OBJECTIVE: To assess whether different forms of arthritis and disease activity could be distinguished by peripheral blood expression profiles of bone-regulatory factors including tumor necrosis factor (TNF)-superfamily [TNF-related apoptosis-inducing ligand (TRAIL), the Fas ligand (FasL), and the ligand for herpesvirus entry mediator (LIGHT)] and bone morphogenetic protein (BMP)-family members (BMP-2, BMP-4, BMP-6) as well as osteoblast differentiation gene Runx2. METHODS: Blood cells from healthy controls (n = 25) and patients at different disease stages with rheumatoid arthritis (RA; n = 49), osteoarthritis (OA; n = 17), or spondyloarthritis, including ankylosing spondylitis (AS; n = 27) or psoriatic arthritis (PsA; n = 23), were processed for quantitative polymerase chain reaction. Gene expression was assessed in comparison with control samples, correlated with clinical data of different forms of arthritis, and analyzed for discriminative efficacy between groups by receiver-operation characteristic (ROC) curves. Results were confirmed on diagnostic RA (n = 5) and AS (n = 8) samples. RESULTS: BMP-4, BMP-6, and Runx2 expressions were significantly decreased in patients with RA and OA versus controls. Patients with RA also had decreased FasL and LIGHT expression, while patients with AS had increased Runx2 expression. Negative correlation with disease activity was found for BMP-4, FasL, and Runx2 in RA and for Runx2 in PsA, while positive correlation was found for BMP-4 in PsA. Gene expression was higher in the therapy-resistant form of AS (for BMP-4, LIGHT, and Runx2) and in methotrexate-treated patients in RA (for BMP-2 and LIGHT). ROC curve analysis confirmed discrimination between groups, particularly decreased LIGHT and Runx2 for RA and increased Runx2 for AS. CONCLUSION: Our study identified BMP and Runx2 as possible biomarkers of bone metabolism in several forms of arthritis, while lower FasL and LIGHT were associated with RA. Correlation between gene expression and disease activity may be clinically useful in assessing therapeutic effectiveness and disease monitoring.
OBJECTIVE: To assess whether different forms of arthritis and disease activity could be distinguished by peripheral blood expression profiles of bone-regulatory factors including tumor necrosis factor (TNF)-superfamily [TNF-related apoptosis-inducing ligand (TRAIL), the Fas ligand (FasL), and the ligand for herpesvirus entry mediator (LIGHT)] and bone morphogenetic protein (BMP)-family members (BMP-2, BMP-4, BMP-6) as well as osteoblast differentiation gene Runx2. METHODS: Blood cells from healthy controls (n = 25) and patients at different disease stages with rheumatoid arthritis (RA; n = 49), osteoarthritis (OA; n = 17), or spondyloarthritis, including ankylosing spondylitis (AS; n = 27) or psoriatic arthritis (PsA; n = 23), were processed for quantitative polymerase chain reaction. Gene expression was assessed in comparison with control samples, correlated with clinical data of different forms of arthritis, and analyzed for discriminative efficacy between groups by receiver-operation characteristic (ROC) curves. Results were confirmed on diagnostic RA (n = 5) and AS (n = 8) samples. RESULTS:BMP-4, BMP-6, and Runx2 expressions were significantly decreased in patients with RA and OA versus controls. Patients with RA also had decreased FasL and LIGHT expression, while patients with AS had increased Runx2 expression. Negative correlation with disease activity was found for BMP-4, FasL, and Runx2 in RA and for Runx2 in PsA, while positive correlation was found for BMP-4 in PsA. Gene expression was higher in the therapy-resistant form of AS (for BMP-4, LIGHT, and Runx2) and in methotrexate-treated patients in RA (for BMP-2 and LIGHT). ROC curve analysis confirmed discrimination between groups, particularly decreased LIGHT and Runx2 for RA and increased Runx2 for AS. CONCLUSION: Our study identified BMP and Runx2 as possible biomarkers of bone metabolism in several forms of arthritis, while lower FasL and LIGHT were associated with RA. Correlation between gene expression and disease activity may be clinically useful in assessing therapeutic effectiveness and disease monitoring.
Authors: Elena V Tchetina; A Robin Poole; Elena M Zaitseva; Eugeniya P Sharapova; Natalya G Kashevarova; Elena A Taskina; Liudmila I Alekseeva; Liudmila A Semyonova; Svetlana I Glukhova; Alexandr N Kuzin; Maxim A Makarov; Sergey A Makarov Journal: Arthritis Date: 2013-06-25
Authors: Eleftheria Zeggini; Kalliope Panoutsopoulou; Lorraine Southam; Nigel W Rayner; Aaron G Day-Williams; Margarida C Lopes; Vesna Boraska; Tonu Esko; Evangelos Evangelou; Albert Hoffman; Jeanine J Houwing-Duistermaat; Thorvaldur Ingvarsson; Ingileif Jonsdottir; Helgi Jonnson; Hanneke J Kerkhof; Margreet Kloppenburg; Steffan D Bos; Massimo Mangino; Sarah Metrustry; P Eline Slagboom; Gudmar Thorleifsson; Emma V A Raine; Madhushika Ratnayake; Michelle Ricketts; Claude Beazley; Hannah Blackburn; Suzannah Bumpstead; Katherine S Elliott; Sarah E Hunt; Simon C Potter; So-Youn Shin; Vijay K Yadav; Guangju Zhai; Kate Sherburn; Kate Dixon; Elizabeth Arden; Nadim Aslam; Phillippa-kate Battley; Ian Carluke; Sally Doherty; Andrew Gordon; John Joseph; Richard Keen; Nicola C Koller; Sheryl Mitchell; Fiona O'Neill; Ellen Paling; Mike R Reed; Fernando Rivadeneira; Diane Swift; Kirsten Walker; Bridget Watkins; Maggie Wheeler; Fraser Birrell; John P A Ioannidis; Ingrid Meulenbelt; Andres Metspalu; Ashok Rai; Donald Salter; Kari Stefansson; Unnur Stykarsdottir; André G Uitterlinden; Joyce B J van Meurs; Kay Chapman; Panos Deloukas; William E R Ollier; Gillian A Wallis; Nigel Arden; Andrew Carr; Michael Doherty; Andrew McCaskie; J Mark Willkinson; Stuart H Ralston; Ana M Valdes; Tim D Spector; John Loughlin Journal: Lancet Date: 2012-07-03 Impact factor: 79.321
Authors: Karina I Halilova; Elizabeth E Brown; Sarah L Morgan; S Louis Bridges; Min-Ho Hwang; Donna K Arnett; Maria I Danila Journal: Int J Rheumatol Date: 2012-07-09
Authors: A N Burska; K Roget; M Blits; L Soto Gomez; F van de Loo; L D Hazelwood; C L Verweij; A Rowe; G N Goulielmos; L G M van Baarsen; F Ponchel Journal: Pharmacogenomics J Date: 2014-03-04 Impact factor: 3.550