FCGR2A/FCGR3A Gene Polymorphisms and Clinical Variables as Predictors of Response to Tocilizumab and Rituximab in Patients With Rheumatoid Arthritis

FCGR3A-V158F gene polymorphism: A potential predictor for rituximab dosing optimization in Chinese patients with neuromyelitis optica spectrum disorder

BACKGROUND

Rituximab (RTX), an anti-CD20 monoclonal antibody, has shown promise in managing neuromyelitis optica spectrum disorders (NMOSD) by depleting B cells and reducing relapses. However, there is no consensus on the optimal RTX dosing regimen, and genetic factors, such as FCGR3A-V158F polymorphism, may influence treatment outcomes. This study investigates how FCGR3A-V158F genotypes influence RTX efficacy in Chinese NMOSD patients under varying dosing regimens and aims to optimize treatment protocols.

METHODS

We conducted a retrospective analysis of 25 Chinese NMOSD patients treated with RTX, grouped into standardized and low-dosage regimens. FCGR3A-V158F genotypes were determined, and treatment responses were evaluated, including relapse rates, time to first relapse (TFR), B-cell depletion, dose adjustments, and treatment retention.

RESULTS

Among all patients, 15 received standardized dosages, while 10 received varied induction doses (500 mg to 1200 mg) in low-dose regimens. For FCGR3A-V158F genotypes, 15 had the FF genotype, and 10 were V carriers (3 VV genotype, 7 VF genotype). Regardless of dosing, FF genotype patients had a higher relapse rate post-RTX treatment compared to V carriers (P < 0.05). None of the 3 VV genotype patients in either dose group experienced relapses post-RTX. In both dose groups, FF genotype patients had significantly shorter TFR and required more RTX dose adjustments post-RTX treatment compared to V carriers in the standardized dosage group (P < 0.05). FF genotype patients in the low dosage group were more likely to experience insufficient B-cell depletion, had lower treatment retention rates, and more discontinuations than V carriers in the standardized dosage group (P < 0.05). Insufficient B-cell depletion significantly predicted clinical relapses after RTX treatment (P < 0.05). In survival analysis, FF genotype patients, regardless of dosing, experienced earlier relapses post-RTX treatment (P < 0.05).

CONCLUSIONS

This study highlights the importance of RTX dosage selection in NMOSD treatment, particularly for FCGR3A-FF genotype patients. Standard-dose RTX therapy with vigilant monitoring of peripheral blood B-cell levels is recommended for these individuals to optimize treatment efficacy.

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.

Correlations of FCGR2A 131R/H and FCGR3A 158V/F Polymorphisms with the Susceptibility of Peri-implantitis in Chinese Han Population

The purpose of the study is to investigate the relationship of peri-implantitis (PI) with FCGR2A and FCGR3A gene polymorphisms. One hundred and forty-four patients with PI and 136 patients without PI infection were selected. Gingival crevicular fluid samples were collected from the two groups. The FCGR2A and FCGR3A polymorphism in the two groups were measured. All volunteers were evaluated for periodontal status. The effect of polymorphisms on PI susceptibility was investigated by chi-square analysis and logistic regression. The frequency of FCGR2A rs1801274 GG genotype of PI group was higher than that of the control group, while the GA and AA genotype carriers were less in PI group. After adjusting for other clinical indicators, rs1801274 GA genotype, AA genotype, and the A allele were still negatively correlated with the onset of PI. FCGR3A rs396991 polymorphism was not associated with PI. FCGR2A rs1801274 polymorphism was significantly associated with PI in the Chinese Han population, and GG genotype might be a genetic risk factor for PI.

A predictive nomogram for short-term outcomes of myasthenia gravis patients treated with low-dose rituximab

BACKGROUND

This study aims to establish and validate a predictive nomogram for the short-term clinical outcomes of myasthenia gravis (MG) patients treated with low-dose rituximab.

METHODS

We retrospectively reviewed 108 patients who received rituximab of 600 mg every 6 months in Huashan Hospital and Tangdu Hospital. Of them, 76 patients from Huashan Hospital were included in the derivation cohort to develop the predictive nomogram, which was externally validated using 32 patients from Tangdu Hospital. The clinical response is defined as a ≥ 3 points decrease in QMG score within 6 months. Both clinical and genetic characteristics were included to screen predictors via multivariate logistic regression. Discrimination and calibration were measured by the area under the receiver operating characteristic curve (AUC-ROC) and Hosmer-Lemeshow test, respectively.

RESULTS

Disease duration (OR = 0.987, p = 0.032), positive anti-muscle-specific tyrosine kinase antibodies (OR = 19.8, p = 0.007), and genotypes in FCGR2A rs1801274 (AG: OR = 0.131, p = 0.024;GG:OR = 0.037, p = 0.010) were independently associated with clinical response of post-rituximab patients. The nomogram identified MG patients with clinical response with an AUC-ROC (95% CI) of 0.875 (0.798-0.952) in the derivation cohort and 0.741(0.501-0.982) in the validation cohort. Hosmer-Lemeshow test showed a good calibration (derivation: Chi-square = 3.181, p = 0.923; validation: Chi-square = 8.098, p = 0.424).

CONCLUSIONS

The nomogram achieved an optimal prediction of short-term outcomes in patients treated with low-dose rituximab.

Patterns and determinants of response to novel therapies in juvenile and adult-onset polyarthritis

Biologic and targeted synthetic DMARDs (b/tsDMARDs) have revolutionized the management of multiple rheumatic inflammatory conditions. Among these, polyarticular JIA (pJIA) and RA display similarities in terms of disease pathophysiology and response pattern to b/tsDMARDs. Indeed, the therapeutic efficacy of novel targeted drugs is variable among individual patients, in both RA and pJIA. The mechanisms and determinants of this heterogeneous response are diverse and complex, such that the development of true 'precision'-medicine strategies has proven highly challenging. In this review, we will discuss pathophysiological, patient-specific, drug-specific and environmental factors contributing to individual therapeutic response in pJIA in comparison with what is known in RA. Although some biomarkers have been identified that stratify with respect to the likelihood of either therapeutic response or non-response, few have proved useful in clinical practice so far, likely due to the complexity of treatment-response mechanisms. Consequently, we propose a pragmatic, patient-centred and clinically based approach, i.e. personalized instead of biomarker-based precision medicine in JIA.

Pharmacogenetic biomarkers for secukinumab response in psoriasis patients in real-life clinical practice

BACKGROUND

Prediction of the response to a biological treatment in psoriasis patients would allow efficient treatment allocation.

OBJECTIVE

To identify polymorphisms associated with secukinumab response in psoriasis patients in a daily practice setting.

METHODS

We studied 180 SNPs in patients with moderate-to-severe plaque psoriasis recruited from 15 Spanish hospitals. Treatment effectiveness was evaluated by absolute PASI ≤3 and ≤1 at 6 and 12 months. Individuals were genotyped using a custom Taqman array. Multiple logistic regression models were generated. Sensitivity, specificity and area under the curve (AUC) were analysed.

RESULTS

A total of 173 patients were studied at 6 months, (67% achieved absolute PASI ≤ 3 and 65% PASI ≤ 1) and 162 at 12 months (75% achieved absolute PASI ≤ 3 and 64% PASI ≤ 1). Multivariable analysis showed the association of different sets of SNPs with the response to secukinumab. The model of absolute PASI≤3 at 6 months showed best values of sensitivity and specificity. Four SNPs were associated with the capability of achieving absolute PASI ≤ 3 at 6 months. rs1801274 (FCGR2A), rs2431697 (miR-146a) and rs10484554 (HLCw6) were identified as risk factors for failure to achieve absolute PASI≤3, while rs1051738 (PDE4A) was protective. AUC including these genotypes, weight of patients and history of biological therapy was 0.88 (95% CI 0.83-0.94), with a sensitivity of 48.6% and specificity of 95.7% to discriminate between both phenotypes.

CONCLUSION

We have identified a series of polymorphisms associated with the response to secukinumab capable of predicting the potential response/non-response to this drug in patients with plaque psoriasis.

Association between functional FCGR3A F158V and FCGR2A R131H polymorphisms and responsiveness to rituximab in patients with autoimmune diseases: a meta-analysis

OBJECTIVES

To investigate the association between the functional Fc gamma receptor 3 A (FCGR3A) V158F and FCGR2A R131H polymorphisms and rituximab therapy in patients with autoimmune diseases.

METHODS

We searched the Medline, Embase, and Cochrane databases for relevant articles. We conducted a meta-analysis of the association between FCGR3A V158F and FCGR2A R131H polymorphisms and responsiveness to rituximab in patients with autoimmune diseases.

RESULTS

Eleven studies, consisting of 661 responders and 267 non-responders for FCGR3A V158F polymorphism and 156 responders and 89 non-responders for FCGR2A R131H polymorphism, were included. The meta-analysis revealed a significant association between the FCGR3A V allele and responsiveness to rituximab (odds ratio [OR] = 1.600, 95% confidence interval [CI] = 1.268-2.018, P < 0.001). Furthermore, associations were found using the dominant and homozygous contrast models. Subgroup analysis showed an association between the FCGR3A V allele and responsiveness to rituximab in European, RA, ITP, small (<50) and large (≥50) groups, and short- (≤6 months) and long-term follow-up periods (≥6 months). These associations were also found in recessive, dominant or homozygous contrast models. Meta-analysis revealed no association between the FCGR2A R allele and responsiveness to rituximab (OR = 1.243, 95% CI = 0.825-1.873, P = 0.229).

CONCLUSIONS

We demonstrated that the FCGR3A F158V polymorphism is associated with better responsiveness to rituximab therapy in patients with autoimmune diseases, indicating that individuals carrying the FCGR3A V allele will likely respond better to rituximab. However, FCGR2A R131H polymorphism was not associated with better response to rituximab.

Association between the functional FCGR3A F158V and FCGR2A R131H polymorphisms and responsiveness to biologics in rheumatoid arthritis patients: A meta-analysis

OBJECTIVES

This study aimed to investigate the association between functional Fc gamma receptor 3A (FCGR3A) V158F and FCGR2A R131H polymorphisms and biologic therapy in rheumatoid arthritis (RA) patients.

METHODS

We searched Medline, Embase, and Cochran databases for available articles. This study is a meta-analysis of the association between the FCGR3A V158F and FCGR2A R131H polymorphisms and their responsiveness to biologics in RA patients.

RESULTS

Seventeen studies involving RA patients with FCGR3A V158F (n = 1884) and FCGR2A R131H (n = 1118) polymorphisms were considered. This meta-analysis showed that the FCGR3A V allele was associated with responsiveness to rituximab (odds ratio [OR] = 1.431, 95% CI = 1.081-1.894, P = 0.012), but not with tumor necrosis factor (TNF) blockers, tocilizumab, or abatacept. A significant association was also found between the FCGR3A V158F polymorphism and responsiveness to biologics using the dominant-recessive model. Additionally, the FCGR3A V158F polymorphism was associated with responsiveness to TNF blockers in the homozygous contrast model. Meta-analysis revealed an association between the FCGR2A RR + RH genotype and responsiveness to biologics (OR = 1.385, 95% CI = 1.007-1.904, P = 0.045).

CONCLUSIONS

This meta-analysis demonstrates that FCGR3A V allele carriers show better responsiveness to rituximab, and FCGR2A R allele carriers may show a better response to biologics in RA treatment. Genotyping of these polymorphisms could be a useful tool to find associations with the responsiveness of personalized medicine to biologics.

Predictors of response of rituximab in rheumatoid arthritis by weighted gene co-expression network analysis

PURPOSE

The purpose of this study was to identify a biomarker that can predict the efficacy of rituximab (RTX) in the treatment of rheumatoid arthritis (RA) patients.

METHODS

Utilized weighted gene co-expression network analysis (WGCNA) and LASSO regression analysis of whole blood transcriptome data (GSE15316 and GSE37107) related to RTX treatment for RA from the GEO database, the critical modules, and key genes related to the efficacy of RTX treatment for RA were found. The biological functions were further explored through enrichment analysis. The area under the ROC curve (AUC) was validated using the GSE54629 dataset.

RESULTS

WGCNA screened 71 genes for a dark turquoise module that were correlated with the efficacy of RTX treatment for RA (r = 0.42, P < 0.05). Through the calculation of gene significance (GS) and module membership (MM), 12 important genes were identified; in addition, 21 important genes were screened by the LASSO regression model; two key genes were obtained from the intersection between the important genes. Then, BANK1 (AUC = 0.704, P < 0.05) was identified as a potential biomarker to predict the efficacy of RTX treatment for RA by ROC curve evaluation of the treatment and validation groups. BANK1 gene expression was significantly decreased after RTX treatment, and a statistically significant difference was found (log FC =  - 2.08, P < 0.05). Immune cell infiltration analysis revealed that the infiltration of CD4 + T cell memory subset was increased in the group with high BANK1 expression, and a statistically significant difference was found (P < 0.05).

CONCLUSIONS

BANK1 can be used as a potential biomarker to predict the response of RTX treatment in RA patients. Key Points • Identifying the hub genes BANK1 as a potential biomarker to predict the response of RTX treatment in RA patients and confirming it in validation data. • Using the WGCNA approach and LASSO analyses to identify the BANK1 in a data set consisting of two GEO data merged and assessing the correlations between BANK1 and immune infiltration by CIBERSORT algorithm.

Comprehensive genetic and functional analyses of Fc gamma receptors influence on response to rituximab therapy for autoimmunity

BACKGROUND

Rituximab is widely used to treat autoimmunity but clinical response varies. Efficacy is determined by the efficiency of B-cell depletion, which may depend on various Fc gamma receptor (FcγR)-dependent mechanisms. Study of FcγR is challenging due to the complexity of the FCGR genetic locus. We sought to assess the effect of FCGR variants on clinical response, B-cell depletion and NK-cell-mediated killing in rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE).

METHODS

A longitudinal cohort study was conducted in 835 patients [RA = 573; SLE = 262]. Clinical outcome measures were two-component disease activity score in 28-joints (2C-DAS28CRP) for RA and British Isles Lupus Assessment Group (BILAG)-2004 major clinical response (MCR) for SLE at 6 months. B-cells were evaluated by highly-sensitive flow cytometry. Single nucleotide polymorphism and copy number variation for genes encoding five FcγRs were measured using multiplex ligation-dependent probe amplification. Ex vivo studies assessed NK-cell antibody-dependent cellular cytotoxicity (ADCC) and FcγR expression.

FINDINGS

In RA, carriage of FCGR3A-158V and increased FCGR3A-158V copies were associated with greater 2C-DAS28CRP response (adjusted for baseline 2C-DAS28CRP). In SLE, MCR was associated with increased FCGR3A-158V, OR 1.64 (95% CI 1.12-2.41) and FCGR2C-ORF OR 1.93 (95% CI 1.09-3.40) copies. 236/413 (57%) patients with B-cell data achieved complete depletion. Homozygosity for FCGR3A-158V and increased FCGR3A-158V copies were associated with complete depletion in combined analyses. FCGR3A genotype was associated with rituximab-induced ADCC, and increased NK-cell FcγRIIIa expression was associated with improved clinical response and depletion in vivo. Furthermore, disease status and concomitant therapies impacted both NK-cell FcγRIIIa expression and ADCC.

INTERPRETATION

FcγRIIIa is the major low affinity FcγR associated with rituximab response. Increased copies of the FCGR3A-158V allele (higher affinity for IgG1), influences clinical and biological responses to rituximab in autoimmunity. Enhancing FcγR-effector functions could improve the next generation of CD20-depleting therapies and genotyping may stratify patients for optimal treatment protocols.

FUNDING

Medical Research Council, National Institute for Health and Care Research, Versus Arthritis.

FCGR3A: A new biomarker with potential prognostic value for prostate cancer

To screen target gene cluster by bioinformatics analysis and verify them by in vitro experiment and clinicopathological correlation analysis. We try to find a new biomarker with prognostic value for prostate cancer (PCa). 42 candidate marker genes were constructed by protein protein interaction (PPI) network and enriched by KEGG pathway to find out the gene cluster we are interested in. Prognostic model was established to preliminarily analyze the prognostic value of this gene cluster in PCa, and Cox risk regression was used for comparative analysis. Immunohistochemistry was used to detect the expression of each gene in clinical tissue microarray. Finally, we analyzed the correlation between each gene and their clinicopathological features of PCa combined with TCGA clinical data. Based on the analysis of PPI and KEGG, we found the target gene cluster (FCGR3A, HAVCR2, CCR7 and CD28). Prognostic model analysis showed that this gene cluster had the ability to predict biochemical recurrence, and the survival rate and ROC analysis showed favorable prediction effect. Univariate Cox regression analysis showed that the risk scores of Gleason score (GS), T stage, N stage and PSA were significantly different (P<0.05), and the risk ratio of high expression was 2.30 times that of low expression (P=0.004). However, it was not statistically significant in multivariate Cox regression analysis (P>0.05). The results of tissue microarray showed that FCGR3A and HAVCR2 were highly expressed in PCa (P<0.01), while the expression of CCR7 and CD28 had no significant difference (P>0.05). Kaplan-Meier analysis showed that there was significant difference in BCR free survival of FCGR3A and HAVCR2 (FCGR3A, P=0.010; HAVCR2, P=0.018), while the expression of CCR7 and CD28 had no significant difference on the survival and prognosis of PCa patients (P>0.05). TCGA clinical data analysis found that the expression of FCGR3A had a unique correlation with the clinicopathological features of PCa, which was closely related to the tumor stage. The expression of FCGR3A is related to BCR free survival of PCa patients. Therefore, FCGR3A is a new biomarker with potential prognostic value of PCa.

A systematic literature review informing the consensus statement on efficacy and safety of pharmacological treatment with interleukin-6 pathway inhibition with biological DMARDs in immune-mediated inflammatory diseases

Objectives

Informing an international task force updating the consensus statement on efficacy and safety of biological disease-modifying antirheumatic drugs (bDMARDs) selectively targeting interleukin-6 (IL-6) pathway in the context of immune-mediated inflammatory diseases.

Methods

A systematic literature research of all publications on IL-6 axis inhibition with bDMARDs published between January 2012 and December 2020 was performed using MEDLINE, EMBASE and Cochrane CENTRAL databases. Efficacy and safety outcomes were assessed in clinical trials including their long-term extensions and observational studies. Meeting abstracts from ACR, EULAR conferences and results on clinicaltrials.gov were taken into consideration.

Results

187 articles fulfilled the inclusion criteria. Evidence for positive effect of IL-6 inhibition was available in various inflammatory diseases such as rheumatoid arthritis, juvenile idiopathic arthritis, giant cell arteritis, Takayasu arteritis, adult-onset Still’s disease, cytokine release syndrome due to chimeric antigen receptor T cell therapy and systemic sclerosis-associated interstitial lung disease. Newcomers like satralizumab and anti-IL-6 ligand antibody siltuximab have expanded therapeutic approaches for Castleman’s disease and neuromyelitis optica, respectively. IL-6 inhibition did not provide therapeutic benefits in psoriatic arthritis, ankylosing spondylitis and certain connective tissue diseases. In COVID-19, tocilizumab (TCZ) has proven to be therapeutic in advanced disease. Safety outcomes did not differ from other bDMARDs, except higher risks of diverticulitis and lower gastrointestinal perforations. Inconsistent results were observed in several studies investigating the risk for infections when comparing TCZ to TNF-inhibitors.

Conclusion

IL-6 inhibition is effective for treatment of several inflammatory diseases with a safety profile that is widely comparable to other bDMARDs.

Pharmacogenomics of Monoclonal Antibodies for the Treatment of Rheumatoid Arthritis

Precision medicine refers to a highly individualized and personalized approach to patient care. Pharmacogenomics is the study of how an individual’s genomic profile affects their drug response, enabling stable and effective drug selection, minimizing side effects, and maximizing therapeutic efficacy. Rheumatoid arthritis (RA) is an autoimmune disease that causes chronic inflammation in the joints. It mainly starts in peripheral joints, such as the hands and feet, and progresses to large joints, which causes joint deformation and bone damage due to inflammation of the synovial membrane. Here, we review various pharmacogenetic studies investigating the association between clinical response to monoclonal antibody therapy and their target genetic polymorphisms. Numerous papers have reported that some single nucleotide polymorphisms (SNPs) are related to the therapeutic response of several monoclonal antibody drugs including adalimumab, infliximab, rituximab, and tocilizumab, which target tumor necrosis factor (TNF), CD20 of B-cells, and interleukin (IL)-6. Additionally, there are some pharmacogenomic studies reporting on the association between the clinical response of monoclonal antibodies having various mechanisms, such as IL-1, IL-17, IL-23, granulocyte-macrophage colony-stimulating factor (GM-CSF) and the receptor activator of nuclear factor-kappa B (RANK) inhibition. Biological therapies are currently prescribed on a “trial and error” basis for RA patients. If appropriate drug treatment is not started early, joints may deform, and long-term treatment outcomes may worsen. Pharmacogenomic approaches that predict therapeutic responses for RA patients have the potential to significantly improve patient quality of life and reduce treatment costs.

Genetic Biomarkers as Predictors of Response to Tocilizumab in Rheumatoid Arthritis: A Systematic Review and Meta-Analysis

Rheumatoid arthritis (RA) is a lifelong, debilitating disease which incredibly impacts a patient’s quality of life if not treated to the optimal target. The clinical response of tocilizumab, an interleukin-6 (IL-6) inhibitor, is associated with several gene polymorphisms, particularly targeting the IL-6 pathway. This systematic review and meta-analysis seeks to investigate genetic biomarkers that predict the treatment outcome of tocilizumab therapy in RA patients. After evaluating the quality of retrieved records, five studies were chosen to carry out a quantitative synthesis involving 591 participants. We analysed genetic markers of IL-6R single nucleotide polymorphism (SNP)s rs12083537, rs2228145 and rs4329505, FCGR3A, CD69, GALNT18 and FCGR2A. A plausible finding based on meta-analysis revealed that RA patients with homozygous AA genotype for rs12083537 polymorphism of the IL-6R gene demonstrate a better response to TCZ treatment as opposed to homozygous and heterozygous patients with the G allele. Nonetheless, limitations in evaluating the available studies by meta-analysis include a lack of studies with dissimilarities in study design and outcome definitions, small sample sizes with low statistical power and heterogeneity of cohorts, a restricted the number of tested SNPs and small effects for the selected variants. Inconsistent finding remains as a great challenge to forge ahead towards personalised medicine for RA management.

Will the Use of Pharmacogenetics Improve Treatment Efficiency in COVID-19?

The COVID-19 pandemic is associated with a global health crisis and the greatest challenge for scientists and doctors. The virus causes severe acute respiratory syndrome with an outcome that is fatal in more vulnerable populations. Due to the need to find an efficient treatment in a short time, there were several drugs that were repurposed or repositioned for COVID-19. There are many types of available COVID-19 therapies, including antiviral agents (remdesivir, lopinavir/ritonavir, oseltamivir), antibiotics (azithromycin), antiparasitics (chloroquine, hydroxychloroquine, ivermectin), and corticosteroids (dexamethasone). A combination of antivirals with various mechanisms of action may be more efficient. However, the use of some of these medicines can be related to the occurrence of adverse effects. Some promising drug candidates have been found to be ineffective in clinical trials. The knowledge of pharmacogenetic issues, which translate into variability in drug conversion from prodrug into drug, metabolism as well as transport, could help to predict treatment efficiency and the occurrence of adverse effects in patients. However, many drugs used for the treatment of COVID-19 have not undergone pharmacogenetic studies, perhaps as a result of the lack of time.

Mechanisms underlying DMARD inefficacy in difficult-to-treat rheumatoid arthritis: a narrative review with systematic literature search

Management of RA patients has significantly improved over the past decades. However, a substantial proportion of patients is difficult-to-treat (D2T), remaining symptomatic after failing biological and/or targeted synthetic DMARDs. Multiple factors can contribute to D2T RA, including treatment non-adherence, comorbidities and co-existing mimicking diseases (e.g. fibromyalgia). Additionally, currently available biological and/or targeted synthetic DMARDs may be truly ineffective (‘true’ refractory RA) and/or lead to unacceptable side effects. In this narrative review based on a systematic literature search, an overview of underlying (immune) mechanisms is presented. Potential scenarios are discussed including the influence of different levels of gene expression and clinical characteristics. Although the exact underlying mechanisms remain largely unknown, the heterogeneity between individual patients supports the assumption that D2T RA is a syndrome involving different pathogenic mechanisms.

Pharmacogenetics and Precision Medicine Approaches for the Improvement of COVID-19 Therapies

Many drugs are being administered to tackle coronavirus disease 2019 (COVID-19) pandemic situations without establishing clinical effectiveness or tailoring safety. A repurposing strategy might be more effective and successful if pharmacogenetic interventions are being considered in future clinical studies/trials. Although it is very unlikely that there are almost no pharmacogenetic data for COVID-19 drugs, however, from inferring the pharmacokinetic (PK)/pharmacodynamic(PD) properties and some pharmacogenetic evidence in other diseases/clinical conditions, it is highly likely that pharmacogenetic associations are also feasible in at least some COVID-19 drugs. We strongly mandate to undertake a pharmacogenetic assessment for at least these drug–gene pairs (atazanavir–UGT1A1, ABCB1, SLCO1B1, APOA5; efavirenz–CYP2B6; nevirapine–HLA, CYP2B6, ABCB1; lopinavir–SLCO1B3, ABCC2; ribavirin–SLC28A2; tocilizumab–FCGR3A; ivermectin–ABCB1; oseltamivir–CES1, ABCB1; clopidogrel–CYP2C19, ABCB1, warfarin–CYP2C9, VKORC1; non-steroidal anti-inflammatory drugs (NSAIDs)–CYP2C9) in COVID-19 patients for advancing precision medicine. Molecular docking and computational studies are promising to achieve new therapeutics against SARS-CoV-2 infection. The current situation in the discovery of anti-SARS-CoV-2 agents at four important targets from in silico studies has been described and summarized in this review. Although natural occurring compounds from different herbs against SARS-CoV-2 infection are favorable, however, accurate experimental investigation of these compounds is warranted to provide insightful information. Moreover, clinical considerations of drug–drug interactions (DDIs) and drug–herb interactions (DHIs) of the existing repurposed drugs along with pharmacogenetic (e.g., efavirenz and CYP2B6) and herbogenetic (e.g., andrographolide and CYP2C9) interventions, collectively called multifactorial drug–gene interactions (DGIs), may further accelerate the development of precision COVID-19 therapies in the real-world clinical settings.

Drug levels, anti-drug antibodies and B-cell counts were not predictive of response in rheumatoid arthritis patients on low dose rituximab

OBJECTIVES

The REDO trial showed that ultra-low dose rituximab (500 mg or 200 mg) was similarly effective in the majority of rheumatoid arthritis (RA) patients. This pre-planned secondary analysis investigates 1) associations between rituximab dosage, drug levels, anti-drug antibodies (ADA) and B cell counts and 2) the predictive value of pharmacokinetic and -dynamic parameters, patient, disease and treatment characteristics in relation to response to ultra-low dose rituximab.

METHODS

For 140 RA patients from the REDO trial, differences in drug levels, ADA and B cell counts were examined at baseline, three and six months after dosing. Treatment response was defined as absence of flare and no extra rituximab or > 1 glucocorticoid injection received during follow-up. The association between potential predictors and response was investigated using logistic regression analyses.

RESULTS

Lower doses of rituximab resulted in lower drug levels but did not significantly affect ADA levels and B cell counts. 3 (10.7%), 12 (20.7%) and 7 (13.0%) patients failed to meet response-criteria in respectively the 1000 mg, 500 mg and 200 mg group. Drug levels, ADA and B cell counts as well as patient, disease and treatment characteristics were not predictive for response to ultra-low dose rituximab.

CONCLUSION

Results of this study further support that continued treatment with 500 or 200 mg rituximab is similarly effective as 1000 mg in RA patients doing well on rituximab. These results, combined with absence of clinical dose response relation in the original REDO study, suggest that 200 mg rituximab is not yet the lowest effective rituximab retreatment dose in RA.

Toward Overcoming Treatment Failure in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is an autoimmune disorder characterized by inflammation and bone erosion. The exact mechanism of RA is still unknown, but various immune cytokines, signaling pathways and effector cells are involved. Disease-modifying antirheumatic drugs (DMARDs) are commonly used in RA treatment and classified into different categories. Nevertheless, RA treatment is based on a "trial-and-error" approach, and a substantial proportion of patients show failed therapy for each DMARD. Over the past decades, great efforts have been made to overcome treatment failure, including identification of biomarkers, exploration of the reasons for loss of efficacy, development of sequential or combinational DMARDs strategies and approval of new DMARDs. Here, we summarize these efforts, which would provide valuable insights for accurate RA clinical medication. While gratifying, researchers realize that these efforts are still far from enough to recommend specific DMARDs for individual patients. Precision medicine is an emerging medical model that proposes a highly individualized and tailored approach for disease management. In this review, we also discuss the potential of precision medicine for overcoming RA treatment failure, with the introduction of various cutting-edge technologies and big data.

Bioinformatics Analysis Identifies Molecular Markers Regulating Development and Progression of Endometriosis and Potential Therapeutic Drugs

Endometriosis, a common disease that presents as polymorphism, invasiveness, and extensiveness, with clinical manifestations including dysmenorrhea, infertility, and menstrual abnormalities, seriously affects quality of life in women. To date, its underlying etiological mechanism of action and the associated regulatory genes remain unclear. This study aimed to identify molecular markers and elucidate mechanisms underlying the development and progression of endometriosis. Specifically, we downloaded five microarray expression datasets, namely, GSE11691, GSE23339, GSE25628, GSE7305, and GSE105764, from the Gene Expression Omnibus (GEO) database. These datasets, obtained from endometriosis tissues, alongside normal controls, were subjected to in-depth bioinformatics analysis for identification of differentially expressed genes (DEGs), followed by analysis of their function and pathways via gene ontology (GO) and KEGG pathway enrichment analyses. Moreover, we constructed a protein–protein interaction (PPI) network to explore the hub genes and modules, and then applied machine learning algorithms support vector machine-recursive feature elimination and least absolute shrinkage and selection operator (LASSO) analysis to identify key genes. Furthermore, we adopted the CIBERSORTx algorithm to estimate levels of immune cell infiltration while the connective map (CMAP) database was used to identify potential therapeutic drugs in endometriosis. As a result, a total of 423 DEGs, namely, 233 and 190 upregulated and downregulated, were identified. On the other hand, a total of 1,733 PPIs were obtained from the PPI network. The DEGs were mainly enriched in immune-related mechanisms. Furthermore, machine learning and LASSO algorithms identified three key genes, namely, apelin receptor (APLNR), C–C motif chemokine ligand 21 (CCL21), and Fc fragment of IgG receptor IIa (FCGR2A). Furthermore, 16 small molecular compounds associated with endometriosis treatment were identified, and their mechanism of action was also revealed. Taken together, the findings of this study provide new insights into the molecular factors regulating occurrence and progression of endometriosis and its underlying mechanism of action. The identified therapeutic drugs and molecular markers may have clinical significance in early diagnosis of endometriosis.

Influence of the FCGR2A rs1801274 and FCGR3A rs396991 Polymorphisms on Response to Abatacept in Patients with Rheumatoid Arthritis

Abatacept (ABA) is an immunosuppressant indicated for treatment of rheumatoid arthritis (RA). Effectiveness might be influenced by clinical RA variants and single-nucleotide polymorphisms (SNPs) in genes encoding protein FCGR2A (His131Arg) and FCGR3A (Phe158Val) involved in pharmacokinetics of ABA. An observational cohort study was conducted in 120 RA Caucasian patients treated with ABA for 6 and 12 months. Patients with the FCGR2A rs1801274-AA genotype (FCGR2A-p.131His) showed a better EULAR response (OR = 2.43; 95% CI = 1.01-5.92) at 12 months and low disease activity (LDA) at 6 months (OR = 3.16; 95% CI = 1.19-8.66) and 12 months (OR = 6.62; 95% CI = 1.25-46.89) of treatment with ABA. A tendency was observed towards an association between the FCGR3A rs396991-A allele (FCGR3A-p.158Phe) and better therapeutic response to ABA after 12 months of treatment (p = 0.078). Moreover, we found a significant association between the low-affinity FCGR2A/FCGR3A haplotypes variable and LDA after 12 months of ABA treatment (OR = 1.59; 95% CI = 1.01-2.58). The clinical variables associated with better response to ABA were lower age at starting ABA (OR = 1.06; 95% CI = 1.02-1.11) and greater duration of ABA treatment (OR = 1.02; 95% CI = 1.01-1.04), lower duration of previous biological therapies (OR = 0.99; 95% CI = 0.98-0.99), non-administration of concomitant disease-modifying antirheumatic drugs (DMARDs) (OR = 24.53; 95% CI = 3.46-523.80), non-use of concomitant glucocorticoids (OR = 0.12; 95% CI = 0.02-0.47), monotherapy (OR = 19.22; 95% CI = 2.05-343.00), lower initial patient's visual analogue scale (PVAS) value (OR = 0.95; 95% CI = 0.92-0.97), and lower baseline ESR (OR = 0.92; 95% CI = 0.87-0.97). This study showed that high-affinity FCGR2A-p.131His variant, low-affinity FCGR3A-p.158Phe variant, and combined use of FCGR2A/FCGR3A genetic variations could affect ABA effectiveness. Further studies will be required to confirm these results.

COVID-19 infection and rheumatoid arthritis: mutual outburst cytokines and remedies

In March 2020, COVID-19 infection caused by SARS-CoV-2 has been declared to be a global pandemic, where its complications, severity and mortality are reported to be due to the released inflammatory cytokines or the so-called cytokine storm. This is quite similar to that observed in the autoimmune and chronic inflammatory rheumatic disease, rheumatoid arthritis (RA). It was hypothesized that RA patients are at a higher risk of acquiring COVID-19; however, recent studies reported that they are not when compared to the rest of the population. In this review, we aim to highlight the mutual pathological features, cytokine profiles and risk factors between COVID-19 and RA. Also, many researchers are currently working to explore therapeutic agents that could aid in the eradication of COVID-19 infection. Due to the similarity between the inflammation status in COVID-19 and RA, many anti-rheumatic drugs such as hydroxychloroquine, tocilizumab, baricitinib and anakinra were proposed to be therapeutic modalities for COVID-19 infection.

Influence of Genetic Polymorphisms on Response to Biologics in Moderate-to-Severe Psoriasis

Psoriasis is a chronic inflammatory skin pathology of autoimmune origin and unknown etiology. There are various therapies for treating it, including a wide range of biopharmaceuticals indicated in moderate-to-severe psoriasis. Depending on their therapeutic target, they are classified as tumor necrosis factor inhibitors (anti-TNF) or cytokine inhibitors (interleukin-12, 23, and 17 antagonists). Although they have proved effective and safe, in clinical practice, many patients show a short- and long-term suboptimal response and even varying degrees of toxicity. This variability in response may be influenced by genetic factors, such as polymorphisms in the genes involved in the pathological environment, metabolism or mechanism of action of the drug that could affect the effectiveness and toxicity of biological therapies. This review assesses pharmacogenetic studies of the impact of genetic factors on response to biopharmaceuticals and toxicity in patients diagnosed with moderate-to-severe psoriasis. The results suggest that polymorphisms detected in the HLA genes, in genes that encode cytokines (TNF, IL genes, TNFAIP3), transporters (PDE3A-SLCO1C1, SLC12A8), receptors (TNFRSF1B, CD84, FCGR2A and FCGR3A, IL17RA, IL23R, TLR genes, PGLYRP4) and associated proteins (TNFAIP3, LY96, TIRAP, FBXL19), as well as other genes implicated in the pathogenesis of psoriasis (CDKAL1, CARD14, PTTG1, MAP3K1, ZNF816A, GBP6, CTNNA2, HTR2A, CTLA4, TAP1) can be used in the future as predictive markers of treatment response and/or toxicity with biological therapies in patients diagnosed with moderate-to-severe psoriasis, tailoring treatment to the individual patient.

Pharmacogenomics and COVID-19: clinical implications of human genome interactions with repurposed drugs

The outbreak of Coronavirus disease 2019 (COVID-19) has evolved into an emergent global pandemic. Many drugs without established efficacy are being used to treat COVID-19 patients either as an offlabel/compassionate use or as a clinical trial. Although drug repurposing is an attractive approach with reduced time and cost, there is a need to make predictions on success before the start of therapy. For the optimum use of these repurposed drugs, many factors should be considered such as drug–gene or dug–drug interactions, drug toxicity, and patient co-morbidity. There is limited data on the pharmacogenomics of these agents and this may constitute an obstacle for successful COVID-19 therapy. This article reviewed the available human genome interactions with some promising repurposed drugs for COVID-19 management. These drugs include chloroquine (CQ), hydroxychloroquine (HCQ), azithromycin, lopinavir/ritonavir (LPV/r), atazanavir (ATV), favipiravir (FVP), nevirapine (NVP), efavirenz (EFV), oseltamivir, remdesivir, anakinra, tocilizumab (TCZ), eculizumab, heme oxygenase 1 (HO-1) regulators, renin–angiotensin–aldosterone system (RAAS) inhibitors, ivermectin, and nitazoxanide. Drug-gene variant pairs that may alter the therapeutic outcomes in COVID-19 patients are presented. The major drug variant pairs that associated with variations in clinical efficacy include CQ/HCQ (CYP2C8, CYP2D6, ACE2, and HO-1); azithromycin (ABCB1); LPV/r (SLCO1B1, ABCB1, ABCC2 and CYP3A); NVP (ABCC10); oseltamivir (CES1 and ABCB1); remdesivir (CYP2C8, CYP2D6, CYP3A4, and OATP1B1); anakinra (IL-1a); and TCZ (IL6R and FCGR3A). The major drug variant pairs that associated with variations in adverse effects include CQ/HCQ (G6PD; hemolysis and ABCA4; retinopathy), ATV (MDR1 and UGT1A1*28; hyperbilirubinemia; and APOA5; dyslipidemia), NVP (HLA-DRB1*01, HLA-B*3505 and CYP2B6; skin rash and MDR1; hepatotoxicity), and EFV (CYP2B6; depression and suicidal tendencies).

Biomarkers to Personalize the Treatment of Rheumatoid Arthritis: Focus on Autoantibodies and Pharmacogenetics

Rheumatoid arthritis (RA) is a chronic inflammatory disease that is very complex and heterogeneous. If not adequately treated, RA patients are likely to manifest excess of morbidity and disability with an important impact on the quality of life. Pharmacological treatment is based on the administration of the disease-modifying antirheumatic drugs (DMARDs), subdivided into conventional synthetic (csDMARDs), targeted synthetic (tsDMARDs), and biological (bDMARDs). bDMARDs are now frequently administered in patients, both as alternative treatment and together with csDMARDs. Unfortunately, there is a therapeutic response variability both to old and new drugs. Therefore, to identify pre-therapeutic and on-treatment predictors of response is a priority. This review aims to summarize recent advances in understanding the causes of the variability in treatment response in RA, with particular attention to predictive potential of autoantibodies and DMARD pharmacogenetics. In recent years, several biomarkers have been proposed to personalize the therapy. Unfortunately, a magic bullet does not exist, as many factors concur to disease susceptibility and treatment outcomes, acting around the patient’s congenital background. Models integrating demographic, clinical, biochemical, and genetic data are needed to enhance the predictive capacity of specific factors singularly considered to optimize RA treatment in light of multidisciplinary patient management.

Impact of Single-Nucleotide Polymorphisms of CTLA-4, CD80 and CD86 on the Effectiveness of Abatacept in Patients with Rheumatoid Arthritis

Abatacept (ABA) is used as a first-line treatment in patients diagnosed with moderate and severe rheumatoid arthritis (RA). The interindividual response to ABA therapy is very variable in these patients. The objective of our study was therefore to investigate the role of polymorphisms of the CTLA-4, CD80 and CD86 genes, as well as that of clinical factors of the disease, in the response to ABA in patients with RA. A retrospective cohort study was carried out in 109 patients receiving treatment with ABA and diagnosed with RA. The genetic variables were analyzed using real-time PCR with TaqMan^® probes. The patients were classified according to the European League Against Rheumatism (EULAR) criteria at 6 and 12 months from start of treatment. The independent variables associated with higher EULAR response were lower duration of previous biologic disease-modifying anti-rheumatic drugs and lower baseline values of the disease activity score 28 after 6 months of ABA treatment; and lower baseline patient’s visual analogue scale (PVAS) after 12 months. In addition, a significant association was found between duration of ABA treatment, non-administration of concomitant glucocorticoids and lower baseline values of the number of inflamed joints and erythrocyte sedimentation rate clinical variables, with remission of the disease after 6 months’ treatment with ABA. Finally, remission of the disease after 12 months’ treatment with ABA was associated with earlier age at start of ABA therapy and lower number of previous biologic therapies (BTs). The CTLA-4rs5742909-T allele and the CTLA-4rs231775-G allele were found to be associated with satisfactory EULAR response and low disease activity (LDA) after 12 months’ treatment with ABA (CTLA-4rs5742909 T vs. CC; OR = 5.88; CI_95% = 1.48–23.29 and OR = 4.75; CI_95% = 1.35–17.94, respectively, and CTLA-4rs231775 G vs. AA, OR = 3.48; CI_95% = 1.20–10.09 and OR = 4.68; CI_95% = 1.49–17.94, respectively). In conclusion, patients with RA treated with ABA showed better EULAR response and LDA rate when they had the CTLA-4 rs5742909-T or CTLA-4 rs231775-G polymorphisms; furthermore, this remission rate increased in patients that began ABA treatment earlier, those with a lower number of previous BTs and those with a lower PVAS value.

Important Pharmacogenetic Information for Drugs Prescribed During the SARS-CoV-2 Infection (COVID-19)

In December 2019, the severe acute respiratory syndrome virus-2 pandemic began, causing the coronavirus disease 2019. A vast variety of drugs is being used off-label as potential therapies. Many of the repurposed drugs have clinical pharmacogenetic guidelines available with therapeutic recommendations when prescribed as indicated on the drug label. The aim of this review is to provide a comprehensive summary of pharmacogenetic biomarkers available for these drugs, which may help to prescribe them more safely.

A pharmacokinetic evaluation of the rituximab biosimilar CT-P10 in the treatment of rheumatoid arthritis

INTRODUCTION

CT-P10 is the first biosimilar of rituximab (RTX) for the treatment of rheumatoid arthritis (RA). The application of valuable biosimilar for the treatment of RA may decrease economic burden of society, and disease activity of RA. Thus, it is worthwhile to identify the economic advantage and further requirement for the proper use of CT-P10 in real world.

AREAS COVERED

Literature searching was performed to identify suitable references written in English for this review article. Rituximab, biosimilar, CT-P10, and rheumatoid arthritis were used as keywords. Current state of RA treatment, position of RTX in the recommendations for the treatment of RA, current status of RTX biosimilar development were assessed before evaluating CT-P10 itself. Physicochemical property, pharmacokinetic profile through phase I to phase III studies, pharmacodynamics, toxicology data, clinical efficacy, and safety were reviewed.

EXPERT OPINION

As the first biosimilar to originator RTX, CT-P10 may be a useful alternative for the treatment of RA in all indications for originator RTX. In addition, more studies are required to identify long-term effectiveness and safety of CT-P10 in real world. It is also important to find out new indications of CT-P10 and effective mechanisms to lessen nocebo effect against biosimilar including CT-P10.

Polymorphisms Involved in Response to Biological Agents Used in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a systemic disease that leads to joint destruction. During the last decade, the therapy of RA has been principally based on biological drugs. Although the efficacy of biological therapy has been established, patients demonstrated a high heterogeneity in clinical response to treatment. Several genetic polymorphisms play a part in the different response to biological drugs. This review summarizes the pharmacogenetics of biological agents approved for clinical RA treatment. We reviewed PubMed papers published over the past 20 years (2000-2020), inserting as the search term "rheumatoid arthritis and polymorphisms". Despite some studies showing important correlations between genetic polymorphisms and response to biological therapy in RA patients, most of these findings are still lacking and inconsistent. The personalized treatment according to a pharmacogenetics approach is promising but the available pharmacogenetics data on biological treatment in RA are not adequate and reliable to recommend pharmacogenetic tests before starting biological therapy in RA patients.

Pharmacogenomics of COVID-19 therapies

A new global pandemic of coronavirus disease 2019 (COVID-19) has resulted in high mortality and morbidity. Currently numerous drugs are under expedited investigations without well-established safety or efficacy data. Pharmacogenomics may allow individualization of these drugs thereby improving efficacy and safety. In this review, we summarized the pharmacogenomic literature available for COVID-19 drug therapies including hydroxychloroquine, chloroquine, azithromycin, remdesivir, favipiravir, ribavirin, lopinavir/ritonavir, darunavir/cobicistat, interferon beta-1b, tocilizumab, ruxolitinib, baricitinib, and corticosteroids. We searched PubMed, reviewed the Pharmacogenomics Knowledgebase (PharmGKB®) website, Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines, the U.S. Food and Drug Administration (FDA) pharmacogenomics information in the product labeling, and the FDA pharmacogenomics association table. We found several drug-gene variant pairs that may alter the pharmacokinetics of hydroxychloroquine/chloroquine (CYP2C8, CYP2D6, SLCO1A2, and SLCO1B1); azithromycin (ABCB1); ribavirin (SLC29A1, SLC28A2, and SLC28A3); and lopinavir/ritonavir (SLCO1B1, ABCC2, CYP3A). We also identified other variants, that are associated with adverse effects, most notable in hydroxychloroquine/chloroquine (G6PD; hemolysis), ribavirin (ITPA; hemolysis), and interferon β -1b (IRF6; liver toxicity). We also describe the complexity of the risk for QT prolongation in this setting because of additive effects of combining more than one QT-prolonging drug (i.e., hydroxychloroquine/chloroquine and azithromycin), increased concentrations of the drugs due to genetic variants, along with the risk of also combining therapy with potent inhibitors. In conclusion, although direct evidence in COVID-19 patients is lacking, we identified potential actionable genetic markers in COVID-19 therapies. Clinical studies in COVID-19 patients are deemed warranted to assess potential roles of these markers.

Fetuin-A and thyroxin binding globulin predict rituximab response in rheumatoid arthritis patients with insufficient response to anti-TNFα

OBJECTIVES

Rheumatoid arthritis (RA) is a debilitating disease, but patient management and treatment have been revolutionized since the advent of bDMARDs. However, about one third of RA patients do not respond to specific bDMARD treatment without clear identified reasons. Different bDMARDs must be tried until the right drug is found. Here, we sought to identify a predictive protein signature to stratify patient responsiveness to rituximab (RTX) among patients with an insufficient response to a first anti-TNFα treatment.

METHODS

Serum samples were collected at baseline before RTX initiation. A proteomics study comparing responders and nonresponders was conducted to identify and select potential predictive biomarkers whose concentration was measured by quantitative assays. Logistic regression was performed to determine the best biomarker combination to predict good or nonresponse to RTX (EULAR criteria after 6 months' treatment).

RESULTS

Eleven biomarkers potentially discriminating between responders and nonresponders were selected following discovery proteomics. Quantitative immunoassays and univariate statistical analysis showed that fetuin-A and thyroxine binding globulin (TBG) presented a good capacity to discriminate between patient groups. A logistic regression analysis revealed that the combination of fetuin-A plus TBG could accurately predict a patient's responsiveness to RTX with an AUC of 0.86, sensitivity of 80%, and a specificity of 79%.

CONCLUSION

In RA patients for whom a first anti-TNFα treatment has failed, the serum abundance of fetuin-A and TBG before initiating RTX treatment is an indicator for their response status at 6 months. ClinicalTrials.gov identifier: NCT01000441. Key Points • Proteomic analysis revealed 11 putative predictive biomarkers to discriminate rituximab responder vs. nonresponder RA patients. • Fetuin-A and TBG are significantly differentially expressed at baseline in rituximab responder vs. nonresponder RA patients. • Algorithm combining fetuin-A and TBG accurately predicts response to rituximab in RA patients with insufficient response to TNFi.

A comprehensive review of rituximab therapy in rheumatoid arthritis patients

Rituximab (RTX) is an approved treatment for rheumatoid arthritis (RA) patients that do not respond adequately to disease-modifying antirheumatic drugs. However, different new concerns, such as efficacy, optimum dose, safety issues, prediction of response to RTX, and pregnancy outcomes have attracted a lot of attention. The PubMed database was systematically reviewed for the last published articles, new findings, and controversial issues regarding RTX therapy in RA using "Rheumatoid arthritis" AND "rituximab" keywords, last updated on June 18, 2019. From 1812 initial recorders, 162 studies met the criteria. Regarding the optimum dose, low-dose RTX therapy (2 × 500 mg) seems as effective as standard dose (2 × 1000 mg), safer, and more cost-effective. The most common reported safety challenges included de novo infections, false negative serologic tests of viral infections, reactivation of chronic infections, interfering with vaccination outcome, and development of de novo psoriasis. Other less reported side effects are infusion reactions, nervous system disorders, and gastrointestinal disorders. Lower exposure to other biologics, presence of some serological markers (e.g., anti-RF, anti-CCP, IL-33, ESR), specific variations in FCGR3A, FCGR2A, TGFβ1, IL6, IRF5, BAFF genes, and also EBV-positivity could be used to predict response to RTX. Although there is no evidence of the teratogenic effect of RTX, it is recommended that women do not expose themselves to RTX at least 6 months before the conception. Only a reversible reduction of B cell-count in the offspring may be the pregnancy-related outcome. Although RTX is an effective therapeutic option for RA, more studies on optimum doses, prevention of RTX-related side effects, prediction of RTX response, and safety during the pregnancy are required.