Precision medicine and management of rheumatoid arthritis

Early prediction of bone destruction in rheumatoid arthritis through machine learning analysis of plasma metabolites

BACKGROUND

To develop a predictive model for bone destruction in patients with rheumatoid arthritis (RA), based on the characteristics of plasma metabolites and common clinical indicators.

METHODS

The cohort comprised 60 patients with RA, with baseline metabolite features identified using the liquid chromatograph-mass spectrometer system. Radiographic outcomes were assessed using the van der Heijde-modified total Sharp score (mTSS) following a one-year follow-up period to quantify bone destruction. The longitudinal association between metabolites and radiographic progression was analyzed using several machine learning algorithms, and the significance of core metabolites was calculated. A new model incorporating metabolites and clinical indicators was created to evaluate its predictive performance for radiographic progression; the model was compared with other prediction models.

RESULTS

The median increase in mTSS was 3.50. Of the 774 detected metabolites, 77 differed between patients with different outcomes. Core metabolites identified using the Gaussian Naive Bayes algorithm included mangiferic acid, O-acetyl-L-carnitine, 5,8,11-eicosatrienoic acid, and 16-methylheptadecanoic acid. A standardized bone erosion risk score (BERS) was developed based on these core metabolite features for assessing the radiographic progression outcome. Individuals with a high BERS exhibited a lower risk of rapid radiographic progression than those with a lower score (OR = 0.01, 95% CI = 0.01-0.03, P = 0.003). The "China-Japan Friendship Hospital-BERS Model" (CjBM), combining BERS with clinical features (methotrexate and C-reactive protein), produced an area under the receiver operating characteristic curve of 0.800. Moreover, compared with the reported models, the CjBM showed near statistical significance in identifying rapid radiographic progression; adding BERS can improve the discrimination of the original reported model (PDeLong=0.035).

CONCLUSIONS

The CjBM was developed for early prediction of bone destruction in patients with RA, and the evaluation of BERS emphasizes the significance of metabolite features.

Global, regional and national trends in the epidemiology of rheumatoid arthritis from 1990 to 2021: an age-period-cohort effect analysis of the global burden of disease study 2021

BACKGROUND

Rheumatoid arthritis (RA) poses a significant global health challenge. This study examined trends in the incidence, prevalence and mortality of RA from 1990 to 2021 at global, regional and national levels, alongside age, period and cohort effects.

METHODS

Age-standardised rates (per 100 000 population) on RA incidence, prevalence and mortality were extracted from the Global Burden of Disease (GBD) study 2021. An age-period-cohort model estimated the overall annual percentage change (net drift), annual percentage change within each age group (local drift), and age/period/cohort relative risks.

RESULTS

Globally, from 1990 to 2021, the age-standardised incidence rate (ASIR) and the age-standardised prevalence rate (ASPR) of RA increased; while age-standardised mortality rate (ASMR) decreased. Low-middle sociodemographic index (SDI) region showed the most notable increases in incidence and prevalence, while high SDI region had the largest decline in RA mortality. The South-East Asia Region exhibited the most significant increases in incidence and prevalence, and the African Region had the greatest mortality decline. Ireland reported the highest ASIR and ASPR in 2021, while the Republic of Honduras had the highest ASMR. Age effects peaked at 65-69 years for incidence and 80-84 years for prevalence, with the mortality risk increased with age. Period effects indicated rising incidence and prevalence but declining mortality, while younger birth cohorts showed increasing risks of incidence and prevalence and decreasing mortality risk.

CONCLUSION

RA incidence and prevalence have risen globally, while mortality has declined. The regional, demographic and temporal variations underscore the need for targeted public health strategies to address the growing burden.

Application of metabolomics in the classification of traditional Chinese medicine syndromes in rheumatoid arthritis

OBJECTIVE

Rheumatoid arthritis (RA) is frequently treated with traditional Chinese medicine (TCM), where patients are classified into distinct syndromes, such as heat-dampness syndrome (HD) and kidney-liver deficiency syndrome (KLD). However, an objective and systematic approach to differentiate these TCM syndromes remains lacking. This study is aimed at analyzing serum metabolomics to identify differential metabolites and pathways associated with HD and GS syndromes in RA patients and at evaluating their potential as diagnostic biomarkers.

METHODS

Serum samples from RA patients classified into HD and KLD groups were analyzed using metabolomics. Partial least squares discriminant analysis was employed to identify significant metabolites, while pathway analysis was conducted using the Kyoto Encyclopedia of Genes and Genomes database. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic potential of key metabolites.

RESULTS

Fifteen differential metabolites and two perturbed pathways-sphingolipid and D-amino acid metabolism-were identified between the KLD and HD groups. Notably, several metabolites, including C17-sphinganine and leucyl-alanine, demonstrated high diagnostic efficacy, with area under the curve (AUC) values exceeding 0.90. Correlation analysis revealed significant associations between certain metabolites and clinical indices, further substantiating their role in syndrome differentiation.

CONCLUSION

This study presents a comprehensive analysis of serum metabolites in RA patients under different TCM syndromes. The identified metabolites hold potential as biomarkers for distinguishing HD and KLD groups, paving the way for more objective and evidence-based diagnostic approaches in TCM. Key Points • Differential metabolites were identified in the serum of RA patients with heat-dampness syndrome and kidney-liver deficiency syndrome, with their metabolic pathways primarily involving sphingolipid metabolism and D-amino acid metabolism. • Serum metabolites demonstrate high efficacy in distinguishing RA patients with different TCM syndromes. • Significant correlations were observed between serum differential metabolites and clinical indicators in RA patients with varying TCM syndromes.

Identification of Disulfidptosis-Related Genes and Molecular Subgroups in Rheumatoid Arthritis for Diagnostic Model and Patient Stratification

Introduction

Cell death contributes to the pathogenesis of rheumatoid arthritis (RA) through various pathways. Disulfidptosis is a recently discovered novel form of cell death characterized by the abnormal accumulation of intracellular disulfide bonds. It remains unclear for the association between RA and disulfidptosis.

Methods

A comprehensive analysis of three GEO datasets was presented in this study. First, the analysis involved the use of weighted gene co-expression network analysis (WGCNA) and differential analysis and were employed to identify the key module genes related to RA and disulfidptosis-related genes. The machine learning algorithms were used to identify the hub genes. Second, a diagnostic model was constructed for RA based on the hub genes. The nomogram and receiver operating characteristic (ROC) curves were utilized to evaluate the diagnostic value of the model. Third, two RA subtypes were identified based on hub genes by using consensus clustering analysis. Then, the disease activity scores, clinical markers, and immune cells were compared between the two RA subgroups. Finally, the differential expression of hub genes was validated between healthy controls and RA patients by qPCR.

Results

Four hub genes (KLHL2, POLK, CLEC4D, NXT2) were identified. The expression of the four hub genes was verified to be significantly higher in RA patients compared with healthy controls. The superior diagnostic value of the model was validated, which demonstrated that the model outperforms each hub gene individually. Two subtypes of RA were determined. Patients in cluster A exhibited relatively lower levels of DAS28-CRP, DAS28-ESR, CDAI, SDAI, RF, CRP, and MMP3. In contrast, patients in cluster B had significantly higher levels of the above markers.

Conclusion

Four hub genes were identified to provide unique insights into the role of disulfidptosis in RA. Additionally, a promising diagnosis model and patient stratification were established based on the hub genes to assess the risk of RA onset and RA disease activity.

Big data for neuroscience in the context of predictive, preventive, and personalized medicine

Accurate and precise diagnosis made the medicine the hallmark of evidence-based medicine. While attaining absolute patient satisfaction may seem impossible in the aspect of disease recurrent, personalized their mecidal conditions to their responsive treatment approach may save the day. The last generation approaches in medicine require advanced technologies that will lead to evidence-based medicine. One of the trending fields in this is the use of big data in predictive, preventive, and personalized medicine (3PM). This review dwelled through the practical examples in which big data tools harness neuroscience to add more individualized apporahes to the medical conditions in a bid to confer a more personalized treatment strategies. Moreover, the known breakthroughs of big data in 3PM, big data and 3PM in neuroscience, AI and neuroscience, limitations of big data with 3PM in neuroscience, and the challenges are thoroughly discussed. Finally, the prospects of incorporating big data in 3PM are as well discussed. The review could point out that the implications of big data in 3PM are still in their infancy and will require a holistic approach. While there is a need to carefully sensitize the community, convincing them will come under interdisciplinary and, to some extent, inter-professional collaborations, capacity building for professionals, and optimal coordination of the joint systems.

Distinct clinical outcomes based on multiple serum cytokine and chemokine profiles rather than autoantibody profiles and ultrasound findings in rheumatoid arthritis: a prospective ultrasound cohort study

OBJECTIVES

To evaluate the potential of clinical factors, ultrasound findings, serum autoantibodies, and serum cytokine and chemokine profiles as predictors of clinical outcomes in rheumatoid arthritis (RA).

PATIENTS AND METHODS

We included 200 patients with RA treated with biological and targeted synthetic disease-modifying antirheumatic drugs in a prospective multicentre ultrasound cohort study. Their serum levels of multiple cytokines and chemokines, rheumatoid factors, and serum autoantibodies (anti-cyclic citrullinated peptide-2 (anti-CCP2) and anti-carbamylated protein antibodies) were measured at baseline, 3 months and 12 months.

RESULTS

Dimensionality reduction using 38 cytokines and chemokines demonstrated four distinct clusters that differed significantly regarding the frequencies of remission defined by clinical composite measures and ultrasound evaluations. Prominent differences in IL-1β, IL-5, IL-7, IL-10, IFNγ, GRO, IP-10, MCP-1 and MIP-1β characterised the between-cluster differences. Two distinct groups made of four clusters showed a significant difference in IgM-anti-CCP2 positivity. The least absolute shrinkage and selection operator regression of 38 cytokines and chemokines for Clinical Disease Activity Index (CDAI) remission at 12 months resulted in the selection of MIP-1β. Logistic regression using baseline levels of anti-citrullinated protein antibody, IgM-anti-CCP2 positivity, the CDAI, the total power Doppler score, the cluster by cytokines and chemokines, MIP-1β, methotrexate dose and mechanisms of action revealed that cluster by cytokines and chemokines was the sole significant factor for CDAI remission at 12 months.

CONCLUSIONS

Specific patterns of cytokines and chemokines-no other clinical factors and autoantibody profiles-were important to distinguish patients with RA achieving remission at 12 months.

TRIAL REGISTRATION NUMBER

UMIN000012524.

Integrating pretest probability for rheumatoid arthritis with likelihood ratios of RF and ACPA to improve clinical utility of rheumatoid arthritis autoantibody testing

BACKGROUND AND AIMS

Rheumatoid arthritis (RA) manifests through various symptoms and systemic manifestations. Diagnosis involves serological markers like rheumatoid factor (RF) and anti-citrullinated protein antibodies (ACPA). Past studies have shown the added value of likelihood ratios (LRs) in result interpretation. LRs can be combined with pretest probability to estimate posttest probability for RA. There is a lack of information on pretest probability. This study aimed to estimate pretest probabilities for RA.

MATERIALS AND METHODS

This retrospective study included 133 consecutive RA patients and 651 consecutive disease controls presenting at a rheumatology outpatient clinic. Disease characteristics, risk factors associated with RA and laboratory parameters were documented for calculating pretest probabilities and LRs.

RESULTS

Joint involvement, erosions, morning stiffness, and positive CRP, ESR tests significantly correlated with RA. Based on these factors, probabilities for RA were estimated. Besides, LRs for RA were established for RF and ACPA and combinations thereof. LRs increased with antibody levels and were highest for double high positivity. Posttest probabilities were estimated based on pretest probability and LR.

CONCLUSION

By utilizing pretest probabilities for RA and LRs for RF and ACPA, posttest probabilities were estimated. Such approach enhances diagnostic accuracy, offering laboratory professionals and clinicians insights in the value of serological testing during the diagnostic process.

Management strategies in rheumatoid arthritis

Management of rheumatoid arthritis (RA) has evolved from simply the direct translation of drug efficacy results from clinical trials to patient care, to a more complex longitudinal process that considers not only drug efficacy but also the safety gestalt of a treatment and patient profiles and preferences, as well as health-economic factors. With numerous DMARDs available to treat RA, knowledge about trial efficacy becomes less important than data that inform an appropriate clinical strategy for their optimal selection and use. Overly ambitious approaches targeting the 'maximum' level of success could, for example, be prone to failure and create frustration, and lead to a large number of patients then being considered as 'difficult to treat'. Safety profiles might be more informative than efficacy profiles for precision medicine approaches. Contemporary RA management strategies might therefore take a more holistic approach, beyond merely efficacy, to the setting of targets that lead to improved compliance rather than aspirational successes, with consideration of each patient's multimorbidity profile and preferences, as well as the safety profile of each treatment. Ultimately, the goal remains unchanged: maximizing health-related quality of life; however, with a focus on optimal balance rather than superlatives.

Advances in mRNA vaccine research in the field of quality control

In recent years, innovative research and development of mRNA vaccines have made remarkable achievements, especially in the context of pandemic infectious diseases such as the COVID-19 virus, and the need for rapid vaccine development has further fueled the rapid growth of this field. Nevertheless, there are still gaps in our understanding of the working mechanism of mRNA vaccines and their long-term safety, efficacy, and quality control. This article summarizes the development background and production process of mRNA vaccines, outlines existing reference guidelines, quality control projects, and testing methods at home and abroad, and also summarizes the difficulties and future prospects in research and development and quality control. It provides a reference for developing guidelines for mRNA vaccine production, quality control, and preclinical and clinical evaluation.

Development of a Controllable Intelligent Drug Delivery System for Efficient Treatment of Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a complex inflammatory disease of the joints, which is often accompanied by degeneration of articular cartilage and bone erosion, seriously affecting the quality of life and psychological state of patients. RA is difficult to be cured completely, and currently the main purpose of relief is through the use of anti-inflammatory and antirheumatic drugs, hormones, and biological agents. Tofacitib is a new type of small molecule inhibitor, which has a good effect in the treatment of RA. The current direct drug delivery method has serious side effects caused by the systemic distribution of the drug, so there is a need to develop an intelligent drug delivery system to realize precise treatment. In this work, tofacitib, gallic acid, targeted molecule folic acid, and Fe(III) were selected to assemble a novel type of artificial controllable nanodrug GF-TF. The self-photoacoustic/magnetic resonance imaging (self-PA/MRI) monitored the enrichment of GF-TF in the lesion in real-time, and artificially regulated the addition of deferoxamine (DFO) at the optimal enrichment. DFO strongly chelates Fe(III) in GF-TF and causes its structure to disintegrate gradually, and the self-PA/MRI signal of GF-TF became weaker while tofacitib began to be released, thus realizing the precise and artificially controlled release of the drug under the guidance of imaging. This nanodrug not only achieves efficient aggregation of drugs in inflamed joints, but also achieves real-time monitoring and precise control of drug release through self-PA/MRI, providing a new strategy for the precise treatment of RA.

The prognostic value of IgA anti-citrullinated protein antibodies and rheumatoid factor in an early arthritis population with a treat-to-target approach

The mucosal origin hypothesis of rheumatoid arthritis has renewed the interest in IgA autoantibodies, but their added value over IgG anti-citrullinated protein antibody (ACPA) and IgM rheumatoid factor (RF) for modern treatment outcomes remains unknown. We aimed to investigate the prognostic value of IgA-ACPA and IgA-RF for treatment outcomes in an early arthritis population. IgA-ACPA/RF isotypes were measured in baseline sera from 480 inflammatory arthritis (IA) patients, who were included in the treatment in the Rotterdam Early Arthritis Cohort trial (tREACH). The tREACH trial was a multicentre, stratified, single-blinded trial with a treat-to-target approach. The prognostic value of IgA-ACPA/RF was determined by evaluating differences in (1) quick-attained (< 6 months after diagnosis) and persistent remission rates, (2) DMARD-free remission and (3) biological use between IA patients with and without IgA-ACPA/RF over 3 years of follow-up. IgA-ACPA was present in 23% of patients and overlapped with IgG-ACPA positivity in 94%. Similarly, IgA-RF overlapped with IgM-RF in 90% of patients. IgA-ACPA positivity was associated with lower DFR rates and more biological use, but this effect was largely mediated by the presence of IgG-ACPA, since this effect disappeared after stratification for IgG-ACPA (HR 0.6, 95%CI 0.2-1.6 for DFR). No differences were observed in 'quick-attained and persistent remission' rates and for IgA-RF. Their seems to be no additional value of IgA-ACPA and IgA-RF for modern, long-term clinical outcomes. The effects of IgA-ACPA seen in our study are largely mediated by the presence of IgG-ACPA. Based on these results, there is no rationale for measuring these isotypes in daily practice.

Qing-Luo-Yin Eased Adjuvant-Induced Arthritis by Inhibiting SIRT1-Controlled Visfatin Production in White Adipose Tissues

Background

Nicotinamide adenine dinucleotide (NAD)-dependent deacetylase SIRT1 regulates both metabolism and immune functions. This study investigated if SIRT1 inhibitory property of herbal formula Qing-Luo-Yin (QLY) contributed to its anti-rheumatic effects.

Methods

Adjuvant-induced arthritis (AIA) rats were treated by QLY and nicotinamide mononucleotide (NMN, a biosynthesis precursor of NAD) for 38 days. After sacrifice, blood, paws, liver and white adipose tissues (WAT) were collected. Pre-adipocytes were cultured by the rats' serum. The medium was used for monocytes culture. Some pre-adipocytes were treated by QLY-derived SIRT1 inhibitors. SIRT1 was silenced or overexpressed beforehand. The samples were subjected to kits-based quantification, polymerase-chain reaction, western-blot, immunofluorescence, and histology experiments.

Results

AIA rats experienced significant fat loss in liver and WAT. Expression of many SIRT1-related signals like PPARγ, PGC-1α, HSL, ATGL and CPT-1A were altered. QLY attenuated all these abnormalities and joint injuries. By pan-acetylation up-regulation, visfatin was obviously reduced in QLY-treated AIA rats' blood (from 191.8 to 127.0 pg/mL). NMN sustained SIRT1 activation by replenishing NAD, and weakened these effects. QLY-containing serum and the related compounds showed similar impacts on pre-adipocytes, resembling the changes in QLY-treated AIA rats' WAT. These treatments suppressed AIA serum-induced visfatin secretion (from 49.3 to 36.1 and 30.7 pg/mL). This effect was impaired by SIRT1 overexpression. The medium from the compounds-treated pre-adipocytes impaired NF-κB activation in AIA serum-cultured monocytes.

Conclusion

Besides fat depletion, SIRT1 up-regulation in rheumatic subjects' WAT promotes visfatin production, and exacerbates inflammation. SIRT1 inhibition in WAT is an anti-rheumatic way of QLY independent of immune regulation.

A radioactive and fluorescent dual modality cysteine cathepsin-B activity-based probe for the detection and treatment evaluation in rheumatoid arthritis

Activated macrophages are key effector cells and specific markers in patients with rheumatoid arthritis (RA). Cysteine cathepsin B (CTS-B) is highly expressed in macrophages and positively associated with RA activity and severity. This study aims to evaluate an activity-based multi-modality diagnostic agent, 68Ga-BMX2, which targets CTS-B to visualize the arthritis activity and evaluate the treatment efficacy. A CTS-B activity-based probe, BMX2, was labeled efficiently with 68Ga to produce 68Ga-BMX2 for fluorescent and positron emission tomography (PET) multi-modality imaging. The affinity and specificity of BMX2 binding with the CTS-B enzyme in macrophages were determined by radioactive experiment using RAW 264.7 cell lines, with CA074 and BMX5 as the inhibitors to test the specificity of the binding. Then, PET and fluorescence imaging were acquired on collagen-induced arthritis (CIA) mice. Additionally, the treatment monitoring capability of 68Ga-BMX2 PET/CT imaging was tested with methotrexate (MTX). RAW 264.7 macrophage cells showed significant uptake of 68Ga-BMX2. The binding of BMX2 with CTS-B in RAW 264.7 macrophage cells is time-dependent and could be blocked by CA074 and BMX5. In vivo optical and PET imaging showed high signals in the right hind arthritis in CIA mice from 68Ga-BMX2 and BMX2 accumulated for at least 120 h. Additionally, 68Ga-BMX2 signals were significantly reduced in the MTX-treated CIA mice compared to the control group. The 68Ga-BMX2, a radioactive and fluorescent dual-modality diagnostic agent targeting CTS-B, demonstrated a practical approach for CIA PET and fluorescence imaging. The 68Ga-BMX2 multimodality imaging could significantly monitor the treatment response in the CIA mice.

Chondroitin sulfate-modified tragacanth gum-gelatin composite nanocapsules loaded with curcumin nanocrystals for the treatment of arthritis

Rheumatoid arthritis (RA) is a chronic autoimmune disease of yet undetermined etiology that is accompanied by significant oxidative stress, inflammatory responses,  and damage to joint tissues. In this study, we designed chondroitin sulfate (CS)-modified tragacanth gum-gelatin composite nanocapsules (CS-Cur-TGNCs) loaded with curcumin nanocrystals (Cur-NCs), which rely on the ability of CS to target CD44 to accumulate drugs in inflamed joints. Cur was encapsulated in the form of nanocrystals into tragacanth gum-gelatin composite nanocapsules (TGNCs) by using an inborn microcrystallization method, which produced CS-Cur-TGNCs with a particle size of approximately 80 ± 11.54 nm and a drug loading capacity of 54.18 ± 5.17%. In an in vitro drug release assay, CS-Cur-TGNCs showed MMP-2-responsive properties. During the treatment of RA, CS-Cur-TGNCs significantly inhibited oxidative stress, promoted the polarization of M2-type macrophages to M1-type macrophages, and decreased the expression of inflammatory factors (TNF-α, IL-1β, and IL-6). In addition, it also exerted excellent anti-inflammatory effects, and significantly alleviated the swelling of joints during the treatment of gouty arthritis (GA). Therefore, CS-Cur-TGNCs, as a novel drug delivery system, could lead to new ideas for clinical therapeutic regimens for RA and GA.

Individual and population-level variability in HLA-DR associated immunogenicity risk of biologics used for the treatment of rheumatoid arthritis

Hypothesis

While conventional in silico immunogenicity risk assessments focus on measuring immunogenicity based on the potential of therapeutic proteins to be processed and presented by a global population-wide set of human leukocyte antigen (HLA) alleles to T cells, future refinements might adjust for HLA allele frequencies in different geographic regions or populations, as well for as individuals in those populations. Adjustment by HLA allele distribution may reveal risk patterns that are specific to population groups or individuals, which current methods that rely on global-population HLA prevalence may obscure.

Key findings

This analysis uses HLA frequency-weighted binding predictions to define immunogenicity risk for global and sub-global populations. A comparison of assessments tuned for North American/European versus Japanese/Asian populations suggests that the potential for anti-therapeutic responses (anti-therapeutic antibodies or ATA) for several commonly prescribed Rheumatoid Arthritis (RA) therapeutic biologics may differ, significantly, between the Caucasian and Japanese populations. This appears to align with reports of differing product-related immunogenicity that is observed in different populations.

Relevance to clinical practice

Further definition of population-level (regional) and individual patient-specific immunogenic risk profiles may enable prescription of the RA therapeutic with the highest probability of success to each patient, depending on their population of origin and/or their individual HLA background. Furthermore, HLA-specific immunogenicity outcomes data are limited, thus there is a need to expand HLA-association studies that examine the relationship between HLA haplotype and ATA in the clinic.

Clinical Phenotypes, Serological Biomarkers, and Synovial Features Defining Seropositive and Seronegative Rheumatoid Arthritis: A Literature Review

Rheumatoid arthritis (RA) is a chronic autoimmune disorder which can lead to long-term joint damage and significantly reduced quality of life if not promptly diagnosed and adequately treated. Despite significant advances in treatment, about 40% of patients with RA do not respond to individual pharmacological agents and up to 20% do not respond to any of the available medications. To address this large unmet clinical need, several recent studies have focussed on an in-depth histological and molecular characterisation of the synovial tissue to drive the application of precision medicine to RA. Currently, RA patients are clinically divided into "seropositive" or "seronegative" RA, depending on the presence of routinely checked antibodies. Recent work has suggested that over the last two decades, long-term outcomes have improved significantly in seropositive RA but not in seronegative RA. Here, we present up-to-date differences in epidemiology, clinical features, and serological biomarkers in seronegative versus seropositive RA and discuss how histological and molecular synovial signatures, revealed by recent large synovial biopsy-based clinical trials, may be exploited to refine the classification of RA patients, especially in the seronegative group.

Obesity is a risk factor for poor response to treatment in early rheumatoid arthritis: a NORD-STAR study

OBJECTIVE

This report from the NORD-STAR (Nordic Rheumatic Diseases Strategy Trials and Registries) trial aimed to determine if obesity is associated with response to conventional and biological antirheumatic treatment in early rheumatoid arthritis (RA).

METHODS

This report included 793 participants with untreated early RA from the randomised, longitudinal NORD-STAR trial, all of whom had their body mass index (BMI) assessed at baseline. Obesity was defined as BMI ≥30 kg/m2. All participants were randomised 1:1:1:1 to one of four treatment arms: active conventional treatment, certolizumab-pegol, abatacept and tocilizumab. Clinical and laboratory measurements were performed at baseline and at 8, 12, 24 and 48-week follow-up. The primary endpoint for this report was response to treatment based on Clinical Disease Activity Index (CDAI) and Simple Disease Activity Index (SDAI) remission and Disease Activity Score with 28 joints using C-reactive protein (DAS28-CRP) <2.6 stratified by BMI.

RESULTS

Out of 793 people included in the present report, 161 (20%) had obesity at baseline. During follow-up, participants with baseline obesity had higher disease activity compared with those with lower BMI, despite having similar disease activity at baseline. In survival analyses, obesity was associated with a lower likelihood of achieving response to treatment during follow-up for up to 48 weeks (CDAI remission, HR 0.84, 95% CI 0.67 to 1.05; SDAI, HR 0.77, 95% CI 0.62 to 0.97; DAS28-CRP <2.6, HR 0.78, 95% CI 0.64 to 0.95). The effect of obesity on response to treatment was not influenced by the treatment arms.

CONCLUSION

In people with untreated early RA followed up for up to 48 weeks, obesity was associated with a lower likelihood of good treatment response, irrespective of the type of randomised treatment received.

TRIAL REGISTRATION NUMBER

NCT01491815.

Impact of age and cardiovascular risk factors on the incidence of adverse events in patients with rheumatoid arthritis treated with Janus Kinase inhibitors: data from a real-life multicentric cohort

Inhibiting Janus Kinases (JAK) is a crucial therapeutic strategy in rheumatoid arthritis (RA). However, the use of JAK inhibitors has recently raised serious safety concerns. The study aims to evaluate the safety profile of JAKi in patients with RA and identify potential risk factors (RFs) for adverse events (AEs). Data of RA patients treated with JAKi in three Italian centers from January 2017 to December 2022 were retrospectively analyzed. 182 subjects (F:117, 64.3%) underwent 193 treatment courses. 78.6% had at least one RF, including age ≥ 65 years, obesity, smoking habit, hypertension, dyslipidemia, hyperuricemia, diabetes, previous VTE or cancer, and severe mobility impairment. We identified 70 AEs (28/100 patients/year), among which 15 were serious (6/100 patients/year). A high disease activity was associated with AEs occurrence (p = 0.03 for CDAI at T0 and T6; p = 0.04 for SDAI at T0 and T6; p = 0.01 and p = 0.04 for DAS28ESR at T6 and T12, respectively). No significant differences in AEs occurrence were observed after stratification by JAKi molecules (p = 0.44), age groups (p = 0.08) nor presence of RFs (p > 0.05 for all of them). Neither the presence of any RFs, nor the cumulative number of RFs shown by the patient, nor age ≥ 65 did predict AEs occurrence. Although limited by the small sample size and the limited number of cardiovascular events, our data do not support the correlation between cardiovascular RFs-including age-and a higher incidence of AEs during JAKi therapy. The role of uncontrolled disease activity in AEs occurrence should by emphasized.

Deconvolution of synovial myeloid cell subsets across pathotypes and role of COL3A1+ macrophages in rheumatoid arthritis remission

Background

Monocyte/macrophage (Mo/Mp) is a critical cell population involved in immune modulation of rheumatoid synovitis (RA) across different pathotypes. This study aims to investigate the contribution of Mo/Mp clusters to RA activity, and the biological function of particular subtypes in RA remission.

Methods

We integrated single-cell RNA sequencing datasets from 4 published and 1 in-house studies using Liger selected by comparison. We estimated the abundance of Mo/Mp subtypes in bulk RNA-seq data from the 81 patients of the Pathobiology of Early Arthritis Cohort (PEAC) using deconvolution analysis. Correlations between Mo/Mp subtypes and RA clinical metrics were assessed. A particular cell type was identified using multicolor immunofluorescence and flow cytometry in vivo and successfully induced from a cell line in vitro. Potential immune modulation function of it was performed using immunohistochemical staining, adhesion assay, and RT-qPCR.

Results

We identified 8 Mo/Mp clusters. As a particular subtype among them, COL3A1+ Mp (CD68+, COL3A1+, ACTA2-) enriched in myeloid pathotype and negatively correlated with RA severity metrics in all pathotypes. Flow cytometry and multicolor immunofluorescence evidenced the enrichment and M2-like phenotype of COL3A1+ Mp in the myeloid pathotype. Further assays suggested that COL3A1+ Mp potentially attenuates RA severity via expressing anti-inflammatory cytokines, enhancing Mp adhesion, and forming a physical barrier at the synovial lining.

Conclusion

This study reported unexplored associations between different pathologies and myeloid cell subtypes. We also identified a fibroblast-and-M2-like cluster named COL3A1+ Mp, which potentially contributes to synovial immune homeostasis. Targeting the development of COL3A1+ Mp may hold promise for inducing RA remission.

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.

Treatment patterns of individualized real-life tapering approaches based on shared decision-making in rheumatoid arthritis

OBJECTIVE

To provide real-world evidence on patient-individual tapering patterns of disease-modifying antirheumatic drugs (DMARDs) in rheumatoid arthritis (RA) patients in daily clinical practice.

METHODS

Data obtained through a controlled prospective cohort study in Germany conducted from July 2018 to March 2021 were analyzed. Participants consist of RA patients in sustained remission who were eligible for DMARD tapering at enrolment. Data from RA patients who experienced tapering of DMARDs at least once during the observational period (n = 200) were used. Descriptive analyses of medical outcomes at baseline and at time of first tapering, time to first tapering, tapering patterns by substance group, and tapering intensity were documented.

RESULTS

We did not observe meaningful differences in either disease activity or quality of life measures between substance groups at enrolment, time of first tapering, and at 6 or 12 months after tapering. Median time until first tapering varied between substance groups (csDMARDs: 108 days; bDMARDs: 189 days; combination: 119 days). Most patients received one iteration of tapering only (147/200 patients, 73.5%). Dose reduction was applied for patients treated with csDMARDs (79/86 patients, 91.8%), spacing of interval was the most frequent strategy for patients treated with bDMARDs only (43/48 patients, 89.5%). Necessity for increased DMARD dosage was observed in only 10% of patients (20/200). Tapering intensity by substance was overall heterogenous, indicating high individualization.

CONCLUSION

We identify highly heterogeneous tapering patterns between substance groups and within substances. Identification and recognition of patient-individual approaches of tapering will help to further improve the management of RA for both patients and rheumatologists.

Prediction of ineffectiveness of biological drugs using machine learning and explainable AI methods: data from the Austrian Biological Registry BioReg

OBJECTIVES

Machine learning models can support an individualized approach in the choice of bDMARDs. We developed prediction models for 5 different bDMARDs using machine learning methods based on patient data derived from the Austrian Biologics Registry (BioReg).

METHODS

Data from 1397 patients and 19 variables with at least 100 treat-to-target (t2t) courses per drug were derived from the BioReg biologics registry. Different machine learning algorithms were trained to predict the risk of ineffectiveness for each bDMARD within the first 26 weeks. Cross-validation and hyperparameter optimization were applied to generate the best models. Model quality was assessed by area under the receiver operating characteristic (AUROC). Using explainable AI (XAI), risk-reducing and risk-increasing factors were extracted.

RESULTS

The best models per drug achieved an AUROC score of the following: abatacept, 0.66 (95% CI, 0.54-0.78); adalimumab, 0.70 (95% CI, 0.68-0.74); certolizumab, 0.84 (95% CI, 0.79-0.89); etanercept, 0.68 (95% CI, 0.55-0.87); tocilizumab, 0.72 (95% CI, 0.69-0.77). The most risk-increasing variables were visual analytic scores (VAS) for abatacept and etanercept and co-therapy with glucocorticoids for adalimumab. Dosage was the most important variable for certolizumab and associated with a lower risk of non-response. Some variables, such as gender and rheumatoid factor (RF), showed opposite impacts depending on the bDMARD.

CONCLUSION

Ineffectiveness of biological drugs could be predicted with promising accuracy. Interestingly, individual parameters were found to be associated with drug responses in different directions, indicating highly complex interactions. Machine learning can be of help in the decision-process by disentangling these relations.

Effectiveness of bDMARDs in ankylosing spondylitis patients by biologic use: experience from the CorEvitas PsA/SpA Registry

OBJECTIVE

To describe bDMARD initiators by biologic experience among ankylosing spondylitis (AS) patients and change in disease activity and patient-reported outcomes (PROs) in real-world US patients.

METHODS

We included patients ≥18 years with AS based on physician diagnosis enrolled between 3/2013 and 11/2019 in the CorEvitas Psoriatic Arthritis (PSA)/Spondyloarthritis Registry (NCT02530268). Patients concurrently diagnosed with PSA were excluded. Baseline (bDMARD initiation) demographics, comorbidities, disease characteristics, treatment, and PROs were collected. Response rates and changes in disease activity and PROs between baseline and 6- and 12- month follow-up visits were calculated.

RESULTS

Of the 489 AS patients in the PsA/SpA Registry, 254 AS (52.0%) patients initiated a bDMARD at enrollment or during follow-up (total initiations: AS = 313). Of the 313 AS initiations, 179 (57.2%) had a 6-month follow-up, 122 (39.0%) had a 12-month follow-up, and 94 (30.0%) had a 6- and 12-month follow-up visit. For those AS initiators with a 6-month follow-up, the mean age was 49.1 years, 44.4% were female, and 70.4%, 47.5%, 96.1%, and 46.9% had never used cDMARDs, TNFis, non-TNFis, and bDMARDs, respectively. Of these 179 AS initiators, 20.1% and 14.0% achieved ASAS20/40, respectively. Further, only 34% achieved low disease activity (ASDAS <2.1). When stratified by biologic-naivete and biologic-experience, the ASAS 20/40 achievement rates were 26.2% and 14.7%, and 21.4% and 7.4%, respectively, for this cohort.

CONCLUSION

Although AS patients initiate bDMARDs, many do not achieve optimal treatment responses. Future research is needed to investigate the aspects associated with inadequate improvement and treatment response to bDMARDs.

Long COVID or Post-COVID-19 Condition: Past, Present and Future Research Directions

The presence of symptoms after an acute SARS-CoV-2 infection (long-COVID) has become a worldwide healthcare emergency but remains underestimated and undertreated due to a lack of recognition of the condition and knowledge of the underlying mechanisms. In fact, the prevalence of post-COVID symptoms ranges from 50% during the first months after the infection up to 20% two-years after. This perspective review aimed to map the existing literature on post-COVID symptoms and to identify gaps in the literature to guide the global effort toward an improved understanding of long-COVID and suggest future research directions. There is a plethora of symptomatology that can be due to COVID-19; however, today, there is no clear classification and definition of this condition, termed long-COVID or post-COVID-19 condition. The heterogeneity in the symptomatology has led to the presence of groups/clusters of patients, which could exhibit different risk factors and different mechanisms. Viral persistence, long-lasting inflammation, immune dysregulation, autoimmune reactions, reactivation of latent infections, endothelial dysfunction and alteration in gut microbiota have been proposed as potential mechanisms explaining the complexity of long-COVID. In such an equation, viral biology (e.g., re-infections, SARS-CoV-2 variants), host biology (e.g., genetics, epigenetics) and external factors (e.g., vaccination) should be also considered. These various factors will be discussed in the current perspective review and future directions suggested.

Efficacy and safety of iguratimod in the treatment of rheumatic and autoimmune diseases: a meta-analysis and systematic review of 84 randomized controlled trials

Objective: To evaluate efficacy and safety of iguratimod (IGU) in the treatment of rheumatic and autoimmune diseases. Methods: Databases such as Pubmed, Embase, Sinomed were searched (as of July 2022) to collect randomized controlled trials (RCTs) of IGU in the treatment of rheumatic and autoimmune diseases. Two researchers independently screened the literature, extracted data, assessed the risk of bias of the included literature, and performed meta-analysis using RevMan 5.4 software. Results: A total of 84 RCTs and 4 types of rheumatic and autoimmune diseases [rheumatoid arthritis (RA), ankylosing spondylitis (AS), primary Sjögren's syndrome (PSS) and Autoimmune disease with interstitial pneumonia]. Forty-three RCTs reported RA and showed that IGU + MTX therapy can improve ACR20 (RR 1.45 [1.14, 1.84], p = 0.003), ACR50 (RR 1.80 [1.43, 2.26], p < 0.0000), ACR70 (RR 1.84 [1.27, 2.67], p = 0.001), DAS28 (WMD -1.11 [-1.69, -0.52], p = 0.0002), reduce ESR (WMD -11.05 [-14.58, -7.51], p < 0.00001), CRP (SMD -1.52 [-2.02, -1.02], p < 0.00001), RF (SMD -1.65 [-2.48, -0.82], p < 0.0001), and have a lower incidence of adverse events (RR 0.84 [0.78, 0.91], p < 0.00001) than the control group. Nine RCTs reported AS and showed that IGU can decrease the BASDAI score (SMD -1.62 [-2.20, -1.05], p < 0.00001), BASFI score (WMD -1.07 [-1.39, -0.75], p < 0.00001), VAS (WMD -2.01 [-2.83, -1.19], p < 0.00001), inflammation levels (decreasing ESR, CRP and TNF-α). Thirty-two RCTs reported PSS and showed that IGU can reduce the ESSPRI score (IGU + other therapy group: WMD -1.71 [-2.44, -0.98], p < 0.00001; IGU only group: WMD -2.10 [-2.40, -1.81], p < 0.00001) and ESSDAI score (IGU + other therapy group: WMD -1.62 [-2.30, -0.94], p < 0.00001; IGU only group: WMD -1.51 [-1.65, -1.37], p < 0.00001), inhibit the inflammation factors (reduce ESR, CRP and RF) and increase Schirmer's test score (IGU + other therapy group: WMD 2.18 [1.76, 2.59], p < 0.00001; IGU only group: WMD 1.55 [0.35, 2.75], p = 0.01); The incidence of adverse events in IGU group was also lower than that in control group (IGU only group: RR 0.66 [0.48, 0.98], p = 0.01). Three RCTs reported Autoimmune disease with interstitial pneumonia and showed that IGU may improve lung function. Conclusion: Based on current evidence, IGU may be a safe and effective therapy for RA, AS, PSS and autoimmune diseases with interstitial pneumonia. Systematic Review Registration: (CRD42021289489).

Fecal microbiota transplantation for the management of autoimmune diseases: Potential mechanisms and challenges

Autoimmune diseases (AIDs) are a series of immune-mediated lethal diseases featured by over-activated immune cells attacking healthy self-tissues and organs due to the loss of immune tolerance, which always causes severe irreversible systematical organ damage and threatens human health heavily. To date, there are still no definitive cures for the treatment of AIDs due to their pathogenesis has not been clearly understood. Besides, the current clinical treatments of AIDs majorly rely on glucocorticoids and immune suppressors, which can lead to serious side effects. In the past years, there are increasing studies demonstrating that an imbalance of gut microbiota is intimately related to the pathogenesis of various AIDs, shedding light on the development of therapeutics by targeting the gut microbiota for the management of AIDs. Among all the approaches targeting the gut microbiota, fecal microbiota transplantation (FMT) has attracted increasing interest, and it has been proposed as a possible strategy to intervene in the homeostasis of gut microbiota for the treatment of various diseases. However, despite the reported good curative effects and clinical studies conducted on FMT, the detailed mechanisms of FMT for the effective treatment of those diseases have not been figured out. To fully understand the mechanisms of the therapeutic effects of FMT on AIDs and improve the therapeutic efficacy of FMT treatment, a systematic review of this topic is necessary. Hence, in this review paper, the potential mechanisms of FMT for the treatment of various AIDs were summarized, including promotion, shaping, activation, or inhibition of the host immune system via the interactions between the microorganisms and the gut immune system, gut-brain, gut-liver, gut-kidney axis, and so on. Then, applications of FMT for the treatment of various AIDs were detailed presented. Finally, the current challenges and potential solutions for the development of FMT formulations and FMT therapeutics were comprehensively discussed.

Identification and Development of Synovial B-Cell-Related Genes Diagnostic Signature for Rheumatoid Arthritis

Background

The aim of the study was to investigate the landscape of B-cell-related gene expression profiling in rheumatoid arthritis (RA) synovium and explore the biological and clinical significance of these genes in RA.

Methods

Expression profiling of synovial biopsies from subjects with 152 RA patients, 22 osteoarthritis (OA) patients, and 28 healthy controls was downloaded from the Gene Expression Omnibus database. Single-sample gene set enrichment analysis (ssGSEA) was performed to evaluate the abundance of infiltrated immune cells, and the results were validated using immunohistochemical staining. GSEA was employed to decipher differences in B-cell-related biological pathways. B-cell-related differential expression genes (BRDEGs) were screened, and BRDEGs-based model was developed by machine learning algorithms and evaluated by an external validation set and clinical RA cohort, then biological functions were further analyzed.

Results

High levels of immune cell infiltration and B-cell-related pathway activation were revealed in RA synovium. BRDEGs were screened, and three key molecular markers consisting of FAS, GPR183, and TFRC were identified. The diagnosis model was established, and these gene markers have good discriminative ability for RA. Molecular pathological evaluation confirmed RA patients with high-risk scores presented higher levels of B-cell activation and RA characteristics. In addition, a competitive endogenous RNA network was established to elucidate the molecular mechanisms of the posttranscriptional network.

Conclusions

We described the B-cell-related molecular landscape of RA synovium and constructed a molecular diagnostic model in RA. The three genes FAS, GPR183, and TFRC may be potential targets for clinical diagnosis and immunoregulatory therapy of RA.

Precision management of post-COVID pain: An evidence and clinical-based approach

Background Pain after a SARS-CoV-2 acute infection (post-COVID pain) is becoming a new healthcare emergency but remains underestimated and most likely undertreated due to a lack of recognition of the phenomenon and knowledge of the underlying pain mechanisms. Evidence supporting any particular treatment approach for the management of post-COVID pain is lacking. Large variability in the patient response to any standard pain treatments is clinically observed, which has led to calls for a personalized, tailored approach to treating patients with chronic post-COVID pain (i.e. 'precision pain medicine'). Applying the global concerted action towards precision medicine to post-COVID pain could help guide clinical decision-making and aid in more effective treatments. Methods The current position paper discusses factors to be considered by clinicians for managing post-COVID pain ranging from identification of the pain phenotype to genetic consideration. Results The ability of clinicians to phenotype post-COVID pain into nociceptive, neuropathic, nociplastic or mixed type is suggested as the first step to better planification of a treatment programme. Further, the consideration of other factors, such as gender, comorbidities, treatments received at the acute phase of infection for onset-associated COVID-19 symptoms, factors during hospitalization or the presence of emotional disturbances should be implemented into a treatment programme. Conclusions Accordingly, considering these factors, management of post-COVID pain should include multimodal pharmacological and non-pharmacological modalities targeting emotional/cognitive aspects (i.e. psychological and/or coping strategies), central sensitization-associated mechanisms (i.e. pain neuroscience education), exercise programmes as well as lifestyle interventions (e.g. nutritional support and sleep management). SIGNIFICANCE: This position paper presents an evidence-based clinical reasoning approach for precision management of post-COVID pain.

Crocus sativus L. Extract (Saffron) Effectively Reduces Arthritic and Inflammatory Parameters in Monotherapy and in Combination with Methotrexate in Adjuvant Arthritis

Rheumatoid arthritis (RA), an autoimmune disease, is characterized by inflammation that affects not only the liver but also other organs and the musculoskeletal system. The standard therapy for RA is methotrexate (MTX), which has safety limitations. The extract from Crocus sativus L. (saffron-SF) is also known for its anti-inflammatory effects. Therefore, we decided to investigate the potential benefit of SF in monotherapy via two doses (SF1-25 mg/kg of b.w.; SF2-50 mg/kg of b.w.) and in combination with MTX (0.3 mg/kg of b.w., twice a week) using adjuvant arthritis in rats. To evaluate these therapeutic settings, we used biometric, immunological, and biochemical parameters, as well as the relative gene expression of the mRNA in the liver. Our results showed a statistically significant increase in the experimental animals' body weight and the arthritic score (AS) on day 14 for monotherapy with SF1 and SF2. The change of hind paw volume (CHPV) was significant only for SF2 monotherapy on the 14th day of the experiment. A combination of SF1 and SF2 with MTX significantly modulated all the biometric parameters during the experimental period. Additionally, AS and CHPV improved considerably compared to MTX monotherapy on day 21. Furthermore, all monotherapies and combination therapies were significant for the biochemical parameter γ-glutamyl transferase (GGT) in the joint. GGT activity in the spleen was less pronounced; only MTX in combination with SF1 significantly modified this parameter. The higher dose of SF monotherapy (SF2) was similarly significant with respect to immunological parameters, such as plasmatic IL-17A, IL-1β, and MMP-9 on day 21. The combination of both doses of SF with MTX significantly improved these immunological parameters, except for C-reactive protein (CRP), which was influenced only by the higher dose of SF2 in combination with MTX in plasma at the end of the experiment. A different effect was found for the relative expression of CD36 mRNA, where only SF1 significantly decreased gene expression in the liver. However, the relative gene mRNA expression of IL-1β in the liver was significantly reduced by the SF monotherapies and the combination of both SF doses with MTX. Our findings showed SF's partial antiarthritic and anti-inflammatory potential in monotherapy, but the effect was stronger in combination with MTX.

Efficacy and safety of total glucosides of paeony in the treatment of 5 types of inflammatory arthritis: A systematic review and meta-analysis

OBJECTIVE

To evaluate efficacy and safety of total glucosides of paeony in the treatment of 5 types of inflammatory arthritis METHODS: Databases such as Pubmed, Cochran Library, Embase were searched to collect RCTs about TGP in the treatment of inflammatory arthritis. Then, the RCTs were assessed for risk of bias and RCT data were extracted. Finally, RevMan 5.4 was used for the meta-analysis.

RESULTS

A total of 63 RCTs were finally included, involving 5293 participants and 5 types of types of inflammatory arthritis: rheumatoid arthritis (RA), ankylosing spondylitis (AS), osteoarthritis (OA), juvenile idiopathic arthritis (JIA), psoriatic arthritis. For AS, TGP may improve AS disease activity score (ASDAS), decrease erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), tumor necrosis factor (TNF)- α and interleukin (IL)- 6; for RA, TGP may improve disease activity of 28 joints (DAS28), decrease ESR, CRP, rheumatoid factor (RF), TNF-α and IL-6; for psoriatic arthritis, TGP may improve psoriasis area and severity index (PASI) and decrease ESR; for OA, TGP may improve visual analogue scale (VAS) and decrease nitric oxide (NO); for JIA, TGP may increase total efficiency rate, decrease ESR, CRP and TNF-α. For safety, RCTs showed that the addition of TGP did not increase adverse events, and may even reduce adverse events.

CONCLUSION

TGP may improve symptoms and inflammation levels in patients with inflammatory arthritis. However, due to the low quality and small number of RCTs, large-sample, multi-center clinical trials are still needed for revision or validation.

Precision Medicine: Disease Subtyping and Tailored Treatment

The genomics-based concept of precision medicine began to emerge following the completion of the Human Genome Project. In contrast to evidence-based medicine, precision medicine will allow doctors and scientists to tailor the treatment of different subpopulations of patients who differ in their susceptibility to specific diseases or responsiveness to specific therapies. The current precision medicine model was proposed to precisely classify patients into subgroups sharing a common biological basis of diseases for more effective tailored treatment to achieve improved outcomes. Precision medicine has become a term that symbolizes the new age of medicine. In this review, we examine the history, development, and future perspective of precision medicine. We also discuss the concepts, principles, tools, and applications of precision medicine and related fields. In our view, for precision medicine to work, two essential objectives need to be achieved. First, diseases need to be classified into various subtypes. Second, targeted therapies must be available for each specific disease subtype. Therefore, we focused this review on the progress in meeting these two objectives.

Verification of cuproptosis-related diagnostic model associated with immune infiltration in rheumatoid arthritis

Background

Rheumatoid arthritis (RA) is a chronic autoimmune disease closely related to inflammation. Cuproptosis is a newly discovered unique type of cell death, and it has been found that it may play an essential role in the occurrence and development of RA. Therefore, we intend to explore the potential association between cuproptosis-related genes (CRGs) and RA to provide a new biomarker for the treatment and prognosis of RA.

Methods

Download GSE93777 datasets from the GEO database. Variance analysis was performed on the CRGs that had been reported. Then, the random forest (RF) model and nomogram of differentially expressed CRGs were constructed, and the ROC curve was used to evaluate the accuracy of the diagnostic model. Next, RA patients were subtyped by consensus clustering, and immune infiltration was analyzed in each subgroup to confirm the correlation between CRGs and abundance of immune cells. The expression levels of CRGs were verified by qRT-PCR.

Results

Eight differentially expressed CRGs (DLST, DLD, PDHB, PDHA1, ATP7A, CDKN2A, LIAS, DLAT) were screened out by differential analysis to construct an RF model. The ROC curve proved that this model had good diagnostic accuracy. Based on the above eight significant CRGs, a nomogram was built to predict effective and high-precision results. The consensus clustering method identified two CRG patterns. Most of the immune cells were enriched in cluster A, indicating that cluster A may be related to the development of RA. Finally, qRT-PCR verified the expression of eight key genes, further confirming our findings.

Conclusion

The diagnosis model of RA based on the above eight CRGs has excellent diagnostic potential. Based on these, patients can be divided into two different molecular subtypes; it is expected to develop a new treatment strategy for RA.

Physical function and severe side effects matter most to patients with RA (< 5 years): a discrete choice experiment assessing preferences for personalized RA treatment

AIM

Early assessment of patient preferences has the potential to support shared decisions in personalized precision medicine for patients with rheumatoid arthritis (RA). The aim of this study was to assess treatment preferences of patients with RA (< 5 years) with previous experience of inadequate response to first-line monotherapy.

METHOD

Patients were recruited (March-June 2021) via four clinics in Sweden. Potential respondents (N = 933) received an invitation to answer a digital survey. The survey included an introductory part, a discrete choice experiment (DCE) and demographic questions. Each respondent answered 11 hypothetical choice questions as part of the DCE. Patient preferences and preference heterogeneity were estimated using random parameter logit models and latent class analysis models.

RESULTS

Patients (n = 182) assessed the most important treatment attributes out of physical functional capacity, psychosocial functional capacity, frequency of mild side effects and likelihood of severe side effects. In general, patients preferred a greater increase in functional capacity and decreased side effects. However, a substantial preference heterogeneity was identified with two underlying preference patterns. The most important attribute in the first pattern was the 'likelihood of getting a severe side effect'. Physical functional capacity was the most important attribute in the second pattern.

CONCLUSION

Respondents focused their decision-making mainly on increasing their physical functional capacity or decreasing the likelihood of getting a severe side effect. These results are highly relevant from a clinical perspective to strengthen communication in shared decision making by assessing patients' individual preferences for benefits and risks in treatment discussions.

Photoacoustic/ultrasound-guided gene silencing: Multifunctional microbubbles for treating adjuvant-induced arthritis

AIMS

To effectively deliver small interfering RNA (siRNA) to inflammatory tissues for treating rheumatoid arthritis (RA), we developed the multifunctional microbubbles (MBs) to perform photoacoustic/ultrasound-guided gene silencing.

METHODS

Fluorescein amidite (FAM)-labelled tumour necrosis factor-α (TNF-α)-siRNA and cationic MBs were mixed to fabricate FAM-TNF-α-siRNA-cMBs. The cell transfection efficacy of FAM-TNF-α-siRNA-cMBs was evaluated in vitro on RAW264.7 cells. Subsequently, wistar rats with adjuvant-induced arthritis (AIA) were injected intravenously with MBs and simultaneously subjected to low-frequency ultrasound for ultrasound-targeted microbubble destruction (UTMD). Photoacoustic imaging (PAI) was utilized to visualize the distribution of siRNA. And the clinical and pathological changes of AIA rats was estimated.

RESULTS

FAM-TNF-α-siRNA-cMBs were evenly distributed within the RAW264.7 cells and significantly reduced TNF-α mRNA levels of the cells. For AIA rats, the entering and collapsing of MBs was visualized by contrast-enhanced ultrasound (CEUS). Photoacoustic imaging showed markedly enhanced signals following injection, indicating localization of the FAM-labelled siRNA. The articular tissues of the AIA rats treated with TNF-α-siRNA-cMBs and UTMD showed decreased TNF-α expression levels.

CONCLUSIONS

The theranostic MBs exhibited a TNF-α gene silencing effect under the guidance of CEUS and PAI. The theranostic MBs served as vehicles for delivering siRNA as well as contrast agents for CEUS and PAI.

Chemically engineering cells for precision medicine

Cell-based therapy holds great potential to address unmet medical needs and revolutionize the healthcare industry, as demonstrated by several therapeutics such as CAR-T cell therapy and stem cell transplantation that have achieved great success clinically. Nevertheless, natural cells are often restricted by their unsatisfactory in vivo trafficking and lack of therapeutic payloads. Chemical engineering offers a cost-effective, easy-to-implement engineering tool that allows for strengthening the inherent favorable features of cells and confers them new functionalities. Moreover, in accordance with the trend of precision medicine, leveraging chemical engineering tools to tailor cells to accommodate patients individual needs has become important for the development of cell-based treatment modalities. This review presents a comprehensive summary of the currently available chemically engineered tools, introduces their application in advanced diagnosis and precision therapy, and discusses the current challenges and future opportunities.

Effect of vitamin E supplementation in rheumatoid arthritis: a systematic review and meta-analysis

OBJECTIVE

The purpose of this study was to evaluate the safety and effectiveness of vitamin E in rheumatoid arthritis patients.

METHODS

A computerized search of PubMed, Embase, The Cochrane Library, and Web of Science databases was conducted to find published randomized controlled trials of vitamin E in rheumatoid arthritis; the experimental group was treated with vitamin E, while the control group was treated with placebo, other drugs, or external therapy; the search period was from the time each database was established to December 31, 2021, and a meta-analysis was conducted using Rev Man 5.4 software.

RESULTS

This research eventually comprised nine publications with a total of 39,845 patients. Vitamin E supplementation was shown to be more effective in individuals with RA for sensitive joints (MD = -1.66, 95% CI - -6.32-2.99; I² = 93%; P < 0.00001) and swollen joints (MD = -0.46, 95% CI - -1.98-1.07; I² = 56%; P = 0.08).

CONCLUSIONS

Vitamin E's ability to restore the intestinal barrier and improve the gastrointestinal tract may be linked to the prevention and treatment of rheumatoid arthritis. Vitamin E supplements used on a regular basis can help individuals with RA reduce joint discomfort, edema, and stiffness, as well as enhance their overall quality of life.

The Role of Autoantibody Testing in Modern Personalized Medicine

Personalized medicine (PM) aims individualized approach to prevention, diagnosis, and treatment. Precision Medicine applies the paradigm of PM by defining groups of individuals with akin characteristics. Often the two terms have been used interchangeably. The quest for PM has been advancing for centuries as traditional nosology classification defines groups of clinical conditions with relatively similar prognoses and treatment options. However, any individual is characterized by a unique set of multiple characteristics and therefore the achievement of PM implies the determination of myriad demographic, epidemiological, clinical, laboratory, and imaging parameters. The accelerated identification of numerous biological variables associated with diverse health conditions contributes to the fulfillment of one of the pre-requisites for PM. The advent of multiplex analytical platforms contributes to the determination of thousands of biological parameters using minute amounts of serum or other biological matrixes. Finally, big data analysis and machine learning contribute to the processing and integration of the multiplexed data at the individual level, allowing for the personalized definition of susceptibility, diagnosis, prognosis, prevention, and treatment. Autoantibodies are traditional biomarkers for autoimmune diseases and can contribute to PM in many aspects, including identification of individuals at risk, early diagnosis, disease sub-phenotyping, definition of prognosis, and treatment, as well as monitoring disease activity. Herein we address how autoantibodies can promote PM in autoimmune diseases using the examples of systemic lupus erythematosus, antiphospholipid syndrome, rheumatoid arthritis, Sjögren syndrome, systemic sclerosis, idiopathic inflammatory myopathies, autoimmune hepatitis, primary biliary cholangitis, and autoimmune neurologic diseases.

Big data analyses and individual health profiling in the arena of rheumatic and musculoskeletal diseases (RMDs)

Health care processes are under constant development and will need to embrace advances in technology and health science aiming to provide optimal care. Considering the perspective of increasing treatment options for people with rheumatic and musculoskeletal diseases, but in many cases not reaching all treatment targets that matter to patients, care systems bare potential to improve on a holistic level. This review provides an overview of systems and technologies under evaluation over the past years that show potential to impact diagnosis and treatment of rheumatic diseases in about 10 years from now. We summarize initiatives and studies from the field of electronic health records, biobanking, remote monitoring, and artificial intelligence. The combination and implementation of these opportunities in daily clinical care will be key for a new era in care of our patients. This aims to inform rheumatologists and healthcare providers concerned with chronic inflammatory musculoskeletal conditions about current important and promising developments in science that might substantially impact the management processes of rheumatic diseases in the 2030s.

Making space for patients' preferences in precision medicine: a qualitative study exploring perspectives of patients with rheumatoid arthritis

OBJECTIVE

Precision medicine in rheumatoid arthritis (RA) creates new opportunities to involve patients in early identification of accurate indicators of health trajectories. The aim of this study was to explore patient perspectives on patient-centredness in precision medicine for RA treatment.

DESIGN

Semistructured interviews were conducted to explore patients' perspectives on a new personalised approach to RA treatment. The interview guide was developed together with patient research partners and health care professionals.

SETTING

An invitation to the interviews was sent through a mobile application. The interviews were one-on-one, using an interview guide with open-ended questions. Interviews were conducted digitally (October 2020-February 2021) via Zoom or telephone, depending on each participant's preferences.

PARTICIPANTS

Patients with RA (N=12) were purposively recruited. Patients were eligible if they had an RA diagnosis, were aged 18-80 years, and understood and expressed themselves in Swedish. Participants and researchers did not know each other prior to the interviews.

RESULTS

Participants expressed desires and needs for patients to have an active role in precision medicine by making shared treatment decisions together with a healthcare professional. In order for that to work, patients need information on potential treatment options, an ability to express their preferences, an individual treatment plan and identification of personal treatment goals. Patients also identified two requirements of healthcare professional in precision medicine: a safe environment to express personal matters and two-way communication with healthcare professionals.

CONCLUSION

Communication between patients and healthcare professionals needs to be more focused on patients' individual treatment preferences and expressed needs, in order to increase patient-centredness in treatment decisions, so shared decision-making can become a reality. More research is needed to design multifaceted implementation strategies to support patients and healthcare professionals to increase patient-centredness throughout treatment personalisation.

Multicentre study to improve clinical interpretation of rheumatoid factor and anti-citrullinated protein/peptide antibodies test results

BACKGROUND

Rheumatoid factor (RF) and anti-citrullinated protein/peptide antibodies (ACPA) are important biomarkers for diagnosis of rheumatoid arthritis (RA). However, there is poor harmonisation of RF and ACPA assays. The aim of this study was to refine RF and ACPA interpretation across commercial assays.

MATERIALS AND METHODS

Six total RF isotype-non-specific assays, 3 RF IgM isotype-specific assays and 9 ACPA immunoglobulin G assays of 13 different companies were evaluated using 398 diagnostic samples from patients with RA and 1073 disease controls.

RESULTS

Using cut-offs proposed by the manufacturer, there was a large variability in diagnostic sensitivity and specificity between assays. Thresholds of antibody levels were determined based on predefined specificities and used to define test result intervals. Test result interval-specific likelihood ratios (LRs) were concordant across the different RF and ACPA assays. For all assays, the LR for RA increased with increasing antibody level. Higher LRs were found for ACPA than for RF. ACPA levels associated with LRs >80 were found in a substantial fraction (>22%) of patients with RA.

CONCLUSION

Defining thresholds for antibody levels and assigning test result interval-specific LRs allows alignment of clinical interpretation for all RF and ACPA assays.

Impact of autoimmune serology test results on RA classification and diagnosis

Rheumatoid arthritis (RA) is the most common systemic autoimmune disease and also the most severe arthritic disorder. The measurement of rheumatoid factor (RF) and anti-citrullinated protein antibodies (ACPA) in serum supports the diagnosis of RA, which gained increasing significance over the last 65 years. However, a high variability between RF and ACPA methods has been described, impacting the diagnostic performance of the current ACR/EULAR RA classification criteria.

The great number of commercially available assays, often lacking traceability to an international standard, is a major factor attributing to this in-between assay variability. The adoption of an international standard for ACPA, as is since long available for rheumatoid factor, is therefore highly desirable.

Further harmonization in clinical interpretation of RF/ACPA assays could be obtained by harmonization of the cut-offs, for both the low and high antibody levels, based on predefined specificity in disease controls. Reporting test result specific likelihood ratios (LR) adds value in the interpretation of autoantibody tests. However, a good understanding of the control population used to define antibody test result interval-associated LRs is crucial in defining the diagnostic performance characteristics of antibody serology.

Finally, specificity in RA classification can be improved by refining serological weight scoring taking into account the nature of the antibody, the antibody level and double RF + ACPA positivity.

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.

Targeting MyD88 Downregulates Inflammatory Mediators and Pathogenic Processes in PBMC From DMARDs-Naïve Rheumatoid Arthritis Patients

MyD88-dependent intracellular signalling cascades and subsequently NF-kappaB-mediated transcription lead to the dynamic inflammatory processes underlying the pathogenesis of rheumatoid arthritis (RA) and related autoimmune diseases. This study aimed to identify the effect of the MyD88 dimerization inhibitor, ST2825, as a modulator of pathogenic gene expression signatures and systemic inflammation in disease-modifying antirheumatic drugs (DMARDs)-naïve RA patients. We analyzed bulk RNA-seq from peripheral blood mononuclear cells (PBMC) in DMARDs-naïve RA patients after stimulation with LPS and IL-1β. The transcriptional profiles of ST2825-treated PBMC were analyzed to identify its therapeutic potential. Ingenuity Pathway Analysis was implemented to identify downregulated pathogenic processes. Our analysis revealed 631 differentially expressed genes between DMARDs-naïve RA patients before and after ST2825 treatment. ST2825-treated RA PBMC exhibited a gene expression signature similar to that of healthy controls PBMC by downregulating the expression of proinflammatory cytokines, chemokines and matrix metalloproteases. In addition, B cell receptor, IL-17 and IL-15 signalling were critically downregulated pathways by ST2825. Furthermore, we identified eight genes (MMP9, CXCL9, MZB1, FUT7, TGM2, IGLV1-51, LINC01010, and CDK1) involved in pathogenic processes that ST2825 can potentially inhibit in distinct cell types within the RA synovium. Overall, our findings indicate that targeting MyD88 effectively downregulates systemic inflammatory mediators and modulates the pathogenic processes in PBMC from DMARDs-naïve RA patients. ST2825 could also potentially inhibit upregulated genes in the RA synovium, preventing synovitis and joint degeneration.

Identification of a Rule to Predict Response to Sarilumab in Patients with Rheumatoid Arthritis Using Machine Learning and Clinical Trial Data

INTRODUCTION

In rheumatoid arthritis, time spent using ineffective medications may lead to irreversible disease progression. Despite availability of targeted treatments, only a minority of patients achieve sustained remission, and little evidence exists to direct the choice of biologic disease-modifying antirheumatic drugs in individual patients. Machine learning was used to identify a rule to predict the response to sarilumab and discriminate between responses to sarilumab versus adalimumab, with a focus on clinically feasible blood biomarkers.

METHODS

The decision tree model GUIDE was trained using a data subset from the sarilumab trial with the most biomarker data, MOBILITY, to identify a rule to predict disease activity after sarilumab 200 mg. The training set comprised 18 categorical and 24 continuous baseline variables; some data were omitted from training and used for validation by the algorithm (cross-validation). The rule was tested using full datasets from four trials (MOBILITY, MONARCH, TARGET, and ASCERTAIN), focusing on the recommended sarilumab dose of 200 mg.

RESULTS

In the training set, the presence of anti-cyclic citrullinated peptide antibodies, combined with C-reactive protein > 12.3 mg/l, was identified as the "rule" that predicts American College of Rheumatology 20% response (ACR20) to sarilumab. In testing, the rule reliably predicted response to sarilumab in MOBILITY, MONARCH, and ASCERTAIN for many efficacy parameters (e.g., ACR70 and the 28-joint disease activity score using CRP [DAS28-CRP] remission). The rule applied less to TARGET, which recruited individuals refractory to tumor necrosis factor inhibitors. The potential clinical benefit of the rule was highlighted in a clinical scenario based on MONARCH data, which found that increased ACR70 rates could be achieved by treating either rule-positive patients with sarilumab or rule-negative patients with adalimumab.

CONCLUSIONS

Well-established and clinically feasible blood biomarkers can guide individual treatment choice. Real-world validation of the rule identified in this post hoc analysis is merited.

CLINICAL TRIAL REGISTRATION

NCT01061736, NCT02332590, NCT01709578, NCT01768572.

Addition of Fibroblast-Stromal Cell Markers to Immune Synovium Pathotypes Better Predicts Radiographic Progression at 1 Year in Active Rheumatoid Arthritis

Objectives

This study aims to investigate if addition of fibroblast-stromal cell markers to a classification of synovial pathotypes improves their predictive value on clinical outcomes in rheumatoid arthritis (RA).

Methods

Active RA patients with a knee needle synovial biopsy at baseline and finished 1-year follow-up were recruited from a real-world prospective cohort. Positive staining for CD20, CD38, CD3, CD68, CD31, and CD90 were scored semiquantitatively (0-4). The primary outcome was radiographic progression defined as a minimum increase of 0.5 units of the modified total Sharp score from baseline to 1 year.

Results

Among 150 recruited RA patients, 123 (82%) had qualified synovial tissue. Higher scores of CD20+ B cells, sublining CD68+ macrophages, CD31+ endothelial cells, and CD90+ fibroblasts were associated with less decrease in disease activity and greater increase in radiographic progression. A new fibroblast-based classification of synovial pathotypes giving more priority to myeloid and stromal cells classified samples as myeloid-stromal (57.7%, 71/123), lymphoid (31.7%, 39/123), and paucicellular pathotypes (10.6%, 13/123). RA patients with myeloid-stromal pathotype showed the highest rate of radiographic progression (43.7% vs. 23.1% vs. 7.7%, p = 0.011), together with the lowest rate of Boolean remission at 3, 6, and 12 months. Baseline synovial myeloid-stromal pathotype independently predicted radiographic progression at 1 year (adjusted OR: 3.199, 95% confidence interval (95% CI): 1.278, 8.010). Similar results were obtained in a subgroup analysis of treatment-naive RA.

Conclusions

This novel fibroblast-based myeloid-stromal pathotype could predict radiographic progression at 1 year in active RA patients which may contribute to the shift of therapeutic decision in RA.

Torque Teno Virus Quantification for Monitoring of Immunomodulation with Biological Compounds in the Treatment of Rheumatoid Arthritis

OBJECTIVES

Rheumatoid arthritis (RA) patients who fail to respond to methotrexate (MTX) can receive biologic disease-modifying antirheumatic drugs (bDMARDs). The Torque Teno Virus (TTV) is a potential novel candidate for monitoring of immunosuppression. We explore TTV in these patients and association with clinical response to bDMARDs.

METHODS

The BioBio Study is a multicentre randomized open-label trial, including RA patients with insufficient response to MTX. Patients were randomized to either TNFi (infliximab, INF), anti-IL-6 (tocilizumab, TCZ), CTLA4-Ig (abatacept, ABA) or anti-CD20 (rituximab, RTX) in addition to MTX. PCR was used to quantify TTV in the peripheral blood.

RESULTS

TTV was measured in 95 patients (INF, n = 23; TCZ, n = 22; ABA, n = 27; RTX; n = 23). TTV increased by a median of 4.5*104 copies/ml (c/ml; inter quartile range [IQR] 0-7.5*105) after 3 months. TTV levels at month 3 were associated with SDAI (p= 0.03) and CDAI response (p= 0.026) at month 6. A TTV cut-off level of 1.2*106 c/ml at month 3 had a positive likelihood ratio of 2.7 for prediction of SDAI85% response at month 6.

CONCLUSION

Our data suggest that TTV levels increase upon TNF, CD20 and co-stimulation blockade and associate with clinical response to bDMARDs in RA patients.

TRIAL REGISTRATION

ClinicalTrials.gov; https://clinicaltrials.gov; NCT01638715.

Characteristics of patients with difficult-to-treat rheumatoid arthritis in clinical practice

OBJECTIVES

The aim of this study was to investigate the clinical characteristics of patients with difficult-to-treat RA (D2T RA) and the usefulness of switching to drugs with different modes of action in real-world.

METHODS

We reviewed all consecutive patients with RA treated at Keio University Hospital between 2016 and 2017 with a definition of D2T RA. We analysed clinical characteristics and evaluated the usefulness of changing drugs according to mode of action.

RESULTS

Among 1709 patients with RA, 173 (10.1%) were D2T RA. The reason for the D2T RA was multi-drug resistance in 59 patients (34.1%), comorbidity in 17 (9.8%), and socio-economic reasons in 97 (56.1%). The multi-drug-resistance group had significantly higher tender joint count and evaluator global assessment than the other groups, despite receiving the most intensive treatment. The comorbidity group showed a significantly older age and higher rheumatic disease comorbidity index. Although changing the drug to another with a different mode of action was useful, the proportion of patients who achieved remission or low disease activity decreased as the number of switches increased.

CONCLUSION

Of the patients with RA, 10.1% were still difficult to treat in clinical practice, despite intensive treatment. Their characteristics were distinct by the reasons of D2T RA, which suggests the need for a personalized approach to D2T RA.