On the origins of complex immune-mediated disease: the example of rheumatoid arthritis

Robust analyses for radiographic progression in rheumatoid arthritis

Demonstrating inhibition of the structural damage to joints as a statistically significant difference in radiographic progression as measured by the van der Heijde modified Total Sharp Score (mTSS) is a common objective in trials for rheumatoid arthritis treatments. The frequently used analysis of the covariance model with missing data imputed using linear extrapolation (analyses of covariance, ANCOVA+LE) may not be ideal for long-term extension studies or for paediatric studies. The random coefficient (RC) model may represent a better alternative.A two-arm (active treatment and placebo) setting with a week 44 study period was considered. RC model, ANCOVA+LE and ANCOVA with last observation carried forward imputation were compared under different scenarios in bias, root mean square error (RMSE), power and type I error rate.The RC model outperformed ANCOVA+LE in metrics measuring bias, RMSE, power and type I error rate under the evaluated scenarios. ANCOVA and RC provide similar performance when there are no missing data. With missing data, RC+observed (OBS) provides similar or better results than ANCOVA+LE in power and bias.Our simulations support that RC is both a more sensitive and a more precise alternative to the commonly used ANCOVA+LE as a primary method for analysing mTSS in long-term extension and paediatric studies with a higher likelihood of missing data. The RC model can provide a reference at time points with missing data by estimating a slope; mTSS change by one unit change in time. ANCOVA+LE is recommended as a sensitivity analysis.

Understanding the Role of Interleukin-6 (IL-6) in the Joint and Beyond: A Comprehensive Review of IL-6 Inhibition for the Management of Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a chronic, debilitating autoimmune disorder involving inflammation and progressive destruction of the joints, affecting up to 1% of the population. The majority of patients with RA have one or more comorbid conditions, the most common being cardiovascular disease, osteoporosis, and depression, the presence of which are associated with poorer clinical outcomes and lower health-related quality of life. RA pathogenesis is driven by a complex network of proinflammatory cells and cytokines, and of these, interleukin-6 (IL-6) plays a key role in the chronic inflammation associated with RA. Through cell signaling that can be initiated by both membrane-bound and soluble forms of its receptor, IL-6 acts both locally to promote joint inflammation and destruction, and in the circulation to mediate extra-articular manifestations of RA, including pain, fatigue, morning stiffness, anemia, and weight loss. This narrative review describes the role of IL-6 in the pathogenesis of RA, its comorbidities, and extra-articular systemic manifestations, and examines the effects of the IL-6 receptor inhibitors sarilumab and tocilizumab on clinical endpoints of RA, patient-reported outcomes, and common comorbidities and extra-articular manifestations.

Prevalence of anti-citrullinated protein antibodies (ACPA) in patients with diffuse large B-cell lymphoma (DLBCL): a case-control study

Background

Antibodies against citrullinated proteins (ACPA) have been recognised as the most specific serum marker for rheumatoid arthritis. However, serum autoantibodies such as anti-nuclear antibodies have also been detected in the sera of different lymphatic malignancies without accompanying rheumatologic disease. Therefore, we conducted a study to evaluate the prevalence of ACPA in diffuse large B-cell non-Hodgkin lymphoma (DLBCL).

Methods

Sera of 395 DLBCL patients and 258 age-matched healthy controls were investigated to evaluate the prevalence of ACPA and RF. ACPA-positive data were stratified into subgroups of RF positivity and established prognostic parameters for DLBCL, including overall survival. In addition, the ACPA serum concentrations levels were compared to an ACPA-positive RA cohort (n = 175). The statistics were performed with χ2 test and Mann- Whitney-U test; Kaplan-Meyer curves (log rank test) were used to analyse the overall survival. P-value <0.05 was statistically significant.

Results

ACPA, but not RF, occurred significantly more frequently in the sera of DLBCL patients than in healthy controls (3.5% versus 0.8%, p = 0.030). However, the ACPA serum concentration levels were significantly lower than in RA patients (median 10.4 versus 124.1 U/ml, p = 0.0001). After subgroup stratification, ACPA positivity in DLBCL was significantly associated with male gender (4.4% versus 0%, p = 0.022; odds ratio 1.046, CI 1.014–1.079) and with RF-IgM seropositivity (1.77% versus 0%, p = 0.043), but not with prognostic parameters for DLBCL.

Conclusions

DLBCL is associated with a significantly higher prevalence of ACPA, with an increased prevalence in male patients, and simultaneous RF-IgM positivity. However, ACPA is not prognostic for DLBCL. The prevalence of RF-IgM, -IgA, or -IgG did not differ from healthy controls.

Genetic risk score predicting risk of rheumatoid arthritis phenotypes and age of symptom onset

Background

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.

Methods/Principal Findings

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.

Conclusions/Significance

Results suggest that seronegative and seropositive/erosive RA have different genetic architecture and support the importance of considering RA phenotypes in RA genetic studies.

Small molecules as friends and foes of the immune system

Every organism is in contact with numerous small molecules (<1000 Da). Chemicals may cause or trigger adverse health effects, including diseases of the immune system. They may also be exploited as drugs. In this review, we look at the interaction between small molecules and the immune system. We discuss the hapten and pharmacological interaction concepts of chemical interaction to trigger T cells and how chemicals can participate in cellular signaling pathways. As a sensor of small molecules, the arylhydrocarbon receptor controls expression of many xenobiotic metabolizing enzymes, including those in the immunological barrier organs; the skin and gut. The relevance of the arylhydrocarbon receptor in the dynamic interaction of the immune system with the chemical environment is therefore discussed.

Anti-CCP antibodies: the past, the present and the future

Rheumatoid arthritis (RA) is an autoimmune disease characterized by autoantibodies against citrullinated antigens. The importance of citrulline for the epitopes bound by these autoantibodies, referred to as ACPA (anti-citrullinated peptide/protein antibodies), was first described in 1998. In addition to citrullinated proteins, cyclic citrullinated peptides (CCP) can also be used as test substrates for detecting ACPA. The standard test for these antibodies is the second-generation CCP (CCP2) test, which is one of the best in terms of sensitivity and specificity. The generation of ACPA is an early event in the disease course, and is dependent on the presence of certain MHC class II alleles. ACPA in the inflamed synovium have been shown to associate with citrullinated antigens to form immune complexes, resulting in progression of the inflammatory process. The involvement of ACPA in the chronicity of RA is probably the reason why ACPA-positive patients have a more erosive disease course than ACPA-negative patients. The presence of ACPA has been included in the 2010 RA classification criteria. Thus, it is important to further standardize ACPA testing, for example by including an internal serum standard, which may lead to a better distinction between low and high ACPA levels.

Causal graph-based analysis of genome-wide association data in rheumatoid arthritis

BACKGROUND

GWAS owe their popularity to the expectation that they will make a major impact on diagnosis, prognosis and management of disease by uncovering genetics underlying clinical phenotypes. The dominant paradigm in GWAS data analysis so far consists of extensive reliance on methods that emphasize contribution of individual SNPs to statistical association with phenotypes. Multivariate methods, however, can extract more information by considering associations of multiple SNPs simultaneously. Recent advances in other genomics domains pinpoint multivariate causal graph-based inference as a promising principled analysis framework for high-throughput data. Designed to discover biomarkers in the local causal pathway of the phenotype, these methods lead to accurate and highly parsimonious multivariate predictive models. In this paper, we investigate the applicability of causal graph-based method TIE* to analysis of GWAS data. To test the utility of TIE*, we focus on anti-CCP positive rheumatoid arthritis (RA) GWAS datasets, where there is a general consensus in the community about the major genetic determinants of the disease.

RESULTS

Application of TIE* to the North American Rheumatoid Arthritis Cohort (NARAC) GWAS data results in six SNPs, mostly from the MHC locus. Using these SNPs we develop two predictive models that can classify cases and disease-free controls with an accuracy of 0.81 area under the ROC curve, as verified in independent testing data from the same cohort. The predictive performance of these models generalizes reasonably well to Swedish subjects from the closely related but not identical Epidemiological Investigation of Rheumatoid Arthritis (EIRA) cohort with 0.71-0.78 area under the ROC curve. Moreover, the SNPs identified by the TIE* method render many other previously known SNP associations conditionally independent of the phenotype.

CONCLUSIONS

Our experiments demonstrate that application of TIE* captures maximum amount of genetic information about RA in the data and recapitulates the major consensus findings about the genetic factors of this disease. In addition, TIE* yields reproducible markers and signatures of RA. This suggests that principled multivariate causal and predictive framework for GWAS analysis empowers the community with a new tool for high-quality and more efficient discovery.

REVIEWERS

This article was reviewed by Prof. Anthony Almudevar, Dr. Eugene V. Koonin, and Prof. Marianthi Markatou.