Patients with ACPA-positive and ACPA-negative rheumatoid arthritis show different serological autoantibody repertoires and autoantibody associations with disease activity.

Patients with rheumatoid arthritis (RA) can test either positive or negative for circulating anti-citrullinated protein antibodies (ACPA) and are thereby categorized as ACPA-positive (ACPA+) or ACPA-negative (ACPA-), respectively. In this study, we aimed to elucidate a broader range of serological autoantibodies that could further explain immunological differences between patients with ACPA+ RA and ACPA- RA. On serum collected from adult patients with ACPA+ RA (n = 32), ACPA- RA (n = 30), and matched healthy controls (n = 30), we used a highly multiplex autoantibody profiling assay to screen for over 1600 IgG autoantibodies that target full-length, correctly folded, native human proteins. We identified differences in serum autoantibodies between patients with ACPA+ RA and ACPA- RA compared with healthy controls. Specifically, we found 22 and 19 autoantibodies with significantly higher abundances in ACPA+ RA patients and ACPA- RA patients, respectively. Among these two sets of autoantibodies, only one autoantibody (anti-GTF2A2) was common in both comparisons; this provides further evidence of immunological differences between these two RA subgroups despite sharing similar symptoms. On the other hand, we identified 30 and 25 autoantibodies with lower abundances in ACPA+ RA and ACPA- RA, respectively, of which 8 autoantibodies were common in both comparisons; we report for the first time that the depletion of certain autoantibodies may be linked to this autoimmune disease. Functional enrichment analysis of the protein antigens targeted by these autoantibodies showed an over-representation of a range of essential biological processes, including programmed cell death, metabolism, and signal transduction. Lastly, we found that autoantibodies correlate with Clinical Disease Activity Index, but associate differently depending on patients' ACPA status. In all, we present candidate autoantibody biomarker signatures associated with ACPA status and disease activity in RA, providing a promising avenue for patient stratification and diagnostics.

Plasma metabolomic profiling in patients with rheumatoid arthritis identifies biochemical features predictive of quantitative disease activity.

BACKGROUND: Rheumatoid arthritis (RA) is a chronic, autoimmune disorder characterized by joint inflammation and pain. In patients with RA, metabolomic approaches, i.e., high-throughput profiling of small-molecule metabolites, on plasma or serum has thus far enabled the discovery of biomarkers for clinical subgroups, risk factors, and predictors of treatment response. Despite these recent advancements, the identification of blood metabolites that reflect quantitative disease activity remains an important challenge in precision medicine for RA. Herein, we use global plasma metabolomic profiling analyses to detect metabolites associated with, and predictive of, quantitative disease activity in patients with RA. METHODS: Ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was performed on a discovery cohort consisting of 128 plasma samples from 64 RA patients and on a validation cohort of 12 samples from 12 patients. The resulting metabolomic profiles were analyzed with two different strategies to find metabolites associated with RA disease activity defined by the Disease Activity Score-28 using C-reactive protein (DAS28-CRP). More specifically, mixed-effects regression models were used to identify metabolites differentially abundant between two disease activity groups ("lower", DAS28-CRP ≤ 3.2; and "higher", DAS28-CRP > 3.2) and to identify metabolites significantly associated with DAS28-CRP scores. A generalized linear model (GLM) was then constructed for estimating DAS28-CRP using plasma metabolite abundances. Finally, for associating metabolites with CRP (an indicator of inflammation), metabolites differentially abundant between two patient groups ("low-CRP", CRP ≤ 3.0 mg/L; "high-CRP", CRP > 3.0 mg/L) were investigated. RESULTS: We identified 33 metabolites differentially abundant between the lower and higher disease activity groups (P < 0.05). Additionally, we identified 51 metabolites associated with DAS28-CRP (P < 0.05). A GLM based upon these 51 metabolites resulted in higher prediction accuracy (mean absolute error [MAE] ± SD: 1.51 ± 1.77) compared to a GLM without feature selection (MAE ± SD: 2.02 ± 2.21). The predictive value of this feature set was further demonstrated on a validation cohort of twelve plasma samples, wherein we observed a stronger correlation between predicted and actual DAS28-CRP (with feature selection: Spearman's ρ = 0.69, 95% CI: [0.18, 0.90]; without feature selection: Spearman's ρ = 0.18, 95% CI: [-0.44, 0.68]). Lastly, among all identified metabolites, the abundances of eight were significantly associated with the CRP patient groups while controlling for potential confounders (P < 0.05). CONCLUSIONS: We demonstrate for the first time the prediction of quantitative disease activity in RA using plasma metabolomes. The metabolites identified herein provide insight into circulating pro-/anti-inflammatory metabolic signatures that reflect disease activity and inflammatory status in RA patients.

Longitudinal Occurrence and Predictors of Patient-Provider Discordance Between Global Assessments of Disease Activity in Rheumatoid Arthritis: A Case-Control Study.

OBJECTIVE: To identify longitudinal predictors of discordance between patients with rheumatoid arthritis (RA) and their health care providers, where patient global assessment of disease activity is substantially higher than provider global assessment. METHODS: This retrospective case-control study included 102 cases with positive discordance (i.e., ≥25 mm between patient and provider global assessments) and 102 controls without discordance who were matched for age, sex, RA duration, and Clinical Disease Activity Index (CDAI) score. Data were collected at the baseline visit (date of diagnosis or earliest available visit), the index visit (participation in a previous cross-sectional study), and at up to 11 additional visits before the index visit. Data included patient characteristics, disease activity measures, Disease Activity Score in 28 joints (3-variable) using the C-reactive protein level (DAS28-CRP), and medications. Data were analyzed by using linear and logistic regression models with smoothing splines for nonlinear trends. RESULTS: Overall, the mean age was 63 years, 75% of patients were female, and the mean RA duration was 10 years. Compared with controls, cases had higher rates of discordant visits during the 4 years before the index visit, and they had a higher CDAI score and DAS28-CRP earlier in the disease course. Cases more frequently had antinuclear antibodies, nonerosive disease, prior depression, or prior use of antidepressants or fibromyalgia medications. Disease-modifying medication use was not different between cases and controls. CONCLUSION: The findings inform new hypotheses about the relationships of disease activity and antinuclear antibodies to the later occurrence of positive discordance among patients with RA.

Time trends in incidence, clinical features, and cardiovascular disease in ankylosing spondylitis over three decades: a population-based study.

OBJECTIVE: To determine trends in the incidence and clinical presentation of ankylosing spondylitis (AS), the incidence of cardiovascular disease (CVD), and cardiovascular (CV) risk factors among patients with AS and compare the observed incidence of CVD with that predicted by the Framingham Risk Score (FRS). METHODS: A population-based inception cohort of residents of Olmsted County, Minnesota age ≥18 years who fulfilled Modified New York Criteria for AS in 1980-2009 was assembled. Clinical features at presentation were recorded. Age- and sex-adjusted incidence rates and survival were estimated. Incident CVD and CV risk factors were identified. The 10-year CVD risk was calculated using the FRS. Standardized incidence ratios (ratios of observed CVD in AS to that predicted by the FRS) were calculated. RESULTS: Eighty-six patients were diagnosed with AS over the study period with an age- and sex-adjusted incidence of 3.1 per 100,000 (95% confidence interval [95% CI] 2.5-3.8). The mean age at diagnosis was 35 years (range 19-69 years). Inflammatory back pain, seen in 90% of patients, was the most common presenting manifestation. The 10-year mean ± SD cumulative incidence of CVD was 15.8% ± 6.1%, three times higher than the predicted events based on the FRS (standardized incidence ratio 3.01, 95% CI 1.35-6.69; P = 0.007). Overall survival was similar to the general population. CONCLUSION: AS occurs in approximately 3 persons per 100,000 per year. Clinical features, extraarticular manifestations, and interval from symptom onset to diagnosis have remained constant in this population over the study period. The CVD risk in these patients is higher than expected and underestimated by the FRS.