Genomics, transcriptomics and proteomics to elucidate the pathogenesis of rheumatoid arthritis

Dieckol ameliorates inflammatory response via inhibition of CHI3L1 expression in collagen-induced arthritis rats

BACKGROUND

Dieckol (DEK), the main phlorotannin of brown algal, has been regarded as a powerful anti-inflammatory agent in various diseases. Rheumatoid arthritis (RA) is a typical inflammatory autoimmune disease affecting synovial joints. However, the pharmaceutical effect of DEK on RA is still waiting to be unveiled.

METHODS

A collagen-induced arthritis (CIA) rat model was established and DEK was administered intraperitoneally for three weeks. Paw swelling and histologic analysis were performed to evaluate CIA progression. Inflammatory cytokine and oxidative biomarker expression were assessed by real-time quantitative polymerase chain reaction (RT-qPCR) and enzyme-linked immunosorbent assay (ELISA). Vascular endothelial growth factor A (VEGFA) expression in synovial joint was assessed by immunoblotting and immunofluorescent (IF) staining. TdT-mediated dUTP nick-end labeling (TUNEL) staining was used to evaluate chondrocyte apoptosis. Western blot assay was performed to determine the expression level of nuclear erythroid-derived 2-like 2 (Nrf2), chitinase 3-like protein 1(CHI3L1) and apoptosis-specific proteins. Finally, CHI3L1 overexpression was used to explore its essential role in the biological effect of DEK in vivo.

RESULTS

DEK treatment significantly ameliorates paw swelling, inflammatory cell infiltration, chondrocyte apoptosis and vascular pannus formation in CIA rats. Moreover, inflammatory cytokine and oxidative biomarker expression was also attenuated by DEK treatment. Notably, DEK treatment obviously promoted Nrf2 nuclear import and CHI3L1 expression in synovial joint. Overexpression of CHI3L1 by AVV-mediated transfection abrogated the pharmaceutical effect of DEK in vivo.

CONCLUSION

This study provides a promising translational potential of DEK as an anti-rheumatic drug facilitating RA clinical treatment.

From genetic variants to therapeutic targets: insights into understanding rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease that affects multiple systems and is driven by various factors, including interactions between genetic and environmental elements. Over the past few decades, genome-wide association studies (GWAS) have been instrumental in regard to identifying genetic and environmental risk factors associated with RA susceptibility and pathogenesis. The recent discoveries of novel genetic susceptibility loci and pathways offer promising therapeutic targets for RA and precision medicine. More than 100 genetic loci have been identified in RA patients. In this review, we have focused on more than 40 genes that have been supported by evidence to be closely associated with the development of RA. These include genes involved in various mechanisms, such as loss of self-tolerance, autoimmune antibody production (e.g., HLA-DRB1, HLA-DPB1), inflammatory signaling and bone destruction (e.g., PTPN22, CCR6), complication (e.g., HLA-DQB1, IRF5), and differential drug responses (e.g., HLA-E, NKG2D). These novel players and mechanisms enhance our understanding of the RA pathogenesis and also provide a reference for personalized and precise medicine, including diagnosis and treatment.

Development and Validation of a Cost-Effective Machine Learning Model for Screening Potential Rheumatoid Arthritis in Primary Healthcare Clinics

Objective

In primary healthcare, diagnosing rheumatoid arthritis (RA) is challenging due to a general lack of in-depth knowledge of RA by general practitioners (GPs) and the lack of effective tools, leading to high rates of missed diagnosis. This study focuses on a screening model for primary healthcare, aiming to improve early RA screening accuracy and efficiency at a relatively lower cost, reducing delays in GPs' recognition of RA.

Methods

We randomly selected 2106 participants from the RA group or combined control group (comprising healthy individuals and patients with non-RA rheumatic diseases) at Peking University Shenzhen Hospital as the developing cohort. Guided by experienced rheumatologists, we built a comprehensive database with 26 clinical features. Using 10 classical machine learning algorithms, we developed screening models. Evaluation metrics determined the best model. Employing multivariatelogistic regression results and the best-performing model to identify the least costly features, ensuring applicability in primary healthcare clinics. Subsequently, we retrained and validated our proposed model based on two primary healthcare validation cohorts.

Results

In experiments, the algorithms achieved over 88% accuracy on training and test sets. Random Forest (RF) excelled with 96.20% (95% CI 95.39% to 97.02%) accuracy, 96.22% (95% CI 95.40% to 97.03%) specificity, 96.18% (95% CI 95.37% to 97.00%) sensitivity, and 96.20% (95% CI 95.39% to 97.02%) Areas Under Curves (AUC). A meticulous feature selection identified 11 key features for RA screening. In an external test on two primary healthcare datasets with these features, RF demonstrated an accuracy of 88.435% (95% CI 85.55% to 91.32%), sensitivity of 98.55% (95% CI 97.47% to 99.63%), specificity of 85.56% (95% CI 82.39% to 88.73%), and an AUC of 92.055% (95% CI 89.62% to 94.49%).

Conclusion

The screening model excels in automating prompt identification of RA in primary healthcare, improving the early detection of RA, and reducing delays and associated costs. Our findings contribute positively and are poised to elevate prospective RA management, fostering improvements in healthcare sector responsiveness and resource efficiency.

L-selectin Promotes Migration, Invasion and Inflammatory Response of Fibroblast-Like Synoviocytes in Rheumatoid Arthritis via NF-kB Signaling Pathway

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease characterized by chronic inflammation of the synovium and progressive joint damage. Fibroblast-like synoviocytes (FLSs) exhibit excessive proliferative and aggressive phenotypes and play a major role in the pathophysiology of RA. Previous studies have confirmed the pathologic role of L-selectin in cell adhesion and migration. In rheumatoid arthritis models, L-selectin regulates leukocyte homing, which leads to joint inflammation. Moreover, in L-selectin knockout mice, there is a reduction in joint inflammation. However, the associations of L-selectin with FLSs in RA remain unclear. This study aims to reveal the effect of L-selectin on RA-FLSs and to investigate the molecular mechanism of L-selectin in RA. Our findings indicated that L-selectin was significantly expressed in RA synovial tissues and RA-FLSs. L-selectin silencing reduced RA-FLSs migration and invasion and attenuated the secretion of pro-inflammatory cytokines TNF-α, IL-1β and IL-6 in vitro. Moreover, investigations into mechanisms revealed that L-selectin activated the nuclear factor kappa-B (NF-κB) signaling pathway while blocking this signaling pathway could compromise the effects of L-selectin. Finally, in vivo experiments with a collagen-induced arthritis rat model revealed that silencing L-selectin alleviated inflammatory infiltration of the synovium and cartilage destruction, and validated the NF-κB signaling pathways findings observed in vitro. In summary, we show that L-selectin enhances the migration and invasion of RA-FLSs through the activation of NF-κB signaling pathways, ultimately worsening the progression of RA.

Analysis of the causal relationship between immune cells and rheumatoid arthritis from the perspective of genetic variation: a bidirectional two-sample Mendelian randomization study

BACKGROUND

Immune factors are crucial in the pathogenesis of rheumatoid arthritis (RA), and immune cells play a key role in the development of RA. However, there is still disagreement regarding the specific roles of each type of immune cell in the pathological process of RA.

METHODS

This study used bidirectional two-sample Mendelian randomization (MR) analysis to determine the causal relationship between immune cell characteristics and RA. Utilizing publicly available genetic data, we initially treated immune cell characteristics as exposures to investigate their causal effects on the risk of RA. Subsequently, we performed reverse two-sample MR using the positively selected cells from the initial analysis as outcomes, aiming to identify the core immune cells involved. Finally, a comprehensive sensitivity analysis was conducted to validate the robustness, heterogeneity, and horizontal pleiotropy of the results.

RESULTS

Using data from 731 immune cells as exposures and cell SNPs as instruments, we independently conducted two-sample MR analysis for each patient with RA. The main analytical method used was the IVW method, with a significance level set at P < 0.05 for inclusion. In total, we identified 42 immune cell phenotypes that were causally associated with the onset of RA. For the reverse MR analysis, we used RA as the exposure factor and focused on 42 immune cell phenotypes as outcomes. Our analysis revealed causal relationships between the onset of RA and 7 immune cell phenotypes. Among these, 6 showed positive causal relationships, while 1 exhibited a negative causal relationship.

CONCLUSIONS

Our study emphasized the causal relationship between immune cells and RA through bidirectional two-sample MR analysis, identifying the immune cells causally associated with RA.

LncRNA SNHG3 discriminates rheumatoid arthritis from healthy individuals and regulates inflammatory response and oxidative stress via modulating miR-128-3p

OBJECTIVES

This study evaluated the expression and significance of SNHG3 in rheumatoid arthritis (RA), aiming to explore a biomarker and regulator for RA.

METHODS

The expression of SNHG3 in serum and synovial tissue was compared between RA patients and healthy individuals using polymerase chain reaction (PCR). The RA animal models were induced by the Porcine Type II collagen in Wistar rats and validated by the foot volume and arthritis index score. The human fibroblast-like synoviocytes were treated with lipopolysaccharide (LPS) to mimic the injury during RA onset, and the cell growth was assessed by cell counting kit-8 (CCK8) assay.

RESULTS

SNHG3 was significantly downregulated in the serum and synovial tissue of RA patients compared with healthy individuals. Downregulated SNHG3 could discriminate RA patients from healthy individuals with high sensitivity (0.875) and specificity (0.844). Porcine Type II collagen induced increasing foot volume and arthritis index scores of rats, and SNHG3 was downregulated in RA rats. In LPS-induced human fibroblast-like synoviocytes, SNHG3 negatively regulated miR-128-3p, and the alleviated effect of SNHG3 overexpression on cellular inflammation and oxidative stress was reversed by miR-128-3p upregulation.

CONCLUSIONS

Serum SNHG3 was considered a potential diagnostic biomarker for RA from healthy individuals. SNHG3 regulated inflammatory response and oxidative stress by negatively modulating miR-128-3p.

An overview of multi-omics technologies in rheumatoid arthritis: applications in biomarker and pathway discovery

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease with a complex pathological mechanism involving autoimmune response, local inflammation and bone destruction. Metabolic pathways play an important role in immune-related diseases and their immune responses. The pathogenesis of rheumatoid arthritis may be related to its metabolic dysregulation. Moreover, histological techniques, including genomics, transcriptomics, proteomics and metabolomics, provide powerful tools for comprehensive analysis of molecular changes in biological systems. The present study explores the molecular and metabolic mechanisms of RA, emphasizing the central role of metabolic dysregulation in the RA disease process and highlighting the complexity of metabolic pathways, particularly metabolic remodeling in synovial tissues and its association with cytokine-mediated inflammation. This paper reveals the potential of histological techniques in identifying metabolically relevant therapeutic targets in RA; specifically, we summarize the genetic basis of RA and the dysregulated metabolic pathways, and explore their functional significance in the context of immune cell activation and differentiation. This study demonstrates the critical role of histological techniques in decoding the complex metabolic network of RA and discusses the integration of histological data with other types of biological data.

Rheumatoid arthritis is a protective factor against Alzheimer's disease: a bidirectional two-sample Mendelian randomization study

BACKGROUND

Epidemiological evidence suggests that there is an association between rheumatoid arthritis (RA) and Alzheimer's disease (AD). However, the causal relationship between RA and AD remains unclear. Therefore, this study aimed to investigate the causal relationship between RA and AD.

METHODS

Using publicly available genome-wide association study datasets, bidirectional two-sample Mendelian randomization (TSMR) was performed using the inverse-variance weighted (IVW), weighted median, MR‒Egger regression, simple mode, and weighted mode methods.

RESULTS

The results of MR for the causal effect of RA on AD (IVW, odds ratio [OR] = 0.959, 95% confidence interval [CI]: 0.941-0.978, P = 2.752E-05; weighted median, OR = 0.960, 95% CI: 0.937-0.984, P = 0.001) revealed a causal association between genetic susceptibility to RA and an increased risk of AD. The results of MR for the causal effect of AD on RA (IVW, OR = 0.978, 95% CI: 0.906-1.056, P = 0.576; weighted median, OR = 0.966, 95% CI: 0.894-1.043, P = 0.382) indicated that there was no causal association between genetic susceptibility to AD and an increased risk of RA.

CONCLUSIONS

The results of this two-way two-sample Mendelian randomization analysis revealed a causal association between genetic susceptibility to RA and a reduced risk of AD but did not reveal a causal association between genetic susceptibility to AD and an increased or reduced risk of RA.

Anti-proliferation and anti-migration effects of Yishen Tongbi decoction in experimental rheumatoid arthritis by suppressing SLC3A2/integrin β3 signaling pathways

BACKGROUND

Yishen Tongbi (YSTB) decoction is a patented herbal formula that is used in China to treat rheumatoid arthritis (RA); however, the exact mechanism of its anti-synovial hyperplasia efficacy has not been fully elucidated.

PURPOSE

Based on our previous proteomics study, we aimed to reveal whether YSTB inhibits the proliferation and migration of RA-FLSs through the SLC3A2/integrin β3 pathway in vivo and in vitro.

STUDY DESIGN

The study design consists of three parts, a comparison of the expression of SLC3A2 and integrin β3 in synovial tissues of RA and OA patients; an animal experiment to verify the pharmacodynamic effect of YSTB, and in vitro experiment to elucidate the specific mechanism of YSTB.

METHODS

The expression of SLC3A2 and integrin β3 in the synovial tissues of patients with RA and osteoarthritis (OA) patients were detected by immunohistochemistry (IHC). In vitro, firstly, the proliferation and migration abilities of HFLS (human fibroblast-like synoviocytes) and HFLS-RA (human fibroblast-like synoviocytes-RA) cells were compared by EdU staining and wound healing assays, respectively, and the differences in the expression and localization of SLC3A2, integrin β3, p-FAK and p-Src between HFLS and HFLS-RA cells were detected by IF and WB. In vivo, DBA/1 mice were injected with bovine collagen II to construct a CIA mouse model. Paw swelling, body weight and the arthritis index (AI) were used as basic treatment evaluation indicators for YSTB. Micro-CT and histopathological analyses of the knee and ankle joints were also performed. In addition, the expression of SLC3A2, integrin β3, p-FAK and p-Src in the synovial tissue of mice was detected by IHC. Subsequently, CCK-8 was used to screen for suitable concentrations of YSTB for use in HFLS-RA cells. EdU staining and transwell migration assays were performed to evaluate the inhibitory effect of YSTB on cell proliferation and migration, and WB was conducted to assess whether YSTB inhibited HFLS-RA migration through downregulation of the SLC3A2/integrin β3 pathways.

RESULTS

IHC showed that the expression of SLC3A2 and integrin β3 was higher in RA synovial tissues than in OA tissues. In vivo experiments showed that YSTB inhibited synovial hyperplasia, prevented bone destruction, and reduced the expression of SLC3A2, integrin β3, p-FAK and p-Src. In vitro experiments showed that YSTB inhibited HFLS-RA migration and proliferation by inhibiting the expression of SLC3A2/integrin β3 and downstream signaling molecules.

CONCLUSION

YSTB inhibits the proliferation and migration of synovial fibroblasts in RA by downregulating the SLC3A2/integrin β3 pathways.

hIgD-Fc-Ig fusion protein regulates T cell functions by inhibiting TCR signaling pathway in adjuvant arthritis rats

This study aimed to investigate the effect of hIgD-Fc-Ig on TCR-Lck-Erk activated by IgD in adjuvant arthritis (AA) rats. Wistar rats were divided into the normal, AA model, hIgD-Fc-Ig (1 mg/kg, 3 mg/kg and 9 mg/kg) and Etanercept (3 mg/kg) groups. The overall index of AA rats was measured every 3 days. The pathologic examination of knee joints and the proliferation of the spleen and thymus of AA rats were detected by H&E staining and CCK-8. The blood flow signal of knee joints of experimental rats was examined by US. The articular bone injury was detected by X-ray. The changes in PBMCs and spleen T cell subsets were detected by flow cytometry. The expression of CD3ε, p-Lck, p-Zap70, Ras, and p-Erk in rat spleens was detected by immunofluorescence and WB. Rat spleen T cells or Jurkat cells treated by IgD to observe the effect of hIgD-Fc-Ig on TCR and its downstream protein expression. The results showed that hIgD-Fc-Ig had a therapeutic effect on AA rats by reducing the secondary inflammation, improving pathological changes. hIgD-Fc-Ig can reduce the ratio of Th cells of PBMCs of AA rats, the ratio of Th, Th1, Th17 cells and increase the ratio of Th2, Treg cells of AA rat spleens. hIgD-Fc-Ig could down-regulate the expression of CD3ε, p-Lck, p-Zap70, Ras, p-Erk in vivo or in vitro. In conclusion, hIgD-Fc-Ig could alleviate the symptoms of AA rats and regulate T cells through TCR-Lck-Erk signaling pathway and maybe a new promising biological agent for RA.

Exosomes as biomarkers and therapeutic delivery for autoimmune diseases: Opportunities and challenges

Exosomes are spherical lipid bilayer vesicles composed of lipids, proteins and nucleic acids that deliver signaling molecules through a vesicular transport system to regulate the function and morphology of target cells, thereby involving in a variety of biological processes, such as cell apoptosis or proliferation, and cytokine production. In the past decades, there are emerging evidence that exosomes play pivotal roles in the pathological mechanisms of several autoimmune diseases (ADs), including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes mellitus (T1DM), Sjogren's syndrome (SS), multiple sclerosis (MS), inflammatory bowel disease (IBD). systemic sclerosis (SSc), etc. Several publications have shown that exosomes are involved in the pathogenesis of ADs mainly through intercellular communication and by influencing the response of immune cells. The level of exosomes and the expression of nucleic acids can reflect the degree of disease progression and are excellent biomarkers for ADs. In addition, exosomes have the potential to be used as drug carriers thanks to their biocompatibility and stability. In this review, we briefly summarized the current researches regarding the biological functions of exosomes in ADs, and provided an insight into the potential of exosomes as biomarkers and therapeutic delivery for these diseases.

Bidirectional two-sample Mendelian randomization study of causality between rheumatoid arthritis and myocardial infarction

Background

Epidemiological evidence suggests an association between rheumatoid arthritis (RA) and myocardial infarction (MI). However, causality remains uncertain. Therefore, this study aimed to explore the causal association between RA and MI.

Methods

Using publicly available genome-wide association study summary datasets, bidirectional two-sample Mendelian randomization (TSMR) was performed using inverse-variance weighted (IVW), weighted median, MR-Egger regression, simple mode, and weighted mode methods.

Results

The MR results for the causal effect of RA on MI (IVW, odds ratio [OR] = 1.041, 95% confidence interval [CI]: 1.007-1.076, P = 0.017; weighted median, OR = 1.027, 95% CI: 1.006-1.049, P = 0.012) supported a causal association between genetic susceptibility to RA and an increased risk of MI. MR results for the causal effect of MI on RA (IVW, OR = 1.012, 95% CI: 0.807-1.268, P = 0.921; weighted median, OR = 1.069, 95% CI: 0.855-1.338, P = 0.556) indicated that there was no causal association between genetic susceptibility to MI and an increased risk of RA.

Conclusion

Bidirectional TSMR analysis supports a causal association between genetic susceptibility to RA and an increased risk of MI but does not support a causal association between genetic susceptibility to MI and an increased risk of RA.

Identification of DNA methylation-regulated differentially expressed genes in RA by integrated analysis of DNA methylation and RNA-Seq data

OBJECTIVE

To identify novel DNA methylation-regulated differentially expressed genes (MeDEGs) in RA by integrated analysis of DNA methylation and RNA-Seq data.

METHODS

The transcription and DNA methylation profiles of 9 RA and 15 OA synovial tissue were generated by RNA-Seq and Illumina 850K DNA methylation BeadChip. Gene set enrichment analysis (GSEA) and Weighted gene co-expression network analysis (WGCNA) were used to analyze methylation-regulated expressed genes by R software. The differentially expressed genes (DEGs), differentially methylated probes (DMPs), differentially methylated genes (DMGs) were analyzed by DESeq and ChAMP R package. The functional correlation of MeDEGs was analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The protein-protein interaction (PPI) network of MeDEGs was constructed by STRING and Reactome FI Cytoscape Plugin. Correlation analysis between methylation level and mRNA expression was conducted with R software.

RESULTS

A total of 17,736 genes, 25,578 methylated genes and 755,852 methylation probes were detected. A total of 16,421 methylation-regulated expressed genes were obtained. The GSEA showed that these genes are associated with activation of immune response, adaptive immune response, Inflammatory response in C5 (ontology gene sets). For KEGG analysis, these genes are associated with rheumatoid arthritis, NF-kappa B signaling pathway, T cell receptor signaling pathway. The WGCNA showed that the turquoise module exhibited the strongest correlation with RA (R = 0.78, P = 1.27 × 10^- 05), 660 genes were screened in the turquoise module. A total of 707 MeDEGs were obtained. GO analysis showed that MeDEGs were enriched in signal transduction, cell adhesion for BP, enriched in plasma membrane, integral component of membrane for CC, and enriched in identical protein binding, calcium ion binding for MF. The KEGG pathway analysis showed that the MeDEGs were enriched in calcium signaling pathway, T cell receptor signaling pathway, NF-kappa B signaling pathway, Rheumatoid arthritis. The PPI network containing 706 nodes and 882 edges, and the enrichment p value < 1.0 × 10^- 16. With Cytoscape, based on the range of more than 10 genes, a total of 8 modules were screened out. Spearman correlation analysis showed RGS1(cg10718027), RGS1(cg02586212), RGS1(cg10861751) were significantly correlated with RA.

CONCLUSIONS

RGS1 can be used as novel methylated biomarkers for RA.

FOXC1‑mediated TRIM22 regulates the excessive proliferation and inflammation of fibroblast‑like synoviocytes in rheumatoid arthritis via NF‑κB signaling pathway

Rheumatoid arthritis (RA) is a common systemic autoimmune disorder of unknown etiology, which threatens public health. The regulatory role of tripartite motif-containing 22 (TRIM22) has been reported in multiple types of cancers and disease, but not in RA. The aim of the present study was therefore to elucidate the potential roles and underlying mechanisms of TRIM22 in fibroblast-like synoviocytes (FLSs) in RA. The Gene Expression Omnibus database was used to examine TRIM22 mRNA expression levels in synovial tissue samples of patients with RA and healthy controls. TRIM22 and forkhead box C1 (FOXC1) mRNA and protein expression levels in normal FLSs and RA-FLSs were assessed using reverse transcription-quantitative PCR (RT-qPCR) and western blotting, respectively. The Cell Counting Kit-8 assay was used to assess cell proliferation. Cell apoptosis was analyzed using flow cytometry. The migratory and invasive abilities of RA-FLSs were assessed using Transwell assays. Western blotting was used to analyze the protein expression levels of apoptosis-related factors, MMP2, MMP9 and NF-κB signaling pathway-related proteins. Inflammatory factors levels were assessed via ELISA and RT-qPCR. Furthermore, the JASPAR database, chromatin immunoprecipitation and the dual-luciferase reporter assays were used to determine the interaction between FOXC1 and the TRIM22 promoter. The results of the present study demonstrated that TRIM22 expression levels were significantly elevated in the synovial tissue samples of patients with RA and RA-FLSs. Moreover, FOXC1 was also significantly overexpressed in RA-FLSs. TRIM22 knockdown significantly reduced cell proliferation, migration, invasion and the inflammatory response, whereas cell apoptosis was significantly increased. Furthermore, the results demonstrated that FOXC1 may have positively mediated TRIM22 expression via binding to the TRIM22 promoter. Moreover, FOXC1 overexpression significantly reversed the outcome of TRIM22 knockdown on the proliferation, apoptosis, migration, invasion and inflammation of RA-FLSs. FOXC1 overexpression also significantly reversed the inactivation of the NF-κB signaling pathway caused by TRIM22 knockdown. In summary, the present study demonstrated that TRIM22 was potentially activated via FOXC1, which contributed to the progression of RA via the NF-κB signaling pathway.

Artificial Intelligence in Rheumatoid Arthritis: Current Status and Future Perspectives: A State-of-the-Art Review

Investigation of the potential applications of artificial intelligence (AI), including machine learning (ML) and deep learning (DL) techniques, is an exponentially growing field in medicine and healthcare. These methods can be critical in providing high-quality care to patients with chronic rheumatological diseases lacking an optimal treatment, like rheumatoid arthritis (RA), which is the second most prevalent autoimmune disease. Herein, following reviewing the basic concepts of AI, we summarize the advances in its applications in RA clinical practice and research. We provide directions for future investigations in this field after reviewing the current knowledge gaps and technical and ethical challenges in applying AI. Automated models have been largely used to improve RA diagnosis since the early 2000s, and they have used a wide variety of techniques, e.g., support vector machine, random forest, and artificial neural networks. AI algorithms can facilitate screening and identification of susceptible groups, diagnosis using omics, imaging, clinical, and sensor data, patient detection within electronic health record (EHR), i.e., phenotyping, treatment response assessment, monitoring disease course, determining prognosis, novel drug discovery, and enhancing basic science research. They can also aid in risk assessment for incidence of comorbidities, e.g., cardiovascular diseases, in patients with RA. However, the proposed models may vary significantly in their performance and reliability. Despite the promising results achieved by AI models in enhancing early diagnosis and management of patients with RA, they are not fully ready to be incorporated into clinical practice. Future investigations are required to ensure development of reliable and generalizable algorithms while they carefully look for any potential source of bias or misconduct. We showed that a growing body of evidence supports the potential role of AI in revolutionizing screening, diagnosis, and management of patients with RA. However, multiple obstacles hinder clinical applications of AI models. Incorporating the machine and/or deep learning algorithms into real-world settings would be a key step in the progress of AI in medicine.

Traditional Chinese Medicine Rhodiola Sachalinensis Borissova from Baekdu Mountain (RsBBM) for Rheumatoid Arthritis: Therapeutic Effect and Underlying Molecular Mechanisms

The lack of effective rheumatoid arthritis (RA) therapies is a persistent challenge worldwide, prompting researchers to urgently evaluate traditional Chinese medicines (TCMs) as potential clinical RA treatments. The present investigation was conducted to evaluate the therapeutic effects and potential molecular mechanisms of the active components isolated from TCM Rhodiola sachalinensis Borissova from Baekdu Mountain (RsB^BM) using an experimental adjuvant arthritis model induced by injection of rats with Freund’s complete adjuvant. After induction of the adjuvant arthritis rat model, the extract-treated and untreated groups of arthritic rats were evaluated for RsB^BM therapeutic effects based on comparisons of ankle circumferences and ELISA-determined blood serum inflammatory factor levels (TNF-α, IL-1β, and PGE2). In addition, the joint health of rats was evaluated via microscopic examination of hematoxylin-eosin-stained synovial tissues. Furthermore, to explore whether NF-κB and RANK/RANKL/OPG signaling pathways participated in observed therapeutic effects from a molecular mechanistic viewpoint, mRNA and protein levels related to the expression of nuclear factor kappa-B (NF-κB), osteoprotegerin (OPG), and receptor activator of nuclear factor kappa-Β ligand (RANKL) were analyzed via quantitative RT-PCR and Western blot analysis, respectively. Treatment of arthritic rats with the extract of RsB^BM was shown to reduce ankle swelling, reduce blood serum levels of inflammatory factors, and alleviate arthritis-associated synovial inflammation and joint damage. Moreover, an RsB^BM 50% ethanol extract treatment inhibited bone destruction by up-regulating OPG-related mRNA and protein expression and down-regulating RANKL-related mRNA and protein expression, while also reducing inflammation by the down-regulating of the NF-κB pathway activity. The results clearly demonstrated that the extract of RsB^BM alleviated adjuvant arthritis-associated joint damage by altering activities of inflammation-associated NF-κB and the RANK/RANKL/OPG signaling pathways. Due to its beneficial effects for alleviating adjuvant arthritis, this RsB^BM 50% ethanol extract should be further evaluated as a promising new therapeutic TCM treatment for RA.

Identification of Critical Biomarkers and Immune Infiltration in Rheumatoid Arthritis Based on WGCNA and LASSO Algorithm

Rheumatoid arthritis(RA) is the most common inflammatory arthritis, and a significant cause of morbidity and mortality. RA patients' synovial inflammation contains a variety of genes and signalling pathways that are poorly understood. It was the goal of this research to discover the major biomarkers related to the course of RA and how they connect to immune cell infiltration. The Gene Expression Omnibus was used to download gene microarray data. Differential expression analysis, weighted gene co-expression network analysis (WGCNA), and least absolute shrinkage and selection operator (LASSO) regression were used to identify hub markers for RA. Single-sample GSEA was used to examine the infiltration levels of 28 immune cells and their connection to hub gene markers. The hub genes' expression in RA-HFLS and HFLS cells was verified by RT-PCR. The CCK-8 assay was applied to determine the roles of hub genes in RA. In this study, we identified 21 differentially expressed genes (DEGs) in RA. WGCNA yielded two co-expression modules, one of which exhibited the strongest connection with RA. Using a combination of differential genes, a total of 6 intersecting genes was discovered. Six hub genes were identified as possible biomarkers for RA after a lasso analysis was performed on the data. Three hub genes, CKS2, CSTA, and LY96, were found to have high diagnostic value using ROC curve analysis. They were shown to be closely related to the concentrations of several immune cells. RT-PCR confirmed that the expressions of CKS2, CSTA and LY96 were distinctly upregulated in RA-HFLS cells compared with HFLS cells. More importantly, knockdown of CKS2 suppressed the proliferation of RA-HFLS cells. Overall, to help diagnose and treat RA, it's expected that CKS2, CSTA, and LY96 will be available, and the aforementioned infiltration of immune cells may have a significant impact on the onset and progression of the disease.

CKS2 and S100A12: Two Novel Diagnostic Biomarkers for Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a chronic systematicness autoimmunity disease with joint inflammation. RA etiology is still unknown. Early and exact diagnosing is still hard to reach. In the paper, we purposed to discover novel diagnosis biological marker for RA. Two open, usable gene expression profiles of human RA as well as controlled specimens (dataset GSE17755 as well as GSE93272) were downloaded from the GEO database. Differentially expressed genes (DEGs) were screened between 331 RA and 88 control samples. Functional enrichment analysis was applied to explore the possible function of DEGs. Expression levels as well as diagnosis values of biological marker in RA were further verified in our cohort by the use of RT-PCR and ROC assays. We identified 13 DEGs between RA samples and control samples. 13 DEGs were remarkably abundant in NF-kappa B signal pathway. Among the 13 DEGs, CKS2, S100A12, LY96, and ANXA3 exhibited a strong diagnostic ability in screening RA specimens from normal specimens using all AUC > 0.8. Moreover, we confirmed that the expression of CKS2 and S100A12 was distinctly upregulated in RA specimens contrasted to normal specimens. Overall, serum CKS2 and S100A12 could be used as novel diagnosis biological markers for RA patients.

MiR-361-5p promotes proliferation and inhibits apoptosis of fibroblast-like synoviocytes via targeting ZBTB10 in rheumatoid arthritis

OBJECTIVES

This study is aimed to explore the key role of miR-361-5p in fibroblast-like synovial (FLS) cells of rheumatoid arthritis (RA) and explore the underlying mechanism.

METHODS

First, we performed RT-qPCR to evaluate the expression of miR-361-5p in both synovial tissues of RA patients and cultured RA-FLS cells. Then CCK-8 assay, EdU staining, Western blot, flow cytometry, and ELISA were conducted to estimate the influence of inhibiting miR-361-5p on RA-FLS cells. Moreover, we used bioinformatics analysis to predict the potential targets of miR-361-5p and perform a dual luciferase report assay for verification. Finally, rescue experiments were performed to prove the role of miR-361-5p/Zinc Finger And BTB Domain Containing 10 (ZBTB10) in the proliferation, cell cycle, and apoptosis of RA-FLS.

RESULTS

We find that the expression of miR-361-5p is increased in both RA tissues and cultured RA-FLS cells. The inhibition of miR-361-5p can not only inhibit proliferation, arrest the cell cycle in G1/G0 phase, and increase apoptosis, but also reduce the inflammatory factors secreted by RA-FLS cells. In addition, ZBTB10 is a direct target for miR-361-5p, over-expression of ZBTB10 reverses the effect of miR-361-5p in RA-FLS.

CONCLUSIONS

MiR-361-5p promotes the progression of rheumatoid arthritis by targeting ZBTB10. Key pointsThe influences of miR-361-5p on RA-FLS cells.

RNA-seq and Network Analysis Reveal Unique Chemokine Activity Signatures in the Synovial Tissue of Patients With Rheumatoid Arthritis

Purpose

This study aimed to provide a comprehensive understanding of the genome-wide expression patterns in the synovial tissue samples of patients with rheumatoid arthritis (RA) to investigate the potential mechanisms regulating RA occurrence and development.

Methods

Transcription profiles of the synovial tissue samples from nine patients with RA and 15 patients with osteoarthritis (OA) (control) from the East Asian population were generated using RNA sequencing (RNA-seq). Gene set enrichment analysis (GSEA) was used to analyze all the detected genes and the differentially expressed genes (DEGs) were identified using DESeq. To further analyze the DEGs, the Gene Ontology (GO) functional enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. The protein-protein interaction (PPI) network of the DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and the hub genes were identified by topology clustering with the Molecular Complex Detection (MCODE)-Cytoscape. The most important hub genes were validated using quantitative real-time PCR (qRT-PCR).

Results

Of the 17,736 genes detected, 851 genes were identified as the DEGs (474 upregulated and 377 downregulated genes) using the false discovery rate (FDR) approach. GSEA revealed that the significantly enriched gene sets that positively correlated with RA were CD40 signaling overactivation, Th1 cytotoxic module, overactivation of the immune response, adaptive immune response, effective vs. memory CD8+ T cells (upregulated), and naïve vs. effective CD8+ T cells (downregulated). Biological process enrichment analysis showed that the DEGs were significantly enriched for signal transduction (P = 3.01 × 10-6), immune response (P = 1.65 × 10-24), and inflammatory response (P = 5.76 × 10-10). Molecule function enrichment analysis revealed that the DEGs were enriched in calcium ion binding (P = 1.26 × 10-5), receptor binding (P = 1.26 × 10-5), and cytokine activity (P = 2.01 × 10-3). Cellular component enrichment analysis revealed that the DEGs were significantly enriched in the plasma membrane (P = 1.91 × 10-31), an integral component of the membrane (P = 7.39 × 10-13), and extracellular region (P = 7.63 × 10-11). The KEGG pathway analysis showed that the DEGs were enriched in the cytokine-cytokine receptor interaction (P = 3.05 × 10-17), chemokine signaling (P = 3.50 × 10-7), T-cell receptor signaling (P = 5.17 × 10-4), and RA (P = 5.17 × 10-4) pathways. We confirmed that RA was correlated with the upregulation of the PPI network hub genes, such as CXCL13, CXCL6, CCR5, CXCR5, CCR2, CXCL3, and CXCL10, and the downregulation of the PPI network hub gene such as SSTR1.

Conclusion

This study identified and validated the DEGs in the synovial tissue samples of patients with RA, which highlighted the activity of a subset of chemokine genes, thereby providing novel insights into the molecular mechanisms of RA pathogenesis and identifying potential diagnostic and therapeutic targets for RA.

Bioinformatics Analysis Identified the Hub Genes, mRNA–miRNA–lncRNA Axis, and Signaling Pathways Involved in Rheumatoid Arthritis Pathogenesis

Objective

Rheumatoid arthritis (RA) is a nonspecific, chronic, systemic autoimmune disease characterized by symmetric polyarticular synovitis. Bioinformatics analysis of potential biomarkers, mRNA–miRNA–lncRNA axes, and signaling pathways in the pathogenesis of RA provides potential targets and theoretical basis for further research on RA.

Methods

The GSE1919 and GSE77298 datasets were downloaded from the Gene Expression Omnibus database (http://www.ncbi.nlm.nih.gov/geo). Perl was used to perform data merging, and R was used to perform batch correction. The “limma” package of R was used to screen differentially expressed genes, and the “clusterProfiler” package was used to perform enrichment analysis of the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Search Tool for the Retrieval of Interacting Genes/Proteins was used to construct the protein–protein interaction network, Cytoscape was used for module analysis, and R was used to screen for hub genes. GraphPad Prism was used to plot the receiver operating characteristic curve of the hub genes. Gene set enrichment analysis and competitive endogenous RNA network analysis were performed on hub genes with the greatest diagnostic values. The hub gene with the greatest diagnostic value was verified using immunohistochemical staining.

Results

We obtained nine hub genes (ITGB2, VAMP8, HLA-A, PTAFR, SYK, FCER1G, HLA-DPB1, LCP2, and ACTR2) and four mRNA–miRNA–lncRNA axes (ITGB2-hsa-miR-486-3p-SNHG3, ITGB2-hsa-miR-338-5p-XIST, ITGB2-hsa-miR-5581-3p-XIST, and ITGB2-hsa-miR-1226-5p-XIST) related to the pathogenesis of RA. The nine hub genes were highly expressed, and ITGB2 had the highest diagnostic value for RA. We also identified signaling pathways related to the pathogenesis of RA: Fc epsilon Rl and chemokine signaling pathways. The immunohistochemical results showed that ITGB2 expression was significantly upregulated in RA.

Conclusion

The hub genes, mRNA–miRNA–lncRNA axes, and signaling pathways related to RA pathogenesis identified in this study provide a new research direction for the mechanism, diagnosis, and treatment of RA.

Recent Major Transcriptomics and Epitranscriptomics Contributions toward Personalized and Precision Medicine

With the advent of genome-wide screening methods-beginning with microarray technologies and moving onto next generation sequencing methods-the era of precision and personalized medicine was born. Genomics led the way, and its contributions are well recognized. However, "other-omics" fields have rapidly emerged and are becoming as important toward defining disease causes and exploring therapeutic benefits. In this review, we focus on the impacts of transcriptomics, and its extension-epitranscriptomics-on personalized and precision medicine efforts. There has been an explosion of transcriptomic studies particularly in the last decade, along with a growing number of recent epitranscriptomic studies in several disease areas. Here, we summarize and overview major efforts for cancer, cardiovascular disease, and neurodevelopmental disorders (including autism spectrum disorder and intellectual disability) for transcriptomics/epitranscriptomics in precision and personalized medicine. We show that leading advances are being made in both diagnostics, and in investigative and landscaping disease pathophysiological studies. As transcriptomics/epitranscriptomics screens become more widespread, it is certain that they will yield vital and transformative precision and personalized medicine contributions in ways that will significantly further genomics gains.

Drug repurposing for rheumatoid arthritis: Identification of new drug candidates via bioinformatics and text mining analysis

Rheumatoid arthritis (RA) is an autoimmune disease that results in the destruction of tissue by attacks on the patient by his or her own immune system. Current treatment strategies are not sufficient to overcome RA. In the present study, various transcriptomic data from synovial fluids, synovial fluid-derived macrophages, and blood samples from patients with RA were analysed using bioinformatics approaches to identify tissue-specific repurposing drug candidates for RA. Differentially expressed genes (DEGs) were identified by integrating datasets for each tissue and comparing diseased to healthy samples. Tissue-specific protein-protein interaction (PPI) networks were generated and topologically prominent proteins were selected. Transcription-regulating biomolecules for each tissue type were determined from protein-DNA interaction data. Common DEGs and reporter biomolecules were used to identify drug candidates for repurposing using the hypergeometric test. As a result of bioinformatic analyses, 19 drugs were identified as repurposing candidates for RA, and text mining analyses supported our findings. We hypothesize that the FDA-approved drugs momelotinib, ibrutinib, and sodium butyrate may be promising candidates for RA. In addition, CHEMBL306380, Compound 19a (CHEMBL3116050), ME-344, XL-019, TG100801, JNJ-26483327, and NV-128 were identified as novel repurposing candidates for the treatment of RA. Preclinical and further validation of these drugs may provide new treatment options for RA.

[Methylation status and expression of TWEAK gene promoter region in peripheral blood of patients with rheumatoid arthritis]

OBJECTIVE

To explore the relationship between tumor necrosis factor like weak inducer of apoptosis (TWEAK) gene and the pathogenesis of rheumatoid arthritis (RA) by detecting the DNA methylation level, mRNA expression level and serum protein concentration of TWEAK gene in peripheral blood.

METHODS

The MassARRAY method was used to detect the DNA methylation level of the TWEAK gene in the peripheral blood of 112 RA patients and 86 matched healthy volunteers. The real-time quantitative polymerase chain reaction method was used to detect the mRNA expression level of the TWEAK gene in the peripheral blood of the subjects. The enzyme-linked immunosorbent assay method was used to detect the serum TWEAK protein concentration of the subjects. The TWEAK gene DNA methylation level, mRNA expression level and serum protein concentration between the RA group and the healthy control group were compared, and the relationship between it and the degree of disease activity analyzed.

RESULTS

The overall DNA methylation level of TWEAK gene and the DNA methylation levels of CpG_11, CpG_17.18.19.20, CpG_40.41.42 site in the RA group were higher than those in the healthy control group (P=0.002, P=0.01, P=0.006, P=0.002, respectively). The DNA methylation level of CpG_55.56 site in the high disease activity group was higher than that in the medium and low disease activity group (P=0.041). The expression level of TWEAK gene mRNA in the peripheral blood of the RA group was lower than that of the healthy control group (P=0.023). The expression level of TWEAK gene mRNA in the high disease activity group was lower than that in the medium and low disease activity group (P=0.035). The serum TWEAK protein concentration of the RA group was not significantly different from that of the healthy control group (P=0.508), but it was positively correlated with the mRNA expression level (r=0.482, P < 0.001).

CONCLUSION

The TWEAK gene is closely related to the onset and progression of RA, and its hypermethylation state may be one of the epigenetic mechanisms regulating its low mRNA expression, and it can be used as one of the important indicators for clinical monitoring and evaluation of RA.

Epigenetically-regulated RPN2 gene influences lymphocyte activation and is involved in pathogenesis of rheumatoid arthritis

BACKGROUND

To identify RA-associated genes and to ascertain epigenetic factors and functional mechanisms underlying RA pathogenesis.

METHODS

Peripheral blood mononuclear cells (PBMC) transcriptome- and proteome- wide gene expressions were profiled in a case-control study sample. Differentially expressed genes (DEGs) were discovered and validated independently. In-house PBMC genome-wide SNP genotyping data, miRNA expression data and DNA methylation data in the same sample were utilized to identify SNPs [expression quantitative trait locus (eQTLs) and protein quantitative trait locus (pQTLs)], miRNAs, and DNA methylation positions (DMPs) regulating key DEG of interest. Lentivirus transfection was conducted to study the effects of RPN2 on T lymphocyte activation, proliferation, apoptosis, and inflammatory cytokine expression. Rpn2 protein level in plasma was quantitated by ELISA to assess its performance in discriminating RA cases and controls.

RESULTS

Twenty-two DEGs were discovered in PBMCs. The most significant DEG, i.e., RPN2, was validated to be up-regulated with RA in PBMCs. A complex regulatory network for RPN2 gene expression in PBMCs was constructed, which consists of 38 eQTL and 53 pQTL SNPs, 3 miRNAs and 2 DMPs. Besides, RPN2 expression was significantly up-regulated with RA in primary T lymphocytes, as well as in PHA-activated T lymphocytes. RPN2 over-expression in T lymphocytes significantly inhibited apoptosis and IL-4 expression and promoted proliferation and activation. PBMCs-expressed RPN2 mRNA and plasma Rpn2 protein demonstrated superior and modest performances in discriminating RA cases and controls, respectively.

CONCLUSIONS

RPN2 gene influences T lymphocyte growth and activation and is involved in the pathogenesis of RA. Rpn2 may serve as a novel protein biomarker for RA diagnosis.

Integrated pharmacology reveals the mechanism of action of Bu-Shen-Tong-Du prescription against collagen-induced arthritis

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease. Bu-Shen-Tong-Du prescription (BSP) has traditionally been used in to treat RA but its underlying mechanisms remain unclear. In this study, we explored the potential mechanisms of BSP in collagen-induced arthritis (CIA) rats, a classic animal model of RA. We employed an integrated pharmacology approach in combination with network pharmacology, 1H-nuclear magnetic resonance (NMR) metabolomics, and biochemical analyses to determine the mechanisms of BSP for treating RA. We found that BSP can regulate immunity and inflammation by decreasing the spleen index; inhibiting hyperplasia of the white pulp; reducing the levels of IL-1β, IL-6, IL-17A, and IFN-γ; and increasing the levels of IL-10 in the serum. Network pharmacology was utilized to predict related signal transduction pathways of BSP in RA treatment. 1H NMR metabolomics of the serum confirmed that BSP regulated energy metabolism and amino acid metabolism. Finally, we validated the Toll-like receptor 4 (TLR4)/nuclear factor (NF)-κB signaling pathway using immunohistochemical methods, which demonstrated that BSP controlled RA-induced inflammation by inhibiting the TLR4/NF-κB signaling pathway. These results confirm the therapeutic effect of BSP in a CIA rat model, which is exerted via the inhibition of the inflammation and the improvement of the immune function, balancing energy metabolism and amino acid metabolism, and inhibiting the TLR4/NF-κB signaling pathway. This study provides an experimental basis for using BSP as a combinatorial drug to inhibit inflammation and regulate immunity in the treatment of RA.

Suppression of Dendritic Cell Maturation by Kefir Peptides Alleviates Collagen-Induced Arthritis in Mice

Arthritis is a disorder that is characterized by joint inflammation and other symptoms. Rheumatoid arthritis (RA), an autoimmune disease, is one of the most common arthritis in worldwide. Inflammation of the synovium is the main factor that triggers bone erosion in the joints in RA, but the pathogenesis of RA is not clearly understood. Kefir grain-fermented products have been demonstrated to enhance immune function and exhibit immune-modulating bioactivities. This study aims to explore the role of kefir peptides (KPs) on the regulation of dendritic cell, which are found in RA synovial fluid, and the protection effects of KPs on mice with collagen-induced arthritis (CIA). Immature mouse bone marrow-derived dendritic cells (BMDCs) were treated with KPs (2.2 and 4.4 mg/ml) and then exposed to lipopolysaccharide (LPS) to study the immune regulation function of KPs in dendritic cells. Mice with CIA (n = 5 per group) were orally administrated KPs (3.75 and 7.5 mg/day/kg) for 21 days and therapeutic effect of KPs on mice with arthritis were assessed. In this study, we found that KPs could inhibit surface molecule expression, reduce inflammatory cytokine release, and repress NF-κB and MAPK signaling in LPS-stimulated mouse BMDCs. In addition, a high dose of KPs (7.5 mg/kg) significantly alleviated arthritis symptoms, decreased inflammatory cytokine expression, suppressed splenic DC maturation and decrease the percentage of Th1 and Th17 in the spleens on mice with CIA. Our findings demonstrated that KPs ameliorate CIA in mice through the mechanism of suppressing DC maturation and inflammatory cytokine releases.

The Efficacy of Antioxidative Stress Therapy on Oxidative Stress Levels in Rheumatoid Arthritis: A Systematic Review and Meta-analysis of Randomized Controlled Trials

Objective

To explore the efficacy of antioxidative stress therapy on oxidative stress levels in rheumatoid arthritis (RA) by a systematic review and meta-analysis of randomized controlled trials.

Methods

Chinese and English databases such as PubMed, Embase, China National Knowledge Infrastructure (CNKI), and China Biomedical Literature were searched, mainly searching for clinical randomized controlled trials of antioxidant therapy for rheumatoid arthritis. The search time is from the establishment of the database to July 2021. Two researchers independently carried out literature search, screening, and data extraction. The bias risk tool provided by the Cochrane Collaboration was used to evaluate the bias risk of all the included literature, and the RevMan 5.3 software was used for meta-analysis.

Results

A total of 24 RCTs (28 records) and 1277 participants were included. The time span of randomized controlled trials (RCTs) is from 1986 to 2020. These RCTs involve 14 types of antioxidants or antioxidant therapies, and these therapies have varying degrees of improvement on oxidative stress in RA patients. The summary results showed that the MDA in the experiment group is lower (SMD -0.82, 95% CI -1.35 to -0.28, P = 0.003). The difference of TAC, SOD, NO, GPx, CAT, and GSH between two groups was of no statistical significance (TAC (SMD 0.27, 95% CI -0.21 to 0.75, P = 0.27), SOD (SMD 0.12, 95% CI -0.16 to 0.40, P = 0.41), NO (SMD -2.03, 95% CI -4.22 to 0.16, P = 0.07), GPx (SMD 0.24, 95% CI -0.07 to 0.54, P = 0.13), CAT (SMD 2.95, 95% CI -2.6 to 8.51, P = 0.30), and GSH (SMD 2.46, 95% CI -0.06 to 4.98, P = 0.06)). For adverse events, the summary results showed that the difference was of no statistical significance (RR 1.16, 95% CI 0.79 to 1.71, P = 0.45). In addition, antioxidant therapy has also shown improvement in clinical efficacy indexes (number of tender joints, number of swollen joints, DAS28, VAS, and HAQ) and inflammation indexes (ESR, CRP, TNF-α, and IL6) for RA patients.

Conclusion

The existing evidence shows potential benefits, mainly in reducing MDA and increasing TAC and GSH in some subgroups. However, more large samples and higher quality RCTs are needed to provide high-quality evidence, so as to provide more clinical reference information for the antioxidant treatment of RA.

Potential role of bioactive lipids in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease, which involves a pathological inflammatory response against articular cartilage in multiple joints throughout the body. It is a complex disorder associated with comorbidities such as depression, lymphoma, osteoporosis and cardiovascular disease (CVD), which significantly deteriorate patients' quality of life and prognosis. This has ignited a large initiative to elucidate the physiopathology of RA, aiming to identify new therapeutic targets and approaches in its multidisciplinary management. Recently, various lipid bioactive products have been proposed to have an essential role in this process; including eicosanoids, specialized pro-resolving mediators, phospholipids/sphingolipids, and endocannabinoids. Dietary interventions using omega-3 polyunsaturated fatty acids or treatment with synthetic endocannabinoids agonists have been shown to significantly ameliorate RA symptoms. Indeed, the modulation of lipid metabolism may be crucial in the pathophysiology and treatment of autoimmune diseases.

Objective and noninvasive biochemical markers in rheumatoid arthritis: where are we and where are we going?

INTRODUCTION

Rheumatoid arthritis (RA) is a chronic autoimmune disease that affects approximately 1% of the adult population. RA is multi-factorial, and as such our understanding of the molecular pathways involved in the disease is currently limited. An increasing number of studies have suggested that several molecular phenotypes (i.e. endotypes) of RA exist, and that different endotypes respond differently to various treatments. Biochemical markers may be an attractive means for achieving precision medicine, as they are objective and easily obtainable.

AREAS COVERED

We searched recent publications on biochemical markers in RA as either diagnostic or prognostic markers, or as markers of disease activity. Here, we provide a narrative overview of different classes of markers, such as autoantibodies, citrulline products, markers of tissue turnover and cytokines, that have been tested in clinical cohorts or trials including RA patients.

EXPERT OPINION

Although many biochemical markers have been identified and tested, few are currently being used in clinical practice. As more treatment options are becoming available, the need for precision medicine tools that can aid physicians and patients in choosing the right treatment is growing.

Coupling of Co-expression Network Analysis and Machine Learning Validation Unearthed Potential Key Genes Involved in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is an incurable disease that afflicts 0.5-1.0% of the global population though it is less threatening at its early stage. Therefore, improved diagnostic efficiency and prognostic outcome are critical for confronting RA. Although machine learning is considered a promising technique in clinical research, its potential in verifying the biological significance of gene was not fully exploited. The performance of a machine learning model depends greatly on the features used for model training; therefore, the effectiveness of prediction might reflect the quality of input features. In the present study, we used weighted gene co-expression network analysis (WGCNA) in conjunction with differentially expressed gene (DEG) analysis to select the key genes that were highly associated with RA phenotypes based on multiple microarray datasets of RA blood samples, after which they were used as features in machine learning model validation. A total of six machine learning models were used to validate the biological significance of the key genes based on gene expression, among which five models achieved good performances [area under curve (AUC) >0.85], suggesting that our currently identified key genes are biologically significant and highly representative of genes involved in RA. Combined with other biological interpretations including Gene Ontology (GO) analysis, protein-protein interaction (PPI) network analysis, as well as inference of immune cell composition, our current study might shed a light on the in-depth study of RA diagnosis and prognosis.

The level of thymic stromal lymphopoietin and its gene polymorphism are associated with rheumatoid arthritis

OBJECTIVE

To study the correlation between TSLP gene SNPs and RA in a Han Chinese population.

METHODS

The genotypes of TSLP genes rs11466749, rs11466750 and rs10073816 among 197 RA patients and 197 controls were analysed by direct sequencing. ELISA was used to detect the plasma TSLP level. Logistic regression analysis was also conducted to identify risk factors for RA.

RESULTS

The rs11466749 locus GG genotype (OR = 5.30, 95% CI: 1.76-15.95, P < 0.01), dominant model (OR = 1.68, 95% CI: 1.03-2.73, P = 0.04), recessive model (OR = 5.15, 95% CI: 1.72-15.43, P < 0.01), and G allele (OR = 2.02, 95% CI: 1.33-3.09, P < 0.01) were associated with an increased risk of RA. The rs1073816 locus AA genotype (OR = 4.58, 95% CI: 1.49-14.01, P < 0.01), dominant model (OR = 1.75, 95% CI: 1.09-2.79, P = 0.03), recessive model (OR = 4.27, 95% CI: 1.40-13.00, P = 0.03) and A allele (OR = 1.94, 95% CI: 1.29-2.91, P < 0.01) were associated with an increased risk of RA. The rs1073816 locus GA genotype (OR = 0.29, 95% CI: 0.18-0.45, P < 0.01), dominant model (OR = 0.32, 95% CI: 0.21-0.49, P < 0.01) and A allele (OR = 0.45, 95% CI: 0.32-0.63, P < 0.01) were related to a decreased risk of RA susceptibility. The rs1466749 locus GG genotype, rs11466750 AA genotype, and rs10073816 GG genotype were independent risk factors for RA (P < 0.05). The AUC of plasma TSLP level in the diagnosis of RA was 0.8661 (95% CI: 0.8301-0.9002, P < 0.001). There were statistically significant differences in plasma TSLP levels among subjects with different genotypes at rs11466749, rs11466750, and rs10073816 in the TSLP gene (P < 0.05).

CONCLUSION

Plasma TSLP levels are a potential molecular marker of RA. SNPs at rs11466749, rs11466750 and rs10073816 of the TSLP gene are related to the susceptibility of the Han Chinese population to RA.

Metabolomic and transcriptomic analyses of the anti-rheumatoid arthritis potential of xylopic acid in a bioinspired lipoprotein nanoformulation

Xylopic acid (XA), a diterpene kaurene and the major active ingredient of the African spice Xylopia aethiopica (Annonaceae), is reported to possess anti-inflammatory and analgesic properties. Here, we investigated the therapeutic potential of XA for rheumatoid arthritis (RA), a debilitating autoimmune inflammatory disease characterized by joint damage, in the complete Freund's adjuvant (CFA)-induced arthritis model in rats. We synthesized bioinspired reconstituted high-density lipoprotein (rHDL) nanoparticles loaded with purified XA crystals (rHDL/XA) that passively accumulate in inflamed joints of CFA-induced arthritic rats. Treatment with rHDL/XA minimized mononuclear cell infiltration of CFA-induced arthritic sites and ameliorated disease burden. Metabolomic and transcriptomic analyses revealed that the major molecular pathways perturbed following CFA-induced arthritis correlated with amino acid and lipid metabolism, which were restored to normal states by rHDL/XA treatment. This work demonstrates the anti-RA potential of XA in a nanoformulation and uncovers its underlying therapeutic mechanisms at the transcript and metabolite levels.

Energy Conversion-Based Nanotherapy for Rheumatoid Arthritis Treatment

Rheumatoid arthritis (RA) is characterized by synovial hyperplasia and cartilage/bone destruction, which results in a high disability rate on human health and a huge burden on social economy. At present, traditional therapies based on drug therapy still cannot cure RA, in accompany with the potential serious side effects. Based on the development of nanobiotechnology and nanomedicine, energy conversion-based nanotherapy has demonstrated distinctive potential and performance in RA treatment. This strategy employs specific nanoparticles with intrinsic physiochemical properties to target lesions with the following activation by diverse external stimuli, such as light, ultrasound, microwave, and radiation. These nanoagents subsequently produce therapeutic effects or release therapeutic factors to promote necrotic apoptosis of RA inflammatory cells, reduce the concentration of related inflammatory factors, relieve the symptoms of RA, which are expected to ultimately improve the life quality of RA patients. This review highlights and discusses the versatile biomedical applications of energy conversion-based nanotherapy in efficient RA treatment, in together with the deep clarification of the facing challenges and further prospects on the final clinical translations of these energy conversion-based nanotherapies against RA.

Potential mechanisms of action of celastrol against rheumatoid arthritis: Transcriptomic and proteomic analysis

The clinical efficacy for treating of celastrol rheumatoid arthritis (RA) has been well-documented, but its mechanism of action remains unclear. Here we explored through what proteins and processes celastrol may act in activated fibroblast-like synoviocytes (FLS) from RA patients. Differential expression of genes and proteins after celastrol treatment of FLS was examined using RNA sequencing, label-free relatively quantitative proteomics and molecular docking. In this paper, expression of 26,565 genes and 3,372 proteins was analyzed. Celastrol was associated with significant changes in genes that respond to oxidative stress and oxygen levels, as well as genes that stabilize or synthesize components of the extracellular matrix. These results identify several potential mechanisms through which celastrol may inhibit inflammation in RA.

In search of pathobiological endotypes: a systems approach to early rheumatoid arthritis

INTRODUCTION

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease. Early referral and treatment are key to the effective management of the disease. This makes imperative the identification of biomarkers and of pathobiological endotypes.

AREAS COVERED

This review describes recent efforts to integrate large-scale datasets for the identification of disease endotypes for precision medicine in early, seropositive RA. We conducted a search for systems and multi-omics papers in early RA patients through to 1 January 2020. We reviewed investigations of multiple technologies such as transcriptomic, proteomic and metabolomic platforms as well as extensive clinical datasets. We outline progress made and describe some of the advantages and limitations of current computational and statistical methods.

EXPERT OPINION

The search for pathobiological endotypes in early RA is rapidly developing. While currently, studies tend to be small, reliant upon new technologies and unproven analytical tools, as the technology becomes cheaper and more reliable, and the properties of analytical tools for the integration of cross-platform biology become better understood, it seems likely that better biomarkers of disease, remission and response to individual therapies will emerge.

Recent advances of metabolic engineering strategies in natural isoprenoid production using cell factories

This review covers the strategies mostly developed in the last three years for microbial production of isoprenoid, classified according to the engineering targets.

LncRNA MEG3 inhibits rheumatoid arthritis through miR-141 and inactivation of AKT/mTOR signalling pathway

Rheumatoid arthritis (RA) is a chronic inflammation mediated by autoimmune responses. MEG3, a kind of long noncoding RNA (lncRNA), participates in cell proliferation in cancer tissues. However, the correlation between MEG3 and RA is yet unclear. Therefore, to clarify how MEG3 works in RA, we performed a series of experiments using RA samples. We found that MEG3 was downregulated in the fibroblast-like synoviocytes of RA patients (RA-FLS), in comparison with healthy subjects. MEG3 was also down-regulated evidently in lipopolysaccharide (LPS)-treated chondrocyte. As part of our experiments, MEG3 was overexpressed in chondrocyte by transfection with lentivirus containing sequences encoding MEG3. In addition, in presence of LPS, reductions were identified not only in the cell proliferation, but also in the generation of interleukin-23 (IL-23), which, however were reversed in the lentivirus (containing MEG3-encoding sequences)-transfected chondrocytes. Up-regulated MEG3 resulted in an increase the level of Ki67. Moreover, MEG3 was negatively correlated with miR-141, and miR-141 was up-regulated in LPS-treated chondrocyte. Inhibitory effects of MEG3 overexpression, mentioned above, were partially abolished by overexpressed miR-141. Further, animal experiment also showed the inhibitory effect of MEG3 in overexpression on the AKT/mTOR signaling pathway. In-vivoexperiments also showed that cell proliferation was facilitated by MEG3 overexpression with inhibited inflammation. In summary, the protective role of MEG3 in RA was proved to be exerted by the increase in the rate of proliferation, which might correlate to the regulatory role of miR-141 and AKT/mTOR signal pathway, suggesting that MEG3 holds great promise as a therapeutic strategy for RA.

Filifactor alocis and Dialister pneumosintes in a Mexican population affected by periodontitis and rheumatoid arthritis: An exploratory study

Filifactor alocis and Dialister pneumosintes have been associated with the initiation and progression of periodontitis (PE). We determined and compared the frequency of both bacteria in patients with PE, rheumatoid arthritis (RA), and PE/RA simultaneously. Detection was performed by polymerase chain reaction in the subgingival biofilm. Bacteria were more frequent in patients with PE, and clinical periodontal parameters such as pocket depth (PD) and clinical attachment loss (CAL) were significantly higher in patients with PE/RA. F. alocis and D. pneumosintes could influence PD and CAL, hence participating in the initiation and progression of PE in patients with RA.

Application of GC/MS-Based Metabonomic Profiling in Studying the Therapeutic Effects of Aconitum carmichaeli with Ampelopsis japonica Extract on Collagen-Induced Arthritis in Rats

Aconitum carmichaeli with Ampelopsis japonica (AA) is a classical traditional Chinese medicine (TCM) formula. There are a lot of examples showing that AA can be used to treat rheumatoid arthritis, but its mechanism of action is still not completely clear. In this research, collagen-induced arthritis (CIA) was chosen as a rheumatoid arthritis (RA) model. Rats of treated groups were continuously administered Aconitum carmichaeli (AC), Ampelopsis japonica (AJ) and Aconitum carmichaeli + Ampelopsis japonica (AA) orally once a day from the day after the onset of arthritis (day 7) until day 42. The results showed that AA not only significantly reduced paw swelling, but also improved the levels of TNF-α and IL-6 in serum. GC-MS-based urine metabonomics was established to analysis metabolic profiles and 21 biomarkers of RA rats were identified by the Partial Least Squares Discriminant Analysis (PLS-DA) and Support Vector Machine (SVM) methods. The prediction rate of the SVM method for the 21 biomarkers was 100%. Twenty of 21 biomarkers, including D-galactose, inositol and glycerol, gradually returned to normal levels after administration of AA. Metabolomic Pathway Analysis (MetPA) generated three related metabolic pathways-galactose metabolism, glycerolipid metabolism and inositol phosphate metabolism-which explain the mechanism of AA treatment of rheumatoid arthritis. This research provides a better understanding of the therapeutic effects and possible therapeutic mechanism of action of a complex TCM (AA) on rheumatoid arthritis.

Effects of a 15-month anti-TNF-α treatment on plasma levels of glycosaminoglycans in women with rheumatoid arthritis

Background

In this study, the effect of 15-month anti-tumor necrosis factor alpha (TNF-α) treatment on circulating levels of plasma sulfated glycosaminoglycans (GAGs) and the nonsulfated GAG hyaluronic acid (HA) in female rheumatoid arthritis (RA) patients was assessed.

Methods

Plasma was obtained from healthy subjects and RA women treated with TNF-α antagonists (etanercept or adalimumab or certolizumab pegol) in combination with methotrexate. GAGs were isolated from plasma samples using ion exchange low-pressure liquid chromatography. Total sulfated GAGs were quantified using a hexuronic acid assay. Plasma levels of keratan sulfate (KS) and HA were measured using immunoassay kits.

Results

Total sulfated GAGs and HA levels were higher in female RA patients before treatment in comparison to healthy subjects. KS levels did not differ between RA women and controls. Anti-TNF-α treatment resulted in normalization of plasma total GAG and HA levels in RA patients, without any effect on KS levels.

Conclusions

Our results suggest that anti-TNF-α therapy has a beneficial effect on extracellular matrix remodeling in the course of RA.

Comprehensive epigenetic landscape of rheumatoid arthritis fibroblast-like synoviocytes

Epigenetics contributes to the pathogenesis of immune-mediated diseases like rheumatoid arthritis (RA). Here we show the first comprehensive epigenomic characterization of RA fibroblast-like synoviocytes (FLS), including histone modifications (H3K27ac, H3K4me1, H3K4me3, H3K36me3, H3K27me3, and H3K9me3), open chromatin, RNA expression and whole-genome DNA methylation. To address complex multidimensional relationship and reveal epigenetic regulation of RA, we perform integrative analyses using a novel unbiased method to identify genomic regions with similar profiles. Epigenomically similar regions exist in RA cells and are associated with active enhancers and promoters and specific transcription factor binding motifs. Differentially marked genes are enriched for immunological and unexpected pathways, with “Huntington’s Disease Signaling” identified as particularly prominent. We validate the relevance of this pathway to RA by showing that Huntingtin-interacting protein-1 regulates FLS invasion into matrix. This work establishes a high-resolution epigenomic landscape of RA and demonstrates the potential for integrative analyses to identify unanticipated therapeutic targets.

Fibroblast-like synoviocytes (FLS) in the intimal layer of the synovium can become invasive and destroy cartilage in patients with rheumatoid arthritis (RA). Here the authors integrate a variety of epigenomic data to map the epigenome of FLS in RA and identify potential therapeutic targets.