Citations

Objective To identify clusters of comorbidities in patients with rheumatoid arthritis (RA) using 4 methods and to compare to patients without RA. Methods In this retrospective, population‐based study, residents of 8 Minnesota counties with prevalent RA as of January 1, 2015 were identified. Age‐, sex‐, and county‐matched non‐RA comparators were selected from the same underlying population. Diagnostic codes were retrieved for 5 years before January 1, 2015. Using 2 codes ≥30 days apart, 44 previously defined morbidities and 11 nonoverlapping chronic disease categories based on Clinical Classifications Software were defined. Unsupervised machine learning methods of interest included hierarchical clustering, factor analysis, K‐means clustering, and network analysis. Results Two groups of 1,643 patients with and without RA (72% female; mean age 63.1 years in both groups) were studied. Clustering of comorbidities revealed strong associations among mental/behavioral comorbidities and among cardiovascular risk factors and diseases. The clusters were associated with age and sex. Differences between the 4 clustering methods were driven by comorbidities that are rare and those that were weakly associated with other comorbidities. Common comorbidities tended to group together consistently across approaches. The instability of clusters when using different random seeds or bootstrap sampling impugns the usefulness and reliability of these methods. Clusters of common comorbidities between RA and non‐RA cohorts were similar. Conclusion Despite the higher comorbidity burden in patients with RA compared to the general population, clustering comorbidities did not identify substantial differences in comorbidity patterns between the RA and non‐RA cohorts. The instability of clustering methods suggests caution when interpreting clustering using 1 method.

Abstract Objectives To investigate the associations of the common MUC5B promoter variant with timing of RA-associated interstitial lung disease (RA-ILD) and RA onset. Methods We identified patients with RA meeting 2010 ACR/EULAR criteria and available genotype information in the Mass General Brigham Biobank, a multihospital biospecimen and clinical data collection research study. We determined RA-ILD presence by reviewing all RA patients who had CT imaging, lung biopsy or autopsy results. We determined the dates of RA and RA-ILD diagnoses by manual records review. We examined the associations of the MUC5B promoter variant (G>T at rs35705950) with RA-ILD, RA-ILD occurring before or within 2 years of RA diagnosis and RA diagnosis at age >55 years. We used multivariable logistic regression to estimate odds ratios (ORs) for each outcome by MUC5B promoter variant status, adjusting for potential confounders including genetic ancestry and smoking. Results We identified 1005 RA patients with available genotype data for rs35705950 (mean age 45 years, 79% female, 81% European ancestry). The MUC5B promoter variant was present in 155 (15.4%) and was associated with RA-ILD [multivariable OR 3.34 (95% CI 1.97, 5.60)], RA-ILD before or within 2 years of RA diagnosis [OR 4.01 (95% CI 1.78, 8.80)] and RA onset after age 55 years [OR 1.52 (95% CI 1.08, 2.12)]. Conclusions The common MUC5B promoter variant was associated with RA-ILD onset earlier in the RA disease course and older age of RA onset. These findings suggest that the MUC5B promoter variant may impact RA-ILD risk early in the RA disease course, particularly in patients with older-onset RA.

Objective To determine the association of allergic conditions with incident rheumatoid arthritis (RA), especially in relation to smoking history and anti-citrullinated peptide antibody (ACPA) status. Methods This case–control study included 3515 incident RA cases and 5429 matched controls from the Epidemiological Investigation of Rheumatoid Arthritis study 1995 to 2016, including questionnaire-based information on eight allergic conditions composed from a list of 59 unique allergies. We used logistic regression and adjusted ORs (aOR) to assess the association between allergic conditions and risk of RA, adjusting for age, sex, residential area, body mass index, education, and smoking, and stratified by smoking and ACPA. Results A history of any reported allergy was equally common in RA (n=1047, 30%) as among population controls (n=1540, 29%), aOR 1.04, 95% CI 0.95 to 1.15. Metal, respiratory, food, plant/pollen and chemical allergies were not associated with risk of RA. By contrast, statistically significant associations were observed for animal dander allergy (6% vs 5%, aOR 1.37, 95% CI 1.03 to 1.82), especially in ACPA-positive RA (aOR 1.46 95% CI 1.06 to 2.01) and for atopic dermatitis, in particular for older and ACPA-negative RA (aOR 2.33, 95% CI 1.37 to 3.96 at age 80). Never smokers with allergic rhinitis also had increased risk of developing RA (aOR 1.30, 95% CI 1.00 to 1.68). Conclusion Most common allergies do not increase risk of RA, nor do they protect against RA. However, some allergic conditions, notably animal dander allergy, atopic dermatitis and allergic rhinitis, were associated with an increased risk for RA.

Objective To comprehensively assess multimorbidity burden in patients with rheumatoid arthritis (RA) in order to unify the multimorbidity definition for RA research and clinical practice. Methods In this population-based study, residents of eight Minnesota counties with prevalent RA on 1 January 2015 were identified. Age, sex and county-matched non-RA comparators were selected from the same population. Diagnostic codes were retrieved for 5 years before 1 January 2015. Using two codes ≥30 days apart, 44 previously defined morbidities and 78 non-overlapping chronic disease categories based on Clinical Classification Software were defined. Prevalence of each morbidity in the RA versus non-RA cohorts was compared using false discovery rate to adjust for multiple comparisons. Morbidities more common in RA than non-RA and those with prevalence ≥5% were retained. Results 1643 patients with RA and 1643 non-RA subjects (72% women; mean age 63.1 years) were studied. Using the 44 morbidities, multimorbidity (defined as 2+ morbidities) was present in 1411 (86%) of RA and 1164 (71%) of non-RA subjects (p<0.001) with 5+ morbidities present in 907 (55%) of RA and 619 (38%) of non-RA (p<0.001). Patients with RA had significantly higher prevalence of 24 of the 44 morbidities compared with non-RA, especially interstitial lung disease, fibromyalgia, osteoarthritis and osteoporosis. Among the additional 78 categories, 7 were significantly higher in RA than non-RA, including organic sleep disorders, vitamin D deficiency and foot ulcers. Conclusion Patients with RA have a higher prevalence of multimorbidity compared with non-RA subjects. These results confirm the list of 44 morbidities and add several other morbidities of interest in RA.

ObjectiveTo identify the incidence, risk factors, and outcomes of rheumatoid arthritis–associated interstitial lung disease (RA‐ILD) and to assess time trends in the incidence and mortality in RA‐ILD.MethodsWe included adult residents of Olmsted County, Minnesota with incident RA between 1999 and 2014. Subjects were followed until death, emigration, or April 30, 2019. ILD was defined as the presence of a radiologist‐defined pattern consistent with ILD on chest computed tomography (CT). When chest CT was absent, the combination of chest radiograph abnormalities compatible with ILD and restrictive pattern on pulmonary function testing was considered consistent with ILD. Potential risk factors included age, sex, smoking, obesity, seropositivity, extraarticular manifestations (EAMs), and medications. For survival analysis, we matched RA‐ILD patients to RA–non‐ILD comparators. The frequency and mortality from clinician‐diagnosed RA‐ILD from 1999 to 2014 was compared against a cohort from 1955 to 1994.ResultsDuring the 1999–2014 time period, 645 individuals (70% women) had incident RA, were a median age of 55.3 years, and 53% never smoked. Twenty‐two patients had ILD before RA, and 51 (67% women) developed ILD during follow‐up. The 20‐year cumulative incidence of RA‐ILD was 15.3%. Ever‐smoking (hazard ratio [HR] 1.92), age at RA onset (HR 1.89 per 10‐year increase), and severe EAMs (HR 2.29) were associated with incident RA‐ILD. The RA‐ILD cases had higher mortality than their matched RA comparators (HR 2.42). Incidence of RA‐ILD was non‐significantly lower from 1999 to 2014 than from 1955 to1994, but mortality was improved.ConclusionsRA‐ILD occurs in nearly 1 in 6 patients with RA within 20 years and is associated with shorter survival. Lack of significant change in RA‐ILD incidence over 6 decades deserves further investigation.

ObjectiveWe aimed to determine the population‐based incidence, prevalence, and mortality of dermatomyositis (DM) using European Alliance of Associations for Rheumatology (EULAR)/American College of Rheumatology (ACR) criteria.MethodsThis population‐based cohort study included incident DM from January 1, 1995 to December 31, 2019. We manually reviewed all individuals with at least 1 code for DM or polymyositis to determine if they met EULAR/ACR criteria, subspecialty physician diagnosis, and/or Bohan and Peter criteria. We age‐ and sex‐adjusted incidence and prevalence estimates to the US non‐Hispanic White year 2000 population and estimated prevalence on January 1, 2015. Standardized mortality ratios (SMRs) with 95% confidence intervals (95% CIs) compared observed to expected mortality adjusting for age, sex, and year.ResultsWe identified 40 cases of verified DM, with 29 cases incident in Olmsted County from 1995 to 2019. The mean age was 57 years, 26 (90%) were female, and 12 (41%) had clinically amyopathic DM (CADM). The median follow‐up time was 8.2 years. The overall adjusted incidence of DM was 1.1 (95% CI 0.7–1.5) per 100,000 person‐years, and prevalence was 13 (95% CI 6–19) per 100,000. The SMR was significantly elevated among the myopathic DM cases (3.1 [95% CI 1.1–6.8]) but not CADM cases (1.1 [95% CI 0.2–3.3]). The positive predictive value of ≥2 DM codes was only 40 of 82 (49%).ConclusionThis population‐based study found that DM incidence and prevalence were higher than previously reported. Mortality was significantly elevated for myopathic DM but not for CADM.

ObjectiveTo investigate the independent relationship of rheumatoid arthritis (RA) to the type and severity of pulmonary patterns on spirometry compared to the pulmonary patterns in general population controls.MethodsIn this cross‐sectional study, we investigated the association of RA with pulmonary function measures on spirometry among subjects in the UK Biobank who underwent spirometry for research purposes. RA cases were identified based on self‐report and current disease‐modifying antirheumatic drug/glucocorticoid use. Controls were subjects without RA from the general population. Outcome measures included continuous forced expiratory volume in 1 second percent predicted (FEV1%) and forced vital capacity percent predicted (FVC%), type of spirometric pattern (restrictive or obstructive), and severity of the restrictive or obstructive pattern. We used multivariable regression to estimate the effects in RA cases compared to the effects in controls, adjusting for age, sex, body mass index, and smoking status/pack‐years.ResultsAmong 350,776 analyzed subjects who underwent spirometry (mean age 56.3 years; 55.8% female; 45.5% ever smokers), we identified 2,008 cases of treated RA. In multivariable analyses, RA was associated with lower FEV1% (β = –2.93 [95% confidence interval (95% CI) –3.63, –2.24]), FVC% (β = –2.08 [95% CI –2.72, –1.45]), and FEV1/FVC (β = –0.008 [95% CI –0.010, –0.005]) compared to controls. RA was additionally associated with restrictive patterns (odds ratio [OR] 1.36 [95% CI 1.21, 1.52]) and obstructive patterns (OR 1.21 [95% CI 1.07, 1.37]) independent of confounders, and was most strongly associated with severe restrictive and obstructive patterns.ConclusionRA is associated with increased odds of restrictive and obstructive patterns, and this relationship is not explained by confounders, including smoking status. In addition to restrictive lung disease, clinicians should also be aware that airway obstruction may be a pulmonary manifestation of RA.

AbstractWomen have up to a fourfold increase in risk for autoimmune disease compared to men. Many explanations have been proposed, including sex hormones, the X chromosome, microchimerism, environmental factors, and the microbiome. However, the mechanism for this autoimmune sex bias remains obscure. In this manuscript, we evaluate the hypothesis that qualitative or quantitative differences in circulating antibodies may explain, at least in part, the pathogenesis of autoimmune disease and its sex bias—especially when considering an evolutionary perspective. Indeed, women have higher absolute levels of antibodies than men, and (auto)antibodies are also associated with most autoimmune diseases. Several facts suggest differences in antibodies may cause increased prevalence of autoimmune disease in women. First, the association between increased quantities of serum antibodies and increased prevalence of autoimmunity is found not only in women, but also in men with Klinefelter syndrome. Second, both serum antibody levels and autoimmunity spike in the postpartum period. Third, a dose–response effect exists between parity and both serum antibodies and prevalence of autoimmune disease. Fourth, many biologically plausible mechanisms explain the association, such as T cell‐dependent activation of B cells and/or VGLL3. The evolutionary underpinning of increased antibodies in women is likely to be protection of offspring from infections. Overall, this evolutionary paradigm can help explain why the phenomenon of autoimmunity occurs preferentially in women and raises the possibility of new treatment options.

Objective The link and interplay between different airway exposures and rheumatoid arthritis (RA) risk are unclear. This study was undertaken to determine whether respiratory disease is associated with development of RA, and specifically to examine this relationship by RA serostatus and smoking exposure. Methods Using data from the Epidemiological Investigation of Rheumatoid Arthritis study, this analysis included 1,631 incident RA cases and 3,283 matched controls recruited from 2006 to 2016. Linking these individuals to the National Patient Register provided information on past acute or chronic, upper or lower respiratory disease diagnoses. For each disease group, we estimated adjusted odds ratios (OR adj ) with 95% confidence intervals (95% CI) for RA, using logistic regression models adjusted for age, sex, residential area, body mass index, and education both overall and stratified by anti–citrullinated protein antibody (ACPA)/rheumatoid factor (RF) status and by smoking status. Results Respiratory disease diagnoses were associated with risk of RA, with an OR adj of 1.2 for acute upper respiratory disease (95% CI 0.8–1.7), 1.4 for chronic upper respiratory disease (95% CI 1.1–1.9), 2.4 for acute lower respiratory disease (95% CI 1.5–3.6), and 1.6 for chronic lower respiratory disease (95% CI 1.5–3.6). These associations were present irrespective of RF or ACPA status, though the association was somewhat stronger for ACPA/RF–positive than ACPA/RF–negative RA. The association between any respiratory disease and RA was stronger for nonsmokers (OR adj 2.1 [95% CI 1.5–2.9]) than for smokers (OR adj 1.2 [95% CI 0.9–1.5]). Conclusion Respiratory diseases increase the risk for both seropositive and seronegative RA, but only among nonsmokers. These findings raise the hypothesis that smoking and airway disease are associated with RA development through partly different mechanisms.

Abstract Objective The study sought to determine the dependence of the Electronic Medical Records and Genomics (eMERGE) rheumatoid arthritis (RA) algorithm on both RA and electronic health record (EHR) duration. Materials and Methods Using a population-based cohort from the Mayo Clinic Biobank, we identified 497 patients with at least 1 RA diagnosis code. RA case status was manually determined using validated criteria for RA. RA duration was defined as time from first RA code to the index date of biobank enrollment. To simulate EHR duration, various years of EHR lookback were applied, starting at the index date and going backward. Model performance was determined by sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve (AUC). Results The eMERGE algorithm performed well in this cohort, with overall sensitivity 53%, specificity 99%, positive predictive value 97%, negative predictive value 74%, and AUC 76%. Among patients with RA duration &lt;2 years, sensitivity and AUC were only 9% and 54%, respectively, but increased to 71% and 85% among patients with RA duration &gt;10 years. Longer EHR lookback also improved model performance up to a threshold of 10 years, in which sensitivity reached 52% and AUC 75%. However, optimal EHR lookback varied by RA duration; an EHR lookback of 3 years was best able to identify recently diagnosed RA cases. Conclusions eMERGE algorithm performance improves with longer RA duration as well as EHR duration up to 10 years, though shorter EHR lookback can improve identification of recently diagnosed RA cases.