Validation of a Prognostic Multivariable Prediction Model for Insufficient Clinical Response to Methotrexate in Early Rheumatoid Arthritis and Its Clinical Application in Evidencio

Dihydroartemisinin alleviates erosive bone destruction by modifying local Treg cells in inflamed joints: A novel role in the treatment of rheumatoid arthritis

Treg cell-based therapy has exhibited promising efficacy in combatting rheumatoid arthritis (RA). Dihydroartemisinin (DHA) exerts broad immunomodulatory effects across various diseases, with its recent spotlight on T-cell regulation in autoimmune conditions. The modulation of DHA on Treg cells and its therapeutic role in RA has yet to be fully elucidated. This study seeks to unveil the influence of DHA on Treg cells in RA and furnish innovative substantiation for the potential of DHA to ameliorate RA. To this end, we initially scrutinized the impact of DHA-modulated Treg cells on osteoclast (OC) formation in vitro using Treg cell-bone marrow-derived monocyte (BMM) coculture systems. Subsequently, employing the collagen-induced arthritis (CIA) rat model, we validated the efficacy of DHA and probed its influence on Treg cells in the spleen and popliteal lymph nodes (PLN). Finally, leveraging deep proteomic analysis with data-independent acquisition (DIA) and parallel accumulation-serial fragmentation (PASEF) technology, we found the alterations in the Treg cell proteome in PLN by proteomic analysis. Our findings indicate that DHA augmented suppressive Treg cells, thereby impeding OC formation in vitro. Consistently, DHA mitigated erosive joint destruction and osteoclastogenesis by replenishing splenic and joint-draining lymph node Treg cells in CIA rats. Notably, DHA induced alterations in the Treg cell proteome in PLN, manifesting distinct upregulation of alloantigen Col2a1 (Type II collagen alfa 1 chain) and CD8a (T-cell surface glycoprotein CD8 alpha chain) in Treg cells, signifying DHA's targeted modulation of Treg cells, rendering them more adept at sustaining immune tolerance and impeding bone erosion. These results unveil a novel facet of DHA in the treatment of RA.

The effect of smoking on response to methotrexate in rheumatoid arthritis patients: A systematic review and meta-analysis

OBJECTIVES

In the current study, we aimed to investigate the effect of smoking on inadequate response to methotrexate (MTX-IR) in rheumatoid arthritis (RA) patients.

METHODS

We searched PubMed, Embase, and Web of Science until 6 June 2022. Observational or interventional studies investigating MTX-IR in RA patients based on smoking status were included. Two independent reviewers assessed the risk of bias and the certainty of the evidence using the Risk of Bias in Nonrandomized Studies-of Interventions and Grades of Recommendation, Assessment, Development, and Evaluation tools, respectively.

RESULTS

We included 23 studies in the systematic review and 13 in the meta-analysis. Of the 13 included studies, 6 had a moderate risk, 3 had a serious risk, and 4 had a critical risk of bias. The overall random-effect meta-analysis suggested that smokers were 58% more likely to be MTX-IR when compared with nonsmokers [odds ratio (OR) 1.58, 95% confidence interval 1.21-2.06; P = .001; I2 = 69.3%]. The common-effect meta-analysis of the adjusted ORs demonstrated an overall OR of 2.69 (1.88-3.83; P < .001; I2 = 27.1%).

CONCLUSIONS

The current study showed that smoking is a significant predictor of MTX-IR, especially in disease-modifying antirheumatic drug-naïve early RA patients, as most of the included studies in the meta-analysis consisted of this population.

Methotrexate Polyglutamates Exposure - Response Modeling in a Large Cohort of Rheumatoid Arthritis Patients Starting Methotrexate

Methotrexate polyglutamates (MTX-PG) concentrations in red blood cells (RBCs) have been suggested as a biomarker of response in patients with rheumatoid arthritis (RA) receiving low-dose MTX therapy. We investigated the association and interpatient variability between RBC-MTX-PG3-5 -exposure and response in patients with RA starting MTX. Data of three prospective cohorts were available. The relationship between exposure and Disease Activity Score in 28 joints (DAS28) was analyzed using a population pharmacokinetic-pharmacodynamic model. Relevant covariates were tested using full covariate modeling and backward elimination. From 395 patients, 3,401 MTX-PG concentrations and 1,337 DAS28 measurements were available between 0 and 300 days after MTX treatment onset. The developed model adequately described the time course of MTX-PG3-5 and DAS28. The median MTX-PG3-5 level at month 1 was 30.9 nmol/L (interquartile range (IQR): 23.6-43.7; n = 41) and at month 3: 69.3 nmol/L (IQR: 17.9-41.2; n = 351). Clearance of MTX-PG3-5 from RBCs was 28% lower (95% confidence interval (CI): 23.6-32.8%) in a woman and 10% lower (95% CI: 7.7-12.4%) in a 65-year-old compared with a 35-year-old patient. MTX-PG3-5 concentrations associated with DAS28: half-maximal effective concentration (EC50 ) was 9.14 nmol/L (95% CI: 4.2 nmol/L-14.1 nmol/L). EF at 80% (EC80 ) above 47 nmol/L was regarded as the optimal response. Independent of the MTX-PG 3-5 - response association, co-administration of disease-modifying antirheumatic drugs and corticosteroids improved response (additive effect on maximum effect (Emax )), whereas smoking, high body mass index and low albumin decreased Emax . In patients with RA starting MTX, RBC-MTX-PG3-5 was associated with clinical response. A dose increase is suggested when MTX-PG3-5 at month 1 is below 9.15 nmol/L, continued with the same dose when the concentration is above 47 nmol/L, and consider other treatment options above 78 nmol/L from 3 months onwards.

Clinical prediction models of rheumatoid arthritis and its complications: focus on cardiovascular disease and interstitial lung disease

Rheumatoid arthritis (RA) is a chronic, systemic, autoimmune disease of unknown etiology with erosive, symmetric polyarthritis as the main clinical manifestations. Its basic pathological changes are the formation of synovitis, and patients gradually develop destruction of articular cartilage destruction and bone erosion, which eventually leads to joint deformity, disability, and various extra-articular manifestations. Clinical prediction models (CPMs), also known as risk prediction models or risk scores, are mathematical formulas used to estimate the probability that a given individual will have a disease or an outcome in the future. The models are mainly divided into two categories: diagnostic models and prognostic models, which can be used to provide information on disease diagnosis or prognosis to help make better medical decisions. Currently, there is no cure for RA, but effective early diagnosis and treatment are crucial for limiting the severity of the disease and preventing the occurrence and development of complications. This paper reviews the CPMs associated with RA and its related complications, including cardiovascular disease (CVD) and interstitial lung disease (ILD), in order to provide reference and evidence for the early diagnosis and treatment of these diseases and personalized medicine for patients. In addition, the possible pathogenesis and risk factors of these comorbidities are summarized, and possible directions for future related research are prospected.

Pharmacokinetics of oral and subcutaneous methotrexate in red and white blood cells in patients with early rheumatoid arthritis: the methotrexate monitoring trial

OBJECTIVE

To investigate the pharmacokinetics of methotrexate polyglutamate (MTX-PG) accumulation in red blood cells (RBCs) and peripheral blood mononuclear cells (PBMCs) in patients with early rheumatoid arthritis (RA) after oral and subcutaneous MTX treatment.

METHODS

In a clinical prospective cohort study (Methotrexate Monitoring study), newly diagnosed patients with RA were randomised for oral or subcutaneous MTX. At 1, 2, 3 and 6 months after therapy initiation, blood was collected and RBCs and PBMCs were isolated. MTX-PG1-6 concentrations were determined by mass spectrometry methods using stable isotopes of MTX-PG1-6 as internal standards.

RESULTS

43 patients (mean age: 58.5 years, 77% female) were included. PBMCs and RBCs revealed disparate pharmacokinetic profiles in both absolute MTX-PG accumulation levels and distribution profiles. Intracellular MTX-PG accumulation in PBMCs was significantly (p<0.001) 10-fold to 20-fold higher than RBCs at all time points, regardless of the administration route. MTX-PG distribution in PBMCs was composed of mostly MTX-PG1 (PG1>PG2>PG3). Remarkably, the distribution profile in PBMCs remained constant over 6 months. RBCs accumulated mainly MTX-PG1 and lower levels of MTX-PG2-5 at t=1 month. After 3 months, MTX-PG3 was the main PG-moiety in RBCs, a profile retained after 6 months of MTX therapy. Subcutaneous MTX administration results in higher RBC drug levels than after oral administration, especially shortly after treatment initiation.

CONCLUSIONS

This is the first study reporting disparate MTX-PG accumulation profiles in RBCs versus PBMCs in newly diagnosed patients with RA during 6 months oral or subcutaneous MTX administration. This analysis can contribute to improved MTX therapeutic drug monitoring for patients with RA.

TRIAL REGISTRATION NUMBER

NTR 7149.

Pre-defined gene co-expression modules in rheumatoid arthritis transition towards molecular health following anti-TNF therapy

BACKGROUND

No reliable biomarkers to predict response to TNF inhibitors (TNFi) in RA patients currently exist. The aims of this study were to replicate changes in gene co-expression modules that were previously reported in response to TNFi therapy in RA; to test if changes in module expression are specific to TNFi therapy; and to determine whether module expression transitions towards a disease-free state in responding patients.

METHOD

Published transcriptomic data from the whole blood of disease-free controls (n = 10) and RA patients, treated with the TNFi adalimumab (n = 70) or methotrexate (n = 85), were studied. Treatment response was assessed using the EULAR response criteria following 3 or 6 months of treatment. Change in transcript expression between pre- and post-treatment was recorded for previously defined modules. Linear mixed models tested whether modular expression after treatment transitioned towards a disease-free state.

RESULTS

For 25 of the 27 modules, change in expression between pre- and post-treatment in the adalimumab cohort replicated published findings. Of these 25 modules, six transitioned towards a disease-free state by 3 months (P < 0.05), irrespective of clinical response. One module (M3.2), related to inflammation and TNF biology, significantly correlated with response to adalimumab. Similar patterns of modular expression, with reduced magnitude, were observed in the methotrexate cohort.

CONCLUSION

This study provides independent validation of changes in module expression in response to therapy in RA. However, these effects are not specific to TNFi. Further studies are required to determine whether specific modules could assist molecular classification of therapeutic response.

Early prediction of treatment response in rheumatoid arthritis by quantitative macrophage PET

Objective

To determine whether macrophage positron emission tomography (PET)/computed tomography (CT) imaging using (R)-[¹¹C]PK11195 at 0 and 2 weeks is associated with clinical response at 13 weeks in patients with early rheumatoid arthritis (RA).

Methods

Whole-body (R)-[¹¹C]PK11195 PET/CT scans were performed at baseline and after 2 weeks of COBRA-light (combination therapy of methotrexate and prednisone) treatment in 35 patients with clinically active early RA. Clinical assessment (Disease Activity Score of 44 joints (DAS44)) was performed at 0, 2 and 13 weeks of treatment. PET/CT scans were assessed visually by two blinded, experienced readers, and by calculating standardised uptake values (SUVs) for shoulders, elbows, hips, knees, and hand and feet joints. Clinical and PET variables were compared using (multivariate) linear regression.

Results

18 males and 17 females were included (baseline DAS44=3.2 ± 1.0). 171 out of 1470 joints were visually PET positive at baseline, decreasing to 100 joints after 2 weeks. In general, small feet joints showed the highest uptake at baseline, and the largest decrease after 2 weeks (Δ_0-2). Neither baseline nor Δ_0-2 PET measures correlated with DAS44 at 13 weeks. However, at 2 weeks, average SUV of the feet significantly correlated with DAS44 at 13 weeks (R²=0.14, p=0.04). In a multivariable model, DAS44 and average SUV of the feet at 2 weeks showed substantial combined predictive value (combined R²=0.297, p<0.01).

Conclusion

Quantitative macrophage PET assessment of feet joints, together with DAS44, after 2 weeks of COBRA light treatment in patients with early RA correlates with clinical response after 3 months of treatment.

Smoking and Methotrexate Inefficacy in Rheumatoid Arthritis: What About Underlying Molecular Mechanisms?

The study by Safy-Khan, et al in the current issue of The Journal of Rheumatology ¹ reports that in a methotrexate (MTX)-based treatment regimen for patients with early arthritis, current smoking was significantly associated with a smaller reduction of Disease Activity Score in 28 joints (DAS28) over time compared to noncurrent smoking. This negative effect of current smoking on DAS28 was dose-dependent: patients who smoked 10-19 cigarettes per day did worse than patients who smoked 1-9 cigarettes per day.

Complex Machine-Learning Algorithms and Multivariable Logistic Regression on Par in the Prediction of Insufficient Clinical Response to Methotrexate in Rheumatoid Arthritis

The goals of this study were to examine whether machine-learning algorithms outperform multivariable logistic regression in the prediction of insufficient response to methotrexate (MTX); secondly, to examine which features are essential for correct prediction; and finally, to investigate whether the best performing model specifically identifies insufficient responders to MTX (combination) therapy. The prediction of insufficient response (3-month Disease Activity Score 28-Erythrocyte-sedimentation rate (DAS28-ESR) > 3.2) was assessed using logistic regression, least absolute shrinkage and selection operator (LASSO), random forest, and extreme gradient boosting (XGBoost). The baseline features of 355 rheumatoid arthritis (RA) patients from the “treatment in the Rotterdam Early Arthritis CoHort” (tREACH) and the U-Act-Early trial were combined for analyses. The model performances were compared using area under the curve (AUC) of receiver operating characteristic (ROC) curves, 95% confidence intervals (95% CI), and sensitivity and specificity. Finally, the best performing model following feature selection was tested on 101 RA patients starting tocilizumab (TCZ)-monotherapy. Logistic regression (AUC = 0.77 95% CI: 0.68–0.86) performed as well as LASSO (AUC = 0.76, 95% CI: 0.67–0.85), random forest (AUC = 0.71, 95% CI: 0.61 = 0.81), and XGBoost (AUC = 0.70, 95% CI: 0.61–0.81), yet logistic regression reached the highest sensitivity (81%). The most important features were baseline DAS28 (components). For all algorithms, models with six features performed similarly to those with 16. When applied to the TCZ-monotherapy group, logistic regression’s sensitivity significantly dropped from 83% to 69% (p = 0.03). In the current dataset, logistic regression performed equally well compared to machine-learning algorithms in the prediction of insufficient response to MTX. Models could be reduced to six features, which are more conducive for clinical implementation. Interestingly, the prediction model was specific to MTX (combination) therapy response.

Identification of Metabolic Biomarkers in Relation to Methotrexate Response in Early Rheumatoid Arthritis

This study aimed to identify baseline metabolic biomarkers for response to methotrexate (MTX) therapy in rheumatoid arthritis (RA) using an untargeted method. In total, 82 baseline plasma samples (41 insufficient responders and 41 sufficient responders to MTX) were selected from the Treatment in the Rotterdam Early Arthritis Cohort (tREACH, trial number: ISRCTN26791028) based on patients' EULAR response at 3 months. Metabolites were assessed using high-performance liquid chromatography-quadrupole time of flight mass spectrometry. Differences in metabolite concentrations between insufficient and sufficient responders were assessed using partial least square regression discriminant analysis (PLS-DA) and Welch's t-test. The predictive performance of the most significant findings was assessed in a receiver operating characteristic plot with area under the curve (AUC), sensitivity and specificity. Finally, overrepresentation analysis was performed to assess if the best discriminating metabolites were enriched in specific metabolic events. Baseline concentrations of homocystine, taurine, adenosine triphosphate, guanosine diphosphate and uric acid were significantly lower in plasma of insufficient responders versus sufficient responders, while glycolytic intermediates 1,3-/2,3-diphosphoglyceric acid, glycerol-3-phosphate and phosphoenolpyruvate were significantly higher in insufficient responders. Homocystine, glycerol-3-phosphate and 1,3-/2,3-diphosphoglyceric acid were independent predictors and together showed a high AUC of 0.81 (95% CI: 0.72-0.91) for the prediction of insufficient response, with corresponding sensitivity of 0.78 and specificity of 0.76. The Warburg effect, glycolysis and amino acid metabolism were identified as underlying metabolic events playing a role in clinical response to MTX in early RA. New metabolites and potential underlying metabolic events correlating with MTX response in early RA were identified, which warrant validation in external cohorts.