TNFRII polymorphism is associated with response to TNF blockers in rheumatoid arthritis patients seronegative for ACPA

The Association between Genetics and Response to Treatment with Biologics in Patients with Psoriasis, Psoriatic Arthritis, Rheumatoid Arthritis, and Inflammatory Bowel Diseases: A Systematic Review and Meta-Analysis

Genetic biomarkers could potentially lower the risk of treatment failure in chronic inflammatory diseases (CID) like psoriasis, psoriatic arthritis (PsA), rheumatoid arthritis (RA), and inflammatory bowel disease (IBD). We performed a systematic review and meta-analysis assessing the association between single nucleotide polymorphisms (SNPs) and response to biologics. Odds ratio (OR) with 95% confidence interval (CI) meta-analyses were performed. In total, 185 studies examining 62,774 individuals were included. For the diseases combined, the minor allele of MYD88 (rs7744) was associated with good response to TNFi (OR: 1.24 [1.02-1.51], 6 studies, 3158 patients with psoriasis or RA) and the minor alleles of NLRP3 (rs4612666) (OR: 0.71 [0.58-0.87], 5 studies, 3819 patients with RA or IBD), TNF-308 (rs1800629) (OR: 0.71 [0.55-0.92], 25 studies, 4341 patients with psoriasis, RA, or IBD), FCGR3A (rs396991) (OR: 0.77 [0.65-0.93], 18 studies, 2562 patients with psoriasis, PsA, RA, or IBD), and TNF-238 (rs361525) (OR: 0.57 [0.34-0.96]), 7 studies, 818 patients with psoriasis, RA, or IBD) were associated with poor response to TNFi together or infliximab alone. Genetic variants in TNFα, NLRP3, MYD88, and FcRγ genes are associated with response to TNFi across several inflammatory diseases. Most other genetic variants associated with response were observed in a few studies, and further validation is needed.

Prediction of response to anti-TNF treatment using laboratory biomarkers in patients with rheumatoid arthritis: a systematic review

OBJECTIVES

In this systematic review, we aim to identify laboratory biomarkers that predict response to tumour necrosis factor inhibitors (TNFi) in patients with rheumatoid arthritis (RA).

METHODS

EMBASE, PubMed and Cochrane Library (CENTRAL) were searched for studies that presented predictive accuracy measures of laboratory biomarkers, or in which these were calculable. Likelihood ratios were calculated in order to determine whether a test result relevantly changed the probability of response. Likelihood ratios between 2-10 and 0.5-0.1 were considered weak predictors, respectively, and ratios above 10 or below 0.1 were considered strong predictors of response. Primary focus was on biomarkers studied ≥3 times.

RESULTS

From 41 included studies, data on 99 different biomarkers were extracted. Five biomarkers were studied ≥3 times, being (1) anti-cyclic citrullinated peptide (CCP), (2) rheumatoid factor, (3) -308 polymorphism in the TNF-α gene, (4) SE copies in the HLA-DRB1 gene and (5) FcGR2A polymorphism. No studies showed a strong predictive association and only one study on anti-CCP showed a weak positive association.

CONCLUSIONS

No biomarkers were found that consistently showed a (strong) predictive effect for response to TNFi in patients with RA. Given the disappointing yield of previous predictive biomarker research, future studies should focus on exploring, combining and validating the most promising laboratory biomarkers identified in this review, and searching for new predictors. Besides this, they should focus on contexts where prediction-aided decision-making can have a large impact (even with limited predictive value of markers/models).

PROSPERO REGISTRATION NUMBER

CRD42021278987.

Gene Ontology Analysis Highlights Biological Processes Influencing Non-Response to Anti-TNF Therapy in Rheumatoid Arthritis

Anti-TNF therapy has significantly improved disease control in rheumatoid arthritis, but a fraction of rheumatoid arthritis patients do not respond to anti-TNF therapy or lose response over time. Moreover, the mechanisms underlying non-response to anti-TNF therapy remain largely unknown. To date, many single biomarkers of response to anti-TNF therapy have been published but they have not yet been analyzed as a system of interacting nodes. The aim of our study is to systematically elucidate the biological processes underlying non-response to anti-TNF therapy in rheumatoid arthritis using the gene ontologies of previously published predictive biomarkers. Gene networks were constructed based on published biomarkers and then enriched gene ontology terms were elucidated in subgroups using gene ontology software tools. Our results highlight the novel role of proteasome-mediated protein catabolic processes (p = 2.91 × 10⁻¹⁵) and plasma lipoproteins (p = 4.55 × 10⁻¹¹) in anti-TNF therapy response. The results of our gene ontology analysis help elucidate the biological processes underlying non-response to anti-TNF therapy in rheumatoid arthritis and encourage further study of the highlighted processes.

Assessing prognosis and prediction of treatment response in early rheumatoid arthritis: systematic reviews

BACKGROUND

Rheumatoid arthritis (RA) is a chronic, debilitating disease associated with reduced quality of life and substantial costs. It is unclear which tests and assessment tools allow the best assessment of prognosis in people with early RA and whether or not variables predict the response of patients to different drug treatments.

OBJECTIVE

To systematically review evidence on the use of selected tests and assessment tools in patients with early RA (1) in the evaluation of a prognosis (review 1) and (2) as predictive markers of treatment response (review 2).

DATA SOURCES

Electronic databases (e.g. MEDLINE, EMBASE, The Cochrane Library, Web of Science Conference Proceedings; searched to September 2016), registers, key websites, hand-searching of reference lists of included studies and key systematic reviews and contact with experts.

STUDY SELECTION

Review 1 - primary studies on the development, external validation and impact of clinical prediction models for selected outcomes in adult early RA patients. Review 2 - primary studies on the interaction between selected baseline covariates and treatment (conventional and biological disease-modifying antirheumatic drugs) on salient outcomes in adult early RA patients.

RESULTS

Review 1 - 22 model development studies and one combined model development/external validation study reporting 39 clinical prediction models were included. Five external validation studies evaluating eight clinical prediction models for radiographic joint damage were also included. c-statistics from internal validation ranged from 0.63 to 0.87 for radiographic progression (different definitions, six studies) and 0.78 to 0.82 for the Health Assessment Questionnaire (HAQ). Predictive performance in external validations varied considerably. Three models [(1) Active controlled Study of Patients receiving Infliximab for the treatment of Rheumatoid arthritis of Early onset (ASPIRE) C-reactive protein (ASPIRE CRP), (2) ASPIRE erythrocyte sedimentation rate (ASPIRE ESR) and (3) Behandelings Strategie (BeSt)] were externally validated using the same outcome definition in more than one population. Results of the random-effects meta-analysis suggested substantial uncertainty in the expected predictive performance of models in a new sample of patients. Review 2 - 12 studies were identified. Covariates examined included anti-citrullinated protein/peptide anti-body (ACPA) status, smoking status, erosions, rheumatoid factor status, C-reactive protein level, erythrocyte sedimentation rate, swollen joint count (SJC), body mass index and vascularity of synovium on power Doppler ultrasound (PDUS). Outcomes examined included erosions/radiographic progression, disease activity, physical function and Disease Activity Score-28 remission. There was statistical evidence to suggest that ACPA status, SJC and PDUS status at baseline may be treatment effect modifiers, but not necessarily that they are prognostic of response for all treatments. Most of the results were subject to considerable uncertainty and were not statistically significant.

LIMITATIONS

The meta-analysis in review 1 was limited by the availability of only a small number of external validation studies. Studies rarely investigated the interaction between predictors and treatment.

SUGGESTED RESEARCH PRIORITIES

Collaborative research (including the use of individual participant data) is needed to further develop and externally validate the clinical prediction models. The clinical prediction models should be validated with respect to individual treatments. Future assessments of treatment by covariate interactions should follow good statistical practice.

CONCLUSIONS

Review 1 - uncertainty remains over the optimal prediction model(s) for use in clinical practice. Review 2 - in general, there was insufficient evidence that the effect of treatment depended on baseline characteristics.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42016042402.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

Association of TRAF1-C5 with risk of uveitis in juvenile idiopathic arthritis

OBJECTIVES

Numerous single nucleotide polymorphisms (SNPs) have been associated with JIA, but few of these studies were replicated. We conducted a candidate-gene approach study to assess if some SNPs could be related to clinical subtypes or other clinical features of the juvenile idiopathic arthritis (JIA) such as the risk of uveitis, ANA positivity and the age at onset.

METHODS

SNPs in six genes were analysed: PTPN22, STAT4, TRAF1-C5, TGFbeta, TNFAIP3, and C12orf30. We retrospectively included 104 JIA patients, fulfilling the ILAR classification criteria. Association between SNPs and JIA clinical subtypes, the presence of ANA, risk of uveitis and age at onset was evaluated using a Chi² test or a Fischer test.

RESULTS

No associations between different clinical subtypes as well as presence of ANA and the 6 SNPs were found. However, the AA genotype of TRAF1-C5 appeared associated in a subgroup of patients with uveitis in oligoarticular and polyarticular forms [OR 3.77 (95% CI: 1.1067, 12.8527); P=0.066]. Furthermore, AA TRAF1-C5 was significantly more frequent in antinuclear antibodies (ANA) positive patients presenting uveitis, compared to patients without uveitis and without ANA (P<0.05).

CONCLUSION

TRAF1-C5 genotype could identify JIA patients with a risk to develop uveitis especially in oligo and polyarticular forms and among ANA-positive children. Given the moderate size of our cohort, this association has to be confirmed in other studies.

Personalized biological treatment for rheumatoid arthritis: a systematic review with a focus on clinical applicability

OBJECTIVES

To review studies that address prediction of response to biologic treatment in RA and to explore the clinical utility of the studied (bio)markers.

METHODS

A search for relevant articles was performed in PubMed, Embase and Cochrane databases. Studies that presented predictive values or in which these could be calculated were selected. The added value was determined by the added value on prior probability for each (bio)marker. Only an increase/decrease in chance of response ⩾15% was considered clinically relevant, whereas in oncology values >25% are common.

RESULTS

Of the 57 eligible studies, 14 (bio)markers were studied in more than one cohort and an overview of the added predictive value of each marker is presented. Of the replicated predictors, none consistently showed an increase/decrease in probability of response ⩾15%. However, positivity of RF and ACPA in case of rituximab and the presence of the TNF-α promoter 308 GG genotype for TNF inhibitor therapy were consistently predictive, yet low in added predictive value. Besides these, 65 (bio)markers studied once showed remarkably high (but not validated) predictive values.

CONCLUSION

We were unable to address clinically useful baseline (bio)markers for use in individually tailored treatment. Some predictors are consistently predictive, yet low in added predictive value, while several others are promising but await replication. The challenge now is to design studies to validate all explored and promising findings individually and in combination to make these (bio)markers relevant to clinical practice.

Seronegative rheumatoid arthritis: pathogenetic and therapeutic aspects

Rheumatoid arthritis (RA) has long been recognised as a highly heterogeneous disease of immune dysregulation. Despite an ever-growing appreciation of the role of circulating autoantibodies in the development of 'seropositive' disease, the pathogenesis of seronegative RA remains poorly understood. Accumulating evidence suggests that RA 'serotypes', in fact, reflect distinct disease entities that, despite their clinical overlap, diverge in respect of genetic architecture, cellular pathology and even therapeutic responsiveness. Focussing on seronegative RA, this review considers these concepts and their implications for the management of patients with this challenging, though sometimes overlooked, condition.