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Background: Radiographic 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., Methods: We 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., Results: A 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)., Conclusions: Using 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.

Background: The aim of this study was to investigate the prevalence of osteoporosis in rheumatoid arthritis (RA) patients and to analyze the risk factors in these patients using the KORean Observational study Network for Arthritis (KORONA) database., Methods: Among the RA patients in the KORONA who were recruited between July 2009 and December 2011, postmenopausal women with bone mineral density (BMD) results within one year from the time of KORONA enrollment were included in this study. The baseline characteristics of patients in three groups, defined by BMD results, were compared. The BMD measurement rates and prevalence of osteoporosis in the study patients were calculated in accordance with age and gender subgroups. Multivariable logistic regression analysis was used to explore the association between osteoporosis and demographics and disease-related risk factors., Results: Of 1322 postmenopausal woman patients with RA in whom BMD was measured within one year of study enrollment, 619 patients (46.8 %) were in the osteoporosis group (T-score ≤ -2.5 SD). RA patients with osteoporosis had a higher frequency of previous fractures than those in other groups, especially fractures of the femur (p = 0.004) and wrist (p = 0.042). Advanced age (≥70 years; OR = 2.28, 95 % CI: 1.40-3.58), lower body mass index (<25; OR = 2.14, 95 % CI:1.52-3.02), longer disease duration (≥10 years; OR = 1.46, 95 % CI: 1.07-2.00), higher cumulative glucocorticoid dose (OR = 1.03, 95 % CI: 1.01-1.05), and higher Health Assessment Questionnaire score (OR = 1.37, 95 % CI:1.11-1.69) were independent risk factors for osteoporosis., Conclusion: A large percentage (90.8 %) of RA patients enrolled in the KORONA cohort had osteoporosis and osteopenia. Nevertheless, BMD measurement rates in this population remained low, despite high risk groups of fractures.

Background: Rheumatoid arthritis (RA) has been known to be associated with increased risk of cardiovascular disease (CVD). The aim of this study was to investigate the effects of Tai Chi exercise on CVD risk in elderly women with RA., Method: In total, 56 female patients with RA were assigned to either a Tai Chi exercise group (29 patients) receiving a 3-month exercise intervention once a week or a control group (27 patients) receiving general information about the benefits of exercise. All participants were assessed at baseline and at 3 months for RA disease activity (Disease Activity Score 28 and Routine Assessment of Patient Index Data 3), functional disability (Health Assessment Questionnaire), CVD risk factors (blood pressure, lipids profile, body composition, and smoking), and three atherosclerotic measurements: carotid intima-media thickness, flow-mediated dilatation (FMD), and brachial-ankle pulse wave velocity (baPWV)., Results: FMD, representative of endothelial function, significantly increased in the Tai Chi exercise group (initial 5.85 ± 2.05 versus 3 months 7.75 ± 2.53%) compared with the control group (initial 6.31 ± 2.12 versus 3 months 5.78 ± 2.13%) (P = 1.76 × 10(-3)). Moreover, baPWV, representative of arterial stiffness, significantly decreased in the Tai Chi exercise group (initial 1693.7 ± 348.3 versus 3 months 1600.1 ± 291.0 cm/s) compared with the control group (initial 1740.3 ± 185.3 versus 3 months 1792.8 ± 326.1 cm/s) (P = 1.57 × 10(-2)). In addition, total cholesterol decreased significantly in the Tai Chi exercise group compared with the control group (-7.8 ± 15.5 versus 2.9 ± 12.2 mg/dl, P = 2.72 × 10(-2)); other changes in RA-related characteristics were not significantly different between the two groups. Tai Chi exercise remained significantly associated with improved endothelial function (FMD; P = 4.32 × 10(-3)) and arterial stiffness (baPWV; P = 2.22 × 10(-2)) after adjustment for improvement in total cholesterol level., Conclusion: Tai Chi exercise improved endothelial dysfunction and arterial stiffness in elderly women with RA, suggesting that it can be a useful behavioral strategy for CVD prevention in patients with RA.

Introduction: The presence of the HLA-B*27 allele is a major risk factor for the development of ankylosing spondylitis (AS), which causes chronic inflammation of the spine and other sites. We investigated residual effects outside HLA-B within the major histocompatibility complex (MHC) region in the Korean population., Methods: Using the Korean HLA reference panel, we inferred the classic HLA alleles and amino-acid residues of the six HLA genes (HLA-A, -B, -C, -DPB1, -DQB1, and -DRB1) and MHC single-nucleotide polymorphisms in 3820 Korean subjects, including 654 Korean cases of AS and 3166 controls, who were genotyped by using Immunochip. Logistic regression and log-likelihood ratio tests were used in AS association tests for imputed markers., Results: The most significant associations were identified at amino-acid positions in the epitope-binding site of HLA-B (P = 1.71 × 10(-481) at position 70, P = 7.20 × 10(-479) at position 97, and P = 2.54 × 10(-484) at positions 114), highlighting the risk effect of the HLA-B*27 allele and the protective effects of other classic alleles. A secondary effect was located at the leucine at amino-acid position 116 in the epitope-binding site of HLA-C (P = 1.69 × 10(-14)), completely tagging the HLA-C*15:02 allele. This residue had a large effect in HLA-B*27-negative patients (odds ratio = 6.6, 95 % confidence interval = 3.8 to 11.4)., Conclusions: The four amino-acid positions of HLA-B and -C account for most of the associations between AS and MHC in the Korean population. This finding updates the list of AS susceptibility loci and provides new insight into AS pathogenesis mediated by MHC class I molecules.

Introduction: Although it has been suggested that rare coding variants could explain the substantial missing heritability, very few sequencing studies have been performed in rheumatoid arthritis (RA). We aimed to identify novel functional variants with rare to low frequency using targeted exon sequencing of RA in Korea., Methods: We analyzed targeted exon sequencing data of 398 genes selected from a multifaceted approach in Korean RA patients (n = 1,217) and controls (n = 717). We conducted a single-marker association test and a gene-based analysis of rare variants. For meta-analysis or enrichment tests, we also used ethnically matched independent samples of Korean genome-wide association studies (GWAS) (n = 4,799) or immunochip data (n = 4,722)., Results: After stringent quality control, we analyzed 10,588 variants of 398 genes from 1,934 Korean RA case controls. We identified 13 nonsynonymous variants with nominal association in single-variant association tests. In a meta-analysis, we did not find any novel variant with genome-wide significance for RA risk. Using a gene-based approach, we identified 17 genes with nominal burden signals. Among them, VSTM1 showed the greatest association with RA (P = 7.80 × 10-4). In the enrichment test using Korean GWAS, although the significant signal appeared to be driven by total genic variants, we found no evidence for enriched association of coding variants only with RA., Conclusions: We were unable to identify rare coding variants with large effect to explain the missing heritability for RA in the current targeted resequencing study. Our study raises skepticism about exon sequencing of targeted genes for complex diseases like RA.

Genotype-expression association analysis using linear regression may produce different test results depending on whether founders only or all pedigreed members are used. This difference is not due to the correlation of samples within a pedigree, because linear mixed models have been applied to account for that correlation. We investigated the possibility that the difference is due to a dependence of expression levels on, among other things, the generation number in the pedigree. Indeed, of the 30 or so studied expression quantitative traits, several of them show significant dependence on the generation number. We propose to use all pedigree members in genotype-expression association analyses whenever the complete genotyping information is available.