Differences in lipid levels associated with cardiovascular (CV) risk between rheumatoid arthritis (RA) and the general population remain unclear. Determining these differences is important in understanding the role of lipids in CV risk in RA.
We studied 2,005 RA subjects from two large academic medical centers. We extracted electronic medical record (EMR) data on the first low density lipoprotein (LDL), total cholesterol (TChol) and high density lipoprotein (HDL) within 1 year of the LDL. Subjects with an electronic statin prescription prior to the first LDL were excluded.
We compared lipid levels in RA to levels from the general United States population (Carroll, et al., JAMA 2012), using the t-test and stratifying by published parameters, i.e. 2007–2010, women. We determined lipid trends using separate linear regression models for TChol, LDL and HDL, testing the association between year of measurement (1989–2010) and lipid level, adjusted by age and gender. Lipid trends were qualitatively compared to those reported in Carroll, et al.
Women with RA had a significantly lower Tchol (186 vs 200mg/dL, p=0.002) and LDL (105 vs 118mg/dL, p=0.001) compared to the general population (2007–2010). HDL was not significantly different in the two groups. In the RA cohort, Tchol and LDL significantly decreased each year, while HDL increased (all with p<0.0001), consistent with overall trends observed in Carroll, et al.
RA patients appear to have an overall lower Tchol and LDL than the general population, despite the general overall risk of CVD in RA from observational studies.
Rheumatic disease and heart disease share common underpinnings involving inflammation. The high levels of inflammation that characterize rheumatic diseases provide a “natural experiment” to help elucidate the mechanisms by which inflammation accelerates heart disease. Rheumatoid arthritis (RA) is the most common of the rheumatic diseases and has the best studied relationships with heart disease.
Review of current literature on heart disease and rheumatoid arthritis
Patients with RA have an increased risk of developing heart disease that is not fully explained by traditional cardiovascular risk factors. Therapies used to treat RA may also affect the development of heart disease; by suppressing inflammation, they may also reduce the risk of heart disease. However, their other effects, as in the case of steroids, may increase heart disease risk.
Investigations of the innate and adaptive immune responses occurring in RA may delineate novel mechanisms in the pathogenesis of heart disease, and help identify novel therapeutic targets for the prevention and treatment of heart disease.
A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological datasets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here, we performed a genome-wide association study (GWAS) meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single nucleotide polymorphisms (SNPs). We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 1012–4. We devised an in-silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci (cis-eQTL)6, and pathway analyses7–9 – as well as novel methods based on genetic overlap with human primary immunodeficiency (PID), hematological cancer somatic mutations and knock-out mouse phenotypes – to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.
Vitamin D may have an immunological role in Crohn’s disease (CD) and ulcerative colitis (UC). Retrospective studies suggested a weak association between vitamin D status and disease activity but have significant limitations.
Using a multi-institution inflammatory bowel disease (IBD) cohort, we identified all CD and UC patients who had at least one measured plasma 25-hydroxy vitamin D [25(OH)D]. Plasma 25(OH)D was considered sufficient at levels ≥ 30ng/mL. Logistic regression models adjusting for potential confounders were used to identify impact of measured plasma 25(OH)D on subsequent risk of IBD-related surgery or hospitalization. In a subset of patients where multiple measures of 25(OH)D were available, we examined impact of normalization of vitamin D status on study outcomes.
Our study included 3,217 patients (55% CD, mean age 49 yrs). The median lowest plasma 25(OH)D was 26ng/ml (IQR 17–35ng/ml). In CD, on multivariable analysis, plasma 25(OH)D < 20ng/ml was associated with an increased risk of surgery (OR 1.76 (1.24 – 2.51) and IBD-related hospitalization (OR 2.07, 95% CI 1.59 – 2.68) compared to those with 25(OH)D ≥ 30ng/ml. Similar estimates were also seen for UC. Furthermore, CD patients who had initial levels < 30ng/ml but subsequently normalized their 25(OH)D had a reduced likelihood of surgery (OR 0.56, 95% CI 0.32 – 0.98) compared to those who remained deficient.
Low plasma 25(OH)D is associated with increased risk of surgery and hospitalizations in both CD and UC and normalization of 25(OH)D status is associated with a reduction in the risk of CD-related surgery.
Crohn’s disease; ulcerative colitis; vitamin D; surgery; hospitalization
The pathophysiology of shrinking lung syndrome (SLS) is poorly understood. We sought to define the structural basis for this condition through the study of pulmonary mechanics in affected patients.
Since 2007, most patients evaluated for SLS at our institutions have undergone standardized respiratory testing including esophageal manometry. We analyzed these studies to define the physiological abnormalities driving respiratory restriction. Chest computed tomography data were post-processed to quantitate lung volume and parenchymal density.
Six cases met criteria for SLS. All presented with dyspnea as well as pleurisy and/or transient pleural effusions. Chest imaging was free of parenchymal disease and corrected diffusing capacities were normal. Total lung capacities were 39-50% of predicted. Maximal inspiratory pressures were impaired at high lung volumes, but not low lung volumes, in 5 patients. Lung compliance was strikingly reduced in all patients, accompanied by increased parenchymal density.
Patients with SLS exhibited symptomatic and/or radiographic pleuritis associated with two characteristic physiological abnormalities: 1) impaired respiratory force at high but not low lung volumes, and 2) markedly decreased pulmonary compliance in the absence of identifiable interstitial lung disease. These findings suggest a model in which pleural inflammation chronically impairs deep inspiration, for example via neural reflexes, leading to parenchymal reorganization that impairs lung compliance, a known complication of persistently low lung volumes. Together these processes could account for the association of SLS with pleuritis as well as the gradual symptomatic and functional progression that is a hallmark of this syndrome.
Shrinking Lung Syndrome; Pleuritis; Pleurisy; Systemic Lupus Erythematosus; Lung
We developed RA risk models based on validated environmental factors (E), genetic risk scores (GRS), and gene-environment interactions (GEI) to identify factors that can improve accuracy and reclassification.
Models including E, GRS, GEI were developed among 317 Caucasian seropositive RA cases and 551 controls from Nurses’ Health Studies (NHS) and validated in 987 Caucasian ACPA positive cases and 958 controls from the Swedish Epidemiologic Investigation of RA (EIRA), stratified by gender. Primary analyses included age, smoking, alcohol, parity, weighted GRS using 31 non-HLA alleles, 8 HLA-DRB1 alleles and HLA X smoking interaction. Expanded models included reproductive, geographic, and occupational factors, and additional GEI terms. Hierarchical models were compared for discriminative accuracy using AUC and reclassification using Integrated Discrimination Improvement (IDI) and continuous Net Reclassification Index.
Mean (SD) age of RA diagnosis was 57 in NHS and 50 in EIRA. Primary models produced an AUC of 0.716 in NHS, 0.728 in EIRA women and 0.756 in EIRA men. Expanded models produced improvements in discrimination with AUCs of 0.738 in NHS, 0.728 in EIRA women and 0.769 in EIRA men. Models including G or G + GEI improved reclassification over E models; the full E+G+GEI model provided the optimal predictive ability by IDI analyses.
We have developed comprehensive RA risk models incorporating epidemiologic and genetic factors and gene-environment interactions that have improved discriminative accuracy for RA. Further work developing and assessing highly specific prediction models in prospective cohorts is still needed to inform primary RA prevention trials.
Prior studies identifying patients with inflammatory bowel disease (IBD) utilizing administrative codes have yielded inconsistent results. Our objective was to develop a robust electronic medical record (EMR) based model for classification of IBD leveraging the combination of codified data and information from clinical text notes using natural language processing (NLP).
Using the EMR of 2 large academic centers, we created data marts for Crohn’s disease (CD) and ulcerative colitis (UC) comprising patients with ≥ 1 ICD-9 code for each disease. We utilized codified (i.e. ICD9 codes, electronic prescriptions) and narrative data from clinical notes to develop our classification model. Model development and validation was performed in a training set of 600 randomly selected patients for each disease with medical record review as the gold standard. Logistic regression with the adaptive LASSO penalty was used to select informative variables.
We confirmed 399 (67%) CD cases in the CD training set and 378 (63%) UC cases in the UC training set. For both, a combined model including narrative and codified data had better accuracy (area under the curve (AUC) for CD 0.95; UC 0.94) than models utilizing only disease ICD-9 codes (AUC 0.89 for CD; 0.86 for UC). Addition of NLP narrative terms to our final model resulted in classification of 6–12% more subjects with the same accuracy.
Inclusion of narrative concepts identified using NLP improves the accuracy of EMR case-definition for CD and UC while simultaneously identifying more subjects compared to models using codified data alone.
Crohn’s disease; ulcerative colitis; disease cohort; natural language processing; informatics
While genetic determinants of LDL cholesterol levels are well characterized in the general population, they are understudied in rheumatoid arthritis (RA). Our objective was to determine the association of established LDL and RA genetic alleles with LDL levels in RA cases compared to non-RA controls.
Using electronic medical records (EMR) data, we linked validated RA cases and non-RA controls to discarded blood samples. For each individual, we extracted data on: 1st LDL measurement, age, gender, and year of LDL measurement. We genotyped subjects for 11 LDL and 44 non-HLA RA alleles, and calculated RA and LDL genetic risk scores (GRS). We tested the association between each GRS and LDL level using multivariate linear regression models adjusted by age, gender, year of LDL measurement, and RA status.
Among 567 RA cases and 979 controls, 80% were female and the mean age at 1st LDL measurement was 55 years. RA cases had significantly lower mean LDL levels than controls (117.2 vs. 125.6mg/dL, respectively, p<0.0001). Each unit increase in LDL GRS was associated with 0.8mg/dL higher LDL levels in both RA cases and controls (p=3.0×10−7). Each unit increase in RA GRS was associated with 4.3mg/dL lower LDL levels in both groups (p=0.01).
LDL alleles were associated with higher LDL levels in RA. RA alleles were associated with lower LDL levels in both RA cases and controls. Since RA cases carry more RA alleles, these findings suggest a genetic basis for epidemiologic observations of lower LDL levels in RA.
Rheumatoid arthritis; low density lipoprotein; genetics; human leukocyte antigen
Psychiatric co-morbidity is common in Crohn’s disease (CD) and ulcerative colitis (UC). IBD-related surgery or hospitalizations represent major events in the natural history of disease. Whether there is a difference in risk of psychiatric co-morbidity following surgery in CD and UC has not been examined previously.
We used a multi-institution cohort of IBD patients without a diagnosis code for anxiety or depression preceding their IBD-related surgery or hospitalization. Demographic, disease, and treatment related variables were retrieved. Multivariate logistic regression analysis was performed to individually identify risk factors for depression and anxiety.
Our study included a total of 707 CD and 530 UC patients who underwent bowel resection surgery and did not have depression prior to surgery. The risk of depression 5 years after surgery was 16% and 11% in CD and UC respectively. We found no difference in the risk of depression following surgery in CD and UC patients (adjusted OR 1.11, 95%CI 0.84 – 1.47). Female gender, co-morbidity, immunosuppressant use, perianal disease, stoma surgery, and early surgery within 3 years of care predicted depression after CD-surgery; only female gender and co-morbidity predicted depression in UC. Only 12% of the CD cohort had ≥ 4 risk factors for depression, but among them nearly 44% were subsequently received a diagnosis code for depression.
IBD-related surgery or hospitalization is associated with a significant risk for depression and anxiety with a similar magnitude of risk in both diseases.
Crohn’s disease; depression; anxiety; surgery; hospitalization
The significance of non-RA autoantibodies in patients with rheumatoid arthritis (RA) is unclear. We studied associations between autoimmune risk alleles and autoantibodies in RA cases and non-RA controls, and autoantibodies and clinical diagnoses from the electronic medical records (EMR).
We studied 1,290 RA cases and 1,236 non-RA controls of European genetic ancestry from the EMR from two large academic centers. We measured antibodies to citrullinated peptides (ACPA), anti-nuclear antibodies (ANA), antibodies to tissue transglutaminase (anti-tTG), antibodies to thyroid peroxidase (anti-TPO). We genotyped subjects for autoimmune risk alleles, and studied the association between number of autoimmune risk alleles and number of types of autoantibodies present. We conducted a phenome-wide association study (PheWAS) to study potential associations between autoantibodies and clinical diagnoses among RA cases and controls.
Mean age was 60.7 in RA and 64.6 years in controls, and both were 79% female. The prevalence of ACPA and ANA was higher in RA cases compared to controls (p<0.0001, both); we observed no difference in anti-TPO and anti-tTG. Carriage of higher numbers of autoimmune risk alleles was associated with increasing types of autoantibodies in RA cases (p=4.4x10−6) and controls (p=0.002). From the PheWAS, ANA was significantly associated with Sjogren’s/siccain RA cases.
The increased frequency of autoantibodies in RA cases and controls was associated with the number of autoimmune risk alleles carried by an individual. PheWAS analyses within the EMR linked to blood samples provide a novel method to test for the clinical significance of biomarkers in disease.
Psychiatric co-morbidity, in particular major depression and anxiety is common in patients with Crohn’s disease (CD) and ulcerative colitis (UC). Prior studies examining this may be confounded by the co-existence of functional bowel symptoms. Limited data exists examining an association between depression or anxiety and disease-specific endpoints such as bowel surgery.
Using a multi-institution cohort of patients with CD and UC, we identified those who also had co-existing psychiatric co-morbidity (major depressive disorder or generalized anxiety). After excluding those diagnosed with such co-morbidity for the first time following surgery, we used multivariate logistic regression to examine the independent effect of psychiatric co-morbidity on IBD-related surgery and hospitalization. To account for confounding by disease severity, we adjusted for a propensity score estimating likelihood of psychiatric co-morbidity influenced by severity of disease in our models.
A total of 5,405 CD and 5,429 UC patients were included in this study; one-fifth had either major depressive disorder or generalized anxiety. In multivariate analysis, adjusting for potential confounders and the propensity score, presence of mood or anxiety co-morbidity was associated with a 28% increase in risk of surgery in CD (OR 1.28, 95% CI 1.03 – 1.57) but not UC (OR 1.01, 95% CI 0.80 – 1.28). Psychiatric co-morbidity was associated with increased healthcare utilization.
Depressive disorder or generalized anxiety is associated with a modestly increased risk of surgery in patients with CD. Interventions addressing this may improve patient outcomes.
Crohn’s disease; ulcerative colitis; depression; surgery; hospitalization
Multiple studies demonstrate an increased cardiovascular (CV) risk associated with RA compared with the general population. While part of this risk appears to be mediated by RA-specific factors, such as long-term inflammation, traditional CV comorbidities also play an important role. We review evidence from previous studies of the relationship between RA and traditional CV comorbidities such as dyslipidaemia, obesity, insulin resistance and diabetes, hypertension, cigarette smoking and physical inactivity. We examine the prevalence and consider the effect of inflammation and RA treatments on these risk factors. Finally, we discuss three widely used CV risk estimators, the Framingham Risk Score, Reynolds Risk Score and the Systematic Coronary Risk Evaluation, and their performance in patients with RA. The traditional CV risk factors that appear to differ significantly between RA cases and controls include insulin resistance, abnormal fat distribution, cigarette smoking and lack of physical activity. Dyslipidaemia, diabetes and hypertension may also be elevated in RA; however, the evidence is conflicting. Overall, we found that the majority of information regarding CV risk factors in RA stems from data collected as covariates for studies on CV disease. A gap in knowledge exists regarding detailed information on individual risk factors in RA, their prevalence and modifications that occur as a result of inflammation or treatment. More studies are needed to develop methods for accurate CV risk estimation in RA.
rheumatoid arthritis; traditional cardiovascular risk factors; cardiovascular disease; coronary artery disease; coronary heart disease; inflammation; C-reactive protein; Reynolds risk score/calculator; Framingham risk score/calculator; hypertension
To optimally leverage the scalability and unique features of the electronic health records (EHR) for research that would ultimately improve patient care, we need to accurately identify patients and extract clinically meaningful measures. Using multiple sclerosis (MS) as a proof of principle, we showcased how to leverage routinely collected EHR data to identify patients with a complex neurological disorder and derive an important surrogate measure of disease severity heretofore only available in research settings.
In a cross-sectional observational study, 5,495 MS patients were identified from the EHR systems of two major referral hospitals using an algorithm that includes codified and narrative information extracted using natural language processing. In the subset of patients who receive neurological care at a MS Center where disease measures have been collected, we used routinely collected EHR data to extract two aggregate indicators of MS severity of clinical relevance multiple sclerosis severity score (MSSS) and brain parenchymal fraction (BPF, a measure of whole brain volume).
The EHR algorithm that identifies MS patients has an area under the curve of 0.958, 83% sensitivity, 92% positive predictive value, and 89% negative predictive value when a 95% specificity threshold is used. The correlation between EHR-derived and true MSSS has a mean R2 = 0.38±0.05, and that between EHR-derived and true BPF has a mean R2 = 0.22±0.08. To illustrate its clinical relevance, derived MSSS captures the expected difference in disease severity between relapsing-remitting and progressive MS patients after adjusting for sex, age of symptom onset and disease duration (p = 1.56×10−12).
Incorporation of sophisticated codified and narrative EHR data accurately identifies MS patients and provides estimation of a well-accepted indicator of MS severity that is widely used in research settings but not part of the routine medical records. Similar approaches could be applied to other complex neurological disorders.
Electronic health records (EHR) can allow for the generation of large cohorts of individuals with given diseases for clinical and genomic research. A rate-limiting step is the development of electronic phenotype selection algorithms to find such cohorts. This study evaluated the portability of a published phenotype algorithm to identify rheumatoid arthritis (RA) patients from EHR records at three institutions with different EHR systems.
Materials and Methods
Physicians reviewed charts from three institutions to identify patients with RA. Each institution compiled attributes from various sources in the EHR, including codified data and clinical narratives, which were searched using one of two natural language processing (NLP) systems. The performance of the published model was compared with locally retrained models.
Applying the previously published model from Partners Healthcare to datasets from Northwestern and Vanderbilt Universities, the area under the receiver operating characteristic curve was found to be 92% for Northwestern and 95% for Vanderbilt, compared with 97% at Partners. Retraining the model improved the average sensitivity at a specificity of 97% to 72% from the original 65%. Both the original logistic regression models and locally retrained models were superior to simple billing code count thresholds.
These results show that a previously published algorithm for RA is portable to two external hospitals using different EHR systems, different NLP systems, and different target NLP vocabularies. Retraining the algorithm primarily increased the sensitivity at each site.
Electronic phenotype algorithms allow rapid identification of case populations in multiple sites with little retraining.
Automated learning; biomedical informatics; discovery and text and data mining methods; electronic health record; genetic; improving the education and skills training of health professionals; infection control; knowledge representations; linking the genotype and phenotype; medical informatics; natural language processing; other methods of information extraction; phenotype algorithms DNA databank machine learning; phenotype identification; phenotyping; rheumatoid arthritis; rheumatology; translational research – application of biological knowledge to clinical care
Objective. Treatment algorithms in RA include factors associated with poor prognosis; however, many patients remain erosion free despite years of disease. Our objective was to characterize the group of RA patients without erosions and identify its clinical predictors.
Methods. Our study was conducted within a prospective observational cohort of RA patients recruited from the outpatient practice of an academic medical centre. We studied patients with bilateral hand radiographs at cohort baseline and 2-year follow-up assessed with Sharp/van der Heijde scores (SHS). The primary outcome was erosion-free status at baseline and 2-year follow-up. We assessed baseline values of the following as potential correlates: age at RA onset, gender, RA duration, BMI, 28-joint DAS (DAS-28), CRP, anti-CCP status, tender and swollen joint counts, functional status [multidimensional HAQ (MDHAQ)], tobacco use and RA treatments. Variables with P ≤ 0.25 in the univariate analyses were assessed using backward selection in multivariable logistic regression models.
Results. Of the 271 subjects included, 21% (n = 56) were considered erosion free. Forty-six per cent (n = 26) of this group was anti-CCP positive compared with 56% (n = 121) in subjects with erosions present. Mean RA duration for erosion-free subjects was 3.9 years compared with 4.6 years in erosive subjects. Treatments for RA did not differ between the two groups. In the multivariable-adjusted analysis, significant predictors of erosion-free status were younger age at onset and shorter RA duration.
Conclusion. In our cohort, 21% of subjects were erosion free at baseline and 2 years. Few baseline clinical characteristics significantly predicted erosion-free status.
Rheumatoid arthritis; Disease progression; Prognosis
Cumulative genetic profiles can help identify individuals at high-risk for developing RA. We examined the impact of 39 validated genetic risk alleles on the risk of RA phenotypes characterized by serologic and erosive status.
We evaluated single nucleotide polymorphisms at 31 validated RA risk loci and 8 Human Leukocyte Antigen alleles among 542 Caucasian RA cases and 551 Caucasian controls from Nurses' Health Study and Nurses' Health Study II. We created a weighted genetic risk score (GRS) and evaluated it as 7 ordinal groups using logistic regression (adjusting for age and smoking) to assess the relationship between GRS group and odds of developing seronegative (RF− and CCP−), seropositive (RF+ or CCP+), erosive, and seropositive, erosive RA phenotypes. In separate case only analyses, we assessed the relationships between GRS and age of symptom onset.
In 542 RA cases, 317 (58%) were seropositive, 163 (30%) had erosions and 105 (19%) were seropositive with erosions. Comparing the highest GRS risk group to the median group, we found an OR of 1.2 (95% CI = 0.8–2.1) for seronegative RA, 3.0 (95% CI = 1.9–4.7) for seropositive RA, 3.2 (95% CI = 1.8–5.6) for erosive RA, and 7.6 (95% CI = 3.6–16.3) for seropositive, erosive RA. No significant relationship was seen between GRS and age of onset.
Results suggest that seronegative and seropositive/erosive RA have different genetic architecture and support the importance of considering RA phenotypes in RA genetic studies.
The American College of Rheumatology and the European League Against Rheumatism have developed new classification criteria for rheumatoid arthritis (RA). The aim of Phase 2 of the development process was to achieve expert consensus on the clinical and laboratory variables that should contribute to the final criteria set.
Twenty-four expert RA clinicians (12 from Europe and 12 from North America) participated in Phase 2. A consensus-based decision analysis approach was used to identify factors (and their relative weights) that influence the probability of “developing RA,” complemented by data from the Phase 1 study. Patient case scenarios were used to identify and reach consensus on factors important in determining the probability of RA development. Decision analytic software was used to derive the relative weights for each of the factors and their categories, using choice-based conjoint analysis.
The expert panel agreed that the new classification criteria should be applied to individuals with undifferentiated inflammatory arthritis in whom at least 1 joint is deemed by an expert assessor to be swollen, indicating definite synovitis. In this clinical setting, they identified 4 additional criteria as being important: number of joints involved and site of involvement, serologic abnormality, acute-phase response, and duration of symptoms in the involved joints. These criteria were consistent with those identified in the Phase 1 data-driven approach.
The consensus-based, decision analysis approach used in Phase 2 complemented the Phase 1 efforts. The 4 criteria and their relative weights form the basis of the final criteria set.
Electronic medical records (EMRs) are a rich data source for discovery research but are underutilized due to the difficulty of extracting highly accurate clinical data. We assessed whether a classification algorithm incorporating narrative EMR data (typed physician notes), more accurately classifies subjects with rheumatoid arthritis (RA) compared to an algorithm using codified EMR data alone.
Subjects with ≥1 ICD9 RA code (714.xx) or who had anti-CCP checked in the EMR of two large academic centers were included into an ‘RA Mart’ (n=29,432). For all 29,432 subjects, we extracted narrative (using natural language processing) and codified RA clinical information. In a training set of 96 RA and 404 non-RA cases from the RA Mart classified by medical record review, we used narrative and codified data to develop classification algorithms using logistic regression. These algorithms were applied to the entire RA Mart. We calculated and compared the positive predictive value (PPV) of these algorithms by reviewing records of an additional 400 subjects classified as RA by the algorithms.
A complete algorithm (narrative and codified data) classified RA subjects with a significantly higher PPV of 94%, than an algorithm with codified data alone (PPV 88%). Characteristics of the RA cohort identified by the complete algorithm were comparable to existing RA cohorts (80% female, 63% anti-CCP+, 59% erosion+).
We demonstrate the ability to utilize complete EMR data to define an RA cohort with a PPV of 94%, which was superior to an algorithm using codified data alone.
Increasingly, assays for the detection of anti-citrullinated peptide antibodies (ACPA) are used in RA diagnosis. This review summarizes the biologic basis and development of ACPA assays, available ACPA assays and their performance characteristics, and diagnostic properties of ACPA alone and compared to rheumatoid factor (RF) in early RA. We also review correlations, precision, costs and cost-effectiveness, availability, stability and reproducibility of the available assays. Taken together, data indicate that ACPA has a higher specificity than RF for early RA, good predictive validity, high sensitivity, apparent cost-effectiveness and good stability and reproducibility. Given its superior performance characteristics and increasing availability, ACPA is emerging as the most useful single assay for the diagnosis of RA.
anti-citrullinated peptide antibody; rheumatoid factor; anti-CCP; ACPA; RF; diagnosis; rheumatoid arthritis; early arthritis
Classification of rheumatoid arthritis (RA) is increasingly important as new therapies can halt the disease in its early stages. Antibodies to cyclic citrullinated peptides (anti-CCP) are widely used for RA diagnosis, but are not in the 1987 American College of Rheumatology (ACR) Criteria for RA Classification. We developed and tested the performance characteristics of new criteria for RA classification, incorporating anti-CCP.
We identified all subjects seen in our Arthritis Center with rheumatoid factor (RF) and anti-CCP tested simultaneously between January 1 and June 30, 2004 and reviewed their medical records for the ACR criteria, rheumatologists' diagnoses, RF and anti-CCP. We revised the ACR criteria in two ways: (1) adding anti-CCP, (2) replacing rheumatoid nodules and erosions with anti-CCP (CCP 6 criteria). We compared sensitivity and specificity of all criteria, in all subjects and in subjects with arthritis symptoms ≤ 6 months.
Medical records of 292 subjects were analysed: mean age was 54 years, 82% were women, and mean symptom duration was 4.1 years. 17% were RF+ and 14% were anti-CCP+ at initial testing. 78 (27%) had definite RA per treating rheumatologist at latest follow-up.
The CCP 6 criteria increased sensitivity for RA classification for all subjects regardless of symptom duration: 74% vs. 51% for ACR criteria with a loss in specificity (81% vs. 91%). Sensitivity was greatly improved in subjects with symptoms ≤ 6 months: 25% vs. 63% for ACR criteria with a decrease in specificity.
The CCP 6 criteria improved upon the sensitivity of the ACR criteria, most remarkably for subjects with symptoms ≤ 6 months and could be used for classification of subjects for RA in clinical studies.
Rheumatoid arthritis; cyclic citrullinated peptide; classification; early RA
Recent studies have increased our understanding of environmental exposures that modify risk for RA such as smoking and alcohol intake. Other factors such as birthweight, breastfeeding, socioeconomic status and region of birth have also been demonstrated to contribute to risk. ACPA status is associated with specific environmental factors and is therefore important to incorporate into present and future studies.
environmental risk factors; epidemiology; gene–environment interaction; rheumatoid arthritis
The co-occurrence of autoimmune diseases such as rheumatoid arthritis (RA) and type 1 diabetes (T1D) has been reported in individuals and families. We studied the strength and nature of this association at the population level.
We conducted a case-control study of 1419 incident RA cases and 1674 controls between 1996 and 2003. Subjects were recruited from university, public and private rheumatology units throughout Sweden. Blood samples were tested for the presence of antibodies to cyclic citrullinated peptide (anti-CCP), rheumatoid factor (RF) and the presence or absence of the 620W PTPN22 allele. Information on history of diabetes was obtained by questionnaire, telephone interview, and medical record review. The prevalence of T1D and type 2 diabetes (T2D) was compared between incident RA cases and controls and further stratified by anti-CCP, RF status, and the presence of the PTPN22 risk allele.
T1D was associated with an increased risk of RA, OR 4.9 (95% CI 1.8–13.1), and was specific for anti-CCP+ RA, OR 7.3 (95% CI 2.7–20.0), but not anti-CCP negative RA. Further adjustment for PTPN22 attenuated the odds ratio for anti-CCP+ RA in individuals with T1D to 5.3 (95% CI 1.5–18.7). No association was observed between RA and T2D.
The association between T1D and RA is specific for a particular RA subset, anti-CCP+ RA. The risk of type 1 diabetics developing RA later in life may be attributed in part to the presence of the 620W PTPN22 allele, suggesting a common pathway for the pathogenesis of these two diseases.
Mutation of the 3β-hydroxysterol Δ7-reductase gene (Dhcr7−/−) results in Smith-Lemli-Opitz syndrome (SLOS). Patients, and genetically altered mice, are unable to produce cholesterol and accumulate 7-dehydrocholesterol (DHC) in serum and tissue. This causes multiple growth and developmental abnormalities as well as immune system anomalies including allergy. Because cholesterol is a key component of liquid-ordered membranes (lipid rafts) and these domains have been implicated in regulating mast cell activation, we examined whether mast cell responsiveness is altered in this model. Mast cells derived from Dhcr7−/− mice (DHCR KO) showed constitutive cytokine production and hyper-degranulation after stimulation of the high affinity IgE receptor (FcɛRI). DHCR KO mast cells, but not wild-type mast cells, accumulated DHC in lipid rafts. DHC partially disrupted lipid raft stability and displaced Lyn kinase protein and activity from lipid rafts. This led to down-regulation of some Lyn-dependent signaling events but increased Fyn kinase activity and Akt phosphorylation. The Lyn-dependent phosphorylation of Csk-binding protein, which negatively regulates Fyn activity, was decreased. This phenotype reproduces some of the characteristics of Lyn-null mast cells, which also demonstrate hyper-degranulation. These findings provide the first evidence of lipid raft dysfunction in SLOS and may explain the observed association of allergy with SLOS.