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Genome-wide analyses using UK Biobank data provide insights into the genetic architecture of osteoarthritis

  • Eleni Zengini
  • , Konstantinos Hatzikotoulas
  • , Ioanna Tachmazidou
  • , Julia Steinberg
  • , Fernando P. Hartwig
  • , Lorraine Southam
  • , Sophie Hackinger
  • , Cindy G. Boer
  • , Unnur Styrkarsdottir
  • , Arthur Gilly
  • , Daniel Suveges
  • , Britt Killian
  • , Thorvaldur Ingvarsson
  • , Helgi Jonsson
  • , George C. Babis
  • , Andrew McCaskie
  • , Andre G. Uitterlinden
  • , Joyce B.J. Van Meurs
  • , Unnur Thorsteinsdottir
  • , Kari Stefansson
  • George Davey Smith, Jeremy M. Wilkinson, Eleftheria Zeggini
  • University of Sheffield
  • Dromokaiteio Psychiatric Hospital
  • Wellcome Sanger Institute
  • Cellzome GmbH
  • Cancer Council NSW
  • Federal University of Pelotas
  • University of Bristol
  • University of Oxford
  • Erasmus University Medical Center
  • deCODE genetics
  • Akureyri Hospital
  • University of Iceland
  • University of Akureyri
  • Landspitali - The National University Hospital of Iceland
  • University of Athens
  • Department of Surgery

Research output: Contribution to journalArticlepeer-review

250 Scopus citations

Abstract

Osteoarthritis is a common complex disease imposing a large public-health burden. Here, we performed a genome-wide association study for osteoarthritis, using data across 16.5 million variants from the UK Biobank resource. After performing replication and meta-analysis in up to 30,727 cases and 297,191 controls, we identified nine new osteoarthritis loci, in all of which the most likely causal variant was noncoding. For three loci, we detected association with biologically relevant radiographic endophenotypes, and in five signals we identified genes that were differentially expressed in degraded compared with intact articular cartilage from patients with osteoarthritis. We established causal effects on osteoarthritis for higher body mass index but not for triglyceride levels or genetic predisposition to type 2 diabetes.

Original languageEnglish
Pages (from-to)549-558
Number of pages10
JournalNature Genetics
Volume50
Issue number4
DOIs
StatePublished - 1 Apr 2018
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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