Severe Radiographic Progression Research Articles

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

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. 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. 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. 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.

Biological function integrated prediction of severe radiographic progression in rheumatoid arthritis: a nested case control study

BackgroundRadiographic progression is reported to be highly heritable in rheumatoid arthritis (RA). However, previous study using genetic loci showed an insufficient accuracy of prediction for radiographic progression. The aim of this study is to identify a biologically relevant prediction model of radiographic progression in patients with RA using a genome-wide association study (GWAS) combined with bioinformatics analysis.MethodsWe obtained genome-wide single nucleotide polymorphism (SNP) data for 374 Korean patients with RA using Illumina HumanOmni2.5Exome-8 arrays. Radiographic progression was measured using the yearly Sharp/van der Heijde modified score rate, and categorized in no or severe progression. Significant SNPs for severe radiographic progression from GWAS were mapped on the functional genes and reprioritized by post-GWAS analysis. For robust prediction of radiographic progression, tenfold cross-validation using a support vector machine (SVM) classifier was conducted. Accuracy was used for selection of optimal SNPs set in the Hanyang Bae RA cohort. The performance of our final model was compared with that of other models based on GWAS results and SPOT (one of the post-GWAS analyses) using receiver operating characteristic (ROC) curves. The reliability of our model was confirmed using GWAS data of Caucasian patients with RA.ResultsA total of 36,091 significant SNPs with a p value <0.05 from GWAS were reprioritized using post-GWAS analysis and approximately 2700 were identified as SNPs related to RA biological features. The best average accuracy of ten groups was 0.6015 with 85 SNPs, and this increased to 0.7481 when combined with clinical information. In comparisons of the performance of the model, the 0.7872 area under the curve (AUC) in our model was superior to that obtained with GWAS (AUC 0.6586, p value 8.97 × 10-5) or SPOT (AUC 0.7449, p value 0.0423). Our model strategy also showed superior prediction accuracy in Caucasian patients with RA compared with GWAS (p value 0.0049) and SPOT (p value 0.0151).ConclusionsUsing various biological functions of SNPs and repeated machine learning, our model could predict severe radiographic progression relevantly and robustly in patients with RA compared with models using only GWAS results or other post-GWAS tools.

Predictors of severe radiographic progression in patients with early rheumatoid arthritis: A Prospective observational cohort study.

To identify predictors of severe radiographic progression in patients with early rheumatoid arthritis (ERA). A total of 374 patients with ERA were selected from a Korean prospective cohort. Based on their annual Sharp/Van der Heijde modified score changes (ΔSHS/year), patients were classified into severe and no progression groups. Predictors of severe progression were evaluated using a multivariable logistic regression. After a mean follow-up duration of 4.2 years, the median (interquartile range) ΔSHS/year were 6.3 (4.4-10.2) and 0 (0-0) in the severe and no progression groups, respectively. Multivariable regression model revealed that Health Assessment Questionnaire (HAQ) score (odds ratio [OR] = 2.17), anticyclic citrullinated peptide antibody (OR = 3.44), body mass index (BMI; OR = 0.88), 6-month cumulative erythrocyte sedimentation rate (OR = 1.01) and baseline SHS (OR = 1.07) were independent predictors of severe progression. A model incorporating all five predictors satisfactorily predicted severe progression, with an area under the curve of 0.80. Baseline SHS was the predictor with the highest contribution to the predictive power of the final model (38%). Our predictive model composed of five clinical predictors showed high discriminative ability between severe and no radiographic progression in patients with ERA. Among them, baseline SHS was the strongest predictor. Also, low BMI in Korean patients with ERA have a high risk of severe radiographic progression, as has previously been found for Caucasians.

The association between anti-carbamylated protein (anti-CarP) antibodies and radiographic progression in early rheumatoid arthritis: a study exploring replication and the added value to ACPA and rheumatoid factor

ObjectiveAnti-carbamylated protein (anti-CarP) antibodies are reported to associate with more radiographic progression within the total rheumatoid arthritis (RA) population and anti-citrullinated peptide antibody (ACPA)-negative subgroup. We explored the association of...

Association of valine and leucine at HLA-DRB1 position 11 with radiographic progression in rheumatoid arthritis, independent of the shared epitope alleles but not independent of anti-citrullinated protein antibodies.

For decades it has been known that the HLA-DRB1 shared epitope (SE) alleles are associated with an increased risk of development and progression of rheumatoid arthritis (RA). Recently, the following variations in the peptide-binding grooves of HLA molecules that predispose to RA development have been identified: Val and Leu at HLA-DRB1 position 11, Asp at HLA-B position 9, and Phe at HLA-DPB1 position 9. This study was undertaken to investigate whether these variants are also associated with radiographic progression in RA, independent of SE and anti-citrullinated protein antibody (ACPA) status. A total of 4,911 radiograph sets from 1,878 RA patients included in the Leiden Early Arthritis Clinic (The Netherlands), Umeå (Sweden), Hospital Clinico San Carlos-Rheumatoid Arthritis (Spain), and National Data Bank for Rheumatic Diseases (US) cohorts were studied. HLA was imputed using single-nucleotide polymorphism data from an Immunochip, and the amino acids listed above were tested in relation to radiographic progression per cohort using an additive model. Results from the 4 cohorts were combined in inverse-variance weighted meta-analyses using a fixed-effects model. Analyses were conditioned on SE and ACPA status. Val and Leu at HLA-DRB1 position 11 were associated with more radiographic progression (meta-analysis P = 5.11 × 10(-7)); this effect was independent of SE status (meta-analysis P = 0.022) but not independent of ACPA status. Phe at HLA-DPB1 position 9 was associated with more severe radiographic progression (meta-analysis P = 0.024), though not independent of SE status. Asp at HLA-B position 9 was not associated with radiographic progression. Val and Leu at HLA-DRB1 position 11 conferred a risk of a higher rate of radiographic progression independent of SE status but not independent of ACPA status. These findings support the relevance of these amino acids at position 11.

Fatigue in rheumatoid arthritis; a persistent problem: a large longitudinal study

ObjectiveFatigue is prevalent and disabling in rheumatoid arthritis (RA). Surprisingly, the long-term course of fatigue is studied seldom and it is unclear to what extent it is influenced by inflammation....

IL10 GGC Haplotype Is Positively and HLA-DQA1*05-DQB1*02 Is Negatively Associated with Radiographic Progression in Undifferentiated Arthritis

In rheumatoid arthritis (RA), many genetic markers, such as the shared-epitope (SE) alleles, are described in association with radiographic progression, but limited data are available on undifferentiated arthritis (UA). We investigated whether single-nucleotide polymorphisms (SNP) and haplotypes in immune response genes and HLA class II alleles are associated with radiographic progression in patients with early UA. Progression of radiographic damage was determined in white Dutch patients with early UA after 2 years of followup. Severe progression was defined as an increase in Sharp/van der Heijde Score > or = 5 points after 2 years of followup. The remainder was classified as mild. These SNP were genotyped by Taqman technology: tumor necrosis factor (TNF) -1031, -863, -857, -308, -238; lymphotoxin-alpha (LTA) +368, +252; interleukin 10 (IL10) -2849, -1082, -819; IL1A -889, IL1B -31, +3953; and IL1RN +2018. Carriage of SE alleles and HLA-DQA1*05-DQB1*02 haplotype was established. These markers were analyzed in relation to radiographic progression. Forty-eight out of 151 patients with early UA had severe radiographic progression. Severe radiographic progression was associated with an increased carrier frequency of SE alleles (OR 5.12, 95% CI 2.0-13.1, p < 0.001) and IL10 GGC haplotype (OR 2.8, 95% CI 1.4-5.8, p = 0.003). Mild radiographic progression was associated with the HLA-DQA1*05-DQB1*02 haplotype (OR 0.3, 95% CI, 0.1-0.8, p = 0.013) and with allele TNF -308A (OR 0.4, 95% CI, 0.2-0.9, p = 0.02). The SE and the IL10 GGC haplotype are associated with severe progression of radiographic damage, in contrast to the DQA1*05-DQB1*02 haplotype and the TNF -308A allele, which are associated with mild radiographic progression in early UA.