ObjectiveDetermine the association between antecedent pharyngitis or tonsillitis and subsequent rheumatic disease.MethodsThis population-based, case-control study identified all incident, criteria-confirmed individuals with rheumatic diseases from 2002-2014, matched to controls 3:1 on age, sex, and length of preceding electronic health record. The primary exposure was pharyngitis or tonsillitis, defined by diagnostic codes (positive predictive value 89% and 70% respectively). We calculated odds ratios (OR) with 95% confidence intervals (CI) for each disease and disease group using logistic regression models adjusting for confounders. Sensitivity analyses studied these associations by time between exposure and incident rheumatic disease (>1-5, >5-10, >10 years), number of codes (1-3, 4-6, 7+), and smoking status.ResultsWe identified 1,427 individuals with incident rheumatic disease matched to 4,281 controls (mean age 61, 67% female). Prior pharyngitis occurred in 25% of cases and 27% of controls, corresponding to decreased odds of any rheumatic disease (OR 0.86, 95% CI 0.74-1.00), rheumatoid arthritis (RA, OR 0.79, 95% CI 0.65-0.98), and lupus (unadjusted OR 0.26, 95% CI 0.11-0.62). Statistically significant lower odds of rheumatic disease were associated with acute pharyngitis, first pharyngitis exposure >10 years prior to index date, and 1-3 pharyngitis codes. Associations between pharyngitis and smoking status also followed these trends. Tonsillitis occurred in only 2% of cases and 1% of controls and was not associated with incident rheumatic disease (OR 1.26, 95% CI 0.77-2.07).ConclusionPreceding pharyngitis was associated with decreased odds of developing rheumatic disease, including lupus and RA. Future studies should replicate these results.

OBJECTIVES:To examine multimorbidity in psoriasis and its association with the development of psoriatic arthritis (PsA). METHODS:A retrospective cohort study was performed using the Rochester Epidemiology Project. Population-based incidence (2000-09) and prevalence (1 January 2010) cohorts of psoriasis were identified by manual chart review. A cohort of individuals without psoriasis (comparators) were identified (1:1 matched on age, sex and county). Morbidities were defined using two or more Clinical Classification Software codes ≥30 days apart within prior 5 years. PsA was defined using ClASsification of Psoriatic ARthritis (CASPAR) criteria. χ2 and rank-sum tests were used to compare morbidities, and age-, sex- and race-adjusted Cox models to examine the association of baseline morbidities in psoriasis with development of PsA. RESULTS:Among 817 incident psoriasis patients, the mean age was 45.2 years with 52.0% females, and 82.0% moderate/severe psoriasis. No multimorbidity differences were found between incident psoriasis patients and comparators. However, in the 1088 prevalent psoriasis patients, multimorbidity was significantly more common compared with 1086 comparators (odds ratio 1.35 and 1.48 for two or more and five or more morbidities, respectively). Over a median 13.3-year follow-up, 23 patients (cumulative incidence: 2.9% by 15 years) developed PsA. Multimorbidity (two or more morbidities) was associated with a 3-fold higher risk of developing PsA. CONCLUSION:Multimorbidity was more common in the prevalent but not incident cohort of psoriasis compared with the general population, suggesting that patients with psoriasis may experience accelerated development of multimorbidity. Moreover, multimorbidity at psoriasis onset significantly increased the risk of developing PsA, highlighting the importance of monitoring multimorbid psoriasis patients for the development of PsA.

Objectives We aimed to cluster patients with rheumatoid arthritis (RA) based on comorbidities and then examine the association between these clusters and RA disease activity and mortality. Methods In this population-based study, residents of an eight-county region with prevalent RA on 1 January 2015 were identified. Patients were followed for vital status until death, last contact or 31 December 2021. Diagnostic codes for 5 years before the prevalence date were used to define 55 comorbidities. Latent class analysis was used to cluster patients based on comorbidity patterns. Standardised mortality ratios were used to assess mortality. Results A total of 1643 patients with prevalent RA (72% female; 94% white; median age 64 years, median RA duration 7 years) were studied. Four clusters were identified. Cluster 1 (n=686) included patients with few comorbidities, and cluster 4 (n=134) included older patients with 10 or more comorbidities. Cluster 2 (n=200) included patients with five or more comorbidities and high prevalences of depression and obesity, while cluster 3 (n=623) included the remainder. RA disease activity and survival differed across the clusters, with cluster 1 demonstrating more remission and mortality comparable to the general population. Conclusions More than 40% of patients with prevalent RA did not experience worse mortality than their peers without RA. The cluster with the worst prognosis (<10% of patients with prevalent RA) was older, had more comorbidities and had less disease-modifying antirheumatic drug and biological use compared with the other clusters. Comorbidity patterns may hold the key to moving beyond a one-size-fits-all perspective of RA prognosis.

Objectives To determine whether antecedent sinusitis is associated with incident rheumatic disease.Methods This population-based case–control study included all individuals meeting classification criteria for rheumatic diseases between 1995 and 2014. We matched three controls to each case on age, sex and length of prior electronic health record history. The primary exposure was presence of sinusitis, ascertained by diagnosis codes (positive predictive value 96%). We fit logistic regression models to estimate ORs for incident rheumatic diseases and disease groups, adjusted for confounders.Results We identified 1729 incident rheumatic disease cases and 5187 matched controls (mean age 63, 67% women, median 14 years electronic health record history). After adjustment, preceding sinusitis was associated with increased risk of several rheumatic diseases, including antiphospholipid syndrome (OR 7.0, 95% CI 1.8 to 27), Sjögren’s disease (OR 2.4, 95% CI 1.1 to 5.3), vasculitis (OR 1.4, 95% CI 1.1 to 1.9) and polymyalgia rheumatica (OR 1.4, 95% CI 1.0 to 2.0). Acute sinusitis was also associated with increased risk of seronegative rheumatoid arthritis (OR 1.8, 95% CI 1.1 to 3.1). Sinusitis was most associated with any rheumatic disease in the 5–10 years before disease onset (OR 1.7, 95% CI 1.3 to 2.3). Individuals with seven or more codes for sinusitis had the highest risk for rheumatic disease (OR 1.7, 95% CI 1.3 to 2.4). In addition, the association between sinusitis and incident rheumatic diseases showed the highest point estimates for never smokers (OR 1.7, 95% CI 1.3 to 2.2).Conclusions Preceding sinusitis is associated with increased incidence of rheumatic diseases, suggesting a possible role for sinus inflammation in their pathogenesis.

Although the etiology of rheumatoid arthritis (RA) is unknown, a strong genetic predisposition and the presence of preclinical antibodies before the onset of symptoms is documented. An expansion of Eggerthella lenta is associated with severe disease in RA. Here, using a humanized mouse model of collagen-induced arthritis, we determined the impact of E. lenta abundance on RA severity. Naïve mice gavaged with E. lenta produce preclinical rheumatoid factor and, when induced for arthritis, develop severe disease. The augmented antibody response was much higher in female mice, and among patients with RA, women had higher average load of E. lenta . Expansion of E. lenta increased CXCL5 and CD4 T cells, and both interleukin-17– and interferon-γ–producing B cells. Further, E. lenta gavage caused gut dysbiosis and decline in amino acids and nicotinamide adenine dinucleotide with an increase in microbe-dependent bile acids and succinyl carnitine causing systemic senescent-like inflammation.

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.

ObjectiveTo assess trends in the incidence of heart failure (HF) in patients with incident rheumatoid arthritis (RA) from 1980 to 2009 and to compare different HF definitions in RA.MethodsThe study population comprised Olmsted County, Minnesota residents with incident RA (age ≥ 18 yrs, 1987 American College of Rheumatology criteria met in 1980-2009). All subjects were followed until death, migration, or April 30, 2019. Incident HF events were defined as follows: (1) meeting the Framingham criteria for HF, (2) diagnosis of HF (outpatient or inpatient) by a physician, or (3) International Classification of Diseases, 9th revision (ICD-9), or ICD, 10th revision (ICD-10), codes for HF. Patients with HF prior to the RA incidence/index date were excluded. Cox proportional hazards models were used to compare incident HF events by decade, adjusting for age, sex, and cardiovascular risk factors. HF definitions 2 and 3 were compared to the Framingham criteria.ResultsThe study included 905 patients with RA (mean age 55.9 years; 68.6% female; median follow-up 13.4 years). The 10-year cumulative incidence of HF events by any chart-reviewed method in the RA cohort in the 1980s was 11.66% (95% CI 7.86-17.29), in the 1990s it was 12.64% (95% CI 9.31-17.17), and in the 2000s it was 7.67% (95% CI 5.36-10.97). The incidence of HF did not change across the decades of RA incidence using any of the HF definitions. Physician diagnosis of HF and ICD-9/10 code-based definitions of HF performed well compared to the Framingham criteria, showing moderate to high sensitivity and specificity.ConclusionThe incidence of HF in patients with incident RA in the 2000s vs the 1980s was not statistically significantly different. Physician diagnosis of HF and ICD-9/10 codes for HF performed well against the Framingham criteria.

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 rho = 0.69, 95% CI: [0.18, 0.90]; without feature selection: Spearman's rho = 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.

Objective To examine demographic and clinical characteristics associated with diagnostic delay in psoriatic arthritis (PsA). Methods We characterized a retrospective, population-based cohort of incident adult (≥ 18 yrs) patients with PsA from Olmsted County, Minnesota, from 2000–2017. All patients met the classification criteria. Diagnostic delay was defined as the time from any patient-reported PsA-related joint symptom to a physician diagnosis of PsA. Factors associated with delay in PsA diagnosis were identified through logistic regression models. Results Of the 164 incident PsA cases from 2000 to 2017, 162 had a physician or rheumatologist diagnosis. Mean (SD) age was 41.5 (12.6) years and 46% were female. Median time from symptom onset to physician diagnosis was 2.5 years (IQR 0.5–7.3). By 6 months, 38 (23%) received a diagnosis of PsA, 56 (35%) by 1 year, and 73 (45%) by 2 years after symptom onset. No significant trend in diagnostic delay was observed over calendar time. Earlier age at onset of PsA symptoms, higher BMI, and enthesitis were associated with a diagnostic delay of > 2 years, whereas sebopsoriasis was associated with a lower likelihood of delay. Conclusion In our study, more than half of PsA patients had a diagnostic delay of > 2 years, and no significant improvement in time to diagnosis was noted between 2000 and 2017. Patients with younger age at PsA symptom onset, higher BMI, or enthesitis before diagnosis were more likely to have a diagnostic delay of > 2 years, whereas patients with sebopsoriasis were less likely to have a diagnostic delay.

Objective: To identify demographic and clinical characteristics associated with time between psoriasis and psoriatic arthritis (PsA). Methods: A retrospective, population-based cohort of incident PsA patients >= 18 years (2000-17) from Olmsted County, MN was identified. PsA patients were divided into two groups: patients with concurrent psoriasis and PsA (within 1 year), and patients with psoriasis before PsA (>1 year). Patients with PsA prior to psoriasis were excluded. Age- and sex-adjusted logistic regression models were used to examine factors associated with the time between psoriasis and PsA diagnosis. Results: Among 164 patients with incident PsA, 158 had a current or personal history of psoriasis. The mean (SD) age at PsA diagnosis was 46.3 (12.0) years, and 46% were females. The median (interquartile range) time from psoriasis to PsA was 35.5 (0.8-153.4) months. 64 patients (41%) patients had concurrent psoriasis and PsA while 94 (59%) had onset of psoriasis before PsA. The estimated age at onset of psoriasis symptom (OR per 10-year decrease = 1.63, 95% CI: 1.26-2.11) and psoriasis severity (OR = 3.65, 95% CI: 1.18-11.32 for severe vs. mild) were associated with having a psoriasis diagnosis more than one year prior to incident PsA. Conclusion: In this population-based study, approximately 60% of the patients had psoriasis before PsA, and the rest had concurrent psoriasis and PsA. Patients with lower age at psoriasis onset or severe psoriasis were more likely to have a longer time to transition from psoriasis to PsA. (c) 2021 Elsevier Inc. All rights reserved.

We thank Luo et. al for their interest in our systematic review.1 They agree with our approach of including observational studies of patients with axial spondyloarthritis (axSpA) in the systematic review in order to study long-term radiographic outcomes, but they critique our handling and interpretation of the observational data. On this point, our perspective is that the well-known shortcomings of observation studies cannot be remedied by systematic reviewers.

Previously, we demonstrated in test and validation cohorts that type I IFN (T1IFN) activity can predict non-response to tumor necrosis factor inhibitors (TNFi) in rheumatoid arthritis (RA). In this study, we examine the biology of non-classical and classical monocytes from RA patients defined by their pre-biologic treatment T1IFN activity. We compared single cell gene expression in purified classical (CL, n = 342) and non-classical (NC, n = 359) monocytes. In our previous work, RA patients who had either high IFNβ/α activity (>1.3) or undetectable T1IFN were likely to have EULAR non-response to TNFi. In this study comparisons were made among patients grouped according to their pre-biologic treatment T1IFN activity as clinically relevant: “T1IFN undetectable (T1IFN ND) or IFNβ/α >1.3” (n = 9) and “T1IFN detectable but IFNβ/α ≤ 1.3” (n = 6). In addition, comparisons were made among patients grouped according to their T1IFN activity itself: “T1IFN ND,” “T1IFN detected and IFNβ/α ≤ 1.3,” and “IFNβ/α >1.3.” Major differences in gene expression were apparent in principal component and unsupervised cluster analyses. CL monocytes from the T1IFN ND or IFNβ/α >1.3 group were unlikely to express JAK1 and IFI27 (p < 0.0001 and p 0.0005, respectively). In NC monocytes from the same group, expression of IFNAR1, IRF1, TNFA, TLR4 (p ≤ 0.0001 for each) and others was enriched. Interestingly, JAK1 expression was absent in CL and NC monocytes from nine patients. This pattern most strongly associated with the IFNβ/α>1.3 group. Differences in gene expression in monocytes among the groups suggest differential IFN pathway activation in RA patients who are either likely to respond or to have no response to TNFi. Additional transcripts enriched in NC cells of those in the T1IFN ND and IFNβ/α >1.3 groups included MYD88, CD86, IRF1, and IL8. This work could suggest key pathways active in biologically defined groups of patients, and potential therapeutic strategies for those patients unlikely to respond to TNFi.

Non-steroidal anti-inflammatory drugs (NSAIDs) and tumor necrosis factor inhibitors (TNFi) are the most common therapies used in AS, however, the associated long-term cardiovascular risk is unclear. We performed a systematic review and meta-analysis on the association of therapies used for ankylosing spondylitis (AS) such as NSAIDs and TNFi on cardiovascular events (CVE) in AS. A comprehensive search was performed from database inception to May 29, 2020 to include controlled studies of AS treated with NSAIDs, oral small molecules, or biologics reporting CVE. Study-specific risk ratios (RR) were pooled using a random effects model. Nine non-randomized studies from 1570 studies screened fulfilled inclusion criteria. Among NSAID users as a whole versus no NSAIDs, no increased risk of CVE (composite outcome) was observed; however, the risk of cerebrovascular accident was significantly lower (RR 0.58, 95% CI 0.37–0.93, I2 = 66%). Cox-2 inhibitor use was associated with reduced risk of all CVE (RR 0.48, 95% CI 0.33–0.70, I2 = 0%). Non-selective NSAIDs were not associated with any increased/decreased risk of any CVE. Meta-analysis of three studies of MI did not show a significant association with TNFi (RR 0.88, 95% CI 0.57–1.35, I2 = 76%). In this meta-analysis of non-randomized studies, NSAID users as a whole and users of non-selective NSAIDs did not seem to have a higher risk of any CVE. Limited data suggest a lower risk of composite CVE outcome with Cox-2 inhibitors, unlike the increased risk reported in the general population. No significant association between TNFi and MI was observed. The certainty in evidence was very low due to all studies being observational. More studies are needed to study the association between TNFi use and CVE in general to evaluate a possible protective role in AS.

ObjectiveTo investigate the effect of therapies on radiographic progression in patients with axial spondyloarthritis (SpA).MethodsA comprehensive database search for studies assessing radiographic progression in axial SpA (particular treatment versus no treatment of interest) was performed. Study‐specific standardized mean differences in treatment outcomes at 2 and ≥4 years were estimated and combined using random‐effects models.ResultsTwenty‐four studies in patients with axial SpA were identified, of which 18 involved tumor necrosis factor inhibitors (TNFi), 8 involved nonsteroidal antiinflammatory drugs (NSAIDs), and 1 involved secukinumab. Spinal radiographic progression, as measured by the modified Stoke Ankylosing Spondylitis Spine Score (mSASSS), was not significantly different between TNFi‐treated and biologics‐naive patients at 2 years (mSASSS difference −0.73 [95% confidence interval (95% CI) −1.52, 0.12], I2 = 28%) and ≥4 years (mSASSS difference −2.03 [95% CI −4.63, 0.72], I2 = 63%). Sensitivity analyses restricted to studies with a low risk of bias showed a significant difference in spinal radiographic progression between TNFi‐treated and biologics‐naive patients at ≥4 years (mSASSS difference −2.17 [95% CI −4.19, −0.15]). No significant difference in spinal radiographic progression was observed between NSAID‐treated and control patients (mSASSS difference −0.30 [95% CI −2.62, 1.31], I2 = 71%) or between secukinumab‐treated and biologics‐naive patients (mSASSS difference −0.34 [95% CI −0.85, 0.17]). With regard to treatment differences in patients with nonradiographic axial SpA or in patients with radiographic progression measured using the sacroiliac joint score, an insufficient number of studies were available for analysis.ConclusionAlthough no significant protective effect of TNFi treatment on spinal radiographic progression was seen over the course of 2 years or ≥4 years in patients with axial SpA, our analysis restricted to studies with a low risk of bias showed a protective effect of TNFi after ≥4 years. Therefore, long‐term TNFi exposure might confer beneficial effects on spinal radiographic progression in axial SpA. No difference in radiographic progression at 2 years was seen in either the NSAID or secukinumab treatment groups compared to their controls. Future studies should explore the effects of biologic treatment on radiographic progression, as well as the effects of long‐term biologics exposure, in patients with early axial SpA or those with nonradiographic axial SpA.