Ontology highlight
ABSTRACT:
SUBMITTER: Rodriguez-Fontenla C
PROVIDER: S-EPMC4660891 | biostudies-literature | 2014 Apr
REPOSITORIES: biostudies-literature
Rodriguez-Fontenla Cristina C Calaza Manuel M Evangelou Evangelos E Valdes Ana M AM Arden Nigel N Blanco Francisco J FJ Carr Andrew A Chapman Kay K Deloukas Panos P Doherty Michael M Esko Tõnu T Garcés Aletá Carlos M CM Gomez-Reino Carnota Juan J JJ Helgadottir Hafdis H Hofman Albert A Jonsdottir Ingileif I Kerkhof Hanneke J M HJ Kloppenburg Margreet M McCaskie Andrew A Ntzani Evangelia E EE Ollier William E R WE Oreiro Natividad N Panoutsopoulou Kalliope K Ralston Stuart H SH Ramos Yolande F YF Riancho Jose A JA Rivadeneira Fernando F Slagboom P Eline PE Styrkarsdottir Unnur U Thorsteinsdottir Unnur U Thorleifsson Gudmar G Tsezou Aspasia A Uitterlinden André G AG Wallis Gillian A GA Wilkinson J Mark JM Zhai Guangju G Zhu Yanyan Y Felson David T DT Ioannidis John P A JP Loughlin John J Metspalu Andres A Meulenbelt Ingrid I Stefansson Kari K van Meurs Joyce B JB Zeggini Eleftheria E Spector Timothy D TD Gonzalez Antonio A
Arthritis & rheumatology (Hoboken, N.J.) 20140401 4
<h4>Objective</h4>To assess candidate genes for association with osteoarthritis (OA) and identify promising genetic factors and, secondarily, to assess the candidate gene approach in OA.<h4>Methods</h4>A total of 199 candidate genes for association with OA were identified using Human Genome Epidemiology (HuGE) Navigator. All of their single-nucleotide polymorphisms (SNPs) with an allele frequency of >5% were assessed by fixed-effects meta-analysis of 9 genome-wide association studies (GWAS) that ...[more]