Association of Polygenic Risk Scores With Radiographic Progression in Patients With Rheumatoid Arthritis

Abstract

Objective To investigate whether polygenic risk scores obtained using data from a genome‐wide association study (GWAS) of rheumatoid arthritis (RA) susceptibility can be predictors of radiographic progression. Methods We constructed polygenic risk scores using GWAS summary data on associations of single‐nucleotide polymorphisms with RA susceptibility. The polygenic risk scores were stratified into quintiles based on levels of significance (ranging from top quintile of polygenic risk scores to bottom quintile). In addition, change in the Sharp/van der Heijde score (SHS) of radiographic progression over the first 5 years after onset of RA was assessed. The change in SHS over 5 years was stratified according to quartiles, with the top quartile of change in SHS defined as severe radiographic progression (score change of >35 points) and the remaining 3 quartiles defined as nonsevere radiographic progression. Polygenic risk scores were assessed for their ability to predict the SHS status over 5 years in a training set (n = 500 RA patients) for selection of the best model, and in a testing set (n = 740 RA patients) for validation of the data. We evaluated the performance of the polygenic risk score as a predictor of severe radiographic progression in univariable and multivariable analyses with inclusion of other factors. Results Polygenic risk scores constructed from 43,784 single‐nucleotide polymorphisms significantly differed between patients who experienced severe radiographic progression and those with nonsevere radiographic progression in both the training set (P = 0.0064) and the testing set (P = 0.017). Patients with polygenic risk scores in the top quintile had a higher risk of severe progression compared to those with polygenic risk scores in the bottom quintile (odds ratio [OR] 1.90, P = 0.0022), and the risk of severe radiographic progression was even higher when restricted to patients who were younger at disease onset (OR 5.06, P = 0.00038). The group with polygenic risk scores in the top quintile and the anti–citrullinated protein antibody (ACPA)–positive group had significantly higher proportions of patients with severe radiographic progression (P = 0.00052 and P = 0.0022, respectively) compared to the remaining groups. Multivariable analysis showed that polygenic risk score (P = 0.00019) as well as female sex (P = 0.0033), ACPA positivity (P = 0.0023), and body mass index (P = 0.024) were independent risk factors for severe radiographic progression. Conclusion A polygenic risk score that is derived from GWAS data on RA susceptibility is associated with the level of severity of radiographic progression in patients with RA.

Matrix Metalloproteinase-9 Level in Synovial Fluid—Association with Joint Destruction in Early Rheumatoid Arthritis

“…Like the results of these studies, our results highlight a significant correlation of ACPA with MMP-9 level in synovial fluid, highlighting the greater importance of this serological parameter than RF for the rapid radiological progression of early RA. According to our results, multivariable risk assessment of rapid radiological progression of early RA showed that ACPA positivity with a polygenic risk score, as well as female gender and body mass index was associated with rapid progression of structural joint changes [ 34 ].…”

Genetic basis of defects in immune tolerance underlying the development of autoimmunity

“…Genetic risk scores for predicting clinical outcomes are also being investigated in the setting of rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). In RA, a polygenic risk score has recently been developed to predict severity of radiographic progression ( 13 ) and in SLE, a high genetic risk score was associated with organ damage and renal dysfunction ( 14 ).…”

Research

“…In this paper from Tokyo (Japan) , a group of investigators has used data from a large genome-wide association study (GWAS) to create a PRS for rheumatoid arthritis, thereby assessing the potential associations and interactions of the various genetic factors associated with development of rheumatoid arthritis (RA). 3 The group used the model to predict the Sharp/van der Heijde score (SHS), indicating the nature and extent of disease progression. The model was initially developed in a training set of 500 cases, before testing it in a validation cohort of 740 cases.…”

“…Essentially, this is a way to visualize additive and interacting genetic-related risk factors for a specific condition. In this paper from Tokyo (Japan), a group of investigators has used data from a large genomewide association study (GWAS) to create a PRS for rheumatoid arthritis, thereby assessing the potential associations and interactions of the various genetic factors associated with development of rheumatoid arthritis (RA) 3. The group used the model to predict the Sharp/ van der Heijde score (SHS), indicating the nature and extent of disease progression.…”