Expression and methylation levels of suppressor of cytokine signaling 3 in rheumatic arthritis synovial fibroblasts

From molecular subgroups to molecular targeted therapy in rheumatoid arthritis: A bioinformatics approach

1Background

Rheumatoid Arthritis (RA) is a heterogeneous autoimmune disease with multiple unidentified pathogenic factors. The inconsistency between molecular subgroups poses challenges for early diagnosis and personalized treatment strategies. In this study, we aimed to accurately distinguish RA patients at the transcriptome level using bioinformatics methods.

2Methods

We collected a total of 362 transcriptome datasets from RA patients in three independent samples from the GEO database. Consensus clustering was performed to identify molecular subgroups, and clinical features were assessed. Differential analysis was employed to annotate the biological functions of specifically upregulated genes between subgroups.

3Results

Based on consensus clustering of RA samples, we identified three robust molecular subgroups, with Subgroup III representing the high-risk subgroup and Subgroup II exhibiting a milder phenotype, possibly associated with relatively higher levels of autophagic ability. Subgroup I showed biological functions mainly related to viral infections, cellular metabolism, protein synthesis, and inflammatory responses. Subgroup II involved autophagy of mitochondria and organelles, protein localization, and organelle disassembly pathways, suggesting heterogeneity in the autophagy process of mitochondria that may play a protective role in inflammatory diseases. Subgroup III represented a high-risk subgroup with pathological processes including abnormal amyloid precursor protein activation, promotion of inflammatory response, and cell proliferation.

4Conclusion

The classification of the RA dataset revealed pathological heterogeneity among different subgroups, providing new insights and a basis for understanding the molecular mechanisms of RA, identifying potential therapeutic targets, and developing personalized treatment approaches.

An integrated network pharmacology approach reveals that Darutigenol reduces inflammation and cartilage degradation in a mouse collagen-induced arthritis model by inhibiting the JAK-STAT3 pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Darutigenol (DL) is a natural active product derived from the Chinese herbal medicine Sigesbeckia glabrescens (Makino) Makino. It is administered as a traditional Chinese medicine (TCM) to dispel rheumatism, benefit the joints, and detoxify. However, its potential mechanism in the treatment of rheumatoid arthritis (RA) remains unknown.

AIMS OF THE STUDY

The objectives of this research were to determine the effects and elucidate the modes of action of DL on RA-related joint inflammation.

MATERIALS AND METHODS

Network pharmacology and molecular docking were used to screen and validate candidate DL targets for RA treatment, respectively. A DBA/1 mouse rheumatoid arthritis model was induced with bovine type II collagen. Intragastric DL administration was followed by the calculation of the clinical arthritis index. A section of the ankle joint was excised and stained and the pathological changes in it were observed. Enzyme-linked immunosorbent assays (ELISA) and western blotting (WB) were used to clarify the mechanisms of DL in RA treatment.

RESULTS

DL effectively attenuated the inflammation, mitigated the articular cartilage degradation, and bone erosion, and alleviated the inflammatory joints associated with RA. Network pharmacology screened six key targets of DL while molecular docking revealed that it docked well with its protein targets. The DL treatment group presented with significantly less ankle joint redness and swelling, a lower arthritis index scores and serum and bone marrow supernatant IL-6 levels, more complete ankle joint surfaces, and less synovial inflammation, cartilage degradation, and bone erosion than the collagen-induced arthritis (CIA) group. The DL treatment also substantially downregulated the Janus kinase (JAK)1, JAK3, matrix metalloproteinase (MMP)2, MMP9, and phospho-signal transducer and activator of transcription (p-STAT)3 proteins in the joints.

CONCLUSIONS

To the best of our knowledge, the present work was the first to demonstrate that DL has significant anti-inflammatory efficacy and reduces cartilage degradation and bone erosion. It also demonstrated that the anti-RA effect of DL may be explained by its ability to inhibit joint inflammation and reduce articular cartilage degradation through the interleukin (IL)-6/JAK1,3/STAT3 axis and downregulate MMP2 and MMP9. Hence, DL might play a therapeutic role in a mouse RA model.

An Integrative Network Approach to Identify Common Genes for the Therapeutics in Tuberculosis and Its Overlapping Non-Communicable Diseases

Tuberculosis (TB) is the leading cause of death from a single infectious agent. The estimated total global TB deaths in 2019 were 1.4 million. The decline in TB incidence rate is very slow, while the burden of noncommunicable diseases (NCDs) is exponentially increasing in low- and middle-income countries, where the prevention and treatment of TB disease remains a great burden, and there is enough empirical evidence (scientific evidence) to justify a greater research emphasis on the syndemic interaction between TB and NCDs. The current study was proposed to build a disease-gene network based on overlapping TB with NCDs (overlapping means genes involved in TB and other/s NCDs), such as Parkinson’s disease, cardiovascular disease, diabetes mellitus, rheumatoid arthritis, and lung cancer. We compared the TB-associated genes with genes of its overlapping NCDs to determine the gene-disease relationship. Next, we constructed the gene interaction network of disease-genes by integrating curated and experimentally validated interactions in humans and find the 13 highly clustered modules in the network, which contains a total of 86 hub genes that are commonly associated with TB and its overlapping NCDs, which are largely involved in the Inflammatory response, cellular response to cytokine stimulus, response to cytokine, cytokine-mediated signaling pathway, defense response, response to stress and immune system process. Moreover, the identified hub genes and their respective drugs were exploited to build a bipartite network that assists in deciphering the drug-target interaction, highlighting the influential roles of these drugs on apparently unrelated targets and pathways. Targeting these hub proteins by using drugs combination or drug repurposing approaches will improve the clinical conditions in comorbidity, enhance the potency of a few drugs, and give a synergistic effect with better outcomes. Thus, understanding the Mycobacterium tuberculosis (Mtb) infection and associated NCDs is a high priority to contain its short and long-term effects on human health. Our network-based analysis opens a new horizon for more personalized treatment, drug-repurposing opportunities, investigates new targets, multidrug treatment, and can uncover several side effects of unrelated drugs for TB and its overlapping NCDs.

Fibroblast pathology in inflammatory joint disease

Rheumatoid arthritis is an immune-mediated inflammatory disease in which fibroblasts contribute to both joint damage and inflammation. Fibroblasts are a major cell constituent of the lining of the joint cavity called the synovial membrane. Under resting conditions, fibroblasts have an important role in maintaining joint homeostasis, producing extracellular matrix and joint lubricants. In contrast, during joint inflammation, fibroblasts contribute to disease pathology by producing pathogenic levels of inflammatory mediators that drive the recruitment and retention of inflammatory cells within the joint. Recent advances in single-cell profiling techniques have transformed our ability to examine fibroblast biology, leading to the identification of specific fibroblast subsets, defining a previously underappreciated heterogeneity of disease-associated fibroblast populations. These studies are challenging the previously held dogma that fibroblasts are homogeneous and are providing unique insights into their role in inflammatory joint pathology. In this review, we discuss the recent advances in our understanding of how fibroblast heterogeneity contributes to joint pathology in rheumatoid arthritis. Finally, we address how these insights could lead to the development of novel therapies that directly target selective populations of fibroblasts in the future.