Haugesund Hospital Haugesund Norway The University of Bergen Institute of Clinical Medicine (K1) Bergen Norway Department of Neurology Oslo University Hospital Oslo Norway Department of Clinical and Molecular Medicine Norwegian University of Science and Technology Trondheim Norway Department of Internal Medicine Division of Cardiovascular Medicine University of Michigan Ann Arbor MI USA Department of Epidemiology Research Statens Serum Institut Copenhagen Denmark HUNT Research Center Department of Public Health and Nursing Faculty of Medicine and Health Scien

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The risk of herpes zoster is positively associated with obesity, especially morbid obesity

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Scientific reports 2024年第1期14卷 14330页

作者： Hsiao-Lan Chen Chia-Hung Chen Wen-Che Hsieh Yu-Han Huang Tzu-Ju Hsu Fuu-Jen Tsai Yung-Chi Cheng Chao-Yu Hsu Division of Respiratory Therapy Ditmanson Medical Foundation Chia-Yi Christian Hospital Chia-Yi Taiwan. Department of Medical Education Ditmanson Medical Foundation Chia-Yi Christian Hospital Chia-Yi Taiwan. Department of Medical Imaging Ditmanson Medical Foundation Chia-Yi Christian Hospital Chia-Yi Taiwan. Department of Chinese Medicine Ditmanson Medical Foundation Chia-Yi Christian Hospital Chia-Yi Taiwan. Management Office for Health Data Clinical Trial Research Center China Medical University Hospital Taichung Taiwan. School of Chinese Medicine College of Chinese Medicine China Medical University Taichung Taiwan. Department of Medical Research China Medical University Hospital Taichung Taiwan. Division of Medical Genetics China Medical University Children's Hospital Taichung Taiwan. Department of Biotechnology and Bioinformatics Asia University Taichung Taiwan. Department of Rehabilitation Ditmanson Medical Foundation Chia-Yi Christian Hospital Chia-Yi Taiwan. Department of Medical Education Ditmanson Medical Foundation Chia-Yi Christian Hospital Chia-Yi Taiwan. 07692@cych.org.tw. Department of Artificial Intelligence and Healthcare Management Central Taiwan University of Science and Technology Taichung Taiwan. 07692@cych.org.tw. Center for General Education National Taichung University of Science and Technology Taichung Taiwan. 07692@cych.org.tw. Department of General Education National Chin-Yi University of Technology Taichung Taiwan. 07692@cych.org.tw.

This study aimed to investigate the association between obesity and herpes zoster (HZ) occurrence. This study used data covering 2 million people in Taiwan in 2000, which were obtained from the National Health Insurance Research database. The cohort study observed aged 20-100 years with obesity from 2000 to 2017 (tracking to 2018). Obesity was indicated by the presence of two or more outpatient diagnoses or at least one admission record. And, obesity was categorized into non-morbid obesity and morbid obesity. Patients with HZ before the index date were excluded. The obesity cohort and control cohort were matched 1:1 according to age, sex, comorbidities, and index year. There were 18,855 patients in both the obesity and control cohorts. The obesity cohort [adjusted hazard ratio (aHR) 1.09] had a higher risk of HZ than the control cohort. Further analysis, the morbid obesity group (aHR 1.47), had a significantly higher risk of HZ than the non-morbid obesity group. Among the patients without any comorbidities, the patients with obesity had a significantly higher risk of developing HZ than the patients without obesity (aHR 1.18). Obese patients are at a higher risk of HZ development, especially in the patients with morbid obesity. Weight reduction is critical for preventing the onset of chronic diseases and decreasing the risk of HZ in patients with obesity.

关键词： Herpes zoster Morbid obesity Obesity Weight reduction

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PO005LBA/#1579 A randomized, phase II/III study of pegylated-liposomal-doxorubicin and atezolizumab (IND #134427) versus pegylated-liposomal-doxorubicin, bevacizumab and atezolizumab versus pegylated-liposomal-doxorubicin and bevacizumab in platinum-resistant ovarian cancer (NRG-GY009)

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International Journal of Gynecological Cancer 2023年 33卷 A4-A4页

作者： Roisin O’Cearbhaill Michael Sill H.o.a. Duong Steven Waggoner Rachel Grisham Floor Backes Robert Mannel Janos Tanyi Matthew Powell Cara Mathews Sharad Ghamande Leah Mcnally Alexander Olawaiye David Bender Linda Duska Heather Lankes Dmitriy Zamarin Russell Schilder Michael Bookman Carol Aghajanian Memorial Sloan Kettering Cancer Center Weill Cornell Medical College Medicine New York USA NRG Oncology Statistics and Data Management Center Biostatistics and Bioinformatics Department Buffalo USA Kaiser-Permanente Sacramento Hematology/oncology Sacramento USA CWRU Case Comprehensive Cancer Center Gynecologic Oncology Cleveland USA Ohio State University Comprehensive Cancer Center Gynecologic Oncology Ohio USA University of Oklahoma Health Sciences Center Obstetrics and Gynecology Oklahoma USA University of Pennsylvania/Abramson Cancer Center Obstetrics and Gynecology Philadelphia USA Washington University Gynecologic Oncology St. Louis USA Women and Infants Hospital Obstetrics and Gynecology Providence USA Georgia Cares Minority Underserved NCORP Gynecologic Oncology Augusta USA Duke Cancer Institute Gynecologic Oncology Durham USA UPMC Hillman Cancer Center Gynecologic Oncology Pittsburgh USA University of Iowa Obstetrics and Gynecology Iowa City USA University of Virginia Cancer Center Gynecologic Oncology Charlottesville USA NRG Oncology Biospecimen Bank-Columbus Translational Science Operations Columbus USA Icahn School of Medicine at Mount Sinai Hematology/oncology New York USA Thomas Jefferson University Gynecologic Medical Oncology Philadelphia USA Kaiser Permanente Northern California Gynecologic Oncology San Francisco USA

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Exposure-associated DNA methylation among people exposed to multiple industrial pollutants

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Clinical epigenetics 2024年第1期16卷 111页

作者： Chi-Hsin Sally Chen Tzu-Hsuen Yuan Tzu-Pin Lu Hsin-Ying Lee Yi-Hsuen Chen Liang-Chuan Lai Mong-Hsun Tsai Eric Y Chuang Chang-Chuan Chan Institute of Environmental and Occupational Health Sciences College of Public Health National Taiwan University Taipei Taiwan. Department of Health and Welfare College of City Management University of Taipei Taipei Taiwan. Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei Taiwan. Institute of Health Data Analytics and Statistics College of Public Health National Taiwan University Taipei Taiwan. Graduate Institute of Physiology College of Medicine National Taiwan University Taipei Taiwan. Institute of Biotechnology College of Bio-Resources and Agriculture National Taiwan University Taipei Taiwan. Department of Electrical Engineering College of Electrical Engineering and Computer Science National Taiwan University Taipei Taiwan. chuangey@ntu.edu.tw. Biomedical Technology and Device Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan. chuangey@ntu.edu.tw. Research and Development Center for Medical Devices National Taiwan University Taipei Taiwan. chuangey@ntu.edu.tw. Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan. chuangey@ntu.edu.tw. Institute of Environmental and Occupational Health Sciences College of Public Health National Taiwan University Taipei Taiwan. ccchan@ntu.edu.tw.

BACKGROUND:Current research on the epigenetic repercussions of exposure to a combination of pollutants is limited. This study aims to discern DNA methylation probes associated with exposure to multiple pollutants, serving as early effect markers, and single-nucleotide polymorphisms (SNPs) as surrogate indicators for population susceptibility. The investigation involved the analysis of urine exposure biomarkers for 11 heavy metals (vanadium, arsenic, mercury, cadmium, chromium, nickel, lead, manganese, copper, strontium, thallium), polycyclic aromatic hydrocarbon (PAHs) (1-hydroxypyrene), genome-wide DNA methylation sequencing, and SNPs array on all study participants. The data were integrated with metabolomics information and analyzed both at a community level based on proximity to home addresses relative to the complex and at an individual level based on exposure biomarker concentrations. RESULTS:On a community level, 67 exposure-related CpG probes were identified, while 70 CpG probes were associated with urine arsenic concentration, 2 with mercury, and 46 with vanadium on an individual level. These probes were annotated to genes implicated in cancers and chronic kidney disease. Weighted quantile sum regression analysis revealed that vanadium, mercury, and 1-hydroxypyrene contributed the most to cg08238319 hypomethylation. cg08238319 is annotated to the aryl hydrocarbon receptor repressor (AHRR) gene, and AHRR hypomethylation was correlated with an elevated risk of lung cancer. AHRR was further linked to deregulations in phenylalanine metabolism, alanine, aspartate, and glutamate metabolism, along with heightened oxidative stress. Additionally, three SNPs (rs11085020, rs199442, and rs10947050) corresponding to exposure-related CpG probes exhibited significant interaction effects with multiple heavy metals and PAHs exposure, and have been implicated in cancer progression and respiratory diseases. CONCLUSION:Our findings underscore the pivotal role of AHRR methylatio

关键词： DNA methylation Gene-environment interaction Heavy metals PAHs Petrochemical industry SNPs

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