DOCSLIB.ORG

Genetic Analysis of Over 1 Million People Identifies 535 New Loci Associated with Blood Pressure Traits

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Genetic Analysis of Over 1 Million People Identifies 535 New Loci Associated with Blood Pressure Traits Evangelou, E. et al. (2018) Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. Nature Genetics, 50, pp. 1412-1425. (doi:10.1038/s41588-018-0205-x) This is the author’s final accepted version. There may be differences between this version and the published version. You are advised to consult the publisher’s version if you wish to cite from it. http://eprints.gla.ac.uk/169952/ Deposited on: 17 April 2018 Enlighten – Research publications by members of the University of Glasgow http://eprints.gla.ac.uk 1 Genetic analysis of over one million people identifies 535 novel loci for blood pressure. 2 Short title: Blood pressure GWAS in one million people 3 Evangelos Evangelou1,2*, Helen R Warren3,4*, David Mosen-Ansorena1*, Borbala Mifsud3*, Raha 4 Pazoki1*, He Gao1,5*, Georgios Ntritsos2*, Niki Dimou2*, Claudia P Cabrera3,4, Ibrahim Karaman1, 5 Fu Liang Ng3, Marina Evangelou1,6, Katarzyna Witkowska3, Evan Tzanis3, Jacklyn N Hellwege7 , 6 Ayush Giri8, Digna R Velez-Edwards8, Yan V Sun9,10,Kelly Cho11,12, J.Michael Gaziano11,12, Peter 7 WF Wilson13, Philip S Tsao14, Csaba P Kovesdy15, Tonu Esko16,17, Reedik Mägi16, Lili Milani16, 8 Peter Almgren18, Thibaud Boutin19, Stéphanie Debette20,21, Jun Ding22, Franco Giulianini23, 9 Elizabeth G Holliday24, Anne U Jackson25, Ruifang Li-Gao26, Wei-Yu Lin27, Jian'an Luan28, Massimo 10 Mangino29,30, Christopher Oldmeadow24, Bram Prins31, Yong Qian22, Muralidharan 11 Sargurupremraj21, Nabi Shah32,33, Praveen Surendran27, Sébastien Thériault34,35, Niek 12 Verweij17,36,37, Sara M Willems28, Jing-Hua Zhao28, Philippe Amouyel38, John Connell39, Renée de 13 Mutsert26, Alex SF Doney32, Martin Farrall40,41, Cristina Menni29, Andrew D Morris42, Raymond 14 Noordam43, Guillaume Paré34, Neil R Poulter44, Denis C Shields45, Alice Stanton46, Simon Thom44, 15 Gonçalo Abecasis47, Najaf Amin48, Dan E Arking49, Kristin L Ayers50, Caterina M Barbieri51,52, 16 Chiara Batini53, Joshua C Bis54, Tineka Blake53, Murielle Bochud55, Michael Boehnke25, Eric 17 Boerwinkle56, Dorret I Boomsma57, Erwin P Bottinger58, Peter S Braund59,60, Marco Brumat61, 18 Archie Campbell62,63, Harry Campbell64, Aravinda Chakravarti49, John C Chambers1,5,65-67, Ganesh 19 Chauhan68, Marina Ciullo69,70, Massimiliano Cocca52, Francis Collins71, Heather J Cordell72, Gail 20 Davies73,74, Martin H de Borst75, Eco J de Geus57, Ian J Deary73,74, Joris Deelen76, Fabiola Del Greco 21 M77, Cumhur Yusuf Demirkale78, Marcus Dörr79,80, Georg B Ehret49,81, Roberto Elosua82, Stefan 22 Enroth83, A Mesut Erzurumluoglu53, Teresa Ferreira84, Mattias Frånberg85-87, Oscar H Franco88, 23 Ilaria Gandin61, Paolo Gasparini61,89, Vilmantas Giedraitis90, Christian Gieger91-93, Giorgia 24 Girotto61,94, Anuj Goel40,41, Alan J Gow73,95, Vilmundur Gudnason96,97, Xiuqing Guo98, Ulf 25 Gyllensten83, Anders Hamsten85,86, Tamara B Harris99, Sarah E Harris62,73, Catharina A 26 Hartman100, Aki S Havulinna101,102, Andrew A Hicks77, Edith Hofer103,104, Albert Hofman88,105, 27 Jouke-Jan Hottenga57, Jennifer E Huffman19, Shih-Jen Hwang106,107, Erik Ingelsson108,109, Alan 28 James110,111, Rick Jansen112, Marjo-Riitta Jarvelin5,113-115, Roby Joehanes116,117, Åsa Johansson83, 29 Andrew D Johnson117,118, Peter K Joshi64, Pekka Jousilahti101, J Wouter Jukema119, Antti Jula101, 30 Mika Kähönen120,121, Sekar Kathiresan17,36,122, Bernard D Keavney123,124, Kay-Tee Khaw125, Paul 31 Knekt101, Joanne Knight126, Ivana Kolcic127, Jaspal S Kooner5,66,67,128, Seppo Koskinen101, Kati 32 Kristiansson101, Zoltan Kutalik55,129, Maris Laan130, Marty Larson117, Lenore J Launer99, Benjamin 33 C Lehne1, Terho Lehtimäki131,132, David CM Liewald73,74, Li Lin81, Lars Lind133, Cecilia M 34 Lindgren40,84,134, YongMei Liu135, Ruth JF Loos28,58,136, Lorna M Lopez73,137,138, Yingchang Lu58, 35 Leo-Pekka Lyytikäinen131,132, Anubha Mahajan40, Chrysovalanto Mamasoula139, Jaume 36 Marrugat82, Jonathan Marten19, Yuri Milaneschi140, Anna Morgan61, Andrew P Morris40,141, 37 Alanna C Morrison142, Peter J Munson78, Mike A Nalls143,144, Priyanka Nandakumar49, Christopher 38 P Nelson59,60, Teemu Niiranen101,145, Ilja M Nolte146, Teresa Nutile69, Albertine J Oldehinkel147, 39 Ben A Oostra48, Paul F O'Reilly148, Elin Org16, Sandosh Padmanabhan63,149, Walter Palmas150, 40 Aarno Palotie102,151,152, Alison Pattie74, Brenda WJH Penninx140, Markus Perola101,102,153, Annette 41 Peters92, Ozren Polasek127,154, Peter P Pramstaller77,155,156, Nguyen Quang Tri78, Olli T 42 Raitakari157,158, Meixia Ren159,160, Rainer Rettig161, Kenneth Rice162, Paul M Ridker23,163, Janina S 43 Ried92, Harriëtte Riese147, Samuli Ripatti102,164, Antonietta Robino52, Lynda M Rose23, Jerome I 44 Rotter98, Igor Rudan165, Daniela Ruggiero69, Yasaman Saba166, Cinzia F Sala51, Veikko Salomaa101, 45 Nilesh J Samani59,60, Antti-Pekka Sarin102, Reinhold Schmidt103, Helena Schmidt166, Nick Shrine53, 46 David Siscovick167, Albert V Smith96,97, Harold Snieder146, Siim Sõber130, Rossella Sorice69, John M 47 Starr73,168, David J Stott169, David P Strachan170, Rona J Strawbridge85,86, Johan Sundström133, 48 Morris A Swertz171, Kent D Taylor98, Alexander Teumer80,172, Martin D Tobin53, Maciej 1 49 Tomaszewski123,124, Daniela Toniolo51, Michela Traglia51, Stella Trompet119,173, Jaakko 50 Tuomilehto174-177, Christophe Tzourio21, André G Uitterlinden88,178, Ahmad Vaez146,179, Peter J van 51 der Most146, Cornelia M van Duijn48, Anne-Claire Vergnaud1, Germaine C Verwoert88, Veronique 52 Vitart19, Uwe Völker80,180, Peter Vollenweider181, Dragana Vuckovic61,182, Hugh Watkins40,41, 53 Sarah H Wild183, Gonneke Willemsen57, James F Wilson19,64, Alan F Wright19, Jie Yao98 , Tatijana 54 Zemunik184, Weihua Zhang1,66, John R Attia24, Adam S Butterworth27,185, Daniel I Chasman23,163, 55 David Conen186,187, Francesco Cucca188,189, John Danesh27,185, Caroline Hayward19, Joanna MM 56 Howson27, Markku Laakso190, Edward G Lakatta191, Claudia Langenberg28, Olle Melander18, 57 Dennis O Mook-Kanamori26,192, Colin NA Palmer32, Lorenz Risch193-195, Robert A Scott28, Rodney J 58 Scott24, Peter Sever128, Tim D Spector29, Pim van der Harst196, Nicholas J Wareham28, Eleftheria 59 Zeggini31, Daniel Levy117,118, Patricia B Munroe3, Christopher Newton-Cheh134,197,198, Morris J 60 Brown3,4, Andres Metspalu16, Adriana M Hung199, Christopher J O’Donnell200, Todd L Edwards7 61 on behalf of the Million Veteran Program, Bruce M. Psaty201,202, Ioanna Tzoulaki1,2,5*, Michael R 62 Barnes3,4*, Louise V Wain53*, Paul Elliott1,5,203,204*‡, Mark J Caulfield3,4*‡ 63 64 * Equal contribution 65 ‡ Corresponding authors 66 67 1. Department of Epidemiology and Biostatistics, Imperial College London, London, 68 UK. 69 2. Department of Hygiene and Epidemiology, University of Ioannina Medical 70 School, Ioannina, Greece. 71 3. William Harvey Research Institute, Barts and The London School of Medicine and 72 Dentistry, Queen Mary University of London, London, UK. 73 4. National Institute for Health Research, Barts Cardiovascular Biomedical 74 Research Center, Queen Mary University of London, London, UK. 75 5. MRC-PHE Centre for Environment and Health, Imperial College London, London 76 W2 1PG, UK. 77 6. Department of Mathematics, Imperial College London, UK 78 7. Division of Epidemiology, Department of Medicine, Institute for Medicine and 79 Public Health, Vanderbilt Genetics Institute, Vanderbilt University Medical 80 Center, Tennessee Valley Healthcare System (626)/Vanderbilt University, 81 Nashville, TN. 82 8. Vanderbilt Genetics Institute, Vanderbilt Epidemiology Center, Department of 83 Obstetrics and Gynecology, Vanderbilt University Medical Center; Tennessee 84 Valley Health Systems VA, Nashville, TN. 85 9. Department of Epidemiology and Biomedical Informatics, Emory University 86 Rollins School of Public Health, Atlanta GA, USA. 87 10. Department of Biomedical Informatics, Emory University School of Medicine, 88 Atlanta, GA. 89 11. Massachusetts Veterans Epidemiology Research and Information Center 90 (MAVERIC), VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, 91 MA 02130, USA. 92 12. Division of Aging, Department of Medicine, Brigham and Women’s Hospital, 93 Boston, MA, Department of Medicine, Harvard Medical School, Boston, MA. 2 94 13. Atlanta VAMC and Emory Clinical Cardiovascular Research Institute, Atlanta, GA, 95 30233. 96 14. VA Palo Alto Health Care System; Division of Cardiovascular Medicine, Stanford 97 University School of Medicine. 98 15. Nephrology Section, Memphis VA Medical Center, Memphis TN. 99 16. Estonian Genome Center, University of Tartu, Tartu, Estonia. 100 17. Program in Medical and Population Genetics, Broad Institute of Harvard and 101 MIT, Cambridge, USA. 102 18. Department Clinical Sciences, Malmö, Lund University, Malmö, Sweden. 103 19. MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, 104 University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU 105 Scotland, UK 106 20. Department of Neurology, Bordeaux University Hospital, F-33000 Bordeaux, 107 France. 108 21. Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 109 1219, CHU Bordeaux, F-33000 Bordeaux, France. 110 22. Laboratory of Genetics and Genomics,NIA/NIH , Baltimore, MD 21224,USA. 111 23. Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, 112 USA. 113 24. Hunter Medical Reseach Institute and Faculty of Health, University of Newcastle, 114 New Lambton Heights, New South Wales, Australia. 115 25. Department of Biostatistics and Center for Statistical Genetics, University of 116 Michigan,
Load more

Recommended publications
  • Analysis of Trans Esnps Infers Regulatory Network Architecture
    Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2014 Anat Kreimer All rights reserved ABSTRACT Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer eSNPs are genetic variants associated with transcript expression levels. The characteristics of such variants highlight their importance and present a unique opportunity for studying gene regulation. eSNPs affect most genes and their cell type specificity can shed light on different processes that are activated in each cell. They can identify functional variants by connecting SNPs that are implicated in disease to a molecular mechanism. Examining eSNPs that are associated with distal genes can provide insights regarding the inference of regulatory networks but also presents challenges due to the high statistical burden of multiple testing. Such association studies allow: simultaneous investigation of many gene expression phenotypes without assuming any prior knowledge and identification of unknown regulators of gene expression while uncovering directionality. This thesis will focus on such distal eSNPs to map regulatory interactions between different loci and expose the architecture of the regulatory network defined by such interactions. We develop novel computational approaches and apply them to genetics-genomics data in human. We go beyond pairwise interactions to define network motifs, including regulatory modules and bi-fan structures, showing them to be prevalent in real data and exposing distinct attributes of such arrangements. We project eSNP associations onto a protein-protein interaction network to expose topological properties of eSNPs and their targets and highlight different modes of distal regulation.
    [Show full text]
  • Genome-Wide DNA Methylation Profiling Identifies Differential Methylation in Uninvolved Psoriatic Epidermis
    Genome-Wide DNA Methylation Profiling Identifies Differential Methylation in Uninvolved Psoriatic Epidermis Deepti Verma, Anna-Karin Ekman, Cecilia Bivik Eding and Charlotta Enerbäck The self-archived postprint version of this journal article is available at Linköping University Institutional Repository (DiVA): http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-147791 N.B.: When citing this work, cite the original publication. Verma, D., Ekman, A., Bivik Eding, C., Enerbäck, C., (2018), Genome-Wide DNA Methylation Profiling Identifies Differential Methylation in Uninvolved Psoriatic Epidermis, Journal of Investigative Dermatology, 138(5), 1088-1093. https://doi.org/10.1016/j.jid.2017.11.036 Original publication available at: https://doi.org/10.1016/j.jid.2017.11.036 Copyright: Elsevier http://www.elsevier.com/ Genome-Wide DNA Methylation Profiling Identifies Differential Methylation in Uninvolved Psoriatic Epidermis Deepti Verma*a, Anna-Karin Ekman*a, Cecilia Bivik Edinga and Charlotta Enerbäcka *Authors contributed equally aIngrid Asp Psoriasis Research Center, Department of Clinical and Experimental Medicine, Division of Dermatology, Linköping University, Linköping, Sweden Corresponding author: Charlotta Enerbäck Ingrid Asp Psoriasis Research Center, Department of Clinical and Experimental Medicine, Linköping University SE-581 85 Linköping, Sweden Phone: +46 10 103 7429 E-mail: [email protected] Short title Differential methylation in psoriasis Abbreviations CGI, CpG island; DMS, differentially methylated site; RRBS, reduced representation bisulphite sequencing Keywords (max 6) psoriasis, epidermis, methylation, Wnt, susceptibility, expression 1 ABSTRACT Psoriasis is a chronic inflammatory skin disease with both local and systemic components. Genome-wide approaches have identified more than 60 psoriasis-susceptibility loci, but genes are estimated to explain only one third of the heritability in psoriasis, suggesting additional, yet unidentified, sources of heritability.
    [Show full text]
  • TASOR Is a Pseudo-PARP That Directs HUSH Complex Assembly and Epigenetic Transposon Control
    Lawrence Berkeley National Laboratory Recent Work Title TASOR is a pseudo-PARP that directs HUSH complex assembly and epigenetic transposon control. Permalink https://escholarship.org/uc/item/6021r2cd Journal Nature communications, 11(1) ISSN 2041-1723 Authors Douse, Christopher H Tchasovnikarova, Iva A Timms, Richard T et al. Publication Date 2020-10-02 DOI 10.1038/s41467-020-18761-6 Peer reviewed eScholarship.org Powered by the California Digital Library University of California ARTICLE https://doi.org/10.1038/s41467-020-18761-6 OPEN TASOR is a pseudo-PARP that directs HUSH complex assembly and epigenetic transposon control Christopher H. Douse 1,4,9, Iva A. Tchasovnikarova2,5,9, Richard T. Timms 2,9, Anna V. Protasio 2,6, Marta Seczynska2, Daniil M. Prigozhin 1,7, Anna Albecka1,2,8, Jane Wagstaff3, James C. Williamson2, ✉ ✉ Stefan M. V. Freund3, Paul J. Lehner 2 & Yorgo Modis 1,2 1234567890():,; The HUSH complex represses retroviruses, transposons and genes to maintain the integrity of vertebrate genomes. HUSH regulates deposition of the epigenetic mark H3K9me3, but how its three core subunits — TASOR, MPP8 and Periphilin — contribute to assembly and targeting of the complex remains unknown. Here, we define the biochemical basis of HUSH assembly and find that its modular architecture resembles the yeast RNA-induced tran- scriptional silencing complex. TASOR, the central HUSH subunit, associates with RNA pro- cessing components. TASOR is required for H3K9me3 deposition over LINE-1 repeats and repetitive exons in transcribed genes. In the context of previous studies, this suggests that an RNA intermediate is important for HUSH activity. We dissect the TASOR and MPP8 domains necessary for transgene repression.
    [Show full text]
  • Noelia Díaz Blanco
    Effects of environmental factors on the gonadal transcriptome of European sea bass (Dicentrarchus labrax), juvenile growth and sex ratios Noelia Díaz Blanco Ph.D. thesis 2014 Submitted in partial fulfillment of the requirements for the Ph.D. degree from the Universitat Pompeu Fabra (UPF). This work has been carried out at the Group of Biology of Reproduction (GBR), at the Department of Renewable Marine Resources of the Institute of Marine Sciences (ICM-CSIC). Thesis supervisor: Dr. Francesc Piferrer Professor d’Investigació Institut de Ciències del Mar (ICM-CSIC) i ii A mis padres A Xavi iii iv Acknowledgements This thesis has been made possible by the support of many people who in one way or another, many times unknowingly, gave me the strength to overcome this "long and winding road". First of all, I would like to thank my supervisor, Dr. Francesc Piferrer, for his patience, guidance and wise advice throughout all this Ph.D. experience. But above all, for the trust he placed on me almost seven years ago when he offered me the opportunity to be part of his team. Thanks also for teaching me how to question always everything, for sharing with me your enthusiasm for science and for giving me the opportunity of learning from you by participating in many projects, collaborations and scientific meetings. I am also thankful to my colleagues (former and present Group of Biology of Reproduction members) for your support and encouragement throughout this journey. To the “exGBRs”, thanks for helping me with my first steps into this world. Working as an undergrad with you Dr.
    [Show full text]
  • WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT
    (12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization I International Bureau (10) International Publication Number (43) International Publication Date WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT (51) International Patent Classification: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, C12Q 1/68 (2018.01) A61P 31/18 (2006.01) DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, C12Q 1/70 (2006.01) HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, (21) International Application Number: MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, PCT/US2018/056167 OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, (22) International Filing Date: SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, 16 October 2018 (16. 10.2018) TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (25) Filing Language: English (84) Designated States (unless otherwise indicated, for every kind of regional protection available): ARIPO (BW, GH, (26) Publication Language: English GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, (30) Priority Data: UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, 62/573,025 16 October 2017 (16. 10.2017) US TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, ΓΕ , IS, IT, LT, LU, LV, (71) Applicant: MASSACHUSETTS INSTITUTE OF MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TECHNOLOGY [US/US]; 77 Massachusetts Avenue, TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, Cambridge, Massachusetts 02139 (US).
    [Show full text]
  • Download Author Version (PDF)
    Molecular BioSystems Accepted Manuscript This is an Accepted Manuscript, which has been through the Royal Society of Chemistry peer review process and has been accepted for publication. Accepted Manuscripts are published online shortly after acceptance, before technical editing, formatting and proof reading. Using this free service, authors can make their results available to the community, in citable form, before we publish the edited article. We will replace this Accepted Manuscript with the edited and formatted Advance Article as soon as it is available. You can find more information about Accepted Manuscripts in the Information for Authors. Please note that technical editing may introduce minor changes to the text and/or graphics, which may alter content. The journal’s standard Terms & Conditions and the Ethical guidelines still apply. In no event shall the Royal Society of Chemistry be held responsible for any errors or omissions in this Accepted Manuscript or any consequences arising from the use of any information it contains. www.rsc.org/molecularbiosystems Page 1 of 29 Molecular BioSystems Mutated Genes and Driver Pathways Involved in Myelodysplastic Syndromes—A Transcriptome Sequencing Based Approach Liang Liu1*, Hongyan Wang1*, Jianguo Wen2*, Chih-En Tseng2,3*, Youli Zu2, Chung-che Chang4§, Xiaobo Zhou1§ 1 Center for Bioinformatics and Systems Biology, Division of Radiologic Sciences, Wake Forest University Baptist Medical Center, Winston-Salem, NC 27157, USA. 2 Department of Pathology, the Methodist Hospital Research Institute,
    [Show full text]
  • Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
    Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A.
    [Show full text]
  • Plasma Proteomic Analysis Reveals Altered Protein Abundances In
    Lygirou et al. J Transl Med (2018) 16:104 https://doi.org/10.1186/s12967-018-1476-9 Journal of Translational Medicine RESEARCH Open Access Plasma proteomic analysis reveals altered protein abundances in cardiovascular disease Vasiliki Lygirou1 , Agnieszka Latosinska2, Manousos Makridakis1, William Mullen3, Christian Delles3, Joost P. Schanstra4,5, Jerome Zoidakis1, Burkert Pieske6, Harald Mischak2 and Antonia Vlahou1* Abstract Background: Cardiovascular disease (CVD) describes the pathological conditions of the heart and blood vessels. Despite the large number of studies on CVD and its etiology, its key modulators remain largely unknown. To this end, we performed a comprehensive proteomic analysis of blood plasma, with the scope to identify disease-associated changes after placing them in the context of existing knowledge, and generate a well characterized dataset for fur- ther use in CVD multi-omics integrative analysis. Methods: LC–MS/MS was employed to analyze plasma from 32 subjects (19 cases of various CVD phenotypes and 13 controls) in two steps: discovery (13 cases and 8 controls) and test (6 cases and 5 controls) set analysis. Follow- ing label-free quantifcation, the detected proteins were correlated to existing plasma proteomics datasets (plasma proteome database; PPD) and functionally annotated (Cytoscape, Ingenuity Pathway Analysis). Diferential expression was defned based on identifcation confdence ( 2 peptides per protein), statistical signifcance (Mann–Whitney p value 0.05) and a minimum of twofold change.≥ ≤ Results: Peptides detected in at least 50% of samples per group were considered, resulting in a total of 3796 identi- fed proteins (838 proteins based on 2 peptides). Pathway annotation confrmed the functional relevance of the fndings (representation of complement≥ cascade, fbrin clot formation, platelet degranulation, etc.).
    [Show full text]
  • An Amino Acid Deletion Inszt2 in a Family with Non- Syndromic Intellectual Disability
    An Amino Acid Deletion inSZT2 in a Family with Non- Syndromic Intellectual Disability Michelle Falcone1, Kemal O. Yariz1, David B. Ross2, Joseph Foster II1, Ibis Menendez1, Mustafa Tekin1* 1 Dr. John T. Macdonald Department of Human Genetics and John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, Florida, United States of America, 2 Comprehensive Neurobehavioral Institute, Plantation, Florida, United States of America Abstract Autosomal recessive intellectual disability (ID) is characterized by extensive genetic heterogeneity. Recently, three mutations in SZT2 were reported in two unrelated children with unexplained infantile epileptic encephalopathy with severe ID. Here we report a European American family with three children having non-syndromic mild or moderate ID without seizures. Whole-exome sequencing of three affected siblings revealed a three base pair deletion (c. 4202_4204delTTC) located in a 19 mb autozygous region on chromosome 1, leading to an amino acid deletion (p.Phe1401del) in SZT2. All three children were homozygous for the deletion and their parents were heterozygous as expected in autosomal recessive inheritance. SZT2 is highly expressed in neuronal tissues and regulates seizure threshold and neuronal excitation in mice. We conclude that the disruption of SZT2 with some residual function might lead to mild or moderate ID without seizures. Citation: Falcone M, Yariz KO, Ross DB, Foster J, Menendez I, et al. (2013) An Amino Acid Deletion inSZT2 in a Family with Non-Syndromic Intellectual Disability. PLoS ONE 8(12): e82810. doi:10.1371/journal.pone.0082810 Editor: Andreas R. Janecke, Innsbruck Medical University, Austria Received September 13, 2013; Accepted November 7, 2013; Published December 6, 2013 Copyright: © 2013 Falcone et al.
    [Show full text]
  • Oncogenic Fusion Protein FGFR2-PPHLN1: Requirements for Biological Activation, and Efficacy of Inhibitors
    UC San Diego UC San Diego Previously Published Works Title Oncogenic fusion protein FGFR2-PPHLN1: Requirements for biological activation, and efficacy of inhibitors. Permalink https://escholarship.org/uc/item/12g996rt Journal Translational oncology, 13(12) ISSN 1936-5233 Authors Li, Fangda Meyer, April N Peiris, Malalage N et al. Publication Date 2020-12-01 DOI 10.1016/j.tranon.2020.100853 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Translational Oncology 13 (2020) 100853 Contents lists available at ScienceDirect Translational Oncology journal homepage: www.elsevier.com/locate/tranon Oncogenic fusion protein FGFR2-PPHLN1: Requirements for biological activation, and efficacy of inhibitors ⁎ Fangda Li a, April N. Meyer a, Malalage N. Peiris a, Katelyn N. Nelson a, Daniel J. Donoghue a,b, a Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA 92093-0367, USA b UCSD Moores Cancer Center and Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA 92093-0367, USA ARTICLE INFO ABSTRACT Article history: Aim of study: Chromosomal translocations such as t(10;12)(q26,q12) are associated with intrahepatic cholangiocarci- Received 2 May 2020 noma, a universally fatal category of liver cancer. This translocation creates the oncogenic fusion protein of Fibroblast Received in revised form 24 July 2020 Growth Factor Receptor 2 joined to Periphilin 1. The aims of this study were to identify significant features required for Accepted 9 August 2020 biological activation, analyze the activation of downstream signaling pathways, and examine the efficacy of the TKIs Available online xxxx BGJ398 and TAS-120, and of the MEK inhibitor Trametinib.
    [Show full text]
  • Developmental and Epileptic Encephalopathy Due to SZT2 Genomic Variants: Emerging Features of a Syndromic Condition
    Epilepsy & Behavior 108 (2020) 107097 Contents lists available at ScienceDirect Epilepsy & Behavior journal homepage: www.elsevier.com/locate/yebeh Review Developmental and epileptic encephalopathy due to SZT2 genomic variants: Emerging features of a syndromic condition Marina Trivisano a, Manuel Rivera a,b, Alessandra Terracciano c,AndreaCiolfi d, Antonio Napolitano e, Chiara Pepi f, Costanza Calabrese a, Maria Cristina Digilio g, Marco Tartaglia d, Paolo Curatolo f, Federico Vigevano h,i, Nicola Specchio a,i,⁎ a Rare and Complex Epilepsy Unit, Department of Neuroscience, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy b Departamento de Neuropediatria, Fleni, Montañeses 2325, C1428AQK Ciudad de Buenos Aires, Argentina c Laboratory of Medical Genetics, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy d Genetics and Rare Diseases Research Division, Bambino Gesù Children's Hospital, IRCSS, Rome, Italy e Neuroradiology Unit, Department of Imaging, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy f Child Neurology and Psychiatry Unit, Systems Medicine Department, Tor Vergata University, Via Montpellier 1, 00133 Rome, Italy g Medical Genetics, Department of Pediatrics, Bambino Gesù Children's Hospital, IRCSS, Rome, Italy h Department of Neuroscience, Bambino Gesù Children's Hospital, IRCCS, Rome i Member of European Reference Network EpiCARE article info abstract Article history: Seizure threshold 2 (SZT2) gene mutations have been associated with developmental and epileptic encephalop- Received 1 April 2020 athies (DEEs). Following a literature review, we collected 22 patients and identified the main clinical features re- Revised 4 April 2020 lated to SZT2 variants that are epilepsy with onset within the first years of life, intellectual disability (ID), Accepted 4 April 2020 macrocephaly with dysmorphic facial features, corpus callosum (CC) shape abnormalities, and cortical migration Available online 11 May 2020 disorders.
    [Show full text]
  • Rabbit Anti-C1orf84 /FITC Conjugated Antibody
    SunLong Biotech Co.,LTD Tel: 0086-571- 56623320 Fax:0086-571- 56623318 E-mail:[email protected] www.sunlongbiotech.com Rabbit Anti-C1orf84 /FITC Conjugated antibody SL15077R-FITC Product Name: Anti-C1orf84 /FITC Chinese Name: FITC标记的1号染色体开放阅读框84抗体 Chromosome 1 open reading frame 84; Hypothetical protein LOC149469; Alias: Uncharacterized protein C1orf84; SZT2_HUMAN. Organism Species: Rabbit Clonality: Polyclonal React Species: Human,Mouse,Rat,Dog,Cow,Horse,Rabbit,Sheep, ICC=1:50-200IF=1:50-200 Applications: not yet tested in other applications. optimal dilutions/concentrations should be determined by the end user. Molecular weight: 378kDa Form: Lyophilized or Liquid Concentration: 1mg/ml immunogen: KLH conjugated synthetic peptide derived from human C1orf84 Lsotype: IgG Purification: affinity purified by Protein A Storage Buffer: 0.01M TBS(pH7.4) with 1% BSA, 0.03% Proclin300 and 50% Glycerol. Storewww.sunlongbiotech.com at -20 °C for one year. Avoid repeated freeze/thaw cycles. The lyophilized antibody is stable at room temperature for at least one month and for greater than a year Storage: when kept at -20°C. When reconstituted in sterile pH 7.4 0.01M PBS or diluent of antibody the antibody is stable for at least two weeks at 2-4 °C. background: SZT2 (seizure threshold 2 homolog (mouse)), also known as SZT2A or SZT2B, is a 3,432 amino acid peroxisomal protein that plays a role in resistance to oxidative stress. Predominantly expressed in the parietal and frontal cortex, as well as in dorsal root Product Detail: ganglia of the brain, SZT2 is implicated in superoxide dismutase activity and the neuroprotection in peroxisomes.
    [Show full text]