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Clinical and epidemiological research
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A weighted genetic risk score using all known susceptibility variants to estimate rheumatoid arthritis risk

Authors

  • Annie Yarwood Arthritis Research UK Epidemiology Unit, Centre for Musculoskeletal Research, Institute of Inflammation and Repair, The University of Manchester, Manchester, UK PubMed articlesGoogle scholar articles
  • Buhm Han Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA PubMed articlesGoogle scholar articles
  • Soumya Raychaudhuri Arthritis Research UK Epidemiology Unit, Centre for Musculoskeletal Research, Institute of Inflammation and Repair, The University of Manchester, Manchester, UK Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA PubMed articlesGoogle scholar articles
  • John Bowes Arthritis Research UK Epidemiology Unit, Centre for Musculoskeletal Research, Institute of Inflammation and Repair, The University of Manchester, Manchester, UK PubMed articlesGoogle scholar articles
  • Mark Lunt Arthritis Research UK Epidemiology Unit, Centre for Musculoskeletal Research, Institute of Inflammation and Repair, The University of Manchester, Manchester, UK PubMed articlesGoogle scholar articles
  • Dimitrios A Pappas Division of Rheumatology, Department of Medicine, New York Presbyterian Hospital, College of Physicians and Surgeons, Columbia University, New York, New York, USA PubMed articlesGoogle scholar articles
  • Joel Kremer Department of Medicine, Albany Medical College, New York, New York, USA PubMed articlesGoogle scholar articles
  • Jeffrey D Greenberg Department of Rheumatology, New York University Hospital for Joint Diseases, New York, New York, USA PubMed articlesGoogle scholar articles
  • Robert Plenge Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA Medical and Population Genetics Program, Broad Institute, Cambridge, Massachusetts, USA PubMed articlesGoogle scholar articles
  • Rheumatoid Arthritis Consortium International (RACI)
    Google scholar articles
  • Jane Worthington Arthritis Research UK Epidemiology Unit, Centre for Musculoskeletal Research, Institute of Inflammation and Repair, The University of Manchester, Manchester, UK NIHR Manchester Musculoskeletal Biomedical Research Unit, Manchester Academic Health Science Centre, Central Manchester Foundation Trust, Manchester, UK PubMed articlesGoogle scholar articles
  • Anne Barton Arthritis Research UK Epidemiology Unit, Centre for Musculoskeletal Research, Institute of Inflammation and Repair, The University of Manchester, Manchester, UK NIHR Manchester Musculoskeletal Biomedical Research Unit, Manchester Academic Health Science Centre, Central Manchester Foundation Trust, Manchester, UK PubMed articlesGoogle scholar articles
  • Steve Eyre Arthritis Research UK Epidemiology Unit, Centre for Musculoskeletal Research, Institute of Inflammation and Repair, The University of Manchester, Manchester, UK PubMed articlesGoogle scholar articles
  1. Correspondence to Dr Steve Eyre, Arthritis Research UK Epidemiology Unit, Stopford Building, The University of Manchester, Oxford Road, Manchester M13 9PT, UK; steve.eyre{at}manchester.ac.uk
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Citation

Yarwood A, Han B, Raychaudhuri S, et al
A weighted genetic risk score using all known susceptibility variants to estimate rheumatoid arthritis risk
Annals of the Rheumatic Diseases 2015;74:170-176.

Publication history

  • Received June 17, 2013
  • Revised August 9, 2013
  • Accepted September 10, 2013
  • First published October 3, 2013.
Online issue publication 
November 02, 2019

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Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/3.0/