Literature DB >> 25573839

Improved prediction of knee osteoarthritis progression by genetic polymorphisms: the Arthrotest Study.

Francisco J Blanco1, Ingrid Möller2, Montserrat Romera2, Antoni Rozadilla2, Jaime A Sánchez-Lázaro2, Arturo Rodríguez2, José Gálvez2, Joaquim Forés2, Jordi Monfort2, Soledad Ojeda2, Carme Moragues2, Miguel Ángel Caracuel2, Teresa Clavaguera2, Carmen Valdés2, Josep Maria Soler2, Cristóbal Orellana2, Miguel Ángel Belmonte2, Florentina Martín2, Sergio Giménez2, Eduardo Úcar2, Josep Pous2, Nerea Bartolomé2, Marta Artieda2, Magdalena Szczypiorska2, Diego Tejedor2, Antonio Martínez2, Eulàlia Montell2, Helena Martínez2, Marta Herrero2, Josep Vergés2.   

Abstract

OBJECTIVE: The aim of this study was to develop a genetic prognostic tool to predict radiographic progression towards severe disease in primary knee OA (KOA) patients.
METHODS: This investigation was a cross-sectional, retrospective, multicentric association study in 595 Spanish KOA patients. Caucasian patients aged ≥40 years at the time of diagnosis of primary KOA of Kellgren-Lawrence grade 2 or 3 were included. Patients who progressed to Kellgren-Lawrence score 4 or who were referred for total knee replacement within 8 years after diagnosis were classified as progressors to severe disease. Clinical variables of the initial stages of the disease (gender, BMI, age at diagnosis, OA in the contralateral knee, and OA in other joints) were registered as potential predictors. Single nucleotide polymorphisms and clinical variables with an association of P < 0.05 were included in the multivariate analysis using forward logistic regression.
RESULTS: A total of 23 single nucleotide polymorphisms and the time of primary KOA diagnosis were significantly associated with KOA severe progression in the exploratory cohort (n = 220; P < 0.05). The predictive accuracy of the clinical variables was limited: area under the curve (AUC) = 0.66. When genetic variables were added to the clinical model (full model), the prediction of KOA progression was significantly improved (AUC = 0.82). Combining only genetic variables (rs2073508, rs10845493, rs2206593, rs10519263, rs874692, rs7342880, rs780094 and rs12009), a predictive model with good accuracy was also obtained (AUC = 0.78). The predictive ability for KOA progression of the full model was confirmed on the replication cohort (two-sample Z-test; n = 62; P = 0.190).
CONCLUSION: An accurate prognostic tool to predict primary KOA progression has been developed based on genetic and clinical information from OA patients.
© The Author 2015. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  knee osteoarthritis; radiographic progression; single nucleotide polymorphism

Mesh:

Year:  2015        PMID: 25573839     DOI: 10.1093/rheumatology/keu478

Source DB:  PubMed          Journal:  Rheumatology (Oxford)        ISSN: 1462-0324            Impact factor:   7.580


  9 in total

1.  Lysophosphatidylcholines to phosphatidylcholines ratio predicts advanced knee osteoarthritis.

Authors:  Weidong Zhang; Guang Sun; Dawn Aitken; Sergei Likhodii; Ming Liu; Glynn Martin; Andrew Furey; Edward Randell; Proton Rahman; Graeme Jones; Guangju Zhai
Journal:  Rheumatology (Oxford)       Date:  2016-05-09       Impact factor: 7.580

2.  A replication study and meta-analysis of mitochondrial DNA variants in the radiographic progression of knee osteoarthritis.

Authors:  Mercedes Fernández-Moreno; Angel Soto-Hermida; María E Vázquez-Mosquera; Estefanía Cortés-Pereira; Sonia Pértega; Sara Relaño; Natividad Oreiro-Villar; Carlos Fernández-López; Francisco J Blanco; Ignacio Rego-Pérez
Journal:  Rheumatology (Oxford)       Date:  2016-11-17       Impact factor: 7.580

3.  Gene-gene interactions of the Wnt/β-catenin signaling pathway in knee osteoarthritis.

Authors:  Javier Fernández-Torres; Yessica Zamudio-Cuevas; Alberto López-Reyes; Daniela Garrido-Rodríguez; Karina Martínez-Flores; Carlos Alberto Lozada; José Francisco Muñóz-Valle; Edith Oregon-Romero; Gabriela Angélica Martínez-Nava
Journal:  Mol Biol Rep       Date:  2018-08-06       Impact factor: 2.316

4.  Multifactor dimensionality reduction reveals a strong gene-gene interaction between STC1 and COL11A1 genes as a possible risk factor of knee osteoarthritis.

Authors:  Javier Fernández-Torres; Gabriela Angélica Martínez-Nava; Yessica Zamudio-Cuevas; Karina Martínez-Flores; Fernando Mijares-Díaz
Journal:  Mol Biol Rep       Date:  2020-03-05       Impact factor: 2.316

5.  Risk scoring for time to end-stage knee osteoarthritis: data from the Osteoarthritis Initiative.

Authors:  R Dunn; J Greenhouse; D James; D Ohlssen; P Mesenbrink
Journal:  Osteoarthritis Cartilage       Date:  2020-05-13       Impact factor: 6.576

6.  Association of SNPs in the TIMP-2 gene and large artery atherosclerotic stroke in southern Chinese Han population.

Authors:  Tie Guo; Haizhen Hao; Lv Zhou; Feng Zhou; Dan Yu
Journal:  Oncotarget       Date:  2017-12-18

7.  TIMP-2 SNPs rs7342880 and rs4789936 are linked to risk of knee osteoarthritis in the Chinese Han Population.

Authors:  Pengcheng Xu; Wen Guo; Tianbo Jin; Jihong Wang; Dongsheng Fan; Zengtao Hao; Shangfei Jing; ChaoQian Han; Jieli Du; Dong Jiang; Shuzheng Wen; Jianzhong Wang
Journal:  Oncotarget       Date:  2017-01-03

8.  Development of a model for predicting the 4-year risk of symptomatic knee osteoarthritis in China: a longitudinal cohort study.

Authors:  Limin Wang; Han Lu; Hongbo Chen; Shida Jin; Mengqi Wang; Shaomei Shang
Journal:  Arthritis Res Ther       Date:  2021-02-26       Impact factor: 5.156

9.  Development of a clinical prediction algorithm for knee osteoarthritis structural progression in a cohort study: value of adding measurement of subchondral bone density.

Authors:  Michael P LaValley; Grace H Lo; Lori Lyn Price; Jeffrey B Driban; Charles B Eaton; Timothy E McAlindon
Journal:  Arthritis Res Ther       Date:  2017-05-16       Impact factor: 5.156

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.