Measuring ACPA in the general population or primary care: is it useful?

Environment and systemic autoimmune rheumatic diseases: an overview and future directions

Introduction

Despite progress in our understanding of disease pathogenesis for systemic autoimmune rheumatic diseases (SARD), these diseases are still associated with high morbidity, disability, and mortality. Much of the strongest evidence to date implicating environmental factors in the development of autoimmunity has been based on well-established, large, longitudinal prospective cohort studies.

Methods

Herein, we review the current state of knowledge on known environmental factors associated with the development of SARD and potential areas for future research.

Results

The risk attributable to any particular environmental factor ranges from 10-200%, but exposures are likely synergistic in altering the immune system in a complex interplay of epigenetics, hormonal factors, and the microbiome leading to systemic inflammation and eventual organ damage. To reduce or forestall the progression of autoimmunity, a better understanding of disease pathogenesis is still needed.

Conclusion

Owing to the complexity and multifactorial nature of autoimmune disease, machine learning, a type of artificial intelligence, is increasingly utilized as an approach to analyzing large datasets. Future studies that identify patients who are at high risk of developing autoimmune diseases for prevention trials are needed.

Rheumatoid Arthritis: The Continuum of Disease and Strategies for Prediction, Early Intervention, and Prevention

Rheumatoid arthritis (RA) is known to include a pre-RA stage that can be defined as the presence of familial or genetic risk factors, biomarker abnormalities (eg, anticitrullinated protein antibodies [ACPA]), symptoms, and even abnormal imaging findings prior to the development of the onset of clinical RA with inflammatory arthritis that is apparent on physical examination. Indeed, there are multiple completed or ongoing retrospective case-control as well as prospective observational studies to identify the key biologic drivers of disease. Further, building on the predictive ability of combinations of biomarkers, symptoms, and imaging for future RA, there are multiple clinical trials completed, underway, or in development to identify approaches that may prevent, delay, or ameliorate future clinical RA in at-risk individuals. Importantly, however, although an effective preventive intervention has not yet been identified, at-risk individuals are being increasingly identified in clinical care; this presents a challenge of how to manage these individuals in clinical practice. This review will discuss the current understanding of the biology and natural history of RA development, nomenclature, and current models for prediction of future RA, as well as evaluate the current and ongoing clinical prevention trials with the overall goal to provide insights into the challenges and opportunities in the field of RA prevention. Moreover, this review will provide up-to-date options for clinical management of individuals at risk for RA.

Predicting Inflammatory Arthritis in At-Risk Persons: Development of Scores for Risk Stratification

BACKGROUND

Inflammatory arthritis (IA) is an immune-related condition defined by the presence of clinical synovitis. Its most common form is rheumatoid arthritis.

OBJECTIVE

To develop scores for predicting IA in at-risk persons using multidimensional biomarkers.

DESIGN

Prospective observational cohort study.

SETTING

Single-center, Leeds, United Kingdom.

PARTICIPANTS

Persons with new musculoskeletal symptoms, a positive test result for anticitrullinated protein antibodies, and no clinical synovitis and followed for 48 weeks or more or until IA occurred.

MEASUREMENTS

A simple score was developed using logistic regression, and a comprehensive score was developed using the least absolute shrinkage and selection operator Cox proportional hazards regression. Internal validation with bootstrapping was estimated, and a decision curve analysis was done.

RESULTS

Of 455 participants, 32.5% (148 of 455) developed IA, and 15.4% (70 of 455) developed it within 1 year. The simple score identified 249 low-risk participants with a false negative rate of 5% (and 206 high-risk participants with a false-positive rate of 72%). The comprehensive score identified 119 high-risk participants with a false-positive rate of 29% (and 336 low-risk participants with a false-negative rate of 19%); 40% of high-risk participants developed IA within 1 year and 71% within 5 years.

LIMITATIONS

External validation is required. Recruitment occurred over 13 years, with lower rates of IA in later years. There was geographic variation in laboratory testing and recruitment availability.

CONCLUSION

The simple score identified persons at low risk for IA who were less likely to need secondary care. The comprehensive score identified high-risk persons who could benefit from risk stratification and preventive measures. Both scores may be useful in clinical care and should also be useful in clinical trials.

PRIMARY FUNDING SOURCE

National Institute for Health and Care Research Leeds Biomedical Research Centre.

Citrullination of C1-inhibitor as a mechanism of impaired complement regulation in rheumatoid arthritis

Background

Dysregulated complement activation, increased protein citrullination, and production of autoantibodies against citrullinated proteins are hallmarks of rheumatoid arthritis (RA). Citrullination is induced by immune cell-derived peptidyl-Arg deiminases (PADs), which are overactivated in the inflamed synovium. We characterized the effect of PAD2- and PAD4-induced citrullination on the ability of the plasma-derived serpin C1-inhibitor (C1-INH) to inhibit complement and contact system activation.

Methods

Citrullination of the C1-INH was confirmed by ELISA and Western blotting using a biotinylated phenylglyoxal probe. C1-INH-mediated inhibition of complement activation was analyzed by C1-esterase activity assay. Downstream inhibition of complement was studied by C4b deposition on heat-aggregated IgGs by ELISA, using pooled normal human serum as a complement source. Inhibition of the contact system was investigated by chromogenic activity assays for factor XIIa, plasma kallikrein, and factor XIa. In addition, autoantibody reactivity to native and citrullinated C1-INH was measured by ELISA in 101 RA patient samples.

Results

C1-INH was efficiently citrullinated by PAD2 and PAD4. Citrullinated C1-INH was not able to bind the serine protease C1s and inhibit its activity. Citrullination of the C1-INH abrogated its ability to dissociate the C1-complex and thus inhibit complement activation. Consequently, citrullinated C1-INH had a decreased capacity to inhibit C4b deposition via the classical and lectin pathways. The inhibitory effect of C1-INH on the contact system components factor XIIa, plasma kallikrein, and factor XIa was also strongly reduced by citrullination. In RA patient samples, autoantibody binding to PAD2- and PAD4-citrullinated C1-INH was detected. Significantly more binding was observed in anti-citrullinated protein antibody (ACPA)-positive than in ACPA-negative samples.

Conclusion

Citrullination of the C1-INH by recombinant human PAD2 and PAD4 enzymes impaired its ability to inhibit the complement and contact systems in vitro. Citrullination seems to render C1-INH more immunogenic, and citrullinated C1-INH might thus be an additional target of the autoantibody response observed in RA patients.

Predicting the onset of rheumatoid arthritis

Various scores have attempted to predict the onset of rheumatoid arthritis (RA). In particular, EULAR proposed a simple rule to identify new-onset arthralgia suspicious for progression to RA. However, its specificity would likely be higher if serological tests were included. In patients with clinical arthritis, reliable predictive criteria for progression to RA have also been identified. Overall, the validity of the available scores is still being debated. Such scores do not fully account for the interactions between risk factors in specific subpopulations. New technologies could help to overcome these limitations, but we need databases containing a sufficient number of RA and pre-RA patients, including pre-diagnostic monitoring. Today, the existing predictive rules cannot compete with expert opinions.

Added value of multiple autoantibody testing for predicting progression to inflammatory arthritis in at-risk individuals

BACKGROUND

Predicting progression to clinical arthritis in individuals at-risk of developing rheumatoid arthritis is a prerequisite to developing stratification groups for prevention strategies. Selecting accurate predictive criteria is the critical step to define the population at-risk. While positivity for anti-citrullinated protein antibodies (ACPA) remains the main recruitment biomarker, positivity for other autoantibodies (AutoAbs) identified before the onset of symptoms, may provide additional predictive accuracy for stratification.

OBJECTIVE

To perform a multiple AutoAbs analysis for both the prediction and the time of progression to inflammatory arthritis (IA).

METHODS

392 individuals were recruited based on a new musculoskeletal complaint and positivity for ACPA or rheumatoid factor (RF). ELISAs were performed for ACPA, RF, anti-nuclear Ab, anti-carbamylated protein (anti-CarP) and anti-collagen AutoAbs. Logistic and COX regression were used for analysis.

RESULTS

Progression to IA was observed in 125/392 (32%) of cases, of which 78 progressed within 12 months. The AutoAbs ACPA, RF, anti-CarP were individually associated with progression (p<0.0001) and improved prediction when combined with demographic/clinical data (Accuracy >77%; area under the curve (AUC) >0.789), compared with prediction using only demographic/clinical data (72.9%, AUC=0.760). Multiple AutoAbs testing provided added value, with +6.4% accuracy for number of positive AutoAbs (AUC=0.852); +5.4% accuracy for AutoAbs levels (ACPA/anti-CarP, AUC=0.832); and +6.2% accuracy for risk-groups based on high/low levels (ACPA/RF/anti-CarP, AUC=0.837). Time to imminent progression was best predicted using ACPA/anti-CarP levels (AUC=0.779), while the number of positive AutoAbs was/status/risk were as good (AUC=0.778).

CONCLUSION

We confirm added value of multiple AutoAbs testing for identifying progressors to clinical disease, allowing more specific stratification for intervention studies.

Autoantibodies in Rheumatoid Arthritis: Historical Background and Novel Findings

Autoantibodies represent a hallmark of rheumatoid arthritis (RA), with the rheumatoid factor (RF) and antibodies against citrullinated proteins (ACPA) being the most acknowledged ones. RA patients who are positive for RF and/or ACPA ("seropositive") in general display a different etiology and disease course compared to so-called "seronegative" patients. Still, the seronegative patient population is very heterogeneous and not well characterized. Due to the identification of new autoantibodies and advancements in the diagnosis of rheumatic diseases in the last years, the group of seronegative patients is constantly shrinking. Aside from antibodies towards various post-translational modifications, recent studies describe autoantibodies targeting some native proteins, further broadening the spectrum of recognized antigens. Next to the detection of new autoantibody groups, much research has been done to answer the question if and how autoantibodies contribute to the pathogenesis of RA. Since autoantibodies can be detected years prior to RA onset, it is a matter of debate whether their presence alone is sufficient to trigger the disease. Nevertheless, there is gathering evidence of direct autoantibody effector functions, such as stimulation of osteoclastogenesis and synovial fibroblast migration in in vitro experiments. In addition, autoantibody positive patients display a worse clinical course and stronger radiographic progression. In this review, we discuss current findings regarding different autoantibody types, the underlying disease-driving mechanisms, the role of Fab and Fc glycosylation and clinical implications.

Proteoform Analysis of Matrix Metalloproteinase-9/Gelatinase B and Discovery of Its Citrullination in Rheumatoid Arthritis Synovial Fluids

Objectives

To explore posttranslational modifications (PTMs), including proteolytic activation, multimerization, complex formation and citrullination of gelatinases, in particular of gelatinase B/MMP-9, and to detect in gelatin-Sepharose affinity-purified synovial fluids, the presence of specific MMP proteoforms in relation to arthritis.

Methods

Latent, activated, complexed and truncated gelatinase-A/MMP-2 and gelatinase B/MMP-9 proteoforms were detected with the use of zymography analysis to compare specific levels, with substrate conversion assays, to test net proteolytic activities and by Western blot analysis to decipher truncation variants. Citrullination was detected with enhanced sensitivity, by the use of a new monoclonal antibody against modified citrullines.

Results

All MMP-9 and MMP-2 proteoforms were identified in archival synovial fluids with the use of zymography analysis and the levels of MMP-9 versus MMP-2 were studied in various arthritic diseases, including rheumatoid arthritis (RA). Secondly, we resolved misinterpretations of MMP-9 levels versus proteolytic activities. Thirdly, a citrullinated, truncated proteoform of MMP-9 was discovered in archival RA synovial fluid samples and its presence was corroborated as citrullinated hemopexin-less MMP-9 in a small prospective RA sample cohort.

Conclusion

Synovial fluids from rheumatoid arthritis contain high levels of MMP-9, including its truncated and citrullinated proteoform. The combination of MMP-9 as analyte and its PTM by citrullination could be of clinical interest, especially in the field of arthritic diseases.

Auto-antibodies to post-translationally modified proteins in osteoarthritis

OBJECTIVE

Autoantibodies (AutoAbs) have been observed in osteoarthritis (OA) with broad antigenicity, although their prevalence and role remain unclear. Post-translational modification (PTMs) of proteins (oxidation, carbamylation, citrullination) is associated with synovitis and can lead to AutoAb development. Given the prevalence of synovitis, we explored whether AutoAbs to PTM-antigens are common in OA compared with rheumatoid arthritis (RA).

METHODS

Serum (n = 895) was obtained from healthy controls, OA and RA patients; and arthritic synovial fluid (SF, n = 290). ELISAs were used to quantify anti-citrullinated peptide (ACPA), anti-carbamylated protein (anti-CarP), anti-oxidized collagen (anti-ROS-CI/CII) antibodies.

RESULTS

In sera, positivity for PTM-antigens AutoAbs was observed at a lower frequency in OA with 64.1% (95%CI: 57.2-70.1%) more ACPA+ and 29.8% (21.0-37.3%) more anti-CarP + patients in RA (both P < 0.0001). Levels of ACPA, anti-CarP were also lower in OA (P < 0.0001). Anti-ROS-CII positivity was lower in OA compared to RA (16.6%, 4.8-28.6%) less frequent, P = 0.033) but not anti-native-CII. There was no impact of age/gender on AutoAbs associations with diseases either looking at positivity or levels. In SF, OA patients were often ACPA+ (45.9%) although less frequently than in RA (P = 0.004). Anti-CarP were rarely observed (<5% all samples). All collagen AutoAbs were more frequent in RA compared to OA (all P < 0.010) but only levels of anti-CII and anti-ROS-CII were significantly higher in they RA (P < 0.050).

CONCLUSION

Although the frequency of AutoAbs for PTM proteins were lower in OA sera compared to RA, a higher proportion of OA SF were positive. The relative retention of AutoAbs in the OA joint requires further investigation.

Identification of biological pathways specific to phases preceding rheumatoid arthritis development through gene expression profiling

The etiopathogenesis of rheumatoid arthritis is partially understood; however, it is believed to result from a multi-step process. The immune onset followed by pre-clinical phases will eventually lead to the development of symptomatic disease. We aim at identifying differentially expressed genes in order to highlight pathways involved in the pre-clinical stages of rheumatoid arthritis development. The study population consisted of first-degree relatives of patients with rheumatoid arthritis, known to have an increased risk of developing disease as compared to the general population. Whole transcriptome analysis was performed in four groups: asymptomatic without autoantibodies or symptoms associated with possible rheumatoid arthritis (controls); having either clinically suspect arthralgias, undifferentiated arthritis or autoimmunity associated with RA (pre-clinical stages of RA: Pcs-RA); having subsequently developed classifiable RA (pre-RA); and early untreated rheumatoid arthritis patients (RA). Differentially expressed genes were determined, and enrichment analysis was performed. Functional enrichment analysis revealed 31 pathways significantly enriched in differentially expressed genes for Pcs-RA, pre-RA and RA compared to the controls. Osteoclast pathway is among the seven pathways specific for RA. In Pcs-RA and in pre-RA, several enriched pathways include TP53 gene connections, such as P53 and Wnt signalling pathways. Analysis of whole transcriptome for phenotypes related to rheumatoid arthritis allows highlighting which pathways are requested in the pre-clinical stages of disease development. After validation in replication studies, molecules belonging to some of these pathways could be used to identify new specific biomarkers for individuals with impending rheumatoid arthritis.